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ON THE INTERACTION BETWEEN ECONOMIC GROWTH AND BUSINESS CYCLES

Published online by Cambridge University Press:  29 March 2016

Ivan Mendieta-Muñoz
Ivan Mendieta-Muñoz*
Affiliation:
University of Kent
*
Address correspondence to: Ivan Mendieta-Muñoz, Keynes College, School of Economics, University of Kent, Canterbury CT2 7NP, Kent, UK; e-mail: [email protected].
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Abstract

The present paper studies the interaction between short-run business cycle fluctuations and economic growth at the empirical level. We identify a measure of potential output with that rate of growth consistent with a constant unemployment rate, and we estimate the effects of GDP growth rates on the latter in 13 Latin American and 18 OECD countries during the period 1981–2011. The results of both parametric (OLS/IV and a panel estimator that allows for parameter heterogeneity and cross-section dependence) and nonparametric (a penalized regression spline estimator) econometric techniques show that the measure of potential output experiences positive (negative) changes in periods of high (low) growth in the majority of countries. However, in contrast to the sample of OECD countries, we find that less than half of the sample of Latin American countries experience statistically significant changes in this measure of potential output in periods of low growth.

Keywords

Growth and CyclesPotential Rate of GrowthRate of Growth Consistent with a Constant Unemployment RateHysteresis
Type
Articles
Information
Macroeconomic Dynamics , Volume 21 , Issue 4 , June 2017 , pp. 982 - 1022
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

I am deeply grateful to Miguel León-Ledesma, Luca Zanin, and Matteo Lanzafame and to one anonymous referee for their constant help, and for valuable comments and suggestions on previous drafts of this paper. I have also benefited from comments by Olivier Blanchard, Tony Thirlwall, Jagjit Chadha, Lucia Buono, Alan Carruth, Katsutuki Shibayama, Hans-Martin Krolzig, Yu Zhu, Arne Risa Hole, and the seminar audience at the University of Kent. All remaining errors are my own.

