Evaluating Growth Volatility Susceptibility within Regional Free Trade Agreements

This paper looks at the effects on trading partners that are included and not included in a Regional Free Trade Agreement (RFTA). Using the system GMM methodology, we consider six control variables to determine whether the volatility is more pronounced in non-RFTA countries (Type 1) or countries that are RFTA trading partners (Type 2). The results are three-fold: 1. whether a country is in an agreement or not there is statistically significant volatility spillover from trading partner economies, 2. being in a RFTA does not insulate oneself from non-RFTA countries, and 3. participating in a RFTA actually increases susceptibility to volatility from other RFTA countries. We conclude that it may be more harmful to be in a RFTA because of the increase in volatility exposure among trading partners relative to not joining a RFTA.

[1]  Norman V. Loayza,et al.  Does Openness Imply Greater Exposure? , 2005 .

[2]  R. Barro,et al.  International Data on Educational Attainment Updates and Implications , 2000 .

[3]  A. Venables.  Winners and Losers from Regional Integration Agreements , 2003 .

[4]  I. Down.  Trade Openness, Country Size and Economic Volatility: The Compensation Hypothesis Revisited , 2007 .

[5]  Joseph E. Stiglitz,et al.  Economic Crises: Evidence and Insights from East Asia , 1998 .

[6]  Rodney D. Ludema.  Increasing returns, multinationals and geography of preferential trade agreements , 2002 .

[7]  Jeffrey D. Sachs,et al.  External Debt and Macroeconomic Performance in Latin America and East Asia , 1985 .

[8]  M. Arellano,et al.  Another look at the instrumental variable estimation of error-components models , 1995 .

[9]  F. Windmeijer.  A Finite Sample Correction for the Variance of Linear Two-Step GMM Estimators , 2000 .

[10]  R. Blundell,et al.  Initial Conditions and Moment Restrictions in Dynamic Panel Data Models , 1998 .

[11]  Cheng Hsiao,et al.  Formulation and estimation of dynamic models using panel data , 1982 .

[12]  M. Arellano,et al.  Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations , 1991 .

[13]  H. Glejser.  A New Test for Heteroskedasticity , 1969 .

[14]  Silvana Tenreyro,et al.  Volatility and Development , 2005 .

[15]  E. Mendoza.  Terms-of-trade uncertainty and economic growth , 1997 .

[16]  J. Williamson,et al.  Winners and losers in the commodity lottery: The impact of terms of trade growth and volatility in the Periphery 1870–1939 , 2007 .

[17]  Russell Hillberry,et al.  A Decomposition of North American Trade Growth Since NAFTA , 2002 .

[18]  Robert Lensink,et al.  Foreign Direct Investment: Flows, Volatility, and the Impact on Growth , 2006 .

[19]  F. Sturzenegger,et al.  On the Consequences of Sudden Stops , 2004 .

[20]  F. Thames,et al.  Measuring the Dissemination of Volatility across Levels of Development , 2006 .

[21]  Elhanan Helpman,et al.  North-South R & D Spillovers , 1997 .

[22]  Joseph E. Stiglitz,et al.  Shaken and Stirred: Explaining Growth Volatility , 2003 .

[23]  A. Krueger.  Are Preferential Trading Arrangements Trade-Liberalizing or Protectionist? , 1999 .

[24]  David R. Cameron,et al.  The Expansion of the Public Economy: A Comparative Analysis , 1978, American Political Science Review.

[25]  F. Windmeijer.  A Finite Sample Correction for the Variance of Linear Two-Step GMM Estimators , 2000 .

[26]  A. Rebucci,et al.  How might CAFTA change macroeconomic fluctuations in Central America?: Lessons from NAFTA , 2005 .

[27]  Robustifying Glejser test of heteroskedasticity , 2000 .

[28]  David Roodman.  How to do Xtabond2: An Introduction to Difference and System GMM in Stata , 2006 .