{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T22:48:49Z","timestamp":1769813329657,"version":"3.49.0"},"reference-count":19,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2006,11,7]],"date-time":"2006-11-07T00:00:00Z","timestamp":1162857600000},"content-version":"vor","delay-in-days":5424,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J of Applied Econometrics"],"published-print":{"date-parts":[[1992,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>If a researcher has mined the data (i.e. selected an empirical model based on a series of trial estimates), inferences based on the final set of results are in general incorrect. This note treats the entire data mining process as an estimator and shows how a bootstrapping technique may improve the quality of inference. The method is applied to an empirical example on the deterrent effects of capital punishment.<\/jats:p>","DOI":"10.1002\/jae.3950070109","type":"journal-article","created":{"date-parts":[[2007,7,12]],"date-time":"2007-07-12T16:50:36Z","timestamp":1184259036000},"page":"93-99","source":"Crossref","is-referenced-by-count":26,"title":["Bootstrapping the process of model selection: AN econometric example"],"prefix":"10.1002","volume":"7","author":[{"given":"Michael R.","family":"Veall","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2006,11,7]]},"reference":[{"key":"e_1_2_1_2_1","unstructured":"Brownstone D. 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