F I N A L D I S S E R T A T I O N R E P O R T P R I N T

IMPACT OF INFLATION ON THE CONSUMER PERCEPTION TOWARDS INSURANCE

DISSERTATION REPORT

ON

“IMPACT OF INFLATION ON THE CONSUMER
PERCEPTION TOWARDS INSURANCE”

Submitted To: Submitted By:
LECT. J.L.KAPOOR SUMIT ARORA
ASIAS 2804
AMITYUNIVERSITY MBA (INSURANCE)

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AMITY SCHOOL OF INSURANCE AND ACTUARIAL SCIENCE
1

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AMITY SCHOOL OF INSURANCE AND ACTUARIAL
SCIENCE


TABLE OF CONTENTS

Chapter Page
No.

1. ACKNOWLEDGEMENT………………………………………………………...0
4
2. OBJECTIVE……………………………………………………………………….
06
3. ABSTRACT………………………………………………………………………...
08
4. METHODOLOGY………………………………………………………………...
10
5. REVIEW OF
LITERATURE……………………………………………………..13
6. INFLATION………………………………………………………………………..
31
 MEANNING
 METHOD OF CALCULATION
 LIMITATION OF METHOD
 INFLATION INDIA
 HOW INFLATION EATS UP THE MONEY?
 IMPACT ON THE INVESTMENT DECISION
7. FINDINGS & ANALYSIS……………………………………………………….75
8. RESULTS…………………………………………………………………………
87
9. CONCLUSION…………………………………………………………………...9

5

3
10. RECOMMENDATION…………………………………………………………..9
5
11. LIMITATION OF STUDY………………………………………………………
97
12. APPENDICES ……………………………………………………………………
99
13. REFERENCE...
……………………………………………………………….102


ACKNOWLEDGEMENT

A work of this magnitude requires inputs, efforts and encouragement of people from all
sides. In compiling this project report, I have been fortunate enough to get active and
kind cooperation from many people without whom my endeavors would not have been a
success.

7

At the very onset, I would like to thank LECT. J. L. Kapoor, FACULTY MENTOR
for giving me an opportunity to such an interesting project on IMPACT OF
INFLATION ON THE CONSUMER PERCEPTION TOWARDS INSURANCE.
The excellent guidance and support provided by him have gone a long way in the
successful completion of this project.

My heart full thanks to all faculty members of ASIAS, AMITY UNIVERSITY who
gave me continuous support in every possible manner to help me in successfully
completing my dissertation.
I also acknowledge to those who directly or indirectly helped me in this endeavor.

SUMIT ARORA


OBJECTIVE

9

The objective of the project is to study the “impact of the inflation on the consumer
perception towards insurance” and find out how consumer perception changes with the
change in inflation rate.

The objectives include the following:

• To study what is the change in the perception when the rate of inflation is high and
when it is low.
• To find out what percentage of saving they would like to invest in insurance when
the rate of inflation is high and when it is low.
• To find out preference of the consumer for investment when the rate of inflation is
high and when it is low.
• To find out which saving option they opt when the rate of inflation is high and when
it is low.
• To study the effect of annual income on the buying decision of an insurance policy.
• To find out which insurance product they preferred more when the rate of inflation
is high and when it is low.
• To find out what is the reason for selecting insurance when the rate of inflation is
high and when it is low.


11

ABSTRACT

In present scenario, consumer considered as a king. Market trend changes with
perception of the consumer. It is the perception of the consumer only which makes one
company the largest company of the world and the other an unknown company.
Consumer perception depends upon various factors like income of consumer, perception
towards product or service, brand name etc.

Today when inflation rate is increasing with a high rate, it creates greater impact on the
consumer perception. Government takes necessary steps to control the inflation rate,
which can have impact on the rate of interest, banking system and financial institution.
This can have impact on the saving part of the consumer, so with increase in inflation
rate with same income there can be impact on the saving part of consumer. Today when
consumer has lot of option for saving like FD, Insurance, Bank saving, mutual fund,
share market. When the rate of inflation is high consumer may want more secure, high
return saving option. There may be chance that consumer perception towards insurance
may get changes with the up and down of the inflation rate. The main aim of the project
is study the impact of the inflation on consumer perception. How much part of the total
saving he/she would like to invest in insurance when the rate of inflation is up and when
it is down. Is there any variation in the perception when the rate of inflation is high and
when it is low. It is very important for insurance company to get to know about these
facts in order to understand consumer perception, which is the only priority of every
insurance company. This dissertation report is tells about the relationship between the
inflation and consumer perception towards insurance.


13

METHODOLOGY

It refers to the process that enables the researcher to collect and analyze the data for
making a multi-dimensional study for a particular aspect of the system. It also analyses
the procedure of enquiry into particular field.

The research methodology adopted in the study is:-

Data Collection Techniques

Primary Research
The method adopt for this survey is Exploratory Research since the main aim is to gain
an insight in to the perception of the consumer towards insurance with rate of inflation
and what are the factors that lead to their decision while choosing a insurance plan. A
questionnaire method is going to be use for purpose of the study. The questionnaire is
thought to be the most suitable because it allows structured, meaningful and uniform
interaction with the respondent.


The following step enumerates the various stages of this project.

Step1. Designing the questionnaire
The first step in the research process is the formation of questionnaire keeping in mind
the need for uniformity and specificity of information. A structured, non disguised
questionnaire will be drafted keeping in mind that it will cover the objectives of the
project. The questionnaire is drafted for respondents.

Step2. Deciding the sample size
The sample size is decided to be 50 so that sufficient information and variability can be
obtained. The place of study is Delhi only.

Step3. Collection of data
The questionnaires will directly filled by the respondents, or a communication will make
through telephone or personal interview.

Step4. Classification and tabulation of data
The data obtained through the questionnaire will then fed in to the computer and
tabulated. The data will obtain through objective questions and will be put in graphical
form. This will done to facilitate analysis about the various aspects

Step5. Analysis and Findings
The data as it will put in the form of graphs will be easier to analyze. Interpretations will
be done and major inferences will be drawn.

15

Secondary Research
Secondary data are data collected by persons or agencies for purposes other than solving
the problem at hand. They are one of the most economical and easiest means of
accessing information.
• Secondary data can also be obtained from published sources such as journals,
reports, govt. publication and magazines.

NULL HYPOTHESIS – I assume that the inflation have a impact on the consumer
perception towards insurance because inflation have a impact on the saving, as it
increases the expenditure with constant level of income.


Review of literature

What is inflation?

When you see the term “inflation” in the newspaper, it refers to a change in the

17

Consumer Price Index (CPI), which tracks the costs of goods and services typically
purchased by consumers. This government figure is good for measuring economic
activity for the country at large, but does little for individuals who have buying habits
based on their age, lifestyle, and where they live that are different from the typical
consumer’s. If you spend a lot on goods and services with high inflation rates, such as
college and medical expenses, the CPI significantly understates the impact that inflation
is having on you

CPI is the traditional benchmark
“The most relevant measure of inflation from a financial planning point of view is the
year-over-year change in the Consumer Price Index (CPI). In contrast to many other
measures of prices, the CPI has the advantage of being restricted to the goods and
services purchased by individuals,” remarked Alexander. However, the CPI will not
reflect the outlays by any specific individual or household. For example, tobacco is a
component of the CPI, but the majority of Canadians are non-smokers. As a result, the
CPI should be viewed as only a rough guide to what is happening to the cost of living.

Inflation to average two per cent
“Although inflation has been low for more than a decade, the memory of the double-
digit and high single-digit inflation in the 1970s and 1980s lingers. However, there is
good reason to believe that history will not repeat itself due to a change in the conduct
of monetary policy by the Bank of Canada,” observed Alexander. During the 1990s the
Bank of Canada introduced targets for keeping inflation in a range of one to three per
cent, and since adopting this approach inflation has averaged 1.8 per cent. “Looking
ahead, although inflation will fluctuate, there is every reason to believe that the Bank


will keep inflation between one and three per cent, and average close to two per cent,”
stated
Alexander.

