Trade Impact on Real Income: Cross-Country Heterogeneity

1. Is the effect of international trade on real income the same for all countries? • No, of course not! • Existing studies on trade and income use • cross-country regressions or • homogeneous panel data models.

2. Cross-country heterogeneity and the trade-income relationship Dierk HerzerChair of Economic Development and Integration, Johann Wolfgang Goethe-University Frankfurt am Main, Germany

3. Contributions • Heterogeneous panel cointegration techniques • to estimate the impact of trade on income for 81 developed and developing countries both individually and as a whole. • Variable-selection approach • to systematically search for country-specific conditions that are important factors in explaining the cross-country differences in the effect of trade on income.

4. Organisation • The impact of trade on income • The determinants of the impact of trade on income • Conclusions

5. The impact of trade on incomeModel and data • ln(Yit) = ai + δit + βln(Tit) + eit • Real (PPP) GDP per worker • Trade relative to GDP at PPP • 81 countries over the period 1960 to 2003 • Unit root tests • Cointegration tests • Estimates of the long-run relationship

6. The impact of trade on incomePanel unit root testsIm, Pesaran, and Shin (2003) (IPS); Cross-sectionally augmented IPS test proposed by Pesaran (2007) (CIPS)

7. The impact of trade on incomePanel cointegration testsMadalla and Wu (1999); Larsson et al. (2001); Pedroni (1999, 2004); Holly et al. (2009, forthcoming)

8. The impact of trade on incomeThe long-run relationship between trade and income • ln(Yit) = ai + δit + βln(Tit) + eit • Between-dimension, group-mean panel DOLS estimator suggested by Pedroni (2001) • allows for heterogeneous cointegrating vectors • does not suffer from endogeneity bias • ln(Yit) = ai + δit + 0.165**ln(Tit); t-value: 6.4

9. The long-run relationship between trade and income

10. The long-run relationship between trade and income

11. The determinants of the impact of trade on income • Bormann et al. (2006); Freund and Bolaky (2008) • the effect of trade on income is negatively related to the level of regulation. • no robust association between the income effect of trade and institutional quality. • They use cross-country income regressions that include interaction terms between trade and a small number of potential determinants of the income effect of trade. • In this study, we follow a different approach: • We use a regression model with the estimated income effect as dependent variable to consider a large number of possible determinants of the trade-income relationship.

12. The determinants of the impact of trade on incomeVariables and data

13. The determinants of the impact of trade on incomeVariables and data

14. The determinants of the impact of trade on incomeEmpirical analysis • General-to-specific model selection approach suggested by Hoover and Perez (2004). • General model • Eq.1 Eq.2 Eq.3 Eq.4 Eq.5 • Stepwise elimination of insignificant variables • Eq.1’ Eq.2’ Eq.3’ Eq.4’ Eq.5’ • Final model

15. The determinants of the impact of trade on incomeEmpirical analysis

16. The determinants of the impact of trade on incomeEmpirical analysis

17. Conclusions • A one percent increase in the trade share of GDP yields, on average, a statistically significant increase in income per worker of about 0.16 percent. • There are large cross-country differences in the income effect of trade, in particular between developed and developing countries. • The cross-country differences in the income effect of trade can be explained by cross-country differences in primary export dependence, labour market regulation, and property rights protection.

18. Thank youforyour attention!