Implementing intersection bounds in Stata

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract. We present the clrbound, clr2bound, clr3bound, and clrtest commands for estimation and inference on intersection bounds as developed by Chernozhukov et al. (2013). The intersection bounds framework encompasses situations where a population parameter of interest is partially identified by a collection of consistently estimable upper and lower bounds. The identified set for the parameter is the intersection of regions defined by this collection of bounds. More generally, the methodology can be applied to settings where an estimable function of a vector-valued parameter is bounded from above and below, as is the case when the identified set is characterized by conditional moment inequalities. Terms of use: Documents inThe commands clrbound, clr2bound, and clr3bound provide bound estimates that can be used directly for estimation or to construct asymptotically valid confidence sets. clrtest performs an intersection bound test of the hypothesis that a collection of lower intersection bounds is no greater than zero. The command clrbound provides bound estimates for one-sided lower or upper intersection bounds on a parameter, while clr2bound and clr3bound provide two-sided bound estimates based on both lower and upper intersection bounds. clr2bound uses Bonferroni's inequality to construct two-sided bounds that can be used to perform asymptotically valid inference on the identified set or the parameter of interest, whereas clr3bound provides a generally tighter confidence interval for the parameter by inverting the hypothesis test performed by clrtest. More broadly, inversion of this test can also be used to construct confidence sets based on conditional moment inequalities as described in Chernozhukov et al. (2013). The commands include parametric, series, and local linear estimation procedures, and can be installed from within STATA by typing "ssc install clrbound".

Econometrics with Partial Identification

“…The code computes the confidence intervals proposed by Imbens and Manski (2004). In the more general context of inference for a one-dimensional parameter defined by intersection bounds, as for example the one in (2.15), Chernozhukov, Kim, Lee, and Rosen (2015) and Andrews, Kim, and Shi (2017) provide portable STATA code implementing, respectively, methods to test hypotheses and build confidence intervals in Chernozhukov, Lee, and Rosen (2013) and Andrews and Shi (2013). Beresteanu, Molinari, and Morris (2010) provide portable STATA code implementing 's method for estimation and inference for best linear prediction with interval outcome data as in Identification Problem 2.4.…”

Complementarity and Identification

“…This, combined with the fact that commercial zoning is unlikely to lower the likelihood of commercial development, suggests that SMTR is an appropriate assumption in this context. Chernozhukov et al (2015) Stata implementation of the inference methods of Chernozhukov et al (2013).…”

Dual regression

“…The construction of the critical valueĉ n (α, θ, v) is delicate and a clear exposition requires introducing significantly more notation, so we refer the reader to Chernozhukov et al (2013d). Notably, the intersection bounds approach can be easily implemented in Stata for certain problems using the package developed by Chernozhukov et al (2013c).…”