Working papers

"Time Aggregation in Health Insurance Deductibles" (with Corina Mommaerts), 2021

Abstract: Health insurance plans increasingly pay for expenses only beyond a large annual deductible. This paper explores the implications of deductibles that reset over shorter timespans. We develop a model of insurance demand between two actuarially equivalent deductible policies, in which one deductible is larger and resets annually and the other deductible is smaller and resets biannually. Our model incorporates borrowing constraints, moral hazard, mid-year contract switching, and delayable care. Calibrations using claims data show that the liquidity benefits of resetting deductibles can generate welfare gains of 6-10% of premium costs, particularly for individuals with borrowing constraints.


"The Peer Effect on Future Wages in the Workplace" (with Salvatore Lattanzio), 2020 Preliminary - new version coming soon

Abstract: We study a critical driver of wage growth: coworkers. Using linked employer-employee data for Italy, we explore coworkers' effect on wage growth in two directions. First, using a novel estimation method and accounting for the endogenous sorting of workers into peer groups and firms, we estimate the impact of the average coworker's quality on future wages. We find that a 10 percent rise in coworker's quality increases one's wage in the next year by 1.8 percent. The effect decreases gradually over time and becomes about 0.7 percent after five years. Second, we delve deeper into the channels that identify the peer effect and, using an event-study specification around mobility episodes, we study how the entry and leave of high-quality and low-quality workers affect wages of movers and coworkers. We find that hiring a high-quality worker is an important driver of wage growth, as well as separating from a low-quality worker. Movers experience an immediate gain when moving into high-quality peers. Knowledge spillover and peer pressure play an important role in explaining the mechanisms behind our findings.


"Social Pension and Labor Supply in Rural China", 2019 [Field paper]

Abstract: This paper examines the effect of the New Rural Pension Scheme (NRPS) on labor supply among the aged population in rural China. Using a ‘reversed’ difference-in-difference specification, I find the introduction of NRPS has increased the (intensive) labor supply for both pensioners and contributors by more than ten percent. The heterogeneity analysis has suggested that the potential mechanisms are different for the pensioner and the contributor. For pensioners, the program has elevated effective labor productivity, through health improvement and credit constraint alleviation, which lead them to work more. On the other hand, the pension contributor, especially those who are hand-to-mouth, increases labor supply because the annual contribution is an additional financial burden to them.

Work in progress

"Coworker sorting, learning, and wages over the life cycle"

"Estimation and inference in a panel data model of peer and spillover effects" (with Mikkel Sølvsten)

Civil conflicts and the mismatch of powers in Subsaharan Africa” (with Massimo Morelli and Laura Ogliari)

Publication

"GiniInc: A Stata Package for Measuring Inequality from Incomplete Income and Survival Data", The Stata Journal, 2018, (with Guido Alfani, Chiara Gigliarano, and Marco Bonetti)

Abstract: Often, observed income and survival data are incomplete because of left- or right-censoring or left- or right-truncation. Measuring inequality (for instance, by the Gini index of concentration) from incomplete data like these will produce biased results. We describe the package giniinc, which contains three independent commands to estimate the Gini concentration index under different conditions. First, survgini computes a test statistic for comparing two (survival) distributions based on the nonparametric estimation of the restricted Gini index for right-censored data, using both asymptotic and permutation inference. Second, survbound computes nonparametric bounds for the unrestricted Gini index from censored data. Finally, survlsl implements maximum likelihood estimation for three commonly used parametric models to estimate the unrestricted Gini index, both from censored and truncated data. We briefly discuss the methods, describe the package, and illustrate its use through simulated data and examples from an oncology and a historical income study.

The package is available to download here or by simply typing - ssc install giniinc - in Stata.