Inflation Expectations
Survey of Households*
Maintaining price stability is a prime
objective of monetary policy. Towards this
end, central banks strive to anchor
inflation expectations and, therefore,
need to collect information on inflation
expectations. Survey-based approach is,
inter alia, a mechanism to construct
estimates of inflation expectation.The
Reserve Bank of India has been
conducting the inflation expectations
survey of households (IESH) on a
quarterly basis for over four years now.
The survey captures the inflation
expectations of 4000 urban households
from 12 cities spread across the country.
The survey represents the expectation of
inflation for the respondent’s own basket
of consumption. The inflation numbers
from this survey thus represent the
expectations of urban households based
on the average inflation of 4000 different
consumption baskets. These are not to be
regarded as predictors of any official
measure of inflation. The households’
inflation expectations provide useful
directional information on near-term
inflationary pressures and are used to
supplement other economic indicators to
get a better indication of future
inflation. This technical note presents the
details on the conceptualisation of the
survey, its technical audit for
methodology and data quality,
methodological improvements based on
expert opinion and the implementation
of the recommendations of the Technical
Advisory Committee on Surveys (TACS)
and the survey results.
I. Introduction
Controlling inflation is a prime objective
of monetary policy. For this purpose, central
banks need to know the determinants of
inflation. Both theoretical considerations
and empirical evidence suggest that
inflation expectations are a crucial
ingredient for monetary policy. Measures of
inflation expectations are therefore
important to central banks to achieve their
mandate towards price stability. In order to
achieve their mandate for low and stable
inflation, the central banks seek to gain
knowledge about the public’s expectations
for inflation in addition to the financial
market based measures. The inflation
targeting countries also use the public’s
expectations of inflation as an indication of
the performance and credibility of their
monetary policy.
Households in any economy form their
inflation expectations which influence
future path of inflation of the economy. A
wide range of the households’ intertemporal
decisions (e.g., purchases of
perishable and durable goods, price of
housing, borrowing costs and return on
saving, investment and wage negotiation)
can be affected by expectations and
uncertainty about future inflation.
Survey-based approach is one of the
several ways of estimating inflation
expectations. Some of the other approaches
involve extraction of information from
financial market instruments. For example,
the differential yields of ordinary and
inflation-indexed government bonds of
similar maturity may provide some
indication of inflation expectations.
However, the simplest way to gauge people’s expectations for inflation is to ask them what
they expect. The survey measures of
inflation expectations are important to policy
makers and researchers because they provide
data on an otherwise unobservable variable.
Keeping in view the importance of
inflation expectations as an input for
monetary policy, the price and inflation
expectations of households are being
captured by RBI through its quarterly
Inflation Expectations Survey of Households
(IESH) since September 2005. The survey
presents a measure of households’ present
perception of inflation as well as its
expectations for the near future. The
households’ inflation expectations are
distinctly different from the inflation
measures available through the official price
indices as the basket of consumption of the
survey participants varies as per their
requirement and perception.
II. Inflation Expectation Survey of
Household - Background
The inflation expectations survey of
households is conducted in twelve cities,
three each from the north, south, east and
west zone covering the major metros from
each zone and eight other cities. The
respondents are chosen within a city in such
a manner that a good geographical coverage
is achieved. Quota sampling is used to get
adequate representation of gender,
categories and age groups.
In the initial two rounds of IESH, the
schedule sought only qualitative feedback on
respondent’s expectation on general prices
for the next quarter and for a year ahead.
Additionally, expectations of prices for food
products, non food products, household durables, houses and services were also
collected. The initial questionnaire is placed
at Appendix I. From Round 3 onwards
quantitative questions were added to seek the expected rate of inflation for the next
three months and one year. From the ninth
round onwards a question on the
respondent’s perception of the present rate of inflation was also sought. The latest
questionnaire is placed in Appendix II.
International experience on Inflation Expectations
Many countries are now conducting household
inflation expectation survey. They use different
methodologies, e.g. mail survey, telephonic
survey, internet survey and face-to-face
interviews. Some banks do independent surveys
(e.g. Federal Reserve Bank of New York, Bank of
England, Reserve Bank of New Zealand, South
African Reserve bank, Czech National Bank) while
some as a part of their consumer confidence
survey (e.g. European Commission, Riksbank,
Bank of Japan, Australia). Different designs, like
independent sample in each round, pure panel
and repeat panel, are used by different countries
for such surveys.
The Bank of England has been conducting
inflation attitudes survey since 1999. The survey
asks a range of questions that examine public
knowledge and understanding of, and attitudes
towards, the MPC process, including people’s
expectations of inflation. The survey is quarterly
and covers 2000 households in its May, August &
November rounds and 4000 households in the
February round where a larger questionnaire is
canvassed. The summary data is released every
quarter on the bank’s web site and an annual
article is put up in its Quarterly Bulletin.
The United States of America has market based
measures of inflation expectations but still gives
importance to the survey based inflation
expectations measure for more than 60 years. The
monthly Michigan survey and Conference Board
survey are the most widely used surveys there.
The Federal Reserve Bank of New York in
collaboration with the Cleveland Federal Reserve
initiated the Household Inflation Expectations
Project (HIEP) in late 2006. They found the
importance of wording of the questions in the
survey. While questions on ‘prices in general’
prompts respondents to think of the most visible
prices (gasoline and food), questions on ‘rate of inflation’ makes respondents to reflect about
general prices and measures the inflation concept
economists have in mind. They conduct internet
survey every six weeks on a fixed panel of
respondents and seek probability distribution of
the respondents’ inflation expectations, to help
them assess the degree of individual uncertainty
about future inflation outcome (see Wandi Bruine
de Bruin et al1)
The Reserve Bank of New Zealand (RBNZ)
conducts quarterly household inflation
expectation survey since 1995. The survey is
telephonic and is conducted by sponsoring a
market research company. The key results are
published on RBNZ website according to an
advance release calendar. The South African
Reserve Bank conducts a dedicated quarterly
inflation expectations survey since 2000 with the
help of Bureau of Economic Research. It used the
interview method for the household survey.
In 2009, the Centre for Central Banking Studies,
UK and National Bank of Poland2 carried out a
survey of 21 countries, of which 14 were inflation
targeters, on inflation expectation measures used.
According to the survey, 85 per cent of the central
banks use survey measure of inflation
expectations for consumers. However, only 47.6
per cent of the banks surveyed used inflation
expectations as a measure of leading indicator
while 57 per cent used it in modeling and
forecasting of inflation.
An inter department Standing
Committee in the Reserve Bank monitors the
technical aspects of the survey. In March
2007, the Reserve Bank constituted a
Technical Advisory Committee on Surveys
(TACS) under the chairmanship of Dr. Rakesh
Mohan, the then Deputy Governor and with
external experts drawn from the Indian
Statistical Institute, Indira Gandhi Institute
of Development Research, and market
analysts as external members and
representatives from user departments as
internal members, to review the
methodology and examine the data quality
of various rounds of survey. The initial
analysis of TACS found that there were
internal inconsistencies in the survey data.
The TACS made several recommendations on
improving the data quality and consistency.
The Bank implemented the recommendations
that largely pertained to regrouping of
questions as in the present schedule,
introduction of a uniform investigator
training (Appendix III) at the central office
and the regional offices of RBI and carrying
out of field check by RBI staff at all centres
where the survey is conducted. The
subsequent analysis by TACS of the unit-level
data from later survey rounds, conducted after
implementation of those recommendations,
shows satisfactory improvement in data
quality. In its report of September 2009, the
Committee being satisfied with the survey
data quality recommended the placement of
the survey results in public domain. Based
on the analysis of variability in survey
responses, TACS found that the sample size
is adequate to get estimates at all-India level.
The composition of the TACS and its report
containing detailed analysis and recommendations of earlier survey rounds
are presented in Appendix IV. The TACS
report recommended that “the Reserve Bank
should emphatically clarify that the IESH
survey results are those of the respondents
and are not necessarily shared by the Reserve
Bank. It also needs to be explained that the
inflation rate is as assessed by the
respondents based on household
consumption basket which need not be
related with inflation rate as measured by
any official price index series.”
The Reserve Bank’s Internal Working
Group on Surveys (Chairman: Shri Deepak
Mohanty) noted that “Expectations of
inflation can influence the linkage between
money, interest rates, and prices. Many
household and business decisions depend on
the inflation expectations of market
participants. First, inflation expectations are
important for wage negotiations. Second,
inflation expectations play a key role in
households’ saving decisions. For a given
level of nominal interest rates, higher
expected inflation implies a lower expected
real rate of return on saving. That would tend
to make spending today more attractive
relative to saving. Finally, businesses need
to make a judgement on the likely path of
the prices of other goods that they may be
competing with, so that they can judge the
likely demand for their product. If they
expect the prices of other goods to be higher,
that may prompt them to raise their own
output prices [Benford and Driver3]. Thus
arriving at a measure of inflation expectation
attains importance for policy makers.”
The Working Group on Surveys (WGS)
also carried out additional evaluation of
Survey Results. The analysis carried out by
them revealed that, among different factors
like gender, age, city and category of
respondents, city is the largest source of
variation in the households’ response. This
was logically appealing as the consumption
pattern varies across cities and large intercity
variations are also reported through
official price indices. They also assessed the
quality of estimates of households’ inflation
expectation by working out confidence
intervals using bootstrap resampling plan.
They found that the confidence intervals
were narrow with width of around 20 to 30
basis points. The Group found that the short
survey schedule that is used for the survey
is adequate to meet its scope. The Group
recommended that since the IESH has
stabilised, the Technical Advisory Committee
on Monetary Policy (TACMP) may consider
placing the survey in public domain.
The TACS observed “in the context of
monetary transparency, it is important that
all the indicators related to inflation and
inflation expectations that are considered
by the Reserve Bank are available to the
market. As the data of the last few rounds
of Survey has high consistency, the results
may be placed in public domain. A one-time
article may be published giving earlier
survey results.” It further recommended
that “when releasing the survey results, the
details of the concepts and methodology
may also be given by the Bank, it will be
interesting to see other agencies in India
take up similar surveys.” This article is
expected to fulfill this need.
The TACS and WGS recommendations
along with the survey results were presented to the Bank’s TACMP and as
recommended by them, the results were
also discussed in a Seminar of select
analysts, economists and market
researchers in December 2009. The pros and
cons of the issue were debated at length in
the Seminar and a consensus was arrived
that the IESH results should be placed in
the public domain.
III. Survey Methodology and Scope
The survey schedule that has been
designed for the IESH is a single-page
schedule. It has been organised into four
blocks. The first block seeks respondent
particulars including name, contact details,
gender, age and category (occupation). The
second and third blocks seek product wise
price expectations respectively for three
months and a year ahead. The fourth block
collects the rate of inflation of the
respondent for three time points - current,
three month ahead and one year ahead.
III.1 Coverage :
The Reserve Bank conducts the survey
in 12 cities every quarter. The major
metropolitan cities, viz., Delhi, Kolkata,
Mumbai and Chennai are represented by 500
households each while the eight other cities,
viz., Jaipur, Lucknow, Bhopal, Ahmedabad,
Patna, Guwahati, Bangalore and Hyderabad
are represented by 250 households each. The
respondents are well spread across the cities
to provide a good geographical coverage. The
male and female respondents in the group
are usually in the ratio of 3:2. The category
wise representation of the respondents is
presented in the table below. The sample
coverage is nearly as per the target in all
rounds.
Table 1: Respondent Profile: Share in total sample (per cent) |
Respondents Category |
Sample |
Target |
Financial Sector Employees |
9.3 |
10.0 |
Other Employees |
16.8 |
15.0 |
Self-employed |
21.3 |
20.0 |
Housewives |
27.3 |
30.0 |
Retired Persons |
8.5 |
10.0 |
Daily Workers |
8.4 |
10.0 |
Other Category |
8.5 |
5.0 |
Note: Sample proportion above is for the March 2010 survey |
III.2 Information Collected
The price expectations are sought in the
survey for general prices and for five groups
(food products, non-food products,
consumer durables, housing and others).
The general price indicates all the other
product groups taken together. The options
for responses are (i) price increase more
than current rate, (ii) price increase similar
to current rate, (iii) price increase lower than
current rate, (iv) no change in prices, and
(v) decline in prices. The first three of the
five options pertain to the respondents’
expectations on the rate of future price
increase compared to the current rate. These
expectations are sought from the
respondents for 3 months ahead as well as
a year ahead period.
The inflation expectations of the
respondents that represent the year-on-year
changes in prices are collected through Block
4. The inflation rates are collected in
intervals - the lowest being ‘less than 1 per
cent’ and the highest being ’16 per cent and
above’ with 100 basis point size of all
intermediate classes.
The rest of this article presents the
results of the survey.
IV. Survey Results
IV.1 Expectations on Prices
General Price Expectations: The survey
shows that the general prices expectations
for both 3 months ahead and one year ahead
which were lowest in December 2008, started
rising in March 2009 and have been upwardly
mobile since then. However, in March 2010,
the 3 months ahead price expectations have
decreased while the one year ahead price
expectations have marginally increased. The
percentage of respondents who expect this
price increase to be higher than current rate
have also risen consistently from March 2009
to December 2009, but declined significantly
in March 2010 (Table 2).
Product wise Price Expectations: The
product wise price expectations are given
in Statement I. The price expectations show
that the respondents have highest
expectations for price rise for food products
which were continuously rising since
December 2008 but declined in March 2010.
The general price expectations are closer to
food expectations indicating that
respondents consider food prices very
important when they think about the prices
in general. The expectations of price rise
were lowest for household durables among
all product groups.
IV.2 Inflation expectations
The inflation expectations are collected
through the Block 4 of the schedule. The
average inflation expectations presented
below represent the average of 4000
respondents. As mentioned earlier these are
based on individual consumption baskets
and are not an assessment of the prevalent official inflation rates. These should be
seen as an inflation rate of households that
represents the average over 4000 different
consumption baskets.
Table 2: General Price Expectations |
Round No./survey period → |
3 months ahead (percentage of respondents) |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
Options |
Sep-08 |
Dec-08 |
Mar-09 |
Jun-09 |
Sep-09 |
Dec-09 |
Mar-10 |
Prices will increase |
95.3 |
89.8 |
92.0 |
93.1 |
95.8 |
97.4 |
95.7 |
Price increase more than current rate |
66.4 |
52.9 |
54.9 |
63.5 |
72.2 |
74.6 |
66.9 |
Price increase similar to current rate |
19.9 |
20.1 |
22.4 |
20.7 |
18.4 |
16.6 |
20.0 |
Price increase less than current rate |
9.0 |
16.8 |
14.8 |
8.9 |
5.1 |
6.2 |
8.8 |
No change in prices |
3.4 |
5.7 |
6.9 |
6.1 |
3.7 |
2.4 |
3.4 |
Decline in price |
1.4 |
4.5 |
1.1 |
0.9 |
0.6 |
0.3 |
0.9 |
Options |
1 year ahead (percentage of respondents) |
Prices will increase |
95.2 |
90.6 |
95.6 |
93.7 |
96.3 |
96.3 |
96.5 |
Price increase more than current rate |
69.6 |
59.7 |
64.7 |
62.8 |
69.5 |
68.2 |
62.8 |
Price increase similar to current rate |
16.3 |
18.0 |
15.9 |
18.5 |
17.3 |
15.2 |
19.8 |
Price increase less than current rate |
9.3 |
12.9 |
15.0 |
12.4 |
9.5 |
12.9 |
13.9 |
No change in prices |
3.2 |
3.1 |
3.3 |
5.3 |
3.1 |
3.1 |
2.6 |
Decline in price |
1.8 |
6.3 |
1.1 |
0.9 |
0.7 |
0.6 |
0.9 |
The perception of current inflation and
expectations of three month and one year
ahead inflation since Round 5 of the survey
are shown in the graph below. The time
series movement of the inflation expectations show that the future inflation
expectations are usually higher than the
current perception. There were, however,
few exceptions to this observation- in March
2007 and in December 2008 the future
(three month ahead) inflation expectations
were lower than the current perception of
inflation. The survey shows that during the
initial two year period up to March 2008, the inflation expectations were stable and
thereafter started rising sharply. There was
a subsequent fall starting December 2008
that took the numbers to 5 to 6 per cent
band and the inflation expectations have
been increasing since then. In the latest
round of the survey, the numbers were in
the range of 10 to 11 per cent.
It is seen from Chart 2 that the future
expectations of inflation move closely in
tandem with the current perception of
inflation. Thus though the numbers do not
attempt to predict the quantum of future
inflation, they give useful input on
directional movement of inflation – i.e.
when the expectations are rising and when
they start moderating. The Chart 3 presents
the household inflation expectations along
with the official inflation measures based
on Wholesale Price Index (WPI) and
Consumer Price Index for Industrial
Workers (CPI-IW). It shows that for a large
part of the survey history, the households’
inflation expectations remained between
the WPI and CPI-IW inflations.
The volatility in responses over
different rounds can be seen from the table
below. It can be seen that the uncertainty
increases with distance in time. The
standard deviation is lower for current
inflation rate than for the 3 month and one
year ahead. This seems to be on expected
track as it is more difficult to identify the
forthcoming events and measure their
impact on inflation.
The volatility is also depicted through
the bubble charts as under. In the chart, the
distribution of respondents over different
inflation brackets is presented. The x-axis
pertains to perception of current inflation
while the y axis for future inflation
expectation (3 month ahead and one year
ahead respectively in the two charts). The
size of each bubble indicates the number of
respondents selecting the corresponding
options. The Chart 4 pertaining to March
2009 survey shows that the bubbles are
diagonal heavy - meaning that the future
expectations are influenced by current
perceptions. Also there is a concentration
of responses in the 2 to 8 per cent range and the average inflation expectations were
between 5 to 6 per cent.
Table 3: Volatility in responses in various rounds |
Round No. |
Survey Quarter |
Current Inflation rate |
Inflation rate- 3 months ahead |
Inflation rate- 1 year ahead |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
12 |
Jun-08 |
6.9 |
1.4 |
7.5 |
1.4 |
7.9 |
1.5 |
13 |
Sep-08 |
11.3 |
2.0 |
11.6 |
3.2 |
12.4 |
3.6 |
14 |
Dec-08 |
9.3 |
1.9 |
8.9 |
3.5 |
9.6 |
3.9 |
15 |
Mar-09 |
5.2 |
1.9 |
5.3 |
2.6 |
6.2 |
2.7 |
16 |
Jun-09 |
5.8 |
4.4 |
6.3 |
4.6 |
6.7 |
4.7 |
17 |
Sep-09 |
8.2 |
6.0 |
8.7 |
6.0 |
9.2 |
5.9 |
18 |
Dec-09 |
11.1 |
4.9 |
11.6 |
4.9 |
11.9 |
5.1 |
19 |
Mar-10 |
10.3 |
4.4 |
10.6 |
4.7 |
11.0 |
4.8 |
The corresponding bubble charts for
December 2009 round shows that a high
proportion of respondents are expecting
the inflation to be in the range of more than
16 per cent. The average inflation
expectations in this period were between
11 to 12 per cent. Also the responses are
scattered and variability is high. This phenomenon of high variability in
households’ inflation expectations has been
observed, internationally, during the
periods of high inflation.
In the recent quarter, the concentration
of inflation expectations on the lower side
have started increasing and both inflation
expectations and the variability in
responses have come down marginally as
portrayed in Chart 6.
The relationship of future inflation with
current inflation from Round 13 onwards
is presented in Statement II.
IV.2.1 Inflation expectations by gender
The inflation expectation according to
gender since Round 13 shows that significant gender wise differences do not
exist in the survey. However, the variability
in responses is generally higher in female
respondents as compared to their male
counterparts for the current inflation rate.
For future inflation, usually the responses
of male respondents are less cohesive.
Table 4: Gender wise Inflation Expectations |
Round
No. |
Survey
Preiod |
|
Current |
3 months ahead |
1 year ahead |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
13 |
Sep-08 |
Male |
11.3 |
1.88 |
11.5 |
3.21 |
12.3 |
3.65 |
|
|
Female |
11.2 |
2.08 |
11.6 |
3.15 |
12.6 |
3.57 |
14 |
Dec-08 |
Male |
9.3 |
1.89 |
8.6 |
3.70 |
9.5 |
3.92 |
|
|
Female |
9.4 |
1.95 |
9.4 |
3.23 |
9.9 |
3.78 |
15 |
Mar-09 |
Male |
5.1 |
1.92 |
5.2 |
2.61 |
6.1 |
2.79 |
|
|
Female |
5.4 |
2.02 |
5.6 |
2.52 |
6.3 |
2.66 |
16 |
Jun-09 |
Male |
5.7 |
4.48 |
6.2 |
4.72 |
6.7 |
4.78 |
|
|
Female |
6.1 |
4.18 |
6.5 |
4.50 |
6.8 |
4.60 |
17 |
Sep-09 |
Male |
8.1 |
6.05 |
8.7 |
6.00 |
9.3 |
5.82 |
|
|
Female |
8.2 |
6.02 |
8.7 |
6.00 |
9.1 |
5.95 |
18 |
Dec-09 |
Male |
11.1 |
4.90 |
11.5 |
4.85 |
11.9 |
4.98 |
|
|
Female |
11.1 |
4.93 |
11.6 |
4.88 |
11.8 |
5.33 |
19 |
Mar-10 |
Male |
10.1 |
4.31 |
10.4 |
4.56 |
11.0 |
4.71 |
|
|
Female |
10.6 |
4.43 |
10.8 |
4.80 |
11.1 |
5.02 |
Table 5: Category wise Inflation Expectations for March 2010 survey |
Survey
Period |
Category of
Respondent |
Current |
3 months ahead |
1 year ahead |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
|
Fin Sec Employees |
9.5 |
4.14 |
9.8 |
4.46 |
10.3 |
4.73 |
|
Other Employees |
9.7 |
4.10 |
10.2 |
4.33 |
10.7 |
4.50 |
Mar-10 |
Self-Employed |
10.2 |
4.34 |
10.6 |
4.59 |
11.1 |
4.69 |
|
Housewife |
10.8 |
4.46 |
10.9 |
4.84 |
11.3 |
5.03 |
|
Retired persons |
10.5 |
4.60 |
10.6 |
4.86 |
10.8 |
5.08 |
|
Daily Workers |
11.1 |
4.80 |
11.0 |
5.24 |
11.6 |
5.35 |
|
Other Category |
9.8 |
3.72 |
10.4 |
4.04 |
11.0 |
4.32 |
IV.2.2 Inflation expectations by category
of respondent
The category of respondents shows
their occupation status. The category wise
inflation expectations since Round 13 are
given in Statement III. For the latest survey
round, daily workers reported highest
inflation expectations but the variation in
their responses was also higher than those
of other category of respondents.
IV.2.3 Inflation expectations by age group
The IESH covers only the adult responses
of 18 years or more. The age wise inflation
expectations since Round 13 are given in
Statement IV. Across rounds, no uniform age
wise trend is seen in the survey responses.
