delays in shipments as well as breakage and theft totaling 8 to 12 percent of the sales value of exported goods (World Bank, 2006b). For South American countries, the World Bank calculates that a 10-percent reduction in transport costs would increase trade by 3.6 percent in Uruguay, 5.5 percent in Brazil, and 3.3 percent in Argentina (World Bank, 2009).

Product and trade-route specific diagnoses, such as logistics supply chain analyses, can be a useful source of disaggregated information on the detailed costs and time requirements involved in cross-border trade. They reveal the relative share of each logistics cost component in the price of the delivered goods and shed light on particular barriers to trade along specific routes. That said, a micro-level supply-chain approach to trade flow does not seek to capture overall regional trading trends or the impact on trade flows of key socioeconomic and spatial variables, including the importance of the size of the trading economies, their proximity to one other and the adjacency or “neighboring” benefits of nearby economies. This geographical information and the related spatial patterns can play a crucial role in the dynamics of regional integration. When coupled with practical tools such as logistics supply chain analyses, sectoral diagnoses and freight flow modeling, spatially-based analyses and geographical representations can serve as complementary tools for informing decisions on public investments, trade and transport regulations and the optimization or prioritization of government resources.

To complement recent supply chain and studies and productivity competitiveness and sectoral diagnoses now underway for Central America, the current paper takes a spatial approach to evaluating the potential impact of physical integration in Central America. It benchmarks the current intra-regional trade performance of the region against the patterns observed in the European Union—selected as a case study of an integrated region with low border frictions and low time-to-distance ratios for transport. This provides some insight into the potential trade volumes that would take place in a "spatially integrated" Central America. Specifically, the paper attempts to measure the extent to which various physical variables act as obstacles to—or drivers of—intra-regional trade. Conversely, it also estimates the maximum potential gains—in terms of increased trade volumes—that could be achieved from raising the level of Central America’s physical trading.

# **_The Use of Gravity Models to Identify Barriers to Trade_**

For estimating the relative impact of such trade-related variables as the distance between production and consumption centers,<sup>6</sup> the adjacency among countries, and the relative incomes of the trading economies, the paper applies a Gravity Model of Trade (GMT). This explains the behavior of the various variables at the regional level and highlights their linkages, correlations and dynamics over time, simultaneously making it feasible to generate and extract spatial information to explain socioeconomic phenomena. The GMT is a “spatially-conscious” econometric model that incorporates a geographical perspective to explain trade flows as the function of two criteria: mass (e.g., GDP, capital stocks, or population) and distance between gravity centers. The GMT, as other models of this type, attempts to explain trade between two countries by their bilateral connectivity, adjacency, and respective market size, assuming that

> 6 Distance measured either in Euclidian terms or adjusted based on such factors as time between points, road quality, trucking costs, or customs efficiency.

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