Low inflation environment has investment implications
The inflation outlook has a number of investment implications. It suggests that the
unadjusted return on fixed income instruments will remain low by historical standards in
the years ahead. Included in the yield on fixed income investments is a premium for the
expected rate of inflation over the lifetime of the assets to compensate for the future loss
of purchasing power, as well as a premium for the volatility and uncertainty about the
future rate of inflation. As inflation has fallen over the past two decades, so too have the
inflation premiums. “The bulk of the decline in long-term Government of Canada bond
yields from an average of almost 12 per cent in the 1980s to below six per cent in the
late 1990s is explained by lower inflation premiums,” remarked Alexander.

The low inflation environment will also constrain corporate profits growth, which, in
turn, may affect equity prices. To illustrate, real GDP measures the increase in the
volume of economic activity. When inflation is added, nominal GDP is an estimate of
national income, which is divided between government, individuals and corporations –
with the bulk of the latter representing profits. “In other words, profits are constrained
by nominal GDP growth, which will be slower in a low inflation environment,”
suggested Alexander.

It is after-inflation returns that matter
“At this point, some readers may have the impression that low inflation is undesirable.

19

But, lower unadjusted returns are not the relevant benchmark. It is after-inflation returns
that matter,” observed Alexander. To illustrate, investors should be indifferent between
an investment paying six per cent when inflation is four per cent and an investment
paying four per cent when inflation is two per cent, as the after-inflation return of two
per cent is the same. However, the sustained low inflation environment may constrain
after-inflation returns due to a reduced premium related to lower volatility in inflation,
but this impact is likely modest. And, as a partial offset, there is a tax advantage to the
low inflation environment, since taxes are paid on the unadjusted income and capital
gains. “Moreover, while after-inflation returns may be slightly lower, the economy is
clearly better off. Indeed, the economy is deeply and adversely affected when inflation
is high and volatile, as it leads to the mis-pricing of real and financial assets and creates
extreme volatility in interest rates. By creating a sustained subdued inflation backdrop,
the Bank of Canada has engineered a low interest rate environment that helps to foster
economic growth and engenders greater prosperity, all of which makes for a superior
investment climate,” said Alexander.
.

How does inflation erode purchasing power?
Most consumers don’t understand how damaging inflation can be over long periods of
time on their purchasing power. One dollar today simply doesn’t buy as much as it did
in 1970 and will buy even less 30 years from now. If you long for the days in which you
could buy a Coke for a nickel, you know exactly what we’re talking about.

Inflation has averaged about 3% annually from 1926–2006. Three percent may not seem
like much, but it can significantly erode your purchasing power over long time horizons.
Take for example the impact a 3% inflation rate can have on a fixed annual income of
$100,000 over a typical 30-year retirement. As the image below demonstrates, your
money would be worth 14% less in five years and in 30 years, the purchasing power of
your income would be reduced by nearly 60% to $40,101. There’s a good chance that
the rate of inflation you will experience in retirement will exceed the long-term 3%


average, simply because goods and services that you will be purchasing won’t resemble
what the typical consumer is buying in the CPI aggregate. Medical expenses in
particular are likely to be a significantly higher portion of your overall spending. A
recent estimate from the Centers for Medicare & Medicaid Services suggests medical
inflation may be as high as 6.3% annually over the period 2005–2015.1

21

Inflation, Uncertainty, and Saving Behavior

In this paper the researcher (PAUL WACHTEL, New York University) investigate the
relationship between inflation and uncertainty and saving behavior. His findings confirm
the hypothesis that the high saving rates observed are related to inflation and
uncertainty, Three basic results emerge from the study: (1) the measurement of inflation
effects is very sensitive to the choice of data source; (2) the major impact of the inflation
uncertainty is to increase saving through a reduced propensity to incur liabilities; (3)
evidence of an uncertainty effect on financial asset acquisitions was not found, a
surprising result that points to the need for further research in this area. The paper
extends previous investigations by examining both flow of funds and national income
and product account data. In addition, saving components from the flow of funds are
examined.
It is well known that the inflationary experience since the mid-l960s has been
accompanied by high personal saving rates.

A number of recent studies of saving functions have indicated that this relationship is
more than coincidental (Juster and Wachtdl972a and 1972b; Wachtel '1977; Taylor
1974; luster and Taylor 1975; luster 1975; Burch and Werneke 1975). Although the
evidence that inflation is a major cause of increased personal saving is strong, there are a
number of gaps in the existing literature. First of all, previous studies rely primarily
upon the personal saving data from the national income accounts. Secondly, very little
has been determined about which components of saving are affected by inflation. In this
paper, he addresses these Issues by estimating saving functions for various definitions of
aggregate saving and its major components.

A desegregation of saving is desirable since saving is the sum of three different


activities; that is, increased saving can be the result of an increase in purchases of
financial assets, a reduction in the net increase in liabilities, or an increase in purchases
of durable assets. Up to this time, researchers have avoided discussing the effects of
Inflation on the

allocation of saving because of the difficulty of defining saving and the poor quality of
the available disaggregated data. Skirting both these issues, researchers have relied
instead upon the most popular definition and data source-personal saving in the national
income and product accounts (NIPA). In this paper he use disaggregated saving data for
the household sector from the f1ow-of-funds (FOF) accounts. In section 1, he outlines
the reasons for expecting an effect on saving because of uncertainty about inflation. In
section 2, the saving data are discussed. The Houthakker-Taylor (1970) model used here
is presented in section 3. The empirical results, presented in section 4, pertain to
aggregates and their components. Section 4 also contains a discussion of the
inconsistencies among data sources and some alternative specifications of the model.

Two basic results emerge from this study. First, the measurement of inflation effects is
very sensitive to the choice of data. This is not surprising; Taubman (1968) reached the
same conclusion in an analysis of the saving-income relationship.' Secondly, the major
impact of inflation uncertainty is to increase saving through a reduced propensity to
incur liabilities. Closely linked to this phenomenon is the negative effect of uncertainty
on net investment in physical assets. There is little firm evidence of any effect on the
acquisition of financial assets, although the results in this area are unclear and further
research is needed.

23

THE EFFECT OF INFLATION ON SAVING

The basic question to be discussed in this section is, quot;Why should inflation affect a
household's saving-consumption decision?quot; For the most part, econometric research on
aggregate saving behavior has ignored inflation effects. Traditionally, economists have
assumed that overall real spending decisions are Unaffected by the general price level.
In addition until recently, the rate of inflation was small enough to be ignored in
empirical research. This is no longer the case, and there is mounting evidence that the
traditional approach is no longer valid. .

The assumption of neutrality is valid if all prices throughout the economy go up at the
same rate. In that case, inflation does not alter real income or relative prices, and it is
reasonable to assume that inflation has no real effects. Although in the long run inflation
may be anticipated and neutral, the stringency of these assumptions for the short run is
often overlooked. Alternatively, there are several ways by which inflation may affect
consumer behavior, some of which reduce saving but most of which increase it. Several
of these are briefly discussed-money illusion, intertemporal substitution,
uncertainty, and indirect effects that operate through interest rates and wealth.


The Money Illusion Effect

Money illusion has a long history in the macroeconomic literature on consumption.
Money illusion occurs when inflation is not recognized. Consumers Overestimate the
purchasing power of their nominal income and decide to raise real consumption levels.
Consequently, real consumption expenditure is increased, and saving is reduced.

Money illusion is contingent upon consumer ignorance. However, the consumer sector
is not necessarily always ignorant of the current inflation rate. Whether money illusion
of this type affects consumption behavior is an empirical question. It was originally
explored by Branson and Klevorick (1969) and more recently by Wachtel (1977).
Branson and Klevorick found a very large money illusion effect. Their results suggested
that a 1 percent price increase leads to an increase of 0.4 percent in real consumption,
rather too large to be believed. Wachtel suggests that the degree of money illusion has
decreased substantially in recent years. In periods of little overall inflation, errors in
perception are likely to be small in magnitude and of little consequence, and there is
little incentive to invest in price information. Although money illusion is observed in
periods of low inflation, the money illusion phenomenon has tended to disappear as

25

inflation has become more severe.