References

REFERENCES

Abiad, Abdul, Balakrishnan, Ravi, Brooks, Petya K., Leigh, Daniel, and Tytell, Irina (2009) What's the Damage? Medium-Term Output Dynamics after Banking Crisis. IMF working paper WP/09/245.Google Scholar
Aghion, Phillipe and Saint-Paul, Gilles (1998) Uncovering some causal relationships between productivity growth and the structure of economic fluctuations: A tentative survey. Labour 12, 279–303.Google Scholar
Anderson, Theodore W. (1951) Estimating linear restrictions on regression coefficients for multivariate normal distributions. Annals of Mathematical Statistics 22, 327–351.CrossRefGoogle Scholar
Ball, Laurence (2014) Long-term damage from the Great Recession in OECD countries. European Journal of Economics and Economic Policies: Intervention 11, 149–160.Google Scholar
Ball, Laurence, De Roux, Nicolás, and Hofstetter, Marc (2013) Unemployment in Latin American and the Caribbean. Open Economies Review 24, 397–424.Google Scholar
Barlevy, Gadi (2007) On the cyclicality of research and development. American Economic Review 97, 1131–1164.Google Scholar
Barreto, Humberto and Howland, Frank (1993) There Are Two Okun's Law Relationships between Output and Unemployment. Working paper, Wabash College.Google Scholar
Baum, Christopher F., Schaffer, Mark E., and Stillman, Steven (2003) Instrumental variables and GMM: Estimation and testing. Stata Journal 3, 1–31.Google Scholar
Baum, Christopher F., Schaffer, Mark E., and Stillman, Steven (2007) Enhanced routines for instrumental variables/generalized method of moments estimation and testing. Stata Journal 7, 465–506.CrossRefGoogle Scholar
Baxter, Marianne and King, Robert G. (1993) Fiscal policy in general equilibrium. American Economic Review 83, 315–334.Google Scholar
Bianchi, Francesco and Kung, Howard (2014) Growth, Slowdowns, and Recoveries. NBER working paper 20725.CrossRefGoogle Scholar
Bijapur, Mohan (2012) Do financial crisis erode potential output? Evidence from OECD inflation responses. Economics Letters 117, 700–703.Google Scholar
Blackburn, Keith and Pelloni, Alessandra (2005) Growth, cycles, and stabilization policy. Oxford Economic Papers 57, 262–282.Google Scholar
Bond, Steve and Eberhardt, Markus (2013) Accounting for Unobserved Heterogeneity in Panel Time Series Models. Working paper, School of Economics, University of Nottingham. Available at https://sites.google.com/site/medevecon/publications-and-working-papers (accessed 27 August 2015).Google Scholar
Boyd, John H., Kwak, Sungkyu, and Smith, Bruce (2005) The real output losses associated with modern banking crises. Journal of Money, Credit and Banking 37, 977–999.Google Scholar
Breusch, Trevor S. (1978) Testing for autocorrelation in dynamic linear models. Australian Economic Papers 17, 334–355.Google Scholar
Breusch, Trevor S. and Pagan, Adrian (1979) A simple test for heteroscedasticity and random coefficient variation. Econometrica 47, 1287–1294.Google Scholar
Caballero, Ricardo J. and Hammour, Mohamad L. (1994) The cleansing effect of recessions. American Economic Review 84, 1350–1368.Google Scholar
Caballero, Ricardo J. and Hammour, Mohamad L. (2005) The cost of recessions revisited: A reverse-liquidationist view. Review of Economic Studies 72, 331–341.Google Scholar
Calderón, César and Fuentes, J. Rodrigo (2014) Have business cycles changed over the last two decades? An empirical investigation. Journal of Development Economics 109, 98–123.CrossRefGoogle Scholar
Cerra, Valerie and Saxena, Sweta C. (2008) Growth dynamics: The myth of economic recovery. American Economic Review 98, 439–457.Google Scholar
Christopoulos, Dimitris and León-Ledesma, Miguel A. (2014) Efficiency and production frontiers in the aftermath of recessions: International evidence. Macroeconomic Dynamics 18, 1326–1350.Google Scholar
Chudick, Alexander and Pesaran, M. Hashem (2013a) Large Panel Data Models with Cross-Sectional Dependence: A Survey. CESifo working paper 4371.Google Scholar
