MIT News reports on a forthcoming paper by Nikhil Agarwal:

An Empirical Model of the Medical Match | Online Appendix
American Economic Review, forthcoming
(NBER Working Paper 20767 - includes analysis of government interventions for rural programs)

Here's the MIT News report:

Is the medical match fair?

Study finds the demand for positions strongly influences medical residents’ salaries.

Peter Dizikes | MIT News Office
January 27, 2015

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When medical-school graduates apply for their residencies, they use a centralized clearinghouse that matches applicants with jobs. This system has sometimes been challenged, such as in a lawsuit several years ago that claimed salaries of residents were reduced by this centralized matching method.

But a forthcoming study by an MIT economist indicates that demand for a limited number of desirable residency positions can keep salaries low — and introduces a new way of assessing that demand despite incomplete data that has previously restricted analysis of the issue.

“Salaries will likely remain low unless residency programs can increase the number of positions,” says Nikhil Agarwal, an assistant professor of economics at MIT, and author of the paper on the subject.

On average, Agarwal’s study finds, salaries of medical residents are lowered by an average of $23,000 due to the demand for slots. As the study puts it, residents are willing to accept an “implicit tuition” in their wages in return for experience and prestige. In the long run, residencies may be a worthwhile tradeoff for doctors establishing themselves in the profession, even with seemingly reduced wages.  

Determining demand

Agarwal’s paper, to be published in the American Economic Review, is based on data from 2003 to 2011 gathered by the National Graduate Medical Education census.

The central clearinghouse — the National Residency Matching Program (NRMP) — matches about 25,000 medical residents annually. Incoming residents rank the positions they would most like to have, and an algorithm matches these choices with the ranked preferences of the medical programs.

A 2002 lawsuit asserted that the residents have limited bargaining power because they are assigned to positions and cannot receive multiple job offers, unfairly lowering their compensation. That suit was eventually dismissed in 2004, a few months after Congress passed an antitrust exemption for the NRMP system.

But that resolution of the lawsuit did not resolve the question of whether or not the clearinghouse does affect residency salaries. As of 2010, residents had a mean salary of about $47,000, compared to $86,000 for physician assistants, who do comparable work. Medical residents also have notably long workweeks and shifts, which themselves are the subject of intermittent public debate.

Agarwal’s study finds a new way of analyzing the compensation issue in the face of limited information. He did not have access to the ranked lists of jobs that applicants submit to the NRMP, nor to the lists of preferred candidates that medical programs submit. Even so, Agarwal was able to study the matched pairs of residents and positions, along with some additional descriptive data, such as geographic location, and determine demand on that basis.

The key to the analysis, Agarwal says, is “the fact that there are multiple residents in the same program. That tells you a lot about the residency program’s preferences for residents. Once you figure out that side of the market, you’re in business.”

For instance, Agarwal adds, “If a program [decides] to hire residents from [highly ranked] medical schools with similar licensing-exam test scores, then everybody it’s matched with will be similar on those characteristics. But if it doesn’t care about prestige of the medical school as much, there might be people from all kinds of medical schools, but their licensing-exam scores will be similar.” Partly by building a picture of those preferences and measuring it against the characteristics of the class of applicants, it is possible to estimate how many qualified applicants are available for residency positions.

An ‘imperfect’ market

An underlying implication of Agarwal’s conclusions is that the idea of a perfectly competitive, uniform market driving salaries does not ultimately hold up to scrutiny when it comes to medical residencies. There appear to be clumps of jobs considered particularly desirable, leading to uneven relationships between supply and demand within the overall residency job market.

“In [my] theory, you get a situation where people are not indifferent” in terms of job preferences, Agarwal notes.

For his part, Agarwal, who focuses on the growing field of market design, believes this method of determining preferences can be applied to other domains as well.  He is continuing to do research in the area of school choice, among other topics.

Nikhil Agarwal defends his Ph.D. dissertation

Nikhil Agarwal defended his Ph.D. dissertation earlier this week. Two members of his committee, me and Susan Athey, skyped in from Stanford. But in the age of photoshop, seeing isn't believing: here is a photo of the post-defense celebration as it happened, and as it would have happened if California were a suburb of Boston...

