research

Job Market Paper

• Bridging the Gap: Information, Returns and Choices PDF Updated!
  Abstract: How much of the gap in choices across social groups is driven by differences in returns or the ability to predict these returns? To address this question, we employ a decomposition exercise and a structural model to quantify the roles of information quality and differences in returns in driving this gap. Focusing on the college attendance decisions of White and Hispanic high school students in Texas, we use administrative data to understand the drivers behind their differing choices. Initially, we demonstrate that the average monetary returns from college for Hispanics are almost zero, in contrast to being positive for Whites. We then estimate the extent to which differences in returns and information quality contribute to the gap in choices and find that differences in information quality narrow the choice gap in college attendance, where most of the gap is explained by differences in returns. Finally, we use our model to show that to achieve parity in choice between the two groups, policymakers would need to provide highly accurate additional information, potentially explaining between 19% and 35% of post-college earnings.

Working Papers

• It’s Not Who You Are, It’s What They Know: Wage Gaps and Informational Frictions PDF
  Abstract: Can informational asymmetries among firms account for all observed wage gaps across social groups? We confirm this through a parsimonious common-value auction model in the labor market with unspecified information structures. Firms with identical characteristics encounter workers with unobserved productivity and extend wage offers based on their information about worker productivity and competing offers. Using 2010 American Community Survey data, we show that wage disparities among both Black and White men and women can be explained using a common productivity distribution for all social groups and differences in what firms know, if the mean of this common productivity distribution ranges between $48,000 and $132,800. Our results emphasize the importance of understanding what firms know in shaping wage distributions and explaining wage disparities
• Uncovering Latent Types in Sequential Choice Data Using Text Embedding Algorithm PDF
  Abstract: In economic analyses of agents making a series of discrete choices, deciding what constitutes an alternative is crucial. This paper introduces a technique for categorizing similar alternatives in contexts where forward-looking agents make a series of decisions. The proposed method groups options that are equivalent from the perspective of the agents, using the renowned word2vec algorithm (Mikolov et al., 2013b, Mikolov et al., 2013a) from the Natural Language Processing literature. The paper discusses the link between the word2vec method and the underlying dynamic optimization problem of the agent.
• Linear Regression in a Nonlinear World PDF
  Abstract: The interpretation of coefficients from multivariate linear regression relies on the assumption that the conditional expectation function (CEF) is linear in the variables. However, in many cases the underlying data generating process is nonlinear. This paper examines how to interpret regression coefficients under nonlinearity. We show that if the relationships between the variable of interest and other covariates are linear, then the coefficient on the variable of interest represents a weighted average of the derivatives of the outcome CEF with respect to the variable of interest. Interestingly, if these relationships are nonlinear, the regression coefficient becomes biased relative to this weighted average. We show that this bias is interpretable, analogous to the biases from measurement error and omitted variable bias under the standard linear model.

Work in Progress

• Quantifying Uncertainty over the Lifecycle Slides
  Abstract: We examine the welfare implications of income uncertainty, specifically its differential impact across social groups. Leveraging a new lifecycle metric for uncertainty costs, we compare utility outcomes from both expected and optimal consumption profiles under certainty. To perform this analysis, we employ a new approach that uses a Generative AI model (Normalized Flow) for the estimation and simulation of future consumption and income trajectories. Utilizing comprehensive household survey data from India, our findings reveal small but persistent disparities in uncertainty costs across different castes, under the assumption of homogeneous utility functions. The study suggests that, in the absence of preference heterogeneity, income-to-welfare mapping may be adequately performed without considering uncertainty.
• Can complementarity explain path dependence in innovation? Evidence from the secondary market of patents

  Publications

• On the Interpretation of the Intergenerational Elasticity and the Rank-Rank Coefficients for Cross Country Comparison. Economics letters (2024) PDF Supplementary Material
  Abstract: This paper investigates Intergenerational Elasticity (IGE) and Rank-Rank coefficients, employing Yitzhaki’s theorem (Yitzhaki, 1996) to express them as weighted averages of underlying causal mechanisms driving mobility. We highlight the challenges of interpreting cross-country comparisons using IGE or Rank-Rank coefficients due to the regression weighting scheme. We also show that, while the Rank-Rank coefficient is more interpretable for positional mobility, it lacks insights into the underlying mechanisms driving mobility across countries. The analysis demonstrates potential drawbacks of using linear regression coefficients as summary statistics in the context of intergenerational mobility comparisons.
• Network-Mediated Knowledge Spillovers in ICT/Information Security. Review of Network Economics (2021) with Neil Gandal and Lee Branstetter Link
• The High-Tech Sector, Chapter 17, The Israeli Economy, 1995–2017: Light and Shadow in a Market Economy. with Neil Gandal and Stefania Gandal Link