Abstract We construct measures of industry performance and welfare in the U.S. automobile market from 1980 to 2018. We estimate a demand model using product-level data on market shares, prices, and attributes, and consumer-level data on demographics, purchases, and stated second choices. We estimate marginal costs assuming Nash-Bertrand pricing. We relate trends in consumer welfare and markups to trends in market structure and the composition of products. Although real prices rose, we find that markups decreased substantially, and the fraction of total surplus accruing to consumers increased. Consumer welfare increased over time due to improved product quality and improved production technology.
{"title":"The Evolution of Market Power in the U.S. Automobile Industry","authors":"Paul L E Grieco, Charles Murry, Ali Yurukoglu","doi":"10.1093/qje/qjad047","DOIUrl":"https://doi.org/10.1093/qje/qjad047","url":null,"abstract":"Abstract We construct measures of industry performance and welfare in the U.S. automobile market from 1980 to 2018. We estimate a demand model using product-level data on market shares, prices, and attributes, and consumer-level data on demographics, purchases, and stated second choices. We estimate marginal costs assuming Nash-Bertrand pricing. We relate trends in consumer welfare and markups to trends in market structure and the composition of products. Although real prices rose, we find that markups decreased substantially, and the fraction of total surplus accruing to consumers increased. Consumer welfare increased over time due to improved product quality and improved production technology.","PeriodicalId":48470,"journal":{"name":"Quarterly Journal of Economics","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135153131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Robert Collinson, John Eric Humphries, Nicholas Mader, Davin Reed, Daniel Tannenbaum, Winnie van Dijk
Abstract More than two million U.S. households have an eviction case filed against them each year. Policymakers at the federal, state, and local levels are increasingly pursuing policies to reduce the number of evictions, citing harm to tenants and high public expenditures related to homelessness. We study the consequences of eviction for tenants using newly linked administrative data from two major urban areas: Cook County (which includes Chicago) and New York City. We document that prior to housing court, tenants experience declines in earnings and employment and increases in financial distress and hospital visits. These pre-trends pose a challenge for disentangling correlation and causation. To address this problem, we use an instrumental variables approach based on cases randomly assigned to judges of varying leniency. We find that an eviction order increases homelessness and hospital visits and reduces earnings, durable goods consumption, and access to credit in the first two years. Effects on housing and labor market outcomes are driven by impacts for female and Black tenants. In the longer run, eviction increases indebtedness and reduces credit scores.
{"title":"Eviction and Poverty in American Cities","authors":"Robert Collinson, John Eric Humphries, Nicholas Mader, Davin Reed, Daniel Tannenbaum, Winnie van Dijk","doi":"10.1093/qje/qjad042","DOIUrl":"https://doi.org/10.1093/qje/qjad042","url":null,"abstract":"Abstract More than two million U.S. households have an eviction case filed against them each year. Policymakers at the federal, state, and local levels are increasingly pursuing policies to reduce the number of evictions, citing harm to tenants and high public expenditures related to homelessness. We study the consequences of eviction for tenants using newly linked administrative data from two major urban areas: Cook County (which includes Chicago) and New York City. We document that prior to housing court, tenants experience declines in earnings and employment and increases in financial distress and hospital visits. These pre-trends pose a challenge for disentangling correlation and causation. To address this problem, we use an instrumental variables approach based on cases randomly assigned to judges of varying leniency. We find that an eviction order increases homelessness and hospital visits and reduces earnings, durable goods consumption, and access to credit in the first two years. Effects on housing and labor market outcomes are driven by impacts for female and Black tenants. In the longer run, eviction increases indebtedness and reduces credit scores.","PeriodicalId":48470,"journal":{"name":"Quarterly Journal of Economics","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135203038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract How should we measure changes in consumer welfare given observed data on prices and expenditures? This paper proposes a nonparametric approach that holds under arbitrary preferences that may depend on observable consumer characteristics, e.g., when expenditure shares vary with income. Using total expenditures under a constant set of prices as our money metric for real consumption (welfare), we derive a principled measure of real consumption growth featuring a correction term relative to conventional measures. We show that the correction can be nonparametrically estimated with an algorithm leveraging the observed, cross-sectional relationship between household-level price indices and household characteristics such as income. We demonstrate the accuracy of our algorithm in simulations. Applying our approach to data from the United States, we find that the magnitude of the correction can be large due to the combination of fast growth and lower inflation for income-elastic products. Setting reference prices in 2019, we find that (i) the uncorrected measure underestimates average real consumption per household in 1955 by 11.5%, and (ii) the correction reduces the annual growth rate from 1955 to 2019 by 18 basis points, which is larger than the well-known “expenditure-switching bias” over the same time horizon.
