International Business Cycle Asymmetry and Time Irreversible Nonlinearities

Using tests of time reversibility, this paper provides further statistical evidence on the long-standing conjecture in economics concerning the potentially asymmetric behaviour of output over the expansionary and contractionary phases of the business cycle. A particular advantage of this approach is that it provides a discriminating test that is instructive as to whether any asymmetries detected are due to asymmetric shocks to a linear model, or an underlying non-linear model with symmetric shocks, and in the latter case is informative as to the potential form of that nonlinear model. Using a long span of international per capita output growth data, the asymmetry detected is overwhelmingly consistent with the long standing perception that the output business cycle is characterized by steeper recessions and longer more gentle expansions, but the evidence for this form of business cycle asymmetry is weaker in the data adjusted for the influence of outliers associated with wars and other extreme events. Statistically significant time irreversibility is reported for the output growth rates of almost all of the countries considered in the full sample data, and there is evidence that this time irreversibility is of a form implying an underlying nonlinear model with symmetrically distributed innovations for 15 of the 22 countries considered. However, the time irreversibility test results for the outlier-trimmed full sample data reveal significant time irreversibility in output growth for around one half of the countries considered, predominantly in Northern Europe and North America, and of a form implying a nonlinear underlying model in only a further half of those cases.     

海德格尔的《存在与时间》有“三重困境”吗——与寇鹏程先生商榷

原载于《汕头大学学报》 (人文社科版 ) 2 0 0 3年第 6期的寇鹏程先生的文章《海德格尔〈存在与时间〉的三重困境》 (另见人大复印资料《外国哲学》 2 0 0 4年第 2期 )指出海德格尔的《存在与时间》存在着三重内在的困境。笔者认为 ,“三重困境”的提法有值得商榷的地方 ,这里一一提出质疑     

晁说之年谱简编

晁说之(1059～1129)是北宋一位不容忽视的经学家。他博通五经,尤精于《易》学,同时又是一位富有创作实绩的作家、画家,与苏轼、黄庭坚等苏门文人、江西诗派作家有着广泛的师友关系。由于元符上书入党籍,其仕途极其坎坷,长期沉沦下僚。他的一生经历了仁宗、神宗、哲宗、徽宗、钦宗、高宗六朝,是难得的一位身入南宋的"元名士"。     

An Investigation of two Sequence-Comparison Statistics

This paper describes an investigation of two statistics which compare two ordered sequences of objects by providing a measure of the discordance when the sequences are slotted together. Configurations having zero discordance are described. Plausible null models for data are postulated, and an account is given of a simulation study which investigated the distribution of the statistics when these models were used in the analysis of physical logging data from two wells.     

A STOCHASTIC LOGISTIC MODEL WITH TIME DELAY

The stochastic version of the logistic model for population growth is generalized to take account of continuously distributed time delay with an exponentially decaying kernel. The theory of diffusion processes is used to analyse the probability density function of the population size. The explicit expression for the stationary distribution is worked out and the effect of time delay on various statistics is discussed.     

Convergence of Discount Time Series Dynamic Linear Models

This article studies the limiting behavior of multiple discount time series dynamic linear models (TSDLMs). It is shown that, under mild conditions, all discount TSDLMs converge to the constant (time-invariant) TSDLM. In particular, the limiting posterior precision matrix of the superposition of multiple discount TSDLMs is explored. For non seasonal models, the elements of the limiting posterior precision of the states are given in a recurrence relationship, while for seasonal models the solution of a linear system provides the elements of the respective limiting precision matrix. The proposed methodology uses canonical Jordan forms and it is illustrated with a detailed example of simulated data featuring both trend and seasonal time series.     

Smoothing Time Series with Local Polynomial Regression on Time

Time series smoothers estimate the level of a time series at time t as its conditional expectation given present, past and future observations, with the smoothed value depending on the estimated time series model. Alternatively, local polynomial regressions on time can be used to estimate the level, with the implied smoothed value depending on the weight function and the bandwidth in the local linear least squares fit. In this article we compare the two smoothing approaches and describe their similarities. Through simulations, we assess the increase in the mean square error that results when approximating the estimated optimal time series smoother with the local regression estimate of the level.     

Nonparametric Trend Estimation for Periodic Autoregressive Time Series

A periodically stationary time series has seasonal variances. A local linear trend estimation is proposed to accommodate unequal variances. A comparison of this proposed estimator with the estimator commonly used for a stationary time series is provided. The optimal bandwidth selection for this new trend estimator is discussed.     

Unit Roots: Bayesian Significance Test

The unit root problem plays a central role in empirical applications in the time series econometric literature. However, significance tests developed under the frequentist tradition present various conceptual problems that jeopardize the power of these tests, especially for small samples. Bayesian alternatives, although having interesting interpretations and being precisely defined, experience problems due to the fact that that the hypothesis of interest in this case is sharp or precise. The Bayesian significance test used in this article, for the unit root hypothesis, is based solely on the posterior density function, without the need of imposing positive probabilities to sets of zero Lebesgue measure. Furthermore, it is conducted under strict observance of the likelihood principle. It was designed mainly for testing sharp null hypotheses and it is called FBST for Full Bayesian Significance Test.     

The Scale Invariant Wigner Spectrum Estimation of Gaussian Locally Self-Similar Processes

We study locally self-similar processes (LSSPs) in Silverman’s sense. By deriving the minimum mean-square optimal kernel within Cohen’s class counterpart of time–frequency representations, we obtain an optimal estimation for the scale invariant Wigner spectrum (SIWS) of Gaussian LSSPs. The class of estimators is completely characterized in terms of kernels, so the optimal kernel minimizes the mean-square error of the estimation. We obtain the SIWS estimation for two cases: global and local, where in the local case, the kernel is allowed to vary with time and frequency. We also introduce two generalizations of LSSPs: the locally self-similar chirp process and the multicomponent LSSP, and obtain their optimal kernels. Finally, the performance and accuracy of the estimation is studied via simulation.