The latest round of the survey shows that the respondents whose age is 45-50 years
have highest inflation expectations. But the
variation in responses is lowest for the
respondents of age group upto 25 years.
IV.2.4 City wise Inflation expectations
The city wise responses on inflation rate
show wide variations in inflation
expectations across cities. The city wise
inflation expectations since Round 13 are
given in Statement V. It can be seen from
this statement that in each survey round,
city wise averages are very divergent. This
reflects the divergence in consumption
patterns across cities. The latest round of
survey shows that the inflation expectation
for Bangalore was highest while it was
lowest for Chennai.
Table 6: Age group wise Inflation Expectations for March 2010 survey |
Survey
Period |
Age Group |
Current |
3 months ahead |
1 year ahead |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
|
upto 25 years |
10.1 |
4.07 |
10.6 |
4.37 |
11.2 |
4.51 |
|
25 to 30 years |
10.0 |
4.46 |
10.4 |
4.62 |
10.9 |
4.81 |
|
30 to 35 years |
10.2 |
4.38 |
10.5 |
4.70 |
11.0 |
4.87 |
|
35 to 40 years |
10.4 |
4.33 |
10.6 |
4.73 |
10.8 |
5.01 |
Mar-10 |
40 to 45 years |
10.2 |
4.53 |
10.3 |
4.91 |
10.9 |
5.00 |
|
45 to 50 years |
10.8 |
4.52 |
11.1 |
4.72 |
11.4 |
4.92 |
|
50 to 55 years |
10.4 |
4.25 |
10.8 |
4.57 |
11.2 |
4.70 |
|
55 to 60 years |
10.0 |
4.38 |
10.3 |
4.76 |
10.9 |
4.97 |
|
60 years & above |
10.6 |
4.43 |
10.7 |
4.72 |
11.1 |
4.85 |
Table 7: City wise Inflation Expectations for March 2010 survey |
Survey
Period |
City |
Current |
3 months ahead |
1 year ahead |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
|
Guwahati |
8.8 |
2.22 |
9.9 |
2.25 |
10.9 |
2.41 |
|
Patna |
10.7 |
1.30 |
11.5 |
1.42 |
11.6 |
1.47 |
|
Kolkata |
8.7 |
1.58 |
8.5 |
2.99 |
8.8 |
3.32 |
|
Lucknow |
9.6 |
3.37 |
10.4 |
3.30 |
10.6 |
3.35 |
|
Delhi |
10.8 |
3.95 |
11.0 |
4.80 |
12.2 |
4.50 |
Mar-10 |
Jaipur |
13.7 |
2.58 |
14.4 |
2.45 |
15.3 |
2.38 |
|
Ahmedabad |
9.4 |
2.86 |
11.1 |
3.03 |
12.2 |
2.29 |
|
Mumbai |
14.3 |
3.67 |
12.9 |
5.41 |
13.5 |
4.95 |
|
Bhopal |
8.3 |
3.53 |
9.4 |
3.60 |
10.6 |
3.93 |
|
Hyderabad |
12.7 |
4.13 |
12.5 |
4.45 |
12.6 |
4.43 |
|
Bangalore |
15.7 |
2.26 |
15.8 |
2.05 |
15.9 |
1.77 |
|
Chennai |
3.9 |
0.91 |
4.4 |
1.51 |
3.6 |
1.47 |
V. Summary
The Reserve Bank monitors an array of
measures of inflation, both overall and
disaggregated components, in conjunction
with other economic and financial
indicators to assess the underlying
inflationary pressures. The Reserve Bank of
India’s quarterly inflation expectations
survey of households (IESH) captures the
inflation expectations of 4000 urban
households across 12 cities spread across
the country. The survey represents the
expectation of inflation for the respondent’s
own basket of consumption. The inflation
numbers from this survey thus provide an
expectation of urban Indian households
based on the average inflation of 4000
different consumption baskets and are not predictors of any official measure of
inflation. The households’ inflation
expectations provide useful directional
information on near-term inflationary
pressures. The survey results show
presence of large inter-city variances in
households’ inflation expectations. The
quarterly update articles on future IESH
rounds would be published in the RBI
Bulletin.
It may again be emphasized that “IESH
survey results are those of the respondents
and are not necessarily shared by the
Reserve Bank. The inflation rate is assessed
by the respondents based on household
consumption basket which need not be
related with inflation rate as measured by
any official price index series.”
Statement I: Product wise expectation of prices for 3 month and 1 year ahead |
1 General Prices |
Round No./survey period → |
3 months ahead (percentage of respondents) |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
Options |
Sep-08 |
Dec-08 |
Mar-09 |
Jun-09 |
Sep-09 |
Dec-09 |
Mar-10 |
Prices will increase |
95.3 |
89.8 |
92.0 |
93.1 |
95.8 |
97.4 |
95.7 |
Price increase more than current rate |
66.4 |
52.9 |
54.9 |
63.5 |
72.2 |
74.6 |
66.9 |
Price increase similar to current rate |
19.9 |
20.1 |
22.4 |
20.7 |
18.4 |
16.6 |
20.0 |
Price increase less than current rate |
9.0 |
16.8 |
14.8 |
8.9 |
5.1 |
6.2 |
8.8 |
No change in prices |
3.4 |
5.7 |
6.9 |
6.1 |
3.7 |
2.4 |
3.4 |
Decline in price |
1.4 |
4.5 |
1.1 |
0.9 |
0.6 |
0.3 |
0.9 |
Options |
1 year ahead (percentage of respondents) |
Prices will increase |
95.2 |
90.6 |
95.6 |
93.7 |
96.3 |
96.3 |
96.5 |
Price increase more than current rate |
69.6 |
59.7 |
64.7 |
62.8 |
69.5 |
68.2 |
62.8 |
Price increase similar to current rate |
16.3 |
18.0 |
15.9 |
18.5 |
17.3 |
15.2 |
19.8 |
Price increase less than current rate |
9.3 |
12.9 |
15.0 |
12.4 |
9.5 |
12.9 |
13.9 |
No change in prices |
3.2 |
3.1 |
3.3 |
5.3 |
3.1 |
3.1 |
2.6 |
Decline in price |
1.8 |
6.3 |
1.1 |
0.9 |
0.7 |
0.6 |
0.9 |
2 Food Prices |
Round No./survey period → |
3 months ahead (percentage of respondents) |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
Options |
Sep-08 |
Dec-08 |
Mar-09 |
Jun-09 |
Sep-09 |
Dec-09 |
Mar-10 |
Prices will increase |
96.0 |
90.9 |
93.6 |
94.6 |
96.3 |
98.0 |
95.9 |
Price increase more than current rate |
69.7 |
53.5 |
58.6 |
64.5 |
76.1 |
81.1 |
70.4 |
Price increase similar to current rate |
17.8 |
19.7 |
23.3 |
21.5 |
15.0 |
11.7 |
15.5 |
Price increase less than current rate |
8.5 |
17.8 |
11.8 |
8.6 |
5.2 |
5.3 |
10.0 |
No change in prices |
2.6 |
5.3 |
5.6 |
4.6 |
3.0 |
1.4 |
3.1 |
Decline in price |
1.5 |
3.8 |
0.8 |
0.9 |
0.8 |
0.6 |
1.0 |
Options |
1 year ahead (percentage of respondents) |
Prices will increase |
95.5 |
91.4 |
96.6 |
94.7 |
96.2 |
96.5 |
96.8 |
Price increase more than current rate |
72.8 |
60.3 |
66.2 |
63.6 |
71.0 |
72.1 |
65.9 |
Price increase similar to current rate |
14.0 |
17.4 |
18.1 |
18.9 |
15.2 |
11.9 |
16.5 |
Price increase less than current rate |
8.7 |
13.7 |
12.4 |
12.2 |
10.0 |
12.5 |
14.5 |
No change in prices |
2.9 |
2.9 |
2.7 |
4.5 |
2.9 |
2.7 |
2.3 |
Decline in price |
1.8 |
5.8 |
0.7 |
0.8 |
0.9 |
0.9 |
0.9 |
3 Non Food Prices |
Round No./survey period → |
3 months ahead (percentage of respondents) |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
Options |
Sep-08 |
Dec-08 |
Mar-09 |
Jun-09 |
Sep-09 |
Dec-09 |
Mar-10 |
Prices will increase |
93.6 |
88.6 |
91.0 |
91.4 |
94.7 |
95.8 |
94.0 |
Price increase more than current rate |
58.0 |
47.5 |
48.6 |
51.2 |
59.3 |
63.1 |
57.4 |
Price increase similar to current rate |
24.1 |
23.3 |
25.5 |
28.4 |
27.1 |
24.8 |
28.0 |
Price increase less than current rate |
11.5 |
17.8 |
17.0 |
11.8 |
8.3 |
7.9 |
8.7 |
No change in prices |
4.9 |
6.6 |
7.8 |
7.7 |
4.7 |
3.7 |
4.8 |
Decline in price |
1.6 |
4.9 |
1.2 |
1.0 |
0.7 |
0.5 |
1.2 |
Options |
1 year ahead (percentage of respondents) |
Prices will increase |
92.9 |
89.3 |
94.6 |
91.9 |
95.2 |
94.6 |
94.7 |
Price increase more than current rate |
61.0 |
54.0 |
57.5 |
53.1 |
59.6 |
60.7 |
53.0 |
Price increase similar to current rate |
20.8 |
21.8 |
20.4 |
25.0 |
23.6 |
20.7 |
27.6 |
Price increase less than current rate |
11.1 |
13.5 |
16.7 |
13.8 |
12.1 |
13.2 |
14.1 |
No change in prices |
4.8 |
4.1 |
4.1 |
7.3 |
4.0 |
4.6 |
4.2 |
Decline in price |
2.3 |
6.6 |
1.4 |
0.8 |
0.8 |
0.8 |
1.1 |
Note: Two Rounds 13 and 13A were conducted in September and October 2008. The results presented in this article for Round 13 pertain to the October 2008 Round as the questionnaire for this and all the subsequent rounds is identical.” |
Statement I: Product wise expectation of prices for 3 month and 1 year ahead (Concld.) |
4 Prices of Household durables |
Round No./survey period → |
3 months ahead (percentage of respondents) |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
Options |
Sep-08 |
Dec-08 |
Mar-09 |
Jun-09 |
Sep-09 |
Dec-09 |
Mar-10 |
Prices will increase |
72.4 |
78.2 |
82.5 |
80.0 |
86.8 |
87.7 |
86.4 |
Price increase more than current rate |
27.9 |
32.6 |
33.2 |
37.2 |
38.4 |
45.5 |
44.1 |
Price increase similar to current rate |
23.3 |
24.6 |
24.2 |
26.3 |
30.5 |
23.4 |
27.2 |
Price increase less than current rate |
21.2 |
21.0 |
25.2 |
16.5 |
18.0 |
18.9 |
15.1 |
No change in prices |
14.4 |
12.9 |
14.6 |
15.7 |
11.0 |
9.5 |
8.8 |
Decline in price |
13.4 |
9.0 |
2.9 |
4.4 |
2.2 |
2.9 |
4.8 |
Options |
1 year ahead (percentage of respondents) |
Prices will increase |
73.1 |
79.1 |
84.6 |
80.4 |
88.7 |
87.8 |
85.2 |
Price increase more than current rate |
30.4 |
38.6 |
40.1 |
38.4 |
43.3 |
45.5 |
43.2 |
Price increase similar to current rate |
22.7 |
21.5 |
22.4 |
24.3 |
28.2 |
22.1 |
25.4 |
Price increase less than current rate |
20.0 |
19.0 |
22.1 |
17.7 |
17.3 |
20.3 |
16.6 |
No change in prices |
13.4 |
12.1 |
11.2 |
16.2 |
9.1 |
8.5 |
9.6 |
Decline in price |
13.5 |
8.8 |
4.2 |
3.5 |
2.2 |
3.7 |
5.3 |
5 Housing Prices |
Round No./survey period → |
3 months ahead (percentage of respondents) |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
Options |
Sep-08 |
Dec-08 |
Mar-09 |
Jun-09 |
Sep-09 |
Dec-09 |
Mar-10 |
Prices will increase |
90.9 |
88.4 |
89.8 |
92.4 |
93.8 |
96.1 |
95.2 |
Price increase more than current rate |
64.4 |
49.7 |
46.2 |
55.9 |
64.4 |
70.8 |
60.4 |
Price increase similar to current rate |
20.2 |
20.8 |
26.4 |
25.4 |
22.0 |
19.8 |
25.4 |
Price increase less than current rate |
6.3 |
17.9 |
17.2 |
11.1 |
7.4 |
5.6 |
9.5 |
No change in prices |
6.0 |
6.8 |
8.3 |
6.4 |
5.0 |
3.4 |
3.5 |
Decline in price |
3.2 |
4.8 |
1.9 |
1.3 |
1.2 |
0.5 |
1.3 |
Options |
1 year ahead (percentage of respondents) |
Prices will increase |
91.4 |
87.0 |
93.0 |
93.0 |
94.9 |
96.4 |
94.1 |
Price increase more than current rate |
65.1 |
56.3 |
57.4 |
57.6 |
66.0 |
73.4 |
61.0 |
Price increase similar to current rate |
20.1 |
20.2 |
20.0 |
22.1 |
21.4 |
15.1 |
21.7 |
Price increase less than current rate |
6.2 |
10.5 |
15.6 |
13.3 |
7.6 |
7.9 |
11.4 |
No change in prices |
5.2 |
5.5 |
5.4 |
5.8 |
3.8 |
2.9 |
4.6 |
Decline in price |
3.5 |
7.6 |
1.6 |
1.2 |
1.3 |
0.7 |
1.3 |
6 Cost of Services |
Round No./survey period → |
3 months ahead (percentage of respondents) |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
Options |
Sep-08 |
Dec-08 |
Mar-09 |
Jun-09 |
Sep-09 |
Dec-09 |
Mar-10 |
Prices will increase |
89.5 |
86.1 |
87.8 |
87.3 |
92.4 |
91.7 |
89.9 |
Price increase more than current rate |
55.0 |
43.9 |
42.2 |
53.1 |
63.7 |
62.7 |
58.6 |
Price increase similar to current rate |
24.2 |
26.9 |
29.2 |
22.2 |
22.9 |
21.2 |
23.9 |
Price increase less than current rate |
10.3 |
15.3 |
16.4 |
12.0 |
5.8 |
7.8 |
7.5 |
No change in prices |
7.6 |
10.3 |
10.4 |
11.3 |
6.3 |
7.0 |
6.7 |
Decline in price |
3.0 |
3.7 |
1.8 |
1.5 |
1.3 |
1.4 |
3.4 |
Options |
1 year ahead (percentage of respondents) |
Prices will increase |
91.0 |
88.4 |
90.7 |
88.1 |
95.0 |
92.3 |
89.9 |
Price increase more than current rate |
60.2 |
52.1 |
49.2 |
54.4 |
65.6 |
62.9 |
57.2 |
Price increase similar to current rate |
20.7 |
23.5 |
23.9 |
20.2 |
21.5 |
18.5 |
23.0 |
Price increase less than current rate |
10.1 |
12.9 |
17.6 |
13.5 |
7.9 |
10.9 |
9.8 |
No change in prices |
5.8 |
6.7 |
7.3 |
10.3 |
4.1 |
6.0 |
6.9 |
Decline in price |
3.3 |
4.9 |
2.1 |
1.6 |
1.0 |
1.8 |
3.2 |
Statement II: Cross-tabulation of current and future Inflation expectation |
Round 13 (September 2008) |
|
3 months ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
Total |
Current inflation rate |
< 1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
0 |
1-2 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
0 |
2-3 |
|
|
1 |
|
|
|
|
|
|
|
|
|
|
|
1 |
|
|
2 |
3-4 |
|
|
1 |
|
5 |
2 |
|
|
|
|
|
|
|
|
|
|
|
8 |
4-5 |
5 |
|
|
1 |
2 |
5 |
5 |
1 |
|
|
|
|
|
|
|
|
|
19 |
5-6 |
8 |
|
|
1 |
1 |
4 |
4 |
10 |
|
|
|
|
|
|
|
|
|
28 |
6-7 |
11 |
|
|
|
1 |
1 |
19 |
27 |
2 |
2 |
|
1 |
|
|
|
|
|
64 |
7-8 |
20 |
|
|
|
|
|
5 |
26 |
20 |
13 |
2 |
1 |
|
|
|
|
|
87 |
8-9 |
13 |
|
|
|
|
|
|
8 |
18 |
58 |
27 |
3 |
|
|
|
|
|
127 |
9-10 |
26 |
|
|
|
|
|
1 |
2 |
6 |
80 |
226 |
99 |
11 |
2 |
4 |
4 |
1 |
462 |
10-11 |
38 |
|
|
1 |
|
|
|
|
2 |
36 |
152 |
339 |
135 |
12 |
19 |
20 |
|
754 |
11-12 |
50 |
|
|
|
|
|
|
|
2 |
14 |
182 |
405 |
553 |
105 |
53 |
36 |
1 |
1401 |
12-13 |
8 |
|
|
|
|
|
|
|
|
|
|
43 |
126 |
246 |
41 |
20 |
3 |
487 |
13-14 |
5 |
|
|
|
|
|
|
|
|
|
|
1 |
10 |
52 |
131 |
28 |
10 |
237 |
14-15 |
3 |
|
|
|
|
|
|
|
|
|
|
|
2 |
4 |
54 |
79 |
9 |
151 |
15-16 |
4 |
|
|
|
|
|
|
|
|
|
|
|
|
|
11 |
55 |
31 |
101 |
>= 16 |
1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
3 |
67 |
72 |
Total |
192 |
0 |
2 |
3 |
9 |
12 |
34 |
74 |
50 |
203 |
589 |
892 |
837 |
421 |
315 |
245 |
122 |
4000 |
|
1 year ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
Total |
Current inflation rate |
< 1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
0 |
1-2 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
0 |
2-3 |
|
|
1 |
|
|
|
|
|
|
|
|
|
|
|
1 |
|
|
2 |
3-4 |
2 |
|
|
1 |
1 |
1 |
2 |
1 |
|
|
|
|
|
|
|
|
|
8 |
4-5 |
4 |
|
|
4 |
4 |
1 |
1 |
4 |
|
|
|
|
|
1 |
|
|
|
19 |
5-6 |
4 |
|
|
|
1 |
10 |
1 |
6 |
|
3 |
3 |
|
|
|
|
|
|
28 |
6-7 |
6 |
|
|
|
1 |
5 |
24 |
5 |
16 |
3 |
2 |
|
1 |
1 |
|
|
|
64 |
7-8 |
16 |
|
|
|
|
1 |
4 |
31 |
7 |
11 |
11 |
4 |
1 |
|
1 |
|
|
87 |
8-9 |
11 |
|
|
|
|
|
1 |
10 |
25 |
7 |
39 |
22 |
6 |
2 |
4 |
|
|
127 |
9-10 |
34 |
|
|
|
|
|
1 |
6 |
13 |
74 |
54 |
122 |
70 |
37 |
19 |
13 |
19 |
462 |
10-11 |
51 |
1 |
|
|
|
|
|
4 |
7 |
40 |
118 |
102 |
145 |
91 |
80 |
46 |
69 |
754 |
11-12 |
47 |
|
|
|
|
|
|
2 |
10 |
15 |
150 |
235 |
182 |
358 |
183 |
85 |
134 |
1401 |
12-13 |
8 |
|
|
|
|
|
|
|
|
|
2 |
40 |
91 |
70 |
150 |
51 |
75 |
487 |
13-14 |
6 |
|
|
|
|
|
|
|
|
|
2 |
1 |
4 |
36 |
47 |
71 |
70 |
237 |
14-15 |
2 |
|
|
|
|
|
|
|
|
|
|
|
3 |
8 |
22 |
47 |
69 |
151 |
15-16 |
2 |
|
|
|
|
|
1 |
|
|
|
|
|
|
2 |
8 |
15 |
73 |
101 |
>= 16 |
2 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
67 |
72 |
Total |
195 |
1 |
1 |
5 |
7 |
18 |
35 |
69 |
78 |
153 |
381 |
526 |
503 |
606 |
515 |
331 |
576 |
4000 |
Statement II: Cross-tabulation of current and future Inflation expectation (Contd.) |
Round 14 (December 2008) |
|
3 months ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
Total |
Current inflation rate |
< 1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1-2 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2-3 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3-4 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
4-5 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
5-6 |
|
|
|
|
2 |
24 |
28 |
1 |
|
|
|
|
|
|
|
|
|
55 |
6-7 |
6 |
|
|
|
|
21 |
57 |
56 |
4 |
1 |
|
|
|
|
|
|
|
145 |
7-8 |
56 |
|
|
|
|
2 |
57 |
139 |
172 |
38 |
17 |
1 |
|
|
|
|
|
482 |
8-9 |
223 |
|
|
|
|
|
43 |
321 |
376 |
478 |
169 |
52 |
14 |
1 |
3 |
|
|
1680 |
9-10 |
43 |
|
|
|
|
|
|
17 |
57 |
172 |
256 |
56 |
34 |
6 |
4 |
|
|
645 |
10-11 |
20 |
|
|
|
|
|
|
3 |
6 |
25 |
92 |
112 |
35 |
17 |
6 |
1 |
|
317 |
11-12 |
22 |
|
|
|
|
|
|
|
2 |
3 |
20 |
73 |
77 |
29 |
6 |
|
1 |
233 |
12-13 |
24 |
|
|
|
|
|
|
|
|
1 |
1 |
27 |
60 |
58 |
17 |
4 |
|
192 |
13-14 |
5 |
|
|
|
|
|
|
|
|
|
|
4 |
13 |
32 |
40 |
13 |
1 |
108 |
14-15 |
5 |
|
|
|
|
|
|
|
|
|
|
2 |
|
10 |
30 |
38 |
4 |
89 |
15-16 |
1 |
|
|
|
|
|
|
|
|
|
|
|
|
3 |
8 |
16 |
14 |
42 |
>= 16 |
2 |
|
|
|
|
|
|
|
|
|
|
|
|
|
2 |
|
8 |
12 |
Total |
407 |
|
|
|
2 |
47 |
185 |
537 |
617 |
718 |
555 |
327 |
233 |
156 |
116 |
72 |
28 |
4000 |
|
1 year ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
Total |
Current inflation rate |
< 1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1-2 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2-3 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3-4 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
4-5 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
5-6 |
