decision to treat capital remunerations as exogenous and hence losing some of the macromicro consistency conforms to the limitation of household surveys to capture incomes deriving from capital (see Szekely and Hilgert, 1999).

A structuralist feature introduced in the model is the assumption of labor market segmentation. Some degree of labor segmentation is allowed between agricultural and non-agricultural sectors and, within urban areas, between formal and informal activities. The labor market segmentation assumption gives rise to wage differentials across labor market segments.<sup>12</sup> At the micro level workers are reallocated among agriculture, nonagriculture informal, and formal activities by means of a probit model where the probability of switching sectors is estimated as a function of several personal and household characteristics (see Annex 3 for the complete list of variables used in the model and its results). Workers are allowed to switch between the different labor market segments until the CGE-predicted labor allocation is achieved. For those workers who switch, a labor income is imputed on the bases of worker‘s observable characteristics and the return of them prevailing in the receiving labor market segment.

The top-down approach used here takes into account important sources of household heterogeneity such as the structure of income by labor segment and the composition of consumption by commodity—the various θ‘s in the above equation. In other words, although there are only a handful of variables linking the macro and the micro, these shocks will have a different welfare impact across households. Additionally, allowing for full heterogeneity means that in the new, _simulated_ , distribution, households, as well as individuals, can be identified according to the complete set of socio-economic characteristics recorded in the survey. It is thus easier to identify a specific characteristic – such as region of residence, employment status, gender, education, age, etc. – that may strongly correlate with larger than average losses from the Canal expansion and then use this information in targeting compensatory measures.

# **4. What If Panama Expands Its Canal? Macroeconomic and Distributional Impacts**

This section contrasts a Business-as-Usual (BaU) scenario with a Canal expansion scenario to assess the potential effects of the Canal expansion project on real GDP and its components, the real exchange rate, the labor markets, and the government budget. The dynamic macro-micro simulation framework used here is not a forecasting tool so the emphasis is mainly on the differences between the BaU and the canal expansion scenario. These differences tend to be robust in that they do not change much with variations in the assumptions and dynamic paths of the exogenous variables used in the BaU scenario. In other words, the value added of the modeling exercise does not consist of forecasting the future level of specific variables, but rather to show how those levels are _ceteris paribus_ changed by the expansion and operation of the Canal.

> 12 The Chow tests for equality on the Mincer-equation parameters between agricultural and non-agricultural sectors and formal and informal activities within urban areas were rejected at the 99 percent level of confidence. This is strong evidence supporting labor market segmentation.

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