In order to discuss nonlinear, it is necessary to know linear regressive as a priori. Without simple regression as the starting point, it would be difficult to understand nonlinear regression. In words, in order to understand the curve and the behavior of a curve, it is necessary to known a...

The problem considered is the estimation of "k" coefficients of interest in a linear regression model when the (k+1)st coefficient is of no interest. It is shown that this problem is equivalent to the problem of estimating the unknown mean of a univariate normal distribution with variance one...

This paper is primarily concerned with extending the results of Stein to spherically symmetric distributions. Specifically, when X ∼f(||X - θ||2), we investigate conditions under which estimators of the form X ag(X) dominate X for loss functions ||δ- θ||2 and loss functions which are...

The ordinary least squares (OLS) estimator for spatial autoregressions may be consistent as pointed out by Lee (2002), provided that each spatial unit is influenced aggregately by a significant portion of the total units. This paper presents a unified asymptotic distribution result of the...

As I document using evidence from a journal data repository that I manage, the datasets used in empirical work are getting larger. When we use very large datasets, it can be dangerous to rely on standard methods for statistical inference. In addition, we need to worry about computational issues....

In this paper, several identities concerning expectation, variance, covariance, cumulative distribution functions, the coefficient of variation, and the Lorenz curve are obtained and they are used in establishing theoretical results. Furthermore, a graphical representation of the variance is...

In this paper we consider the interval availability distribution of a two state single unit. WE fit the interval availability distribution directly to a Beta distribution, such that the probability of nil and a hundred percent availability is correct as well as the espectation and the variance

The problem of multicollinearity in the assessments of coefficients is well established. However, it is rarely researched in the estimations of macroeconomic variables and economic performance of developing countries. Predicatively, it has impacts on the estimations of coefficients that should...

We discuss the use of calibration techniques in economic models. Calibration contrasts with estimation in relying on deterministic calculation of model parameter values consistent with data, rather than econometric estimation. The reasons why calibrators use these methods, as well as the main...

This paper studies the properties of generalised empirical likelihood (GEL) methods for the estimation of and inference on partially identified parameters in models specified by unconditional moment inequality constraints. The central result is, as in moment equality condition models, a large...