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Measuring inflation
Nikhil Patel and Agustín Villar^1
Abstract
This note focusses on key issues-both conceptual and practical- with regard to the
measurement of inflation such as the tradeoff between different measures and the
incorporation of prices not fully determined by market forces of supply and demand.
It also draws on a recent survey of emerging market economy central banks
conducted by the BIS to highlight specific issues faced by these economies and how
the resulting inflation indices differ across countries.
Keywords: Price index, Inflation measurement
JEL classifications: E31, P24, P
(^1) Bank for International Settlements. Diego Urbina provided excellent research assistance. The paper
draws on a recent BIS survey of emerging market economy central banks that was conducted specifically for this meeting.
Introduction
Broadly considered, there are two main rationales for measuring inflation. First,
inflation reduces welfare. Second, inflation provides an indication of the degree of
slack or short-term developments in the economy.^2 The weight given to these
respective elements will determine the definition of inflation used.
How to measure inflation is a highly technical issue and involves many choices
that could have significant consequences for the level and dynamics of the series one
would like to construct. At the same time, it is important to measure inflation in a
transparent and credible way, one that is understood by different constituencies of
society. That said, if the measurement of inflation relies on cost of living estimates
across different groups of the population, such a measurement could vary across
groups; targeting the cost of living index relevant to one specific group might not be
appropriate for another group.
This note reviews different aspects of inflation measurement. Section 1 discusses
what is to be measured. Section 2 reports on alternative prices indices and their
possible biases. Section 3 deals with the challenges faced by emerging market
economy (EME) central banks in appropriately defining and measuring inflation,
focusing in particular on the treatment of administered prices and owner-occupied
housing across a surveyed sample of EME central banks.
- What are we trying to measure?
Inflation acts as a tax on money: high and volatile inflation rates affect negatively the
demand for money. To the extent that money provides services valued by consumers
and producers, inflation imposes a welfare cost. Moreover, inflation can result in
relative price changes in the presence of nominal price and wage rigidities (Vedrin
(2015)), which can create significant welfare costs. How large these welfare costs are
depends, inter alia, on the competitive structure of the economy, government
interference, market imperfections and financial factors. As a consequence, central
banks care about the level and variability of inflation.
The theoretical basis of inflation measurement is the concept of a “composite
good” whose price is measured by a cost-of-goods index. A special case of a cost-of-
goods index is the cost-of-living index (Wynne (2008)), which derives the choice of
goods to be included in the index and their weights from the theory of consumer
behaviour. The relative importance of different goods and services changes in
response to changes in prices and preferences. A fixed bundle of goods is therefore
likely to become less representative as time elapses. Popular cost-of-living indices are
the CPI and retail price index (RPI), both of which measure the rate of change in the
prices of goods and services consumed by households.^3
(^2) Of course, the degree of slack in an economy and other short-term developments are also affected
by other factors not reflected in current inflation rates.
(^3) The difference between these two indices is more historical than conceptual. The RPI originated as a
measure of the cost-of-living needed to maintain healthy living conditions in a working class household in the United Kingdom. However, over time its scope expanded to include all major categories of household expenditure. The CPI, which was originated in the United States, initially valued the expenditure of a clerical urban wage-earner. Later on, coverage was extended to all urban
regulated or administered prices in EMEs, as insurmountable obstacles in the
achievement of their monetary policy objectives. In particular, by choosing the CPI
over other measures of inflation, EME central banks appear to place greater weight
on the welfare cost rationale for measuring inflation than on measures of slack or
short-term developments.
The widespread use of the CPI as the preferred price index in inflation targeting
and other monetary policy strategies in EMEs seems to reflect a number of perceived
advantages. First, the CPI is relatively easy to understand and is the best available
measure of the cost of living faced by consumers. Second, it is familiar to large
segments of the population, regularly reported in the news media, used as a reference
for the provision of government benefits or contracts and is widely followed as an
indicator of macroeconomic stability. Finally, it is available at a relatively high
frequency and is not subject to many revisions, enhancing its transparency and use
in monetary policy (Moreno (2010)).
What measure of inflation and for what?
Summary of questionnaire responses Table 1
Target^1
Other uses^2
Set policy Forecasting Assessment of policy stance
CPI 16 (22) 13 (15) 16 (18) 15 (18)
CPI (core) ... 10 (12) 13 (14) 13 (15)
Import prices^3 ... 1 7 2
GDP deflator ... 1 2 2
Producer price index ... 2 8 7
(^1) Total number of countries that provided information in parenthesis. 2 Number of countries using the CPI (headline) for inflation
targeting and for other uses. 3 Chile uses external prices instead of import prices for forecasting purposes.
Source: BIS survey.
