An Empirical Model of the Medical Match

Agarwal, Nikhil

doi:10.3386/w20767

Cited by 27 publications

(41 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A growing literature is interested in methods of analyzing preferences in matching markets, usually using pairwise stability (Choo and Siow, 2006;Fox, 2010Fox, , 2017Chiappori et al, 2017;Agarwal, 2015;Diamond and Agarwal, 2016). In some cases, estimates are based on the strategic decision to engage in costly courting decisions (Hitsch et al, 2010).…”

Section: Related Literaturementioning

confidence: 99%

Demand Analysis using Strategic Reports: An application to a school choice mechanism

Agarwal

Somaini

2014

Self Cite

View full text Add to dashboard Cite

Several school districts use assignment systems that give students an incentive to misrepresent their preferences. We find evidence consistent with strategic behavior in Cambridge. Such strategizing can complicate preference analysis. This paper develops empirical methods for studying random utility models in a new and large class of school choice mechanisms. We show that preferences are non-parametrically identified under either sufficient variation in choice environments or a preference shifter. We then develop a tractable estimation procedure and apply it to Cambridge. Estimates suggest that while 82% of students are assigned to their stated first choice, only 72% are assigned to their true first choice because students avoid ranking competitive schools. Assuming that students behave optimally, the Immediate Acceptance mechanism is preferred by the average student to the Deferred Acceptance mechanism by an equivalent of 0.08 miles. The estimated difference is smaller if beliefs are biased, and reversed if students report truthfully.

show abstract

Section: Related Literaturementioning

confidence: 99%

Demand Analysis using Strategic Reports: An application to a school choice mechanism

Agarwal

Somaini

2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…This insight has enabled and guided the empirical analyses of more flexible models of the medical match (Agarwal (2015)) and the market for oil drilling rights (Vissing (2017)). An extension of our analogy of a matching model to a measurement error model has also been used to prove identification results for and study a labor market model with data on worker productivity (Jiang (2016)).…”

Section: Identification From Many-to-one Matchesmentioning

confidence: 99%

“…Specifically, we show that a many-to-one matching market is needed for such identification. Agarwal (2015) and Vissing (2017) use our insight on the information in many-to-one matching to, respectively, estimate preferences in the market for medical residents and the market for oil drilling contracts using simulated minimum distance estimators. This approach is different from work by Logan, Hoff, and Newton (2008) and Boyd, Lankford, Loeb, and Wyckoff (2013), who propose techniques that use only the sorting of observed characteristics of agents as given by the matches (sorting patterns) to recover primitives.…”

Section: Related Literaturementioning

confidence: 99%

“…For instance, Agarwal (2015) uses a similar model to quantify the value for various attributes of medical residency programs such as size, prestige, and patient mix. An important restriction in the latent index framework is that agents have homogeneous ordinal preferences over their match partners.…”

Section: Nontransferable Utility Matching Models Of Matching Markets mentioning

confidence: 99%

“…The model may also provide an approximation in labor or education markets in which workers or students are primarily differentiated by skill and firms or colleges are primarily differentiated by quality. Further, the insights and results from our analysis have proven useful to empirical approaches in related models (see Agarwal (2015Agarwal ( , 2017, Vissing (2017), Jiang (2016)). …”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Latent indices in assortative matching models

Diamond

Agarwal

2017

Quantitative Economics

Self Cite

View full text Add to dashboard Cite

A large class of two-sided matching models that include both transferable and non-transferable utility result in positive assortative matching along a latent index. Data from matching markets, however, may not exhibit perfect assortativity due to the presence of unobserved characteristics. This paper studies the identification and estimation of such models. We show that the distribution of the latent index is not identified when data from one-to-one matches are observed. Remarkably, the model is nonparametrically identified using data in a single large market when each agent on one side has at least two matched partners. The additional empirical content in many-to-one matches is demonstrated using simulations and stylized examples. We then derive asymptotic properties of a minimum distance estimator as the size of the market increases, allowing estimation using dependent data from a single large matching market. The nature of the dependence requires modification of existing empirical process techniques to obtain a limit theorem.

show abstract

Path‐flow matching: Two‐sided matching and multiobjective evolutionary algorithm for traffic scheduling in cloud data^* center network

Tan

Gao

et al. 2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

Improving the operational efficiency of data center has always been an important direction for the development of ICT. In this paper, we apply two‐sided matching decision‐making process in game theory to traffic scheduling problem in data center network. From the perspective of matching between flow and path, the traffic scheduling is properly arranged. We first propose and model the path‐flow matching problem, considering the preference ordering, then formulate the problem as a multiobjective optimization problem with the target to ensure the stability and satisfaction from the matching scheme, and design a preference‐based path‐flow ordering method Extended PIAS, and finally propose a lightweight scheduling algorithm LinkGame based on multiobjective evolutionary algorithm. Compared with the previous scheduling methods (ECMP, Hedera, and Fincher), experiment results demonstrate that LinkGame can simultaneously consider the stability and satisfaction of the matching results, with improved bandwidth utilization and flow completion time.

show abstract

An Empirical Model of the Medical Match

Cited by 27 publications

References 27 publications

Demand Analysis using Strategic Reports: An application to a school choice mechanism

Demand Analysis using Strategic Reports: An application to a school choice mechanism

Latent indices in assortative matching models

Path‐flow matching: Two‐sided matching and multiobjective evolutionary algorithm for traffic scheduling in cloud data^* center network

Contact Info

Product

Resources

About

An Empirical Model of the Medical Match

Cited by 27 publications

References 27 publications

Demand Analysis using Strategic Reports: An application to a school choice mechanism

Demand Analysis using Strategic Reports: An application to a school choice mechanism

Latent indices in assortative matching models

Path‐flow matching: Two‐sided matching and multiobjective evolutionary algorithm for traffic scheduling in cloud data* center network

Contact Info

Product

Resources

About

Path‐flow matching: Two‐sided matching and multiobjective evolutionary algorithm for traffic scheduling in cloud data^* center network