Price-setting and inflation in India

Jyotirmoy Bhattacharya

March 4, 2011

AbstractWe use disaggregated weekly Wholesale Price Index data to study

the nature of price-setting in the Indian manufacturing sector. Theprimary variables studied are the duration between price changesand the magnitude of price changes. By studying the patterns, deter-minants and cross-sector movements of these variables we hope tobetter understand the inflationary process in India and also bring ev-idence to bear on the debate in macroeconomic theory between mod-els of time-dependent vs. state-dependent price setting.

PRELIMINARY DRAFT. PLEASE DO NOT CITE OR CIRCULATE

1 Introduction

Inflation is a subject of serious public concern and its control is one of thechief tasks of monetary policy. The correct conduct of monetary policydepends on an understanding of the processes that determine the pricelevel and the possible conflicts between the stabilization of inflation andother tasks of monetary policy such as the stabilization of output andemployment. Macroeconomic thinking on these questions is presentlycentered around a “new neoclassical synthesis” (Goodfriend and King,1997; Clarida et al., 1999) that combines explicit intertemporal optimiza-tion, rational expectations and nominal rigidities. Nominal rigidities—the fact that wages and prices are set in money terms and do not changecontinuously—are an essential part of this framework. Without these rigidi-ties it would not be possible to explain the actually observed effects ofmonetary policy on real variables.

At the microeconomic level “sticky” prices and wages have been mod-eled in a number of different ways. The chief distinction is between time-dependent and state-dependent models. In time-dependent models such

1

as those of Taylor (1980) or Calvo (1983) the timing of price changes byfirms is exogeneous or random. In state-dependent models such as thoseof Sheshinski and Weiss (1977) or Caplin and Spulber (1987) the timing ofprice changes is decided endogeneously by firms given their expectationsof the future and a fixed cost of changing prices. The implications of thesetwo kinds of models can differ markedly. For example, Caplin and Spul-ber (1987) contains the surprising result that under certain circumstancesan economy of firms following state-dependent pricing rules would showno price stickiness in the aggregate even though the price charged by eachfirm is sticky. This is not possible with time-dependent rules. Thus it be-comes important for the design of monetary policy to know which, if any,of these models better fits the circumstances of a particular economy.

The assumption of sticky prices is consistent with the general obser-vation that firms in imperfectly competitive markets change their pricesonly infrequently. However, systematic use of microeconomic evidenceto study the price-setting process is relatively recent. A pioneering studywas by Bils and Klenow (2004) who used firm-level Consumer Price Indexdata collected by the US Bureau of Labor Statistics for 350 different cate-gories of goods. They found a median duration between price changes of4.3 months but also large differences among different product categories.Later Klenow and Kryvtsov (2008) employing a larger data set from thesame source found little difference between the predictions of state- andtime-dependent models calibrated from the observed data. Subsequentstudies for a number of developed and developing countries have founda great diversity of pricing behaviour at the microeconomic level. For ex-ample, a recent survey of evidence by Klenow and Malin (2010) reportsmean monthly frequency of price changes that are as high as 51.5% forSierra Leone and as low as 10.0% for Italy. The structural causes for thisdiversity and the appropriate way to model the details of the price-settingprocess still remain unresolved issues.

Our study contributes to this literature by using disaggregated priceindices to study the price-setting process at the commodity level for India.This would be an innovation in the study of inflation in India where exist-ing studies (for example Balakrishnan (1991); Rangarajan and Arif (1990))have confined themselves to the use to aggregate time series.

2 Data

While most studies of firm-level price setting have looked at consumerprice data, in India firm-level data on consumer prices is not available.

2

Even the rural and urban Consumer Price Indices published by the Min-istry of Labour are available only for broad aggregates and at a monthlyfrequency. Given these limitations we choose to conduct our study usingthe Wholesale Price Index (WPI) data released by the Office of the Eco-nomic Advisor to the Government of India.

The most recent revision of the Indian WPI is the series with the baseyear 2004–05. However prices for manufactured goods are released onlyon a monthly basis for this series. Therefore we primarily use data fromthe earlier series with base year 1993–94 for which weekly data is availablefor the period April 1994 to August 2010.

The WPI 1993–94 series covers three broad classes of commodities: pri-mary products; fuel, power, light and lubricants; manufactured products.We exclude the first two categories from our analysis since these commodi-ties are traded in competitive markets and do not exhibit price stickiness.The category of “manufactured products” which we study contains 435commodities for which we have data over a period of 815 weeks—a totalof 354,525 data points.