Chudick, Alexander and Pesaran, M. Hashem (2013b) Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Data Models with Weakly Exogenous Regressors. CESifo working paper 4232.Google Scholar
Comin, Diego (2009) On the integration of growth and business cycles. Empirica 36, 165–176.Google Scholar
Cumby, Robert E. and Huizinga, John (1992) Testing the autocorrelation structure of disturbances in ordinary least squares and instrumental variables regressions. Econometrica 60, 185–195.Google Scholar
Daly, Mary C., Fernald, John G., Óscar Jordá, and Fernanda Nechio (2014) Output and Unemployment Dynamics. Federal Reserve Bank of San Francisco working paper 32.Google Scholar
Davis, Steve and Haltiwanger, John (1992) Gross job creation, gross job destruction, and employment reallocation. Quarterly Journal of Economics 107, 819–864.Google Scholar
Davison, Anthony C. and Hinkley, David V. (1997) Bootstrap Methods and their Application. Cambridge, UK: Cambridge University Press.Google Scholar
DeLong, J. Bradford and Summers, Lawrence H. (1986) Is increased price flexibility stabilizing? American Economic Review 76, 1031–1044.Google Scholar
DeLong, J. Bradford and Summers, Lawrence H. (2012) Fiscal policy in a depressed economy. Brookings Papers on Economic Activity 44, 233–297.CrossRefGoogle Scholar
Doornik, Jurgen A. and Hansen, Henrik (2008). An omnibus test for univariate and multivariate normality. Oxford Bulletin of Economics and Statistics 70, 927–939.Google Scholar
Eberhardt, Markus (2012) Estimating panel time-series models with heterogeneous slopes. Stata Journal 12, 61–71.CrossRefGoogle Scholar
Eberhardt, Markus and Teal, Francis (2014) The Magnitude of the Task Ahead: Productivity Analysis with Heterogeneous Technology. Working paper, School of Economics, University of Nottingham. Available at https://sites.google.com/site/medevecon/publications-and-working-papers (accessed 27August 2015).Google Scholar
Efron, Bradley and Tibshirani, Robert J. (1994) An Introduction to the Bootstrap. CRC Monographs on Statistics and Applied Probability. Boca Raton, FL: Chapman & Hall.Google Scholar
Evans, George W., Honkapohja, Seppo, and Romer, Paul (2005) Growth cycles. American Economic Review 88, 495–515.Google Scholar
Fatás, Antonio (2000a) Do business cycles cast long shadows? Short-run persistence and economic growth. Journal of Economic Growth 5, 147–162.Google Scholar
Fatás, Antonio (2000b) Endogenous growth and stochastic trends. Journal of Monetary Economics 45, 107–128.Google Scholar
Fatás, Antonio (2002) The effects of business cycles on growth. In Loayza, Norman and Soto, Raimundo (eds.), Economic Growth: Sources, Trends and Cycles, pp. 191–220. Central Bank of Chile.Google Scholar
Fatás, Antonio and Mihov, Ilian (2013) Recoveries. Working paper prepared for the annual economic conference at the Boston Federal Reserve.Google Scholar
Fernald, John G. (2014) Productivity and Potential Output before, during and after the Great Recession. NBER working paper 20248.Google Scholar
Francois, Patrick and Lloyd-Ellis, Huw (2003) Animal spirits through creative destruction. American Economic Review 99, 530–550.Google Scholar
Francois, Patrick and Shi, Shouyong (1999) Innovation, growth, and welfare-improving cycles. Journal of Economic Theory 85, 226–257.Google Scholar
Fuller, Wayne A. (1977) Some properties of a modification of the limited information estimator. Econometrica 45, 939–953.Google Scholar
Furceri, Davide and Mourougane, Annabelle (2012) The effect of financial crisis on potential output: New empirical evidence from OECD countries. Journal of Macroeconomics 34, 822–832.Google Scholar
Furukawa, Yuichi (2007) Endogenous growth cycles. Journal of Economics 91, 69–96.Google Scholar
Furukawa, Yuichi (2013) The struggle to survive in the R&D sector: Implications for innovation and growth. Economics Letters 121, 26–29.Google Scholar
Godfrey, Leslie G. (1978) Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica 46, 1293–1301.Google Scholar
Guérin, Pierre, Maurin, Laurent, and Mohr, Matthias (2015) Trend–cycle decomposition of output and euro area inflation forecasts: A real-time approach based on model combination. Macroeconomic Dynamics 19, 363–393.Google Scholar