|
|
|
|
1 |
12 |
36 |
6 |
|
|
|
|
|
|
|
|
|
55 |
6-7 |
4 |
|
|
|
1 |
8 |
21 |
85 |
17 |
4 |
5 |
|
|
|
|
|
|
145 |
7-8 |
50 |
|
|
|
|
2 |
49 |
81 |
145 |
84 |
44 |
11 |
8 |
2 |
|
1 |
5 |
482 |
8-9 |
194 |
|
|
|
|
1 |
54 |
196 |
323 |
304 |
331 |
158 |
59 |
32 |
15 |
8 |
4 |
1679 |
9-10 |
60 |
|
|
|
|
|
12 |
37 |
43 |
116 |
124 |
113 |
40 |
31 |
30 |
23 |
16 |
645 |
10-11 |
25 |
|
|
|
|
|
2 |
6 |
9 |
17 |
55 |
58 |
70 |
24 |
22 |
14 |
15 |
317 |
11-12 |
10 |
|
|
|
|
|
|
|
3 |
4 |
12 |
33 |
45 |
58 |
35 |
22 |
11 |
233 |
12-13 |
14 |
|
|
|
|
|
|
1 |
|
2 |
|
21 |
35 |
44 |
42 |
16 |
17 |
192 |
13-14 |
5 |
|
|
|
|
|
|
|
|
|
1 |
2 |
4 |
21 |
23 |
26 |
26 |
108 |
14-15 |
7 |
|
|
|
|
|
|
|
|
|
|
|
|
11 |
28 |
23 |
20 |
89 |
15-16 |
6 |
|
|
|
|
|
|
|
|
|
|
|
|
|
5 |
15 |
16 |
42 |
>= 16 |
1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
3 |
7 |
12 |
Total |
376 |
|
|
|
2 |
23 |
174 |
412 |
540 |
531 |
572 |
396 |
261 |
223 |
201 |
151 |
137 |
3999 |
Statement II: Cross-tabulation of current and future Inflation expectation (Contd.) |
Round 15 (March 2009) |
|
3 months ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
Total |
Current inflation rate |
< 1 |
2 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2 |
1-2 |
2 |
1 |
2 |
1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
6 |
2-3 |
17 |
9 |
16 |
17 |
6 |
4 |
2 |
|
|
|
|
|
|
|
|
|
|
71 |
3-4 |
87 |
20 |
116 |
285 |
405 |
159 |
29 |
10 |
|
2 |
|
|
|
|
|
|
|
1113 |
4-5 |
64 |
7 |
13 |
102 |
245 |
419 |
89 |
11 |
2 |
1 |
|
1 |
|
|
|
|
|
954 |
5-6 |
79 |
17 |
3 |
4 |
99 |
201 |
417 |
36 |
3 |
1 |
1 |
|
|
|
|
|
|
861 |
6-7 |
34 |
16 |
7 |
1 |
3 |
72 |
108 |
212 |
14 |
3 |
1 |
1 |
|
|
1 |
|
|
473 |
7-8 |
20 |
5 |
6 |
3 |
|
4 |
25 |
72 |
115 |
6 |
3 |
1 |
|
|
|
|
|
260 |
8-9 |
7 |
2 |
3 |
3 |
|
|
2 |
7 |
11 |
28 |
8 |
|
|
|
|
|
|
71 |
9-10 |
5 |
|
|
|
|
|
|
2 |
1 |
11 |
17 |
4 |
|
1 |
|
|
|
41 |
10-11 |
2 |
|
|
|
|
|
2 |
1 |
|
1 |
10 |
39 |
25 |
4 |
1 |
|
|
85 |
11-12 |
1 |
|
|
|
|
|
|
|
|
|
1 |
2 |
5 |
3 |
1 |
|
|
13 |
12-13 |
|
|
|
|
|
|
|
|
|
|
|
|
5 |
4 |
4 |
|
|
13 |
13-14 |
1 |
|
|
|
|
|
|
|
|
|
|
|
|
2 |
3 |
2 |
|
8 |
14-15 |
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
3 |
6 |
|
10 |
15-16 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
1 |
6 |
8 |
>= 16 |
1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
|
9 |
11 |
Total |
322 |
77 |
166 |
416 |
758 |
859 |
674 |
351 |
146 |
53 |
41 |
48 |
35 |
15 |
15 |
9 |
15 |
4000 |
|
1 year ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
Total |
Current inflation rate |
< 1 |
2 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2 |
1-2 |
2 |
1 |
1 |
1 |
|
1 |
|
|
|
|
|
|
|
|
|
|
|
6 |
2-3 |
5 |
7 |
23 |
11 |
9 |
5 |
7 |
2 |
2 |
|
|
|
|
|
|
|
|
71 |
3-4 |
46 |
22 |
63 |
184 |
198 |
205 |
211 |
109 |
31 |
14 |
13 |
11 |
5 |
|
|
|
1 |
1113 |
4-5 |
43 |
3 |
24 |
75 |
161 |
277 |
215 |
101 |
34 |
4 |
14 |
|
2 |
|
1 |
|
|
954 |
5-6 |
39 |
6 |
8 |
38 |
137 |
131 |
197 |
256 |
32 |
7 |
4 |
2 |
2 |
2 |
|
|
|
861 |
6-7 |
21 |
4 |
6 |
15 |
30 |
82 |
65 |
93 |
131 |
11 |
7 |
3 |
1 |
3 |
|
|
1 |
473 |
7-8 |
13 |
|
5 |
5 |
5 |
5 |
22 |
58 |
73 |
56 |
12 |
1 |
4 |
|
1 |
|
|
260 |
8-9 |
3 |
1 |
1 |
1 |
1 |
4 |
1 |
8 |
14 |
7 |
20 |
3 |
6 |
1 |
|
|
|
71 |
9-10 |
2 |
|
|
|
|
|
|
2 |
|
7 |
4 |
17 |
4 |
4 |
|
1 |
|
41 |
10-11 |
1 |
|
|
1 |
|
|
|
|
|
3 |
11 |
7 |
25 |
16 |
14 |
2 |
5 |
85 |
11-12 |
1 |
|
|
|
|
|
|
|
|
1 |
|
1 |
1 |
3 |
3 |
2 |
1 |
13 |
12-13 |
1 |
|
|
|
|
|
|
|
|
1 |
1 |
|
1 |
|
2 |
4 |
3 |
13 |
13-14 |
|
|
|
|
|
|
|
|
|
|
|
|
|
2 |
1 |
2 |
3 |
8 |
14-15 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
6 |
2 |
2 |
10 |
15-16 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2 |
6 |
8 |
>=16 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
1 |
9 |
11 |
Total |
|
44 |
131 |
331 |
541 |
710 |
718 |
629 |
317 |
111 |
86 |
45 |
51 |
31 |
29 |
16 |
31 |
4000 |
Statement II: Cross-tabulation of current and future Inflation expectation (Contd.) |
Round 16 (June 2009) |
|
3 months ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
Total |
Current inflation rate |
< 1 |
204 |
96 |
20 |
3 |
|
1 |
1 |
|
|
|
|
|
|
|
|
|
|
325 |
1-2 |
122 |
127 |
105 |
39 |
3 |
2 |
|
|
|
|
|
|
|
|
|
|
|
398 |
2-3 |
38 |
21 |
76 |
119 |
87 |
9 |
1 |
1 |
|
|
|
|
|
|
|
|
|
352 |
3-4 |
38 |
3 |
25 |
101 |
351 |
70 |
4 |
1 |
|
|
|
|
|
|
|
|
|
593 |
4-5 |
31 |
|
2 |
42 |
85 |
246 |
37 |
2 |
|
|
2 |
|
1 |
|
|
|
|
448 |
5-6 |
28 |
|
1 |
1 |
41 |
91 |
311 |
37 |
2 |
3 |
2 |
3 |
|
|
|
|
1 |
521 |
6-7 |
13 |
|
1 |
1 |
4 |
16 |
50 |
156 |
24 |
3 |
1 |
1 |
|
|
|
|
|
270 |
7-8 |
6 |
|
|
|
1 |
4 |
9 |
27 |
72 |
22 |
8 |
|
2 |
2 |
|
|
|
153 |
8-9 |
3 |
|
|
|
|
2 |
1 |
1 |
15 |
31 |
23 |
4 |
2 |
|
|
|
|
82 |
9-10 |
7 |
|
|
|
|
1 |
3 |
1 |
2 |
18 |
43 |
22 |
8 |
5 |
8 |
2 |
2 |
122 |
10-11 |
8 |
|
|
|
2 |
|
2 |
1 |
4 |
8 |
54 |
53 |
65 |
16 |
9 |
5 |
4 |
231 |
11-12 |
|
|
|
|
|
|
1 |
|
|
1 |
|
3 |
13 |
12 |
7 |
1 |
2 |
40 |
12-13 |
1 |
|
|
|
|
|
|
|
|
|
|
1 |
19 |
19 |
17 |
5 |
1 |
63 |
13-14 |
1 |
|
|
|
|
|
|
|
|
|
|
1 |
|
6 |
4 |
17 |
9 |
38 |
14-15 |
9 |
|
|
|
|
|
|
|
|
|
3 |
1 |
|
1 |
10 |
31 |
20 |
75 |
15-16 |
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
|
7 |
25 |
33 |
>= 16 |
6 |
|
|
|
|
1 |
1 |
|
|
1 |
4 |
|
1 |
1 |
1 |
1 |
239 |
256 |
Total |
515 |
247 |
230 |
306 |
574 |
443 |
421 |
227 |
119 |
87 |
140 |
89 |
111 |
63 |
56 |
69 |
303 |
4000 |
|
1 year ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
Total |
Current inflation rate |
< 1 |
110 |
125 |
39 |
17 |
22 |
7 |
1 |
3 |
|
|
1 |
|
|
|
|
|
|
325 |
1-2 |
105 |
121 |
52 |
74 |
31 |
8 |
4 |
2 |
|
1 |
|
|
|
|
|
|
|
398 |
2-3 |
33 |
21 |
83 |
63 |
80 |
50 |
12 |
7 |
|
2 |
|
|
1 |
|
|
|
|
352 |
3-4 |
30 |
10 |
41 |
100 |
52 |
265 |
62 |
25 |
4 |
2 |
|
2 |
|
|
|
|
|
593 |
4-5 |
28 |
2 |
16 |
62 |
82 |
65 |
138 |
35 |
12 |
1 |
4 |
|
2 |
|
|
|
1 |
448 |
5-6 |
37 |
|
1 |
27 |
108 |
84 |
54 |
165 |
22 |
9 |
7 |
5 |
|
1 |
|
|
1 |
521 |
6-7 |
12 |
1 |
|
2 |
8 |
33 |
54 |
44 |
90 |
11 |
9 |
5 |
|
|
|
1 |
|
270 |
7-8 |
11 |
|
|
|
2 |
5 |
4 |
20 |
31 |
50 |
12 |
8 |
2 |
2 |
2 |
3 |
1 |
153 |
8-9 |
4 |
|
|
|
|
1 |
2 |
1 |
8 |
19 |
19 |
7 |
11 |
6 |
3 |
|
1 |
82 |
9-10 |
6 |
|
|
|
|
2 |
1 |
4 |
6 |
14 |
20 |
32 |
12 |
6 |
11 |
2 |
6 |
122 |
10-11 |
5 |
|
1 |
1 |
2 |
|
1 |
4 |
1 |
11 |
54 |
9 |
62 |
27 |
29 |
13 |
11 |
231 |
11-12 |
2 |
|
|
|
|
|
|
2 |
|
|
|
3 |
5 |
8 |
6 |
11 |
3 |
40 |
12-13 |
3 |
|
|
|
|
|
|
|
|
|
2 |
3 |
13 |
11 |
14 |
8 |
9 |
63 |
13-14 |
1 |
|
|
|
|
|
|
|
|
1 |
1 |
1 |
|
8 |
1 |
7 |
18 |
38 |
14-15 |
5 |
|
|
|
1 |
|
1 |
3 |
|
1 |
2 |
1 |
1 |
2 |
9 |
17 |
32 |
75 |
15-16 |
1 |
|
|
|
|
|
|
|
|
|
1 |
|
1 |
|
1 |
5 |
24 |
33 |
>= 16 |
3 |
|
|
|
|
1 |
1 |
1 |
|
|
2 |
|
2 |
|
2 |
4 |
240 |
256 |
Total |
396 |
280 |
233 |
346 |
388 |
521 |
335 |
316 |
174 |
122 |
134 |
76 |
112 |
71 |
78 |
71 |
347 |
4000 |
Statement II: Cross-tabulation of current and future Inflation expectation (Contd.) |
Round 17 (September 2009) |
|
3 months ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
Total |
Current inflation rate |
< 1 |
223 |
154 |
53 |
7 |
9 |
1 |
5 |
1 |
1 |
2 |
|
2 |
1 |
|
|
|
|
459 |
1-2 |
23 |
63 |
169 |
47 |
13 |
7 |
1 |
1 |
|
1 |
2 |
|
|
|
1 |
|
|
328 |
2-3 |
12 |
14 |
39 |
209 |
24 |
8 |
3 |
|
|
2 |
2 |
|
|
|
|
|
1 |
314 |
3-4 |
11 |
|
14 |
45 |
268 |
12 |
3 |
2 |
|
|
|
|
|
|
|
|
|
355 |
4-5 |
27 |
|
|
10 |
42 |
143 |
22 |
7 |
|
2 |
|
|
|
|
|
|
|
253 |
5-6 |
16 |
|
|
3 |
17 |
44 |
104 |
26 |
1 |
1 |
2 |
|
|
|
|
|
|
214 |
6-7 |
6 |
|
|
|
6 |
9 |
29 |
80 |
41 |
3 |
2 |
|
|
|
|
1 |
|
177 |
7-8 |
13 |
|
|
|
|
9 |
5 |
20 |
41 |
24 |
7 |
|
1 |
|
1 |
1 |
|
122 |
8-9 |
5 |
|
|
|
|
|
3 |
2 |
14 |
26 |
9 |
|
4 |
1 |
1 |
|
|
65 |
9-10 |
3 |
|
|
|
|
|
|
0 |
1 |
14 |
33 |
26 |
11 |
1 |
1 |
|
|
90 |
10-11 |
5 |
|
|
|
|
|
1 |
3 |
|
4 |
39 |
91 |
75 |
7 |
5 |
9 |
5 |
244 |
11-12 |
1 |
|
|
|
|
|
|
|
|
|
1 |
8 |
22 |
5 |
8 |
1 |
1 |
47 |
12-13 |
4 |
|
|
|
|
|
|
|
|
|
1 |
|
15 |
37 |
12 |
6 |
9 |
84 |
13-14 |
1 |
|
|
|
|
|
|
|
|
|
|
|
1 |
11 |
18 |
12 |
9 |
52 |
14-15 |
8 |
|
|
|
|
|
|
|
|
|
1 |
1 |
|
1 |
21 |
76 |
45 |
153 |
15-16 |
3 |
|
|
|
|
|
|
|
|
|
3 |
|
|
1 |
3 |
35 |
130 |
175 |
>= 16 |
14 |
|
|
|
|
|
|
|
|
|
2 |
|
2 |
|
1 |
8 |
841 |
868 |
Total |
375 |
231 |
275 |
321 |
379 |
233 |
176 |
142 |
99 |
79 |
104 |
128 |
132 |
64 |
72 |
149 |
1041 |
4000 |
|
1 year ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
Total |
Current inflation rate |
< 1 |
162 |
28 |
141 |
42 |
34 |
15 |
12 |
8 |
2 |
4 |
1 |
1 |
2 |
3 |
1 |
2 |
1 |
459 |
1-2 |
12 |
38 |
42 |
102 |
49 |
30 |
21 |
15 |
4 |
4 |
2 |
3 |
2 |
|
2 |
2 |
|
328 |
2-3 |
13 |
38 |
59 |
23 |
98 |
24 |
10 |
21 |
6 |
5 |
7 |
1 |
|
|
|
4 |
5 |
314 |
3-4 |
25 |
5 |
87 |
81 |
16 |
111 |
15 |
5 |
4 |
1 |
|
1 |
2 |
1 |
1 |
|
|
355 |
4-5 |
17 |
|
2 |
39 |
60 |
26 |
76 |
11 |
9 |
5 |
3 |
3 |
1 |
|
1 |
|
|
253 |
5-6 |
9 |
|
|
3 |
18 |
50 |
34 |
69 |
14 |
9 |
3 |
1 |
2 |
|
1 |
|
1 |
214 |
6-7 |
5 |
|
|
|
8 |
11 |
31 |
27 |
72 |
12 |
7 |
2 |
1 |
|
|
|
1 |
177 |
7-8 |
7 |
|
|
|
|
8 |
9 |
18 |
22 |
29 |
11 |
6 |
3 |
4 |
|
3 |
2 |
122 |
8-9 |
5 |
|
|
|
|
|
3 |
6 |
11 |
8 |
16 |
5 |
4 |
0 |
2 |
4 |
1 |
65 |
9-10 |
0 |
|
|
|
|
1 |
|
1 |
2 |
10 |
6 |
18 |
20 |
12 |
11 |
5 |
4 |
90 |
10-11 |
5 |
|
|
|
|
1 |
|
1 |
|
4 |
40 |
27 |
59 |
40 |
33 |
17 |
17 |
244 |
11-12 |
1 |
|
|
|
|
|
|
|
1 |
|
2 |
4 |
3 |
14 |
8 |
9 |
5 |
47 |
12-13 |
2 |
|
|
|
|
1 |
|
|
|
|
3 |
|
8 |
9 |
25 |
11 |
25 |
84 |
13-14 |
4 |
|
|
|
|
|
|
|
|
|
1 |
|
1 |
4 |
8 |
13 |
21 |
52 |
14-15 |
8 |
|
|
|
|
|
|
|
1 |
|
1 |
|
2 |
1 |
22 |
24 |
94 |
153 |
15-16 |
6 |
|
|
|
|
1 |
|
|
|
1 |
|
|
2 |
2 |
4 |
37 |
122 |
175 |
>= 16 |
19 |
|
|
|
|
1 |
|
|
|
1 |
4 |
1 |
5 |
2 |
7 |
9 |
819 |
868 |
Total |
300 |
109 |
331 |
290 |
283 |
280 |
211 |
182 |
148 |
93 |
107 |
73 |
117 |
92 |
126 |
140 |
1118 |
4000 |
Statement II: Cross-tabulation of current and future Inflation expectation (Contd.) |
Round 18 (December 2009) |
|
3 months ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
no idea |
Total |
Current inflation rate |
< 1 |
|
3 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
1-2 |
2 |
3 |
9 |
5 |
2 |
1 |
|
|
|
|
|
|
|
|
|
|
|
|
22 |
2-3 |
2 |
6 |
16 |
131 |
10 |
4 |
1 |
1 |
|
|
|
|
|
|
|
|
|
|
171 |
3-4 |
7 |
1 |
14 |
44 |
305 |
23 |
|
|
|
|
|
|
|
|
|
1 |
|
|
395 |
4-5 |
5 |
|
|
2 |
30 |
114 |
47 |
6 |
1 |
|
2 |
|
|
|
1 |
|
|
|
208 |
5-6 |
1 |
|
1 |
1 |
5 |
16 |
67 |
38 |
4 |
1 |
|
2 |
1 |
|
1 |
|
|
|
138 |
6-7 |
2 |
|
|
2 |
|
|
19 |
46 |
25 |
4 |
3 |
|
1 |
|
|
|
1 |
2 |
105 |
7-8 |
4 |
|
|
|
|
|
2 |
19 |
33 |
29 |
9 |
2 |
|
1 |
2 |
|
1 |
2 |
104 |
8-9 |
|
|
|
|
|
|
1 |
3 |
21 |
27 |
18 |
3 |
3 |
2 |
|
|
3 |
|
81 |
9-10 |
1 |
|
|
|
|
|
|
2 |
1 |
26 |
40 |
37 |
19 |
3 |
2 |
|
|
1 |
132 |
10-11 |
6 |
|
|
|
|
1 |
1 |
1 |
5 |
13 |
87 |
182 |
74 |
17 |
15 |
5 |
3 |
5 |
415 |
11-12 |
3 |
|
1 |
|
|
|
1 |
|
|
1 |
11 |
130 |
55 |
36 |
22 |
13 |
1 |
8 |
282 |
12-13 |
4 |
|
|
|
|
|
|
|
|
|
2 |
5 |
96 |
76 |
34 |
15 |
5 |
9 |
246 |
13-14 |
3 |
|
|
|
|
|
|
|
|
|
1 |
2 |
1 |
56 |
56 |
36 |
5 |
7 |
167 |
14-15 |
2 |
|
|
|
|
|
|
|
|
|
|
|
1 |
1 |
62 |
98 |
29 |
6 |
199 |
15-16 |
5 |
|
|
|
|
|
|
|
1 |
|
1 |
|
|
|
1 |
28 |
167 |
7 |
210 |
>= 16 |
28 |
|
|
|
|
2 |
|
|
|
1 |
7 |
1 |
7 |
2 |
3 |
13 |
1033 |
14 |
1111 |
no idea |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
1 |
|
9 |
11 |
Total |
75 |
13 |
41 |
185 |
352 |
161 |
139 |
116 |
91 |
102 |
181 |
364 |
258 |
194 |
200 |
210 |
1248 |
70 |
4000 |
|
1 year ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
no idea |
Total |
Current inflation rate |
< 1 |
1 |
|
1 |
1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
1-2 |
4 |
8 |
1 |
4 |
3 |
1 |
|
1 |
|
|
|
|
|
|
|
|
|
|
22 |
2-3 |
11 |
58 |
23 |
4 |
61 |
4 |
3 |
4 |
|
|
|
|
|
|
1 |
|
1 |
1 |
171 |
3-4 |
41 |
11 |
147 |
62 |
14 |
105 |
9 |
3 |
|
1 |
|
|
|
|
|
1 |
1 |
|
395 |
4-5 |
4 |
2 |
3 |
28 |
44 |
20 |
63 |
21 |
10 |
3 |
4 |
|
2 |
1 |
2 |
|
1 |
|
208 |
5-6 |
2 |
1 |
|
4 |
4 |
26 |
21 |
31 |
18 |
19 |
4 |
2 |
1 |
1 |
|
3 |
1 |
|
138 |
6-7 |
1 |
1 |
|
|
1 |
4 |
18 |
15 |
25 |
7 |
16 |
7 |
3 |
|
2 |
|
2 |
3 |
105 |
7-8 |
4 |
|
|
|
|
|
3 |
16 |
15 |
16 |
19 |
12 |
8 |
2 |
1 |
|
2 |
6 |
104 |
8-9 |
|
|
|
|
|
|
2 |
1 |
11 |
16 |
21 |
10 |
5 |
5 |
2 |
1 |
5 |
2 |
81 |
9-10 |
1 |
|
|
|
|
1 |
|
2 |
|
21 |
23 |
17 |
26 |
20 |
11 |
5 |
2 |
3 |
132 |
10-11 |
8 |
|
1 |
|
|
|
1 |
1 |
4 |
13 |
75 |
59 |
113 |
55 |
39 |
9 |
24 |
13 |
415 |
11-12 |
2 |
|
|
|
|
|
1 |
|
1 |
6 |
13 |
67 |
26 |
53 |
55 |
33 |
9 |
16 |
282 |
12-13 |
2 |
|
|
|
|
|
|
|
|
2 |
5 |
5 |
29 |
72 |
62 |
40 |
17 |
12 |
246 |
13-14 |
2 |
|
|
|
|
|
|
|
|
1 |
2 |
2 |
|
19 |
48 |
57 |
28 |
8 |
167 |
14-15 |
2 |
|
|
|
|
|
|
|
|
|
1 |
|
5 |
2 |
29 |
58 |
94 |
8 |
199 |
15-16 |
4 |
|
|
|
|
|
|
|
1 |
|
1 |
|
|
|
1 |
23 |
169 |
11 |
210 |
>= 16 |
19 |
|
1 |
|
4 |
2 |
|
1 |
|
1 |
8 |
6 |
2 |
3 |
6 |
20 |
1010 |
28 |
1111 |
no idea |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
1 |
|
9 |
11 |
Total |
108 |
81 |
177 |
103 |
131 |
163 |
121 |
96 |
85 |
106 |
192 |
187 |
220 |
233 |
260 |
251 |
1366 |
120 |
4000 |
Statement II: Cross-tabulation of current and future Inflation expectation (Concld.) |
Round 19 (March 2010) |
|
|
3 months ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
no idea |
Total |
Current inflation rate |
< 1 |
|
2 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2 |
1-2 |
|
2 |
3 |
1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
6 |
2-3 |
1 |
13 |
17 |
57 |
8 |
3 |
2 |
|
|
|
|
|
|
|
|
|
|
|
101 |
3-4 |
21 |
1 |
18 |
37 |
132 |
8 |
3 |
|
|
|
|
|
|
|
|
|
|
|
220 |
4-5 |
11 |
|
1 |
7 |
34 |
162 |
11 |
4 |
6 |
1 |
1 |
|
|
|
|
|
1 |
|
239 |
5-6 |
1 |
|
|
|
5 |
38 |
68 |
31 |
4 |
5 |
3 |
|
1 |
|
|
|
1 |
4 |
161 |
6-7 |
2 |
|
1 |
|
1 |
4 |
39 |
85 |
37 |
8 |
7 |
1 |
|
|
|
|
1 |
3 |
189 |
7-8 |
10 |
|
|
|
|
5 |
9 |
98 |
99 |
38 |
24 |
4 |
2 |
|
|
|
2 |
14 |
305 |
8-9 |
30 |
|
1 |
|
|
|
5 |
42 |
214 |
171 |
66 |
22 |
12 |
9 |
2 |
1 |
2 |
29 |
606 |
9-10 |
9 |
|
|
|
|
|
|
2 |
5 |
57 |
106 |
30 |
14 |
3 |
1 |
|
|
18 |
245 |
10-11 |
12 |
|
|
|
|
|
|
1 |
2 |
9 |
96 |
230 |
72 |
25 |
5 |
|
3 |
13 |
468 |
11-12 |
3 |
|
|
|
|
|
|
|
1 |
2 |
3 |
27 |
49 |
39 |
14 |
2 |
2 |
4 |
146 |
12-13 |
2 |
|
|
|
|
|
|
|
|
2 |
2 |
1 |
20 |
56 |
40 |
6 |
|
3 |
132 |
13-14 |
6 |
|
|
|
|
|
|
|
|
|
3 |
1 |
2 |
18 |
41 |
32 |
2 |
2 |
107 |
14-15 |
7 |
|
|
|
|
|
|
|
|
|
|
|
|
1 |
17 |
59 |
9 |
|
93 |
15-16 |
6 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
27 |
67 |
2 |
102 |
>= 16 |
48 |
|
|
|
|
|
|
|
|
1 |
|
1 |
2 |
1 |
3 |
1 |
818 |
3 |
878 |
Total |
169 |
18 |
41 |
102 |
180 |
220 |
137 |
263 |
368 |
294 |
311 |
317 |
174 |
152 |
123 |
128 |
908 |
95 |
4000 |
|
1 year ahead inflation rate |
< 1 |
1-2 |
2-3 |
3-4 |
4-5 |
5-6 |
6-7 |
7-8 |
8-9 |
9-10 |
10-11 |
11-12 |
12-13 |
13-14 |
14-15 |
15-16 |
>= 16 |
no idea |
Total |
Current inflation rate |
< 1 |
|
1 |
|
|
|
|
|
|
|
|
|
1 |
|
|
|
|
|
|
2 |
1-2 |
|
1 |
2 |
2 |
|
|
|
1 |
|
|
|
|
|
|
|
|
|
|
6 |
2-3 |
5 |
31 |
29 |
|
19 |
4 |
5 |
3 |
2 |
2 |
|
|
1 |
|
|
|
|
|
101 |
3-4 |
3 |
12 |
87 |
64 |
8 |
30 |
6 |
3 |
3 |
1 |
1 |
|
|
|
|
|
2 |
|
220 |
4-5 |
10 |
|
3 |
95 |
58 |
6 |
37 |
4 |
5 |
4 |
5 |
3 |
1 |
2 |
|
|
1 |
5 |
239 |
5-6 |
2 |
|
|
3 |
21 |
37 |
10 |
21 |
17 |
11 |
19 |
7 |
3 |
1 |
3 |
1 |
1 |
4 |
161 |
6-7 |
3 |
|
|
|
3 |
3 |
32 |
14 |
50 |
21 |
27 |
17 |
6 |
5 |
2 |
|
3 |
3 |
189 |
7-8 |
12 |
|
|
|
|
5 |
13 |
80 |
48 |
45 |
38 |
26 |
13 |
5 |
|
|
3 |
17 |
305 |
8-9 |
32 |
|
|
|
|
|
29 |
8 |
176 |
66 |
132 |
42 |
43 |
12 |
13 |
4 |
6 |
43 |
606 |
9-10 |
9 |
|
|
|
|
|
|
4 |
2 |
51 |
45 |
50 |
29 |
12 |
6 |
3 |
6 |
28 |
245 |
10-11 |
7 |
|
|
|
|
|
|
3 |
2 |
8 |
91 |
135 |
82 |
53 |
33 |
11 |
15 |
28 |
468 |
11-12 |
3 |
|
|
|
|
|
|
|
1 |
1 |
2 |
29 |
9 |
38 |
31 |
15 |
8 |
9 |
146 |
12-13 |
4 |
|
|
|
|
|
|
|
|
2 |
|
|
12 |
11 |
44 |
33 |
20 |
6 |
132 |
13-14 |
3 |
|
|
|
|
|
|
|
|
2 |
3 |
1 |
1 |
11 |
16 |
51 |
16 |
