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Price stickiness, inflation, and persistence in real exchange rate
fluctuations: cross-country results
*
Hashmat Khan
Research Department, Bank of Canada, 234 Wellington St., Ottawa, Canada K1A 0G9 Received 7 June 2000; accepted 6 December 2000
Abstract
Models that emphasize sticky prices to explain persistent real exchange rate fluctuations predict that such fluctuations should be less persistent in high inflation countries relative to low inflation countries. Cross-country regression results, in general, do not support this implication. 2001 Elsevier Science B.V. All rights reserved.
Keywords: Real exchange rate; Price stickiness; Inflation
JEL classification: E31; F41
1. Introduction
An important puzzle in international macroeconomics is why are fluctuations in the real exchange rate so persistent (e.g., Froot and Rogoff, 1995). One explanation for this phenomenon is based on the microfoundation of sticky prices. In the presence of sticky prices the national price level is slow to adjust in response to shocks (e.g., Taylor, 1980; Blanchard, 1987). Therefore, nominal exchange rate fluctuations cause the real exchange rate to deviate from its long run parity level (some examples of the sticky price approach are Betts and Devereux, 1996; Obstfeld and Rogoff, 1996; Kollman, 1997; Chari et al., 1998; Bergin and Feenstra, 1999). In a sticky price model, the duration of real exchange rate deviations from the parity level depends directly on the time it takes for prices to adjust fully. A key prediction of the sticky price model of real exchange rate fluctuations is that the fluctuations in the real exchange rate should be less persistent in countries with high trend inflation relative to those with low trend inflation.The idea behind this cross-sectional prediction is fairly intuitive. Prices adjust faster in high inflationary environments relative to the low ones. This rapid adjustment reduces
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E-mail address: [email protected] (H. Khan).
the stickiness in the national price level. As a result, shocks to the nominal exchange rate get absorbed by the faster adjustment in the aggregate price level. In a sticky price model, the persistent effect of shocks depends on the degree of price stickiness. Therefore, the lower price stickiness in high inflation countries implies that the deviations of the real exchange rate from the long run parity level in these countries should be less persistent. The objective of this paper is to examine this prediction of the sticky price model of real exchange rate fluctuations.
I use annual International Financial Statistics data from 49 countries over the period 1972–1996 to investigate the inverse relationship between trend inflation and the persistence in real exchange rate fluctuations. The estimation results indicate that the statistical support for the inverse relationship is extremely fragile. This finding is difficult to reconcile with the sticky price based explanation of real exchange rate fluctuations.
2. The Model
The real exchange rate q , for a country i, is defined asit
Pt ]
qit;eit F, (1)
Pt
where e is the nominal exchange rate (units of foreign currency per unit of domestic currency), Pit t
F 1
and (P ) are aggregate price levels for the domestic and the foreign economy. A rise in q impliest it real appreciation. Typically, the sticky price assumption is incorporated in a model by using the Calvo (1983) framework. Firms are assumed to receive common exogenous signals for changing the price of their output. In any given period, a firm either continues to charge the predetermined nominal price with probabilityf or it charges the optimal price with probability 12f. At the macro level, f has the interpretation of the fraction of firms in the economy that charge the predetermined price (Pt21)
*
and 12f is the remaining fraction of the firms that charge the optimal price (P ) (e.g., Rotemberg,t 1987; Yun, 1996). Romer (1990) endogenizes the probability f to depend inversely on the trend
T 2
inflation rate p to capture the notion that trend inflation influences the frequency of price changes.
T T
*
Therefore, the appregate price level in (1) can be expressed as Pt5f(Pt21,P ,t f(p )) and ≠f(p ) / T
≠p ,0. A higher trend inflation lowersf and therefore, the aggregate price level is more flexible. The quicker price adjustment in high inflation economies implies that shocks to the nominal exchange rate will transmit faster into relative price adjustments. Consequently, such adjustments in the prices cause less persistent fluctuations in the real exchange rate.
To test the hypothesis, I use a simple two-stage approach that has been employed extensively in examining the predictions of macroeconomic theories (e.g., Lucas, 1973; Ball et al., 1988). In the first stage, I run a country-specific regression to estimate the parameterri which captures the persistence in (HP-filtered) real exchange rates.
1
The nominal exchange rate is typically determined by an uncovered interest parity condition (e.g., Obstfeld and Rogoff, 1996).
2
hp hp
qit 5riqit211u .it (2)
ˆ
In the second stage, I regress the estimated coefficients, ri values, on trend inflation as captured by the ¯
average inflation rates, pi values. This cross-sectional regression is
ˆ
*
¯ri5b01b p1 i1u ,i i51, . . . ,48. (3)
The prediction of the sticky price model is that the coefficient b1 is negative.