Hall, Robert E. (1991) Recessions as Reorganizations. Working paper prepared for the NBER Macro Annual Conference.Google Scholar
Haltmaier, Jane (2012) Do Recessions Affect Potential Output? Board of Governors of the Federal Reserve System, International Finance Discussion Paper 1066.Google Scholar
Hamilton, Lawrence C. (1991) How robust is robust regression? Stata Technical Bulletin 2, 21–26.Google Scholar
Harrod, Roy (1939) An essay in dynamic theory. Economic Journal 49, 14–33.Google Scholar
Harrod, Roy (1960) Second essay in dynamic theory. Economic Journal 70, 277–293.Google Scholar
Harrod, Roy (1970) Harrod after twenty-one years. A comment. Economic Journal 81, 737–741.Google Scholar
Hastie, Trevor and Tibshirani, Robert J. (1993) Varying-coefficient models. Journal of the Royal Statistical Society. Series B (Methodological) 55, 757–796.Google Scholar
Hayashi, Fumio (2000) Econometrics. Princeton, NJ: Princeton University Press.Google Scholar
Hosseinkouchack, Mehdi and Wolters, Maik H. (2013) Do large recessions reduce output permanently? Economics Letters 121, 516–519.Google Scholar
International Monetary Fund (2010) World Economic Outlook. Rebalancing Growth, pp. 69–107. Washington, DC: International Monetary Fund.Google Scholar
Jarque, Carlos M. and Bera, Anil K. (1987) A test for normality of observations and regression residuals. International Statistical Review 55, 163–172.Google Scholar
Kandil, Magda (1998) Supply-side asymmetry and the non-neutrality of demand fluctuations. Journal of Macroeconomics 20, 785–809.Google Scholar
Kapadia, Sujit (2005) Optimal Monetary Policy under Hysteresis. Oxford University, Department of Economics discussion paper 250.Google Scholar
Keating, John W. (2013) What do we learn from Blanchard and Quah decompositions of output if aggregate demand may not be long-run neutral? Journal of Macroeconomics 38, 203–217.Google Scholar
Kienzler, Daniel and Schmid, Kai D. (2014) Hysteresis in potential output and monetary policy. Scottish Journal of Political Economy 61, 317–396.Google Scholar
Knotek, Edward S. (2007) How useful is Okun's law? Federal Reserve Bank of Kansas City Economic Review 4, 73–103.Google Scholar
Lanzafame, Matteo (2010) The endogeneity of the natural rate of growth in the regions of Italy. International Review of Applied Economics 24, 533–552.Google Scholar
León-Ledesma, Miguel A. and Thirlwall, Anthony P. (2002) The endogeneity of the natural rate of growth. Cambridge Journal of Economics 26, 441–459.Google Scholar
Maliar, Lilia and Maliar, Serguei (2004) Endogenous growth and endogenous business cycles. Macro-economic Dynamics 8, 559–581.Google Scholar
Marra, Giampiero and Radice, Rosalba (2010) Penalised regression splines: Theory and application to medical research. Statistical Methods in Medical Research 19, 107–125.Google Scholar
Marra, Giampiero and Radice, Rosalba (2011) A flexible instrumental variable approach. Statistical Modelling 11, 581–603.Google Scholar
Matsuyama, Kiminori (1999) Growing through cycles. Econometrica 67, 335–347.Google Scholar
Murphy, Kevin M. and Topel, Robert H. (1985) Estimation and inference in two-step econometric models. Journal of Business and Economic Statistics 3, 370–379 Google Scholar
Nuño, Galo (2011) Optimal research and development and the cost of business cycles. Journal of Economic Growth 16, 257–283.Google Scholar
Orphanides, Athanasios and Solow, Robert M. (1990) Money, inflation and growth. In Friedman, Benjamin M. and Hahn, Frank H. (eds.), Handbook of Monetary Economics, pp. 223–261. San Diego: North-Holland.Google Scholar
Pagan, Adrian (1984) Econometric issues in the analysis of regressions with generated regressors. International Economic Review 25, 221–247.Google Scholar
Pagan, Adrian and Hall, Anthony D. (1983) Diagnostic tests as residual analysis. Econometric Reviews 2, 159–218.Google Scholar
Papell, David H. and Prodan, Ruxandra (2012) The statistical behavior of GDP after financial crisis and severe recessions. B.E. Journal of Macroeconomics 12, 1–29.Google Scholar
