Existing estimates of the Federal Reserve’s implicit inflation target typically rely on the assumption that it is constant for the duration of the period of analysis. This paper relaxes this assumption and estimates the implicit inflation target using a time-varying parameter model and the Kalman filter. In applying this method to the Volcker–Greenspan period, it finds significant time variatio...

This paper analyzes the application of the Markov-switching ARCH model (Hamilton and Susmel, 1994) in improving value-at-risk (VaR) forecast. By considering a mixture of normal distributions with varying variances over different time and regimes, we find that the “spurious high persistence” found in the GARCH model is adjusted. Under relative performance and hypothesis-testing evaluations, the ...

In this paper we use new statistical methods to examine the connection between economic expectations and support for the government in the U.S.A. For this purpose, we analyse the order of integration for Congressional Approval and Economic Expectations from a fractional point of view. The results show that though both individual series can be specified in terms of fractional processes, the unit...

In this paper, we estimate a health care demand function for 18 OECD countries for the period 1972-1995. We consider a demand side approach where health expenditure depend on per capita GDP and the relative price of health care. We use panel data unit root and stationarity tests to characterize our data. Then, we test cointegration between our variables with Kao[16] panel data cointegration tes...

Recently Chen and Fan (2003a) introduced a new class of semiparametric copula-based multivariate dynamic (SCOMDY) models. A SCOMDY model specifies the conditional mean and the conditional variance of a multivariate time series parametrically (such as VAR, GARCH), but specifies the multivariate distribution of the standardized innovation semiparametrically as a parametric copula evaluated at non...

This paper analyses revisions of Swiss current account data, taking into account the actual data revision process and the implied types of revisions. In addition we investigate whether the first release of current account data can be improved upon by the use of survey results as gathered by the KOF Swiss Economic Institute, ETH Zurich. An answer in the affirmative indicates that it is possible ...

This paper focuses on the performance of various GARCH models in terms of their ability of delivering volatility forecasts for stock return data. Volatility forecasts obtained from a variety of mean and variance specifications in GARCH models are compared to a proxy of actual volatility calculated using daily data. In-sample tests suggest that a regression of volatility estimates on actual vola...

In this paper a Bayesian approach to unit root testing for panel data models is proposed based on the comparison of stationary autoregressive models with and without individual deterministic trends, with their counterpart models with a unit autoregressive root. This is done under cross-sectional dependence among the units of the panel. Simulation experiments are conducted with the aim to assess...

We agree that either mistaking a stochastic trend for a deterministic trend (or vice-versa) is consequential for unit root tests and for tests of nonlinear serial dependence. In addition, we comment that similar results obtain for ordinary parameter inference in simple linear models. In particular, we note that detrending stochastically trended data with a deterministic polynomial or by applyin...

There have been a number of studies that have sought to understand the pattern of aggregate business failure rates and model the macro-economic determinants of aggregate corporate liquidations in the UK. This paper uses quarterly data (1961.1-1998.2) on failure rates and potential macroeconomic determinants to build a time-series econometric model which explicitly tests for the impact of change...