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Inflation persistence during periods of structural change: an assessment using Greek data

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Abstract

The paper estimates inflation persistence in Greece from 1975 to 2003, a period of high variation in inflation and changes in policy regimes. Two empirical methodologies, univariate autoregressive (AR) modelling and second-generation random coefficient (RC) modelling, are employed to estimate inflation persistence. The empirical results from all the procedures suggest that inflation persistence was high till 1996, while it started to decline after 1997, when inflationary expectations seem to have been stabilised, and thus, monetary policy was effective at reducing inflation. Empirical findings also detect a sluggish response of inflation to changes in monetary policy. This observed delay seems to have changed little over time.

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Notes

  1. See also Barsky (1987), Evans and Watchel (1993) and the recent work of Cogley and Sargent (2001, 2003). For an investigation of the inflation-productivity nexus in European countries, see Tsionas (2003a).

  2. To the best of our knowledge, this paper is the first study of inflation persistence in Greece. In an earlier paper, Lazaretou (1995) presents some historical perspective on the behaviour of inflation in Greece in the pre- and post-WWI periods. The historical data of Greek price indices suggest that there was a positive association between the time series properties of inflation and the country’s choice of nominal exchange rate regime. By employing non-parametric measures of persistence, Kalyvitis and Lazaretou (1997) examine the persistence of Greek inflation under the Bretton Woods system and the subsequent floating rate system. Statistics show that inflation exhibits higher persistence under floating.

  3. For a detailed analysis on second generation RC estimates, see Swamy and Tavlas (1995, 2001).

  4. For a detailed analysis on inflation performance during this period, see Garganas and Tavlas (2001).

  5. We have applied a naïve measure of inflation persistence. AR modelling allows us to study the autocorrelation properties of inflation and to detect evidence whether inflation persistence is an intrinsic structural phenomenon or depends on the monetary policy regime. Departing from the univariate autoregressive presentation of inflation, we might estimate as a topic for future research, a structural model including excess demand, wage pressure and cost driven factor as the main determinants of inflation (see, for example, Tsionas 2003a, b on EE15 and Tsionas and Christopoulos 2004 on Greece).

  6. That is, the break point Chow test and recursive coefficient estimates. In running Chow break point tests for all potential break point dates, we allow for a change both in the intercept and in the autoregressive coefficients. By allowing different intercept and slope coefficients, Eq. (2) is fitted separately to different sub-samples and then we compare them to the restricted (full-sample) equation by means of a Chow test. However, the timing of a structural change in the inflation series need not have coincided precisely with the formal adoption of a new policy regime. By recursive coefficient estimates we are able to trace the evolution of the persistence coefficient as more and more of the sample data are added to the estimating regression. Recursive estimates suggest that although there is no movement outside the critical values of the 2% standard error bands, persistence increases till the mid-1990s, while the sample mean value of the inflation rate declines.

  7. Over the last decade the analysis of structural breaks in a time series has considerably developed. Different test statistics are proposed in the literature detecting single and multiple breaks. Properly accounting for them is of great importance in the analysis of the time series properties of a macroeconomic variable, such as shifts in the mean rate of inflation and the measure of its persistence. See Altissimo and Corradi (2003) and Altissimo (2003).

  8. The same behaviour is exhibited by the WPI inflation series. There is a structural break in the intercept, while the serial correlation of the inflationary process remains unchanged. The sample mean of the inflation rate falls to 5.8% in the second period compared with 15.8% pre-1991, whereas there is no variation in persistence over time; it goes from 0.59 to 0.58 after 1991. Furthermore, the variance before and after the break decreases; WPI inflation is 1.4 times less volatile in disinflation relative to the period of high inflation. The results for core CPI inflation reveal a substantial rise in the serial correlation of Greek inflation, with the autoregressive coefficient going from 0.53 to 0.88, before and after 1991. The mean of core inflation is 2.5 times lower after the break, while inflation has approximately the same variance between the two periods.

  9. By contrast, empirical work for the US and the UK detects high inflation persistence, at least for the pre-1990 period. See, for example, Nelson and Plosser (1982), Fuhrer and Moore (1995), Gali and Gertler (1999), Taylor (2000), Cogley and Sargent (2001), Batini and Nelson (2001), Stock (2001) and Sbordone (2002).

  10. EMU membership might explain this structural change appeared at the end of the sample. Levin and Piger (2004) run rolling regressions using different data window sizes for US GDP price deflator and also find that with a shorter window the drop in persistence appears earlier.

  11. For other recent applications of RC methodology on different topics, see Hondroyiannis et al. (2000, 2001a, b) and Brissimis et al. (2003).

  12. The RC methodology is concerned with the “real world interpretation”, tries to uncover the “true structure” and provides consistent estimates of the coefficients of Eq. (1). Since the explanatory variables of Eq. (1) are unobservable, such estimates can only be derived from consistent estimates of the coefficients of Eq. (3). Equation (3) is more complicated than a structural equation without exogenous variables since \( \Delta p_{{t - 1}} ,\;\Delta p_{{t - 2}} \;{\text{and}}\;\Delta p_{{t - 3}} \) are correlated with γ1t , γ2t and γ3t . Many authors use the instrumental variable estimation to overcome this problem. However, an instrumental variable estimation is not designed to decompose the γ′s into bias-free, omitted-variables bias and mis-measurement effects or to deal with the correlation between the γ′s and a measured \( \Delta p_{{t - 1}} ,\;\Delta p_{{t - 2}} \;{\text{and}}\;\Delta p_{{t - 3}} \). Economic theory provides us with many categories of variables that may, indirectly or directly, influence the inflation process. In particular, interest rates reflect monetary conditions in the economy. Assuming a constant mark-up, wages might be expected to be transmitted to output prices and hence CPI inflation. Output is considered as a measure of demand pressure and thus affects inflation expectations. For a formal discussion on alternative structural models, using Greek data, see Tsionas (2001).

