We consider temporal aggregation of stationary and nonstationary time series with short memory, long memory and antipersistence, within the framework of fractional autoregressive processes. Asymptotically, long memory and antipersistence are preserved whereas short memory components vanish. In...

In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparametric trend and maximum likelihood estimation of the parameters. For selecting the bandwidth, the proposal of Beran and Feng (1999) based...

This paper studies non-cooperative commodity taxation in a trade model with im-perfect competition and trade costs. Nationally optimal tax policy simultaneously tries to correct the domestic distortion from imperfect competition and to shift rents to the home country. Importantly, this trade-off...

Time series in many areas of application often display local or global trends. Typical models that provide statistical explanations of such trends are, for example, polynomial regression, smooth bounded trends that are estimated nonparametrically, and difference-stationary processes such as, for...

This peper anlyzes the impact of tax competition between two countries of un- equal per-capita capital endownments on tax rates and efficiency when distorting wage, residence-based and source-based capital taxes (or any combination of two instruments) are available for governments. The national...

This paper puts focus on the hazard function of inter-trade durations to characterize the intraday trading process. It sheds light on the time varying trade intensity and, thus, on the liquidity of an asset and the informations channels which propagate price signals among asymmetrically informed...

Models of international tax competition typically assume the existence of a benevolent government. This paper presents a model which integrates the view of government as source of inefficiency with an analysis of distorting taxes on capital investment, savings and labor income in a common...

The procedures of estimating prediction intervals for ARMA processes can be divided into model based methods and empirical methods. Model based methods require knowledge of the model and the underlying innovation distribution. Empirical methods are based on the sample forecast errors. In this...

In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparamet- ric trend and maximum likelihood estimation of the parameters. Convergence and asymptotic properties of the proposed algorithms are...