Our study period of April 1994 to August 2010 also has the advantagethat in this period overall WPI inflation rates in India saw large variations,with annual year-on-year inflation rates ranging from 1.63% to 12.6%. Thisvariation in the rate of inflation is helpful in estimating the response of theprice-setting behaviour of firms to inflationary expectations.

Our data set suffers from two limitations. First, we use commodityprice indices rather than prices set by a individual firms. Since the indexchanges whenever the price is changed by any firm, this would cause us tounderestimate the stickiness of firm-level prices. However our estimateswould still act as useful lower bounds and it would be possible to comparethem with commodity-level results of studies that use more disaggregateddata.

Second, no indication is given by the Office of Economic Advisor re-garding missing observations and substitution of discontinued commodi-ties with other similar commodities. However, it is unlikely that suchevents would not have occured at all in a weekly series spanning almosttwo decades. We attempt to partially correct for these problems by elimi-nating obvious outliers in our observations.

3 Basic Observations

Tables 1, 2 and 3 summarize the characteristics of price stickiness acrosscommodities for our entire sample period.

3

While interpreting Table 1 on the duration of price changes we mustkeep in mind that we are looking at price indices and not prices chargedby individual firms. Therefore the the durations reported will be under-estimates of the duration between price changes by firms. Despite thiscaveat, it is clear from Table 1 that there is a large degree of heterogeneitybetween the different sectors in the duration between price changes, evenif we exclude primary products whose prices are determined in commod-ity markets. Table 4 in the Appendix which reports durations at a disag-gregated level makes this heterogeneity even clearer.

Table 2 gives the median of the absolute percentage change in indicesfor the periods when the index changes. The large values here reflect anumber of factors. First, it reflects the fact that for commodities with stickyprices the index does not change in every period and therefore when itchanges it does so with a relatively large magnitude.

More interestingly, as Table 3 shows for all the sectors index decreasesare a large fraction of the changes in indices, with the median proportionfor all commodities being 0.39 and the median proportion for manufac-tured goods being 0.42. This shows that it would be incorrect to believethat prices set in imperfectly competitive markets are sticky downward.Prices do remain unchanged for long periods, but when they do changethey decrease quite often. Thus a steady rate of aggregate inflation rideson top of large upward and downward swings in relative prices broughtabout by idiosyncratic shocks.

4

Commodity Duration(Weeks)ALL COMMODITIES 1.00

PRIMARY ARTICLES 1.00Food Articles 1.00Non-Food Articles 1.00Minerals 5.00

FUEL,POWER,LIGHT & LUBRICANTS 5.00Coal Mining 47.00Minerals Oil 3.00Electricity 13.00

MANUFACTURED PRODUCTS 1.00Food Products 1.00Beverages,Tobacco & Tobacco Products 10.00Textiles 1.00Wood & Wood Products 12.00Paper & Paper Products 4.00Leather & Leather Products 8.00Rubber & Plastic Products 8.00Chemicals & Chemical Products 4.00Non-Metallic Mineral Products 1.00Basic Metals Alloys & Metal Products 4.00Machinery & Machine Tools 7.00Transport Equipment & Parts 9.00

Table 1: Median Duration Between Index Changes

5

Commodity Annualized Change (%)ALL COMMODITIES 51.40

PRIMARY ARTICLES 59.42Food Articles 56.65Non-Food Articles 64.51Minerals 1076.25

FUEL,POWER,LIGHT & LUBRICANTS 141.42Coal Mining 1779.97Minerals Oil 203.18Electricity 103.50

MANUFACTURED PRODUCTS 42.76Food Products 31.60Beverages,Tobacco & Tobacco Products 168.23Textiles 54.80Wood & Wood Products 2576.92Paper & Paper Products 47.99Leather & Leather Products 179.64Rubber & Plastic Products 156.74Chemicals & Chemical Products 130.41Non-Metallic Mineral Products 18.26Basic Metals Alloys & Metal Products 117.50Machinery & Machine Tools 75.35Transport Equipment & Parts 70.90

Table 2: Median Absolute Change in Index

6

Commodity ProportionALL COMMODITIES 0.39

PRIMARY ARTICLES 0.43Food Articles 0.42Non-Food Articles 0.46Minerals 0.46

FUEL,POWER,LIGHT & LUBRICANTS 0.32Coal Mining 0.07Minerals Oil 0.36Electricity 0.32

