On the Stock-Yogo Tables

A standard test for weak instruments compares the first-stage F-statistic to a table of critical values obtained by Stock and Yogo (2005) using simulations. We derive a closed-form solution for the expectation from which these critical values are derived, as well as present some second-order asymptotic approximations that may be of value in the presence of multiple endogenous regressors. Inspection of this new result provides insights not available from simulation, and will allow software implementations to be generalised and improved. Finally, we explore the calculation of p-values for the first-stage F-statistic weak instruments test

Distributions You Can Count On …But What’s the Point?

The Poisson regression model remains an important tool in the econometric analysis of count data. In a pioneering contribution to the econometric analysis of such models, Lung-Fei Lee presented a specification test for a Poisson model against a broad class of discrete distributions sometimes called the Katz family. Two members of this alternative class are the binomial and negative binomial distributions, which are commonly used with count data to allow for under- and over-dispersion, respectively. In this paper we explore the structure of other distributions within the class and their suitability as alternatives to the Poisson model. Potential difficulties with the Katz likelihood leads us to investigate a class of point optimal tests of the Poisson assumption against the alternative of over-dispersion in both the regression and intercept only cases. In a simulation study, we compare score tests of ‘Poisson-ness’ with various point optimal tests, based on the Katz family, and conclude that it is possible to choose a point optimal test which is better in the intercept only case, although the nuisance parameters arising in the regression case are problematic. One possible cause is poor choice of the point at which to optimize. Consequently, we explore the use of Hellinger distance to aid this choice. Ultimately we conclude that score tests remain the most practical approach to testing for over-dispersion in this context.</jats:p

A note on Amemiya's form of the weighted least squares estimator

Includes bibliographical references (p. 13)

Some Exact Results for Estimators of the Coefficients on the Exogenous Variables in a Single Equation

This paper is devoted to a detailed examination of the exact sampling properties of the instrumental variables (IV) estimator of the vector of coefficients on the exogenous variables in a single structural equation. The first two moments of a linear combination of the elements of this estimator and the joint distribution of these elements are considered. Estimable bounds for the first moment that can readily be incorporated into any IV estimation package are provided. The results obtained are in terms of the same special functions as those that characterize other results for this model, allowing a unified treatment of the model.

Instrumental Variables Estimation in Misspecified Single Equations

This paper examines the exact sampling behavior of a family of instrumental variables estimators of the coefficients in a single structural equation when the model has been misspecified by the incorrect inclusion or exclusion of variables. It is found that such specification errors can have implications for the structure of the exact results obtained. A brief numerical examination of the analytical results is also provided.

The Impact of Cannabis Use on Health

cannabis, cigarettes, productivity, self-assessed health, I1,

Temporal integration and compression near absolute threshold in normal and impaired ears.

The decrease in absolute threshold with increasing stimulus duration (often referred to as “temporal integration”) is greater for listeners with normal hearing than for listeners with sensorineural hearing loss. It has been suggested that the difference is related to reduced basilar-membrane (BM) compression in the impaired group. The present experiment tested this hypothesis by comparing temporal integration and BM compression in normal and impaired ears at low levels. Absolute thresholds were measured for 4, 24, and 44 ms pure-tone signals, with frequencies (fs) of 2 and 4 kHz. The difference between the absolute thresholds for the 4 and 24 ms signals was used as a measure of temporal integration. Compression near threshold was estimated by measuring the level of a 100 ms off-frequency (0.45fs) pure-tone forward masker required to mask a 44 ms pure-tone signal presented at sensation levels of 5 and 10 dB. There was a significant negative correlation between amount of temporal integration and absolute threshold. However, there was no correlation between absolute threshold and compression at low levels; both normal and impaired ears showed a nearly linear response. The results suggest that the differences in integration between normal and impaired ears cannot be explained by differences in BM compression

Monte carlo evidence on the robustness of conditional moment tests in tobit and probit models

This paper numerically examines the size robustness of various conditional moment tests in misspecified tobit and probit models. The misspecifications considered include the incorrect exclusion of regressors, ignored heteroskedasticity and false distributional assumptions. An important feature of the experimental design is that it is based on an existing empirical study and is more realistic than many simulation studies. The tests are seen to have mixed performance depending on both the original null hypothesis being tested and type of misspecification encountered.and Phrases, probit models, tobit models, conditional moment tests, omitted variables, heteroskedasticity, non-normality,