Central banks that target inflation as measured by the CPI also make use of the
inflation index for other aspects of their monetary strategy. Of the 16 central banks
that target consumer price inflation, 13 replied that they also make use of CPI inflation
to set their policy (Table 1). This reveals consistency between the measured target
and the use of this measure in setting the policy rate. The three central banks that do
not set policy on the basis of the CPI tend to use a narrower measure. A few central
banks do not target consumer price inflation in their monetary policy but instead
forecast it (three central banks) and use the forecasts to assess the policy stance (three
others) or set policy (two others).
Many central banks also rely on measures of “core inflation” to forecast inflation,
assess the policy stance and set policy. There is a large overlap in the central banks
that make use of a “core inflation” measure as part of their monetary policy strategy
with those that target a measure of consumer price inflation. But “core” can mean
different things to different countries. It may exclude highly volatile prices (eg those
of foodstuffs and fuel), non-monetary expenditures (eg imputed housing costs for
owner-occupied property or rents) or the effects of changes in taxes, subsidised
prices or rents, and administered prices.
Biases in the measurement of inflation
While the CPI has a central role to play in the monetary policy framework of many
EMEs, there are reasons to believe that it may be biased. The most common
arguments suggest that it typically overestimates inflation. This bias reflects
substitution effects, household heterogeneity, and quality improvement and product
replacement effects. Unless the weights are revised frequently, the index will become
less representative as goods with larger price increases tend to be demanded less
and those with lower prices increases or price decreases tend to be demanded more.
The obvious solution lies in a more frequent updating of the index. However, this
comes at the cost of more frequent expenditure surveys and possibly also perceptions
of index manipulation.
Heterogeneity of household income is a significant potential source of bias in
EMEs. The weights of the CPI are often based on the average share of expenditure
from different groups in society. Because the distribution of expenditure tends to be
skewed, the index is likely to overweight the expenditure patterns of the more affluent
segments of society. This problem might be more serious in EMEs where the
distribution of income is more unequal. The impact on the inflation rate is less clear:
it would depend on the relative prices changes taking place in the economy. If the
prices of goods prominent in the expenditure of households at the higher end of the
income distribution scale are growing faster than those of groups at the lower end,
the measurement of inflation will be biased upwards.
The implications of overestimation have often been flagged in other areas of
public policy such as fiscal policy and the assessment of economic competitiveness.
For example, an upward bias may drive up pensions and social spending more rapidly
than justified by changes in the cost of living. If it is not anticipated, the systematic
overestimation of the inflation rate due to a bias can also have significant
consequences for perceived real interest rates and thus for saving and investment as
well as monetary policy.
The replies to the survey show that half of the 16 central banks have estimates
for the potential bias in CPI inflation, although the type of bias and even sometimes
the sign vary across countries. The central banks of Malaysia, Poland, Russia and
Thailand estimate an upward bias. In Chile, by contrast, the quality bias in the clothing
category imparts a negative bias to inflation as estimated by the CPI. In Malaysia, the
heterogeneity of income is a motive for considerable control of surveys carried out
at five-year intervals. The substitution bias is also monitored with surveys carried out
every six months in order to adjust expenditure shares.
- Some practical issues in measuring inflation
Prices of goods and services that are not freely determined in the market present a
challenge to inflation measurement. Conceptually, it is not always clear whether and
to what extent these prices should be incorporated in an inflation measure used for
conducting monetary policy. Moreover, given the difficulty of estimating and inferring
prices in the absence of explicit markets, it is not always feasible to implement an
optimal index even if one attempts to base it on firm conceptual grounds.^6 Central
banks therefore face the complex task of striking a balance between practice and
(^6) For instance, while in theory it may be optimal to fully incorporate the cost of owner-occupied
housing (an issue discussed in detail below), in practice this may not be feasible in the absence of good proxies for the cost of owner-occupied housing, given the lack of actual market prices.
et al (2010)), presents a challenge for inflation measurement since these prices are
excluded from the computation of economic indices.
3.2 Measuring the price of housing services
Housing services, whether explicitly accounted for by rental payments or implicitly
incorporated in owner-occupied housing estimates, account for a large proportion of
total household expenditure. But houses tend to be big-ticket items that are
purchased infrequently, so the cost of the implicit services provided must be
estimated.^10 This could be done by including house prices directly in the measure of
inflation, for instance through the net acquisition approach that measures the average
change in the price paid by a household to acquire a home, or by estimating implicit
rents. Yet another option is to follow the user cost approach, which covers various
costs of home ownership such as interest payments on mortgages, taxes, insurance,
repairs and maintenance costs (see McCarthy and Peach (2010) and Cecchetti (2007)
for discussions of how those issues are being addressed in advanced economies).^11
Our survey responses show that EME central banks address these issues in very
different ways. As a result, the share of housing in the inflation measures varies widely,
ranging from 1.2% in Hungary to 31.7% in Hong Kong SAR (Appendix
Table 3.2).
