ACADEMY OF ECONOMIC STUDIES BUCHAREST DOCTORAL SCHOOL OF FINANCE - BANKING DISSERTATION PAPER

1. ACADEMY OF ECONOMIC STUDIES BUCHAREST DOCTORAL SCHOOL OF FINANCE - BANKING DISSERTATION PAPER Inflation and Economic Growth Supervisor: Professor Moisa ALTAR MCs Student: Radu ZARA July 2003

2. 1. Theoretical Background 2. Empirical Evidence 3. Data and Methodology 4. Regression Analysis and Results 5. Concluding Remarks

3. 1. Theoretical Background • important issue for monetary policy-makers • inflation seemed positively correlated with growth (aggregate demand) • inflation undermines investors’ confidence – investment channel • inflation reduces total factor productivity – efficiency channel • equally plausible models yield qualitatively different predictions (Tobin, Sidrauski, Stockman)

4. TobinEffect • real wealth is held in two assets: real money and physical capital – A = B*(M/P) + (1-B)*K • money yields a real rate of interest defined as r = i – π(P) • capital yields a return equivalent to its marginal productivity – f(K) • the portfolio allocation decision basically resolves into: B = h(r-f(K)) • if r < f(K), then B falls and more wealth is held in the form of capital • Tobin recommended that moderate levels of inflation be instituted to eat away at the rate of return on money

5. Sidrauski Model • money is treated as an alternative store of wealth to capital (like Tobin) • people choose the saving ratio to maximize their happiness • in Sidrauski’s economy, people’s saving ratio falls in response to an increase in inflation, as do their real money balances • capital is unchanged as its rate of return is not influenced by inflation • the result is that an increase in the inflation ratedoes not affect the capital stock

6. Stockman Effect • money is a complement to capital • firms frequently put up some cash in financing their investment projects • money acquisition is necessary for capital accumulation • the Stockman effect can also operate through effects on the labor–leisure decision • as the return to labor falls when the inflation rate rises, people will substitute away from consumption and toward leisure which ultimately will induce a decrease in output • the term generally applies to results in which output is inversely related to the inflation rate.

7. Depending on money’s role, an increase in the inflation rate can result in less output (the Stockman effect), more output (the Tobin effect), or no change in output (Sidrauski). In short: • (1) if money is a complement to capital, inflation and output are negatively related; • (2) if money and capital are substitutes, inflation and output are positively related; • (3) if money is primarily a medium of exchange and some substitute payment medium exists, inflation and output are independent.

8. 2. Empirical evidence • cross-country growth regressions to examine the correlation between inflation and output growth • growth experience of a set of countries is explained in terms of a base set of regressors including long-run trends in human and physical capital accumulation • the horizon examined is typically 25 to 30 years, from the 1960s to the mid 1990s depending on data availability • Levine and Renelt (1992) robustness examination • Results worth mentioning are those of Fischer (1993), Motley (1994), Barro (1995), Judson and Orphanides (1996)

9. 3. Data and Methodology • Data Source: Win Stars v.4.2 2002 World Development Indicators CD and • IMF’s International Financial Statistics (IFS) • 15 countries (EU member states) • 1971-2000 • Data availability: 99.03% of the observations

10. 4. Regression Analysis and Results • econometric specification GDP = Cn + λ1*LNINFL + λ2*LNCAP + λ3*RAPPIB • estimation method Pooled Least Squares Variable Coefficient Std. Error t-Statistic Prob. LNINFL? -15.24616 2.749988 -5.544081 0.0000 LNCAP? 8.214361 0.991685 8.283239 0.0000 RAPPIB? -3.497720 1.421112 -2.461256 0.0142 GLS Seemingly Unrelated Regression Variable Coefficient Std. Error t-Statistic Prob. LNINFL? -12.35785 1.734683 -7.123978 0.0000 LNCAP? 7.455170 0.638024 11.68477 0.0000 RAPPIB? -5.014583 0.937811 -5.347116 0.0000

11. White covariance estimation for the pooled least squares regression • this variance estimator is robust to heteroskedasticity within each cross-section, but does not account for the possibility of contemporaneous correlation across cross-sections • applying White covariance estimation has no effect on the values of the parameters only on their significance • the Hausman test returns the value of 7.62 significantly smaller than the value of the chi-squared distribution with three degrees of freedom (12.84) - this result suggests that the difference between the two models is relatively small

12. fixed parameters or random variables • fixed effects approach or random effects approach Variable Coefficient Std. Error t-Statistic Prob. C 14.44273 1.465471 9.855355 0.0000 LNINFL? -11.12847 2.531338 -4.396280 0.0000 LNCAP? 7.793686 0.855892 9.105919 0.0000 RAPPIB? 0.285549 0.126434 2.258485 0.0244 Random Effects _ANG--C 0.756707 _AUS--C -0.650778 _BEL--C -0.214005 _DAN--C -0.413529 _FIN--C -0.508745 _FRA--C 0.155353 _GER--C -0.289377 _GRE--C -0.319165 _IRL--C 1.185958 _ITA--C 0.263100 _LUX--C 0.270316 _OLA--C -0.254164 _POR--C -0.118365 _SPA--C 0.079639 _SUE--C 0.034922 Variable Coefficient Std. Error t-Statistic Prob. LNINFL? -15.24616 2.749988 -5.544081 0.0000 LNCAP? 8.214361 0.991685 8.283239 0.0000 RAPPIB? -3.497720 1.421112 -2.461256 0.0142 Fixed Effects _ANG--C 23.60383 _AUS--C 26.95789 _BEL--C 27.01275 _DAN--C 28.24299 _FIN--C 29.30029 _FRA--C 21.19476 _GER--C 18.64968 _GRE--C 30.12706 _IRL--C 35.71898 _ITA--C 22.86270 _LUX--C 39.01228 _OLA--C 25.47547 _POR--C 31.33270 _SPA--C 24.95936 _SUE--C 27.93454 • the Hausman test yields a value of 28.07 • random effects would introduce a bias in the regression