MANUFACTURED PRODUCTS 0.42Food Products 0.48Beverages,Tobacco & Tobacco Products 0.19Textiles 0.50Wood & Wood Products 0.40Paper & Paper Products 0.42Leather & Leather Products 0.37Rubber & Plastic Products 0.43Chemicals & Chemical Products 0.37Non-Metallic Mineral Products 0.48Basic Metals Alloys & Metal Products 0.32Machinery & Machine Tools 0.36Transport Equipment & Parts 0.20

Table 3: Median Proportion of Index Changes That Were Decreases

7

4 Distribution of durations

In the simplest time-dependent model of price-setting all prices changeafter the same duration. In the popular Calvo model, the prices whichchange in each period are randomly chosen and therefore the distributionof durations would be exponentially distributed. However as Figure 1shows, either of these simple distributions seems to fit only a few of thecommodity groups. Moreover, there is once again large intra-commodityheterogeneity in the distribution of the durations.

8

duration

dens

ity

0.00.10.20.30.4

0.00.10.20.30.4

0.000.050.100.150.200.250.300.35

0.000.020.040.060.080.100.12

0.000.050.100.150.20

0.000.050.100.150.20

0.000.020.040.060.08

0.000.010.020.030.040.050.060.07

0.000.050.100.150.200.250.30

0.000.020.040.060.08

0.000.020.040.060.080.100.120.14

0.000.020.040.060.08

0.00.10.20.30.4

0.000.050.100.15

0.000.020.040.060.08

0.000.050.100.150.200.250.30

0.000.020.040.060.08

0.000.020.040.060.08

0.000.050.100.15

0.000.020.040.060.080.10

Food Grains(Cereals+Pulses)