The Intertemporal Substitution Effect

It is often argued that when price increases are expected, expenditures are advanced in
time. If the expenditures are on investment goods, measured saving will increase;
otherwise, consumption increases. Intertemporal substitution is relatively rare because
rational behavior requires that the expected price increases be sufficiently large and
certain to make it worthwhile to maintain goods inventories (which may entail
substantial opportunity costs). In a relatively stable economy this is not likely to be true
very often, and buying sprees, though observed on occasion, are relatively rare in the
United States.

The Uncertainty Effect

The term quot;uncertainty effectquot; refers to a set of hypotheses which suggest that inflation
leads to increased saving. My contention is that these hypotheses describe the main
effect of inflation on saving.
One such hypothesis is based on Katona's finding that the public has a strong distaste
for inflation. Inflation is viewed as an undesirable phenomenon, and its presence is
associated with increased pessimism about economic conditions, which may lead to
increased saving for precautionary reasons. Thus, inflation is a proxy for attitudes about
economic conditions, particularly uncertainty. This hypothesis is unsatisfactory,
however, because it relies upon a tenuous psychological link between inflation and
uncertainty to explain the increase in saving in inflationary times.
There are more specific reasons for relating inflation to uncertainty. Both time series
and cross-sectional observations suggest that inflation tends to be more variable as it


increases. Therefore, inflation forecasts deteriorate, forecast errors become more
prevalent, and the dispersion of inflation forecasts also increases. Consequently, the
uncertainty of real income expectations increases with inflation. It can be argued that
increased saving is a precautionary response to the increase in uncertainty. Saving is
determined by both the expected level of real income and the certainty with which those
expectations are held. The greater the uncertainty of expectations, the greater will be
saving.
In specifying a saving function, I include a direct measure of inflation uncertainty. The
appropriate measure would be the variance (or higher moments) of the average
individual's subjective probability distribution of the expected rate of inflation. Although
a time series of the mean expected rate of inflation is available from the quarterly
surveys conducted by the Survey Research Center, the variance cannot be readily
measured. Therefore, the proxy I use is the variance among individuals in their inflation
expectations. The construction of the mean and variance from the survey responses is
discussed in Wachtel (1977)
There are other sources of real income uncertainty that increase saving. The most
frequently cited is the effect of unemployment or general economic conditions on
money income expectations. When economic conditions worsen, the employed save
more in order to be able to maintain their consumption if they become unemployed. This
effect is offset by the dissaving of those already unemployed. Clearly, nominal income
expectations and their dispersion (there is greater downside risk in a recession) will also
affect aggregate saving behavior. Juster has shown that the unemployment rate has a
strong negative influence and in the unemployment a strong positive influence on the
saving rates, reflecting these two effects.

Indirect Effects

27

Inflation also affects saving behavior indirectly through its effects on other determinants
of saving. In particular, inflation will affects interest rates and the real wealth of
households. The real value of household financial wealth is often eroded in inflationary
periods, and an attempt by individuals to maintain the purchasing power of their stock of
financial assets will lead to higher saving. Inflation reduces real financial Wealth and
thus induces saving only when rates of return fail to incorporate an inflation premium.
In the long run, rates of return either adjust to include an inflation premium or consumer
reallocates their portfolio. Any long-run inflation effect on saving is likely to reflect
uncertainty rather than a wealth effect. Furthermore, the wealth effect should apply
primarily to financial assets and not to other forms of saving, since the real value of the
flow of services from the stock of durables is unchanged. In my empirical investigation
of inflation effects on the consumption of saving, I show the importance of inflation,
presumably because of its uncertainty, on no financial saving.

SAVING DATA

The difficulties in working with saving data are well known to researchers .There is
variety of definitions and data sources available, with large and variable discrepancies
among them. Saving by individuals is determined residually in both the flow of funds
and national income and product accounts. Consequently, there is a serious problem of
errors in measurement.

Although there are a large number of alternative saving measures, I restrict my analysis
to personal saving as defined in NIPA and saving as defined in the FOF household


account. The NIPA definition is the most common measure used: saving there is
determined residually as personal income less personal outlays and tax and non tax
payment for government services.

The data represent the saving of individuals (including proprietors), nonprofit
institutions, private noninsured welfare funds, and private trust funds. FOF, however,
defines saving as the sum of the sectoral fund flows into various assets. The FOF
household account covers households, nonprofit organizations, and personal trusts but
excludes the farm and non-farm non-corporate business sectors. Unfortunately, with the
exception of plant and equipment investments of the nonprofit sector, it is not possible
to further isolate the saving flows of households!

The conceptual definitions of saving in the official accounts are not entirely satisfactory.
In particular, in both published data sources, capital gains on financial and physical asset
are ignored. Although difficult to estimate, they are sometimes considered as
components of saving and can be expected to affect saving in other forms. In addition,
the recent improvements in NIPA, to provide, among other things, a better economic
definition of depreciation, had not yet been incorporated in the FOF data used here.

Given the large number of independent data sources (income and product or f1ow-of-
funds bases), the discrepancies among consistently defined saving figures are
remarkably small. But given the accuracy that researchers have come to expect in the
aggregate data, it is appalling to find discrepancies that often exceed $10 billion (at
annual rates). Since there is very little that can be done to rectify this confusing
situation, it has been the overwhelming tendency of both research economists and the
more practically inclined to ignore the problem. Given our interest here in
disaggregating saving, this will not be possible.

29

THE SAVING MODEL

While most models of consumer behavior are highly aggregated and concentrate on a
single consumption-saving decision, in some models the components of consumption
and saving are disaggregated. With desegregation it is necessary to take account of the


institutional structure and relative price phenomena that affect each of the components.
This latter task is a difficult one for saving components and beyond the scope of this
paper. We cannot distinguish between the gross effects of inflation and its indirect
effects through other determinants. Since our interest here is to identify the existence of
gross inflation and uncertainty effects, it is preferable to use a model that provides a
uniform framework for estimation of both an aggregate saving function and its
components. Of course such a general model cannot take account of all the diverse
factors that might affect aggregate saving.

Comparison with Other Results

31

The results obtained are broadly consistent with the literature cited in the introduction.
Most of those studies use some variant of personal saving and find significant positive
inflation or uncertainty effects. The point estimates are very sensitive to differences in
specification and sample period. This, however, is not surprising in light of our results
with different saving data.
Taylor's (1974) is the only study in which saving components and the flow of funds data
were examined. His price expectations variable is not comparable to my measure and
his reduced form model includes a large number of additional saving determinants. He
finds positive expectations effects for aggregate saving from both NIPA and FOF as
well as for physical investment and net acquisitions of financial assets. The differences
in results are not due to his shortened sample period, but apparently are the
consequences of specification differences. Taylor's specifications differ for each saving
component. In order to compare inflation and uncertainty effects on each component. I
adopted a simpler model with a common, simplified structure.


CONCLUSION

The discussions in this paper confirmed that the hypothesis of a relationship between
saving and inflation and uncertainty is well founded. However, it was also shown that
some important issues remain to be investigated. In particular, a better understanding of
the determinants of the disaggregated saving flows is needed. The implication of this
study is that as economists formulate better models for the components of saving by
individuals, inflation and uncertainty are likely to play an important role.

The results are sensitive to the sources of data used. This makes precise estimation of
inflation effects on saving difficult. Although the discrepancy in results can be
explained, it is not dear which data set should be viewed as correct. A better
understanding of the relationship probably depends on improvements in the quality of
the data.
Financial asset acquisitions are probably the weakest link in the data and also yield the
most ambiguous results. There is very little evidence of precautionary saving leading to
increased liquid asset holding. The hypothesis may be incorrect or the data and models
may be inadequate; either is an equally plausible explanation, and the issue remains
unsettled.

My evidence suggests that when households are uncertain about inflation, they reduce
their borrowing. I conclude that this is the major source of the often observed inflation-
saving relationship. A corollary is that inflation leads to reduced physical investment.
Although this contradicts the usual notion that inflation produces a shift to real assets,
the strength of the results for liabilities and physical investment is convincing. These
results hold when interest rates are held constant and with either the inflation rate or the
survey variance representing uncertainty.

