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Inference And Specification Testing In Threshold Regression With Endogeneity, Ping Yu, Qin Liao, Peter C.B. Phillips
Inference And Specification Testing In Threshold Regression With Endogeneity, Ping Yu, Qin Liao, Peter C.B. Phillips
Cowles Foundation Discussion Papers
We propose three new methods of inference for the threshold point in endogenous threshold regression and two specification tests designed to assess the presence of endogeneity and threshold effects without necessarily relying on instrumentation of the covariates. The first inferential method is a parametric two-stage least squares method and is suitable when instruments are available. The second and third methods are based on smoothing the objective function of the integrated difference kernel estimator in different ways and these methods do not require instrumentation. All three methods are applicable irrespective of endogeneity of the threshold variable. The two specification tests are …
'Follow The Data' — What Data Says About Real-World Behavior In Commons Problems, Caleb M. Koch, Heinrich H. Nax
'Follow The Data' — What Data Says About Real-World Behavior In Commons Problems, Caleb M. Koch, Heinrich H. Nax
Cowles Foundation Discussion Papers
We test the game-theoretic foundations of common-pool resources using an individual-level dataset of groundwater usage that accounts for 3% of US irrigated agriculture. Using necessary and sufficient revealed preference tests for dynamic games, we find: (i) a rejection of the standard game-theoretic arguments based on strategic substitutes, and instead (ii) support for models building on reciprocity-like behavior and strategic complements. By estimating strategic interactions directly, we find that reciprocity-like interactions drive behavior more than market and climate trends. Taken together, we take a step toward developing more realistic models to understand groundwater usage, and related issues pertaining to tragedy of …
Inference In Moment Inequality Models That Is Robust To Spurious Precision Under Model Misspecification, Donald W.K. Andrews, Soonwoo Kwon
Inference In Moment Inequality Models That Is Robust To Spurious Precision Under Model Misspecification, Donald W.K. Andrews, Soonwoo Kwon
Cowles Foundation Discussion Papers
Standard tests and confidence sets in the moment inequality literature are not robust to model misspecification in the sense that they exhibit spurious precision when the identified set is empty. This paper introduces tests and confidence sets that provide correct asymptotic inference for a pseudo-true parameter in such scenarios, and hence, do not suffer from spurious precision.
Inference In Moment Inequality Models That Is Robust To Spurious Precision Under Model Misspecification, Donald W.K. Andrews, Soonwoo Kwon
Inference In Moment Inequality Models That Is Robust To Spurious Precision Under Model Misspecification, Donald W.K. Andrews, Soonwoo Kwon
Cowles Foundation Discussion Papers
Standard tests and confidence sets in the moment inequality literature are not robust to model misspecification in the sense that they exhibit spurious precision when the identified set is empty. This paper introduces tests and confidence sets that provide correct asymptotic inference for a pseudo-true parameter in such scenarios, and hence, do not suffer from spurious precision.
Misspecified Moment Inequality Models: Inference And Diagnostics, Donald W.K. Andrews, Soonwoo Kwon
Misspecified Moment Inequality Models: Inference And Diagnostics, Donald W.K. Andrews, Soonwoo Kwon
Cowles Foundation Discussion Papers
This paper is concerned with possible model misspecification in moment inequality models. Two issues are addressed. First, standard tests and confidence sets for the true parameter in the moment inequality literature are not robust to model misspecification in the sense that they exhibit spurious precision when the identified set is empty. This paper introduces tests and confidence sets that provide correct asymptotic inference for a pseudo-true parameter in such scenarios, and hence, do not suffer from spurious precision. Second, specification tests have relatively low power against a range of misspecified models. Thus, failure to reject the null of correct specification …