Condiments & Spices

Other Non−Food Articles

Non−coking coal

Petrol

Light diesel oil

Lubricants

Electricity for Industry

Grain Mill Products

Cocoa,Chocolate & sugar confectionery

Other Food Products n.e.c

Manufacture of Bidi,Cigarettes,Tobacco & Zarda

Jute Hemp & Mesta Textiles

Paper & Pulp

Tyres & Tubes

Basic Heavy Organic Chamicals

Drugs & Medicines

Structural Clay Products

Basic Metals & Alloys

Electrical Machinery

0 10 20 30 40 50 60

0.00.10.20.30.4

0.00.10.20.30.4

0.000.050.100.150.20

0.00.10.20.30.40.5

0.000.020.040.06

0.000.050.100.150.200.250.300.35

0.000.020.040.06

0.000.010.020.030.040.050.06

0.000.010.020.030.040.050.060.07

0.00.10.20.30.4

0.000.020.040.060.08

0.000.050.100.150.200.250.30

0.000.050.100.15

0.000.020.040.060.08

0.000.020.040.060.080.100.12

0.000.020.040.060.08

0.000.010.020.030.040.05

0.000.020.040.060.08

0.000.020.040.060.080.100.12

0.000.010.020.030.04

Fruits & Vegetables

Other Food Articles

Metallic Minerals

Coke

Kerosene

Naphtha

Electricity for Domestic use

Electricity for Railway Traction

Bakery Products

Edible Oils

Wine Industries

Cotton Textiles

Other Misc. Textiles

Manufacture of Boards

Plastic Products

Fertilizers & Pesticides

Perfumes, Cosmetics, Toiletries etc

Glass,Earthedtnware, Chinaware & their products

Non−Ferrous Metals

Locomotives Railway Wagons & Parts

0 10 20 30 40 50 60

0.000.050.100.150.20

0.00.10.20.30.4

0.000.050.100.15

0.000.050.100.150.20

0.000.050.100.150.20

0.000.050.100.150.200.25

0.000.020.040.060.080.10

0.000.050.100.150.200.250.30

0.00.10.20.30.4

0.00.10.20.3

0.000.020.040.060.080.10

0.000.050.100.150.200.25

0.000.020.040.060.08

0.000.020.040.060.080.10

0.000.010.020.030.040.050.060.07

0.000.010.020.030.040.050.060.07

0.000.020.040.060.080.100.120.14

0.000.050.100.150.200.250.300.35

0.000.010.020.030.040.050.06

0.000.010.020.030.040.050.060.07

Milk

Fibres

Other Minerals

Lignite

Aviation turbine fuel

Bitumen

Electricity for Commercial use

Dairy Products

Sugar, Khandsari & Gur

Oil Cakes

Malt liquor

Man Made Textiles

Plywood commercial planks

Printing & Publishing of Newspapers,Periodicals etc

Other Rubber & Plastic Products

Paints Varnishes & Lacquers

Turpentine, Synthetic Resins, Plastic materials etc

Cement

Metal Products

Motor Vehicles, Motorcycles, Scooters, bicycles & part

0 10 20 30 40 50 60

0.000.050.100.150.200.250.300.35

0.00.10.20.30.4

0.000.020.040.060.08

0.000.020.040.060.08

0.000.050.100.15

0.000.050.100.150.200.250.300.35

0.000.010.020.030.040.050.06

0.000.010.020.030.040.050.060.07

0.000.050.100.15

0.000.050.100.150.200.250.30

0.000.020.040.060.08

0.000.050.100.15

0.000.020.040.060.080.10

0.000.020.040.060.08

0.000.050.100.15

0.000.010.020.030.040.050.06

0.000.010.020.030.040.05

0.000.020.040.06

0.000.020.040.060.080.10

Eggs,Meat & Fish

Oil Seeds

Coking coal

Liquefied petroleum gas

High speed diesel oil

Furnace oil

Electricity for Agricultural use

Canning, Preserving & Processing of fish

Manufacture of Common Salt

Tea & Coffee Proccessing

Soft Drinks & Carbonated Water

Woollen Textiles

Timber Planks

Footwear Western type

Basic Heavy Inorganic Chemicals

Dyestuffs & Indigo

Matches,Explosives & Other Chemicals n.e.c

Cement Slate & Graphite Products

Non−Electrical Machinery & Parts

0 10 20 30 40 50 60

Figure 1: Distribution of duration between index changes

9

5 Inflation vs. frequency of price changes

Figure 2 shows how the proportion of indices which undergo a changevaries as a function of the prevailing rate of inflation. We notice that theproportion responds sharply to the rate of inflation. Once again this isinconsistent with time-dependent models of price setting which wouldpredict each of these curves to be flat.

10

infl

coun

t

0.1

0.2

0.3

0.4

0.5

−40 −20 0 20 40

category

all

neg

pos

Figure 2: Proportion of indices which change(all), increase(pos) and de-crease(neg) as a function of the overall rate of inflation (lowess smoother)

11

6 Conclusion

1. Time-dependent models of pricing are not supported by the data.

2. Periods of high-inflation are not just periods of large price changesbut also periods of more frequent price changes. Therefore mod-els of price setting need to explain both these variables rather thanholding either the frequency (time-dependent) or size (simple state-dependent) fixed.

3. There is a great heterogeniety among even imperfectly competitivesectors in terms of the nature of price setting behaviour. This shouldcaution us against using simple aggregative models.

7 Appendix

7.1 Detailed median duration between index changes

Commodity Duration(Weeks)ALL COMMODITIES 1.00

PRIMARY ARTICLES 1.00Food Articles 1.00

Food Grains(Cereals+Pulses) 1.00Fruits & Vegetables 1.00Milk 2.00Eggs,Meat & Fish 1.00Condiments & Spices 1.00Other Food Articles 1.00

Non-Food Articles 1.00Fibres 1.00Oil Seeds 1.00Other Non-Food Articles 1.00

Minerals 5.00Metallic Minerals 5.00Other Minerals 6.00

FUEL,POWER,LIGHT & LUBRICANTS 5.00Coal Mining 47.00

Coking coal 42.00Non-coking coal 47.00Coke 151.00Lignite 71.00

12

Commodity Duration(Weeks)Minerals Oil 3.00

Liquefied petroleum gas 20.00Petrol 4.00Kerosene 27.00Aviation turbine fuel 4.00High speed diesel oil 5.00Light diesel oil 3.00Naphtha 2.00Bitumen 2.00Furnace oil 2.00Lubricants 9.00

Electricity 13.00Electricity for Domestic use 13.00Electricity for Commercial use 13.00Electricity for Agricultural use 17.00Electricity for Industry 12.00Electricity for Railway Traction 13.00

