This study investigates dynamic relationships among U.S. corn cash prices for the years 2006-2011. With daily data from 182 spatially separated markets spreading across 7 states, Iowa (IA), Illinois (IL), Indiana (IN), Ohio (OH), Minnesota (MN), Nebraska (NE), and Kansas (KS), we apply an error...

This study examines the competitiveness of four Canadian agricultural industries (eggs, milk, chicken and turkey) using a general equilibrium farm to retail pricing model developed by Wohlgenant (1989). The model generates retail and farm pricing equations that are estimated using maximum...

This study estimates the transfer efficiency of government payments on Canadian agriculture. Three measures of efficiency are used: (1) the capitalization of support into farmland values, (2) the rate of income stabilization, and (3) the effect of past government support on the variance of...

This study estimates the transfer efficiency of government payments on Canadian agriculture. Three measures of efficiency are used: (1) the capitalization of support into farmland values, (2) the rate of income stabilization, and (3) the effect of past government support on the variance of...

In this work, we study the short- and long-run properties of different inequality series vis-à-vis the most important macroeconomic series for a set of OECD countries. We employ standard tools of time series macro-econometrics (e.g. stationarity tests, detrending, co-movements analysis,...

Literature shows that the regression of independent and (nearly) nonstationary time series could result in spurious outcomes. In this paper, we conjecture that under some situations, the regression of two independent and nearly non-stationary series does not have any spurious problem at all. To...

We examine a kernel regression smoother for time series that takes account of the error correlation structure as proposed by Xiao et al. (2008). We show that this method continues to improve estimation in the case where the regressor is a unit root or near unit root process.