FTA Effects on Agricultural Trade with Matching Approaches

Abstract

While the trade effect of free trade agreements (FTAs) is a global issue, little research has examined the economic effects of trade liberalization on agricultural products with robust empirical methods. In this study, propensity score matching for controlling selection bias is used to examine and analyze the effect of FTAs on the trade of South Korea's agricultural products. To enhance the robustness of the estimated results, differences between the FTA treatment effects in 2010 and 2012 are analyzed. The results reveal that the effect of FTAs on agricultural trade varies slightly, depending on the matching approach used; however, the signs of all estimated average treatment effects on the treated (ATT) values are positive. Analysis of the difference between selection bias controlled through matching and uncontrolled selection bias shows that the value of the average treatment effect (ATE) with uncontrolled bias is greater than the ATT estimate calculated through matching. This implies that controlled versus uncontrolled selection bias can result in different ATE and ATT estimates, and that previous studies on FTA trade effects have overestimated the effect, because selection bias was not fully addressed. JEL C54 F15 Q17

Evaluating the impact of preferential trade agreement on fishery imports: An application of difference‐in‐differences with matching method

“…Also, a nonparametric matching method can be used to effectively control frequent errors arising from nonrandom selections during general linear regressions (Hur & Park, 2012). To gain an in-depth understanding of the causal effect between trade flow and PTAs, recent PTA studies have begun to address the causal effect of policy evaluation (Baier & Bergstrand, 2007;Chen et al, 2018;Egger et al, 2008;Lee & Lim, 2015). The main intent is to use the signing of PTA as a treatment variable to address the causal effect.…”

“…In addition, the signing of PTAs can promote trade flows due to growth in intra-industry trade rather than interindustry trade (Egger et al, 2011). Most previous studies show that the signing of PTAs and accession to international economic and trade organizations can boost trade flows significantly (Baier & Bergstrand, 2009;Chang & Lee, 2011;Egger et al, 2011;Lee & Lim, 2015), but does not significantly affect economic growth (Hur & Park, 2012). To evaluate the causal relationship between the signing of PTAs and trade flows, many previous studies used a matching or a DID method to estimate the policy effectiveness of the signing of PTAs.…”

“…In other words, based on this definition, the MFN scheme is a general measure. In addition, due to the partner country entitled to MFN scheme is adopted as a control group by previous studies in country pair level by gravity model (Baier & Bergstrand, 2009;Lee & Lim, 2015), we adopt the MFN scheme suggested as a common measure as the control group in more detailed product level.…”

“…Therefore, they have used matching methods to investigate the selection of PTA scheme. In other words, they have found that the specification in previous studies may cause biased results due to the endogeneity problem in the evaluation of the effect of PTAs (Baier & Bergstrand, 2007;Hur & Park, 2012; Lee & Lim, 2015).…”

Risk factors in the agriculture sector

“…Firstly, as a business with a typical price and demand fluctuations (Uematsu and Mishra 2011;Sulewski and Kloczko-Gajewska 2014), emerging from the trade liberalization and the changes of the Common Agricultural Policy (Lien et al 2003;Bureau et al 2005;Flaten et al 2005;Ahn et al 2009;Park 2013;Lee and Lim 2015), but also another risks characteristic for this sector as the climate, weather, infections, which have the tendency to rise (Alcamo et al 2007;Kundzewicz and Kozyra 2011;Olesen et al 2011;Kemény et al 2013;Legg and Blandford 2015;Kan et al 2015;Prokopy et al 2015).…”