Agricultural land protection near the urban-rural fringe is a goal of many jurisdictions, including British Columbia, Canada, which uses a provincial-wide zoning scheme to prevent subdivisions and non-agricultural uses of the land. Preferential taxes are also used to encourage agricultural use...

Agricultural land protection near the urban-rural fringe is a goal of many jurisdictions, and none more so than British Columbia, Canada, which uses a provincial-wide zoning scheme to prevent subdivisions and non-agricultural uses of the land. A preferential tax regulation scheme for farmers is...

The multiproduct symmetric generalized McFadden cost function is increasingly prominent in empirical production analysis. Researchers should be aware that the scope for imposing and testing nonjointness in this model is limited. In the general version of the model, nonjointness requires the...

We introduce a new panel data estimation technique for cost and production functions: the Recursive Thick Frontier Approach (RTFA). RTFA has two advantages over existing thick frontier methods. First, technical inefficiency is allowed to be dependent on the explanatory variables of the frontier...

Since 1973, British Columbia created an Agricultural Land Reserve to protect farmland from development. In this study, we employ GIS-based hedonic pricing models of farmland values to examine factors that affect farmland prices. We take spatial lag and error dependence into explicit account....

Using generalizations of Benford’s Law we test for the absence of psychological barriers at various price levels in eBay auctions for professional football tickets. Our empirical results indicate that this hypothesis cannot be rejected.

The Anderson-Darling goodness-of-fit test has a highly skewed and non-standard limit distribution. Various attempts have been made to tabulate the associated critical points, using both theoretical approximations and simulation methods. We show that a standard saddlepoint approximation performs...

A spurious regression model is one in which the dependent and independent variables are non-stationary, but not cointegrated, and the data are not filtered (e.g., by differencing) before the model is estimated. It is well known that in this case the asymptotic behaviour of the least squares...

A “spurious regression” is one in which the time-series variables are non-stationary and independent. It is well-known that in this context the OLS parameter estimates and the R2 converge to functionals of Brownian motions; the “t-ratios” diverge in distribution; and the Durbin-Watson...

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,...