33

So once the consumer saving perception changes as per inflation then it may have
impact on the consumer perception about the insurance. So the above study can be used
as a secondary data to do the project

Inflation is a rise in the general level of prices of goods and services in an economy over
a period of time. The term quot;inflationquot; once referred to increases in the money supply
(monetary inflation); however, economic debates about the relationship between money
supply and price levels have led to its primary use today in describing price inflation.
Inflation can also be described as a decline in the real value of money—a loss of
purchasing power in the medium of exchange which is also the monetary unit of
account. When the general price level rises, each unit of currency buys fewer goods and
services. A chief measure of price inflation is the inflation rate, which is the percentage
change in a price index over time.

Inflation can cause adverse effects on the economy. For example, uncertainty about
future inflation may discourage investment and saving. High inflation may lead to
shortages of goods if consumers begin hoarding out of concern that prices will increase
in the future.

Economists generally agree that high rates of inflation and hyperinflation are caused by
an excessive growth of the money supply. Views on which factors determine low to
moderate rates of inflation are more varied. Low or moderate inflation may be attributed
to fluctuations in real demand for goods and services, or changes in available supplies
such as during scarcities, as well as to growth in the money supply. However, the
consensus view is that a long sustained period of inflation is caused by money supply
growing faster than the rate of economic growth.

Today, most economists favor a low steady rate of inflation. Low (as opposed to zero or


negative) inflation may reduce the severity of economic recessions by enabling the labor
market to adjust more quickly in a downturn, and reducing the risk that a liquidity trap
prevents monetary policy from stabilizing the economy. The task of keeping the rate of
inflation low and stable is usually given to monetary authorities. Generally, these
monetary authorities are the central banks that control the size of the money supply
through the setting of interest rates, through open market operations, and through the
setting of banking reserve requirements.

35


What is meant by Inflation?
A persistent increase in the level of consumer prices or a persistent decline in the
purchasing power of money, caused by an increase in available currency and credit
beyond the proportion of available goods and services.

Cost of Living:

The cost of certain essential commodities in the years 1987, 1997 and the present cost
(February 2004) are shown below. Assuming that the inflation rate will be the same as
that in the period 1987-1997, the prospective inflation rate for 2017 is shown below.
Financial planning of a person shall be such that he must be capable of buying essential
commodities at inflated rate during post retirement period.

37

2017
1987 1997 Feb’ 2006
Items (Rs.)
(Rs.) (Rs.) (Rs.)
Colgate
104.00
toothpaste 8.05 18.90 35.00
(100gm tube)
52.00
Hamam Soap 3.05 7.85 13.00

259.12
Petrol 7.99 25.48 47.49

830.80
LPG Cylinder 56.15 137.85 288.10

Inflation robs your

Purchasing power? A chart showing the cost inflation indexation from financial year
1981-82 to 2004-2005 as announced by Government of India is given below. This table
facilitates to calculate Adjustment of Purchase price of a movable / immovable property
for payment of Capital Gain Tax.


Financial Cost Inflation
Cost Inflation
Indexation
Year Indexation

1981-82 100

1982-83 109

1983-84 116

1984-85 125

1985-86 133

1986-87 140

1987-88 150

1988-89 161

1989-90 172

1990-91 182

1991-92 199

1992-93 223

Year
1993-94 244

1994-95 259

1995-96 281

1996-97 305

1997-98 331

1998-99 351

1999-00 389

39

2000-01 406

2001-02 426

2002-03 447

2003-04 463

2004-05 480

Origin

Inflation originally referred to the debasement of the currency. When gold was used as
currency, gold coins could be collected by the government (e.g. the king or the ruler of
the region), melted down, mixed with other metals such as silver, copper or lead, and
reissued at the same nominal value. By diluting the gold with other metals, the
government could increase the total number of coins issued without also needing to
increase the amount of gold used to make them. When the cost of each coin is lowered
in this way, the government profits from an increase in seignior age. This practice would
increase the money supply but at the same time lower the relative value of each coin. As
the relative value of the coins decrease, consumers would need more coins to exchange
for the same goods and services. These goods and services would experience a price
increase as the value of each coin is reduced.

By the nineteenth century, economists categorized three separate factors that cause a rise
or fall in the price of goods: a change in the value or resource costs of the good, a


change in the price of money which then was usually a fluctuation in metallic content in
the currency, and currency depreciation resulting from an increased supply of currency
relative to the quantity of redeemable metal backing the currency. Following the
proliferation of private bank note currency printed during the American Civil War, the
term quot;inflationquot; started to appear as a direct reference to the currency depreciation that
occurred as the quantity of redeemable bank notes outstripped the quantity of metal
available for their redemption. The term inflation then referred to the devaluation of the
currency, and not to a rise in the price of goods.
This relationship between the over-supply of bank notes and a resulting depreciation in
their value was noted by earlier classical economists such as David Hume and David
Ricardo, who would go on to examine and debate to what effect a currency devaluation
(later termed monetary inflation) has on the price of goods (later termed price inflation,
and eventually just inflation).

Related definitions

The term quot;inflationquot; usually refers to a measured rise in a broad price index that
represents the overall level of prices in goods and services in the economy. The
Consumer Price Index (CPI), the Personal Consumption Expenditures Price Index
(PCEPI) and the GDP deflator are some examples of broad price indices. The term
inflation may also be used to describe the rising level of prices in a narrow set of assets,
goods or services within the economy, such as commodities (which include food, fuel,
metals), financial assets (such as stocks, bonds and real estate), and services (such as
entertainment and health care). The Reuters-CRB Index (CCI), the Producer Price
Index, and Employment Cost Index (ECI) are examples of narrow price indices used to
measure price inflation in particular sectors of the economy.

Core inflation is a measure of price fluctuations in a sub-set of the broad price index

41

which excludes food and energy prices. The Federal Reserve Board uses the core
inflation rate to measure overall inflation, eliminating food and energy prices to mitigate
against short term price fluctuations that could distort estimates of future long term
inflation trends in the general economy.

Other related economic concepts include: deflation – a fall in the general price level;
disinflation – a decrease in the rate of inflation; hyperinflation – an out-of-control
inflationary spiral; stagflation – a combination of inflation, slow economic growth and
high unemployment; and reflation – an attempt to raise the general level of prices to
counteract deflationary pressures.

MEASURES
Inflation is usually measured by calculating the inflation rate of a price index, usually
the Consumer Price Index. The Consumer Price Index measures prices of a selection of
goods and services purchased by a quot;typical consumerquot;. The inflation rate is the
percentage rate of change of a price index over time.

For example, in January 2007, the U.S. Consumer Price Index was 202.416, and in
January 2008 it was 211.080. The formula for calculating the annual percentage rate
inflation in the CPI over the course of 2007 is

(211.080 -202.416) / 202.416 =4.28%


A consumer price index (CPI) is a measure of the average price of consumer goods and
services purchased by households. It is a price index determined by measuring the price
of a standard group of goods meant to represent the typical market basket of a typical
urban consumer. [1]Related, but different, terms are the CPI, the RPI, and the RPIX
used in the United Kingdom. It is one of several price indexes calculated by most
national statistical agencies. The percent change in the CPI is a measure of inflation. The
CPI can be used to index (i.e., adjust for the effects of inflation) wages, salaries,
pensions, or regulated or contracted prices. The CPI is, along with the population census
and the National Income and Product Accounts, one of the most closely watched
national economic statistics.

Two basic types of data are needed to construct the CPI: price data and weighting data.
The price data are collected for a sample of goods and services from a sample of sales

outlets in a sample of locations for a sample of times. The weighting data are estimates
of the shares of the different types of expenditure as fractions of the total expenditure
covered by the index. These weights are usually based upon expenditure data obtained
for sampled periods from a sample of households. Although some of the sampling is
done using a sampling frame and probabilistic sampling methods, much is done in a
commonsense way (purposive sampling) that does not permit estimation of confidence
intervals. Therefore, the sampling variance is normally ignored, since a single estimate
is required in most of the purposes for which the index is used. Stocks greatly affect this
cause.