{"title":"Measuring Growth in Consumer Welfare with Income-Dependent Preferences Nonparametric Methods and Estimates for the United States","authors":"Xavier Jaravel, Danial Lashkari","doi":"10.1093/qje/qjad039","DOIUrl":"https://doi.org/10.1093/qje/qjad039","url":null,"abstract":"Abstract How should we measure changes in consumer welfare given observed data on prices and expenditures? This paper proposes a nonparametric approach that holds under arbitrary preferences that may depend on observable consumer characteristics, e.g., when expenditure shares vary with income. Using total expenditures under a constant set of prices as our money metric for real consumption (welfare), we derive a principled measure of real consumption growth featuring a correction term relative to conventional measures. We show that the correction can be nonparametrically estimated with an algorithm leveraging the observed, cross-sectional relationship between household-level price indices and household characteristics such as income. We demonstrate the accuracy of our algorithm in simulations. Applying our approach to data from the United States, we find that the magnitude of the correction can be large due to the combination of fast growth and lower inflation for income-elastic products. Setting reference prices in 2019, we find that (i) the uncorrected measure underestimates average real consumption per household in 1955 by 11.5%, and (ii) the correction reduces the annual growth rate from 1955 to 2019 by 18 basis points, which is larger than the well-known “expenditure-switching bias” over the same time horizon.","PeriodicalId":48470,"journal":{"name":"Quarterly Journal of Economics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136024133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Atkin, Benjamin Faber, Thibault Fally, Marco Gonzalez-Navarro
We propose and implement a new approach that allows us to estimate income-specific changes in household welfare in contexts where well-measured prices are not available for important subsets of consumption. Using rich but widely available expenditure survey microdata, we show that we can recover income-specific equivalent and compensating variations from horizontal shifts in what we term “relative Engel curves”—as long as preferences fall within the broad quasi-separable class (Gorman 1970; 1976). Our approach is flexible enough to allow for nonparametric estimation at each point of the income distribution. We apply the methodology to estimate inflation and welfare changes in rural India between 1987 and 2000. Our estimates reveal that lower rates of inflation for the rich erased the real income convergence found in the existing literature that uses the subset of consumption with well-measured prices to calculate inflation.
{"title":"Measuring Welfare and Inequality with Incomplete Price Information","authors":"David Atkin, Benjamin Faber, Thibault Fally, Marco Gonzalez-Navarro","doi":"10.1093/qje/qjad037","DOIUrl":"https://doi.org/10.1093/qje/qjad037","url":null,"abstract":"We propose and implement a new approach that allows us to estimate income-specific changes in household welfare in contexts where well-measured prices are not available for important subsets of consumption. Using rich but widely available expenditure survey microdata, we show that we can recover income-specific equivalent and compensating variations from horizontal shifts in what we term “relative Engel curves”—as long as preferences fall within the broad quasi-separable class (Gorman 1970; 1976). Our approach is flexible enough to allow for nonparametric estimation at each point of the income distribution. We apply the methodology to estimate inflation and welfare changes in rural India between 1987 and 2000. Our estimates reveal that lower rates of inflation for the rich erased the real income convergence found in the existing literature that uses the subset of consumption with well-measured prices to calculate inflation.","PeriodicalId":48470,"journal":{"name":"Quarterly Journal of Economics","volume":"65 32","pages":""},"PeriodicalIF":13.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David R Baqaee, Ariel Burstein, Yasutaka Koike-Mori
The money metric utility function is an essential tool for calculating welfare-relevant growth and inflation. We show how to recover it from repeated cross-sectional data without making parametric assumptions about preferences. We do this by solving the following recursive problem. Given compensated demand, we construct money metric utility by integration. Given money metric utility, we construct compensated demand by matching households over time whose money metric utility value is the same. We illustrate our method using household consumption survey data from the United Kingdom from 1974 to 2017 and find that real consumption calculated using official aggregate inflation statistics overstates money metric utility in 1974 pounds for the poorest households by around half a percent per year and understates it by around a third of a percentage point per year for the richest households. We extend our method to allow for missing or mismeasured prices, assuming preferences are separable between goods with well-measured prices and the rest. We discuss how our results change if the prices of some service sectors are mismeasured.
