It is argued that the general formulation of point-optimal tests, as summarized in King (1988), (i) makes use of a benchmark which is excessively stringent, (ii) fails to integrate the method with traditional methods of testing, (iii) involves using data to form a specific null hypothesis, (iv) offers no guidance as to proper procedures in the event the null is rejected, (v) eschews the use of Bayesian methods while demanding the use of prior information, and (vi) yields tests with unknown power in the presence of specification error. For these and other reasons, point-optimal testing cannot yet be wholeheartedly recommended as part of "the econometrican's repertoire"
Different criteria of optimality are used in different subcultures of statistical surveillance. One ...
Statistically inclined experimental scientists may be interested in chapters 1 and 9, and in parts o...
This paper presents optimal tests for parameter instability in the generalized method of moments (GM...
This paper puts the case for the inclusion of point optimal tests in the econometrician's repertoire...
In the absence of uniformly most powerful (UMP) tests or uniformly most powerful invariant (UMPI) te...
King's Point Optimal (PO) test of a simple null hypothesis is useful in a number of ways, for e...
In the context of the linear regression model, Shively (1988) has constructed a point optimal test f...
This paper reviews important concepts and methods that are useful for hypothesis testing. First, we ...
In this paper, we use the generalized Neyman-Pearson lemma to introduce a new approximate point opti...
© 2012 Dr. Muhammad Saqib ManzoorIn this dissertation, we revisit the method of Elliott and Stock (2...
This paper is concerned with the general problem of testing one form of covariance structure against...
Via the leading unit-root case, the problem of testing on a lagged dependent variable is characteriz...
The objective of this paper is to derive a point optimal test for the null hypothesis of near integr...
We know very little about the performance of point optimal (PO) and approximate point optimal (APO) ...
Testing a point (sharp) null hypothesis is arguably the most widely used statistical inferential pro...
Different criteria of optimality are used in different subcultures of statistical surveillance. One ...
Statistically inclined experimental scientists may be interested in chapters 1 and 9, and in parts o...
This paper presents optimal tests for parameter instability in the generalized method of moments (GM...
This paper puts the case for the inclusion of point optimal tests in the econometrician's repertoire...
In the absence of uniformly most powerful (UMP) tests or uniformly most powerful invariant (UMPI) te...
King's Point Optimal (PO) test of a simple null hypothesis is useful in a number of ways, for e...
In the context of the linear regression model, Shively (1988) has constructed a point optimal test f...
This paper reviews important concepts and methods that are useful for hypothesis testing. First, we ...
In this paper, we use the generalized Neyman-Pearson lemma to introduce a new approximate point opti...
© 2012 Dr. Muhammad Saqib ManzoorIn this dissertation, we revisit the method of Elliott and Stock (2...
This paper is concerned with the general problem of testing one form of covariance structure against...
Via the leading unit-root case, the problem of testing on a lagged dependent variable is characteriz...
The objective of this paper is to derive a point optimal test for the null hypothesis of near integr...
We know very little about the performance of point optimal (PO) and approximate point optimal (APO) ...
Testing a point (sharp) null hypothesis is arguably the most widely used statistical inferential pro...
Different criteria of optimality are used in different subcultures of statistical surveillance. One ...
Statistically inclined experimental scientists may be interested in chapters 1 and 9, and in parts o...
This paper presents optimal tests for parameter instability in the generalized method of moments (GM...