The index is usually computed yearly, or quarterly in some countries, as a weighted
average of sub-indices for different components of consumer expenditure, such as food,

43

housing, clothing, each of which is in turn a weighted average of sub-sub-indices. At the
most detailed level, the elementary aggregate level, (for example, men's shirts sold in
department stores in San Francisco), detailed weighting information is unavailable, so
elementary aggregate indices are computed using an unweighted arithmetic or geometric
mean of the prices of the sampled product offers. (However, the growing use of scanner
data is gradually making weighting information available even at the most detailed
level.) These indices compare prices each month with prices in the price-reference
month. The weights used to combine them into the higher-level aggregates, and then
into the overall index, relate to the estimated expenditures during a preceding whole
year of the consumers covered by the index on the products within its scope in the area
covered. Thus the index is a fixed-weight index, but rarely a true Laspeyres index, since
the weight-reference period of a year and the price-reference period, usually a more
recent single month, do not coincide. It takes time to assemble and process the
information used for weighting which, in addition to household expenditure surveys,
may include trade and tax data.

Ideally, the weights would relate to the composition of expenditure during the time
between the price-reference month and the current month. There is a large technical
economics literature on index formulae which would approximate this and which can be
shown to approximate what economic theorists call a true cost of living index. Such an

Index would show how consumer expenditure would have to move to compensate for
price changes so as to allow consumers to maintain a constant standard of living.
Approximations can only be computed retrospectively, whereas the index has to appear
monthly and, preferably, quite soon. Nevertheless, in some countries, notably in North
America and Sweden, the philosophy of the index is that it is inspired by and
approximates the notion of a true cost of living (constant utility) index, whereas in most
of Europe it is regarded more pragmatically.


The coverage of the index may be limited. Consumers' expenditure abroad is usually
excluded; visitors' expenditure within the country may be excluded in principle if not in
practice; the rural population may or may not be included; certain groups such as the
very rich or the very poor may be excluded. Saving and investment are always excluded,
though the prices paid for financial services provided by financial intermediaries may be
included along with insurance.

The index reference period, usually called the base year, often differs both from the
weight-reference period and the price reference period. This is just a matter of rescaling
the whole time-series to make the value for the index reference-period equal to 100.
Annually revised weights are a desirable but expensive feature of an index, for the older
the weights the greater is the divergence between the current expenditure pattern and
that of the weight reference-period.

Weights and sub-indices

Weights can be expressed as fractions or ratios summing to one, as percentages
summing to 100 or as per mille numbers summing to 1000. In the European Union's
Harmonised Index of Consumer Prices, for example, each country computes some 80
prescribed sub-indices, their weighted average constituting the national Harmonised
Index. The weights for these sub-indices will consist of the sum of the weights of a

45

number of component lower level indexes. The classification is according to use,
developed in a national accounting context. This is not necessarily the kind of
classification that is most appropriate for a Consumer Price Index. Grouping together of
substitutes or of products whose prices tend to move in parallel might be more suitable.

For some of these lower level indexes detailed reweighing to make them be available,
allowing computations where the individual price observations can all be weighted. This
may be the case, for example, where all selling is in the hands of a single national
organization which makes its data available to the index compilers. For lower level
indexes, however, the weight will consist of the sum of the weights of a number of
elementary aggregate indexes, each weight corresponding to its fraction of the total
annual expenditure covered by the index. An 'elementary aggregate' is a lowest-level
component of expenditure, one which has a weight but within which, weights of its sub-
components are usually lacking. Thus, for example: Weighted averages of elementary
aggregate indexes (e.g. for men’s shirts, raincoats, women’s dresses etc.) make up low
level indexes (e.g. Outer garments),

Weighted averages of these in turn provide sub-indices at a higher, more aggregated
level,(e.g. Clothing) and Weighted averages of the latter provide yet more aggregated
sub-indices (e.g. Clothing and Footwear).
Some of the elementary aggregate indexes, and some of the sub-indexes can be defined
simply in terms of the types of goods and/or services they cover, as in the case of such
products as newspapers in some countries and postal services, which have nationally
uniform prices. But where price movements do differ or might differ between regions or
between outlet types, separate regional and/or outlet-type elementary aggregates are
ideally required for each detailed category of goods and services, each with its own
weight. An example might be an elementary aggregate for sliced bread sold in
supermarkets in the Northern region.


Most elementary aggregate indexes are necessarily 'unweighted' averages for the sample
of products within the sampled outlets. However in cases where it is possible to select
the sample of outlets from which prices are collected so as to reflect the shares of sales
to consumers of the different outlet types covered, self-weighted elementary aggregate
indexes may be computed. Similarly, if the market shares of the different types of
product represented by product types are known, even only approximately, the number
of observed products to be priced for each of them can be made proportional to those
shares.

Estimating weights
The outlet and regional dimensions noted above mean that the estimation of weights
involves a lot more than just the breakdown of expenditure by types of goods and
services, and the number of separately weighted indexes composing the overall index
depends upon two factors:
1. The degree of detail to which available data permit breakdown of total consumption
expenditure in the weight reference-period by type of expenditure, region and outlet
type.
2. Whether there is reason to believe that price movements vary between these most
detailed categories.
How the weights are calculated, and in how much detail, depends upon the availability
of information and upon the scope of the index. In the UK the RPI does not relate to the
whole of consumption, for the reference population is all private households with the
exception of a) pensioner households that derive at least three-quarters of their total
income from state pensions and benefits and b) “high income households” whose total
household income lies within the top four per cent of all households. The result is that it
is difficult to use data sources relating to total consumption by all population groups.

47

For products whose price movements can differ between regions and between different
types of outlet:
The ideal, rarely realizable in practice, would consist of estimates of expenditure for
each detailed consumption category, for each type of outlet, for each region.
At the opposite extreme, with no regional data on expenditure totals but only on
population (e.g. 24% in the Northern region) and only national estimates for the shares
of different outlet types for broad categories of consumption (e.g. 70% of food sold in
supermarkets) the weight for sliced bread sold in supermarkets in the Northern region
has to be estimated as the share of sliced bread in total consumption × 0.24 × 0.7.

The nature of the data used for weighting
No firm rules can be suggested on this issue for the simple reason that the available
statistical sources differ between countries. However, all countries conduct periodical
Household Expenditure surveys and all produce breakdowns of Consumption
Expenditure in their National Accounts. The expenditure classifications used there may
however be different. In particular: Household Expenditure surveys do not cover the
expenditures of foreign visitors, though these may be within the scope of a Consumer
Price Index.

National Accounts include imputed rents for owner-occupied dwellings which may not
be within the scope of a Consumer Price Index. Even with the necessary adjustments,
the National Account estimates and Household Expenditure Surveys usually diverge.

The statistical sources required for regional and outlet-type breakdowns are usually
weaker. Only a large-sample Household Expenditure survey can provide a regional
breakdown. Regional population data are sometimes used for this purpose, but need
adjustment to allow for regional differences in living standards and consumption


patterns. Statistics of retail sales and market research reports can provide information for

estimating outlet-type breakdowns, but the classifications they use rarely correspond to
COICOP categories.

The increasingly widespread use of bar codes and scanners in shops has meant that
detailed cash register printed receipts are provided by shops for an increasing share of
retail purchases. This development makes possible improved Household Expenditure
surveys, as Statistics Iceland has demonstrated. Survey respondents keeping a diary of
their purchases need to record only the total of purchases when itemized receipts were
given to them and keep these receipts in a special pocket in the diary. These receipts
provide not only a detailed breakdown of purchases but also the name of the outlet.
Thus response burden is markedly reduced, accuracy is increased, and product
description is more specific and point of purchase data are obtained, facilitating the
estimation of outlet-type weights. There are only two general principles for the
estimation of weights: use all the available information and accept that rough estimates
are better than no estimates.