{"title":"Measuring Welfare by Matching Households across Time","authors":"David R Baqaee, Ariel Burstein, Yasutaka Koike-Mori","doi":"10.1093/qje/qjad038","DOIUrl":"https://doi.org/10.1093/qje/qjad038","url":null,"abstract":"The money metric utility function is an essential tool for calculating welfare-relevant growth and inflation. We show how to recover it from repeated cross-sectional data without making parametric assumptions about preferences. We do this by solving the following recursive problem. Given compensated demand, we construct money metric utility by integration. Given money metric utility, we construct compensated demand by matching households over time whose money metric utility value is the same. We illustrate our method using household consumption survey data from the United Kingdom from 1974 to 2017 and find that real consumption calculated using official aggregate inflation statistics overstates money metric utility in 1974 pounds for the poorest households by around half a percent per year and understates it by around a third of a percentage point per year for the richest households. We extend our method to allow for missing or mismeasured prices, assuming preferences are separable between goods with well-measured prices and the rest. We discuss how our results change if the prices of some service sectors are mismeasured.","PeriodicalId":48470,"journal":{"name":"Quarterly Journal of Economics","volume":"65 27","pages":""},"PeriodicalIF":13.7,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adrien Auclert, Rodolfo Rigato, Matthew Rognlie, Ludwig Straub
We show that, in a broad class of menu cost models, the first-order dynamics of aggregate inflation in response to arbitrary shocks to aggregate costs are nearly the same as in Calvo models with suitably chosen Calvo adjustment frequencies. We first prove that the canonical menu cost model is first-order equivalent to a mixture of two time-dependent models, which reflect the extensive and intensive margins of price adjustment. We then show numerically that, in any plausible parameterization, this mixture is well approximated by a single Calvo model. This close numerical fit carries over to other standard specifications of menu cost models. Thus, for shocks that are not too large, the Phillips curve for a menu cost model looks like the New Keynesian Phillips curve, but with a higher slope.
{"title":"New Pricing Models, Same Old Phillips Curves?","authors":"Adrien Auclert, Rodolfo Rigato, Matthew Rognlie, Ludwig Straub","doi":"10.1093/qje/qjad041","DOIUrl":"https://doi.org/10.1093/qje/qjad041","url":null,"abstract":"We show that, in a broad class of menu cost models, the first-order dynamics of aggregate inflation in response to arbitrary shocks to aggregate costs are nearly the same as in Calvo models with suitably chosen Calvo adjustment frequencies. We first prove that the canonical menu cost model is first-order equivalent to a mixture of two time-dependent models, which reflect the extensive and intensive margins of price adjustment. We then show numerically that, in any plausible parameterization, this mixture is well approximated by a single Calvo model. This close numerical fit carries over to other standard specifications of menu cost models. Thus, for shocks that are not too large, the Phillips curve for a menu cost model looks like the New Keynesian Phillips curve, but with a higher slope.","PeriodicalId":48470,"journal":{"name":"Quarterly Journal of Economics","volume":"30 1","pages":""},"PeriodicalIF":13.7,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Debates about the taxation of business owners often center on the distributional effects of these taxes, particularly the degree to which they affect workers. Drawing on a new linked owner-firm-worker data set created from U.S. administrative tax records, I analyze how an increase in the top marginal tax rate faced by business owners affected the earnings of their employees. I use panel difference-in-differences methods to compare the earnings of workers in similar firms but whose owners were differentially exposed to the tax increase. I estimate that 11–18 cents per dollar of new business income tax liability was passed through to employee earnings. I find no change in employment in response to the tax increase. The responses were generally associated with lower earnings growth, not changes in workforce composition. The burden was not borne equally by all workers. Essentially all of the workers’ share of the burden was borne by those in the top 30% of the earnings distribution, highlighting that the ultimate distributional effects of the policy depend not only on the share of the burden borne by workers but on the shares borne by different types of workers. Furthermore, since the owners bore the majority of the burden, the policy resulted in a decrease in after-tax earnings inequality between top-bracket owners and lower-bracket workers. I discuss the implications of the findings for the mediating labor market mechanisms and for welfare analyses of income taxation using a marginal value of public funds framework.
