THREE ESSAYS ON PRICE ANALYSIS AND INTERNATIONAL TRADE

The first chapter of this dissertation examines price discovery and volatility spillovers in the coffee spot-futures commodity market over the post-ICA period by employing the PT-IS and bivariate EGARCH models. This research covers two actively traded coffee types, Arabica and Robusta, and utilizes daily time-series price data over 1990:01-2020:04 for Arabica and over 2008:01-2020:04 for Robusta. The empirical results indicate that coffee spot markets play a dominant role in the coffee price discovery for both Arabica and Robusta. The results also show volatility spillovers take place from the coffee spot market to the futures markets. This study helps small-scale coffee growers and coffee-processing firms with their business decision makings and provides insights into the appropriate position of the spot-futures commodity markets. This study also has implications for governments of coffee exporting countries to protect their domestic coffee growers and mitigate global market risks by building necessary price risk-management mechanisms. The purpose of the second chapter is to fill a void in the literature about the driving forces behind U.S. bourbon whiskey exports. This study adopts the panel gravity model approach and introduces geographical indication and trade dispute factors to analyze bourbon trade patterns between the U.S. and 69 bourbon trade partners over 1990-2019. This study reveals that income level, free trade agreements, trade facilitation, common language, and the weighted share of adults who drink in the importing country are important factors in boosting bourbon trade flows. Yet, trade disputes between the U.S. and its trading partners are found to have significantly negative impacts on U.S. bourbon exports. Contrary to our expectation, we are unable to find evidence to confirm that U.S. bourbon’s geographical indication is playing an important role in boosting bourbon exports. This third chapter aims to investigate the dynamics and determinants of value-added agricultural comparative advantage for selected OECD nations over 2005-2015. This research adopts various indicators to measure and compare value-added and gross comparative advantages, employs OLS approach to examine the dynamics of the value-added comparative advantage, and utilizes regression analysis to identify the determinants of value-added and gross comparative advantages in agriculture. Findings reveal that land-scarce economies have higher motivation and are more successful in transforming from land-based to processing-based production types. Moreover, the dynamics of value-added comparative advantage is divergent for various OECD nations over 2005-2015. Findings also indicate that production per worker and land per worker have significant and positive influences on value-added comparative advantage, whereas labor cost per worker has negative influences