Reweighing
Ideally, in computing an index, the weights would represent current annual expenditure
patterns. In practice they necessarily reflect past expenditure patterns, using the most
recent data available or, if they are not of high quality, some average of the data for
more than one previous year. Some countries have used a three-year average in
recognition of the fact that household survey estimates are of poor quality. In some
cases some of the data sources used may not be available annually, in which case some
of the weights for lower level aggregates within higher level aggregates are based on
older data than the higher level weights.
Infrequent reweighing saves costs for the national statistical office but delays the
introduction into the index of new types of expenditure. For example, subscriptions for

49

Internet Service entered index compilation with a considerable time lag in some
countries, and account could be taken of digital camera prices between re-weightings

Only by including some digital cameras in the same elementary aggregate as film
cameras.

Other widely used price indices for calculating price inflation include the following:

Cost-of-living indices (COLI) are indices similar to the CPI which are often used to
adjust fixed incomes and contractual incomes to maintain the real value of those
incomes.

Producer price indices (PPIs) which measures average changes in prices received by
domestic producers for their output. This differs from the CPI in that price subsidization,
profits, and taxes may cause the amount received by the producer to differ from what
the consumer paid. There is also typically a delay between an increase in the PPI and
any eventual increase in the CPI. Producer price index measures the pressure being put
on producers by the costs of their raw materials. This could be quot;passed onquot; to
consumers, or it could be absorbed by profits, or offset by increasing productivity. In
India and the United States, an earlier version of the PPI was called the Wholesale Price
Index.
Core price indices: because food and oil prices can change quickly due to changes in
supply and demand conditions in the food and oil markets, it can be difficult to detect
the long run trend in price levels when those prices are included. Therefore most
statistical agencies also report a measure of 'core inflation', which removes the most
volatile components (such as food and oil) from a broad price index like the CPI.
Because core inflation is less affected by short run supply and demand conditions in
specific markets, central banks rely on it to better measure the inflationary impact of


current monetary policy.

SCRIPT FOR INFLATION

VIDEO &
BACKGROUND AUDIO
MUSIC

Definition of Inflation

We often complain about prices that are going up—Gasoline—airline
tickets—medical costs…These are individual prices. Economists are also
concerned about the general level of prices increasing. When inflation
occurs, a dollar of your income will purchase fewer goods and services than
it used to. Or, put another way, it takes the average American more money
to purchase the same amount of goods and services.

Calculation of the Consumer Price Index:

Audio: The best-known measure of inflation in the US is the CPI—or
consumer price index. Compiled by the Bureau of Labor Statistics, the CPI

51

is a statistical measure of changes in prices of goods and services bought by
urban families. This index is often called the ‘cost of living index’ and is
used the government to adjust Social Security benefits, by labor unions to
adjust wages. Each month the BLS checks the prices of some 300 goods and
services typically purchased by American consumers. The changes in the
average prices of these goods are related to their price in a ‘base year’. The
base year is the period we are comparing to, and at the moment we are using
1982-84 as that base period. So the CPI for 1982-84=100.

CPI= Current prices of the market basket of goods x 100
price of the same basket in base year

So—as you can see, if the current year and the base year are the same, then
the CPI in the base year is always equal to 100. If the index is higher than
100, it means that prices are higher than in the base year, if the index is under
100—it means that prices are less.
Calculation of Inflation Rate

a. Percentage Change in Inflation Rate

To calculate the rate of inflation or percentage change in prices:

Subtract the CPI in the base year from the current year and divide by the base
year, then multiply by 100.
For example:
If the CPI in 2001=177.1
2002=179.9


Then the % Change in the price level is calculated by:
(179.9-177.1)/177.1 x 100
2.8/177.1 x 100 or .0158 x 100 =1.58% increase in prices from 2001 to
2002

Rule of 70

This is an easy way to find the number of years it will take for prices to
double: Divide 70 by the annual rate of inflation.
For example, if the annual inflation rate is 2 percent then divide 70 by
2 and it will take approximately 35 years for prices to double.
However if the inflation rate is 4 it will take………………… (Pause) that’s
right…prices will double in only 17 and half years.

Types of Inflation

While inflation is the rate of increase in average prices, it is important
to understand some of the causes of inflation. Economists are concerned
about two primary causes, Demand-Pull and Cost-Push.

Demand-Pull:

Demand-pull inflation occurs when households, businesses,
governments, and net foreign trade spending is going up faster than the
ability of the economy to produce these goods and services. Sometimes you
will hear this expressed as ‘too many dollars chasing too few goods’. If
resources are already employed at (or near) capacity, more demand simply

53

leads to higher prices –Sort of like going to an auction where there is only
one item and lots of people are bidding on it. This can also be caused by the
Central bank (The FED) increasing the money supply more rapidly than the
output of goods and services.
Cost Push Inflation

Three Stages of inflation related to GDP
major unemployment
intermediate
full employment

Cost-Push:

Prices sometimes increase because wages and raw material costs go
up. This is described as ‘cost push inflation and occurs on the supply side.
Cost-push inflation is the result of rising per unit production costs that ‘push’
prices up. For example, auto workers get a pay increase but don’t produce
more cars, so the per unit production costs of automobiles goes up and this
puts a squeeze on profit margins, so the automobile companies are willing to
provide the automobiles but only at a higher price.

The major source of cost-push inflation is Supply Shocks

Supply shocks are abrupt increases in the costs of important raw
materials. For example, in 1973-74 when OPEC rapidly increased oil prices
—the effects were felt throughout the American economy—rising fuel costs


for workers going to and from work, goods being transported, and even the
energy used to produce electricity and petroleum related goods.
Redistributive Effects of Inflation

Increasing prices affect some people more than others. Some are even
helped by rising prices—but no matter which, all of us will have some
redistribution of our income and changes in our buying behaviors when
prices go up.
Economic and Social Costs of Inflation

Visual: Real
Value=(Nominal nominal vs. real income
Value)/(Price Index/
100) Nominal income is the income we receive when we cash our paychecks.
Nominal values are not comparable over time because of changes in the price
level. So we calculate ‘real’ values by adjusting for changes in the average
level of prices.
Another way of looking at this shows us how much a person’s real income is
affected by price changes:

Percentage change in real income=percentage change in nominal-percentage
change in price level.

For example, if you get a 3 percent pay increase while prices go up by 5
percent, your ‘real’ income has….. (Pause) gone down by 2 percent!!!

INFLATION REDISTRIBUTES INCOME:

55

Those people who live on a fixed income (income that doesn’t change) are
hurt by inflation. Many retirees, who planned their retirement based on
prices from yesteryear, find that they do not have the purchasing power they
used to. Minimum wage workers, unable to get pay increases because of
their lack of skills find that their ‘fixed’ paychecks buy less as prices rise.

Likewise people who save money find that their money is less valuable in the
future. One measure is:

The absolute value of their future purchasing power declines when the
inflation rate exceeds the interest rate.

Creditors are also hurt. If you loan $1000 to your friend Mary to be paid
back in five years (no interest, right?) and there is inflation over that five
years, you will be paid back in ‘cheaper’ dollars—that is the future value of
your $1000 will buy less than it does today.
WHO IS Unaffected or HELPED?

Remember Mary, when she pays back your $1000 5 years later, she
is really paying back in dollars with less purchasing power, so as a debtor she
is better off because of inflation. Those American families who purchased
housing many years ago with a 30-year mortgage are paying back in
‘cheaper’ dollars.

Some workers have a cost of living adjustment, or ‘COLA’ clause in
their contract—and when there is 3 percent inflation, their nominal wages go
up by the same amount, thus negating the effects of a price increase.
Another major group of income recipients with a cost of living adjustment is


Social Security recipients.

Anticipated Inflation

Today, many lenders are aware of the impact of inflation on their real return,
so anticipating inflation, they build it into their interest rates, thus:

The real interest rate=nominal – inflation rate.

Discussion of major U.S. inflationary periods 1960-present
Although for the most of the last half of the century, inflation was low—in
the US we did suffer from major inflationary pressures during the decade of
the 1970s when prices rose as much as 11% in 1974 and 13.5% in 1980. In
the decade from 1972 to 1982 prices in the US increased by over 130
percent!!

