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We explore how different data aggregation levels affect the gravity estimates of non‐tariff barriers (NTBs) in the agro‐food sector, and we examine their related impacts on policy simulations of an expansion to the European Union (EU) that would include Turkey. We calculate two sets of ad valorem equivalents (AVEs) of NTBs using the gravity approach to disaggregated and aggregated Central Product Classification data for 15 Global Trade Analysis Project (GTAP) agro‐food sectors. We find that the AVEs of NTBs vary substantially across products and that using aggregated data primarily results in greater effects of NTBs. In a second step, we incorporate the AVEs of NTBs into the GTAP model to evaluate Turkey's EU membership and conclude that aggregation bias has considerable effects on both the estimation of NTBs and the general equilibrium simulation results. Utilising different data aggregation levels leads to a great variability of trade costs of NTBs and, hence, to misleading trade and welfare effects. 相似文献
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Mehmet F. Dicle Aydin Beyhan Lee J. Yao 《International Review of Economics & Finance》2010,19(2):313-339
This study evaluates one of the most important emerging markets, India (Bombay Stock Exchange and Indian National Exchange), for its efficiency and for its potential to offer diversification benefits to international investors. Market-wide tests include; 1) contemporaneous relationship, 2) Granger type causality and 3) day-of-the-week effect. Tests on individual Indian stocks include: 1) panel estimation of Granger causality, 2) stock-by-stock estimation of Granger causality and 3) runs test. In sum, Indian markets are well integrated with the international equity markets, a characteristic that lowers the international diversification benefits. While day-of-the-week effect is an international spillover, it may be possible to predict individual Indian stocks' returns through causality with international equity markets and through momentum trading techniques. 相似文献
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