MANUFACTURED PRODUCTS 1.00Food Products 1.00

Dairy Products 1.00Canning, Preserving & Processing of fish 56.00Grain Mill Products 1.00Bakery Products 9.00Sugar, Khandsari & Gur 1.00Manufacture of Common Salt 4.00Cocoa,Chocolate & sugar confectionery 8.00Edible Oils 1.00Oil Cakes 1.00Tea & Coffee Proccessing 4.00Other Food Products n.e.c 4.00

Beverages,Tobacco & Tobacco Products 10.00Wine Industries 9.00Malt liquor 5.00Soft Drinks & Carbonated Water 8.00Manufacture of Bidi,Cigarettes,Tobacco & Zarda 10.00

Textiles 1.00Cotton Textiles 1.00Man Made Textiles 1.00Woollen Textiles 3.00Jute Hemp & Mesta Textiles 1.00Other Misc. Textiles 6.00

Wood & Wood Products 12.00

13

Commodity Duration(Weeks)Plywood commercial planks 24.00Timber Planks 8.00

Paper & Paper Products 4.00Paper & Pulp 4.00Manufacture of Boards 6.00Printing & Publishing of Newspapers,Periodicals etc 6.00

Leather & Leather Products 8.00Footwear Western type 8.00

Rubber & Plastic Products 8.00Tyres & Tubes 9.00Plastic Products 6.00Other Rubber & Plastic Products 37.00

Chemicals & Chemical Products 4.00Basic Heavy Inorganic Chemicals 2.00Basic Heavy Organic Chamicals 4.00Fertilizers & Pesticides 11.00Paints Varnishes & Lacquers 11.00Dyestuffs & Indigo 17.00Drugs & Medicines 11.00Perfumes, Cosmetics, Toiletries etc 17.00Turpentine, Synthetic Resins, Plastic materials etc 6.00Matches,Explosives & Other Chemicals n.e.c 18.00

Non-Metallic Mineral Products 1.00Structural Clay Products 7.00Glass,Earthedtnware, Chinaware & their products 13.00Cement 1.00Cement Slate & Graphite Products 15.00

Basic Metals Alloys & Metal Products 4.00Basic Metals & Alloys 4.00Non-Ferrous Metals 4.00Metal Products 13.00

Machinery & Machine Tools 7.00Non-Electrical Machinery & Parts 5.00Electrical Machinery 9.00

Transport Equipment & Parts 9.00Locomotives Railway Wagons & Parts 26.00Motor Vehicles, Motorcycles, Scooters, bicycles & part 9.00

Table 4: Median Duration Between Price Changes (detailed)

14

References

BALAKRISHNAN, P. (1991): Pricing and Inflation in India, Oxford UniversityPress.

BILS, M. AND P. J. KLENOW (2004): “Some evidence on the importance ofsticky prices,” Journal of political economy, 112, 947–985.

CALVO, G. (1983): “Staggered prices in a utility-maximizing framework,”Journal of monetary Economics, 12, 383–398.

CAPLIN, A. S. AND D. F. SPULBER (1987): “Menu costs and the neutralityof money,” The Quarterly Journal of Economics, 102, 703–725.

CLARIDA, R., J. GALI, AND M. GERTLER (1999): “The science of monetarypolicy: a new Keynesian perspective,” Journal of economic literature, 37,1661–1707.

ENGLE, R. AND J. RUSSELL (1998): “Autoregressive conditional duration:A new model for irregularly spaced transaction data,” Econometrica, 66,1127–1162.

GOODFRIEND, M. AND R. G. KING (1997): “The new neoclassical synthe-sis and the role of monetary policy,” NBER macroeconomics annual, 12,231–283.

KLENOW, P. J. AND O. KRYVTSOV (2008): “State-Dependent or Time-Dependent Pricing: Does It Matter for Recent US Inflation?” QuarterlyJournal of Economics, 123, 863–904.

KLENOW, P. J. AND B. A. MALIN (2010): “Microeconomic Evidence onPrice-Setting,” Working Paper 15826, NBER.

RANGARAJAN, C. AND R. ARIF (1990): “Money, Output and Prices: AMacro econometric Model,” Economic and Political Weekly, 25, 837–852.

SHESHINSKI, E. AND Y. WEISS (1977): “Inflation and costs of price adjust-ment,” The Review of Economic Studies, 44, 287–303.

TAYLOR, J. (1980): “Aggregate dynamics and staggered contracts,” TheJournal of Political Economy, 88, 1–23.

15