Define hyperinflation and discuss its impact on real output using historical
international example (Germany 1920s)

When inflation is extremely rapid we refer to ‘hyperinflation’ and the
impact can be devastating! Such was the case in Germany in the 1920s
where the price level went up by 1380 percent 1923. Some examples of this
‘hyperinflation’ can be seen in changes in such everyday items as milk and
bread.

57

Hyperinflation in Germany
Item Price in Marks
Aug 1923 Sept 23 Nov 23

Liter milk 38,000 8,400,000 350,000,000,000
1b butter 900,000 100,000,000
loaf bread 90,000 27,000,000
bacon 950,000 130,000,000
By November 1923 the dollar stood at 65,000,000,000 as compared to only
64 marks 30 months earlier!!!

International Impact of Inflation:
Remember that what happens in our country or in countries with whom we
trade, it will have an effect on our economy. For example, when there is
high inflation in the US, it means that our goods are more expensive for
foreigners and therefore sale of many of our exports fall, fewer foreigners
visit our country, and there is downward pressure on our GDP.


Inflation Measures in India

WPI in India is used extensively for short term policy intervention because it is the only
index that is available on a weekly basis with a two weeks’ lag. In principle, inflation
requires to be managed with respect to changes in prices of final goods or consumer
prices. A number of consumer price indices like Consumer Price index for Industrial
Workers (CPI-IW), for Agricultural Laborers (CPI-AL), and for Urban Non-Manual
Employees (CPI-UNME) are compiled on a monthly basis.

The Labor Bureau of Government of India prepares the CPI-IW. It attempts to measure
changes in the retail prices of fixed baskets of goods and services being consumed by
the target group (namely the average working class family). Based on the Income and

59

Expenditure survey by NSSO in 78 selected centers, this index is constructed on a
monthly basis. The weighting diagram for this index has been constructed on the basis
of average monthly family expenditures on consumption groups: food, Pan, Supari and
Tobacco, fuel and light, housing, cloth, bedding and miscellaneous (including medical
care, education, recreation, transport, communication etc.). This index is also used for
determining the dearness allowances to be paid to Central and State Government
employees and to industrial workers besides fixation and revision of minimum wages to
scheduled employments. The coverage of CPI-IW is broader than that for CPI-AL and
for CPI-UNME. The CPI-AL and CPI-UNME are designed for specific groups of
population with the main objective of measuring the impact of increase in prices on
rural and urban poverty. The CPI-IW captures to some extent the price increase in the
service sector.

One comprehensive alternative measure for inflation comes from the implicit price
deflator of GDP. This is an annual series, which is available with a lag of two years.
More recently, the quarterly series of GDP have become available but from time to time
data revisions compromise its usability for inflation-related price interventions. For
these reasons, the WPI continues to be used extensively for measuring inflation and for
related policy interventions. This can however be justified only if it is a reliable
predictor of the CPI inflation. We need to verify empirically whether the WPI inflation
is a good predictor of CPI inflation.


India Inflation Rate in last year

India Inflation Rate chart, historical data, forecast and news. Inflation rate refers to a
general rise in prices measured against a standard level of purchasing power. The most
well known measures of Inflation are the CPI which measures consumer prices, and the
GDP deflator, which measures inflation in the whole of the domestic economy.

61

Dec
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

5.51
2008 4.84 5.23 6.02 7.81

5.07
2007 7.36 7.81 7.56 7.74 6.79 6.08 6.86 6.41 5.74 5.48 5.10

6.94
2006 5.00 4.80 5.00 4.97 5.84 6.47 5.71 6.14 7.02 7.17 6.70

Variation in Annual Inflation since last year
Inflation, as measured by year-on-year variations in the wholesale price index (WPI),
fell by more than half from its intra-year peak of 12.91 per cent on August 2, 2008 to
5.60 per cent by January 10, 2009. While prices of primary articles and manufactured


products increased, fuel prices declined. In terms of relative contribution to decelerating
headline inflation between August 2, 2008 and January 10, 2009, petroleum and basic
metals (combined weight of 13.2 per cent in WPI) together accounted for 79.4 per cent,
followed by ‘oilseeds, edible oils & oil cakes’ (16.4 per cent). Clearly, the fall in
commodity prices reflecting global trends has been the key driver of the sharp fall in
WPI inflation although effective management of domestic demand too has contributed
to this moderation.

Table: Annual Inflation Rate (%)

January 12, 2008January 10, 2009
Wholesale Price Index (WPI)
(y-o-y)
(y-o-y)
5.60
WPI - All Commodities 4.36
11.64
WPI - Primary Articles 4.49
-1.32
WPI - Fuel Group 3.69
5.90
WPI - Manufactured Products 4.57
7.53
WPI - Excluding Fuel 4.55
6.52
WPI - Excluding Food and Fuel 5.21
2007December 2008
Consumer Price Index (CPI) December
(y-o-y)
(y-o-y)
10.45
1. CPI for Industrial Workers* 5.51
11.14
2. CPI for Agricultural Laborers 5.90
11.14
3. CPI for Rural Laborers 5.63
10.79
4. CPI for Urban Non-Manual Employees* 5.06

On the other hand, inflation based on various consumer price indices (CPIs) is still in

63

double digits due to the firm trend in prices of food articles and the higher weight of
food articles in measures of consumer price inflation. As the decline in input prices
percolates over time to the prices of manufactured and other products, consumer price
inflation too is expected to soften in the months ahead. For its overall assessment of
inflation outlook for policy purposes, the Reserve Bank continues to monitor the full
array of price indicators.


Early warnings

Seasonally adjusted data is well suited for short term forecasting. For this, a variety of
econometric models can be applied to the seasonally adjusted data. In order to obtain
greater intuition into the usefulness of seasonal adjustment, we merely examine the data
looking for large values.

The 6% threshold for a `high inflation episode' works out to the 60th percentile of the
data. The 60th percentile of the POP SA WPI inflation works out to an annualized value
of 6.65%. Hence, we done a high inflation episode as year-on-year inflation exceeding
6% and consider the consequences of putting out an early warning when the POP SA
inflation exceeds 6.65%. In the following tables, these `high inflation episode' or
`warning' values are shown in boldface.

In order to obtain estimates of the real interest rate at the short-end of the yield, forward-
looking estimates of inflation are required. In this, we seek to adjust the nominal rate for
the 90 day maturity using inflation forecasts for a 90 day horizon. To achieve this, the
POP SA data is used to make forecasts, for the coming three months. At each month,
information available till that month is used to estimate the AR model, and to make
forecasts for POP SA inflation over the coming three months using this model. The
average of these three forecasts is used to convert the nominal short-term interest rate
into the short-term real rate.

65

Example: the high inflation episode of 1994-95
A large POP SA change took place in April 1994. This may be partly related to
statistical measurement issues of WPI. At this time, the 90 day interest rate in the
economy was 7.36%. In the following two months, POP SA
Inflation showed large values of 7.17% and 16.78%. Large values for POP SA inflation
are visible till May 1995. In this period, monetary policy was; the short-term rate
became negative in real terms. The short-term rate was negative in real terms all the way
till January 1995. From June 1995 onwards, POP SA inflation dropped sharply.
However, large values for YOY inflation continued to be recorded, since YOY inflation
is the average of the last 12 values for POP inflation.

Monetary policy tightening is visible right from the start. The real rate, which was
negative, started rising. In June 1995, when POP SA inflation had started easing, the
real rate was +2.21%. The short term rate stayed above 2% in real terms till August
1996. Over this period, YOY WPI inflation ebbed away. However, when judged by POP
SA data, WPI inflation had subsided 14 months earlier, by June 1995. Examining POP
SA data does not substantially alter the date at which the tightening began. However,
POP SA inflation had subsided by June 1995, which suggests that the easing could have
begun earlier and progressed faster. In this period, the use of POP SA data would have
given a useful early warning that inflation had subsided.

Example: the high inflation episode of 2007
Going by the year-on-year series, the high inflation episode erupted in January 2007 and
ended in April 2007. The POP SA data, however, shows a very divergent picture. It
shows that the high inflation episode began in May 2006: an early warning of 8 months.


