{"title":"robustpf: A command for robust estimation of production functions","authors":"Yingyao Hu, Guofang Huang, Yuya Sasaki","doi":"10.1177/1536867X231161977","DOIUrl":null,"url":null,"abstract":"We introduce a new command, robustpf, to estimate parameters of Cobb–Douglas production functions. The command is robust against two potential problems. First, it is robust against optimization errors in firms’ input choice, unobserved idiosyncratic cost shocks, and measurement errors in proxy variables. In particular, the command relaxes the conventional assumption of scalar unobservables. Second, it is also robust against the functional dependence problem of static input choice, which is known today as a cause of identification failure. The main method is proposed by Hu, Huang, and Sasaki (2020, Journal of Econometrics 215: 375–398).","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"23 1","pages":"86 - 96"},"PeriodicalIF":3.2000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stata Journal","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1177/1536867X231161977","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
We introduce a new command, robustpf, to estimate parameters of Cobb–Douglas production functions. The command is robust against two potential problems. First, it is robust against optimization errors in firms’ input choice, unobserved idiosyncratic cost shocks, and measurement errors in proxy variables. In particular, the command relaxes the conventional assumption of scalar unobservables. Second, it is also robust against the functional dependence problem of static input choice, which is known today as a cause of identification failure. The main method is proposed by Hu, Huang, and Sasaki (2020, Journal of Econometrics 215: 375–398).
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The Stata Journal is a quarterly publication containing articles about statistics, data analysis, teaching methods, and effective use of Stata''s language. The Stata Journal publishes reviewed papers together with shorter notes and comments, regular columns, book reviews, and other material of interest to researchers applying statistics in a variety of disciplines.
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