3 |
107 |
14-15 |
1 |
|
|
|
|
|
|
|
|
|
|
|
1 |
|
16 |
24 |
51 |
|
93 |
15-16 |
6 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
17 |
72 |
7 |
102 |
>= 16 |
41 |
|
|
|
|
|
|
|
|
|
1 |
|
2 |
|
5 |
4 |
819 |
6 |
878 |
Total |
141 |
45 |
121 |
164 |
109 |
85 |
132 |
141 |
306 |
214 |
364 |
311 |
203 |
150 |
169 |
163 |
1023 |
159 |
4000 |
Statement III: Category wise inflation rates |
Survey
Period |
Category of
Respondent |
Current |
3 months ahead |
1 year ahead |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Sep-08 |
Fin Sec Employees |
11.2 |
1.84 |
11.6 |
3.14 |
12.4 |
3.62 |
Other Employees |
11.3 |
1.91 |
11.3 |
3.48 |
12.1 |
3.72 |
Self-Employed |
11.3 |
1.86 |
11.6 |
3.13 |
12.3 |
3.84 |
Housewife |
11.3 |
2.05 |
11.8 |
2.97 |
12.8 |
3.45 |
Retired persons |
11.2 |
2.04 |
11.2 |
3.67 |
12.1 |
3.84 |
Daily Workers |
11.2 |
2.23 |
11.7 |
2.84 |
12.5 |
3.49 |
Other Category |
11.3 |
1.65 |
11.5 |
3.18 |
12.5 |
3.27 |
Dec-08 |
Fin Sec Employees |
9.2 |
1.69 |
8.2 |
3.63 |
8.5 |
4.09 |
Other Employees |
9.1 |
1.76 |
8.4 |
3.65 |
9.4 |
3.74 |
Self-Employed |
9.3 |
1.85 |
8.8 |
3.69 |
9.5 |
4.06 |
Housewife |
9.4 |
2.00 |
9.6 |
3.02 |
10.4 |
3.29 |
Retired persons |
9.4 |
1.99 |
8.8 |
3.71 |
9.3 |
4.35 |
Daily Workers |
9.5 |
2.08 |
9.3 |
3.40 |
9.8 |
4.23 |
Other Category |
9.3 |
2.06 |
8.4 |
4.01 |
9.4 |
3.76 |
Mar-09 |
Fin Sec Employees |
4.9 |
1.82 |
4.8 |
2.52 |
5.7 |
2.64 |
Other Employees |
5.1 |
1.80 |
5.1 |
2.51 |
6.0 |
2.66 |
Self-Employed |
5.1 |
1.94 |
5.1 |
2.64 |
6.1 |
2.84 |
Housewife |
5.4 |
2.06 |
5.6 |
2.56 |
6.4 |
2.72 |
Retired persons |
5.2 |
1.99 |
5.3 |
2.59 |
6.1 |
2.80 |
Daily Workers |
5.3 |
2.00 |
5.6 |
2.58 |
6.5 |
2.72 |
Other Category |
5.3 |
2.01 |
5.6 |
2.55 |
6.4 |
2.73 |
Jun-09 |
Fin Sec Employees |
5.3 |
4.35 |
5.6 |
4.48 |
6.0 |
4.65 |
Other Employees |
5.3 |
4.26 |
5.8 |
4.58 |
6.3 |
4.64 |
Self-Employed |
5.7 |
4.43 |
6.2 |
4.65 |
6.7 |
4.70 |
Housewife |
6.3 |
4.30 |
6.7 |
4.64 |
7.0 |
4.75 |
Retired persons |
6.4 |
4.87 |
6.9 |
5.06 |
7.1 |
5.14 |
Daily Workers |
6.2 |
4.33 |
6.8 |
4.51 |
7.2 |
4.53 |
Other Category |
5.2 |
3.90 |
5.7 |
4.27 |
6.3 |
4.41 |
Sep-09 |
Fin Sec Employees |
8.3 |
6.19 |
8.7 |
6.05 |
9.3 |
5.85 |
Other Employees |
8.0 |
6.12 |
8.4 |
6.09 |
9.0 |
5.87 |
Self-Employed |
7.9 |
6.02 |
8.4 |
6.00 |
9.0 |
5.90 |
Housewife |
8.5 |
6.02 |
9.0 |
5.98 |
9.5 |
5.93 |
Retired persons |
8.4 |
6.14 |
9.1 |
6.01 |
9.7 |
5.86 |
Daily Workers |
8.0 |
5.69 |
8.6 |
5.79 |
9.2 |
5.71 |
Other Category |
7.8 |
5.97 |
8.3 |
6.03 |
9.1 |
5.79 |
Dec-09 |
Fin Sec Employees |
10.2 |
4.98 |
10.7 |
5.01 |
11.1 |
5.21 |
Other Employees |
10.9 |
4.97 |
11.4 |
4.88 |
11.8 |
5.02 |
Self-Employed |
11.1 |
4.94 |
11.4 |
4.92 |
11.7 |
5.12 |
Housewife |
11.5 |
4.81 |
12.0 |
4.74 |
12.1 |
5.14 |
Retired persons |
11.2 |
5.06 |
11.6 |
4.94 |
11.8 |
5.27 |
Daily Workers |
11.1 |
5.10 |
11.5 |
4.97 |
11.7 |
5.25 |
Other Category |
11.3 |
4.43 |
11.9 |
4.50 |
12.2 |
4.71 |
Mar-10 |
Fin Sec Employees |
9.5 |
4.14 |
9.8 |
4.46 |
10.3 |
4.73 |
Other Employees |
9.7 |
4.10 |
10.2 |
4.33 |
10.7 |
4.50 |
Self-Employed |
10.2 |
4.34 |
10.6 |
4.59 |
11.1 |
4.69 |
Housewife |
10.8 |
4.46 |
10.9 |
4.84 |
11.3 |
5.03 |
Retired persons |
10.5 |
4.60 |
10.6 |
4.86 |
10.8 |
5.08 |
Daily Workers |
11.1 |
4.80 |
11.0 |
5.24 |
11.6 |
5.35 |
Other Category |
9.8 |
3.72 |
10.4 |
4.04 |
11.0 |
4.32 |
Statement IV: Age wise inflation rates |
Survey
Period |
Age Group |
Current |
3 months ahead |
1 year ahead |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Sep-08 |
upto 25 years |
11.4 |
1.93 |
11.9 |
2.83 |
12.8 |
3.23 |
25 to 30 years |
11.3 |
1.97 |
11.8 |
3.01 |
12.8 |
3.62 |
30 to 35 years |
11.3 |
1.91 |
11.6 |
3.11 |
12.5 |
3.49 |
35 to 40 years |
11.4 |
1.93 |
11.9 |
2.97 |
12.6 |
3.60 |
40 to 45 years |
11.2 |
1.94 |
11.5 |
3.20 |
12.3 |
3.71 |
45 to 50 years |
11.0 |
1.91 |
11.4 |
3.14 |
12.3 |
3.45 |
50 to 55 years |
11.0 |
1.84 |
10.8 |
3.57 |
11.6 |
3.72 |
55 to 60 years |
11.2 |
2.04 |
11.3 |
3.63 |
12.3 |
3.53 |
60 years & above |
11.1 |
2.14 |
11.0 |
3.83 |
11.6 |
4.32 |
Dec-08 |
upto 25 years |
9.4 |
2.02 |
9.2 |
3.39 |
10.0 |
3.72 |
25 to 30 years |
9.3 |
1.97 |
9.2 |
3.31 |
9.8 |
3.72 |
30 to 35 years |
9.3 |
1.93 |
9.1 |
3.36 |
9.9 |
3.72 |
35 to 40 years |
9.5 |
2.00 |
9.0 |
3.70 |
9.8 |
3.91 |
40 to 45 years |
9.1 |
1.68 |
8.6 |
3.40 |
9.2 |
3.86 |
45 to 50 years |
9.2 |
1.94 |
8.4 |
3.99 |
9.3 |
3.87 |
50 to 55 years |
9.2 |
1.65 |
8.4 |
3.71 |
9.3 |
3.75 |
55 to 60 years |
9.1 |
1.73 |
8.5 |
3.74 |
8.8 |
4.39 |
60 years & above |
9.4 |
1.92 |
8.8 |
3.68 |
9.4 |
4.18 |
Mar-09 |
upto 25 years |
5.1 |
1.72 |
5.3 |
2.33 |
6.2 |
2.48 |
25 to 30 years |
5.3 |
2.01 |
5.3 |
2.61 |
6.2 |
2.77 |
30 to 35 years |
5.4 |
2.09 |
5.5 |
2.65 |
6.4 |
2.82 |
35 to 40 years |
5.3 |
1.95 |
5.5 |
2.59 |
6.3 |
2.85 |
40 to 45 years |
5.2 |
1.98 |
5.1 |
2.60 |
6.0 |
2.78 |
45 to 50 years |
5.3 |
2.22 |
5.4 |
2.87 |
6.3 |
3.02 |
50 to 55 years |
5.1 |
1.59 |
5.0 |
2.32 |
5.9 |
2.44 |
55 to 60 years |
5.1 |
1.95 |
5.1 |
2.57 |
6.0 |
2.50 |
60 years & above |
5.1 |
1.98 |
5.1 |
2.69 |
6.0 |
2.85 |
Jun-09 |
upto 25 years |
5.9 |
4.26 |
6.5 |
4.46 |
6.9 |
4.57 |
25 to 30 years |
6.0 |
4.18 |
6.6 |
4.40 |
7.0 |
4.50 |
30 to 35 years |
5.9 |
4.20 |
6.4 |
4.45 |
6.8 |
4.54 |
35 to 40 years |
5.9 |
4.40 |
6.3 |
4.66 |
6.7 |
4.73 |
40 to 45 years |
5.9 |
4.51 |
6.4 |
4.86 |
6.8 |
4.87 |
45 to 50 years |
5.0 |
3.98 |
5.4 |
4.35 |
5.8 |
4.60 |
50 to 55 years |
5.8 |
4.68 |
5.9 |
4.94 |
6.1 |
4.88 |
55 to 60 years |
5.3 |
4.38 |
5.6 |
4.66 |
5.8 |
4.59 |
60 years & above |
6.4 |
4.94 |
6.8 |
5.20 |
7.2 |
5.26 |
Statement IV: Age wise inflation rates (Concld.) |
Survey
Period |
Age Group |
Current |
3 months ahead |
1 year ahead |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Sep-09 |
upto 25 years |
8.4 |
6.05 |
8.9 |
6.08 |
9.4 |
5.82 |
25 to 30 years |
7.8 |
5.90 |
8.4 |
5.82 |
9.1 |
5.72 |
30 to 35 years |
8.1 |
5.91 |
8.6 |
5.90 |
9.0 |
5.88 |
35 to 40 years |
8.0 |
6.05 |
8.5 |
5.97 |
9.2 |
5.85 |
40 to 45 years |
7.7 |
6.02 |
8.2 |
6.03 |
8.8 |
5.95 |
45 to 50 years |
8.1 |
6.21 |
8.7 |
6.16 |
9.0 |
6.06 |
50 to 55 years |
8.8 |
6.04 |
9.0 |
6.09 |
9.6 |
5.92 |
55 to 60 years |
9.1 |
6.16 |
9.7 |
5.95 |
10.0 |
5.78 |
60 years & above |
8.3 |
6.15 |
9.0 |
6.10 |
9.5 |
5.98 |
Dec-09 |
upto 25 years |
11.4 |
4.73 |
11.9 |
4.70 |
12.3 |
4.90 |
25 to 30 years |
10.6 |
5.07 |
11.1 |
4.95 |
11.4 |
5.29 |
30 to 35 years |
11.0 |
4.96 |
11.5 |
4.86 |
11.6 |
5.18 |
35 to 40 years |
10.8 |
5.01 |
11.1 |
4.98 |
11.5 |
5.29 |
40 to 45 years |
11.1 |
5.03 |
11.5 |
5.07 |
11.9 |
5.16 |
45 to 50 years |
11.4 |
4.66 |
11.9 |
4.57 |
12.3 |
4.68 |
50 to 55 years |
11.6 |
4.60 |
12.1 |
4.66 |
12.3 |
4.82 |
55 to 60 years |
10.8 |
5.21 |
11.1 |
5.17 |
11.5 |
5.49 |
60 years & above |
12.1 |
4.58 |
12.6 |
4.50 |
12.5 |
4.94 |
Mar-10 |
upto 25 years |
10.1 |
4.07 |
10.6 |
4.37 |
11.2 |
4.51 |
25 to 30 years |
10.0 |
4.46 |
10.4 |
4.62 |
10.9 |
4.81 |
30 to 35 years |
10.2 |
4.38 |
10.5 |
4.70 |
11.0 |
4.87 |
35 to 40 years |
10.4 |
4.33 |
10.6 |
4.73 |
10.8 |
5.01 |
40 to 45 years |
10.2 |
4.53 |
10.3 |
4.91 |
10.9 |
5.00 |
45 to 50 years |
10.8 |
4.52 |
11.1 |
4.72 |
11.4 |
4.92 |
50 to 55 years |
10.4 |
4.25 |
10.8 |
4.57 |
11.2 |
4.70 |
55 to 60 years |
10.0 |
4.38 |
10.3 |
4.76 |
10.9 |
4.97 |
60 years & above |
10.6 |
4.43 |
10.7 |
4.72 |
11.1 |
4.85 |
Statement V: City wise inflation rates |
Survey
Period |
City |
Current |
3 months ahead |
1 year ahead |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Sep-08 |
Guwahati |
11.7 |
0.48 |
10.6 |
2.79 |
10.8 |
2.06 |
Patna |
9.4 |
1.83 |
10.1 |
1.72 |
10.4 |
1.94 |
Kolkata |
10.8 |
2.66 |
9.0 |
5.44 |
9.9 |
5.45 |
Lucknow |
10.0 |
2.15 |
10.4 |
3.19 |
10.2 |
3.97 |
Delhi |
11.2 |
1.13 |
11.9 |
1.43 |
12.6 |
2.01 |
Jaipur |
12.3 |
1.10 |
13.1 |
1.48 |
13.8 |
1.90 |
Ahmedabad |
11.4 |
1.08 |
13.6 |
2.62 |
14.8 |
3.17 |
Mumbai |
11.4 |
0.93 |
11.9 |
1.47 |
14.2 |
1.48 |
Bhopal |
14.2 |
1.78 |
14.8 |
1.41 |
15.7 |
1.21 |
Hyderabad |
13.3 |
1.48 |
14.1 |
1.51 |
14.7 |
1.79 |
Bangalore |
11.0 |
1.60 |
11.6 |
1.81 |
12.2 |
1.66 |
Chennai |
10.1 |
0.96 |
10.6 |
2.65 |
11.5 |
4.34 |
Dec-08 |
Guwahati |
8.4 |
0.29 |
4.7 |
3.54 |
8.0 |
1.14 |
Patna |
7.8 |
1.17 |
8.7 |
1.29 |
8.5 |
1.63 |
Kolkata |
9.0 |
1.03 |
8.5 |
2.59 |
9.2 |
2.52 |
Lucknow |
8.5 |
0.98 |
6.5 |
3.88 |
6.7 |
3.88 |
Delhi |
8.8 |
1.23 |
9.0 |
2.22 |
9.7 |
2.22 |
Jaipur |
10.5 |
2.24 |
10.7 |
3.10 |
11.3 |
4.20 |
Ahmedabad |
9.4 |
0.90 |
9.5 |
4.37 |
10.6 |
5.83 |
Mumbai |
12.3 |
1.66 |
11.1 |
4.23 |
12.5 |
3.55 |
Bhopal |
8.5 |
0.43 |
9.5 |
1.06 |
10.3 |
1.22 |
Hyderabad |
7.3 |
1.33 |
7.3 |
1.52 |
8.1 |
1.61 |
Bangalore |
10.7 |
2.30 |
11.7 |
2.72 |
13.4 |
2.71 |
Chennai |
8.8 |
0.82 |
8.3 |
3.45 |
7.2 |
4.93 |
Mar-09 |
Guwahati |
4.4 |
0.88 |
4.9 |
1.09 |
5.0 |
1.16 |
Patna |
4.8 |
0.68 |
5.6 |
0.86 |
5.9 |
0.71 |
Kolkata |
4.1 |
1.35 |
3.5 |
2.21 |
4.6 |
2.45 |
Lucknow |
6.1 |
2.60 |
6.6 |
3.11 |
6.9 |
3.05 |
Delhi |
5.3 |
1.75 |
5.9 |
2.35 |
7.2 |
2.47 |
Jaipur |
6.3 |
2.76 |
7.3 |
3.16 |
8.5 |
3.69 |
Ahmedabad |
4.6 |
1.55 |
3.7 |
2.04 |
5.6 |
3.08 |
Mumbai |
5.0 |
1.44 |
4.4 |
1.99 |
5.2 |
2.08 |
Bhopal |
3.6 |
0.42 |
4.0 |
1.21 |
6.1 |
1.47 |
Hyderabad |
6.6 |
2.05 |
7.4 |
2.36 |
8.0 |
2.56 |
Bangalore |
7.1 |
3.20 |
7.0 |
3.52 |
8.2 |
3.39 |
Chennai |
5.6 |
0.72 |
5.4 |
1.87 |
5.4 |
2.03 |
Jun-09 |
Guwahati |
0.7 |
0.42 |
0.8 |
0.48 |
1.3 |
0.62 |
Patna |
10.7 |
2.48 |
11.4 |
3.41 |
11.6 |
3.74 |
Kolkata |
2.7 |
1.82 |
2.4 |
2.08 |
2.8 |
2.35 |
Lucknow |
3.3 |
1.28 |
4.6 |
1.34 |
5.1 |
1.61 |
Delhi |
4.0 |
2.86 |
4.9 |
3.16 |
5.7 |
3.44 |
Jaipur |
7.9 |
4.70 |
8.9 |
4.86 |
9.8 |
5.05 |
Ahmedabad |
11.7 |
3.67 |
11.9 |
4.48 |
12.5 |
4.29 |
Mumbai |
4.9 |
2.18 |
4.8 |
2.67 |
5.0 |
2.72 |
Bhopal |
3.3 |
0.97 |
4.2 |
1.41 |
5.3 |
1.78 |
Hyderabad |
7.1 |
2.56 |
8.2 |
2.87 |
8.8 |
2.87 |
Bangalore |
14.8 |
3.42 |
15.0 |
3.15 |
15.1 |
2.96 |
Chennai |
5.3 |
0.81 |
5.9 |
1.33 |
5.4 |
2.00 |
Statement V: City wise inflation rates (Concld.) |
Survey
Period |
City |
Current |
3 months ahead |
1 year ahead |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Mean |
Std. Dev. |
Sep-09 |
Guwahati |
5.7 |
2.93 |
4.6 |
3.49 |
5.1 |
3.18 |
Patna |
13.4 |
2.87 |
14.2 |
2.58 |
14.3 |
2.51 |
Kolkata |
1.4 |
1.90 |
2.1 |
2.31 |
2.9 |
2.48 |
Lucknow |
10.2 |
5.41 |
11.0 |
5.28 |
11.4 |
5.20 |
Delhi |
6.2 |
4.86 |
6.9 |
5.21 |
8.1 |
5.22 |
Jaipur |
11.8 |
4.23 |
12.8 |
4.03 |
13.4 |
4.38 |
Ahmedabad |
9.4 |
4.23 |
10.0 |
4.39 |
10.4 |
4.41 |
Mumbai |
12.1 |
5.46 |
11.9 |
5.82 |
11.9 |
5.60 |
Bhopal |
2.3 |
1.90 |
4.3 |
2.58 |
7.5 |
3.53 |
Hyderabad |
15.6 |
1.56 |
16.1 |
1.02 |
16.2 |
0.92 |
Bangalore |
15.7 |
2.02 |
15.8 |
1.78 |
16.0 |
1.43 |
Chennai |
3.4 |
0.94 |
4.2 |
1.06 |
3.8 |
1.73 |
Dec-09 |
Guwahati |
13.3 |
2.85 |
13.7 |
2.51 |
14.3 |
2.22 |
Patna |
12.3 |
2.41 |
13.0 |
2.55 |
13.3 |
2.57 |
Kolkata |
11.9 |
2.70 |
12.1 |
2.84 |
12.7 |
2.91 |
Lucknow |
6.1 |
3.40 |
7.0 |
3.38 |
7.1 |
3.64 |
Delhi |
11.2 |
4.74 |
11.9 |
4.74 |
12.1 |
5.04 |
Jaipur |
13.2 |
2.96 |
14.2 |
3.03 |
14.7 |
3.60 |
Ahmedabad |
9.1 |
3.49 |
10.9 |
3.51 |
11.6 |
2.99 |
Mumbai |
15.3 |
2.71 |
14.2 |
4.83 |
14.8 |
3.92 |
Bhopal |
9.6 |
4.47 |
10.8 |
4.51 |
11.8 |
4.67 |
Hyderabad |
15.2 |
2.62 |
15.5 |
2.33 |
15.7 |
2.05 |
Bangalore |
15.4 |
2.19 |
15.4 |
2.17 |
15.6 |
1.83 |
Chennai |
3.4 |
0.76 |
4.2 |
1.01 |
3.4 |
1.77 |
Mar-10 |
Guwahati |
8.8 |
2.22 |
9.9 |
2.25 |
10.9 |
2.41 |
Patna |
10.7 |
1.30 |
11.5 |
1.42 |
11.6 |
1.47 |
Kolkata |
8.7 |
1.58 |
8.5 |
2.99 |
8.8 |
3.32 |
Lucknow |
9.6 |
3.37 |
10.4 |
3.30 |
10.6 |
3.35 |
Delhi |
10.8 |
3.95 |
11.0 |
4.80 |
12.2 |
4.50 |
Jaipur |
13.7 |
2.58 |
14.4 |
2.45 |
15.3 |
2.38 |
Ahmedabad |
9.4 |
2.86 |
11.1 |
3.03 |
12.2 |
2.29 |
Mumbai |
14.3 |
3.67 |
12.9 |
5.41 |
13.5 |
4.95 |
Bhopal |
8.3 |
3.53 |
9.4 |
3.60 |
10.6 |
3.93 |
Hyderabad |
12.7 |
4.13 |
12.5 |
4.45 |
12.6 |
4.43 |
Bangalore |
15.7 |
2.26 |
15.8 |
2.05 |
15.9 |
1.77 |
Chennai |
3.9 |
0.91 |
4.4 |
1.51 |
3.6 |
1.47 |
![1](../scripts/images/4ARB080510_07.gif) |
|
![1](../scripts/images/4ARB080510_08.gif) |
Appendix II (Contd.) |
Description of Parameters |
Food Products |
(i) |
Cereals (Wheat, Rice, Pulses etc),Fruits, Vegetables, Sugar, Edible oils,
Dairy products and bakery products, Tea, coffee |
|
(ii) |
Meat, fish and sea products |
|
(iii) |
Soft drinks carbonated and mineral water, Beverages |
|
(iv) |
Bidi, cigarette and other tobacco products like zarda, pan masala and
related products etc. |
Non-Food Products |
(i) |
Clothes and wearing apparels |
|
(ii) |
Pharmaceutical and Medicines, Cleaning and polishing products,
Soaps and detergents |
|
(iii) |
Rubber and rubber products, Tyres and tubes |
|
(iv) |
Plastic and plastic products |
|
(v) |
Leather and leather products (footwear etc.) |
|
(vi) |
Paper and paper products (stationery etc.) |
|
(vii) |
Petroleum and coal products |
|
(viii) |
Basic chemical and chemical products, Dyes and dye stuff |
|
(ix) |
Basic metal non-metallic mineral products etc. |
House holds Durables |
(i) |
Audiovisual equipment (Radio, television, video camera
telephone microphone, mobile etc.) |
|
(ii) |
Furniture, Wood and wood products |
|
(iii) |
Washing machines, Air cooler and Air conditioner |
|
(iv) |
Personal computer |
|
(v) |
Watches and clocks, etc. |
Housing |
(i) |
Construction and maintenance of residential/office premises |
|
(ii) |
Site preparation |
Services |
(i) |
Computer, related activities like computer hardware/software
consultancy, data processing, computer related education institute |
|
(ii) |
Health and social work |
|
(iii) |
Banking/postal services |
|
(iv) |
Activities of membership organizations |
|
(v) |
Other business activities like washing, cleaning, hairdressing, courier activities, etc. |
Code Lists for filling in Respondents’ Codes:
A. Zone Codes
Sr.No. |
Zone |
Zone Code |
1 |
Mumbai |
1 |
2 |
Kolkata |
2 |
3 |
Chennai |
3 |
4 |
Delhi |
4 |
B. City Codes
Zone |
Sr.No |
City Name |
City Code |
Mumbai |
1 |
Mumbai |
600 |
|
2 |
Ahmedabad |
540 |
|
3 |
Bhopal |
700 |
Kolkata |
4 |
Kolkata |
100 |
|
5 |
Guwahati |
010 |
|
6 |
Patna |
060 |
Chennai |
7 |
Chennai |
900 |
|
8 |
Hyderabad |
800 |
|
9 |
Bangalore |
840 |
Delhi |
10 |
Delhi |
290 |
|
11 |
Jaipur |
500 |
|
12 |
Lucknow |
200 |
C. Gender Codes
Sr.No. |
Gender |
Gender Code |
1 |
Male |
1 |
2 |
Female |
2 |
D. Category Codes
Sr. No. |
Category of Respondent |
Category Code |
1 |
FINANCIAL SECTOR EMPLOYEES |
1 |
2 |
OTHER EMPLOYEES |
2 |
3 |
SELF-EMPLOYED |
3 |
4 |
HOUSEWIFE |
4 |
5 |
RETIRED PERSONS |
5 |
6 |
DAILY WORKERS |
6 |
7 |
OTHER CATEGORY |
7 |
E. Age Group Codes
Sr.No. |
Age Group |
Age group code |
1 |
Up to 25 years |
1 |
2 |
25 to 30 years |
2 |
3 |
30 to 35 years |
3 |
4 |
35 to 40 years |
4 |
5 |
40 to 45 years |
5 |
6 |
45 to 50 years |
6 |
7 |
50 to 55 years |
7 |
8 |
55 to 60 years |
8 |
9 |
60 years and above |
9 |
Appendix III
Training of investigators
As recommended by TACS, a training of
investigators is carried out before launch of each
round of survey. The training, as designed by the
experts at Indian Statistical Institute, Kolkata, is
done in a uniform manner at each regional office
and at the central office of the Department of
Statistics and Information Management (DSIM).
The training broadly covers the following:
-
Brief concepts on price movements and
inflation movements are provided to the
investigators. They are informed that the RBI
is not seeking the respondents’ assessment/
forecast on official price measures but the
respondents own assessment of inflation
based on his or her own consumption basket.
-
To help the respondent to arrive at his or her
inflation rate, the investigator is asked to say
“how much does your usual basket of consumption that cost Rs. 100/- a year back, cost
