ratio.<sup>18</sup><sup>_,_19</sup> The table is sorted by the inventories to sales ratio, so sectors with low liquidity needs are presented at the top of the table.

A comparison of the top and bottom halves of the table shows that, as previously mentioned, sectors with low liquidity needs are mainly non-durable goods industries, while sectors with high liquidity needs are mainly durable goods industries. In fact, 27 out of 36 non-durable industries are among the 35 sectors with lowest liquidity needs, while 27 out of 34 durable industries are among the 35 sectors with highest liquidity needs. This distribution is consistent with the idea that industries with longer and more expensive productive processes have higher liquidity needs, as the durable goods sectors produce more elaborate goods that are more likely to require expensive inputs and longer processes. The only exceptions to the rule is the presence of some nondurable industries at the very bottom of the table among those sectors with the highest liquidity needs. Most of these cases correspond to sector 3200, which includes Textiles, Wearing Apparel, and Leather industries. A possible explanation for this finding is that if these sectors have a very seasonal demand, measuring the level of inventories in December may overestimate the average liquidity needs of the sectors. However, these sectors remain at the bottom of the table when the average level of inventory over assets during a year is measured using quarterly data. Nevertheless, the results are not affected by the exclusion of these sectors.

Another sector that is somewhat problematic is sector 3530, which corresponds to petroleum refineries. This sector appears as one of the industries with lowest liquidity needs for various alternative measures. Even though this is not necessarily wrong, this sector is very particular because of its association with the fluctuations in the price of oil; therefore, its presence at one extreme of the distribution of liquidity needs may affect the results. However, as in the case of the Textile sector, the results are not significantly affected by the inclusion or exclusion of this sector.

> 18This measure was built using data from the NBER Productivity Database (Bartelsman et al. (2001)). The reason to use a different source of data to build the measure is that most of the Compustat firms do not report data on wage payments or labor expenditures. So, when Compustat data was used, a large number of sectors was dropped from the estimation for lack of data. Moreover, even in the sectors with enough observations, the number of firms used to build the typical industry measure is significantly smaller than in the case of inventories, which significantly increases the noise of the measure. These problems are avoided by using the NBER data. However, the trade-off is that the argument that large corporate firms are less affected by financial constraints does not apply to the NBER sample, which includes small firms. So, the concern about endogeneity (financial constraints affecting the technology choice of the firms) is more important in this case.

19The basic intuition for the relation between this measure and an industry’s liquidity needs is that a good fraction of the working capital a firm typically needs is devoted to pay wages and salaries. For this reason, sectors where labor costs are relatively more important are likely to be sectors with larger liquidity needs. An additional motivation for the use of this measure comes from Kremer (1993), who argues that it is likely that firms producing more complex products (requiring more tasks) will use more workers and that the average quality of the workers will be higher. Therefore, there is a potential correlation between the length of the production process and the relative importance of labor expenses.

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