What drives international trade? Robust analysis for the European Union

Abstract

Economic literature is full of theories explaining international trade flows and empirical studies striving to verify them. Most of these attempts focus on the verification of single theory at a time without regard to the problem of model uncertainty. As a consequence, empirical research has brought a bulk of inconsistent results. The aim of the present paper is to validate which theories are correct on a purely empirical basis. To accomplish this, Bayesian model averaging was employed to 71 potential determinants of international trade for a sample of EU countries over the 1995-2015 period. The results show that the gravity model takes the lead in the explanation of trade flows. Membership in the EU has also a profound impact on trade, as each year of membership in the EU is associated with a growth rate of bilateral trade between 0.5 and 1.5. Finally, the analysis provides support to the predictions under Heckscher-Ohlin model of trade.

Empirical Analysis of Factors Affecting the Bilateral Trade between Mongolia and China

“…In addition, the gravity model is the combination of numerous research efforts and it is significant for both historically and analytically, while it is a valuable approach in order to analyze international trade. In order to analyze the bilateral trade for two or more two countries, numerous studies have used the gravity model alone or with combination of other models, such as Bayesian model averaging [12,13], Heckscher-OhlinVanek model [14], extreme bound analysis [15,16], and robustness tests [17], etc. In addition, the gravity model has been applied to investigate the effects of bilateral trade for numerous countries [18,19] using various variables including population, culture [17], GDP, geographical distance, currencies [20,21], population [12], transportation cost and trading blocs [22], institutional framework [23], fixed exchange rate [24], and adjacent borders [25].…”

Optimizing Intermodal Transport and Hub Location Problem for ECOWAS in the Context of Improving Intra-African Trade

“…return demand, GDP is the gross domestic product of the city calculated in equation ( 1), Pop refers to the population of the O.D. cities, |GDP i − GDP j | is the absolute size of the gap in wealth between the two cities adopted by researchers such as Adler et al [11] and Beck [42]. e distance refers to the distance between the two nodes; the CPI refers to the corruption index.…”

Changes in perception of coffee in EU: Luxury good becoming inferior good

“…Least squares method based on multiple regression is suitable for reversal analysis and dynamical processes (Petráš a Bednářová, 2010;Chlebisz and Mierzejewski, 2020). The successful use of multiple regression allowed defining core factors of demand and supply in different markets (Beck, 2020;Roshchyk et al, 2022), including analysis and forecast in international trade (Nikensari et al, 2021). In macroeconomics, it can be effectively used to analyse the relationship of the response of market interest rates to discount rate changes of central banks (Bai, 1997).…”