POP SA inflation was high in the period from
May 2006 till October 2006: over this period, inflation averaged 7.81%.
The inflationary pressures subsided by October 2006, before the high inflation episode
had even showed up in the year-on-year data. To the extent that policy responses took
place after October 2006, they were possibly in the wrong direction. In the critical
period from May 2006 to October 2006, when there was high inflation, monetary policy
was expansionary. Monetary policy tightening is visible much later. The real rate went
up from -0.55% in September 2006 to 3.35% in June 2007. Inflation had subsided
before the tightening began.

Example: the high inflation episode of 2008
From December 2007 onwards, inflation pressures were visible in the POP SA data.
They burst into the public consciousness in March 2008, with reports of high YOY WPI
inflation. The use of POP SA data would have given an early warning by three months.
A high rate of POP SA inflation is visible all the way to the latest data for July 2008.
The future evolution of this high inflation episode is as yet unclear. The short term real
interest rate was at 2.59% in November 2007, the last month prior to large inflation
shocks. This plunged to -4.50% in March 2008. At a time of positive inflationary
shocks, monetary policy was expansionary. Real rates remain very low when compared
with those required to rein inflation. The last observation of the real rate, -0.88% in July
2008, remained much below the level of +2.59% in November 2007, before this
inflationary episode began. This suggests that until July 2008, monetary policy
tightening aiming to combat inflation has not taken place.

67

Looking forward into the high inflation episode of 2008
How might inflation play out in coming months? The key issue that is of importance is
inflation persistence. If economic agents build inflationary expectations into their
decisions, this will lead to persistence of inflation. The WPI fuel and WPI primary have
substantial external and policy influences. It is WPI manufacturing which is primarily
influenced by the behavior of the private sector.
It shows strong positive autocorrelations in the early months. This shows the extent of
inflation persistence which is now found in India. Through this inflation persistence, the
recent shocks to POP SA WPI manufacturing are likely to be correlated with further
above-trend values in coming months.

There were large shocks to WPI Primary from December 2007 to March 2008. WPI
Fuel had large shocks in many of the months also. WPI Manufacturing shows high
inflation for almost all the months shown. The key question that arises after the March
shock is that of inflation persistence. To the extent that economic agents are placed in a
well structured monetary policy framework, their inflation expectations get anchored. A
large shock like the March shock then does not generate further reverberations. In the
Indian setting, inflation persistence did arise: with WPI Manufacturing inflation of
13.8% in April, 10.04% in May, 12.7% on June and 11.15% in July. The simplest notion
of forecasting is that of undertaking uni-variate time series forecasting using ARMA
models of the POP SA series. These models have no economic content; they do not
react the impact of economic considerations such as the expansionary stance of


monetary policy with negative real rates, the coming fuel price rises or the inflationary
impact of the recent rupee depreciation. Given the greater inflation persistence in WPI
manufacturing, the recent positive shocks to WPI manufacturing are projected to induce
positive shocks in the coming six months of data. In the case of the overall WPI, there is
a faster convergence to the long-term mean, given lower persistence.

Figures restate these forecasts for the POP SA series into point estimates for the
forecasted levels of the two price indexes. Figure 7 and Figure 8 restate these point
estimates into the familiar year- on-year inflation estimates which are widely used in
India. This suggests that WPI inflation may worsen towards the end of the year before
declining. However, even by June 2009, YOY WPI inflation may continue to be in the
region of 8%. It should be emphasized that these forecasts have no economic content.
They do not relate economic policy issues such as expansionary monetary policy with
negative real rates, the inflationary impact of the recent currency depreciation, the
impending price rises of petroleum products, etc. They merely project the POP SA
series for WPI and WPI manufacturing into the future using ARMA models; they
efficiently utilize the autocorrelation structure of these series for the purpose of
forecasting.

69

Assuming the rate of cost inflation index is same as in the past 25 years, a bar chart has
been developed for the financial years from 2005-06 to 2030-31 taking the index figure
of year 1981-82 as the base for the year 2005-06 which reflects “How the inflation robs
the purchase power of a person?”.


Assuming the rate of inflation is same as in the past 25 years

7.00
Cost Inflation Index Converted

6.00
6.00

5.00
to Rs. in Lakhs

4.26
4.00
3.05
3.00
1.99
2.00
1.40
1.00
1.00

0.00
2005-06 2010-11 2015-16 2020-21 2025-26 2030-31
Financial Year

How inflation eats up the money?

Inflation is an economic concept... What is important to us is the effect of inflation! The
effect of inflation is the prices of everything going up over the years.

A movie ticket was for a few paisas in my dad’s time. Now it is worth Rs.150. My dad’s
first salary for the month was Rs.400 and over the years it has now become Rs.20, 000.
This is what inflation is, the price of everything goes up. Because the price goes up, the
salaries go up?

If we really thing about it, inflation makes the worth of money reduce. What you could
buy in my dad’s time for Rs.10, now a days you will not be able to buy for Rs.500 also.
The worth of money has reduced! If this is still not clear consider this, when my father
was a kid, he used to get 50paise pocket money. He used to use this money to go and
watch a movie (At that time we could watch a movie for50paise!)
Now, just for the sake of understanding assume that my dad decided in his childhood to

71

save 50paise thinking, that one day when he becomes big, he will go for a movie. Many
years pass. My dad goes to the theater and asks for a ticket. He offers the ticket-booth-
guy at the theater 50paise and asks for a ticket. The ticket booth guy says, “I am sorry
sir, the ticket is worth Rs.50. You will not be able to even buy a “paan” with the
50paise!!”
The moral of the story is that, the worth of the 50paise reduced dramatically. 50paise
could buy a whole lot when my dad was a kid. Now, 50paise can buy nothing. This is
inflation. This tells us two important things:

Firstly: Do not keep your money stagnant. If you just save money by putting it your
safe it will loose value over time. If you have Rs.1000 in your safe today and you keep it
there for 10years or so, it will be worth a lot less after 10 years. If you can buy
something for Rs.1000 today, you will probably require Rs.1500 to buy it 10 years from
now. So do not keep money locked up in your safe.

Always invest money.

If you can’t think where to invest your money, then put it in a bank. Let it grow by
gaining interest. But whatever you do, do not just lock your money up in your safe and
keep it stagnant. If you do this, you will be loosing money without even knowing it. The
more money you keep stagnant the more money you will be loosing.
Secondly: When investing, you have to make sure that the rate of return on your
investment is higher than the rate of inflation.

What is the rate of inflation?

As we said earlier, the price of everything goes up over time and this phenomenon is
called inflation. The question is: By how much do the prices go up? At what rate do the
prices go up?


The rate at which the prices of everything go up is called the quot;rate of inflationquot;. For
example, if the price of something is Rs.100 this year and next year the price becomes
approximately Rs.104 then the rate of inflation is 4%. If the price of something is Rs.80
then after a year with a rate of inflation of 4% the price go up to (80 x 1.04) = 83.2
So, when you make an investment, make sure that your rate of return on the investment
is higher than the rate of inflation in your country. In our county India, for the year
2005-2006 the rate of inflation was 4% (Which is really low and amazing!). This rate
keeps changing every year. The finance minister generally gives the official statement
on the inflation rate of the country for a particular year.
What is the rate of return?
The rate of return is how much you make on an investment. Suppose you invest Rs.100
in the market and over a year, you make Rs.120, then you rate of return is 20%.
If you invest Rs.100 in the market today and you make money at a 3% quot;rate of returnquot; in
one year you will have Rs.103. But now, since the rate of inflation is at 4%, an item
costing Rs.100 today will cost Rs.104 a year from now. So what you can buy with
today’s Rs.100, you will only be able to buy with Rs.104 a year from now.
But the Rs.100 that you invested has grown only at a 3% rate of return and so it is worth
Rs.103.In effect you are loosing your money So in conclusion, the rate of return on your
investments, have to be higher than the inflation.

HOW INFLATION DISTORTING THE INVESTMENT
DECISIONS TOWARDS INSURANCE?

To understand the impact of inflation on the consumer perception towards insurance, it
is firstly very important to understand how the inflation distorting the investment
decision of the consumer and consumption pattern of the consumer. Insurance is one of
the most important saving and investment option for the consumer.

73

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