interaction.

Overall, the results reported in this section suggest that there are aspects of an industry’s dependence on financial markets that are not completely captured in the measure of liquidity needs. Nevertheless, the coefficient of the liquidity needs interaction is robust to the consideration of these alternative channels.

# **7.2 Financial development or institutions?**

This section explores the possibility that the measure of financial development captures the effect of either the general level of economic development or institutional quality. The reasons to consider this possibility are that (i) a country’s financial development is correlated with the quality of its institutions (see La Porta et al. (1998)), (ii) the measure of a country’s liquidity needs may be related to its “institutional dependence”,<sup>50</sup> and (iii) countries with weak institutions are more likely to experience political crises in which the whole institutional framework is altered. By explicitly considering this channel, the regressions presented in this section attempt to disentangle the effects of financial and institutional development.

Results from this analysis are presented in Table 9. Column (1) reproduces the base regression to facilitate comparison. In column (2), the interaction of initial GDP per capita, which is a proxy for institutional development, and the measure of liquidity needs was added to the main specification. The results show that financial development bears the main responsibility for the differences in sectorial volatility, not economic development.

The specifications reported in columns (3) to (5) add to the base specification the interaction of a different measure of institutional development, the extent of _constraints on the executive_ from the Polity IV dataset,<sup>51</sup><sup>_,_52</sup> with industry characteristics that proxy for a sector’s institutional dependence. Column (3) employs a measure of a sector’s technology use as a proxy for its dependence on institutions, while columns (4)and (5) use measures of a sector’s human and physical capital intensity respectively.<sup>53</sup> In contrast to the specification reported in column (2), the regressions of columns (3) to (5) explicitly consider the possibility of endogeneity and measurement error in the institutional dependence proxy. Following Acemoglu et al. (2001), a coun-

> 50For example, Section 4 discussed the relation between an industry’s liquidity needs, the length of its production process, and product complexity. It is also very likely that industries that produce more complex product will have to deal with more suppliers and the quality of the inputs and outputs will be less observable. Therefore, it is probable that a sector’s level of liquidity needs is going to be correlated with its dependence on the quality of the overall institutional environment, for example on the legal and contracting system.

> 51The average of the measure in the years 1960, 1970, and 1980 was used, instead of the value in 1980, to reduce the noise induced by considering a single year.

> 52This variable has been used by Acemoglu et al. (2002) in a similar manner.

> 53The measures of technology use, human capital dependence and physical capital intensity were described in Section 7.1.

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