Working Papers 2023
Working paper 1-2023
Capability Building in Sluggish Organizations
Kfir Eliaz, Ran Spiegler
In order to thrive, organizations need to build and maintain an ability to meet unexpected external challenges. Yet, many organi-zations are sluggish: their capabilities can only undergo incremental changes over time. What are the stochastic processes governing .routinely occurring.challenges that best prepare a sluggish organization for unexpected challenges? We address this question with a stylized principal-agent model. The .agent. represents a sluggish organization that can only change its capability by one unit at a time, and the .principal. represents the organization.s head or its competitive environment. The principal commits ex-ante to a Markov process over challenge levels. We characterize the process that maximizes long-run capability, for both myopic and arbitrarily patient agents. We show how stochastic, time-varying challenges dramatically improve a sluggish organization’s preparedness for sudden challenges.
Published in Management Science, Volume 69, Issue 3, March 2023 Pages 1323-1934, iii-iv
Working paper 2-2023
Challenging Encounters and Within-Physician Practice Variability
Gabriel Chodick, Yoav Goldstein, Ity Shurtz, Dan Zeltzer
We examine how physician decisions are impacted by di_cult cases|encounters with newly diagnosed cancer patients. Using detailed administrative data, we compare primary care physicians' decisions in visits that occurred before and after di_cult cases and matched comparison cases by the same physicians on other dates. Immediately following a di_cult case, physicians increase referrals for common tests, including diagnostic tests unrelated to cancer. The e_ect lasts only for about an hour and is not driven by patient selection or schedule disruption. The results highlight difficult encounters as a source of variability in physician practice.
Published in The Review of Economics and Statistics 1–27, March 15 2023
Working paper 3-2023
A Note on the Equilibrium Effects of Predictive Credit-Risk Models
I present a simple model of a credit market in which lenders use predictive models to evaluate borrowers’ credit risk. Each firm trades off its ability to predict borrowers’ risk according to their observed characteristics against their simplicity. Firms are heterogeneous in the weights they attach to each conisderation. Crucially, firms evaluate risk models’ predictive success against the aggregate distribution of active borrowers. I show that in this model, lenders that attach low importance to explainability exert a positive externality on other lenders, because their complex predictive models make the aggregate distribution of active borrowers less adversley selective.
Working paper 4-2023
Behavioral Causal Inference
When inferring the causal effect of one variable on another from correlational data, a common practice by professional researchers as well as lay decision makers is to control for some set of exogenous confounding variables. Choosing an inappropriate set of control variables can lead to erroneous causal inferences. This paper presents a model of lay decision makers who use long-run observational data to learn the causal effect of their actions on a payoff-relevant outcome. Different types of decision makers use different sets of control variables. I obtain upper bounds on the equilibrium welfare loss due to wrong causal inferences, for various families of data-generating processes. The bounds depend on the structure of the type space. When types are “ordered” in a certain sense, the equilibrium condition greatly reduces the cost of wrong causal inference due to poor controls.
Working paper 5-2023
Machine Learning for Treatment Effect Heterogeneity:
Recovering Partial Effects
Elad Guttman, Dor Leventer, Itay Saporta-Eksten, Analia Schlosser
Recent developments in the causal inference literature introduced Machine Learning (ML) algorithms to the analysis of heterogeneous treatment effects. Relying on these methods, various studies examine how treatment effects vary as a function of covariates. We highlight the potential interpretation challenges when one analyzes treatment effect heterogeneity without taking into account correlated covariates, and propose to examine the partial effect of a covariate on the estimated conditional average treatment effect. Our approach introduces the application of Partial Dependence Plots (PDP) and Accumulated Local Effects (ALE) used in the prediction literature, to the analysis of heterogeneous treatment effects.
Working paper 6-2023
“Soft” Affirmative Action and Minority Recruitment
Daniel Fershtman, Alessandro Pavan
We study search, evaluation, and selection of candidates of unknown quality for a position. We examine the effects of “soft" affirmative action policies increasing the relative percentage of minority candidates in the candidate pool. We show that, while meant to encourage minority hiring, such policies may backfire if the evaluation of minority candidates is noisier than that of non-minorities. This may occur even if minorities are at least as qualified and as valuable as non-minorities. The results provide a possible explanation for why certain soft affirmative action policies have proved counterproductive, even in the absence of (implicit) bias.
Working paper 7-2023
Search, Dating, and Segregation in Marriage
Yair Antler, Daniel Bird, Daniel Fershtman
We study statistical discrimination in a marriage market where agents, characterized by attractiveness (e.g., wealth, education) and background (e.g., race, ethnicity), engage in time-consuming search. Upon meeting, couples date to learn about their match’s quality. Following Phelps (1972), different backgrounds impede such learning. We show that even absent any bias, equilibrium features segregation. Moreover, welfare improvements enhance segregation. In particular, radical improvements in search technologies induce complete segregation and a “dating apocalypse” where agents replace partners frequently. We show that, in line with empirical findings, segregation is decreasing in couples’ attractiveness, and provide conditions for (probabilistic) positive sorting by attractiveness.
