We study the asymptotic behavior of the least squares estimators of the unknown parameters of general pth-order bifurcating autoregressive processes. Under very weak assumptions on the driven noise of the process, namely conditional pair-wise independence and suitable moment conditions, we establish the almost sure convergence of our estimators together with the quadratic strong law and the cen...

The applications of the Rothbarth model of inferring child gender discrimination from the variations in parental living standard have consistently failed to uncover evidence for bias from surveys in countries with some of the world's worst welfare outcomes for girls. This paper demonstrates the importance of the remedies required for an effective implementation of that model with applications t...

The widely used method of least squares for state estimation is revisited. The commonly used least squares philosophy is based on the L 2 Hölder norm. The L 1 and L 8 norms are considered for applications in power engineering. The effects of outliers in measurements and multicolinearity on state estimation are studied. An application in parameter estimation for synchronous generators is given a...

A three-staged least squares translog cost function is estimated for 13 heavy-rail and nine light-rail United States urban mass transit systems for the period 1985-1991. Firm output is taken to be endogenous. Large economies of density are found in operating costs. These economies become even more substantial when the cost of way and structure maintenance and capital costs are incorporated. How...

The effects of improving covariate measurement are investigated when the covariate is endogenous even in the absence of measurement error. Reducing measurement error can exacerbate the finite sample bias of Two-Stage Least Squares. An application reveals this is of practical importance. JEL: C36, C81

We consider two methods of defining a regression analogue to a trimmed mean. The first was suggested by Koenker and Bassett and uses their concept of regression quantiles. Its asymptotic behavior is completely analogous to that of a trimmed mean. The second method uses residuals from a preliminary estimator. Its asymptotic behavior depends heavily on the preliminary estimate; it behaves, in gen...

The most widely used method for finding relationships between several quantities is multiple regression. This however is restricted to a single dependent variable. We present a more general method which allows models to be constructed with multiple variables on both sides of an equation and which can be computed easily using a spreadsheet program. The underlying principle (originating from cano...

An extensive set of diagnostics for linear regression models has been developed to handle nonsurvey data. The models and the sampling plans used for finite populations often entail stratification, clustering, and survey weights, which renders many of the standard diagnostics inappropriate. In this article we adapt some influence diagnostics that have been formulated for ordinary or weighted lea...

Despite the considerable reduction in rates of fire that have been seen in the UK in recent years analysis of three years of service data from a large UK fire service reveals that there continue to be striking inequalities in the way in which fire is distributed through society. The use of principal component analysis (PCA) and ordinary least squares regression enabled the development of a mode...