Showing 1 - 10 of 3,065
Since identification, instrumental variables and variables exclusion, core concepts in econometrics, are entwined …, several questions arise: How is identification related to the existence of IVs? How are identification criteria related to …
Persistent link: https://www.econbiz.de/10011779245
There is hope for the generalized method of moments (GMM). Lanne and Saikkonen (2011) show that the GMM estimator is inconsistent, when the instruments are lags of noncausal variables. This paper argues that this inconsistency depends on distributional assumptions, that do not always hold. In...
Persistent link: https://www.econbiz.de/10013117256
Persistent link: https://www.econbiz.de/10010326499
+r, even though there is an issue of local non-identification that causes non-elliptical shapes of the posterior. This stresses …
Persistent link: https://www.econbiz.de/10010326354
Persistent link: https://www.econbiz.de/10010191002
Persistent link: https://www.econbiz.de/10009722969
variables models. Our test is valid uniformly over a large class of distributions allowing for identification failure and …
Persistent link: https://www.econbiz.de/10013020836
This paper investigates four topics. (1) It examines the different roles played by the propensity score (probability of selection) in matching, instrumental variable and control functions methods. (2) It contrasts the roles of exclusion restrictions in matching and selection models. (3) It...
Persistent link: https://www.econbiz.de/10010274216
The Ramsey regression equation specification error test (RESET) furnishes a diagnostic for omitted variables in a linear regression model specification (i.e., the null hypothesis is no omitted variables). Integer powers of fitted values from a regression analysis are introduced as additional...
Persistent link: https://www.econbiz.de/10011506413
identification results and to fast, easy to implement, and tuning-free estimators that do not require the availability of high …
Persistent link: https://www.econbiz.de/10012053040