Dix-Carneiro and Kovak Trade Reform and Regional Dynamics decline came substantial heterogeneity in tariff cuts across industries, with some industries such as agriculture and mining facing small tariff changes, and others such as apparel and rubber facing declines of more than 30 percentage points. In this paper, we measure liberalization using longdifferences in tariffs during the period of liberalization, from 1990 to 1995. Specifically, we use changes in the log of one plus the tariff rate, shown in Figure 1. During this time period, tariffs accurately measure the degree of protection faced by Brazilian producers and reflect the full extent of liberalization faced by each industry. We do not rely on the timing of tariff cuts between 1990 and 1995 because this timing was chosen to maintain support for the liberalization plan, cutting tariffs on intermediate inputs earlier and consumer goods later (Kume et al. 2003).

As discussed below, along with regional differences in industry mix, the cross-industry variation in tariff cuts provides the identifying variation in our analysis. Following the argument in Goldberg and Pavcnik (2005), we note that the tariff cuts were nearly perfectly correlated with the pre-liberalization tariff levels (correlation coefficient = -0.90). These initial tariff levels reflected a protective structure initially imposed in 1957 (Kume et al. 2003), decades before liberalization. This feature left little scope for political economy concerns that might otherwise have driven systematic endogeneity of tariff cuts to counterfactual industry performance. To check for any remaining spurious correlation between tariff cuts and other steadily evolving industry factors, we regress pre-liberalization (1980-1991) changes in industry employment and wage premia on the 1990-1995 tariff changes, with detailed results reported in Appendix A.2. We attempted a variety of alternative specifications and emphasize that the results should be interpreted with care, as they include only 20 tradable industry observations. Most specifications exhibit no statistically significant relationship, but heteroskedasticity-weighted specifications place heavy weight on agriculture and find a negative relationship. Agriculture was initially the least protected industry, and it experienced approximately no tariff change. It also had declining wages and employment before liberalization, driving the negative relationship. Consistent with earlier work, when omitting agriculture, tariffcuts are unrelated to pre-liberalization earnings trends (Krishna, Poole and Senses 2011). Given these varying results, we include controls for pre-liberalization outcome trends in all of the analyses presented below to account for any potential spurious correlation. Consistent with the notion that the tariff changes were exogenous in practice, these pre-trend controls have little influence on the vast majority of our results.

# **3 Data**

In this paper, we use two main data sources, the _Rela ̧c ̃ao Annual de Informa ̧c ̃oes Sociais_ (RAIS), and the Decennial Census of Population. RAIS is a matched employer-employee dataset assembled by the Brazilian Ministry of Labor every year since 1976 and provides a high quality census of the Brazilian formal labor market (De Negri, de Castro, de Souza and Arbache 2001, Saboia and 7