In this paper we consider the use of fuzzy modelling in the context of econometric analysis of both time-series and cross-section data. We discuss and demonstrate a semi-parametric methodology for model identification and estimation that is based on the Fuzzy c-Means algorithm that is widely...

This paper examines the very long-run relationship between income and emissions of enteric methane in New Zealand, over the period 1895 to 1996. Controlling the emissions of this particular greenhouse gas is of crucial importance if that country is to meet its obligations as a signatory to the...

We compare testing strategies for Granger noncausality in vector autoregressions (VARs)that may or may not have unit roots and cointegration. Sequential testing methods are examined; these test for cointegration and use either a differenced VAR or a vector error correction model(VECM), in which to...

Revised productivity accounts recently released by Statistics Canada are used to estimate a Klump-McAdam-Willman normalized CES supply-side system for the half-century 1961–2010. The model permits distinct rates of factor-augmenting technical change for capital and labour that distinguish...

We compare testing strategies for Granger noncausality in vector autoregressions (VARs) that may or may not have unit roots and cointegration. Sequential testing methods are examined; these test for cointegration and use either a differenced VAR or a vector error correction model (VECM), in which...

The Lomax (Pareto II) distribution has found wide application in a variety of fields. We analyze the second-order bias of the maximum likelihood estimators of its parameters for finite sample sizes, and show that this bias is positive. We derive an analytic bias correction which reduces the...

Interpreted as an instrumental variables estimator, nonlinear least squares constructs its instruments optimally from the explanatory variables using the nonlinear specification of the regression function. This has implications for the use of GMM estimators in nonlinear regression models,...

We derive analytic expressions for the biases, to O(n-1), of the maximum likelihood estimators of the parameters of the generalized Pareto distribution. Using these expressions to bias-correct the estimators is found to be extremely effective in terms of bias reduction, and can also result in a...

We derive analytic expressions for the biases, to O(n-1), of the maximum likelihood estimators of the parameters of the generalized Rayleigh distribution family. Using these expressions to bias-correct the estimators is found to be extremely effective in terms of bias reduction, and generally...

Extreme value theory (EVT) measures the behavior of extreme observations on a random variable. EVT in risk management, an approach to modeling and measuring risks under rare events, has taken on a prominent role in recent years. This paper contributes to the literature in two respects by...