_Table 5. Dependent variable: Ln hosts pc in Latin America_

||(fir<br>|strolum<br><br>|nis coef<br><br>|ficien s<br> <br>|econdisp<br>|-value)<br>|||||
|---|---|---|---|---|---|---|---|---|---|---|
|_|a<br>~|~~<br>|~~<br>1|~~<br>2|~I|3||4||_5_|
|||entire|sample<br>||||Restricte<br> <br>|dsamp<br>|le<br>||
|Laggeddependentvariable||_p.|0_;<br>257|p.602|||T|1<br>|T|r|l|
|LnGDPpc|1.822|.001|1.703|p.001|1.887|1.013|2.219|p.004|.460|p.002|
|LnCosts|0.410|.282|-0.321|0.407|-0.956|0.004|-0.759|0.028|1.012|.)016|
|LnLinespc|1.227|.043|1.021|0.076|2.255|0.067|2.231|.011|.094|.072|
|LnPC'spc|-1.062|.381|-1.248|0.348|-3.395|.037|-4.836|0.008|6.294|).009|
|InGini||.||_|||-10.149|0.039|13.870|.010|
|Regulation|_|_|||||||1.061<br>|.070<br>|
|Regulation*privatization||=|||||||-1.076|.093|
|Obs.|60||||**3**04||34||34||
|R2|.984|.|988||.988||.992||.994||
|Allspecificationscontrol foradditiv|e yearand c|ountryeff|ects||||||||

The table confirms the rejection of the diffusion model for internet hosts. As before, once country fixed effects are taken into consideration, the lagged dependent variable is not significant.'<sup>7</sup> Interestingly the In computer variable enters with a negative sign. One possible interpretation for this result is that the low internet diffusion is primarily explained by the absence of adequate infrastructures (fixed lines). At given fixed lines, a rise in the number of PCs tends to depress internet diffusion, possibly because of the congestion of the available lines. 18 In column 3 we replicate the same specification as in column 1 on the restricted sample. The results are similar, although the value of the coefficients is somehow magnified. In column 4, we control for the log of the Gini. Inequality seems to matter substantially: a 10% fall in the Gini (approximately one standard deviation increase), leads to a doubling of internet diffusion (n10.149*.10). This is a remarkable effect. The other coefficients remain essentially unchanged and still significant.

17 Some caution must be exerted in the interpretation of the coefficient. The Anderson Hsiao estimator is consistent for N (Number of cross sectional observations) going to infinity. Clearly, when we restrict to Latin America only, we are short of fulfilling this condition. Some caution must be exerted in the interpretation of the coefficients. The Anderson Hsiao estimator is consistent for N (Number of cross sectional observations) going to infinity. Clearly, when we restrict to Latin America only, we are short of fulfilling this condition.

18 As noted by a referee, computers per capita might be endogenous to intemet diffusion, since the more people use the internet, the higher will be the incentive for others to buy a PC, perhaps due to a demonstration or an externality effect. The direction of this bias, however, is likely to lead to an overestimate of the coefficient: on log computers. Similarly, it is worth remarking that costs of access might be endogenous to intemet growth. In this case, an increase in the number of hosts would lower access costs through higher competition. On the other hand, if higher access costs attract more providers, the bias would be in the opposite direction. Finally note that GDP per capita might itself be endogenous to telecommunications infrastructure since the latter can affect economic growth (Roller and Waverman, 2001). In this case, one would reasonably suspect that our estimate of the effect of GDP is upward biased. Unfortunately we do not have credible instruments for these variables.

14