Docsity
Docsity

Prepare for your exams
Prepare for your exams

Study with the several resources on Docsity


Earn points to download
Earn points to download

Earn points by helping other students or get them with a premium plan


Guidelines and tips
Guidelines and tips

Measuring Inflation: Challenges and Alternative Approaches in Emerging Markets, Slides of Market economy

Key issues in measuring inflation, focusing on the tradeoff between different measures and the challenges faced by emerging market central banks in defining and measuring inflation, particularly in relation to administered prices and owner-occupied housing. The document also discusses the use of alternative price indices and their potential biases.

Typology: Slides

2021/2022

Uploaded on 09/27/2022

alannis
alannis 🇺🇸

4.7

(13)

263 documents

1 / 13

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
BIS Papers No 89
9
Measuring inflation
Nikhil Patel and Agustín Villar1
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, P44
1 Bank for International Settlements. Diego Urbina provided excellent research assistance. The paper
draws on a recent BIS survey of emergi ng market economy central banks that was conducted
specifically for this meeting.
pf3
pf4
pf5
pf8
pf9
pfa
pfd

Partial preview of the text

Download Measuring Inflation: Challenges and Alternative Approaches in Emerging Markets and more Slides Market economy in PDF only on Docsity!

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.

  1. 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.

  1. 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.
    • Telephone 2.
    • Water 1.
  • 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.
    • Energy 11.
    • Raw foods 3.
  • 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.

References

Agénor, P-R and L Pereira da Silva (2013): Inflation targeting and financial stability: a

perspective from the developing world , Inter-American Development Bank and Centro

de Estudios Monetarios Latinoamericanos.

Cecchetti, S (2007): “Housing in inflation measurement”, voxeu.org, 13 June.

Deaton, A (1998): “Getting prices right: what should be done? ”, Journal of Economic

Perspectives , vol 12, no 1, pp 37–46.

Diewert, E (2010): “On the stochastic approach to index numbers”, in Price and

productivity measurement: vol 6 – Index number theory , pp 235–62.

Frankel, J (2011): “A comparison of product price targeting and other monetary

anchor options for commodity exporters in Latin America”, Harvard Kennedy School

Faculty Research Working Paper Series , no 11-027, July.

Gillingham, R (1983): “Measuring the cost of shelter for homeowners: theoretical and

empirical considerations”, The Review of Economics and Statistics , vol 65, no 2, May,

pp 254–65.

Hanson, C and I Weir (1992): “Measures of inflation”, in The New Palgrave Dictionary

of Money and Finance , vol 2, pp 685–8.

Lebow, D and J Rudd (2008): “Inflation measurement”, in The New Palgrave Dictionary

of Economics , Second Edition.

McCarthy, J and R Peach (2010): “The measurement of rent inflation”, Federal Reserve

Bank of New York, Staff Reports , no 425, January.

Moreno, R (2010): “Some issues in measuring and tracking prices in emerging market

economies”, BIS Papers , no 49, January, pp 13–51.

Poole, R, F Ptacek and R Verbrugge (2005): Treatment of owner-occupied housing in

the CPI , Federal Economic Statistics Advisory Committee (FESAC ), 9 December.

Schneider, F, A Buehn and C Montenegro (2010): “New estimates for the shadow

economies all over the world”, International Economic Journal , vol 24, no 4,

pp 443–61.

Vedrin, A (2015): “Inflation targeting and financial stability: providing policymakers with relevant information”, BIS Working Papers , no 503, July.

Wynne, M (2008): “Core inflation: review of some conceptual issues”, Federal Reserve

Bank of St Louis, Review , Part 2, May/June, pp 205–28.