{"title":"Does Taxing Business Owners Affect Employees? Evidence from a Change in the Top Marginal Tax Rate","authors":"Max Risch","doi":"10.1093/qje/qjad040","DOIUrl":"https://doi.org/10.1093/qje/qjad040","url":null,"abstract":"Abstract Debates about the taxation of business owners often center on the distributional effects of these taxes, particularly the degree to which they affect workers. Drawing on a new linked owner-firm-worker data set created from U.S. administrative tax records, I analyze how an increase in the top marginal tax rate faced by business owners affected the earnings of their employees. I use panel difference-in-differences methods to compare the earnings of workers in similar firms but whose owners were differentially exposed to the tax increase. I estimate that 11–18 cents per dollar of new business income tax liability was passed through to employee earnings. I find no change in employment in response to the tax increase. The responses were generally associated with lower earnings growth, not changes in workforce composition. The burden was not borne equally by all workers. Essentially all of the workers’ share of the burden was borne by those in the top 30% of the earnings distribution, highlighting that the ultimate distributional effects of the policy depend not only on the share of the burden borne by workers but on the shares borne by different types of workers. Furthermore, since the owners bore the majority of the burden, the policy resulted in a decrease in after-tax earnings inequality between top-bracket owners and lower-bracket workers. I discuss the implications of the findings for the mediating labor market mechanisms and for welfare analyses of income taxation using a marginal value of public funds framework.","PeriodicalId":48470,"journal":{"name":"Quarterly Journal of Economics","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135254283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marcella Alsan, Maya Durvasula, Harsh Gupta, Joshua Schwartzstein, Heidi Williams
This article examines the consequences and causes of low enrollment of Black patients in clinical trials. We develop a simple model of similarity-based extrapolation that predicts that evidence is more relevant for decision-making by physicians and patients when it is more representative of the group that is being treated. This generates the key result that the perceived benefit of a medicine for a group depends not only on the average benefit from a trial, but also on the share of patients from that group who were enrolled in the trial. In survey experiments, we find that physicians who care for Black patients are more willing to prescribe drugs tested in representative samples, an effect substantial enough to close observed gaps in the prescribing rates of new medicines. Black patients update more on drug efficacy when the sample that the drug is tested on is more representative, reducing Black-White patient gaps in beliefs about whether the drug will work as described. Despite these benefits of representative data, our framework and evidence suggest that those who have benefited more from past medical breakthroughs are less costly to enroll in the present, leading to persistence in who is represented in the evidence base.
{"title":"Representation and Extrapolation: Evidence from Clinical Trials","authors":"Marcella Alsan, Maya Durvasula, Harsh Gupta, Joshua Schwartzstein, Heidi Williams","doi":"10.1093/qje/qjad036","DOIUrl":"https://doi.org/10.1093/qje/qjad036","url":null,"abstract":"This article examines the consequences and causes of low enrollment of Black patients in clinical trials. We develop a simple model of similarity-based extrapolation that predicts that evidence is more relevant for decision-making by physicians and patients when it is more representative of the group that is being treated. This generates the key result that the perceived benefit of a medicine for a group depends not only on the average benefit from a trial, but also on the share of patients from that group who were enrolled in the trial. In survey experiments, we find that physicians who care for Black patients are more willing to prescribe drugs tested in representative samples, an effect substantial enough to close observed gaps in the prescribing rates of new medicines. Black patients update more on drug efficacy when the sample that the drug is tested on is more representative, reducing Black-White patient gaps in beliefs about whether the drug will work as described. Despite these benefits of representative data, our framework and evidence suggest that those who have benefited more from past medical breakthroughs are less costly to enroll in the present, leading to persistence in who is represented in the evidence base.","PeriodicalId":48470,"journal":{"name":"Quarterly Journal of Economics","volume":"29 6","pages":""},"PeriodicalIF":13.7,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Books shape how children learn about society and norms, in part through representation of different characters. We use computational tools to characterize representation in children’s books widely read in homes, classrooms, and libraries over the past century and describe economic forces that may contribute to these patterns. We introduce new artificial intelligence methods for systematically converting images into data. We apply these tools, alongside text analysis methods, to measure skin color, race, gender, and age in the content of these books, documenting what has changed and what has endured over time. We find underrepresentation of Black and Latinx people in the most influential books, relative to their population shares, though representation of Black individuals increases over time. Females are also increasingly present but appear less often in text than in images, suggesting greater symbolic inclusion in pictures than substantive inclusion in stories. Characters in these influential books have lighter average skin color than in other books, even after conditioning on race, and children are depicted with lighter skin color than adults on average. We present empirical analysis of related economic behavior to better understand the representation we find in these books. On the demand side, we show that people consume books that center their own identities and that the types of children’s books purchased correlate with local political beliefs. On the supply side, we document higher prices for books that center nondominant social identities and fewer copies of these books in libraries that serve predominantly White communities.
