the 1% level across all specifications, which is consistent with the hypothesis that financial development _reduces_ the relative volatility of sectors with high liquidity needs. Column (A1) reports the coefficient obtained when no additional controls are included in the regression. That is, when the only country-industry variable is the interaction between liquidity needs and financial development. Columns (A2) to (A4) include additional controls. Column (A2) includes the initial share of a sector in a country’s manufacturing value added; column (A3) adds the average growth rate of the industry in each country; column (A4) introduces the interaction between a measure of an industry’s intrinsic volatility and a country’s aggregate volatility. The first two controls are included because a sector that is initially large or is growing fast may be relatively less volatile.<sup>28</sup> The interaction between an industry’s volatility and a country’s aggregate volatility is included to control for the possibility that some industries may be more volatile than the average in every country.<sup>29</sup><sup>_,_30</sup> Columns (A5) to (A8) report the 2SLS parameters of the same regressions reported in columns (A1) to (A4). Finally, the specification in column (A9) is identical to column (A5), but in this case an alternative measure of liquidity needs is used as an instrument for the base measure.

The negative coefficient of the initial share of a sector in total manufacturing output shows that, as expected, larger or more mature sectors are relatively less volatile (see columns (A2) and (A6)). Columns (A3) and (A7) show that the rate of growth of an industry is not significantly related to its relative volatility. Finally, the evidence suggests that relatively volatile industries are not relatively more volatile in unstable countries (columns (A4) and (A8)).<sup>31</sup> Overall, it is clear that the inclusion of these additional variables in the specification (corresponding to the _Xij_ variables in equation (2)) does not affect the sign, magnitude, or significance of the coefficient of the interaction of financial development and liquidity needs.<sup>32</sup> A comparison of the first and second half of the table shows that the 2SLS coefficient of the interaction between liquidity needs and financial development is always

> 28For the relation between growth and volatility see Ramey and Ramey (1995).

29This is especially relevant because of the relation between the measure of liquidity needs and the durability of the goods. As it has been documented, durable goods industries tend to be relatively more volatile than non-durable goods industries.

> 30Under the assumption of technological similarities across countries (see Section 4), the intrinsic volatility of an industry was measured by the standard deviation of real value added growth of that industry in the U.S.. The aggregate volatility of a country was measured as the volatility of the aggregate manufacturing sector.

> 31This result also holds if the _β_ of each industry in the U.S. (covariance of that industry with aggregate manufacturing volatility) is interacted with each country’s volatility instead of using the interaction of each industry’s volatility in the US with each country’s aggregate volatility.

> 32As the results are based on a subset of country-industries from UNIDO and that there are missing years within this subset, there is a legitimate concern about the presence of sample selection bias on the coefficients. The effect of this bias on the coefficients is analyzed in appendix E. The results indicate that the explicit consideration of sample selection bias either does not significantly the or biased them toward zero.

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