UNDERSTANDING INFLATION IN

INDIA

Laurence Ball

Johns Hopkins University

Anusha Chari

University of North Carolina

Prachi Mishra

Reserve Bank of India

India Policy Forum July 14-15, 2015

The views represent those of the authors, and not necessarily those of the Reserve Bank of India, or any of the institutions to which the authors belong.

RECENT HISTORY

• 12-month CPI inflation rose from 3.7% to 12.1% over 2000-2010. What caused this increase?

• Inflation fell to 5.2% in early 2015. Will lower inflation be sustained?

– More generally, various factors put forth as drivers of India’s inflation rate.

– Rising food prices. Government price supports. Fiscal policy. Policy

bottlenecks.

• Can the RBI control inflation? Are there costs to doing so? • Does high inflation become embedded in expectations?

CONTRIBUTION

• Recent discussions of India’s inflation are reminiscent of debates in advanced economies during the 1970s and 1980s, when inflation was high.

• This experience spawned a large literature on inflation dynamics, especially in the United States. Less research on India.

• We contribute to basic research on India’s inflation dynamics. We find that the factors driving the inflation process have similarities to factors in the U.S.

WHAT THIS PAPER DOES

• We measure core inflation in the WPI with the weighted median of industry price changes.

• We estimate a Phillips curve in which core inflation is determined by the output gap and expected inflation.

MEASURING CORE INFLATION

• Headline inflation = Core inflation + “Large Relative Price Changes” aka supply or demand shocks

• Ball and Mankiw (1995): Large changes in the relative prices of certain industries

caused by supply shocks, which are reflected in asymmetries in the distribution of price changes.

• Bryan and Cecchetti (1994): Weighted median inflation filters out large relative

price changes, yielding a measure of core inflation. • The Federal Reserve Bank of Cleveland produces a series for weighted median

inflation in the United States. • The weighted median is a better measure of core inflation than inflation excluding

food and energy (especially for India).

APPLICATION TO INDIA

• Wholesale price index (WPI), 1994Q3 - 2014Q4

• WPI is disaggregated into 61 industries in the first half of the sample and 81 industries in the second half.

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Figure 2A: Quarterly WPI Inflation: Weighted Mean and Weighted Median

Weighted Mean Weighted Median

Median inflation is less volatile than headline inflation.

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Figure 2B: Quarterly WPI Inflation: Weighted Mean and Weighted Median (Seasonally Adjusted)

Weighted Mean Weighted Median

A surprising result: the average level of median inflation (3.4% annualized) is lower than the average level of headline inflation (5.6%).

This difference reflects the fact that the distribution of price changes is often skewed to the right: a thick

SUMMARY OF OUR FINDINGS 1. Weighted median inflation is substantially less volatile at

the quarterly frequency than headline inflation (2.62% vs. 3.93%).

2. The average weighted median inflation is substantially less than the average headline inflation (3.4% vs. 5.6%).

3. The distribution of price changes across industries is often skewed to the right and rarely to the left. A tail of large price increases raise headline inflation but are filtered out of the median.

4. Deviations of headline inflation from the weighted median are caused largely, but not entirely, by changes in the relative prices of food and energy.

Food and fuel account for a large share of these tails, as measured by the top 10% of price changes.

Table 1. Contributors to Top 10% of Price Changes

Industry Rescaled Weighted Frequency

Primary Articles: Food 27.83

Fuel & Power 23.50

Mfg: Food 12.22

Primary Articles: Non Food 8.50

Mfg: BM: Basic Metals, Alloys and Metal Products 7.55

Mfg: CC: Chemicals & Chemical Products 6.02

Mfg: Textiles 4.46

Primary Articles: Minerals 2.31

Mfg: NM: Non Metallic Mineral Products 1.95

Mfg: Paper & Paper Products 1.21

Mfg: MM:Machinery & Machine Tools 0.96

Mfg: BT: Beverages, Tobacco & Tobacco Products 0.95

Mfg: TE: Transport, Equipment & Parts 0.93

Mfg: Rubber & Plastic 0.85

Mfg: Leather & Leather Products (LL) 0.52

Mfg: Wood Wood Products 0.25

Notes. Weighted frequency is rescaled to sum to 100. Industries are sorted By weighted frequency. Total number of quarters=82 (1994q3:2014q4)

A PHILLIPS CURVE FOR CORE INFLATION

Inflation, Expected inflation, Level of economic activity, Long run level of x. Output gap: the deviation of output (seasonally adjusted) from its Hodrick-Prescott trend. Quarterly data are available starting in 1996Q2.

p t

p t

*

xtxt

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A PHILLIPS CURVE FOR CORE INFLATION (contd.)

• Hypothesize: expected inflation is determined by past inflation rates.

– Expectations have not been anchored in India

A PHILLIPS CURVE FOR CORE INFLATION (contd.)

Estimate the parameters by non-linear least squares.

Table 2. Phillips Curve Estimates

Dependent Variable. Weighted Median WPI Inflation

Output gap, α 1.074**

[0.540]

Adjustment parameter, γ 0.902***

[0.053]

Number pf observations 74

R-squared 0.19

Adjusted R-squared 0.179

Notes: ***, **, and * denote statistical significance at 1,5, and 10 percent percent respectively. Standard errors are denoted in parentheses.

INTERPRETATION OF ESTIMATES • Expectations adjust slowly to changes in

actual inflation – Coefficients on the first four inflation lags are

approximately 0.1, 0.09, 0.08, 0.07; the sum of these coefficients is only 0.34.

• T-statistic for the output gap is 1.99. – Output affects inflation

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Figure 6B. Phillips Curve Estimates with Weighted Median: 8-quarter Moving Avaerages

Weighted Median Inflation Fitted Values Expected Inflation

INTERPRETATION OF ESTIMATES (contd.) – SACRIFICE RATIO

• Implied “sacrifice ratio” for reducing inflation is 2.7

INTERACTIONS OF HEADLINE AND CORE INFLATION

• A Phillips curve for headline WPI inflation does not fit well – estimated γ is statistically indistinguishable from 1.

• Some evidence that core inflation depends on lags of headline inflation rather than lags of core inflation

• Suggests that a change in relative prices can have a persistent effect on inflation – E.g. a supply shock, such as a large change in food prices,

– Shock raises headline inflation, which raises future expected inflation, which raises core inflation.

– Similar to U.S. in 1970s.

SUMMARY OF OUR FINDINGS

1. Develop a new measure of core inflation. Weighted median inflation is substantially less volatile and

systematically lower at the quarterly frequency than headline inflation A tail of large price increases raise headline inflation but are

filtered out of the median. Deviations of headline inflation from core are caused largely, but

not entirely, by changes in the relative prices of food and energy.

2. Expectations are adaptive but adjust slowly.

Current core inflation depends on many lags of past inflation with weights that decline slowly Expected inflation is a long moving average of past inflation rates

Expectations inertia implies that high inflation can become embedded in expectations.

3. Output affects inflation

For a given level of expected inflation, positive relationship between inflation and the deviation of output from trend.

Estimate a sacrifice ratio of 2.7

• Thank you!