now”. This helps in arriving at the respondent’s
‘current’ inflation rate. The respondent’s
current rate of inflation is kept as the point of
comparison for the rest of the interview when
the respondent is enquired if he feels the prices
after 3 months or 1 year will move at, faster or
slower than the ‘current’ rate.
-
In case a respondent provides an inconsistent
response, the investigator is informed to seek
clarification but in no way influence the
response.
-
The investigators are asked to spend 10-15
minutes with each respondent and conduct
not more than 20 interviews in a day.
-
In case the respondent has any doubt, the
investigators are asked to provide clarification
in a simple manner without using any
technical jargons.
![1](../scripts/images/4ARB080510_09.gif) |
Letter of Transmittal
September , 2009
Dr. D. Subbarao
Governor
Reserve Bank of India
Mumbai
Dear Sir,
Report of the Technical Advisory Committee on
Inflation Expectations Survey of Households
We are pleased to submit our Report on the Inflation Expectations Survey of Households.
TABLE OF CONTENTS
Acknowledgements |
i |
Executive Summary |
ii-iv |
List of acronyms |
v |
I. |
Introduction |
1 |
|
I.1 |
Formation of TACS |
|
|
I.2 |
Organisation of the Report |
|
II. |
Inflation Expectation- Theory, Measurement and International Experience |
4 |
II.1 |
Theory and Measurement |
|
II.2 |
International Experience |
|
III. Inflation Expectation Survey of Reserve Bank |
8 |
|
III.1 |
First Report of TACS |
|
|
III.2 |
Analysis of data quality by ISI team for new rounds of data |
|
|
III.3 |
Characteristics of IESH results |
|
IV. |
Conclusion and Recommendations |
18 |
Annexes |
|
Annex-I |
Constitution of TACS |
21 |
Annex-II |
Review of International Practices- secelct countries |
23 |
Annex-III |
Findings of the analysis of the latest rounds of data by the ISI team |
26 |
|
A Consistency of response to the qualitative question |
|
|
B Consistency of response to the quantitative question |
|
|
C Interconsistency between response to qualitative and quantitative questions |
|
|
D Logistic Issues |
|
Annex-IV |
ANOVA Analysis of IESH data |
37 |
Annex-VI |
Schedule |
42 |
Acknowledgements
The Committee wishes to place on record its gratitude to Professor Shibdas Bandyopadhyay and Professor
Debasish Sengupta of the Indian Statistical Institute (ISI), Kolkata for their active participation in the
meetings of the Committee as special invitees and for sharing the burden of empirical validation of
the micro-level data from various rounds of the IESH survey with the help of their team members at
the ISI, Kolkata who handled this novel issue with expertise. The Committee also acknowledges the
dedicated efforts put in by members of its Secretariat especially Shri S.N.S. Tyagi, Assistant Adviser,
Department of Statistics and Information Management (DSIM), RBI who was associated with the initial
analysis and Dr. (Smt.) Praggya Das, Assistant Adviser, DSIM, RBI who made valuable contributions in
the deliberations and also shouldered the responsibility of drafting the Committee’s report. The
Committee also appreciates the RBI team consisting of Shri M.S. Adki, Smt.Vijaya Gangadharan,
Dr. O.S. Swami, Shri Avijit Joarder and other officials and staff members of Survey Division, DSIM for
the secretariat support in bringing out this report.
Report of the Technical Advisory Committee on Surveys
Executive Summary
1. The Reserve Bank of India has been conducting quarterly surveys on inflation expectations (IE) of
households since 2005 to seek views on inflationary expectations from the general public. The
survey findings are presented every quarter in the Monetary Policy Strategy meeting and the
highlights of the survey are presented in the quarterly meetings of the Technical Advisory
Committee (TAC) on Monetary Policy. In the seventh meeting of the TAC on Monetary Policy held
in January 2007, a member pointed to the divergence between the results of the IE survey and
price movements reflected in official price indices. Subsequently, a Technical Advisory Committee
on Surveys (TACS) was constituted by the Reserve Bank under the chairmanship of Dr. Rakesh
Mohan, Deputy Governor to review the methodology and data quality of various rounds of survey
and suggest ways to improve on it.
2. For more than a year and a half, the TACS has been watching the Survey data and suggesting
recommendations on improving the data quality and consistency. This report presents the
developments over this period and the recommendations of the Committee on placing the survey
results in public domain.
3. The Report is organised in four sections, Section I being introduction. The Section II presents a
brief theoretical background, measurement issues for inflation expectation and a review of
international practice in carrying out the survey. The review indicates the findings of these surveys
are used by the respective central banks of these countries for gauging the public sentiment on
inflation. The central banks are usually the major stakeholders and conduct the survey themselves
or by appointing an agency to conduct the survey for them. Some countries have more than one
such survey. The data are published by them on their websites and periodic articles on the subject
are brought out in their publications. There are several countries where private agencies, universities
or statistics offices conduct such surveys.
4. Section III presents the details on RBI’s Inflation Expectation Surveys of Households (IESH). It
provides details on the first report of the TACS, the recommendations it made, the follow-up of
recommendations and subsequent developments. To study the effect of RBI’s close examination
of the IESH data, the ISI team carried out quality checks on subsequent rounds of data. This
analysis for the later rounds of survey broadly indicated that the
-
inconsistency between responses to direct and indirect questions has reduced.
-
inconsistency between responses to different indirect questions has reduced.
-
standard deviation of responses to the direct question was reducing over time. The trend has
been arrested.
-
variation of average response from one city to another was observed. It was found that this
trend is consistent across cities.
-
too many investigators in some cities, too few in others – trend continues as in the past. Both
extremes are undesirable.
-
standard deviation of response to direct question was too small in some cities- there has
been some improvement. In the recent rounds this trend is not seen.
5. Section III also presents an exercise carried out by RBI on some additional characteristics of IESH data
6. Section IV presents the conclusion and recommendations. The major recommendations of the
survey are:
A. Releasing the survey results in public domain
-
In the context of monetary transparency, it is important that all the indicators related to
inflation and inflation expectations that are considered by the Reserve Bank are available
to the market. As the data of the last few rounds of Survey have high consistency, the
results may be placed in the public domain. A one-time article may be published giving
earlier survey results.
-
The Reserve Bank may also provide unit-level data to researchers and users with the
information that the survey results are internally more consistent from Round 12
onwards.
-
While releasing the survey results, the details of the concepts and methodology may
also be given by the Bank. This will encourage other agencies in India to take up similar
surveys.
-
The Reserve Bank should emphatically clarify that the IESH survey results are those of
the Households’ and not of the Reserve Bank of India. It also needs to be explained that
the inflation rate is as assessed by the respondents presumably based on their own
respective consumption baskets which need not necessarily reflect the inflation rate as
measured by any official price index series.
B. The questionnaire
- The survey schedule can be easily filled in by respondents with tick marks. It serves the
purpose well and is appropriate in the present context.
C. Logistic issues of the survey
-
One investigator may cover around 20 respondents of a city in a day.
-
It is necessary that the Bank continues with the recent practice of training of investigators
before launching each round of the survey.
-
The Bank should continuously monitor the genuineness of respondents and investigator
visits from the details provided by respondents in the questionnaire.
D. Further analysis of data
- There is a scope for additional analysis like testing the manner of expectations formation
once fairly long time series of survey results is available.
List of Acronyms
1ya |
One year ahead |
3ma |
Three month ahead |
B-CI |
Bootstrap Conficende Interval |
BER |
Bureau of Economic Research, South Africa |
BOE |
Bank Of England |
CPI |
Consumer Price Index |
CPI-IW |
Consumer Price Index for Industrial Workers |
DSIM |
Department of Statistics and Information Management |
IESH |
Inflation Expectation Survey of Households |
ANOVA |
Analysis of Variance |
RBNZ |
Reserve Bank of New Zealand |
SARB |
South African Reserve Bank |
TACS |
Technical Advisary Committee on Surveys |
Section I
Introduction
1.1 Inflation control is central to a good public
policy of which monetary policy is a critical
component. Price stability is one of the prime
objectives of monetary policy. Low stable inflation
and well-anchored inflation expectations also aid
in achieving the other two objectives of monetary
policy, namely, economic growth and financial
stability. Unstable inflation expectation cause
noise into the price system and makes long-term
financial planning more complex by undermining
public confidence in the economy and in the
management of economic policy, with potentially
adverse effects on risk-taking, investment, and
other productive activities that are sensitive to
the public’s assessments of the prospects for
future economic stability.
1.2 The state of inflation expectations greatly
influences actual inflation and thus the central
bank’s ability to achieve price stability. Central
Banks pursue the objective of anchoring inflation
expectations. Well-anchored inflation
expectations are relatively insensitive to incoming
data, i.e., the long-run expectation of inflation of
public changes little, in a period witnessing
inflation that is higher than their long-run
expectation. If, on the other hand, the public
reacts to a short period of higher-than-expected
inflation by marking up their long-run
expectation considerably, then expectations are
poorly anchored. In a market economy, employees
are concerned with the purchasing power of their
earnings, and bargain their nominal pay
accordingly since higher prices reduce real
spending power. If inflation is expected to be
persistently higher, employees may seek higher
nominal wages, which could in turn lead to
upward pressure on companies’ output prices
and, hence, higher consumer prices. Inflation
expectations of producers also affect inflation
directly by influencing their pricing setting
behaviour. If the business sector expects higher
generalised inflation in future, it would believe
that prices of products can be increased without
suffering a drop in their demand.
1.3 India has a rich history of collection of price
data and release of price indices. The index of
Indian prices was compiled and released on a
regular basis since 1861 giving inflation rates based
on domestic price index at major group levels along
with export and import price indices. The weekly
Wholesale Price Index (WPI) is being compiled
uninterruptedly since 1939 and provides rich and
detailed data for monitoring of inflation at
aggregate as well as at disaggregated levels. The
consumer price inflation is estimated based on
consumer price index (CPI) for four population
groups, viz., industrial workers, urban non-manual
employees, agricultural labourers and rural
labourers, of which the first one is used for wage
indexation in the organised sector. Inflation rates
based on all the official price indices are keenly
watched by public authorities for taking measures
relating to supply and demand management. While
these inflation measures reflect the past (observed)
inflation, additional information on the perceived
changes in inflation expectations is considered a
prerequisite in a forward-looking framework of
monetary policy analysis.
1.4 It is essential for the effectiveness of
monetary policy that inflation expectations
remain anchored to the target range. Good
estimates of inflation expectations, and
understanding what influences them, are
therefore important for successful monetary
policy. Most of the central banks, which have
adopted inflation targeting as an objective of
monetary policy and a few other central banks,
which have not adopted inflation as an objective
of monetary policy are conducting inflation
expectation surveys regularly. The results of
inflation surveys are mainly used in two ways,
namely for inflation forecasts and to evaluate
their policies adopted in controlling inflation.
I.1 Formation of TACS
1.5 In a bid to keep a tab on changes in
household expectation of prices across different population groups in major cities of the country,
the Reserve Bank has been conducting quarterly
survey on inflation expectations of households
(IESH) since 2005.
1.6 The survey findings are presented every
quarter in the Monetary Policy Strategy meeting
and the highlights of the survey are presented in
the quarterly meetings of the Technical Advisory
Committee on Monetary Policy (TACMP). In the
seventh meeting of the TAC on Monetary Policy
held in January 2007, a member pointed to the
divergence between the results of the IE survey
and price movements reflected in official price
indices. In view of its highly sensitive nature,
before making the survey results public, it was
considered critical to be assured of its
methodological aspects, quality and consistency
even though it in no way represents the views of
the Reserve Bank. Subsequently in March 2007, a
Technical Advisory Committee on Surveys (TACS)
was constituted by the Reserve Bank under the
chairmanship of Dr. Rakesh Mohan, Deputy
Governor to review the methodology and examine
the data quality of various rounds of survey. The
composition of the TACS, both initial and current,
is given in Annex–I.
1.7 For more than a year and a half, the TACS
has examined the IESH data including those
collected in the rounds conducted before the
TACS constitution. It made several
recommendations on improving the data quality
and consistency and unit-level data from survey
rounds conducted after implementation of those
recommendations were also examined during
this period. This report presents the
developments over this period, the findings and
the recommendations of the Committee
including those on placing the survey results in
public domain.
I.2 Organisation of the Report
1.8 This Report is organised into four
sections. Section II presents theoretical
background and the international experience
on inflation expectation measurement
including those based on surveys. Section III
presents the Inflation Expectation survey of
the Reserve Bank, the findings of first TACS
report, further analysis of IESH data and their
consistency with other inflation measurement.
The concluding Section IV presents the findings
and recommendations of the Committee.
Section II
Inflation Expectation – Theory, Measurement issue
and
International Experience
II.1 Theory and Measurement
2.1 Economic agents base their current
demand and supply decisions based on their
current and expected future income as well as
their expectations on future inflation rates.
