Relação entre Desempenho Financeiro e Evidenciação Socioambiental à Luz do Modelo de Epstein e Roy ## Relation Between Financial Performance and Socio-Environmental Disclosure in the Light of the Epstein and Roy Model

Esta pesquisa buscou verificar a relação entre desempenho financeiro e o nível de evidenciação socioambiental de empresas brasileiras, entre 2007 e 2017. Analisou-se 30 empresas utilizando o modelo adaptado de Epstein e Roy (2003), que verifica as evidenciações socioambientais nas dimensões: ambiental, saúde e segurança, comunidade e empregados. Para o desempenho financeiro utilizou-se o modelo de Epstein e Roy (2001), que indica o retorno sobre investimento (ROI), o retorno sobre o capital empregado (ROCE) e o valor econômico adicionado (EVA) como indicadores financeiros de longo prazo. Por meio de análise de dados em painel, estimou-se quatro regressões que buscaram confirmar as hipóteses de que o nível de evidenciação sustentável poderia influenciar as variáveis de desempenho financeiro em período posterior; assim como se o desempenho financeiro é fator determinante para os níveis de evidenciação de sustentabilidade nos períodos seguintes. Verificou-se que o EVA não apresentou relação significativa com o nível de divulgação, não exercendo influência sobre a evidenciação da empresa. Já as variáveis ROI e ROCE apresentaram relação com o nível de divulgação socioambiental, demonstrando que quanto mais se evidencia informações sustentáveis, maiores serão as possibilidades de retorno sobre o capital empregado e sobre o capital investido. Além disso, frente ao aumento da variável ROI, as empresas demonstraram maior determinação em divulgar informações socioambientais. Desse modo, constatou-se efetividade da perspectiva de Epstein e Roy, ao observar que demonstrar sustentabilidade impulsiona maiores retornos sobre o capital investido e empregado, assim como o capital investido tende a otimizar os níveis de divulgação sustentável.

Social Networks and Migration

The frictions that restrict migration are among the largest sources of inefficiency in the global economy. The first step in designing policies to address these frictions is to understand the fundamental forces that drive migration. However, the Roy model—the workhorse model of migration in economics—does a poor job of explaining many important features of this phenomenon. This limitation can be rectified by adding migrant networks to the Roy model. A rich qualitative literature in the social sciences has documented the role played by social networks in supporting migrants in their new locations. Economists have advanced this literature by identifying and quantifying the contribution of these networks to migration. Although much progress has been made over the past two decades, important gaps in the literature remain: Migrant assimilation has received little theoretical or empirical attention, and a richer characterization of the social interactions that support these networks is needed to tie research on migration to the economic literature on networks.

The price of polarization: Estimating task prices under routine‐biased technical change

This paper proposes a new approach to estimate task prices per efficiency unit of skill in the Roy model. I show how the sorting of workers into tasks and their associated wage growth can be used to identify changes in task prices under relatively weak assumptions. The estimation exploits the fact that the returns to observable talents will change differentially over time depending on the changes in prices of those tasks that they predict workers to sort into. In the generalized Roy model, also the average non‐pecuniary amenities in each task are identified. I apply this approach to the literature on routine‐biased technical change, a key prediction of which is that task prices should polarize. Empirical results for male workers in U.S. data indicate that abstract and manual tasks' relative prices indeed increased during the 1990s and 2000s.

Estimation of a Roy/Search/Compensating Differential Model of the Labor Market

In this paper, we develop a model that captures key components of the Roy model, a search model, compensating differentials, and human capital accumulation on‐the‐job. We establish which components of the model can be non‐parametrically identified and which ones cannot. We estimate the model and use it to assess the relative contribution of the different factors for overall wage inequality. We find that variation in premarket skills (the key feature of the Roy model) is the most important component to account for the majority of wage variation. We also demonstrate that there is substantial interaction between the other components, most notably, that the importance of the job match obtained by search frictions varies from around 4% to around 29%, depending on how we account for other components. Inequality due to preferences for non‐pecuniary aspects of the job (which leads to compensating differentials) and search are both very important for explaining other features of the data. Search is important for turnover, but so are preferences for non‐pecuniary aspects of jobs as one‐third of all choices between two jobs would have resulted in a different outcome if the worker only cared about wages.

Roy-model bounds on the wage effects of the Great Migration

Summary This paper combines a Roy model of migration and counterfactual wages with racial differences in migration rates during the Great Migration to recover lower bounds on black–white differences in the wage impacts of northward migration. Identification is predicated on the idea that, when migration is more selective for whites, regional wage differentials for whites will be more contaminated with selection bias. In this case, the black–white difference in North–South wage differentials bounds the racial difference in wage impacts from below. Furthermore, as long as the impact of migration on whites’ wages is nonnegative, a lower bound on the black–white difference in wage impacts is also a lower bound on the impact itself for blacks. Applying the identification result, I find that northward migration increased blacks’ wages by at least 36% more than whites’, and hence by at least 36%, on average between 1940 and 1970.

The Allocation of Talent and U.S. Economic Growth

In 1960, 94 percent of doctors and lawyers were white men. By 2010, the fraction was just 62 percent. Similar changes in other highly‐skilled occupations have occurred throughout the U.S. economy during the last 50 years. Given that the innate talent for these professions is unlikely to have changed differently across groups, the change in the occupational distribution since 1960 suggests that a substantial pool of innately talented women and black men in 1960 were not pursuing their comparative advantage. We examine the effect on aggregate productivity of the convergence in the occupational distribution between 1960 and 2010 through the prism of a Roy model. Across our various specifications, between 20% and 40% of growth in aggregate market output per person can be explained by the improved allocation of talent.