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Using administrative data for high-priority calls in Calgary, Alberta, we estimate how ambulance travel times depend on distance. We find that a logarithmic transformation produces symmetric travel-time distributions with heavier tails than those of a normal distribution. Guided by non-parametric estimates of the median and coefficient of variation, we(More)
Recent theoretical work has suggested a number of potentially important factors in causing incomplete pass-through of exchange rates to prices, including markup adjustment, local costs and barriers to price adjustment. We empirically analyse the determinants of incomplete pass-through in the coffee industry. The observed pass-through in this industry(More)
In this paper we propose an improvement of the Kolmogorov-Smirnov test for normality. In the current implementation of the Kolmogorov-Smirnov test, a sample is compared with a normal distribution where the sample mean and the sample variance are used as parameters of the distribution. We propose to select the mean and variance of the normal distribution(More)
The evaluation of the impact of an increase in gasoline tax on demand relies crucially on the estimate of the price elasticity. This paper presents an extended application of the Partially Linear Additive Model (PLAM) to the analysis of gasoline demand using a panel of US households, focusing mainly on the estimation of the price elasticity.(More)
In this paper two kernel-based nonparametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a viable alternative to the method of De Gooijer and Zerom (2003). By making use of an internally normalized kernel smoother, the(More)
The evidence in the inflation forecasting literature suggests that simple time series models are typically hard to outperform in predicting the dynamics of the first moment, and that using information about indicators of economic activity does not lead to out-of-sample forecasting gains. While most of the earlier literature focused on the ability of leading(More)
Purpose – Following the deregulation of electricity markets in the USA, independent power producers operate as for-profit entities. Their profit depends on the price of electricity and an accurate forecast is critical in making bidding decisions on the electricity and reserve markets or engaging in bilateral contracts. Competing price forecasts have their(More)
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