Pedersen, Torben M. and Elmer, Anne M. (2003) International evidence on the connection between business cycles and economic growth. Journal of Macroeconomics 25, 255–275.Google Scholar
Pesaran, M. Hashem (2004) General Diagnostic Tests for Cross Section Dependence in Panels. IZA discussion paper 1240.Google Scholar
Pesaran, M. Hashem (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74, 967–1012.Google Scholar
Pesaran, M. Hashem and Smith, Ron (1995) Estimating long-run relationships from dynamic heterogeneous panels. Journal of Econometrics 68, 79–113.Google Scholar
Pesaran, M. Hashem and Smith, Ron (1999) Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association 94, 621–634.Google Scholar
Pesaran, M. Hashem and Taylor, Larry W. (1999) Diagnostics for IV regressions. Oxford Bulletin of Economics and Statistics 61, 255–281.Google Scholar
Posch, Olaf and Wälde, Klaus (2011) On the link between volatility and growth. Journal of Economic Growth 16, 285–308.Google Scholar
Ramsey, James B. (1969) Tests for specification errors in classical linear least-squares regression analysis. Journal of the Royal Statistical Society. Series B (Methodological) 31, 350–371.Google Scholar
Reifschneider, Dave, Wascher, William, and Wilcox, David (2013) Aggregate Supply in the United States: Recent Developments and Implications for the Conduct of Monetary Policy. Paper presented at the 14th Jaques Polak Annual Research Conference.Google Scholar
Reinhart, Carmen and Rogoff, Keneth S. (2014) Recovery from financial crisis: Evidence from 100 episodes. American Economic Review 104, 50–55.CrossRefGoogle Scholar
Saint-Paul, Gilles (1997) Business cycles and long-run growth. Oxford Review of Economic Policy 13, 145–153.CrossRefGoogle Scholar
Schnabel, Gert (2002) Output Trends and Okun's Law. Bank for International Settlements (BIS) working paper 111.Google Scholar
Sedgley, Norman and Elmslie, Bruce (2013) The dynamic properties of endogenous growth models. Macroeconomic Dynamics 17, 1118–1134.Google Scholar
Stadler, George W. (1990) Business cycle models with endogenous technology. American Economic Review 80, 763–778.Google Scholar
Stiglitz, Joseph E. (1994) Endogenous growth and cycles. In Shionoya, Yuichi and Perlman, Mark (eds.), Innovation in Technology, Industries, and Institutions: Studies in Schumpeterian Perspectives, pp. 121–156. Ann Arbor: The University of Michigan Press.Google Scholar
Stock, James H., Wright, Jonathan H., and Yogo, Motohiro (2002) A survey of weak instruments and weak identification in generalized method of moments. Journal of Business and Economic Statistics 20, 518–529.Google Scholar
Stock, James H. and Yogo, Motohiro (2005) Testing for weak instruments in linear IV regression. In Andrews, Donald W.K. and Stock, James H. (eds.), Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg, pp. 80–108. Cambridge, UK: Cambridge University Press.Google Scholar
Thirlwall, Anthony P. (1969) Okun's law and the natural rate of growth. Southern Economic Journal 36, 87–89.Google Scholar
Tobin, James (1965) Money and economic growth. Econometrica 7, 671–684.Google Scholar
Wälde, Klaus (2005) Endogenous growth cycles. International Economic Review 46, 867–894.Google Scholar
Wiesenfarth, Manuel, Hisgen, Carlos Matías, Kneib, Thomas, and Cadarso-Suarez, Carmen (2014) Bayesian nonparametric instrumental variables based on penalized splines and Dirichlet process mixtures. Journal of Business and Economic Statistics 32, 468–481.Google Scholar
Wood, Simon N. (2003) Thin plate regression splines. Journal of the Royal Statistical Society Series B (Statistical Methodology) 65, 95–114 Google Scholar
Wood, Simon N. (2006) Generalized Additive Models: An Introduction with R. London: Chapman & Hall.Google Scholar
Zanin, Luca and Marra, Giampiero (2012) Rolling regression versus time-varying coefficient modelling: An empirical investigation of the Okun's law in some euro area countries. Bulletin of Economic Research 64, 91–108.Google Scholar