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The Surrogate Index: Combining Short-Term Proxies to Estimate Long-Term Treatment Effects More Rapidly and Precisely

Susan Athey, Raj Chetty, Guido Imbens, and Hyungseung Kang

A common challenge in estimating the impact of interventions (e.g., job training programs, educational programs) is that many outcomes of interest (e.g., lifetime earnings or other labor market outcomes) are observed with a long delay. In biomedical settings this is often addressed by using short-term outcomes as so-called “surrogates” for the outcome of interest, e.g., tumor size as a surrogate for mortality in cancer studies. We build on this literature by combining multiple, possibly qualitatively distinct, short-term outcomes (e.g., short-run earnings and employment indicators) systematically into a “surrogate index.”

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Sanctions and the Exchange Rate

Oleg Itskhoki and Dmitry Mukhin

Trade wars and financial sanctions are again becoming an increasingly common part of the international economic landscape, and the dynamics of the exchange rate are often used in real time to evaluate the effectiveness of sanctions and policy responses. We show that sanctions limiting a country’s exports or freezing its assets depreciate the exchange rate, while sanctions limiting imports appreciate it, even when both types of policies have exactly the same effect on real allocations, including household welfare and government fiscal revenues.

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Patents, News, and Business Cycles

Silvia Miranda-Agrippino, Sinem Hacioglu-Hoke, and Kristina Bluwstein

We exploit information in patent applications to construct an instrumental variable for the identification of technology news shocks that relaxes all the identifying assumptions traditionally used in the literature. The instrument recovers news shocks that have no effect on aggregate productivity in the short-run, but are a significant driver of its trend component. The shock prompts a broad-based expansion in anticipation of the future increase in TFP, with output, consumption, and investment all rising well before any material increase in TFP is recorded.

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What’s My Employee Worth? The Effects of Salary Benchmarking

Zoe B. Cullen, Shengwu Li, and Ricardo Perez-Truglia

Firms are allowed to use aggregate data on market salaries to set pay, a practice known as salary benchmarking. Using national payroll data, we study firms that gain access to a tool that reveals market benchmarks for each job title. Using a difference-in-differences design, we find that the benchmark information reduces salary dispersion by 25%. Thus, salary dispersion must stem partly from aggregate uncertainty about the salaries offered by other firms.

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Algorithmic Recommendations and Human Discretion

Victoria Angelova, Will Dobbie, and Crystal S. Yang

Human decision-makers frequently override the recommendations generated by predictive algorithms, but it is unclear whether these discretionary overrides add valuable private information or reintroduce human biases and mistakes. We develop new quasi-experimental tools to measure the impact of human discretion over an algorithm on the accuracy of decisions, even when the outcome of interest is only selectively observed, in the context of bail decisions.

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Supply Chain Disruption and Reorganization: Theory and Evidence From Ukraine’s War

Vasily Korovkin, Alexey Makarin, and Yuhei Miyauchi

How do localized conflicts disrupt supply chains and prompt firms to reorganize them? How do these forces affect firm-level and aggregate economic activity? Using firm-to-firm Ukrainian railway-shipment data before and during the 2014 Russia-Ukraine conflict, we document that firms with prior supplier and buyer exposure to the conflict areas substantially decreased their output. Simultaneously, firms reorganized their production linkages away from partners directly or indirectly exposed to the conflict shock.

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Temporal-Difference Estimation of Dynamic Discrete Choice Models

Karun Adusumilli and Dita Eckardt

We study the use of Temporal-Difference learning for estimating the structural parameters in dynamic discrete choice models. Our algorithms are based on the conditional choice probability approach but use functional approximations to estimate various terms in the pseudo-log-likelihood function. We suggest two approaches: The first—linear semi-gradient—provides approximations to the recursive terms using basis functions. The second—Approximate Value Iteration—builds a sequence of approximations to the recursive terms by solving non-parametric estimation problems.

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"New study finds salary benchmarking cuts pay gaps by 25%. Pay dispersion partly arises from firms’ uncertainty about market rates, with key implications for pay transparency policy."

New paper from @pereztruglia, @zoebcullen, @ShengwuLi:

https://www.restud.com/whats-my-employee-worth-the-effects-of-salary-benchmarking/

#econtwitter

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"Competition via repo contracts resolves the lemons problem! A closed-form solution
for the unique pooling equilibrium explains why markets feature high haircuts and
low repo rates."

New paper from @SakiBigio & @liyan_shi:

https://www.restud.com/repurchase-options-in-the-market-for-lemons/

#econtwitter
#REStud

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"Wars disrupt supply chains, but firms adapt by reorganizing them. The 2014 war cut
Ukraine’s output in nonconflict areas by 5.5%, with one-third mitigated by link
reorganization."

New paper from @KorovkinVasily, @alexeymakarin & @MiyauchiYuhei:

https://www.restud.com/supply-chain-disruption-and-reorganization-theory-and-evidence-from-ukraines-war/
#REStud

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Recently accepted to #REStud, "Normalizations and misspecification in skill formation models," from Joachim Freyberger:

https://www.restud.com/normalizations-and-misspecification-in-skill-formation-models/

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