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Income and Price Elasticities of Croatian Trade – A Panel Data Approach by Vida Bobic Discussant: K. Zigic CERGE-EI Prague, Czech Republic The Fifteenth.

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Presentation on theme: "Income and Price Elasticities of Croatian Trade – A Panel Data Approach by Vida Bobic Discussant: K. Zigic CERGE-EI Prague, Czech Republic The Fifteenth."— Presentation transcript:

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

2 Summary of the Paper Objective: – analysis of factors determining Croatian merchandise trade Motivation: large trade deficits of Croatia Methodology: – Panel data for , 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 – Shouldnt the equation include x it instead of x it ? – 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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