3. Results
The results from the second stage estimation are reported in Table 1. In the full sample, the coefficient is negative and statistically significant. That is, the fluctuations in the real exchange rate are less persistent in high inflation countries. However, I find that this empirical support for the hypothesis is very fragile.
In the empirical implementation, the cross-sectional variation in average inflation rates is a desirable feature. However, in the data, a higher average inflation rate is correlated with a higher variability of inflation. Therefore, for an accurate representation of the hypothesis, it is important to control for the within-country variability in inflation. In particular, Argentina, Brazil, and Israel have historically experienced periods of hyperinflation driven by extreme monetary instability. I identify periods of high and low volatility within these countries (Table 2). For Argentina (A), the inflation rate high volatility period is more than 3 times as volatile as in the low volatility period. For Brazil (B) and Israel (I), the inflation rate in the high volatility period is more than 5 times that in the low volatility period. I refer to these years of relatively high inflation volatility as episodes of hyperinflation. The inflation rate for the high volatility period is greater than three standard deviations of the average inflation for low volatility period. These episodes of hyperinflation are more than 3% of the entire panel data.
Table 1
ˆ
Two-stage estimation: dependent variableri
Countries b1 b0
a a
Full sample 20.220 0.541
(0.09) (0.02) a Full sample (excl. episodes) 0.063 0.520
(0.11) (0.02) a Excluding A, B, I 0.030 0.520
(0.17) (0.02) Non-OECD (excl. episodes) 0.175 0.577
(0.13) (0.03) a
Table 2
Relative inflation volatility
a
¯
Country Period Years p sp Relative
volatility Argentina Full sample 1973–1996 1.052 0.9048 1.76
High vol. 1989–1996 1.52 1.63 3.18 Low vol. 1973–1988 1.101 0.5122 1 Brazil Full sample 1973–1996 1.185 1.0113 4.76
High vol. 1984–1996 1.784 1.0366 4.88 Low vol. 1973–1983 0.477 0.2121 1 Israel Full sample 1973–1996 0.421 0.4219 4.90
High vol. 1973–1985 0.637 0.4743 5.15 Low vol. 1986–1996 0.167 0.0860 1 a
sp denotes the volatility of inflation.
Once the episodes of hyperinflation are excluded from the estimation, the coefficient b1 is statistically insignificant. When I exclude Argentina, Brazil, and Israel from the estimation, the coefficientb1 is still statistically insignificant. Within the OECD countries there is no support for the hypothesis. For the non-OECD countries, b1 is negative and statistically significant. Once again, for non-OECD countries, the statistical support for the hypothesis is driven by the episodes of hyperinflation.
The results presented here indicate that the prediction of the sticky price model of real exchange rate fluctuations is supported only when we consider periods of extreme monetary instability in a few countries. However, such monetary instability is not the focus of the theoretical sticky price model of real exchange rate fluctuations. Further, it is likely that the inverse relationship arises due to factors other than sticky prices. For instance, the autocorrelation in the HP filtered real exchange rate for Israel is negative (20.1). If price stickiness were to completely disappear at very high levels of inflation then the model predicts that the autocorrelation should be zero.
4. Conclusion
Acknowledgements
This paper is based on a chapter of my Ph.D. thesis. I would like to thank Michael Devereux, Francisco Gonzalez, Jim Nason, Angela Redish, Christian Sigouin, and especially Paul Beaudry for useful comments. The views expressed in this paper are solely mine and no responsibility for them should be attributed to the Bank of Canada.
Appendix A
A.1. Data source and variables
All data are annual and taken from the International Financial Statistics (IFS). The nominal exchange rate data is the IFS series rh which denotes US dollars per unit of national currency. The overall sample period is 1972–1996. For each country, I construct the real exchange rate ( q ) seriesit as
*
Pit ]] qit;eit U S.
Pt
U S
*
where Pt is the GDP deflator price index in the US and Pit is the GDP (GNP) deflator in country i. I detrend the data using the HP filter. The price index is the GDP (or GNP) deflator. The inflation rate is the growth rate of the deflator.
Appendix B
B.1. Data summary
No. Country Average
inflation (%)
1 Argentina 100.1
a
2 Australia 7.5
a
3 Austria 4.4
a
4 Belgium 5
5 Bolivia 6
6 Brazil 123
a
7 Canada 5.5
8 Colombia 21.7
10 Denmark 6.3
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