BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH PRODID:-//Telerik Inc.//Sitefinity CMS 15.1//EN BEGIN:VTIMEZONE TZID:Eastern Standard Time BEGIN:STANDARD DTSTART:20251102T020000 RRULE:FREQ=YEARLY;BYDAY=1SU;BYHOUR=2;BYMINUTE=0;BYMONTH=11 TZNAME:Eastern Standard Time TZOFFSETFROM:-0400 TZOFFSETTO:-0500 END:STANDARD BEGIN:DAYLIGHT DTSTART:20250301T020000 RRULE:FREQ=YEARLY;BYDAY=2SU;BYHOUR=2;BYMINUTE=0;BYMONTH=3 TZNAME:Eastern Daylight Time TZOFFSETFROM:-0500 TZOFFSETTO:-0400 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT DESCRIPTION:Bo E. Honoré is a Professor of Economics at Princeton Universit y. Professor \;Honoré will discuss his study\, "“Selection Without Exc lusion” (co-authored with \;Luojia Hu)Abstract: \;It is well under stood that classical sample selection models are not semiparametrically id entified without exclusion restrictions. Lee (2009) developed bounds for t he parameters in a model that nests the semiparametric sample selection mo del. These bounds can be wide. In this paper\, we investigate bounds that impose the full structure of a sample selection model with errors that are independent of the explanatory variables but have unknown distribution. W e find that the additional structure in the classical sample selection mod el can significantly reduce the identified set for the parameters of inter est. Specifically\, we show that the identified set for the parameter vect or of interest is a one-dimensional line-segment in the parameter space\, and we demonstrate that this line segment can be short in principle as wel l as in practice. We also provide non-sharp bounds. We expect these to be easier to compute and likely to be associated with lower statistical uncer tainty than the sharp bounds. Throughout the paper\, we illustrate our app roach by estimating a standard sample selection model for wages.For more i nformation\, please contact Matt O'Keefe by email at mkokeefe@maxwell.syr. edu \;Sponsored by the Economics Department DTEND:20180330T173000Z DTSTAMP:20260512T222133Z DTSTART:20180330T153000Z LOCATION: SEQUENCE:0 SUMMARY:Economics presents: Bo E. Honoré UID:RFCALITEM639142068934540753 X-ALT-DESC;FMTTYPE=text/html:

Bo E. Honoré is a Professor of Economics at Prince ton University. Professor \;Honoré will discuss his study\, "“Selectio n Without Exclusion” (co-authored with \;Luojia Hu)

Abstract:  \;It is well understood that classical sample selection models ar e not semiparametrically identified without exclusion restrictions. Lee (2 009) developed bounds for the parameters in a model that nests the semipar ametric sample selection model. These bounds can be wide. In this paper\, we investigate bounds that impose the full structure of a sample selection model with errors that are independent of the explanatory variables but h ave unknown distribution. We find that the additional structure in the cla ssical sample selection model can significantly reduce the identified set for the parameters of interest. Specifically\, we show that the identified set for the parameter vector of interest is a one-dimensional line-segmen t in the parameter space\, and we demonstrate that this line segment can b e short in principle as well as in practice. We also provide non-sharp bou nds. We expect these to be easier to compute and likely to be associated w ith lower statistical uncertainty than the sharp bounds. Throughout the pa per\, we illustrate our approach by estimating a standard sample selection model for wages.

For more information\, please contact Matt O'Keef e by email at mkokeefe@maxwell.syr.edu \;
Sponsored by the Economics Department

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