Parag Pathak, Nikhil Agarwal, Ariel Pakes

Al Roth, Parag Pathak, Nikhil Agarwal, Ariel Pakes and Susan Athey

I blogged about his job market paper here, and his job market here.

Welcome to the club, Nikhil.

Matching and more: Continuing Education at the AEA meetings in Philadelphia

2018 Continuing Education, January 7-9, 2018, Sheraton Philadelphia Downtown

The AEA's 2018 Continuing Education Program will be held at the Sheraton Philadelphia Downtown on January 7-9, 2018, immediately following the close of ASSA. Participants can choose from three concurrent programs. Registration now open. (Alternatively, download PDF Registration form.)

Matching Market Design

Atila Abdulkadiroglu (Duke University)

Atila Abdulkadiroglu joined the Department of Economics at Duke University in the Fall of 2006. He taught at Northwestern University and Columbia University before coming to Duke. He received his PhD in Economics at the University of Rochester. His research has led to the design and implementation of better admissions policies in school choice programs in the US, He has consulted several school districts in redesigning student assignment systems, including Boston (MA), Chicago (Il), Denver (CO), New Orleans (LA), New York City (NY). His current research also focuses on economics of education. He is a recipient of an Alfred P. Sloan Research Fellowship and a National Science Foundation CAREER award. Abdulkadiroglu serves as an Editor-in-Chief of Review of Economic Design. He serves on the board of The Institute for Innovation in Public School Choice.

Nikhil Agarwal (MIT)

Nikhil Agarwal is the Castle Krob Career Development Assistant Professor of Economics at Massachusetts Institute of Technology, where he has been teaching since 2014. He completed his PhD in Economics at Harvard University in 2013, and was a Postdoctoral Associate at the Cowles Foundation for Research in Economics at Yale University. Agarwal specializes in the empirical study of matching markets. He has developed tools that have been applied to labor markets, education markets and organ allocation systems.

Parag Pathak (MIT)

Parag A. Pathak is the Jane Berkowitz Carlton and Dennis William Carlton Professor of Microeconomics at MIT, found­ing co-director of the NBER Working Group on Market Design, and founder of MIT's School Effectiveness and Inequality Initiative (SEII), a laboratory focused on education, human capital, and the income distribution.  Pathak has helped to design the Boston, Chicago, Denver, Newark, New Orleans, New York, and Washington DC school choice systems.   His work on mar­ket design and edu­ca­tion was garnered numerous recognitions including a Presidential Early Career Award for Scientists and Engineers and the 2016 Social Choice and Welfare prize.  He has also authored leading studies on charter schools, high school reform, selective education, and school vouchers.  Pathak is a Fellow of the Econometric Society, and has served on the editorial boards of Econometrica, American Economic Review, and the Journal of Political Economy.

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Machine Learning and Econometrics

Susan Athey (Stanford University)

Susan Athey is the Economics of Technology Professor at Stanford Graduate School of Business.  She received her bachelor’s degree from Duke University and her PhD from Stanford, and she holds an honorary doctorate from Duke University. She previously taught at the economics departments at MIT, Stanford and Harvard. Her current research focuses on the economics of digitization, marketplace design, and the intersection of econometrics and machine learning.  She has worked on several application areas, including timber auctions, internet search, online advertising, the news media, and virtual currency. As one of the first “tech economists,” she served as consulting chief economist for Microsoft Corporation for six years, and now serves on the boards of Expedia, Rover, and Ripple.  She also serves as a long-term advisor to the British Columbia Ministry of Forests, helping architect and implement their auction-based pricing system.

Guido Imbens (Stanford University)

Guido Imbens is Professor of Economics at the Stanford Graduate School of Business. After graduating from Brown University Guido taught at Harvard University, UCLA, and UC Berkeley. He joined the GSB in 2012. Imbens specializes in econometrics, and in particular methods for drawing causal inferences. Guido Imbens is a fellow of the Econometric Society and the American Academy of Arts and Sciences. Guido Imbens has taught in the continuing education program previously in 2009 and 2012.

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DSGE Models and the Role of Finance

Lawrence Christiano (Northwestern University)

Larry Christiano's research has been focused primarily on the problem of determining how the government's monetary and fiscal instruments ought to respond to shocks over the business cycle. This research has two parts: one involves formulating and estimating an empirically plausible model of the macroeconomy, and the second involves developing economic concepts and computational methods for determining optimal policy in an equilibrium model. He is a Fellow of the Econometric Society, and a research associate of the National Bureau of Economic Research.

