type="main" xml:id="obes12065-abs-0001" <title type="main">Abstract</title> <p>This article investigates the evidence of time-variation and asymmetry in the persistence of US inflation. We compare the out-of-sample performance of different forecasting models and find that quantile forecasts from an Auto-Regressive (AR) model...</p>

In this paper, we introduce a kernel estimator for the finite-dimensional parameter of a partially linear additive model. Under some regularity conditions, we establish n1/2-consistency and asymptotic normality of the estimator. Unlike existing kernel-based estimators: Fan et al. (1998. Ann....

The evaluation of the impact of an increase in gasoline tax on demand relies crucially on the estimate of the price elasticity. This article presents an extended application of the Partially Linear Additive Model (PLAM) to the analysis of gasoline demand using a panel of U.S. households,...

Much of the inflation forecasting literature examines the ability of macroeconomic indicators to predict the mean inflation accurately. For the period after 1984, the existing empirical evidence largely suggests that the likelihood of predicting inflation accurately using macroeconomic...

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 analyze the determinants of incomplete pass-through in the...

We propose a kernel-based multi-stage conditional median predictor for [alpha]-mixing time series of Markovian structure. Mean squared error properties of single-stage and multi-stage conditional medians are derived and discussed.

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 nonparametric...