The estimation of standard errors is essential to statistical inference. Statistical variability is inherent within data, but is usually of secondary interest; still, some options exist to deal with this variability. One approach is to carefully model the covariance structure. Another approach...

In this paper we suggest an extension of the forward search methodology to GARCH models which are often used for forecasting stock market volatility. It is frequently found that estimated residuals from GARCH models have excess kurtosis, even when one allows for conditional t-distributed errors....

In this paper we suggest an extension of the forward search methodology to GARCH models which are often used for forecasting stock market volatility. It is frequently found that estimated residuals from GARCH models have excess kurtosis, even when one allows for conditional t-distributed errors....

In frontier analysis, most of the nonparametric approaches (DEA, FDH) are based on envelopment ideas which suppose that with probability one, all the observed units belong to the attainable set. In these “deterministic” frontier models, statistical theory is now mostly available (Simar and...

An important aspect of income distribution is the modelling of the data using an appropriate parametric model. This involves estimating the parameters of the models, given the data at hand. Income data are typically in grouped form. Moreover, they are not always reliable in that they may contain...

In this paper, we show the existence, uniqueness and Fréchet differentiability of [psi]-estimates T([mu]):[integral operator]R-[infinity],+[infinity](y,T([mu]))d[mu](y)=0 where [mu] is a stationary ergodic measure on (R-[infinity],+[infinity], B-[infinity],+[infinity] which include M-,...