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Appendix A. Proofs
Appendix B. Oil Price Decompositions
Appendix C. Empirical Results
I am grateful to Christopher Carroll, Pravin Krishna, Mark Gersovitz, Ketil Hviding, Dmitriy Kovtun and Alan Gelb for their invaluable comments, and Elif Arbatli for kindly providing her dataset. All remaining errors are mine.
This may have played a role in why studies that used aggregated data – such as Gelb (1988), and Spatafora and Warner (1995) – could not find evidence of Dutch disease in manufacturing due to oil booms.
Gelb (1988) finds that Ecuador, Iran, Nigeria and Trinidad and Tobago went through the Dutch disease, mainly due to a decline in Agriculture, over the first and second oil booms of 1972–81, while Algeria, Indonesia and Venezuela went through a strengthening of their non-oil tradables.
Though the Stopler-Samuelson theorem is meant for two tradable sectors, the same concept can be extended here.
While Proposition 7 illustrates the variation in the tradable sector’s elasticity to oil shocks between open and closed capital markets, it does not indicate the impact of capital account liberalization itself on the level of tradable production. The effect of capital account liberalization on tradable production depends on the capital abundance of the country relative to the world. However, Proposition 7 may have normative implications through the higher exposure of the tradable sector to oil volatility through an open capital market.
An issue here is the short time span of the cross section, which makes estimates sensitive to assumptions on initial capital stock.
Lane and Milesi-Ferretti (2006) uses (stock of FDI assests + stock of FDI liabilities)/Gross Domestic Product.
All standard errors in these estimations are clustered by sector per country for robustness.
I use λ = 1600 for the H-P filter’s value function.
This result is consistent with Arbatli (2008) which finds a significant impact of these futures prices based Kalman filtered shocks on consumption across a sample of oil-exporting countries.
My sample division is based on a capital market openness index cutoff of 0.2. For countries with less open capital markets, I use Colombia, Iran, Kuwait, Indonesia and Mexico. The other group includes Ecuador, Russia, Trinidad and Tobago, Malaysia, Gabon, Nigeria, and Venezuela). I eliminated Canada, Norway and the UK from this test since their Dutch disease results were weak possibly due to a high degree of windfall sterilization.
Using the Chow test, I can reject the hypothesis that the coefficient for the group with more open capital markets is equal to that of the other group at up to the 93 percent confidence interval.
I use shocks to oil price rather than windfall since relative factor prices and factor intensities are unit-less ratios, whereas windfall shocks are not. Here, the oil price shock is considered as a relative price shock of oil to other goods since the permanent price shock includes only unanticipated innovations in the oil price.
I use the revision 2 edition of the dataset.