In this paper, I pursue three goals. The first is to model collusion in a way that is distinct from noncooperative collusion. The second and third are to develop a particular specification of a standard model of noncooperative collusion that permits explicit solution for equilibrium outputs and reversion thresholds and to extend this analysis to allow for a deterrence-based competition policy t...

This paper derives analytical results for determination of the window size that explores the trade-off between bias and forecast error variance to minimize the mean squared forecast error in the presence of breaks. We show analytically how to determine the estimation window optimally for the case with strictly exogenous regressors. Through Monte Carlo simulations the paper compares the performa...

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted under the assumption of mean squared error loss. Under this loss function optimal forecasts should be unbiased and forecast errors serially uncorrelated at the single period horizon with increasing variance as the forecast horizon grows. Using analytical results we show that standard properties of o...

Tests of stationarity are routinely applied to highly autocorrelated time series. Following Kwiatkowski et al. (J. Econom. 54 (1992) 159), standard stationarity tests employ a rescaling by an estimator of the long-run variance of the (potentially) stationary series. This paper analytically investigates the size and power properties of such tests when the series are strongly autocorrelated in a ...

Value at Risk (VaR) has become the industry standard to measure the market risk. However, the selection of the VaR models is controversial. Simulation Results indicate Historical Simulation has significant positive bias, while GARCH (1,1) has has significant negative bias. Also HS adapts structural change slowly but stable, while GARCH adapts structural break rapidly but less stable. Thus the m...

This paper introduces cointegrating mixed data sampling (CoMiDaS) regressions, generalizing nonlinear MiDaS regressions in the extant literature. Under a linear mixed-frequency data-generating process, MiDaS regressions provide a parsimoniously parameterized nonlinear alternative when the linear forecasting model is over-parameterized and may be infeasible. In spite of potential correlation of ...

This study re-examines the validity of Purchasing Power Parity (PPP) by focusing on the real effective exchange rates (REERs) for the post-Bretton Woods period, using newly developed unit root tests that account for both nonlinearity and smooth temporary multiple breaks in the data. The tests are applied to the REERs of 23 developed countries and are able to reject the null hypothesis of a unit...

From the spot prices we have to identify the following six parameters: α , μ, σ, Km , γ, Φ. If necessary, a seventh parameter, λ, should be identified from the futures prices. The six parameters mentioned above can be identified using the maximum likelihood method (Ball and Torous, 1983; Lien and Strom, 1999; Clewlow and Strickland, 2000) or the moments method (Lien and Strom, 1999; Deng, 1999)...