While rental prices are relatively easy to obtain and are incorporated by all the
surveyed countries, with the exception of Peru, Saudi Arabia and the United Arab
Emirates, the extent to which owner-occupied housing is covered differs widely. Some
central banks choose to exclude owner-occupied housing completely (Chile, Hungary,
Korea, Malaysia, the Philippines, Poland, Russia and Turkey).^12 This could be either
because they prefer to work with an inflation measure that is representative only of
market prices or because it is not feasible to obtain satisfactory measures. Among the
central banks that do incorporate owner-occupied housing in their inflation measure,
the rental equivalence approach is nearly the unanimous choice (Appendix
Table 3.2).^13 This is consistent with Gillingham (1983), who argues that this is
preferable on both theoretical and empirical grounds.
Even in the case of rents, central banks in our survey highlight potential sources
of bias. Typically, the longitudinal nature of most surveys implies that newly
constructed houses are often underrepresented, leading to a downward bias in
measured inflation. Central banks address this issue in several ways. For instance,
some countries report using rotating samples and replace a certain fraction of the
sample at a specific frequency.^14 Recognising the problem posed by lags between
construction of new housing units and their full incorporation in the rental
(^10) From the point of view of national income accounting, homeowners living in their own houses are
assumed to pay themselves a market rent, which appears as consumption expenditure in GDP. The rationale is that if some or all homeowners become renters or vice versa, GDP should not be affected.
(^11) See Poole et al (2005) for a detailed description and comparison of these methods.
(^12) This is also the approach taken in computing the Harmonised Index of Consumer Prices (HIPC), the
primary inflation measure used by the ECB to set monetary policy for the euro area.
(^13) The only exceptions are Israel, which in addition to the rental equivalence approach gives a small
weight to the cost of insurance and legal services; Chile, which reports using repairs and maintenance services; and the Czech Republic, which reported using the user cost approach in the past, but switched to the rental equivalence approach in 2007.
(^14) One thirty-sixth of the sample is replaced in Korea every month, while one third is replaced by Turkey
every year.
computation programme, the Czech Republic makes annual adjustments based on
finalised construction works and liquidated housing.
Survey attrition, small sample coverage and changes in neighbourhood quality
are some of the other sources of bias that affect the measurement of housing services
for both tenant and owner-occupied units. Israel, for instance, identifies the small
sample of rental housing units as a major potential source of bias and uses a hedonic
estimation routine to address it.
Sometimes the biases are not easy to minimise, and central banks may be left
with little choice but to use an inflation index that excludes housing inflation to reflect
inflationary pressure, as is done by Thailand.
- Alcoholic beverages and tobacco 2.
- Food (controlled price) 1.
- Transport services 0.
- Mexico 14.8 Gasoline 3.
- Electricity 3.
- Public transportation 2.
- Liquefied petroleum gas 1.
- Peru Electricity 2.
- Poland Energy 9.
- Services 5.
- Electricity 4.
- Gas 2.
- Russia Public utilities 5.
- Housing services other than apartment rentals 2.
- Local railway and municipal transportation 1.
- Vital medicines 0.
- Singapore Electricity 3.
- Bus fares 1.
- Train fares 1.
- for foreign domestic worker 0. Household services and supplies: government levy
- South Africa 18.5 Petrol 5.
- Electricity 4.
- Education 3.
- Communication 76.
- Thailand 34.6 Core 19.
- Turkey Energy 6. …
- Alcoholic beverages and tobacco 4.
- United Arab Emirates Gas, electricity and water 5. …
Housing rental cost in the CPI (^) Table 3.
Imputed rent based on: Market rent Net acquisition approach
Rental equivalent approach
User cost approach
Other Share in price index (%)
Chile YES ... ... ... ... 4.
China YES ... YES ... ... 20.
Colombia YES ... YES ... ... 18.
Czech Republic YES ... YES ... ... 13.
Hong Kong SAR YES ... YES ... ... 31.
Hungary YES ... ... ... ... 1.
India YES ... YES ... ... 10.
Indonesia YES ... ... ... ... 8.
Israel YES ... YES ... ... 24.
Korea YES ... ... ... ... 9.
Malaysia YES ... ... ... ... 17.
Mexico YES ... YES ... ... 17.
Peru ... ... YES ... ... 2.
Philippines YES ... ... ... YES 13.
Poland YES ... ... ... ... 1.
Russia YES ... ... ... ... 2.
Saudi Arabia ... ... ... ... ... 20.
Singapore YES ... YES ... ... 22.
South Africa YES ... YES ... ... 0.
Thailand YES ... YES ... ... 15.
Turkey YES ... ... ... ... 5.
United Arab Emirates ... ... ... ... ... 39.
Source: BIS survey responses.
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