Thomas Philippon (New York University)

Thomas Philippon is Professor of Finance at New York University - Stern School of Business. Philippon was named one of the “top 25 economists under 45” by the IMF in 2014, he won the 2013 Bernácer Prize for Best European Economist under 40, the 2010 Michael Brennan & BlackRock Award, the 2009 Prize for Best Young French Economist, and the 2008 Brattle Prize for the best paper in Corporate Finance. He was elected Global Economic Fellow in 2009 by the Kiel Institute for the World Economy. He has studied various topics in finance and macroeconomics: financial distress, systemic risk, government interventions during financial crises, asset markets and corporate investment. Recently his work has focused on the evolution of the financial system and on the Eurozone crisis. He currently serves on the Monetary Policy Advisory Panel of the NY Federal Reserve Bank, and as a board member and director of the scientific committee of the French prudential regulator (ACPR). He was the senior economic advisor to the French finance minister in 2012-2013. Philippon graduated from Ecole Polytechnique, received a PhD in Economics from MIT, and joined New York University in 2003.

MIT celebrates Nikhil Agarwal

Optimizing kidney donation and other markets without money
MIT economist Nikhil Agarwal analyzes the efficiency of markets that match suppliers and consumers but don’t use prices.

“In economics,” Agarwal says, “we often [assume] there’s the demand, the supply, the price, and the market clears, somehow. It just happens.” And yet, he says, “That’s not how a lot of markets work. There are all these different important markets where we do not allow prices.”

Scholars in the field of “market design,” therefore, closely examine these nonfinancial markets, observing how their rules and procedures affect outcomes. Agarwal calls himself a specialist in “resource allocation systems that do not use prices.” These include kidney donations: The law forbids selling vital organs. Many education systems and entry-level labor markets, for example, also fit into this category. "
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I've followed Nikhil's work for a long time--here are some other posts that mention his work.

Ariel Pakes gives the Arrow Lecture in Jerusalem

If you're in Jerusalem tomorrow, you have a chance to hear Ariel Pakes' Arrow Lecture:

17:00-18:00 Ariel Pakes, Arrow lecture:

Learning and Equilibrium in A New Market

It is part of

The 29th Jerusalem Summer School of Economics

Industrial Organization

Event date: June 26 - July 5, 2018 

Organizers:

Eric Maskin, General Director (Harvard University)
Ariel Pakes, Codirector (Harvard University)
Elchanan Ben-Porath,Codirector (The Hebrew University)





Industrial Organization studies how markets are structured and the way they respond to changes in conditions (e.g., to policy revisions). The field draws heavily on both theory and empirical work, and both will be amply represented in the Summer School. We will focus on several topics of current research interest: vertical markets, allocation in markets without prices, market dynamics, and regulation.


  
List of speakers:


NAME AFFILIATION EMAIL TOPICS Nikhil Agarwal Massachusetts Institute of Technology agarwaln@mit.edu The analysis of centralized market allocation mechanisms John Asker The University of California johnaskecr@econ.ucla.edu The analysis of regulation Alon Eizenberg  The Hebrew University of Jerusalem       aloneiz@mscc.huji.ac.il The analysis of regulation Myrto Kalouptsidi Harvard University  myrto@fas.harvard.edu The analysis of market dynamics Robin Lee Harvard University robinlee@fas.harvard.edu The   analysis of   vertical markets Eric Maskin          Harvard University emaskin@fas.harvard.edu  The analysis of market dynamics Ariel Pakes Harvard University apakes@fas.harvard.edu The analysis of market dynamics Parag Pathak Massachusetts Institute of Technology ppathak@mit.edu The analysis of centralized market allocation mechanisms Mike Whinston Massachusetts Institute of Technology whinston@mit.edu The analysis of vertical markets Ali Yurukoglu Stanford University ayurukog@stanford.edu The analysis of regulation

Here's a link to the full program.

