It has been known since Phillips and Hansen (1990) that cointegrated systems can be consistently estimated using stochastic trend instruments that are independent of the system variables. A similar phenomenon occurs with deterministically trending instruments. The present work shows that such ‘‘irrelevant’’ deterministic trend instruments may be systematically used to produce asymptotically eff...

This paper examines the determinants of firm growth in the Swedish energy sector using a sample of 200 energy firms active from 2000 to 2010. The article has two aims. First, we seek to investigate whether there is reason to believe that the Swedish energy market will become more concentrated in the future, dominated by a few firms. That would be the result if, for example, large firms systemat...

A possibly non-stationary autoregressive process, of unknown finite order, with possibly infinite-variance innovations is studied. The Ordinary Least Squares autoregressive parameter estimates are shown to be consistent, and their rate of convergence, which depends on the index of stability, α, is established. We also establish consistency of lag-order selection criteria in the non-stationary c...

The paper is a contribution to parameter estimation in fuzzy regression models with random fuzzy sets. Here models with crisp parameters and fuzzy observations of the variables are investigated. This type of regressionmodelsmay be understood as an extension of the ordinary single equation linear regression models by integrating additionally the physical vagueness of the involved items. So the s...

Estimating the salaries of professional athletes has received a substantial amount of attention both in the press and in academic journals. A statistical technique that can be used to obtain an estimate of a player’s salary with a given set of performance characteristics is the classical least squares regression analysis. This technique does not work well, however, if the data upon which the mo...

The bias-eliminating least squares (BELS) method is one of the consistent estimators for identifying dynamic errors-in-variables systems. The attraction of the BELS method lies in its good accuracy and its modest computational cost. In this report, we investigate the accuracy properties of the BELS estimates. It is shown that the estimated system parameters and the estimated noise variances are...

In regression analysis for deriving scaling laws that occur in various scientific disciplines, usually standard regression methods have been applied, of which ordinary least squares (OLS) is the most popular. In many situations, the assumptions underlying OLS are not fulfilled, and several other approaches have been proposed. However, most techniques address only part of the shortcomings of OLS...

An adjusted least squares estimator is derived that yields a consistent estimate of the parameters of an implicit quadratic measurement error model. In addition, a consistent estimator for the measurement error noise variance is proposed. Important assumptions are: (1) all errors are uncorrelated identically distributed and (2) the error distribution is normal. The estimators for the quadratic ...