# _5.1. A Gravity Model to Assess Trade Performance_

Countries’ economic characteristics and geographical distance to trading partners can be used to predict the potential bilateral trade flows and compare the predicted volume to actual trade and estimate the untapped exports potential. We use a gravity model<sup>4</sup> to analyze the determinants of bilateral trade flows, essentially the countries’ income level and the geographical distance between them, in addition to other relevant factors such as common borders, common languages, common legal systems, common currencies and common colonial legacies. The model is also used to test the effectiveness of free trade agreements. The basic model for trade between two countries (i and j) takes the following form: where F stands for the trade flow, G is the constant, D stands for the distance and M stands for the economic dimensions of the countries _i_ and _j_ that are being measured. A better understanding of the gravity equation is achieved by using the logarithmic values of all variables. We use the UN Comtrade database for 175 countries including Egypt, with 99 sectors (two‐digit HS commodities) for the period 1995 – 2016.<sup>5</sup> Our equation takes the following form: lnX���� �β� �β�lnGDP/cap�� �β�lnGDP/cap�� �β� lnDist�� �β�Contig�� �β�Comleg�� � β�Col�� �β�ComLang��� β�Landlocked� β�GAFTA��� �β��Agadir���� β��EgyptEU��� � β��COMESA��� �σt�σj�ε���� where _Xijkt_ is the bilateral trade flow between Egypt (the exporter) and country _j_ (the importer) in year _t_ for sector _k_ ; lnGDP/cap�� and lnGDP/cap�� are country _i_ and j’s real gross domestic product per capita in year _t_ ; _lnDistij_ is the bilateral distance between the two countries, measured as the great circle distance between Cairo and the capital city of its trading partner, in miles. The distance variable is meant to represent typical trade barriers such as transport costs and time and cultural unfamiliarity. _Contigij, Colij, ComLegij, ComLangij and Landlocked_ are dummy variables that take the value of 1 if the two countries share common borders, had previous colonial links, have common legal origin, have common language, or the destination is landlocked, respectively, as these characteristics are expected to boost trade. We also introduce three variables of trade policy measuring the most important trade agreements for Egypt. Three dummy variables take the value of 1 to capture the association agreement between Egypt and EU countries (changing over time as each EU member joined in different years); _Agadir_ a dummy variable that takes the value of 1 for Tunisia, Jordan and Morocco starting 2005, _GAFTA_ a dummy variable that takes the value of 1 for GAFTA countries starting 1998 and _COMESA_ a dummy variable that takes the value of 1 for COMESA countries.

The predicted level of trade is estimated from the gravity model as the difference between the observed level and the residual of the regression (2) as follows: The observed level of trade is then compared to the estimated level of trade as predicted by the gravity model:

> 4 Gravity models (Tinbergen, 1962 and Anderson, 1979) witnessed significant theoretical and empirical improvements (Mac Callum, 1995; Feenstra et al., 2001; Feenstra, 2002; Evenett and Keller, 2002; Anderson and van Wincoop, 2003; Santos Silva and Tenreyro, 2006), enforcing its theoretical base and narrowing the gap between theoretical and empirical findings.

> 5 The lists of countries and sectors included in the data set are included in Table A.4 and A.5 in Appendix 2.

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