There will be several sessions on matching markets:

Wednesday, July 4

9:30-11:00 Parag Pathak: Introduction to Matching Theory

11:00-11:30 Coffee Break

11:30-13:00 Nikhil Agarwal: Revealed Preference for Matching Markets

Thursday, July 5

9:30-11:00 Parag Pathak: Market Design Meets Research Design

11:00-11:30 Coffee break

11:30-13:00 Nikhil Agarwal: The Organization of Organ Markets

Nikhil Agarwal, in Forbes

30 Under 30: The Entrepreneurs Making Healthcare Digital

"Then there are the big thinkers. MIT Assistant Prof. Nikhil Agarwal is using economics theory to understand how the medical match, which decides where doctors train, works."

Nikhil Agarwal, 28

Assistant professor, MIT

The match system that decides where doctors do their residencies can seem unfair. Worse: it seemed more prestigious hospitals paid less than they should. This MIT economist has created models showing that this is simply the result of having a limited number of positions at the programs that provide the best training. Next up: a study of the similar match system used in New York City high schools.

The NBER market design lectures from the 2016 Summer Institute (Videos)

This summer the "methods lectures" at the NBER summer institute were on market design. Videos of the five lectures (each about 45 minutes long) are here.

Summer Institute 2016 Methods Lectures

July 26, 2015
Lecturers: Al Roth, Parag Pathak, Atila Abdulkadiroglu, Nikhil Agarwal, Itai Ashlagi

Reading List

Al Roth
Game Theory and Market Design

You can download this video from here

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Parag Pathak
Design of Matching Markets

You can download this video from here

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Atila Abdulkadiroglu
Research Design meets Market Design

You can download this video from here

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Nikhil Agarwal
Revealed Preference Analysis in Matching Markets

You can download this video from here

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Itai Ashlagi
Matching Dynamics and Computation

You can download this video from here 


And you can see a short introductory video in which I am interviewed about market design here (and for the time being on the NBER home page, http://nber.org/). 

NBER Market Design: 2016 Methods Lectures, Tuesday July 26 (Abdulkadiroglu, Agarwal, Ashlagi, Pathak, and Roth)

Atila Abdulkadiroglu, Nikhil Agarwal, Itai Ashlagi, Parag Pathak and I will be delivering a set of "Methods Lectures" on Market Design as part of the NBER Summer Institute sessions on Labor Economics, which will be held July 25-29, 2016 at the Royal Sonesta Hotel in Cambridge MA.
The program for the whole week is here, and below is the Tuesday afternoon Market Design program.

NBER Market Design: 2016 Methods Lectures
1:15 pm	Welcome
1:20 pm	Al Roth: Game Theory and Market Design
2:05 pm	Parag Pathak and Atila Abdulkadiroglu: Design of Matching Markets
2:50 pm	Break
3:00 pm	Atila Abdulkadiroglu and Parag Pathak: Research Design meets Market Design
3:45 pm	Nikhil Agarwal: Revealed Preference Analysis in Matching Markets
4:30 pm	Break
4:40 pm	Itai Ashlagi: Matching Dynamics and Computation
5:30 pm	Adjourn

Nikhil Agarwal investigates the medical match (and school choice)

The matching literature has been short on theoretically sophisticated investigators who are simultaneously tooled-up for the most serious kinds of empirical work and curious about the rules of the game that make markets work.  Nikhil Agarwal should put your mind at rest on that score. His dissertation committee consists of Ariel Pakes, Susan Athey, Parag Pathak and me. And his job market paper reports an investigation of a market close to my heart:  An Empirical Model of the Medical Match

"Abstract: This paper develops a framework for estimating preferences in two-sided matching markets with non-transferable utility using only data on observed matches. Unlike single-agent choices, matches depend on the preferences of other agents in the market. I use pairwise stability together with a vertical preference restriction on one side of the market to identify preference parameters for both sides of the market. Recovering the distribution of preferences is only possible in an environment with many-to-one matching. These methods allow me to investigate two issues concerning the centralized market for medical residents. First, I examine the antitrust allegation that the clearinghouse restrains competition, resulting in salaries below the marginal product of labor. Counterfactual simulations of a competitive wage equilibrium show that residents' willingness to pay for desirable programs results in estimated salary markdowns ranging from $23,000 to $43,000 below the marginal product of labor, with larger markdowns at more desirable programs. Therefore, a limited number of positions at high quality programs, not the design of the match, is the likely cause of low salaries. Second, I analyze wage and supply policies aimed at increasing the number of residents training in rural areas while accounting for general equilibrium effects from the matching market. I find that financial incentives increase the quality, but not the number of rural residents. Quantity regulations increase the number of rural trainees, but the impact on resident quality depends on the design of the intervention."

