From the standard errors one can construct confidence intervals. Indeed, they reflect the curvature of the likelihood function at the point estimates and hence they also reveal the potential for errors<sup>in</sup> the convergence to a global maximum. The magnitude of the standard errors, however, tell us little about how sensitive the dynamics of the model are to the parameters. In Section 8 below we address this issue by performing a sensitivity analysis. It is also interesting that both estimates of m fall within the permitted boundaries. Related, the SES data estimate of the parameter m implies a distribution of talent more skewed towards low cost agents.

# 6 (Calibration

We still need to pin down the cost of living v and the "dynamic" parameters, namely, the savings rate _w_ and the subsistence income growth rate **Ygr.** One way to determine these parameters is calibration: look for the best _v, w_ and 'yr combination according to some metric relating the dynamic data to be matched with the simulated data.

In this section we first discuss the Thai macro dynamic data that will be used to calibrate the model and then discuss some issues concerning the calibration itself.

## 6.1 Data

The Thai economy from 1976-1996 displayed nontrivial growth with increasing (and then decreasing) inequality. LEB and related models are put forward in the literature as candidate qualitative explanations for this growth experience. Here we naturally go one step further and ask whether the LEB model at some parameter values can match quantitatively the actual Thai economy, focusing in particular on the time series of growth, labor shares, savings rates, fraction of entrepreneurs, and the Gini measure of income inequality. The actual Thai data are summarized in Table 2 in the Appendix.

The data show an initially high net growth rate of roughly 8 percent in the first three years. This then fell to a more modest 4 percent up through 1986. The period 1986-1994 displayed a relatively high and sustained average growth of 8.43 percent, and within that, from 1987-1989 the net growth rate was 8.83 percent. During this same period, the Thai economy GDP growth rate was the highest in the world at 10.3 percent. These high growth periods have attracted much attention. Labor share is relatively stable at 0.40 and rising after 1990, to 0.45 by 1995. A trend from the 1990-1995 data was used to extrapolate labor share for 1996. Savings as a percent of national income were roughly 22 percent from the initial period to 1985. Savings then increased after 1986 to 33 percent, in the higher growth period. These numbers, though typical of Asia, are relatively high. The fraction of entrepreneurs is remarkably steady, though slightly increasing, from 14 percent to 18 percent. The Gini coefficient stood at 0.42 in the 1976 SES survey and increased more or less steadily to 0.53 in 1992. Inequality decreased slightly in both the 1994 and 1996 rounds, to 0.50. This downward trend mirrors the rise in the labor share during the same period, and both may be explained by the increase in the wage rate. This level of inequality is relatively high, especially for Asia, and rivals many countries in Latin America (though dominated as usual by Brazil). Other measures of inequality, e.g., Lorenz, display similar orders of magnitude within Thailand over time and relative to other countries<sup>26</sup> .

> 26 The mterested reader will find a more detailed explanation in Jeong (1999).

14