The discrete choice or ”referendum” contingent valuation technique has become a popular tool for assessing the value of non-market goods. Surveys used in these studies frequently suffer from large non-response which can lead to significant bias in parameter estimates and in the estimate of...

The asymmetric power ARCH model is a recent addition to time series models that may be used for predicting volatility. Its performance is compared with that of standard models of conditional heteroskedasticity such as GARCH. This has previously been done empirically. In this paper the same issue...

Starting from a linear error correction model the stability and linearity of a German M1 moneyt demand function are investigated, applying smooth transition regression techniques. Using seasonally unadjusted data from 1961 (1) to 1990 (2) it is found that the money demand equation is both linear...

The detection of structural change and determination of lag lengths are long-standing issues in time series analysis. This paper demonstrates how these can be successfully married in a Bayesian analysis. By taking account of the inherent uncertainty about the lag length when deciding on the...

This paper analyzes the net barter terms of trade measured by the primary commodity price index relative to the index of unit values of export of manufactures from industrial countries. The starting-point is that the series is stationary but possibly nonlinear. Statistical tests indicate that...

We consider a family of GARCH(1,1) processes introduced in He and Teräsvirta (1999a). This family contains various popular GARCH models as special cases. A necessary and sufficient condition for the existence of a strictly stationary solution is given.

This paper presents a new dynamic ARCH-related conditionally heteroscedastic stochastic frontier model specification where firm and time-specific technical inefficiency is represented by an autoregressive stochastic process in the error components. Monte Carlo results reveal that a one-sided...

This paper is concerned with efficient GMM estimation and inference in GARCH models. Sufficient conditions for the estimator to be consistent and asymptotically normal are established for the GARCH(1,1) conditional variance process. In addition efficiency results are obtained in the general...

The recent findings by McCoskey and Selden (1997, Journal of Health Economics, forthcoming) that health expenditure and GDP are stationary are driven by the omission of time trends in their ADF regressions. Since both health expenditure and GDP are trending, this omission raise serious doubts on...

Since the true nature of a time series process is often unknown it is important to understand the effects of model choice. This paper examines how the choice between modelling stationary time series as ARMA or ARFIMA processes affects the accuracy of forecasts. This is done, for first-order...