Working paper 8-2023
What to Study and When: A Dynamic Roy Model of Specialization
Titan Alon, Daniel Fershtman
This paper generalizes the canonical model of human capital accumulation through schooling to endogenize the process of academic specialization. It provides the solution to a class of dynamic investment problems with switching and stopping under sequential uncertainty. Under mild assumptions, we show that the model’s optimal policy has a particularly simple form that can be reduced to the comparison of independent indices. The optimal policy implies that schooling should begin with a period of general education, common to all students, followed by a period of gradual academic specialization before graduation. At the microeconomic level, it is consistent with the dynamics of student course taking observed in the data and the outcomes of educational interventions studied in the literature. At the macroeconomic level, its predictions are consistent with models of how education should adapt to changes in the speed and scope of technological change in labor markets.
Working paper 9-2023
Unintended Consequences: Israel’s Pension Reform and the Dollar-Shekel Exchange Rate
Moshe Hazan, David Weiss, Yaniv Yedid Levi
We argue that the pension reform in Israel, implemented during the 2000s, has had unintended consequences for the exchange rate between the US Dollar and the Israeli Shekel. This reform resulted in a significant concentration of wealth managed by a small number of institutional investors (IIs). As the local capital market became relatively small compared to their assets under management, these investors increased their holdings of foreign assets. When institutional investors observe excess returns on their foreign assets, they rebalance their portfolios by reducing their holdings of foreign assets and increasing their investments in domestic assets. This capital flow leads to an appreciation of the domestic currency. By using the S&P 500 as an instrument for the purchase or sale of US dollars (USD) by IIs, we find that a purchase of 1 billion USD results in a depreciation of the Shekel by approximately 2-2.5%. Importantly, this relationship has only emerged in recent years as the wealth managed by institutional investors has grown substantially.
Working paper 10-2023
(Asset) Pricing the Business Cycle
Optimal hiring and investment over the business cycle is governed by asset values – the expected present value of workers (QN), of capital (QK), and of the firm (Q). Importantly, labor and capital Qs are inter-related. The paper formalizes the connections between aggregate shocks (TFP, investment-specific, and matching technology), the afore-cited asset values, investment and hiring decisions, and the production of aggregate output. Using aggregate U.S. data and structural estimation, time series for the unobserved Qs are derived; a local projections methodology is then used to study the cyclical behavior of asset values and of the decision variables.
Working paper 11-2023
Bilateral trade with a benevolent intermediary
Ran Eilat, Ady Pauzner
We study intermediaries who seek to maximize gains from trade in bilateral negotiations. Intermediaries are players: they cannot commit to act against their objective function and deny, in some cases, trade they believe to be beneficial. This impairs their ability to assist the parties relative to conventional mechanisms. We analyze this limited commitment environment as a standard mechanism design problem with an additional “credibility” constraint, requiring that every outcome be interim-optimal conditional on available information. We investigate how such intermediaries communicate with the parties, analyze the tradeoffs they face, and study the bounds on what they can achieve.
Published in Theoretical Economics, Volume 16, Issue 4 Nov 2021, Pages i-ii, 1195-1714, iii-iv.
Working paper 12-2023
A spatial vaccination strategy to reduce the risk of vaccine-resistant variants
Xiyun Zhang, Gabriela Lobinska, Michal Feldman, Eddie Dekel, Martin A. Nowak,Y itzhak Pilpel, Yonatan Pauzner, Baruch Barzel, Ady Pauzner
The COVID-19 pandemic demonstrated that the process of global vaccination against a novel virus can be a prolonged one. Social distancing measures, that are initially adopted to control the pandemic, are gradually relaxed as vaccination progresses and population immunity increases. The result is a prolonged period of high disease prevalence combined with a fitness advantage for vaccine-resistant variants, which together lead to a considerably increased probability for vaccine escape. A spatial vaccination strategy is proposed that has the potential to dramatically reduce this risk. Rather than dispersing the vaccination effort evenly throughout a country, distinct geographic regions of the country are sequentially vaccinated, quickly bringing each to effective herd immunity. Regions with high vaccination rates will then have low infection rates and vice versa. Since people primarily interact within their own region, spatial vaccination reduces the number of encounters between infected individuals (the source of mutations) and vaccinated individuals (who facilitate the spread of vaccine-resistant strains). Thus, spatial vaccination may help mitigate the global risk of vaccine-resistant variants.
Published in PLOS Computational Biology, August 10, 2022 [https://doi.org/10.1371/journal.pcbi.1010391]