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Dynamic Perturbation

5 April 2024

Alessandro Mennuni, Juan Rubio-Ramirez, and Serhiy Stepanchuk

We present a novel algorithm called Dynamic Perturbation for solving large-scale macroeconomic models. Our approach involves computing first-order Taylor expansions of the policy functions along the entire equilibrium path. This method applies to a wide range of models and offers significantly higher accuracy than traditional perturbation approaches. Remarkably, even when utilizing first-order approximations, our method can effectively handle models with strong nonlinearities and occasionally binding constraints, such as the zero lower bound.

Interview Sequences and the Formation of Subjective Assessments

5 April 2024

Jonas Radbruch and Amelie Schiprowski

Interviewing is a decisive stage of most processes that match candidates to firms and organizations. This paper studies how and why a candidate’s interview outcome depends on the other candidates interviewed by the same evaluator. We use large-scale data from high-stakes admission and hiring processes, where candidates are quasi-randomly assigned to evaluators and time slots. We find that the individual assessment decreases as the quality of other candidates assigned to the same evaluator increases. The influence of the previous candidate stands out, leading to a negative autocorrelation in evaluators’ votes of up to 40% and distorting final admission and hiring decisions.

The Macroeconomics of Supply Chain Disruptions

5 April 2024

Daron Acemoglu and Alireza Tahbaz-Salehi

This paper develops a model to study the macroeconomic implications of supply chain disruptions with three key ingredients: (i) a firm-level network of customized supplier-customer links that generate relationship-specific productivity gains; (ii) bargaining over these relationship-specific surpluses; and (iii) an extensive margin of adjustment, whereby firms decide to form or sever relations with suppliers and customers.

Monopoly of Taxation Without a Monopoly of Violence: The Weak State’s Trade-Offs From Taxation

1 April 2024

Soeren J. Henn, Christian Mastaki Mugaruka, Miguel Ortiz, Raúl Sánchez de la Sierra, and David Qihang Wu

This study presents a new economic perspective on state-building based on a case study in the Democratic Republic of the Congo’s hinterland. We explore the implications for the state of considering rebels as stationary bandits. When the state, through a military operation, made it impossible for rebels to levy taxes, it inadvertently encouraged them to plunder the assets of the very citizens they previously preferred to tax.

Signaling with Private Monitoring

1 April 2024

Gonzalo Cisternas and Aaron Kolb

We study dynamic signaling when the sender does not see the signals that her actions generate. The sender then uses her past play to forecast what a receiver believes, in turn forcing the receiver to forecast the previous forecast, and so forth. We identify a class of linear-quadratic-Gaussian games where this endogenous higher-order uncertainty can be handled. The sender’s second-order belief is key: it is a private state that she controls, and it creates a new channel for information transmission.

The Heterogeneous Effects of Government Spending: It’s All about Taxes

25 March 2024

Axelle Ferriere and Gaston Navarro

Historically, large changes in U.S. government spending induced fiscal efforts that were not all alike, with some using more progressive taxes than others. We develop a heterogeneous-agent New Keynesian model to analyze how the distribution of taxes across households shapes spending multipliers. The model yields empirically realistic distributions in marginal propensities to consume and labor elasticities, which result in lower responsiveness to tax changes for higher-income earners. In turn, multipliers are larger when spending is financed with higher tax progressivity—that is, when the tax burden falls more heavily on higher-income earners.

Dynamic Demand Estimation in Auction Markets

25 March 2024

Matthew Backus and Gregory Lewis

We study demand estimation in a large auction market. In our model, a dynamically evolving population of buyers with unit demand and heterogeneous and privately known preferences for a finite set of differentiated products compete in a sequence of auctions that occur in discrete time. We define an empirically tractable equilibrium concept in which bidders behave as though they are competing with the stationary distribution of opposing bids, characterize bidding strategies, and prove existence of equilibrium. Having developed this demand system, we prove that it is non-parametrically identified from panel data.

International Comovement in the Global Production Network

25 March 2024

Zhen Huo, Andrei Levchenko, and Nitya Pandalai-Nayar

This paper provides a general framework to study the role of production networks in international GDP comovement. We first derive an additive decomposition of bilateral GDP comovement into components capturing shock transmission and shock correlation. We quantify this decomposition in a parsimonious multi-country, multi-sector dynamic network propagation model, using data for the G7 countries over the period 1978-2007. Our main finding is that while the network transmission of shocks is quantitatively important, it accounts for a minority of observed comovement under the estimated range of structural elasticities.

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How does capital irreversibility (and other investment frictions) shape economic booms and recoveries?

I explore these ideas in this @FacultiNet video (20mins)

Based on my research with @jandres_blanco forthcoming at the @RevEconStudies

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Recently accepted to #REStud, "Quantifying the Benefits of Labor Mobility in a Currency Union," from House, Proebsting and Tesar:

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"Winners of Excellence in Refereeing Award for 2024"

The Review of Economic Studies thanks all of the exceptional referees who have contributed their time & expertise to the journal.

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Chris and I had the pleasure of writing a nontechnical summary of our forthcoming @RevEconStudies paper () in the @LSEUSAblog!

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