Visa trial of international trade: evidence from support vector machines and neural networks

Abstract

International trade depends on networking, interaction and in-person meetings which stimulate cross-border travels. The countries are seeking policies to encourage inbound mobility to support bilateral trade, tourism, and foreign direct investments. Some nations have been implementing liberal visa regimes as an important part of facilitating policies in view of security concerns. Turkey has been among the nations introducing liberal visa policies to support trade in the last decade and recorded significant increases in the volumes of exports. In this paper, we employed machine learning methodologies, Support vector machines (SVM) and Neural networks (NN), to investigate the facilitating impact of liberal visa policies on bilateral trade, using the export data from Turkey for the period of 2000–2014. The research disentangled the variables that have the strongest impact on trade utilizing SVM and NN models and exhibited that visa policies have significant impacts on the bilateral trade. More relaxed visa policies are recommended for the countries in the pursuit of increasing exports.

Keywords:

• trade modeling
• visa policy
• support vector machine
• neural network

Disclosure statement

No potential conflict of interest was reported by the author(s).

ORCID

Abdullah S. Karaman http://orcid.org/0000-0001-5768-7382

Cemil Kuzey http://orcid.org/0000-0003-0141-1744

Notes

1 CEPII is an international economic research center focusing on the global economy and its progression, and produces studies, research, databases and/or analyses.