Economic transactions are determined by the
subjective distribution of expected inflation rates
across agents and, from a macroeconomic point
of view, the magnitude of their converged
inflation expectations is critical
2.2 The changes in inflation expectations are
associated with business cycle analysis and supply
shocks. As per the “natural rate hypothesis”
(Friedman–Phelps), inflation will affect output
and unemployment only to the extent it is
unexpected and to that extent the process of formation of inflation expectations is extremely
important. On the other hand, the steady state
path of inflationary expectations constitutes the
difference between the nominal interest rate
(influencing money demand) and the real interest
rate (influencing capital accumulation decision)
thereby influencing allocations of resources in an
economy. Friedman (1969) argued that since there
are virtually no resource costs of creating fiat
money, overall efficiency requires a rate of
expected inflation that drives the opportunity
cost of holding money to zero and thereby satiates
agents with real money balances. Until the mid-
1970s, it was generally believed expectations
formation was based on adaptive expectations
which make each period’s change in expectational
variable proportional to the most recent expectational error. Such specifications allowed
occurrence of costly repeated systemic
expectational errors which were addressed under
the rational expectations hypothesis which
assumed economic agents expectational errors are
independent over time with all elements of his
information set.
2.3 There are various measures of inflation
expectations, survey measures, and financial
market measures. Internationally, the two main
survey measures are the European Commission
qualitative survey of European consumers, a
monthly series, and the ECB’s own survey of
professional forecasters. Whether survey measures
of inflation expectations are a good representation
of true scenario or not is a debatable point. They
often do not track well with actual inflation rates.
Indeed, survey measures of inflation expectations
often tend to track better with current or past
inflation than with future inflation, raising
questions as to their usefulness as proxies for true
expectations. However survey data generally
provide very useful directional information
regarding near-term inflationary pressures and can
be used to supplement other economic indicators,
giving a better indication of future inflation.
2.4 As regards financial market measures,
prices of index-linked financial securities provide
market-based measures of inflation expectations
and attitudes to inflation risk. In the United Kingdom, ‘breakeven’ inflation rates derived from
index-linked and conventional gilts reflect
investors’ forecasts of future inflation, and also
act as a barometer of monetary policy credibility.
A more favourable market-based indicator is the
inflation-linked swaps, in which agents trade their
inflation expectations more directly. Implied
breakeven inflation rates are a useful alternative
to surveys and econometric forecasts. In times
of fairly stable inflation, measures of inflation
expectation are all very close to actual inflation.
II.2 International Experience
2.5 Most of the central banks, which have
adopted inflation targeting as an objective of
monetary policy are conducting inflation
expectation surveys regularly, while a few other
central banks, which have not adopted inflation
targeting are also collecting information on
inflation expectations through surveys. The
results of these surveys are mainly used for
gauging changes in expectations and to evaluate
their policies adopted for controlling inflation.
2.6 A summary of the inflation expectation
surveys conducted in other major countries is
provided in Table 2.1 with more details given in
Annex-II. The review shows that the information
on inflation expectation is either collected through
dedicated Inflation Expectation Survey or by
adding questions about inflation and other related parameters in Consumer Expectation/Consumer
Confidence Survey. The periodicity of these
surveys is either monthly or quarterly and the
target respondent group of the survey is usually
households. The surveys are conducted either
through face-to-face telephonic interviews or
through postal questionnaires. Most of the surveys
attempt to elicit information on expected inflation
figures along with the directional change in prices.
Central bank involved in the conduct of such
surveys release the survey results through their
website and periodic articles on the subject are also
brought out in their publications.
Table 2.1: Inflation Expectation Survey of different countries |
Name of the Country |
Name of the Agency conducting Inflation Expectation Survey |
Frequency of the Survey |
Sample Size |
Australia |
Melbourne Institute of Applied Economic &
Social Research |
Monthly |
1200 (5000 are approached) |
United States |
1. University Michigan |
Monthly |
500 households |
|
2. Conference Board, New York |
Monthly |
5000 households |
United Kingdom |
A consumer research agency GfK/NOP |
Quarterly |
2000 in May/Aug/Nov and 4000 in Feb |
New Zealand |
A market research company sponsered by RBNZ |
Monthly |
Randomly selected 1000 households |
Sweden |
National Institute of Economic Research of
Sweden |
Monthly |
Randomly selected 1500 households |
South Africa |
Bureau of Economic Research (BER) |
Quarterly |
Area-stratified 2500 households |
Czech Republic |
Czech National Bank |
Quarterly |
Randomly selected sample of 600
households |
Indonesia |
Central bank of Indonesia |
Monthly |
Randomly selected sample of more
than 4300 households |
2.7 While some countries collect the inflation
expectations as a number reported by the
respondents (e.g. Australia), there are others that
capture the information in class intervals. When
class intervals are used, the range of classes are
usually centred around their target inflation rate
(e.g. United Kingdom). The Bank of England (BoE)
in addition to seeking inflation expectations also
seeks public’s attitude to interest rates and monetary policy and satisfaction with the BoE.
Interestingly, in the wake of sharp increase in
inflation during 2008, the BoE survey gave option
to the respondents to indicate their perception
outside the given range to capture the maximum
variation while maintaining dynamic comparison
across rounds.
2.8 Thus, households’ inflation expectation
are critical inputs for central banks and other
public agencies for gauging the public sentiment
on inflation, for monitoring of the level of
anchoring in inflation expectations and,
consequently, for their own performance. Surveys
are an important source of information in this
regard. The central banks are usually the major
stakeholders and conduct the survey themselves
or by appointing an agency to conduct the survey
for them. Some countries have more than one
such survey. There are several countries where
private agencies, academic/research institutions
or statistics offices conduct such surveys. The
survey results are generally released to the public.
Section III
Reserve Bank’s Inflation Expectations Survey of Households
3.1 The Reserve Bank of India has been
conducting the quarterly survey of inflation
expectations of households since September 2005.
The survey is being conducted with an endeavour
for further improvement in information base used
by the Bank for decision making towards meeting
the objective of price stability. The first two rounds
of the survey were qualitative and contained
questions on changes in price expectations of
households in relation to the prevailing inflation
rate. In addition to expectations on general prices,
expectations on prices of food products, non-food
products, household durables, housing and
services were also collected. The respondent
categories include financial sector employees,
other employees, self-employed, housewives,
retired persons, daily workers and others. The
survey also collected respondents’ details like
name, gender, age and contact details.
3.2 From the third round onwards, additional
questions on expected rate of inflation over the next three months and next one year were also
asked. In September 2007, from the ninth round
of the survey, a question on the respondents’
perception of the prevailing inflation rate was also
added. The initial rounds of the survey kept equal
representation of each category though the
individual respondents keep changing across the
survey rounds. From September 2008, the
representation of different groups was changed,
increasing the representation of “Housewife” and
“Self-employed” persons and reducing those of
the ‘Others’ category.
3.3 The survey is conducted in four metros
and eight other major cities. The metros and other
cities are chosen such that there are three cities
from each of the four zones (North, South, East
and West). While metros are represented by 500
households each, 250 households each are
selected from other cities. The final sample is of
4000 households in each round of the survey. The
sample is chosen randomly so as to cover the city uniformly. For each survey round, different areas
of cities are chosen.
3.4 The survey is conducted by the
Department of Statistics and Information
Management (DSIM) of the Reserve Bank. An
Inter-Departmental Standing Committee with a
Chairman from DSIM and members from DSIM
and user departments, viz., the Monetary Policy
Department (MPD) and the Department of
Economic Analysis (DEAP) monitors the technical
aspects of the survey.
3.5 In the first meeting of the TACS held in
April 2007, it was decided that Indian Statistical
Institute (ISI), Kolkata will examine the survey
methodology and look at the unit level data of
the IE survey rounds for the four quarters of 2006.
The objectives of the evaluation were to test
consistency of data and to explore the scope of
its analysis; to identify causes of anomaly, if any;
and to make suggestions for improvements of the
survey, based on the empirical investigation.
III.1 First Report of TACS
Findings
3.6 The findings of the ISI team were discussed
in the 2nd
meeting of the TACS in June 2007. These
were also included the first report submitted by
TACS in July 2007 to the Reserve Bank which
contained the following major findings:
3.6.1 Multivariate Analysis of Variance
(MANOVA) carried out with ‘gender’, ‘category’
and ‘city’ as factors indicated that city is the
largest source of variation in each round of the
IE survey.
3.6.2 There was very low standard deviation
reported by some investigators, but mostly
investigators reported variation.
3.6.3 It was found that most of the respondents
gave quantitative responses on their expectation
of inflation in the next quarter/year and the
percentage of those who responded “don’t know”
was very low. Moreover, the share of “don’t know”
in 1-year horizon was more than that for the 3-
month horizon which appears logical and
internally consistent.
3.6.4 A consistency index was compiled for
September and December 2006 for each city and
category quarter surveys separately to check if
there was any evidence of lack of consistency
between the direct question on rate of inflation
and the indirect question on change in rate of
price. The analysis revealed some lack of
consistency prevailing across all cities and all
respondent categories. It also pointed out that
there was a possibility that the direct question
may have been misunderstood, as also some
indirect questions. It was found that no category
of respondents gave near-perfect and consistent
answer.
3.6.5 In order to examine whether the
respondents understood the indirect question
correctly or not, a Consistency Index was
constructed. It was observed that, as desired, the
distribution of observations around the centre
was heavy and only 7.3 per cent responses were
on the extreme values indicating that the
qualitative responses are broadly reliable.
Recommendations
3.7 The following recommendations were
made in the report:
3.7.1 On the Survey:
3.7.1.1 Considering the very large population size,
adding one or two more cities in each zone will
further improve the data quality.
3.7.1.2 As more rounds of surveys are conducted,
there would be scope for additional useful analysis
like testing the manner of expectations formation.
3.7.1.3 The instances of low standard deviation
in case of few investigators to be treated with
proper training of investigators.
3.7.1.4 The investigators should be trained to
seek true perceptions from respondents and
provide clarifications, if required, in simple terms
without leading to any specific response.
3.7.1.5 There is a need for random checking of a
few respondents (say 3 to 5 per cent) in each city
through personal visits by the Reserve Bank’s staff
to ensure the quality of data.
3.7.2 On the Questionnaire :
3.7.2.1 The option of “Don’t know” may be added
in the qualitative part of the questionnaire.
3.7.2.2 A question on the rate of inflation
prevailing three months ago may be added to be
used as a concomitant variable for further analysis
of data.
3.7.2.3 To club all the indirect (qualitative)
questions together, followed by the direct
(quantitative) questions.
Follow up of TACS Recommendations
3.8 As suggested by the TACS, the survey
schedule was modified to club all the quantitative
questions in one block and place them after the
qualitative block and pre-launch training of
investigators was started. The investigators were
sensitised about the purpose for which the survey
was being conducted. They were told not to guide/
prompt the respondent or use any technical term.
They were briefed about the inconsistencies.
3.9 To conduct training before each round of
survey, and to keep the training uniform across
the country, the specialised officers from the
Regional Offices of DSIM were associated with
the job of imparting the training to investigators
at regional level in the future rounds of surveys.
The Regional Offices were involved in conducting
the survey not only by training of investigators
but also by conducting quality check of the data
(5 per cent each by field visit and phone calls).
Thus the surveys from March 2008 onwards are
being conducted with full involvement of the
Regional Offices.
3.10 It was decided not to add a “Don’t know”
option in the qualitative block. It was felt that if
a respondent is not able to answer about the price
movements for General or Food category, she/he
would not be interviewed any further in keeping
with the objective of the survey. Accordingly, such
respondents who have not idea on the subject are
not included in the survey and the schedule is
canvassed in another household to ensure that
the number of valid respondents does not go
much below the target of 4000. On the other hand, if a respondent is able to express his/her price
expectation for General and Food category, but
not for any of the other categories, then the
answer for those categories would not be insisted
on and such schedules will be included in the
survey.
Subsequent developments
3.11 The TACS met for the third time on March
12, 2008. The members were briefed about the
progress of the survey and the issue of placing
the results of the survey in public domain was
discussed in detail. The Committee reviewed the
actions taken by RBI on the recommendations
made by TACS. It was decided to wait and watch
the quality of few more rounds of surveys after
the recommendations of the TACS were
implemented.
3.12 On the issue of increasing the sample size,
the Committee felt that since the headline
inflation is the only concern, present sample size
may be adequate and the sample size of such time
critical surveys cannot be too large. Meanwhile
emphasis was laid on uniform training at each
centre and monitoring data quality through field
visit and telephonic checks. Wherever the quality
was found unacceptable, the interviews were
asked to be redone. The remaining incidence of
inconsistency over the qualitative and
quantitative block was thought to be addressed
by emphasis on the same during the training to
investigators.
3.13 It was felt that after assurance on
methodological aspects of the IESH based on
validation of subsequent survey rounds, the
results could be published along with the
methodology/procedure of the survey, the
information about appointment of the TACS, its
findings and recommendations, the subsequent
action taken by the Reserve Bank and subsequent
reviews by TACS.
3.14 In the 12th Round the question on 3 month
back inflation was dropped as discussed with the
ISI team. In the 12th Round of survey in June 2008,
it was also found that more than 40 per cent
respondents had responded the inflation value more than 8 per cent, the highest bracket. As high
levels of inflation were prevailing in the economy
then, the brackets of the qualitative blocks were
extended to the right to capture the true variation
in the responses. For the 13th Round, the highest
class was made as ‘more than 16 per cent’ from
‘more than 8 per cent’ and the lowest class was
made ‘less than 4 per cent’ as against ‘less than
one per cent’ in earlier schedule. However, on a
review, to keep class width same as that of earlier
rounds, the brackets were again restructured,
making the smallest as ‘less than 1 per cent’ and
keeping the highest as ‘more than 16 per cent’.
Each class width was kept as 100 basis points. An
additional Round 13A was carried out in October
2008 with this set of brackets.
III.2 Further Analysis of data quality by ISI team
Internal consistency tests and other findings:
3.15 With close vigil on the data quality by the
Reserve Bank in the subsequent survey rounds,
further examination of survey data by the ISI
team revealed that inconsistencies were reducing
with new rounds of data (12th to 14th round). The
consistency of qualitative and quantitative blocks
has improved. The inter-consistency between
quantitative and qualitative blocks has also shown
improvement and the data is now nearly
consistent. The logistic checks on interviews
conducted per day, number of investigators used
and duration of survey also show stability.
3.16 The details of quality checks carried out
by the ISI team are given in the Annex-III. The
summary of the findings are as under:
3.16.1 Inconsistency between responses to direct
and indirect questions has reduced considerably;
3.16.2 Inconsistency between responses to
different indirect questions has reduced
considerably;
3.16.3 Standard deviation of response to direct
question which was reducing over time increased
in a period of high inflation;
3.16.4 Variation of average response from one
city to another was observed. It was found that
this trend is consistent across cities.
3.16.5 Non-uniform percentage of “Don’t know”
answers to direct question across cities and over
survey rounds. The trend continues and could
reflect possible difference in way in which the
investigator understands the question. It could
also possibly indicate that in periods of high
volatility in price movements, the respondents
are unsure of what the inflation could be 3 month
or one year down the line.
3.16.6 Three-month back inflation has as much
variation as three-month ahead inflation and its
presence did not serve much purpose. This
question was discontinued from September 2008
round. Some cities had more than required
number of investigators wheres there was more
load on investigators in some other cities. This
both extremes are undesirable. Incidentally, it
was also noted that in instances of too many
investigators, the count of investigator also
increased due to different spelling of
investigators’ name.
3.16.7 Wide variation was observed in the
duration of survey in different cities (pointing
towards different practice) continues. Further
investigations revealed that the centres where the
days taken appear to be too large are the centres
where a particular investigator’s lot was rejected
as none of his respondents could be reached. In
such cases the interviews are asked to be redone
at a later date and this increased the duration of
survey in such centres. Thus, by and large, the
survey data seems to be consistent on this
account also.
3.16.8 Standard deviation of response to direct
question was too small in some cities in earlier
rounds. There has been some improvement in the
recent rounds and this trend is not seen. In the
June 2008 round, this was reported as that was
the period when the inflation was reaching
double digits and the households’ responses got
clubbed in the largest bracket, thereby reducing
the standard deviation.
3.17 Based on their analysis, the ISI team noted
that the persistent efforts to improve the quality
of survey data are yielding results and that the
results can be put in public domain.
III.3 Characteristics of IESH results
3.18 The additional analysis of new rounds of
IESH data established good quality and high level
of internal consistency. In order to identify the
factors that explain the variations in responses
of households, an analysis of the variability in
households’ response is done.
Behaviour of mean expectations
3.19 The inflation expectation survey of
households measures perception on current
inflation and expectations for 3-month ahead and
1-year ahead. The movement in these numbers
over years, as seen from the table below, shows
that the average perception of the households on
the current rate has, throughout the survey
history, been lower than the 3-month ahead
expectations (with an exception of the December
2008 quarter) which are lower than the 1-year
ahead expectation. Thus whether it is a low
inflation environment or high inflation
environment, households’ believe that the
inflation in near future will be a shade higher
than the prevailing rate.
Deviation from central tendencies:
3.20 During 2007-08, the headline WPI
inflation was stable and remained on an average
around 5 per cent. The IESH rounds carried out
during this period yielded stable inflation
numbers, with low variation. When in 2008-09,
there was a surge in inflation, the volatility in
the response also increased as there was
divergence in respondents’ expectation about
inflation. We can see the variation in the three
inflation numbers in the Chart 3.1.
Quality of estimates
3.21 The confidence intervals worked out using
bootstrap resampling yields narrow confidence
intervals of around 20 to 30 basis points. The size
of the confidence intervals increases with the
time horizon, indicating that the respondents are
more coherent on their perception of the current
inflation than their expectation of near future.
This also shows that the estimates of households’
inflation expectations are of good quality. It can
also be inferred from here that if the requirement
for monetary policy is for a headline inflation
expectation, than the present sample size of 4000
respondents covering different regions of the
country is sufficient. However, if the intention
is to get a regional flavour of inflation
expectation or a measure at disaggregated level
of a factor (age, category, etc), then the survey
coverage could be extended by adding more cities
or increase the respondents in those factors.
Table 3.2: Bootstrap Confidence Interval for Households’ Inflation |
Period |
Round 13a |
Round 14 |
Round 15 |
99% B-CI for Mean |
Interval width |
99% B-CI for Mean |
Interval width |
99% B-CI for Mean |
Interval width |
Current |
11.18-11.35 |
0.17 |
9.24-9.40 |
0.16 |
5.14-5.31 |
0.17 |
3 month ahead |
11.44-11.71 |
0.27 |
8.77-9.05 |
0.28 |
5.21-5.42 |
0.21 |
1 year ahead |
12.28-12.58 |
0.30 |
9.47-9.80 |
0.33 |
6.08-6.30 |
0.52 |
Factors explaining volatility in Households’
expectations
3.22 The total variability in responses is
explained by different factors over different
rounds. An analysis of variance carried out over
different rounds of data revealed that city has
been a significant source of variation in all rounds
(Annex IV). City is expected to cause divergence
in inflation expectations as the basket of
consumption usually varies with city. Moreover
different regions may be surplus or deficit in
different products and the prices of these
products may vary over regions. Free movements
of goods may be bringing some uniformity in
prices after adjusting for transportation costs, etc.;
however there may be some lags in bringing about
this homogeny. An analysis of city-wise data for
the official consumer price index for industrial
workers confirms similar wide divergence in
inflation across cities. Detailed table of the
analysis are presented in Annex-V.
Table 3.3: Factors that explain the total variability |
Round |
Current |
3 month ahead |
1 year ahead |
12 |
City, Age, Category |
City, Age, Category |
City, Age |
13 |
City |
City, Age, Category |
City, Age |
13a |
City |
City |
City |
14 |
City, Gender, Age |
City, Gender, Category |
City, Category |
15 |
City, Category |
City, Gender, Category |
City, Category |
Source: Anova outputs |
Product-wise price expectations
3.23 The price expectation, according to
different product groups, shows that highest
proportion of respondents expect price rise for
the food products, both for the next quarter and
next year. This trend has been observed so for a
larger part of the survey history. In the official
indices as well, the food-inflation has remained high in the last two years and the household price
expectations were in tune with the actual prices
movements prevailing in the economy. Similarly,
the price expectations for household durables
remained at the lowest among all product groups,
mapping the movements of the inflation of the
manufactured product group in WPI. The charts
3.2 and 3.3 show these movements for 3 month
ahead and 1 year ahead periods.
Section IV
Conclusion and Recommendations
4.1 Based on the examination of the survey
methodology and findings of the above analysis,
and drawing from the international experience,
the following recommendations are offered:
4.1.1 The quarterly Inflation Expectations
Survey of Households (IESH) measures changes
in consumers’ inflation expectations in the
economy which is critical for monetary policy.
Technical audit of the methodological aspects and
consistency of such a critical survey is a right
approach. Such an evaluation of survey results is
one of the first of its kind in India.
4.1.2 Given the objective of timeliness of this
survey, it is recognised that the survey is
conducted nation-wide in a very short time span.
The availability of time is even shorter for data
scrutiny, processing, tabulation and analysis of
results. Time-criticality becomes an overriding
constraint for this policy survey.
4.1.3 It is found that local conditions and
consumption patterns are the major sources of
variation in differing inflation expectations across
various centres. Accordingly, cities are the largest
source of variations. This comes as no surprise
and is consistent with the city-wise divergence
in inflation based on the official CPI series. The
trend in responses is found to be similar across
all categories of respondents.
4.1.4 Based on this Committee’s earlier report
on Survey Methodology and Data Quality of the
Survey (July 2007), several measures have been
taken by the Reserve Bank for training of
investigators and follow up with respondents.
There has been considerable improvement in
consistency of survey results due to these measures.
4.1.5 The present survey schedule does not
include any leading question guide to the
respondents on responses in any specific
direction. Investigators should be regularly
sensitized to seek true perceptions from
respondents so that they do not guide the
respondents in filling in the schedule.
Investigators can provide clarifications in simple terms (not through technical explanation) if the
meanings of some economic terms are required
to be explained.
4.1.6 It is necessary that the Reserve Bank
continues with the recent practice of training of
investigators before launching each round of the
survey. Training should ensure that investigators
are adequately sensitised, they understand the
survey questions correctly and are told ways to
ask certain questions in simple language. A
manual on training should be prepared for the
purpose.
4.1.7 The survey schedule can be easily filled
in by respondents with tick marks. It serves the
purpose well and is appropriate in the present
context.
4.1.8 While the survey does not have a fixed
sample frame, it needs to be recognised that price
expectations move in similar direction for a
majority of population and a sample of different
set of individuals in each round would be able to
capture the expectations closely.
4.1.9 Allotting less time to an investigator for
canvassing schedule would put pressure on them
and result in a hasty job. At the same time, care
should be taken that investigators do not spend
too much time with a respondent and possibly
influence his answers. Also, the survey is timebound
and the fieldwork is required to be
completed within a short time span of a fortnight.
It is proposed that one investigator may cover
around 20 respondents of a city in a day.
