WPS4249

# _(b) Growth and Inequality Results_

The results of estimating the growth equation (7) are reported in table 1. Each column reports the results that are obtained when the GMM estimator described above is implemented using a different instrument set. The estimation in column (1) is based on internal instruments only. Columns (2) to (7) use in addition to the internal instruments for the control variables (female and male education and the cost of investment) one exogenous variable (either Distance of Migration) that can enter in the instrument set in levels, growth rates, or both. In all cases the validity of the chosen instrumental variables is confirmed by the _Sargan_ and second order serial correlation tests, which do not reveal any serious misspecification problem.<sup>15</sup>

# TABLE 1 HERE

Inspection of this table indicates that remittances tend to have a positive and statistically significant effect on growth regardless of the instrument set used. The estimated slopes range between .005 and .013, implying that doubling the share of remittances in GDP would on average increase growth by between .5 and 1.3 percentage points. The finding that higher remittances would lead to higher growth holds both for the typical country of the world and for the average Latin American and Caribbean country. Indeed, the interaction term between remittances and the Latin America dummy is not statistically different from zero, implying that the impact of remittances on growth is the same in Latin America and the rest of the world..

Regarding the coefficients of the other control variables, as expected the proxy for the cost of capital carries a negative coefficient although it is not always significantly different from zero. In turn, the education variables carry coefficients of opposite signs, in line with the findings of other studies such as Perotti (1996), Forbes (2000) and Knowles (2005).<sup>16</sup> The only somewhat disappointing result is the positive sign that lagged income carries which would be at odds with (conditional) convergence arguments.<sup>17</sup> In sum, the results that emerge from table 1 would suggest that remittances are good for growth. We next address whether remittances are also good for income inequality. Table 2 reports the results of estimating model (8) and we start by noting that, as in the growth equation case, the specification tests do not indicate any particular misspecification problem. However, unlike in the previous case, the results are now more mixed. For example, when we use the Distance-level, Distance-growth and Migration-growth instruments we do find that, at the global level, remittances tend to be associated with higher levels of inequality but do not find a significant impact for Latin America. With the rest of instruments we still find a positive impact on the Gini coefficient at the global level, but now the Latin American specific impact is

> changes in the gini variable for that same period. The problem is subsequently compounded when we cross these two variables with the rest of the database.

> 15 The results of the estimation remain virtually unchanged when we include among the regressors a time effect to account for the effect of common events to all countries in the sample.

> 16 See e.g., Table 4 in Perotti (1996), Table 4 in Forbes (2000) and Tables 1 and 3 in Knowles (2005). Perotti (1996) explains this noting that “lower initial female attainment, indicates more backwardness and therefore faster subsequent growth as the economy converges toward its steady state” (Perotti, 1996, p.159)..

> 17  Note, however, that using a similar specification Knowles (2005) has also failed to find evidence of cross-country conditional convergence.

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