{"title":"What We Teach About Race and Gender: Representation in Images and Text of Children’s Books","authors":"Anjali Adukia, Alex Eble, Emileigh Harrison, Hakizumwami Birali Runesha, Teodora Szasz","doi":"10.1093/qje/qjad028","DOIUrl":"https://doi.org/10.1093/qje/qjad028","url":null,"abstract":"Books shape how children learn about society and norms, in part through representation of different characters. We use computational tools to characterize representation in children’s books widely read in homes, classrooms, and libraries over the past century and describe economic forces that may contribute to these patterns. We introduce new artificial intelligence methods for systematically converting images into data. We apply these tools, alongside text analysis methods, to measure skin color, race, gender, and age in the content of these books, documenting what has changed and what has endured over time. We find underrepresentation of Black and Latinx people in the most influential books, relative to their population shares, though representation of Black individuals increases over time. Females are also increasingly present but appear less often in text than in images, suggesting greater symbolic inclusion in pictures than substantive inclusion in stories. Characters in these influential books have lighter average skin color than in other books, even after conditioning on race, and children are depicted with lighter skin color than adults on average. We present empirical analysis of related economic behavior to better understand the representation we find in these books. On the demand side, we show that people consume books that center their own identities and that the types of children’s books purchased correlate with local political beliefs. On the supply side, we document higher prices for books that center nondominant social identities and fewer copies of these books in libraries that serve predominantly White communities.","PeriodicalId":48470,"journal":{"name":"Quarterly Journal of Economics","volume":"29 4","pages":""},"PeriodicalIF":13.7,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abe Dunn, Joshua D Gottlieb, Adam Hale Shapiro, Daniel J Sonnenstuhl, Pietro Tebaldi
Abstract Who bears the consequences of administrative problems in health care? We use data on repeated interactions between a large sample of U.S. physicians and many different insurers to document the complexity of health care billing, and estimate its economic costs for doctors and consequences for patients. Observing the back-and-forth sequences of claim denials and resubmissions for past visits, we can estimate physicians’ costs of haggling with insurers to collect payments. Combining these costs with the revenue never collected, we estimate that physicians lose 18% of Medicaid revenue to billing problems, compared with 4.7% for Medicare and 2.4% for commercial insurers. Identifying off of physician movers and practices that span state boundaries, we find that physicians respond to billing problems by refusing to accept Medicaid patients in states with more severe billing hurdles. These hurdles are quantitatively just as important as payment rates for explaining variation in physicians’ willingness to treat Medicaid patients. We conclude that administrative frictions have first-order costs for doctors, patients, and equality of access to health care. We quantify the potential economic gains—in terms of reduced public spending or increased access to physicians—if these frictions could be reduced and find them to be sizable.
{"title":"A Denial a Day Keeps the Doctor Away","authors":"Abe Dunn, Joshua D Gottlieb, Adam Hale Shapiro, Daniel J Sonnenstuhl, Pietro Tebaldi","doi":"10.1093/qje/qjad035","DOIUrl":"https://doi.org/10.1093/qje/qjad035","url":null,"abstract":"Abstract Who bears the consequences of administrative problems in health care? We use data on repeated interactions between a large sample of U.S. physicians and many different insurers to document the complexity of health care billing, and estimate its economic costs for doctors and consequences for patients. Observing the back-and-forth sequences of claim denials and resubmissions for past visits, we can estimate physicians’ costs of haggling with insurers to collect payments. Combining these costs with the revenue never collected, we estimate that physicians lose 18% of Medicaid revenue to billing problems, compared with 4.7% for Medicare and 2.4% for commercial insurers. Identifying off of physician movers and practices that span state boundaries, we find that physicians respond to billing problems by refusing to accept Medicaid patients in states with more severe billing hurdles. These hurdles are quantitatively just as important as payment rates for explaining variation in physicians’ willingness to treat Medicaid patients. We conclude that administrative frictions have first-order costs for doctors, patients, and equality of access to health care. We quantify the potential economic gains—in terms of reduced public spending or increased access to physicians—if these frictions could be reduced and find them to be sizable.","PeriodicalId":48470,"journal":{"name":"Quarterly Journal of Economics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135210756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：