4.1.10 The Reserve Bank should continuously
monitor the genuineness of respondents and
investigator visits from the details provided by
respondents in the questionnaire. This would be
akin to a follow-up survey.
4.1.11 In the context of monetary transparency,
it is important that all the indicators related to
inflation and inflation expectations that are
considered by the Reserve Bank are available to
the market. As the data of the last few rounds of Survey has high consistency, the results may be
placed in public domain. A one-time article may
be published giving earlier survey results.
4.1.12 The Reserve Bank may also provide unitlevel
data to researchers and users with the
information that the survey results are internally
more consistent from Round 12 onwards. There
is a scope for additional useful analysis like
testing the manner of expectations formation
once fairly long time series of survey results are
available.
4.1.13 In India, exclusive inflation expectation
survey of households is conducted only by the
Reserve Bank. When releasing the survey results,
the details of the concepts and methodology may
also be given by the Bank, it will be interesting to
see other agencies in India take up similar
surveys. It would be good if more public and
research agencies conduct such surveys and their
results are shared, similar to the business
expectation surveys conducted by several
agencies. Other agencies surveys could cover
general population and also the areas not covered
by the RBI survey like the non-capital cities, the rural India, and other population groups. This
would aid further economic analysis.
4.1.14 There is always an issue in release of
inflation expectation data by the central bank as
it could be seen as self-fulfilling prophecy. It is
important to distinguish between the inflation
projection given by the Reserve Bank for policy
purposes and the inflation expectation of
households. The Reserve Bank should
emphatically clarify that the IESH survey results
are those of the respondents and are not
necessarily shared by the Reserve Bank. It also
needs to be explained that the inflation rate is as
assessed by the respondents based on household
consumption basket which need not be related
with inflation rate as measured by any official
price index series.
4.2 Given the objective and focus of the
survey and the criticality of timeliness of its
results, the ISI study team was appreciative of the
short survey questionnaire which could be
processed quickly for getting desired analysis. The
persistent effort to improve the quality of survey
data is yielding results.
Annex-I
Constitution of TACS
The present constitution of the Technical Advisory Committee on Surveys is as under:
Dr. Rakesh Mohan
Deputy Governor
Reserve Bank of India (upto June 10, 2009)
Distinguished Visiting Professor
Stanford University
USA |
Chairman |
Shri Deepak Mohanty
Reserve Bank of India |
Vice Chairman |
Prof. D.M. Nachne,
Indira Gandhi Institute for Development Research, Mumbai
Prof. Bimal Roy,
Indian Statistical Institute, Kolkata
Shri Gaurav Kapur,
Senior Economist ABN AMRO Bank, Mumbai
Smt. Yashika Singh,
Chief Economist, Dun & Bradstreet, Mumbai
|
External Experts |
Prof. Shibdas Bandopadhyay
Indian Statistical Institute, Kolkata
Prof. Debasis Sengupta
Indian Statistical Institute, Kolkata
|
Special Invitees |
Dr. Amal Kanti Ray, Principal Adviser (upto August 31, 2009)
Deptt. of Statistics and Information Management, RBI
Dr. Janak Raj, Adviser-in-Charge
Monetary Policy Department, RBI
Shri Pardeep Maria, Adviser
Deptt. of Statistics and Information Management, RBI
Shri K.U.B. Rao, Adviser
Deptt. of Economic Analysis and Policy, RBI
Dr. O.P. Mall, Director
Monetary Policy Department, RBI
|
Internal Members |
Smt. S. Augustine, Director, DSIM
Deptt. of Statistics and Information Management, RBI |
Convenor |
The initial constitution of TACS as it was constituted in 2007 was as below: |
Dr. Rakesh Mohan, Deputy Governor |
Chairman |
Dr. R.B. Barman, Executive Director |
Vice Chairman |
Prof. D.M. Nachne, IGIDR
Prof. Bimal Roy, ISI Kolkata
Shri Gaurav Kapur, ABN AMRO
Smt. Yashika Singh, Dun & Bradstreet |
External Experts |
Dr. Amal Kanti Ray, O-in-C, DSIM
Dr. Michael Patra, Adviser-in-Charge, MPD
Dr. Janak Raj, Adviser, DEAP
Dr. O.P. Mall, Director, MPD |
Internal Members |
Dr. C.L. Agarwal, Director, DSIM |
Convenor |
Annex-II
Review of International Practice- Select countries
Country/Bank |
1. |
Australia/ Reserve Bank of Australia |
Name of the Survey |
|
Melbourne Institute Survey of Consumer Inflationary Expectations |
Periodicity |
|
Monthly |
History of Survey |
|
Quarterly since March 1973 & monthly since December 1986 |
Target Respondents |
|
Households |
Sample size |
|
Stratified random sample of 1200 respondents (5000 respondents approached) |
Conduct of survey |
|
Conducted not by RBA but independently by the Melbourne Institute of Applied Economic and Social Research |
Questions asked |
|
In next one year, the economic conditions, employment conditions, price changes, rate of price changes, wage changes |
Dissemination of Information |
|
Priced publication of the Melbourne Institute |
Country/Bank |
2a. |
United States of America |
Name of the Survey |
|
Survey on consumer sentiment |
Periodicity |
|
Monthly |
History of Survey |
|
Since 1997 |
Target Respondents |
|
Households |
Sample size |
|
500 American Households |
Conduct of survey |
|
By University of Michigan |
Questions asked |
|
By how much do you expect the conumer price index (CPI) to increase over the next year and over the next 5 to 10 years |
Dissemination of Information |
|
By the University |
Country/Bank |
2b. |
United States of America |
Name of the Survey |
|
Consumer confidence survey |
Periodicity |
|
Monthly |
History of Survey |
|
Consumer confidence index since 1967 |
Target Respondents |
|
Households |
Sample size |
|
5000 US Households |
Conduct of survey |
|
For the Conference Board by TNS, a customer research company) |
Questions asked |
|
Questions are asked on both current conditions and expectations |
Dissemination of Information |
|
– |
Country/Bank |
3. |
United Kingdom: Bank of England |
Name of the Survey |
|
GfK/NOP Bank of England Public Attitudes towards Inflation |
Periodicity |
|
Quarterly |
History of Survey |
|
Since 2000 |
Target Respondents |
|
Households |
Sample size |
|
2000 in May/Aug/Nov and 4000 in Feb |
Conduct of survey |
|
Conducted jointly with an agency called GfK/NOP |
Questions asked |
|
Inflation- current/ 1 year ahead; movements in interest rates; satisfaction on conduct of Monetary Policy by Bank of England |
Dissemination of Information |
|
Every quarter, release of summary & detailed data with a brief writeup on website and an article in Quarterly Bulletin once a year |
Country/Bank |
4. |
New Zealand: Reserve Bank of New Zealand |
Name of the Survey |
|
Household inflation expectation survey |
Periodicity |
|
Quarterly |
History of Survey |
|
Since 1995 |
Target Respondents |
|
Households |
Sample size |
|
750-1000 |
Conduct of survey |
|
Telephonic, by sponsoring a market research company |
Questions asked |
|
Current inflation perceptions, Expected change (12 month), Expected inflation (12 month) |
Dissemination of Information |
|
Key results published on RBNZ website at the end of second month of refernce quarter as per an advance release calendar. |
Country/Bank |
5. |
Sweden, RIKSBANK |
Name of the Survey |
|
Consumer tendency Survey (previously Household purchasing plans) |
Periodicity |
|
Monthly |
History of Survey |
|
1979 |
Target Respondents |
|
House holds |
Sample size |
|
1500 Swedish Households |
Conduct of survey |
|
National Institute of Economic Research, Sweden |
Questions asked |
|
Households are asked to state how many per cent they believe that ”prices in general” will rise over the coming 12 months. |
Dissemination of Information |
|
Published by RISKBANK on their website |
Country/Bank |
6. |
South Africa/ South African Reserve Bank |
Name of the Survey |
|
Inflation Expectation Survey |
Periodicity |
|
Quarterly |
History of Survey |
|
Since 2000 |
Target Respondents |
|
Households, Business Executives, Analysts and Labour. Design of households’ survey was separate |
Sample size |
|
2500 households using area-stratification |
Conduct of survey |
|
Dedicated quantitative survey by BER on behalf of SARB. For households personal interviews are conducted. |
Questions asked |
|
By how much do you expect prices in general to rise in 2001? (Last 5 years’ and last 1 year’s infaltion numbers are provided as an input to them.) |
Dissemination of Information |
|
– |
Country/Bank |
7. |
Czech Repoblic/Czech National Bank |
Name of the Survey |
|
Inflation Expectation Survey |
Periodicity |
|
Quarterly |
History of Survey |
|
Since 1999 |
Target Respondents |
|
Households (separate surveys for non-financial corporations and
financial markets) |
Sample size |
|
600 randomly chosen households |
Conduct of survey |
|
Market research agency-Ecoma Plus for households (by CNB for other
two surveys) |
Questions asked |
|
Expectation of year-on-year consumer price change in next 12
months & in next 36 months. |
Dissemination of Information |
|
Summary data released on their website |
Country/Bank |
8. |
Indonesia, Bank Indonesia |
Name of the Survey |
|
Consumer Expectation Survey |
Periodicity |
|
Monthly |
History of Survey |
|
Since 1999 |
Target Respondents |
|
Households |
Sample size |
|
4600 Households |
Conduct of survey |
|
Real Sector Statistics Team, Directorate of Economic and Monetary Statistics do data canvassing through telephonic interviews and direct visits in particular cities based on rotated system |
Questions asked |
|
Price and Income expectations, Expectations of Savings and interest rates, Economic conditions for the next 3 and 6 months |
Dissemination of Information |
|
Results are regularly published in the bulletin of the bank |
Annex-III
Findings of analysis of the latest rounds of
data by the ISI team
Background:
After the first meeting of the TACS, the ISI studied
the March to December 2006 data and identified
some problem areas. As suggested by ISI changes
were brought out in the questionnaire, briefing
of investigators was done and some logistic
adjustment was done.
The survey was constantly monitored and
subsequent analysis by ISI of the March to
December 2007 data showed that there were
improvements but some anomalies persisted. The
March 2008 survey had already been launched in
the meanwhile. The subsequent rounds of the
survey were conducted with joint efforts of DSIM
Regional Offices and Central Office. Training to
investigators and trainers was provided by the ISI
team at two centres. Later the training of
investigators was made uniform across all
Regional Office, quality checks were put in place
and 10 per cent of the data was subject to scrutiny,
5 per cent by field visit and another 5 per cent by
telephonic checks. The agency was asked to
conduct repeat interviews if some schedules were
identified as inconsistent.
The data for the rounds 12 to 14 were sent to ISI
to carry out the further analysis of quality and
compare the findings with those of the earlier
rounds and to determine is the data are ready for
placement in the public domain. The findings of
the analysis are detailed below:
A. Consistency of response to qualitative
question
In the quantitative block, the respondents are
asked about their expectations on the price
movements in the next 3 months and in next one
year. These expectations are sought for General
prices and also for its breakup into Food products,
Non-food products, Household durables, Housing
and Services.
To check the consistency of data reported through
this block, an indicator is worked out as under:
-
Define consistency index of 3-month ahead
price query as
(Number of categories in which perceived
price rise is more than perceived price rise
in General category)
minus (Number of categories in which
perceived price rise is less than perceived
price rise in General category)
-
Consistency index of 3-month ahead price
query
-
is between -5 and 5;
-
should ideally be around 0;
-
is 5 when General price rise is less than price
rise in all categories;
-
is -5 when General price rise is more than
price rise in all categories.
The three month ahead consistency indices for
the surveys carried out in 2006 and in 2008 are
given in the table below
Survey |
Consistency index |
Total count |
Extreme |
Border line |
-5 |
-4 |
-3 |
-2 |
-1 |
0 |
1 |
2 |
3 |
4 |
5 |
Mar-06 |
58 |
148 |
375 |
391 |
382 |
539 |
414 |
484 |
470 |
462 |
272 |
3995 |
8.3% |
23.5% |
Jun-06 |
129 |
260 |
322 |
292 |
273 |
463 |
400 |
551 |
511 |
590 |
197 |
3988 |
8.2% |
29.5% |
Sep-06 |
114 |
159 |
224 |
304 |
239 |
843 |
625 |
627 |
525 |
222 |
108 |
3990 |
5.6% |
15.1% |
Dec-06 |
148 |
152 |
344 |
314 |
347 |
766 |
585 |
530 |
445 |
207 |
132 |
3970 |
7.1% |
16.1% |
Mar-08 |
51 |
60 |
136 |
334 |
297 |
686 |
640 |
729 |
689 |
296 |
80 |
3998 |
3.3% |
12.2% |
Jun-08 |
12 |
5 |
54 |
207 |
267 |
1160 |
845 |
1100 |
291 |
56 |
3 |
4000 |
0.4% |
1.9% |
Sep-08 |
0 |
3 |
33 |
257 |
242 |
1286 |
894 |
1122 |
158 |
4 |
1 |
4000 |
0.0% |
0.2% |
Sep-08A |
0 |
0 |
27 |
138 |
244 |
1149 |
1241 |
1098 |
103 |
0 |
0 |
4000 |
0.0% |
0.0% |
Dec-08 |
12 |
5 |
54 |
207 |
267 |
1160 |
845 |
1100 |
291 |
56 |
3 |
4000 |
0.4% |
1.9% |
The extreme values are the consistency index
values of -5 or 5. It is seen that the percentage of
inconsistence response was steadily high in 2006
but has significantly improved in 2008. This
establishes that the quality of responses has
markedly improved.
B. Consistency of response to quantitative question
The consistency of responses to the quantitative
question is looked at from various angles. While
checking the standard deviation of 3 month and
a year ahead, it was noticed in the surveys of 2006
that the standard deviation had reduced across
the four survey rounds. The following subsections
describe the of quantitative responses
for the 2008 data.
1. Standard deviation over time
The declines in standard deviations as noticed in
the 2006 rounds have been arrested as can be seen
from the table below.
The low standard deviation for June 2008 Round
was low due to a different reason. June 2008 was
a period of global price shock and inflation was
rising sharply and was nearing double digits in
India. The households’ inflation expectations too
may have increased as they were facing periods
of high inflation. However the highest bracket to
capture the inflation was ‘more than 8%’. The
responses really intended to be 9 or above may
have got coded here. More than 44% responses
for 3 month and more than 55% responses for a year ahead got reported in this bracket. This
reduced the standard deviation in the month of
June 2008.
Survey round |
Mean |
Standard deviation |
Mar-06 |
4.0 |
2.1 |
Jun-06 |
4.9 |
2.1 |
Sep-06 |
5.6 |
1.8 |
Dec-06 |
5.8 |
1.6 |
Mar-07 |
6.3 |
1.5 |
Jun-07 |
6.5 |
1.2 |
Sep-07 |
6.0 |
1.6 |
Dec-07 |
5.9 |
1.5 |
Mar-08 |
6.3 |
1.5 |
Jun-08 |
7.9 |
1.2 |
Sep-08 |
13.5 |
3.0 |
Sep-08A |
12.4 |
3.6 |
Dec-08 |
9.6 |
3.9 |
The schedule was modified after the June 2008
Round and the highest bracket was made ‘more
than 16%’. In September 2008 two sets of brackets
were used one with 8 classes of 200 basis points
width (schedule was modified in consultation
with the members of TACS) and the other with
17 classes with width of 100 basis points. These
rounds are referred to as Sep-08 and Sep-08A
round (conducted in October 2008). The
questionnaire of Sep-08A Round has been used
in the subsequent rounds as well.
The table shows that the standard deviation is
high in the period after June 2008. This depicts
the volatility present in the households’
expectations as the actual economy was also
seeing sharp changes in price movements. Thus
on this count as well the quality check results are
comforting on the data quality.
2. Behaviour across cities
The city-to-city mean value of one-year ahead
inflation expectation as shown in the following
graph, looks haphazard. While in one round one
city records least variation, in the other round it is
a different city. Similar behaviour is seen in the CPI centre-wise data, where no city consistently
records low or high variation. This finding thus
shows a desirable attribute of the survey data.
The standard deviations across cities also shows
similar behaviour as the following graph shows.
ISI has raised concern on too little variation in
some cities. The low variation recorded in Patna
and New Delhi during June 2008 represents the
high sentiment that prevailed during that period
which got clubbed in the last bracket, causing
low standard deviation.
The variation in the latest rounds for the cities
shows that in this aspect also the survey numbers
are plausible.
3. ‘Don’t know’ responses
The ‘Don’t know’ responses in the current rounds
are not uniform. The ISI analysis points out that
more ‘Don’t know’ answers are beginning to
show.
Few cities produce no ‘Don’t know’ answers. Too
few Sep-08 ‘Don’t know’ answers may have been
prompted by high inflation prevailing then.
C. Inter-consistency between response to
qualitative and quantitative questions
To check the inter-consistency between the
qualitative and the quantitative blocks, the
variables X and Y are defined as under:
Define X equal to
-
A, if general prices will increase faster after 1 year;
-
B, if general prices will increase at current rate
after 1 year;
-
C, if general prices will increase slower after 1
year;
-
D, if general prices will stay the same or
decline.
-
E, if general prices response is not available.
Define Y equal to
-
A, if 1 year ahead inflation > current inflation
(neither response is “don’t know”);
-
B, if 1 year ahead inflation = current inflation
> 0-1 (neither response is “don’t know”);
-
C, if 0-1 < 1 year ahead inflation < current
inflation, (neither response is “don’t know”);
-
D, if 1 year ahead inflation is reported as 0-1;
-
E, if none of the above conditions hold.
Now a consistency index of a group of survey
response is defined as
(Number of times X is equal to Y) * 100 / (Number
of times X or Y is not equal to E)
The consistency index should be 100 if X and Y are perfectly consistent; should have a lesser value
(that can be calculated for a given cross-tabulation) if X and Y are completely independent.
1. Consistency Index
The consistency indices worked out for various rounds of surveys according to city and category are
presented below
Cities |
Mar’08 |
Jun’08 |
Sep’08 |
Sep’08A |
Dec’08 |
Obs |
Exp* |
Obs |
Exp* |
Obs |
Exp* |
Obs |
Exp* |
Obs |
Exp* |
Ahmedabad |
49.4 |
47.9 |
59.4 |
56.7 |
90.4 |
48.6 |
99.6 |
67.6 |
99.6 |
53.8 |
Bangalore |
45.5 |
45.2 |
94.8 |
71.2 |
89.2 |
64.2 |
93.2 |
68.7 |
96.0 |
84.5 |
Bhopal |
69.2 |
66.7 |
56.5 |
61.3 |
26.4 |
23.7 |
80.0 |
77.5 |
99.2 |
76.3 |
Chennai |
73.9 |
60.9 |
85.4 |
84.5 |
99.0 |
86.2 |
97.2 |
55.4 |
100.0 |
31.8 |
Guwahati |
18.6 |
17.6 |
66.8 |
58.8 |
98.8 |
30.7 |
99.6 |
44.4 |
99.6 |
37.1 |
Hyderabad |
77.3 |
41.8 |
81.6 |
58.0 |
85.2 |
46.6 |
94.0 |
51.9 |
98.8 |
68.2 |
Jaipur |
76.4 |
75.8 |
10.4 |
10.1 |
83.2 |
47.7 |
99.2 |
52.1 |
100.0 |
49.5 |
Kolkata |
27.2 |
24.1 |
42.2 |
40.0 |
98.6 |
41.0 |
99.4 |
33.5 |
99.0 |
35.5 |
Lucknow |
13.7 |
11.9 |
86.0 |
62.2 |
98.8 |
58.2 |
98.4 |
43.4 |
98.8 |
27.4 |
Mumbai |
63.9 |
56.4 |
57.6 |
52.1 |
71.5 |
45.3 |
99.6 |
88.6 |
99.0 |
41.0 |
New Delhi |
76.2 |
68.1 |
60.6 |
61.8 |
91.2 |
54.9 |
98.6 |
66.3 |
99.2 |
49.6 |
Patna |
88.5 |
89.1 |
74.3 |
49.6 |
94.8 |
50.8 |
97.6 |
48.4 |
99.6 |
59.6 |
All Cities |
57.1 |
44.0 |
65.0 |
52.9 |
86.7 |
47.7 |
97.0 |
51.1 |
99.1 |
41.2 |
a) City-wise consistency
The consistency index that was just 57 per cent
in March 2008, improved substantially in the
recent survey rounds. This was so due to the
uniform training being imparted across
different centres and the field checks. The
cities of Bhopal, Guwahati, Kolkata and
Lucknow had very weak consistency in earlier
rounds but improved considerably in the latest
two rounds.
b) Category-wise consistency
The category wise response shown below also
depicts sharp improvement in the interconsistency
between qualitative and
quantitative responses.
2. Weak consistency
The X and Y variable as defined in this section
are arranged in a X x Y size matrix. The
diagonal responses in this matrix represent
consistent responses. However, not all offdiagonals
are incorrect responses. E.g. if a
respondent says that 3 month ahead, prices
are going to increase more than present rate
(i.e. X=A), then in the qualitative block, the
respondent should also give the 3 month ahead
rate a number greater than the current rate
(i.e. Y=A). Now X=A and Y=A, that is a
diagonal element, is consistence response.
However, if the respondent responds for the
current and 3 month ahead rate in the same
bracket (Y=B), he could still be correct. X=A and Y=B is an off-diagonal element, which is
correct.
Respondent category |
Mar’08 |
Jun’08 |
Sep’08 |
Sep’08A |
Dec’08 |
Obs |
Exp* |
Obs |
Exp* |
Obs |
Exp* |
Obs |
Exp* |
Obs |
Exp* |
Financial Sector Employee |
54.7 |
39.7 |
56.3 |
46.3 |
85.8 |
46.0 |
96.0 |
50.8 |
99.5 |
32.1 |
Other Employee |
61.3 |
47.6 |
65.6 |
52.1 |
87.0 |
46.2 |
95.7 |
45.8 |
99.2 |
38.6 |
Self-Employed |
55.8 |
45.2 |
64.2 |
54.2 |
87.8 |
48.5 |
97.9 |
49.1 |
99.2 |
41.1 |
Housewife |
60.3 |
47.2 |
70.8 |
61.7 |
85.6 |
49.1 |
97.6 |
56.7 |
99.3 |
48.9 |
Retired Person |
52.5 |
39.2 |
61.3 |
48.0 |
88.6 |
46.7 |
96.9 |
46.9 |
99.8 |
40.1 |
Daily Worker |
57.6 |
40.8 |
64.7 |
55.0 |
86.9 |
51.0 |
95.8 |
53.9 |
98.1 |
45.0 |
Other |
54.3 |
44.0 |
66.9 |
51.1 |
86.2 |
43.3 |
97.7 |
51.3 |
98.4 |
36.0 |
All categories |
57.1 |
44.0 |
65.0 |
52.9 |
86.7 |
47.7 |
97.0 |
51.1 |
99.1 |
41.2 |
Based on the above example, the concept of weak
consistency is defined as nder:
- Define a ‘near miss’ as the situation, where
smallest alteration of response to direct
question on either current or one-year ahead
inflation would have made the resulting Y
equal to X.
