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CROSS‐SECTION ESTIMATES OF LIQUID ASSET DEMAND BY MANUFACTURING CORPORATIONS
On the Exact Small Sample Distribution of the Instrumental Variable Estimator
The purpose of this note is to point out that the bimodality is a consequence of the special case considered by N-S. The exact finite sample distribution of the IV estimator has been derived in the economic literature earlier, but its tabulation or plotting involves some assumptions about the nuisance parameters. In this note we plot the densities of the exact finite sample distribution of the IV estimator for several parameter values and show that the bimodality feature noted by N-S is a consequence of a singular covariance matrix and not of a poor instrument.
Asymptotic Covariance Matrices of Two-Stage Probit and Two-Stage Tobit Methods for Simultaneous Equations Models with Selectivity
Lung-Fei Lee, G. S. Maddala, R. P. Trost, Asymptotic Covariance Matrices of Two-Stage Probit and Two-Stage Tobit Methods for Simultaneous Equations Models with Selectivity, Econometrica, Vol. 48, No. 2 (Mar., 1980), pp. 491-503
Bootstrap Variance Estimation of Nonlinear Functions of Parameters: An Application to Long-Run Elasticities of Energy Demand
In many practical applications, one is interested in obtaining confidence intervals for nonlinear functions of the parameters. This paper considers the following different methods: Fieller's method, Taylor's series expansion, and bootstrap methods. Compared to some of the earlier results in the empirical studies that are against the application of bootstrap, our results suggest a different conclusion in favor of the bootstrap methods.
Testing the Rationality of Survey Data Using the Weighted Double-Bootstrapped Method of Moments
Jinook Jeong, G. S. Maddala, Testing the Rationality of Survey Data Using the Weighted Double-Bootstrapped Method of Moments, The Review of Economics and Statistics, Vol. 78, No. 2 (May, 1996), pp. 296-302
A Function for Size Distribution of Incomes: Reply
Tests for Serial Correlation in Regression Models with Lagged Dependent Variables and Serially Correlated Errors
The paper compares the power of two tests for serial correlation in regression models with lagged dependent variables, recently suggested by Durbin, with that of the likelihood ratio test by means of two sets of Monte-Carlo experiments-one in which the exogenous series is taken to be the quarterly GNP series for the USA and the other in which the exogenous series is generated by a known autoregression.
Estimation of Returns to Scale and the Elasticity of Substitution
This paper concerns itself with the following problem: Suppose the true production function is of the CES type with constant returns to scale. If we fit an unrestricted Cobb-Douglas production function instead, what is the nature of the bias in the estimate of the returns to scale parameter?