Many contributions in the recent literature have investigated over the relationship between GDP growth and its volatility without getting a clear and unambiguous answer. Besides reassessing the well-known effect of output volatility on growth as benchmark analysis, this study aims at looking into the “black box” of the business cycle volatility by disentangling the impacts of volatility of GDP major components—that is, private consumption, private investment and government expenditure—on growth, simultaneously considered. Our empirical analysis unveils a remarkably robust and strong negative correlation of consumption volatility with mean growth and a positive one with volatility of investment and of public expenditure. If these findings shed some additional light on the (still controversial) relationship between economic fluctuations and growth, they will also make it possible to compare the relative impact of each component, with possibly relevant policy implications. Importantly, this might reconcile opposite views about the issue that different empirical results might originate from the relative importance across empirical studies of the various components of volatility. 1. Introduction Among the issues economists largely debated upon over the recent decades, the relationship between the volatility of business cycle and output growth deserves a particular attention. Nonetheless, for a long time, long-run growth and business cycle were conceived of as independent phenomena to be analyzed by means of separated tools. This view was strongly supported by Lucas [1] who claimed that the trade-off between growth and business cycle fluctuations was pretty inexistent. Then, the Real Business Cycle (RBC) paradigm [2] pointed to the exogenous stochastic process driving the technological progress as the common root of both trend growth and cyclical fluctuations. However, once the endogenous technological progress hypothesis was introduced into the RBC framework [3, 4] the idea of a causal relationship between the instability of the business cycle and growth gained theoretical support, thereby prompting the subsequent empirical literature on volatility and growth (see Aghion and Saint-Paul [5] for a very interesting analysis of the theoretical evolution on this issue and Gaggl and Steindl [6] for a literature review on growth and cycle). This paper is meant to contribute to the stream of literature which aimed at verifying both the existence of a statistically significant causal relationship between output volatility and growth and the sign of that relationship.
References
[1]
R. E. Lucas Jr., Models of Business Cycles, Basil Blackwell, New York, NY, USA, 1987.
[2]
E. Kydland and E. C. Prescott, “Time to build and aggregate fluctuations,” Econometrica, vol. 50, no. 6, pp. 1345–1370, 1982.
[3]
G. W. Stadler, “Business cycle models with endogenous technology,” American Economic Review, vol. 80, no. 4, pp. 763–778, 1990.
[4]
R. G. King and S. Rebelo, “Public policy and economic growth: developing neoclassical implications,” Journal of Political Economy, vol. 98, no. 5, pp. S126–S150, 1990.
[5]
P. Aghion and G. Saint-Paul, “Virtues of bad times: interaction between productivity growth and economic fluctuations,” Macroeconomic Dynamics, vol. 2, no. 3, pp. 322–344, 1998.
[6]
P. Gaggl and S. Steindl, “Business cycles and growth: a survey,” WIFO Working Papers 308, 2007.
[7]
G. Ramey and V. A. Ramey, “Cross-country evidence on the link between volatility and growth,” The American Economic Review, vol. 85, pp. 1138–1151, 1995.
[8]
P. Martin and C. A. Rogers, “Stabilization policy, learning-by-doing, and economic growth,” Oxford Economic Papers, vol. 49, no. 2, pp. 152–166, 1997.
[9]
V. Hnatkovska and N. Loayza, “Volatility and growth,” in Managing Economic Volatility and Crises: A Practitioner's Guide, J. Aizenman and B. Pinto, Eds., Cambridge University Press, Cambridge, UK, 2005.
[10]
M. A. Kose, E. S. Prasad, and M. E. Terrones, “How do trade and financial integration affect the relationship between growth and volatility?” Journal of International Economics, vol. 69, no. 1, pp. 176–202, 2006.
[11]
J. Imbs, “Growth and volatility,” Journal of Monetary Economics, vol. 54, no. 7, pp. 1848–1862, 2007.
[12]
R. C. Kormendi and P. G. Meguire, “Macroeconomic determinants of growth: cross-country evidence,” Journal of Monetary Economics, vol. 16, no. 2, pp. 141–163, 1985.