- Define weaker consistency index of a group
of survey responses as
(Number of times X is equal to Y + Number
of near misses) * 100 /
(Number of times X or Y is not equal to E)
a) City-wise consistency
The city-wise strong and weak consistency
indices are presented in the table below. The
weak consistency indices show further
improvement in the data quality. The
consistency indices that were very close to the
expected values also show sharp
improvement.
Cities |
Mar’08 |
Jun’08 |
Sep’08 |
Sep’08A |
Dec’08 |
Strong |
Weak |
Strong |
Weak |
Strong |
Weak |
Strong |
Weak |
Strong |
Weak |
Ahmedabad |
49.4 |
90.0 |
59.4 |
95.7 |
90.4 |
100.0 |
99.6 |
100.0 |
99.6 |
100.0 |
Bangalore |
45.5 |
50.4 |
94.8 |
99.6 |
89.2 |
100.0 |
93.2 |
100.0 |
96.0 |
100.0 |
Bhopal |
69.2 |
84.0 |
56.5 |
98.4 |
26.4 |
100.0 |
80.0 |
100.0 |
99.2 |
100.0 |
Chennai |
73.9 |
96.2 |
85.4 |
89.4 |
99.0 |
99.8 |
97.2 |
99.6 |
100.0 |
100.0 |
Guwahati |
18.6 |
50.7 |
66.8 |
99.6 |
98.8 |
99.2 |
99.6 |
99.6 |
99.6 |
100.0 |
Hyderabad |
77.3 |
96.8 |
81.6 |
98.8 |
85.2 |
100.0 |
94.0 |
99.6 |
98.8 |
100.0 |
Jaipur |
76.4 |
77.7 |
10.4 |
24.5 |
83.2 |
100.0 |
99.2 |
100.0 |
100.0 |
100.0 |
Kolkata |
27.2 |
66.5 |
42.2 |
90.9 |
98.6 |
99.4 |
99.4 |
99.6 |
99.0 |
99.8 |
Lucknow |
13.7 |
47.4 |
86.0 |
95.6 |
98.8 |
99.6 |
98.4 |
99.2 |
98.8 |
100.0 |
Mumbai |
63.9 |
74.5 |
57.6 |
85.0 |
71.5 |
92.8 |
99.6 |
99.8 |
99.0 |
100.0 |
New Delhi |
76.2 |
94.5 |
60.6 |
92.4 |
91.2 |
99.0 |
98.6 |
99.6 |
99.2 |
100.0 |
Patna |
88.5 |
97.4 |
74.3 |
95.6 |
94.8 |
99.6 |
97.6 |
99.6 |
99.6 |
100.0 |
All Cities |
57.1 |
78.1 |
65.0 |
88.4 |
86.7 |
98.8 |
97.0 |
99.7 |
99.1 |
100.0 |
b) Category-wise consistency
The category-wise weak consistency indices behave similar to the city-wise weak consistency indices.
The categories that did not offer strong consistent responses did so with the relaxed criteria. The
overall response for the last 2-3 rounds is very good on this count.
Respondent category |
Mar’08 |
Jun’08 |
Sep’08 |
Sep’08A |
Dec’08 |
Strong |
Weak |
Strong |
Weak |
Strong |
Weak |
Strong |
Weak |
Strong |
Weak |
Financial Sector Employee |
54.7 |
76.5 |
56.3 |
85.5 |
85.8 |
98.7 |
96.0 |
99.8 |
99.5 |
100.0 |
Other Employee |
61.3 |
80.9 |
65.6 |
90.3 |
87.0 |
98.5 |
95.7 |
99.4 |
99.2 |
100.0 |
Self-Employed |
55.8 |
77.4 |
64.2 |
89.9 |
87.8 |
99.0 |
97.9 |
100.0 |
99.2 |
99.9 |
Housewife |
60.3 |
78.4 |
70.8 |
89.5 |
85.6 |
98.5 |
97.6 |
99.9 |
99.3 |
100.0 |
Retired Person |
52.5 |
76.8 |
61.3 |
88.7 |
88.6 |
99.5 |
96.9 |
99.2 |
99.8 |
100.0 |
Daily Worker |
57.6 |
77.4 |
64.7 |
83.0 |
86.9 |
99.2 |
95.8 |
99.7 |
98.1 |
100.0 |
Other |
54.3 |
77.3 |
66.9 |
88.5 |
86.2 |
98.6 |
97.7 |
99.3 |
98.4 |
100.0 |
All categories |
57.1 |
78.1 |
65.0 |
88.4 |
86.7 |
98.8 |
97.0 |
99.7 |
99.1 |
100.0 |
D. Logistic Issues
The other logistic issue that were examined by ISI
were the issues of number of investigators engaged
and the time taken to complete the survey.
1. Number of investigators engaged
The number of investigators used in the 2008
rounds shows that there is more uniformity
required across cities. However on examining the
cities where the number of investigators was too
high, it was seen that due to typographical error
in coding the investigator name, the number has
so increased. It is being impressed upon the
agency that they should not send too few or too
many investigators for conducting as it dilutes
the check that can be exercised on them. To keep
a check on this aspect of quality, the present
attention need to be continued in future rounds
as well.
Cities |
Jun’ 08 |
Sep ‘08 |
Sep ’08a |
Dec ‘08 |
Four
Surveys Average
(Per 250
Respon-dents) |
Ahmedabad |
4 |
3 |
3 |
1 |
2.8 |
Bangalore |
3 |
7 |
4 |
9 |
5.8 |
Bhopal |
2 |
3 |
5 |
8 |
4.5 |
Chennai |
7 |
3 |
5 |
7 |
2.8 |
Guwahati |
1 |
1 |
1 |
1 |
1.0 |
Hyderabad |
3 |
3 |
3 |
3 |
3.0 |
Jaipur |
3 |
2 |
2 |
2 |
2.3 |
Kolkata |
4 |
8 |
3 |
4 |
2.4 |
Lucknow |
4 |
2 |
2 |
3 |
2.8 |
Mumbai |
7 |
14 |
15 |
8 |
5.5 |
New Delhi |
8 |
4 |
8 |
6 |
3.3 |
Patna |
4 |
3 |
3 |
3 |
3.3 |
All Cities
Average
(Per 250 Respondents) |
3.3 |
3.5 |
3.6 |
3.7 |
3.5 |
2. Duration of the survey
The frequency distribution of the duration of
survey is given in the table below. It shows that by
and large the time taken to complete the survey is
a week to ten days. The centres where the days
taken appear to be too large are the centres where
a particular investigator’s lot was rejected as none
of his respondents could be reached. In such cases
the interviews are asked to be redone. Thus by and
large on this account as well the survey data seems
to be consistent.
Cities |
Jun ’08 |
Sep ’08 |
Sep ’08a |
Dec ’08 |
Ahmedabad |
27 May, |
5 Sep , |
10 Oct, |
5 Dec, |
|
19 Days |
8 Days |
21 Days |
9 Days |
Bangalore |
25 May, |
4 Sep, |
2 Nov, |
5 Dec, |
|
9 Days |
10 Days |
5 Days |
7 Days |
Bhopal |
27 May, |
2 Sep, |
10 Oct, |
8 Dec, |
|
6 Days |
8 Days |
12 Days |
19 Days |
|
|
|
|
|
Chennai |
28 May, |
1 Sep, |
20 Oct, |
5 Dec, |
|
18 Days |
18 Days |
6 Days |
7 Days |
Guwahati |
3 June, |
6 Sep, |
24 Oct, |
6 Dec, |
|
5 Days |
5 Days |
5 Days |
7 Days |
Hyderabad |
27 May, |
2 Sep, |
20 Oct, |
7 Dec, |
|
12 Days |
17 Days |
4 Days |
5 Days |
Jaipur |
30 May, |
3 Sep, |
19 Oct, |
5 Dec, |
|
8 Days |
10 Days |
10 Days |
8 Days |
Kolkata |
31 May, |
5 Sep, |
21 Oct, |
5 Dec, |
|
7 Days |
8 Days |
12 Days |
9 Days |
Lucknow |
29 May, |
3 Sep, |
21 Oct, |
5 Dec, |
|
4 Days |
8 Days |
4 Days |
6 Days |
Mumbai |
28 May, |
3 Sep, |
23 Oct, |
5 Dec, |
|
14 Days |
8 Days |
2 Days |
5 Days |
New Delhi |
28 May, |
2 Sep, |
19 Oct, |
4 Dec, |
|
9 Days |
7 Days |
16 Days |
6 Days |
Patna |
30 May, |
3 Sep, |
22 Oct, |
5 Dec, |
|
6 Days |
5 Days |
8 Days |
6 Days |
All Cities |
25 May, |
1 Sep, |
10 Oct, |
4 Dec, |
|
21 Days |
18 Days |
28 Days |
23 Days |
3. Households interviewed per day per
investigator
The frequency distribution of the households
interviewed per day is presented in the following
table. The instances of very high interviews
conducted by an investigator per day should affect the quality of data collected. A check on this aspect
needs to be kept and the matter can be handled
at the time of investigator training and field check.
It can still be seen that the average number of
interviews conducted per day across the twelve
cities is close to 20, which is an acceptable number.
Jun’ 08 (Round 12) |
Sep ‘08 (Round 13) |
Sep ’08A (Round 13A) |
Dec ‘08 (Round 14) |
Bin |
Frequency |
Bin |
Frequency |
Bin |
Frequency |
Bin |
Frequency |
1-5 |
25 |
1-5 |
29 |
1-5 |
16 |
1-5 |
19 |
6-10 |
35 |
6-10 |
28 |
6-10 |
13 |
6-10 |
11 |
11-15 |
37 |
11-15 |
36 |
11-15 |
19 |
11-15 |
13 |
16-20 |
16 |
16-20 |
33 |
16-20 |
23 |
16-20 |
23 |
21-25 |
65 |
21-25 |
56 |
21-25 |
74 |
21-25 |
92 |
26-52 |
33 |
26-64 |
35 |
26-77 |
37 |
26-75 |
31 |
Median = 16 |
Median = 19 |
Median = 24 |
Median = 25 |
Annex-IV
ANOVA results for Round 12
Tests of Between-Subjects Effects
Dependent Variable: current inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
3704.7 |
26 |
142.5 |
132.1 |
0.000 |
Intercept |
80826.0 |
1 |
80826.0 |
74931.5 |
0.000 |
citycode |
3215.2 |
11 |
292.3 |
271.0 |
0.000 |
gendercode |
5.9 |
1 |
5.9 |
5.5 |
0.019 |
agegroup |
41.2 |
8 |
5.2 |
4.8 |
0.000 |
categorycd |
34.9 |
6 |
5.8 |
5.4 |
0.000 |
Error |
4094.6 |
3796 |
1.1 |
|
|
Total |
191233.8 |
3823 |
|
|
|
Corrected Total |
7799.3 |
3822 |
|
|
|
a. R Squared = .475 (Adjusted R Squared = .471) |
Tests of Between-Subjects Effects
Dependent Variable: 3 months ahead inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
1981.8 |
26 |
76.22 |
52.81 |
0.00 |
Intercept |
94432.8 |
1 |
94432.84 |
65429.31 |
0.00 |
citycode |
1696.9 |
11 |
154.26 |
106.88 |
0.00 |
gendercode |
0.1 |
1 |
0.09 |
0.06 |
0.80 |
agegroup |
68.0 |
8 |
8.50 |
5.89 |
0.00 |
categorycd |
25.9 |
6 |
4.32 |
2.99 |
0.01 |
Error |
5304.1 |
3675 |
1.44 |
|
|
Total |
214175.5 |
3702 |
|
|
|
Corrected Total |
7285.8 |
3701 |
|
|
|
a. R Squared = .272 (Adjusted R Squared = .267) |
Tests of Between-Subjects Effects
Dependent Variable: 1 year ahead inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
905.299 |
26 |
34.82 |
30.32 |
0.000 |
Intercept |
95601.0 |
1 |
95600.96 |
83235.76 |
0.000 |
citycode |
797.2 |
11 |
72.47 |
63.10 |
0.000 |
gendercode |
1.1 |
1 |
1.13 |
0.98 |
0.322 |
agegroup |
38.9 |
8 |
4.86 |
4.23 |
0.000 |
categorycd |
7.5 |
6 |
1.25 |
1.09 |
0.365 |
Error |
3894.8 |
3391 |
1.15 |
|
|
Total |
216222.5 |
3418 |
|
|
|
Corrected Total |
4800.1 |
3417 |
|
|
|
a. R Squared = .189 (Adjusted R Squared = .182) |
ANOVA results for Round 13
Tests of Between-Subjects Effects
Dependent Variable: current inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
7496.385 |
26 |
288.3 |
80.9 |
0.000 |
Intercept |
227373.7 |
1 |
227373.7 |
63807.1 |
0.000 |
citycode |
7422.4 |
11 |
674.8 |
189.4 |
0.000 |
gendercode |
4.7 |
1 |
4.7 |
1.3 |
0.252 |
agegroup |
51.2 |
8 |
6.4 |
1.8 |
0.073 |
categorycd |
16.6 |
6 |
2.8 |
0.8 |
0.587 |
Error |
14143.4 |
3969 |
3.6 |
|
|
Total |
595361.0 |
3996 |
|
|
|
Corrected Total |
21639.7 |
3995 |
|
|
|
a. R Squared = .346 (Adjusted R Squared = .342) |
Tests of Between-Subjects Effects
Dependent Variable: 3 months ahead inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
6907.31 |
26 |
265.67 |
51.02 |
0.00 |
Intercept |
261335.3 |
1 |
261335.29 |
50187.21 |
0.00 |
citycode |
6723.1 |
11 |
611.19 |
117.37 |
0.00 |
gendercode |
2.1 |
1 |
2.06 |
0.40 |
0.53 |
agegroup |
135.9 |
8 |
16.98 |
3.26 |
0.00 |
categorycd |
90.4 |
6 |
15.07 |
2.89 |
0.01 |
Error |
20667.4 |
3969 |
5.21 |
|
|
Total |
684847.0 |
3996 |
|
|
|
Corrected Total |
27574.7 |
3995 |
|
|
|
a. R Squared = .250 (Adjusted R Squared = .246) |
Tests of Between-Subjects Effects
Dependent Variable: 1 year ahead inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
9319.18 |
26 |
358.43 |
53.05 |
0.000 |
Intercept |
287330.5 |
1 |
287330.47 |
42529.43 |
0.000 |
citycode |
9135.4 |
11 |
830.49 |
122.93 |
0.000 |
gendercode |
25.3 |
1 |
25.27 |
3.74 |
0.053 |
agegroup |
139.0 |
8 |
17.37 |
2.57 |
0.008 |
categorycd |
82.2 |
6 |
13.70 |
2.03 |
0.059 |
Error |
26787.7 |
3965 |
6.76 |
|
|
Total |
761841.0 |
3992 |
|
|
|
Corrected Total |
36106.9 |
3991 |
|
|
|
a. R Squared = .258 (Adjusted R Squared = .253) |
ANOVA results for Round 13a
Tests of Between-Subjects Effects
Dependent Variable: current inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
5702.56 |
26 |
219.33 |
90.39 |
0.00 |
Intercept |
214828.27 |
1 |
214828.27 |
88536.05 |
0.00 |
citycode |
5489.02 |
11 |
499.00 |
205.65 |
0.00 |
gendercode |
3.89 |
1 |
3.89 |
1.60 |
0.21 |
agegroup |
23.47 |
8 |
2.93 |
1.21 |
0.29 |
categorycd |
16.26 |
6 |
2.71 |
1.12 |
0.35 |
Error |
9640.28 |
3973 |
2.43 |
|
|
Total |
523124.00 |
4000 |
|
|
|
Corrected Total |
15342.84 |
3999 |
|
|
|
a. R Squared = .373 (Adjusted R Squared = .368) |
Tests of Between-Subjects Effects
Dependent Variable: 3 months ahead inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
11047.54 |
26 |
424.91 |
57.04 |
0.00 |
Intercept |
230048.23 |
1 |
230048.23 |
30880.04 |
0.00 |
citycode |
10292.37 |
11 |
935.67 |
125.60 |
0.00 |
gendercode |
3.19 |
1 |
3.19 |
0.43 |
0.51 |
agegroup |
53.41 |
8 |
6.68 |
0.90 |
0.52 |
categorycd |
65.01 |
6 |
10.83 |
1.45 |
0.19 |
Error |
29597.81 |
3973 |
7.45 |
|
|
Total |
576892.00 |
4000 |
|
|
|
Corrected Total |
40645.35 |
3999 |
|
|
|
a. R Squared = .273 (Adjusted R Squared = .267) |
Tests of Between-Subjects Effects
Dependent Variable: 1 year ahead inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
14317.71 |
26 |
550.68 |
57.24 |
0.00 |
Intercept |
262895.02 |
1 |
262895.02 |
27327.29 |
0.00 |
citycode |
13184.97 |
11 |
1198.63 |
124.60 |
0.00 |
gendercode |
1.86 |
1 |
1.86 |
0.19 |
0.66 |
agegroup |
100.41 |
8 |
12.55 |
1.30 |
0.24 |
categorycd |
101.23 |
6 |
16.87 |
1.75 |
0.10 |
Error |
38221.20 |
3973 |
9.62 |
|
|
Total |
670832.00 |
4000 |
|
|
|
Corrected Total |
52538.91 |
3999 |
|
|
|
a. R Squared = .274 (Adjusted R Squared = .268) |
ANOVA results for Round 14
Tests of Between-Subjects Effects
Dependent Variable: current inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
7917.8 |
26 |
304.5 |
178.6 |
0.000 |
Intercept |
157339.2 |
1 |
157339.2 |
92293.0 |
0.000 |
citycode |
7821.1 |
11 |
711.0 |
417.1 |
0.000 |
gendercode |
22.3 |
1 |
22.3 |
13.1 |
0.000 |
agegroup |
31.1 |
8 |
3.9 |
2.3 |
0.020 |
categorycd |
12.6 |
6 |
2.1 |
1.2 |
0.285 |
Error |
6773.1 |
3973 |
1.7 |
|
|
Total |
362010.0 |
4000 |
|
|
|
Corrected Total |
14690.9 |
3999 |
|
|
|
a. R Squared = .539 (Adjusted R Squared = .536) |
Tests of Between-Subjects Effects
Dependent Variable: 3 months ahead inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
13238.695 |
26 |
509.2 |
54.9 |
0.000 |
Intercept |
142285.0 |
1 |
142285.0 |
15328.2 |
0.000 |
citycode |
11777.2 |
11 |
1070.7 |
115.3 |
0.000 |
gendercode |
61.7 |
1 |
61.7 |
6.6 |
0.010 |
agegroup |
38.6 |
8 |
4.8 |
0.5 |
0.843 |
categorycd |
370.0 |
6 |
61.7 |
6.6 |
0.000 |
Error |
36879.6 |
3973 |
9.3 |
|
|
Total |
367546.0 |
4000 |
|
|
|
Corrected Total |
50118.3 |
3999 |
|
|
|
a. R Squared = .264 (Adjusted R Squared = .259) |
Tests of Between-Subjects Effects
Dependent Variable: 1 year ahead inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
16585.85 |
26 |
637.9 |
58.6 |
0.000 |
Intercept |
164063.3 |
1 |
164063.3 |
15078.8 |
0.000 |
citycode |
14621.9 |
11 |
1329.3 |
122.2 |
0.000 |
gendercode |
0.6 |
1 |
0.6 |
0.1 |
0.810 |
agegroup |
73.5 |
8 |
9.2 |
0.8 |
0.563 |
categorycd |
722.1 |
6 |
120.3 |
11.1 |
0.000 |
Error |
43217.0 |
3972 |
10.9 |
|
|
Total |
430987.8 |
3999 |
|
|
|
Corrected Total |
59802.9 |
3998 |
|
|
|
a. R Squared = .277 (Adjusted R Squared = .273) |
ANOVA results for Round 15
Tests of Between-Subjects Effects
Dependent Variable: current inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
3641.5 |
26 |
140.1 |
47.4 |
0.000 |
Intercept |
46043.5 |
1 |
46043.5 |
15590.3 |
0.000 |
citycode |
3472.6 |
11 |
315.7 |
106.9 |
0.000 |
gendercode |
11.2 |
1 |
11.2 |
3.8 |
0.052 |
agegroup |
24.0 |
8 |
3.0 |
1.0 |
0.422 |
categorycd |
41.4 |
6 |
6.9 |
2.3 |
0.030 |
Error |
11733.6 |
3973 |
3.0 |
|
|
Total |
124494.0 |
4000 |
|
|
|
Corrected Total |
15375.1 |
3999 |
|
|
|
a. R Squared = .237 (Adjusted R Squared = .232) |
Tests of Between-Subjects Effects
Dependent Variable: 3 months ahead inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
6871.8 |
26 |
264.3 |
53.1 |
0.000 |
Intercept |
49706.5 |
1 |
49706.5 |
9978.8 |
0.000 |
citycode |
6371.8 |
11 |
579.3 |
116.3 |
0.000 |
gendercode |
33.1 |
1 |
33.1 |
6.6 |
0.010 |
agegroup |
44.7 |
8 |
5.6 |
1.1 |
0.345 |
categorycd |
178.3 |
6 |
29.7 |
6.0 |
0.000 |
Error |
19790.3 |
3973 |
5.0 |
|
|
Total |
139744.0 |
4000 |
|
|
|
Corrected Total |
26662.0 |
3999 |
|
|
|
a. R Squared = .258 (Adjusted R Squared = .253) |
Tests of Between-Subjects Effects
Dependent Variable: 1 year ahead inflation
Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Corrected Model(a) |
6568.75 |
26 |
252.6 |
42.6 |
0.000 |
Intercept |
66176.8 |
1 |
66176.8 |
11164.1 |
0.000 |
citycode |
6257.9 |
11 |
568.9 |
96.0 |
0.000 |
gendercode |
7.0 |
1 |
7.0 |
1.2 |
0.278 |
agegroup |
25.0 |
8 |
3.1 |
0.5 |
0.837 |
categorycd |
153.6 |
6 |
25.6 |
4.3 |
0.000 |
Error |
23550.6 |
3973 |
5.9 |
|
|
Total |
183520.0 |
4000 |
|
|
|
Corrected Total |
30119.4 |
3999 |
|
|
|
a. R Squared = .218 (Adjusted R Squared = .213) |
*
Prepared in the Survey Division of Department of
Statistics and Information Management.
1 Bruine de Bruin, W., Manski, C. F., Topa, G. and Van
der Klaauw, W. (2009), Measuring Consumer Uncertainty
about Future Inflation, Federal Reserve Bank of New
York Staff Report , No. 415, December 2009.
2 http://www.bankofengland.co.uk/publications/events/ccbs_cew2009/presentation_kokoszczynski.pdf
3 Benford, James and Driver, Ronnie (2008), Public
attitudes to inflation and interest rates, Bank of England
Quarterly Bulletin, 2008:Q2, pp 148-156. |