  13. Adding concomitants successively should reduce the RMSE of the estimated regressions.

  14. Growth rate of nominal GDP and short-term interest rate are broader measures compared to growth rates of wages. Hence, the first two concomitants may give a better measure of the bias-free effect than the latter.

  15. A richer specification of concomitants might provide different results.

  16. The estimation period for all RC models is 1976 Q1–2000 Q4 and the forecast period is 2001 Q1–2002 Q4. The estimation period for Figs. 5 and 6 is 1976 Q1–2002 Q4.

  17. A true comparison of the empirical findings from the RC estimation with those of OLS requires us to re-estimate Eq. (1) using year-on-year inflation. The estimated inflation persistence is equal to 0.98 for the period 1976 Q1–2002 Q4, 0.86 for the period 1976 Q1–1990 Q4 and 0.94 for the period 1991 Q1–2002 Q4. As expected, the estimates of persistence are higher using year-on-year data since the latter is a four quarter moving average of the quarter-on-quarter rate which in itself introduces some persistence.

  18. The short-term real interest rate is computed as the difference between the nominal interest rate and the ex ante inflation rate. Ex ante inflation is approximated by the fitted values of an AR(4) scheme for CPI inflation. A H-P trend of the log of the real GDP is also included in the explanatory variables. We use the short-term bank lending rate (quarterly averages) and inflation is the quarter-on-quarter change of CPI.

  19. The yield spread is the spread of the long-term bond rate over the short-term interest rate. As the long-term interest rate we use the 12-month Treasury bill rate. Fixed income government securities at 5 years and over were issued for the first time in 1997. Initially, Greek markets were thin; it took some time to develop. Therefore, the 12-month Treasury bill rate is used as a proxy for the long-term interest rate.

  20. We also try to determine the number of lags it takes for inflation to have its maximum response to non-systematic monetary changes (i.e. policy shocks). See, for example, Christiano et al. (2001) and Rotemberg and Woodford (1997) for the US economy, and Smets and Wouters (2002) and Fagan et al. (2001) for the euro area. To this end, we estimate an unconstrained VAR model for the Greek economy with three endogenous variables: the quarterly change of CPI, the deviation of the log of the real GDP from its H-P trend and the short-term nominal interest rate. Monetary policy shocks are identified as innovations in the monetary policy reaction function. The short-term lending rate, the 12-month Treasury Bill rate and the reserve money are used as policy instruments. However, impulse response functions produce weak evidence.

  21. Correlations between the measures of monetary policy and inflation are also computed using core CPI inflation and WPI inflation. The results confirm the evidence for CPI inflation.

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Acknowledgements

We are indebted to an anonymous referee of this Journal for useful comments and suggestions. An earlier draft of this paper was presented at the Eurosystem Inflation Persistence Network (IPN) Workshop hosted by the European Central Bank on 29–30 September and 1 October 2003. A longer version of the paper is published in the ECB, Working Paper Series, 370/June 2004 and Bank of Greece Working Paper Series, 13/June 2004. We are grateful to the IPN participants and especially to Andy Levin, Jordi Gali, Benoit Mojon and an anonymous referee for their comments and suggestions. We have also benefited from the constructive comments and suggestions of Sophocles Brissimis, Heather Gibson, George Tavlas and Philip Vermeulen. We also acknowledge helpful discussions with Steven Hall, Nicos Magginas, Dafni Papadopoulou, George Simigiannis, P. A. V. B. Swamy, Tetti Tzamourani and Hercules Voridis. We would like to thank the Department of Statistics and the Domestic Economy Division of the Bank of Greece for supplying the data. The views expressed are solely of the authors, and should not be interpreted as reflecting those of the Bank of Greece.

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Authors and Affiliations

  1. Economic Research Department, Bank of Greece, 21 El. Venizelos, 102 50, Athens, Greece

    George Hondroyiannis & Sophia Lazaretou

  2. Harokopio University, Athens, Greece

    George Hondroyiannis

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  1. George Hondroyiannis
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  2. Sophia Lazaretou
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Correspondence to George Hondroyiannis.

Appendix: Data sources and definitions

Appendix: Data sources and definitions

  • CPI, Consumer Price Index (1999 = 100), sample period 1975 Q1–2003 Q2, quarterly averages seasonally adjusted. Source: National Statistical Service of Greece.

  • Short-term bank lending rate to enterprises (quarterly averages), sample period 1975 Q1–2003 Q1, in percent. Source: Bank of Greece.

  • Gross Domestic Product, market prices, at 1995 constant prices, in million euro (ESA 95), quarterly data, no seasonal adjustment, sample period 1975 Q1–2003 Q1. Source: National Statistical Service of Greece.

  • Gross Domestic Product, market prices, at current prices, in million euro (ESA 95), quarterly data, no seasonal adjustment, sample period 1975 Q1–2002 Q4. Source: National Statistical Service of Greece.

  • M3 money, M1 money, ECB definition, in million euro, no seasonal adjustment, end-of quarter data, sample period 1980 Q1–2003 Q1. Source: Bank of Greece.

  • Nominal wages, minimum monthly salary of white colour workers in manufacturing, in thousands of drachmas, quarterly data, no seasonal adjustment, sample period 1975 Q1–2002 Q4. Source: National General Collective Agreements.

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Hondroyiannis, G., Lazaretou, S. Inflation persistence during periods of structural change: an assessment using Greek data. Empirica 34, 453–475 (2007). https://doi.org/10.1007/s10663-007-9043-2

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