Search results

The exchange rate has been an important topic in the Turkish Economy for many years. It affects prices with exchange rate pass-through. The aim of this chapter is to analyze the dual relationship between exports and imports, exports and the exchange rate, imports and the exchange rate by using time series analysis. The results indicate that there is only one causal relationship between exports and imports. The direction is from imports to exports.

This study constructs a comprehensive, internationally comparative set of foreign trade data for the period 1857–1875. The dataset is constructed using information at the commodity group-level and contains import and export values for the UK, France, the Zollverein, the Netherlands, Belgium, Austria-Hungary, and the United States, itemised by trade partner. The study tackles three basic problems related to the heterogeneity in national statistics of the period: different definitions of aggregates, inadequate ‘official’ pricing, and the ‘proximity bias’, i.e. the misleading practice of crediting imports to bordering countries from where they physically entered, but where they did not originate. After passing successfully a consistency test, the resulting dataset contains harmonised and country of origin-corrected bilateral trade values for 7 central importers, 10 points in time, and 21 commodity groups, along with ad valorem tariff rates for all commodity groups and countries. They offer new detailed insights into the composition and evolution of trade and tariffs in the third quarter of the 19th century. Furthermore, a basic implementation of the gravity equation shows that as a consequence of the proximity bias estimates using uncorrected data are to be taken with care, especially when assessing border effects and the impact of policy variables.

The present study deals with the growth performance of export (X), ­import (M), and economic growth (Y) in India over the period 1970–1971 to 2016–2017 as well as tariff (TR) for the period 1990–2017 by employing the methodology of one-time endogenous structural break suggested by Zivot and Andrews (1992). Also, an attempt has been taken to examine the direction of causality between the above-mentioned trade-related variables and economic growth using Granger Causality Test. Results of estimation reveal that all the variables converge toward a stationarity process having constant variability overtime. There exists structural break in the year 1996, 2006, 2008, and 2010, respectively, for economic growth, tariff, imports, and exports. Bidirectional causality is found running from economic growth to tariff and from tariff to economic growth. But there is unidirectional causality from imports to tariff, imports to exports and from exports to tariff.

The aim of this chapter is to develop a strong research base for the academia and the industry to understand the importance of data analytics in International Trade. This chapter focuses on the case of cotton trade from India and explores different methodologies developed by the World Bank and International Trade Center to analyze the Big Data available on export and import. Through Big Data analysis, this chapter attempts to find out the export performance, market demand, export potential, and attractive markets for Indian cotton. This chapter also explores the trade competitiveness of Indian cotton over the years. The data through appropriate analysis can address some simple yet complicated questions in trade like what export potential the commodity holds, if the commodity is competitive or not in international market, what are new markets to look up to, and other similar questions. In other words, this information could make huge difference in decision-making of traders and policymakers directly, and farmers indirectly.