Job market advice for new Ph.D. economists, from John Cawley

 From applying for jobs, to signaling for interviews,  through interviews, flyouts, offers and the scramble, John Cawley, the chair of the American Economic Association's Committee on the Job Market has measured advice in this video.  If you're on the market this year, do yourself a favor (pour a stiff drink) and listen, not just to the beginning discussion of disruptions in demand thisyear, but to the whole thing.

    
2025 Webinar on the Economics PhD Job Market 

Recent good looking market design papers I hope to read (on auctions, unraveling, and interviews)

There was a time when I could reasonably hope to have read market design papers before they appeared in print, but now there are many fine papers that I'll never have a chance to read. (I'm sure that's just because the field is growing so much...)  I haven't given up, however...   Here are three that recently caught my eye.

Hu, Edwin, and Dermot Murphy. "Vestigial tails? Floor brokers at the close in modern electronic markets." Management Science (2025).

 Abstract: The closing auction is an increasingly important trade mechanism due to the rise of passive funds that require closing price execution. We study differences in auction mechanism design on NYSE and Nasdaq that may affect closing price efficiency. Unlike Nasdaq, NYSE allows late auction orders through its floor brokers, providing traders with more flexibility to mitigate or create large last-minute auction imbalances. Price changes in the closing auction are more likely to reverse on NYSE compared with Nasdaq, suggesting greater price inefficiency in NYSE closing auctions. Larger last-minute abnormal imbalances on NYSE, particularly in stocks where auction competition may be inhibited by relatively high floor broker auction fees, explain these stronger reversals. Evidence from the NYSE floor closure during the COVID-19 pandemic supports a causal interpretation. Our results highlight an important tradeoff between auction flexibility and price efficiency.

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Stable Matching with Interviews, by Itai Ashlagi, Jiale Chen, Mohammad Roghani, Amin Saberi

    Part of: Volume: 16th Innovations in Theoretical Computer Science Conference (ITCS 2025)
    Series: Leibniz International Proceedings in Informatics (LIPIcs)
    Conference: Innovations in Theoretical Computer Science Conference (ITCS)  

Abstract: "In several two-sided markets, including labor and dating, agents typically have limited information about their preferences prior to mutual interactions. This issue can result in matching frictions, as arising in the labor market for medical residencies, where high application rates are followed by a large number of interviews. Yet, the extensive literature on two-sided matching primarily focuses on models where agents know their preferences, leaving the interactions necessary for preference discovery largely overlooked. This paper studies this problem using an algorithmic approach, extending Gale-Shapley’s deferred acceptance to this context.
Two algorithms are proposed. The first is an adaptive algorithm that expands upon Gale-Shapley’s deferred acceptance by incorporating interviews between applicants and positions. Similar to deferred acceptance, one side sequentially proposes to the other. However, the order of proposals is carefully chosen to ensure an interim stable matching is found. Furthermore, with high probability, the number of interviews conducted by each applicant or position is limited to O(log² n).
In many seasonal markets, interactions occur more simultaneously, consisting of an initial interview phase followed by a clearing stage. We present a non-adaptive algorithm for generating a single stage set of in tiered random markets. The algorithm finds an interim stable matching in such markets while assigning no more than O(log³ n) interviews to each applicant or position."

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Deadlines and matching, by Garth Baughman, Journal of Economic Theory, Volume 228, September 2025
https://doi.org/10.1016/j.jet.2025.106065

Abstract: Deadlines and fixed end dates are pervasive in matching markets. Deadlines drive fundamental non-stationarity and complexity in behavior, generating significant departures from the steady-state equilibria usually studied in the search and matching literature. I consider a two-sided matching market with search frictions where vertically differentiated agents attempt to form bilateral matches before a deadline. I give novel proofs of existence and uniqueness of equilibria, and show that all equilibria exhibit an “anticipation effect” where less attractive agents become increasingly choosy over time, preferring to wait for the opportunity to match with attractive agents who, in turn, become less selective as the deadline approaches. When agents are patient, a sharp characterization is available: at any point in time, the market segments into a first class of matching agents and a second class of waiting agents. This points to a different interpretation of unraveling.

Stable Matching with Interviews, by Ashlagi, Chen, Roghani and Saberi

 Job applicants can now easily submit many job applications, and so interviewing applicants, which is time consuming, has become a major source of congestion in many labor markets.  But even in labor markets that use a clearinghouse to process offers and acceptances (like the market for medical residents in the U.S., the NRMP match) interviews are often organized in a decentralized manner. Here's a paper that tackles the question of how to organize an interview match, under some assumptions about what kind of information is obtained in interviews.  Two approaches are considered: an 'adaptive' algorithm that takes into account the results of previous interviews in assigning subsequent interviews, and a 'non-adaptive' algorithm that matches candidates to interviews before any interview results are known.

Stable Matching with Interviews, by Itai Ashlagi, Jiale Chen, Mohammad Roghani, and Amin Saberi (all at Stanford)

Abstract
"In several two-sided markets, including labor and dating, agents typically have limited information about their preferences prior to mutual interactions. This issue can result in matching frictions, as arising in the labor market for medical residencies, where high application rates are followed by a large number of interviews. Yet, the extensive literature on two-sided matching primarily focuses on models where agents know their preferences, leaving the interactions necessary for preference discovery largely overlooked. This paper studies this problem using an algorithmic approach, extending Gale-Shapley’s deferred acceptance to this context. Two algorithms are proposed. The first is an adaptive algorithm that expands upon GaleShapley’s deferred acceptance by incorporating interviews between applicants and positions. Similar to deferred acceptance, one side sequentially proposes to the other. However, the order of proposals is carefully chosen to ensure an interim stable matching is found. Furthermore, with high probability, the number of interviews conducted by each applicant or position is limited to O(log^2 n).
"In many seasonal markets, interactions occur more simultaneously, consisting of an initial interview phase followed by a clearing stage. We present a non-adaptive algorithm for generating a single stage set of in tiered random markets. The algorithm finds an interim stable matching in such markets while assigning no more than O(log^3 n) interviews to each applicant or position. "

Signaling to decongest job applications and interviews: update on the market for medical residents

 Signaling for interviews is evolving in the market for new doctors, i.e. for medical residencies.  Some specialties are allowing a relatively small number of signals (as in Economics), while others are moving towards many signals, which are functioning as soft caps on the number of applications, since many residency programs in those specialties won't give an interview to someone who doesn't signal them.

Ozair, A., Hanson, J. T., Detchou, D. K., Blackwell, M. P., Jenkins, A., Tissot, M. I., Barrie, U., & McDermott, M.  W. (2024). Program Signaling and Geographic Preferences in the United States Residency Match for Neurosurgery. Cureus, 16(9), e69780. https://doi.org/10.7759/cureus.69780