Rodimiro Rodrigo

We examine the impact of industrial robots on wage inequality both between and within occupations. We show that, in a standard wage-posting model, high-productivity firms are more likely to adopt robots, which reduces within-occupation wage inequality by compressing the top of the wage distribution. However, robot adoption may increase between-occupation wage inequality. Analyzing two decades of U.S. data, we find that robots reduce within-occupation inequality by 4% and increase between-occupation inequality by 2-6.5% of their respective standard deviation. These findings are robust to various confounding factors, inequality measures, and instrumental variables, highlighting the complex interplay between robot adoption and occupational wage inequality in frictional labor markets.

Conferences and Seminars: Boston U (TPRI), LACEA-LAMES, The World Bank*, U Wisconsin-Madison*. 

Previous studies for developed countries show negative short-run impacts of industrial robots on earnings and employment. This paper examines whether robotization by a major trade partner can hurt workers in developing countries. We combine Colombian Social Security administrative records from 2008 to 2016 with U.S. robot adoption data by industry. Colombian workers who in 2008 were working in industries heavily exposed to U.S. robots, afterward experienced lower cumulative earnings and spent more time working in the same industry. Workers switching industries undergo the largest earnings losses. We show these results are not driven by other capital or digital technologies adopted in Colombia. Earning losses are stronger as workers age, for higher-earnings workers, and for those working in larger firms. Notably, higher exposure to U.S. robots decreases Colombian exports to the U.S., particularly in the primary sector.

Conferences and Seminars: LACEA-LAMES, EEA-ESEM, WALES, Georgetown-McDonough (Strategy), George Mason, IADB. Previous version under the title "US robots and their impacts in the tropics: Evidence from Colombian labor markets" NBER-WP28034.

Major technological changes have come with an adjustment period of stagnant productivity before the economy operates at its full potential.  The mechanism of this adoption process is still not well understood. I document that productivity increases with a five-year lag after the adoption of industrial robots in Brazil. Combining Brazil employer-employee matched data with a novel measure of robot adoption, I document that the short-term effect of robots is not on productivity but on the within-firm organization of labor across occupations. Only when the reorganization of labor stabilizes -about five years later- productivity gains kick in. I estimate a general equilibrium model with heterogeneous firms, endogenous robot adoption, and organizational capital accumulation. The model shows that the organizational capital mechanism explains 20% of the aggregate skills demand change observed in Brazil over the last decade.

Conferences and Seminars: AoM, EEA-ESEM, IADB, The World Bank, Harvard Kennedy School, U Toronto, NBER SI, NASMES, SED, GWUSB, U Delaware, U Los Andes, U Queensland, ITAM Business, Banco de México, PUC Chile, Harvard, HBS, Boston U (TPRI), LACEA–LAMES, LACEA–RIDGE, World Bank, Georgetown (Macro, Trade), GU-McDonough (Strategy), AOM (TIM–Doctoral Consortium), Wharton Innovation Doctoral Symposium.

We use a database generated by a policy intervention that incentivized learning as measured by standardized exams to investigate empirically the relationship between cheating by students and cash incentives to students and teachers. We adapt methods from the education measurement literature to calculate the extent of cheating and show that cheating is more prevalent under treatments that provide monetary incentives to students (versus no incentives or incentives only to teachers). We provide evidence suggesting that students may have learned to cheat, with the number of cheating students per classroom increasing over time under treatments that provide monetary incentives to students.

This paper evaluates the impact of an intervention targeted at marginalized low-performance students in public secondary schools in Mexico City, consisting in free additional math courses, taught by undergraduate students from the most prestigious Mexican universities. We exploit the information of all students’ (treated and not treated) transcripts enrolled in participating and non-participating schools. Before the implementation of the program, participating students lagged behind non-participating ones by more than a half base point in their GPA (over 10). Using a difference-in-differences approach, we find that students participating in the program observed a higher increase in their school grades, and that by the end of the school year, when the free extra courses had been offered for 10 weeks, participating students’ grades were not significantly lower than non-participating students’ grades. These results provide evidence that short and low-cost interventions can have important effects on student achievement.