We analyze the properties of a bias-corrected realized variance (RV) in the presence of iid market microstructure noise. The bias correction is based on the first-order autocorrelation of intraday returns and we derive the optimal sampling frequency as defined by the mean squared error (MSE)...

A new approach for Robust DEA technical efficiency measurements is presented, based on a combination of Jackknife and Bootstrap resampling schemes. First, an algorithm implementing jackknife is used to extract leverage for all data points, that is, the impact of the removal of the observed point...

In this paper, we study the statistical relationship between money and prices in Argentina during the last quarter of the 20th century. We first look at the unit root characteristics of the series which suggest dividing the whole sample into two sub-samples: 1976 to 1989 and 1991 to 2001, as...

In this paper, we propose the use of bootstrapping methods to obtain correct critical values for dating breaks. Following the procedure proposed in Banerjee, Lazarova and Urga (1998), we consider the case of estimating a system with two or more marginal processes and a conditional process....

A Vector Autoregressive model (VAR) with normally distributed innovations is a Curved Exponential Model (CEM). Cointegration imposes further curvature on the model and this means that in addition to the important reasons for conditioning in non-stationary time series as given by Johansen (1995,...

Researchers typically assume experimental subjects have rational expectations. If the object of the experiment is to learn the distibution of decision makers' types, then this amounts to assuming subjects' know the very thing the researcher wishes to learn. We propose a method of conducting...

This paper studies weak exogeneity of conditioning variables for the inference of a subset of parameters of the conditional student's t and elliptical linear regression models considered by Spanos (1994). Weak exogeneity of the conditioning variables is shown to hold for the inference of...