equipment and electronic apparatus, the printing industry, the production of transportation equipment as well as the petrochemical and chemical sectors, exhibit great increases in their use of ICT, while more traditional sectors such as apparel, leather and furniture, show low levels of ICT use which do not vary much across time. In the case of the services sector, mainly transportation and other services related to this subsector, along with information, software and publications and the electronic processing of accommodation and related services, exhibit the highest levels of ICT adoption during the period of analysis. Finally, for commerce, great increases in ICT use are observed for subsectors such as apparels and footwear retail, as well as commerce of health products. The changes for this last sector could in part be related to the increasing adoption of e-commerce.

Analyzing our main outcomes of interest, which are wages and labor by skill level, we find that the average number of white-collar workers increased slightly between 2008 and 2013, from around 24 to 27 employees for the manufacturing sector. Similar figures are observed for the services sector, while the commerce sector exhibits a much lower number of white-collar workers (around 9 employees). This is consistent with the fact that firms in this sector tend to be small, relative to the other two sectors.

Something similar was observed for blue-collar workers in the manufacturing industry, which increased from an average of 123 to 127 workers during this period. Once again, comparable magnitudes are observed for the services sector, while for commerce, the number of blue-collar workers is on average of 24 and this figure does not change much between 2008 and 2013.

As the numbers of white and blue-collar workers increased in the manufacturing sector, clearly there is an overall increase in the average size of the firms considered in the sample. Once again, when we dig further into the composition by NAICS 3-digit code as in Figure 4, we find that there is great heterogeneity as some subsectors exhibit much higher white/blue-collar ratios. For example, for the manufacturing industry, the chemical and petrochemical sectors, along with machinery and equipment have the highest ratios while other sectors such as clothing, leather and wood products have a low proportion of white-collar workers. However, these ratios do not appear to change much over time.

Similar heterogeneity is observed in terms of wages. Though on average the wages of white-collar workers are two times the ones of blue-collar workers regardless of the sector, the magnitude of these gaps varies across NAICS 3-digits codes. As Figure 5 shows, the biggest gaps for manufacturing are observed in electrical apparatus, computer equipment and transportation equipment. On the other hand, sectors such as leather, printing and furniture exhibit the lowest wage gaps. Additionally, between 2008 and 2013, these ratios changed significantly for some sectors. As depicted in the figure, the wage ratio increased for computers and equipment, finished textiles and machinery and equipment.

In the case of the services sector, the highest wage ratios are observed for restaurants and electronic 11