Nikhil is also doing exciting empirical work on school choice: here's the abstract from a forthcoming (and largely completed) working paper;

Sorting and Welfare Consequences of Coordinated Admissions: Evidence from New York City
with Atila Abdulkadiroglu and Parag Pathak, Coming Soon.

Centralized and coordinated application systems are a growing part of recent school choice reforms. This paper estimates preferences for schools using rank order lists from New York City's new high school assignment system launched in Fall 2003 to study the consequences of coordinating school admissions in a mechanism based on the student-proposing deferred acceptance algorithm. Compared to the prior mechanism with multiple offers and a limited number of choices, there is a 40% increase in enrollment at assigned school. The old mechanism restricted choices and placed many students close to home, while the new mechanism assigns students to schools 0.7 miles further from home on average. Student preferences trade off proximity and school quality, but are substantially heterogeneous. Even though students prefer closer schools, the new mechanism is more likely to assign students to schools they prefer and this more than compensates for the distance increase. The average welfare increases by the equivalent of 0.25 miles from the new mechanism. Students from all boroughs, demographic groups, and baseline achievement categories obtain a more preferred assignment on average from the new mechanism, suggesting that allocative changes involving assignment mechanisms need not be zero-sum.

Nikhil is on the market. You could hire him this year.

WSJ channels Nikhil Agarwal on salaries of medical residents

Here’s the Real Reason Medical Residents Make Just $47,000 a Year, Study Suggests

"In an upcoming paper in the American Economic Review, Dr. Agarwal argues thatstudents are willing to take a hefty pay cut to end up at a prestigious residency, and this lowers resident salaries by an average of $23,000 annually for all programs. In 2010, the average medical resident made about $47,000 a year, while physician assistants made about $86,000.

“The matching algorithm results in very efficient allocations and a very timely and well-functional market, but people have been resistant to using it because of this issue–they fear that it might negatively affect salaries,” Dr. Agarwal said. “After this paper, we learned that the fact that salaries are low in the medical residency market has nothing to do with the algorithm itself. Rather, it’s because of fundamental economic forces, like the limited number of positions at fantastic hospitals.”

In the medical-residency market, students and residency programs both rank their top choices, and are then matched using this algorithm. In 2012, Alvin Roth and Lloyd Shapley received the Nobel Prize in economics in part for their work creating said algorithm, which is also used in areas such as matching students with public high schools.

A 2002 class-action lawsuit claimed that the medical residency algorithm violated antitrust laws and artificially lowered resident salaries, which are not negotiated between residents and programs. The lawsuit was dismissed after Congress made a special exception for the medical match program under antitrust law.

Dr. Agarwal’s paper finds that applicants are willing to pay an “implicit tuition”—defined as the difference between their actual salary and the salary their labor is worth–to have a prestigious and high-demand residency, such as those at Massachusetts General Hospital or Johns Hopkins Hospital. This keeps salaries low across the board, since all programs are able to levy an “implicit tuition” based on how desirable they are. The implicit tuition is the largest at the top.

“The top programs pay a little bit more than the average programs, but there’s a sense in which their salaries are low relative to the value of the medical resident labor they’re getting,” he said.

Dr. Agarwal used data collected from 2003 to 2011 by the National Graduate Medical Education census. He knew only the outcomes and not how the residents and programs ranked each other.

However, programs that hire multiple residents reveal a lot about their preferences. By comparing the profiles of the residents ultimately accepted by a program, he could infer which factors–such as licensing scores or educational prestige–the program valued most in the admissions process. After doing this for various programs, he was then able to figure out which options a given resident was likely to have had, and estimate the demand for each position.

Since the number of positions is limited relative to demand, more positions at these top residencies would mean the programs will have to compete with each other, therefore increasing salaries, he explained."

The econometrics of many-to-one matching: Nikhil Agarwal and William Diamond

It turns out that you can get a lot more information about preferences from many to one (or many to many) matching than from one to one matching, because e.g. something about your employer's preferences (and why they wanted to hire you) can be deduced from who else they hired.

