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Income and Price Elasticities of Croatian Trade – A Panel Data Approach by Vida Bobic

The Fifteenth Dubrovnik Economic Conference Organized by the Croatian National Bank. Income and Price Elasticities of Croatian Trade – A Panel Data Approach by Vida Bobic. Discussant : K. Zigic CERGE-EI Prague, Czech Republic. Summary of the Paper. Objective:

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Income and Price Elasticities of Croatian Trade – A Panel Data Approach by Vida Bobic

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  1. The Fifteenth Dubrovnik Economic Conference Organized by the Croatian National Bank Income and Price Elasticities of Croatian Trade – A Panel Data Approachby Vida Bobic Discussant: K. Zigic CERGE-EI Prague, Czech Republic

  2. Summary of the Paper • Objective: • analysis of factors determining Croatian merchandise trade • Motivation: large trade deficits of Croatia • Methodology: • Panel data for 2000-2007, sectoral level (30 NCEA sectors) • Models with lagged explained variable estimated by Arellano & Bond (1991) methodology • Domestic and foreign commodities treated as imperfect substitutes • Independent estimates of export and import function • Imports assumed to depend on domestic GDP, import price, tariffs, exchange rate • Exports function of world GDP, export price, and exchange rate • Croatia treated as a small country

  3. Comments (1): Motivation • Page 1: • “… current account deficit. This deficit is, in turn, for the most part a consequence of a large deficit in merchandise trade” • Small conceptual objection • Deep current account deficits are mostly results of deeper macroeconomic disequilibria • While Croatia indeed has deep trade deficit, the current account deficit is lower thanks to services account

  4. Current Accounts of Selected New EU Members% of GDP Source: World Development Indicators

  5. Comments (2): Econometric Methodology • Page 9, equation 2 – demonstration of Arellano & Bond framework • Shouldn’t the equation include xit instead of xit ? • Could Blundell & Bond (1998) further improve the methodology?

  6. Comments (3a): Variables • Tariffs omitted from export equation because: • “The very large number of countries to which goods are being exported and the resulting equally large number of different tariffs being applied to those exports makes the construction of a single tariff indicator very difficult” • But: EU accounts for about 60% of Croatian exports and it has common tariff schedule • How about using the EU common tariff as proxy?

  7. Comments (3b): Variables • Tariff measure used in the import equation is derived as tariff revenues / total value of imports • Problem: interaction between tariff rate and volume of imports, higher protection does not always mean higher revenue from the tariff • Possible solution: • Simple non-weighted average tariffs are often used in trade literature (they are imperfect too, but may lead to less biased results in the presence of highly protected sectors)

  8. Conclusion • Author met the main objective (estimation of income and price elasticities) • Estimates are made with the use of more reliable methodology than many previous applied papers (simple fixed effects or OLS are not uncommon) • Results seem to be in line with both previous estimates and expectations. However, look more into the issue of quality upgrading

  9. References • Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and application to employment equations. Review of Economic Studies, 58, 227–297. • Blundell, R. W., & Bond, S. R. (1998). Initial conditions and moment restrictions in dynamic panel data model. Journal of Econometrics, 87, 115–143. • World Bank: World Development Indicators

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