13. Nonlinearity of the Inflation-Growth Relation • several authors (Sarel (1996), Judson and Orphanides (1996), Ghosh and Phillips (1998), Khan and Senhadji (2000)) have raised the issue of the nonlinearity of the inflation-growth relationship • low, moderate and high inflation rate cuts

14. single kink at 5% (maximum R-squared) • specification of the spline • this result does not indicate precisely 5 percent as an optimal or growth maximizing rate of inflation (similar results at 2.5 %) • my interest is in whether a robust negative inflation-growth relationship is limited only to higher inflation range or whether it extends down much further

15. Level vs. Volatility Effect • intra-year measure of inflation volatility • correlation coefficient 0.44 (Levine and Renelt – 0.97) • the measure of volatility is intended to capture the magnitude of the underlying inflation uncertainty at the annual horizon

16. Endogeneity of the Inflation Rate • the above results need not necessarily reflect causation from inflation to growth • an inverse relation between growth and inflation would arise if an exogenous slowing of the growth rate tended to generate higher inflation • another possibility is that some omitted third variable is correlated with growth and inflation • the way to handle this type of problem is to find satisfactory instrumental variables – reasonably exogenous variables that are themselves significantly related to inflation

17. there are several instruments that can be used: • instruments that account for central bank independence ; • the idea is that independence enhances the ability of the central bank to commit to price stability and, hence, to deliver low and stable inflation • problem of constructing a relevant index • this index remains unchanged for long periods of time 2. earlier values of a country’s inflation rate; • lagged inflation is exogenous with respect to innovations in subsequent growth rates • reflects persistent characteristics of a country’s monetary policy 3. dummy variable approach can be used for specifying the instruments; • dummy variables can be employed in order to control for different time or country specific effects

18. instrumental variable: five year lag of the inflation rate (Barro (1995)) • the estimation method is two stage least squares

19. 5. Concluding Remarks • econometric specifications that took into consideration the very important cross-country unobserved heterogeneity • allowed time dimension of the data to manifest (not using multi-year average regressions) • the non-linearity has been taken into account • the endogeneity of the inflation rate was considered • significant negative effect of inflation on economic growth • this effect occurs both at moderate inflation rates but also at low levels of inflation • this effect is due both to the level and volatility of the inflation rate

20. importance for Romania • the use of other instruments to account for a possible endogeneity of the inflation rate, like, for instance, money supply indexes, could prove beneficial to remove any doubt • using a proxy for human capital accumulation would narrow the distance between theory and empirical undertakings • by restricting attention to inflation uncertainty at the annual horizon, this paper does not address the issue of long-term inflation uncertainty

21. References Andres, Javier and Ignacio Hernando (1997), “Does Inflation Harm Economic Growth? Evidence for the OECD”, NBER Working Paper 6062. Barro, Robert J. and Xavier Sala-i-Martin (1995), “Economic Growth”, New York, McGraw Hill. Barro, Robert J. (1995), “Inflation and Economic Growth”, NBER Working Paper 5326. DeGregario, Jose (1993), “Inflation, Taxation and Long-Run Growth”, Journal of Monetary Economics, 31, 271-298. Enders, Walter (1994), “Applied Econometric Time Series”, John Wiley & Sons. Ericsson, Neil R., John S. Irons, and Ralph W. Tryone (2000), “Output and Inflation in the Long-Run”, International Finance Discussion Papers, Board of Governors of the Federal Reserve System. Fisher, Stanley (1993), “The Role of Macroeconomic Factors in Growth”, NBER Working Paper 4565. Ghosh, Atish and Steven Phillips (1998), “Warning: Inflation May Be Harmful to Your Growth”, IMF Staff Papers, Vol. 45, No. 4, 672-710. Gillman, Max, Mark Harris, and Laszlo Matyas (2002), “Inflation and Growth: Some Theory and Evidence”, Central European University Department of Economics Working Paper 6/2002. Greene, William H. (1993), “Econometric Analysis”, Second Edition, New York: Macmillan. Haslag, Joseph H. (1997), “Output, Growth, Welfare, and Inflation: A Survey”, Federal Reserve Bank of Dallas, Economic Review Second Quarter, 11-21. Jones, Larry E., Rodolfo E. Manuelli, and Henry E. Siu (2000), “Growth and Business Cycles”, NBER Working Paper 7633. Judson, Ruth, and Athanasios Orphanides (1996), “Inflation, Volatility and Growth”, Finance and Economics Discussion Paper No. 96-19 (Washington: Board of Governors of the Federal Reserve System). Kormendi, Roger C. and Philip G. Meguire (1995), “Macroeconomic Determinants of Growth: Cross-Country Evidence”, Journal of Monetary Economics, 16, 141-163. Levine, Ross, and David Renelt (1992), “A Sensitivity Analysis of Cross-Country Growth Regressions”, American Economic Review, September, 942-963. Motley, Brian (1994), “Growth and Inflation: A Cross-Country Study”, Federal Reserve Bank of San Francisco Working Paper 94-08. Orphanides, Athanasios, and Robert M. Solow (2000), “Money, Inflation and Growth”, in Handbook of Monetary Economics, edited by Benjamin M. Friedman, and Frank H. Hahn, Amsterdam: North Holland. Sarel, Michael (1996) “Nonlinear Effects of Inflation on Economic Growth”, IMF Staff Papers, Vol. 43, No. 1, 199-215. Tobin, James (1965), “Money and Economic Growth”, Econometrica, 33, No.4, part 2 (October), 671-684.