IDENTIFICATION AND ESTIMATION IN TWO-SIDED MATCHING MARKETS 
By Nikhil Agarwal and William Diamond

Abstract: We study estimation and non-parametric identification of preferences in two-sided matching markets using data from a single market with many agents. We consider a model in which preferences of each side of the market is homogeneous, utility is nontransferable utility and the observed matches are pairwise stable. We show that preferences are not identified with data on one-to-one matches but are non-parametrically identified when data from many-to-one matches are observed. This difference in the identifiability of the model is illustrated by comparing two simulated objective functions, one that does and the other that does not use information available in many-to-one matching. We also prove consistency of a method of moments estimator for a parametric model under a data generating process in which the size of the matching market increases, but data only on one market is observed. Since matches in a single market are interdependent, our proof of consistency cannot rely on observations of independent matches. Finally, we present Monte Carlo studies of a simulation based estimator.


Here's my post on Nikhil's defense.

Four Harvard students on the economics job market this year (2012-13)

Moving between universities isn't a simple thing: although I'm no longer at Harvard, I'll be helping four Harvard students go on the market this year.

Postdoctoral positions seem to be playing a larger role in the economics job market than they used to; one of the four (Scott Kominers) is going on the market after completing a two year postdoc. Another student of mine (Alex Peysakhovich) is defending this semester but taking a postdoc and planning to go on the general market next year.

On the market this year are Nikhil Agarwal, Stephanie Hurder, Scott Kominers, and Johanna Mollerstrom 

I hope to post a blog about each of them in the coming days (as I did for my students last year), although this year I am busier and later. (Perhaps I'll be able to post a bit about being busy in the next few weeks as well.)  But time and the tide and the job market wait for no man, so keep an eye out for posts on these students.

I'll update this post with links to subsequent posts on these folks.
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Stephanie Hurder on Occupation Choice, Spouse Choice, and Family Labor Supply

Scott Kominers on designing matching markets for diversity

Nikhil Agarwal investigates the medical match (and school choice)

Johanna Mollerstrom on Quotas and Cooperation
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update: and here's where they went--

Update on those Four Harvard students on the economics job market this year (2012-13)

Market Design by Nikhil Agarwal & Eric Budish (forthcoming in the Handbook of Industrial Organization)

 Here's an NBER working paper that will appear in the Handbook of Industrial Organization:

Market Design by Nikhil Agarwal & Eric Budish

NBER WORKING PAPER 29367,  DOI 10.3386/w29367,  October 2021

Abstract: "This Handbook chapter seeks to introduce students and researchers of industrial organization (IO) to the field of market design. We emphasize two important points of connection between the IO and market design fields: a focus on market failures—both understanding sources of market failure and analyzing how to fix them—and an appreciation of institutional detail.

"Section II reviews theory, focusing on introducing the theory of matching and assignment mechanisms to a broad audience. It introduces a novel “taxonomy” of market design problems, covers the key mechanisms and their properties, and emphasizes several points of connection to traditional economic theory involving prices and competitive equilibrium.

"Section III reviews structural empirical methods that build on this theory. We describe how to estimate a workhorse random utility model under various data environments, ranging from data on reported preference data such as rank-order lists to data only on observed matches. These methods enable a quantification of trade-offs in designing markets and the effects of new market designs.

"Section IV discusses a wide variety of applications. We organize this discussion into three broad aims of market design research: (i) diagnosing market failures; (ii) evaluating and comparing various market designs; (iii) proposing new, improved designs. A point of emphasis is that theoretical and empirical analysis have been highly complementary in this research"

Here's the first paragraph:

"Textbook models envision markets as abstract institutions that clear supply and demand. Real markets have specific designs and market clearing rules. These features affect market participants and their allocations in various ways – they determine the actions an agent can take, the incentives for taking those actions, the information environment, the interactions between agents’ actions, and, ultimately, the final allocation. Well-designed markets have rules that coordinate and incentivize behavior in ways that lead to desirable outcomes. But it is not a given that all markets have good design. The Market Design field studies these  rules in order to understand their implications, to identify potential market failures, and to remedy them by designing better institutions."