[13]
K. B. Grier and G. Tullock, “An empirical analysis of cross-national economic growth, 1951–1980,” Journal of Monetary Economics, vol. 24, no. 2, pp. 259–276, 1989.
[14]
T. Caporale and B. McKiernan, “The relationship between output variability and growth: evidence from post war UK data,” Scottish Journal of Political Economy, vol. 43, no. 2, pp. 229–236, 1996.
[15]
J. A. Schumpeter, Capitalism, Socialism, and Democracy, Harper and Brothers, New York, NY, USA, 1976, Harper Colophon edition.
[16]
S. Davis and J. C. Haltiwanger, “Gross job creation, gross job destruction, and employment reallocation,” The Quarterly Journal of Economics, vol. 107, no. 3, pp. 819–863, 1992.
[17]
C. R. Bean, “Endogenous growth and the procyclical behaviour of productivity,” European Economic Review, vol. 34, no. 2-3, pp. 355–363, 1990.
[18]
R. Caballero and M. Hammour, “The cleansing effect of recessions,” American Economic Review, vol. 84, no. 5, pp. 383–398, 1991.
[19]
K. J. Arrow, “The economic implications of learning by doing,” Review of Economic Studies, vol. 29, pp. 155–173, 1962.
[20]
A. Shleifer, “Implementation Cycles,” Journal of Political Economy, vol. 94, no. 6, pp. 1163–1190, 1986.
[21]
K. Blackburn and A. Pelloni, “On the relationship between growth and volatility,” Economics Letters, vol. 83, no. 1, pp. 123–127, 2004.
[22]
A. Afonso and D. Furceri, “Government size, composition, volatility and economic growth,” European Journal of Political Economy, vol. 26, no. 4, pp. 517–532, 2010.
[23]
A. Fatàs and I. Mihov, “Policy volatility, institutions and economic growth,” Review of Economics and Statistics, vol. 95, no. 2, pp. 362–376, 2013.
[24]
G. Schnabl, “Exchange rate volatility and growth in small open economies at the EMU periphery,” Economic Systems, vol. 32, no. 1, pp. 70–91, 2008.
[25]
P. Aghion, P. Bacchetta, R. Rancière, and K. Rogoff, “Exchange rate volatility and productivity growth: the role of financial development,” Journal of Monetary Economics, vol. 56, no. 4, pp. 494–513, 2009.
[26]
R. Judson and A. Orphanides, “Inflation, volatility and growth,” International Finance, vol. 2, no. 1, pp. 117–138, 1999.
[27]
F. Al-Marhubi, “Cross-country evidence on the link between inflation volatility and growth,” Applied Economics, vol. 30, no. 10, pp. 1317–1326, 1998.
[28]
D. Furceri, “Long-run growth and volatility: which source really matters?” Applied Economics, vol. 42, no. 15, pp. 1865–1874, 2010.
[29]
F. Black, Business Cycles and Equilibrium, Blackwell, Cambridge, Mass, USA, 1987.
[30]
L. Mirman, “Uncertainty and optimal consumption decisions,” Econometrica, vol. 39, pp. 179–185, 1971.
[31]
J. Sachs and X. Sala-i-Martin, “Fiscal federalism and optimum currency areas: evidence for Europe from the US,” NBER Working Paper 3885, 1991.
[32]
P. Asdrubali, B. E. S？rensen, and O. Yosha, “Channels of interstate risk sharing: United States 1963–1990,” Quarterly Journal of Economics, vol. 111, no. 4, pp. 1080–1110, 1996.
[33]
R. Lensink, H. Bo, and E. Sterken, “Does uncertainty affect economic growth? An empirical analysis,” Review of World Economics, vol. 135, no. 3, pp. 393–396, 1999.
[34]
M. Rafferty, “The effects of expected and unexpected volatility on long-run growth: evidence from 18 developed economies,” Southern Economic Journal, vol. 71, no. 3, pp. 582–591, 2005.
