measures of investment climate into a real model. In addition, the current model structure does not include features that allow FDI to have certain “special” effects on the domestic economy, such as increasing returns to scale and endogenous mark-ups in a Dixit-Stiglitz framework, product differentiation by firm ownership and location of production, or the use of business services (provided by both domestic firms and foreign multinationals) as essential inputs into the production process (see Lejour and Rojas-Romagosa, 2006, for a review of relevant literature). Instead, this section considers some basic links between preferential trade liberalization and FDI inflows through reduced-form parameter estimates obtained from econometric studies. Although clearly simplistic, the approach is very transparent while still allowing us to evaluate the different channels of transmission of FDI shocks.

In order to implement the FDI scenarios in this section, we make several modifications to the dataset and the dynamic updating equations. To accurately model the increase in foreign capital stock following the potential acceleration in FDI, we need to distinguish capital by ownership type (domestic or foreign) and, for the agricultural sectors, to distinguish capital from land. The latter is important because, as shown in section 4.4, capital intensities in agriculture are much higher than capital intensities in manufacturing and services, which is a result of attributing all land and natural resource income to aggregate capital, as well as potential misclassification of self-employed income. This issue was not particularly relevant for the trade simulations but is very important for the scenarios in this section, since the base year distribution of capital stocks by sector largely determines the allocation of new investment. Unfortunately, data on capital and land value added is not readily available for Honduras, and therefore we rely on the Central America SAM from GTAP to separate the two. For each farm sector in this SAM, capital accounts for 47 percent of the total capital-land value added bundle, and we use this information to split payments to aggregate capital into capital and land payments for bananas, coffee, sugar, livestock, non-traditional and domestic crops. For the remaining sectors, all payments to aggregate capital are assumed to go to “proper” capital.

The next step is to distinguish capital by foreign and domestic ownership. Because data on capital stocks by ownership is not available for Honduras, we must make an assumption about which sectors use foreign capital in the base year and, more importantly, which sectors are likely to receive the additional FDI generated by DR-CAFTA. A simple solution would be to assume that foreign capital exists in every sector and, allowing the rental rate to be the same for both types of capital, use a fraction such as the ratio of capital income remitted abroad to total capital income to split the capital value added into domestic and foreign components. However, this approach is not likely to be very interesting or realistic. Instead, it is not implausible to assume that foreign capital will only flow into those sectors that are likely to experience the largest increases in export volumes following trade reform under DR-CAFTA. In particular, we consider the export changes generated by the _CBL_ scenario in the previous section, since much of the new investment is likely to be attracted by Honduras having improved access to the US market.<sup>41</sup> Therefore, we assume that foreign capital only exists and will be attracted to bananas, coffee, mining, wood, food/beverages/tobacco, and textiles and wearing apparel sectors (we will call these the FDI-target sectors). Assuming that rental rates are the same across all of these (mainly because any other assumption would require additional data that is not available), we can use the ratio of capital income remitted abroad to total capital income (7 percent) to calculate the payments to each capital type. This share, however, is not consistent with the composition of private investment, which is 84 percent domestic and 16

> 41See, for example, Medvedev (2006a), which uses a measure of an extended common market from preferential trade liberalization to quantify net FDI gains from joining PTAs.

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