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Intra-industry trade in a vertical differentiation framework

Başlık çevirisi mevcut değil.

  1. Tez No: 400930
  2. Yazar: AYŞEN HİÇ GENCER
  3. Danışmanlar: PROF. WLLIAM P. ANDERSON
  4. Tez Türü: Doktora
  5. Konular: Ekonomi, Economics
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 2006
  8. Dil: İngilizce
  9. Üniversite: Boston University
  10. Enstitü: Yurtdışı Enstitü
  11. Ana Bilim Dalı: Belirtilmemiş.
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: 153

Özet

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Özet (Çeviri)

An intra-industry trade model was developed to explain trade between countries with similar endowments. The model is a variant of New Economic Geography (NEG) models, which differ from Heckscher-Ohlin-Vanek framework by their assumption of Dixit-Stiglitz type of monopolistic competition and increasing returns to scale production function, resulting in specialization of production and intra-industry trade. This model differs from Krugman's NEG framework in assuming vertical differentiation of goods and consumers' different income levels as the driving force for the existence of differentiated goods on the market, rather than consumers' love of variety. The standard vertical differentiation framework was modified such that consumers' income distribution results in firms in a poor country producing lower quality and cheaper goods, while firms in a rich country specialize in higher quality and more expensive goods. Trade of these goods within the same category explains the intra-industry trade. A computer program was written to solve consumer's and producer's optimization problems numerically. This program was used with different input variables to analyze trends predicted by the model. In order to test the predictive power of the model, EU trade data for years 1976- 1987 was used. In these tests trade patterns between the EU countries and one partner country, which could be either poorer or richer than EU countries, was examined. First, the model was tested directly by inputting actual income and population data into the computer program and comparing the predictions with EU trade data. Then, trends predicted by the model were formulated and the resulting five hypotheses were tested by employing OLS. Overall, the model is fairly successful in explaining trade patterns to and from EU countries in apparel and in food industries. However, in some cases there are special relationships between countries that cannot be explained solely based on income and population. These are exogenous to the model and have to be represented in the empirical analysis by employing the dummy variables method. Inclusion of transportation costs improves the predictive ability of the model. An increase in transportation costs between trading countries affects trade in both directions negatively, controlling for all other factors.

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