[35]
J. A. Edwards, “Dynamics of the cross-country growth/volatility relationship,” Global Economy Journal, vol. 7, no. 2, article 4, 2007.
[36]
A. Heston, R. Summers, and B. Aten, “Penn World Table Version 6.3,” 2010.
[37]
R. Barro and J. W. Lee, “A new data set of educational attainment in the world, 1950–2010,” NBER Working Paper 15902, 2010.
[38]
K. S. Im, M. H. Pesaran, and Y. Shin, “Testing for unit roots in heterogeneous panels,” Journal of Econometrics, vol. 115, no. 1, pp. 53–74, 2003.
[39]
H. S. Esfahani, “Understanding economic growth in specific contexts: an overview of the first phase of global research project ‘explaining growth’,” in Diversity in Economic Growth: Global Insights and Explanations, Edward Elgar Publishing, Glos, UK, 2009.
[40]
W. Easterly and A. Kraay, “Small states, small problems? Income, growth, and volatility in small states,” World Development, vol. 28, no. 11, pp. 2013–2027, 2000.
[41]
L. Pritchett, “A conclusion to cross national growth research: a foreword ‘to the countries themselves’,” in Explaining Growth. A Global Research Project, G. McMahon and L. Squire, Eds., chapter 6, 2003.
[42]
R. Levine and D. Renelt, “A sensitivity analysis of cross-country growth regressions,” American Economic Review, vol. 82, no. 4, pp. 942–963, 1992.
[43]
C. F. Baum, M. E. Schaffer, and S. Stillman, “Enhanced routines for instrumental variables/generalized method of moments estimation and testing,” The Stata Journal, vol. 7, no. 4, pp. 465–506, 2007.
[44]
Schaffer, “XTIVREG2: Stata module to perform extended IV/2SLS, GMM and AC/HAC, LIML and k-class regression for panel data models,” Statistical Software Components S456501, Boston College Department of Economics, 2005.
[45]
S. J. Nickell, “Biases in dynamic models with fixed effects,” Econometrica, vol. 49, no. 6, pp. 1417–1426, 1981.
[46]
R. A. Judson and A. L. Owen, “Estimating dynamic panel data models: a guide for macroeconomists,” Economics Letters, vol. 65, no. 1, pp. 9–15, 1999.
[47]
J. F. Kiviet, “On bias, inconsistency, and efficiency of various estimators in dynamic panel data models,” Journal of Econometrics, vol. 68, no. 1, pp. 53–78, 1995.
[48]
T. W. Anderson and C. Hsiao, “Formulation and estimation of dynamic models using panel data,” Journal of Econometrics, vol. 18, no. 1, pp. 47–82, 1982.
[49]
M. Arellano and S. Bond, “Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations,” The Review of Economic Studies, vol. 58, pp. 277–297, 1991.
[50]
G. S. F. Bruno, “XTLSDVC: stata module to estimate bias corrected LSDV dynamic panel data models,” Statistical Software Components S450101, Boston College Department of Economics, 2005.
[51]
M. N. Harris and L. Mátyás, “A comparative analysis of different IV and GMM estimators of dynamic panel data models,” International Statistical Review, vol. 72, no. 3, pp. 397–408, 2004.
[52]
M. Arellano and O. Bover, “Another look at the instrumental variable estimation of error-components models,” Journal of Econometrics, vol. 68, no. 1, pp. 29–51, 1995.
[53]
R. Blundell and S. Bond, “Initial conditions and moment restrictions in dynamic panel data models,” Journal of Econometrics, vol. 87, no. 1, pp. 115–143, 1998.
[54]
D. Roodman, “How to do xtabond2: an introduction to “Difference” and “System” GMM in Stata,” Center For Global Development Working Paper 103, 2006.
[55]
D. Roodman, “A short note on the theme of too many instruments,” Center For Global Development Working Paper 125, 2007.
[56]
G. Saint-Paul, “Productivity growth and the structure of the business cycle,” European Economic Review, vol. 37, pp. 861–890, 1993.
