"The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies" with Andrea Naghi
A new and rapidly growing econometric literature is making advances in the problem of using machine learning (ML) methods for causal inference questions. Yet, the empirical economics literature has not started to fully exploit the strengths of these modern methods. We revisit influential empirical studies with causal machine learning methods and identify several advantages of using these techniques. We show that these advantages and their implications are empirically relevant and that the use of these methods can improve the credibility of causal analysis.
"The Long-Run Effect of Migration on Firms' Trade and Performance: The Case of the Bamboo Network" with Christina Ammon
We empirically assess the long-term effect of migrant networks created because of past migration on current exporting behaviour and performance of firms in the migrants' origin country. We focus on ethnic migrant networks formed because of a mass migration wave of ethnic Cantonese people from the province of Guangdong in Southern China to the United States in the late 19th century. We define network exposure as the interaction of two dimensions, one measuring the likelihood of firms to interact to the Cantonese-American network at the industry level, and the other measuring the cultural similarity to the network in the U.S. Using firm-level data from 2004 for Guangdong, we show that in the long run exposure to the Cantonese ethnic network has positive effects on firms exports, but a negative effect on domestic sales, indicating that connected firms tend to specialize in exporting. Moreover, our results indicate that migrant networks improve firm performance by increasing international trade.
"The Persistent Effect of Gender Division of Labour: African American Women After Slavery"
This paper explores the role of historical gender division of labour in shaping gender norms. To answer this question, I analyze whether differences in the gender division of labour during slavery have a persistent effect on gender equality among African Americans after the end of slavery up to today. I use variation in the production of cotton and tobacco across counties during slavery as a proxy for gender division of labour: tobacco was characterized by a starker gender division of labour compared to cotton. Using data from 1870 to 2010, I show that women living in counties which had a higher production of cotton relative to tobacco during slavery experience lower gender inequality after slavery.
Work in progress
"Female Higher Education in Iran: The Effect of Restrictions to University Admission" with Laura Hering and Julian Emami Namini (first version: spring 2020)
We study the effect of an Iranian education policy that restricts access to higher education for women in about 40 public universities in specific subjects, mainly prestigious fields such as engineering. The policy was implemented in 2012 and lasted for two years. To analyze the effect of the policy, we exploit its differential impact across cohorts and regions. We find that the policy has a negative effect on higher education for women. Additionally, we investigate the effects of the policy on marriage rates and labour market outcomes.
"Long Term Effects of Migration on Attitudes Towards Migrants: A Machine Learning Approach" with Andrea Naghi and Nadja van't Hoff (first version: 2020)