客户信用评级体系的校准度检验研究

利用多种统计量对客户信用评级体系进行校准度检验,以对其准确性做出定量评估。同时,使用这些统计量对由两种不同方法构造的信用评级进行了实证对比检验,结果表明,校准度检验能够对客户信用评级的准确性做出有效评估。     

An objective Bayesian analysis of common stochastic trends in international stock prices and exchange rates

This paper uses Bayesian methods to analyze unit root and cointegration properties of two different finance data sets. Avoiding the use of subjective prior information, the paper surveys and utilizes several different objective Bayesian methodologies in an investigation of common stochastic trends in international stock markets and in spot and forward exchange rates for several different countries.     

纽约股票市场对中国A股市场的影响

首先，本文考察了纽约股市波动对中国A股市场的影响。一般认为，中国的A股市场由于严格的资本控制而免受外国影响。但是，通过月度、每周、每日的样本数据（1992年到2004年），经过季节性调整和汇率变动调整后，我们发现上海和深圳A股市场的变动与美国股票价格指数变动相一致。其次，我们考察国家贝塔值（country beta）在马尔可夫转换误差修正模型中的动态关系。对中国市场来说，国家贝塔值和错误纠正项的重要性紧密相连。在东亚金融危机之前，美国市场对中国A股市场的影响普遍存在，而东亚金融危机产生后，则是通过国家贝塔值来影响中国股市的收益。     

Evidence on the existence of speculative bubbles in farmland prices

We conduct tests for the contribution of speculative bubbles to farmland prices. These tests are carried out under the hypothesis that farmland investors rationally form expectations. The outcome of tests reported here allows us to infer whether farmland prices are determined by market fundamentals-discounted returns from the highest economic land use-or whether rumors about farmland price movements are self-fulfilling. The tests are stationarity and cointegration tests relating farmland prices to rents. The tests are carried out using data from three farm production regions-the Corn Belt, the Northern Plains, and the Lake States. In each region, we find little evidence to reject the hypothesis that market fundamentals determine farmland prices.     

A model of fractional cointegration, and tests for cointegration using the bootstrap

The paper proposes a framework for modelling cointegration in fractionally integrated processes, and considers methods for testing the existence of cointegrating relationships using the parametric bootstrap. In these procedures, ARFIMA models are fitted to the data, and the estimates used to simulate the null hypothesis of non-cointegration in a vector autoregressive modelling framework. The simulations are used to estimate p-values for alternative regression-based test statistics, including the F goodness-of-fit statistic, the Durbin–Watson statistic and estimates of the residual d. The bootstrap distributions are economical to compute, being conditioned on the actual sample values of all but the dependent variable in the regression. The procedures are easily adapted to test stronger null hypotheses, such as statistical independence. The tests are not in general asymptotically pivotal, but implemented by the bootstrap, are shown to be consistent against alternatives with both stationary and nonstationary cointegrating residuals. As an example, the tests are applied to the series for UK consumption and disposable income. The power properties of the tests are studied by simulations of artificial cointegrating relationships based on the sample data. The F test performs better in these experiments than the residual-based tests, although the Durbin–Watson in turn dominates the test based on the residual d.     

油品测试用规格仪器国产化回眸

指出规格仪器是油品测试方法标准化的基础，总结了油品测试用规格仪器国产化的过程，并对今后的发展方向加以分析。     

Demand for broad money and expenditure components in Japan: an empirical study

The main objective of the present study is to examine empirically the long-run relation of broad money demand and its determinants in Japan. In contrast with previous study, the present study considers various components of final expenditure demand as determinants that are final consumption goods, expenditure on investment goods and exports. Using quarterly data over the period 1973Q1–2000Q2, the results of the bounds test [J. Appl. Econ. 16 (2001) 289] indicate a stable long-run relationship between demand of real M2 and its determinants. The empirical results also highlight that different domestic demand components yields different effects on Japanese broad money demand behavior. The estimated unrestricted error-correction model appears to track the data well and the results have important policy implications.     

Analysis of cointegrated VARMA processes

VARMA (vector autoregressive moving average) processes are proposed for modelling cointegrated variables. For this purpose the echelon form is combined with the error correction form. Procedures for estimating the Kronecker indices which characterize the echelon form and for specifying the cointegration rank are discussed. The asymptotic distribution of the coefficient estimators is given. An example based o n US macroeconomic data illustrates the procedure and demonstrates its feasibility in practice.     

CEV模型的单位根检验研究

CEV模型（Constant Elasticity of Variance Model）作为常用的利率模型，在实证分析中得到了广泛运用，但是其单位根检验一直被忽略或者被默认可以使用迪基一富勒检验。本文首次运用Box—Cox变换的技巧，针对CEV模型的单位根检验问题，找到了合适的统计量并且证明其渐进分布存在，然后通过蒙特卡罗方法求出了该统计量的分布表。得到了在大样本的情形下可以沿用迪基一富勒检验，但在小样本的情形下与迪基一富勒检验有所偏差的结论。     

Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models

Nine macroeconomic variables are forecast in a real-time scenario using a variety of flexible specification, fixed specification, linear, and nonlinear econometric models. All models are allowed to evolve through time, and our analysis focuses on model selection and performance. In the context of real-time forecasts, flexible specification models (including linear autoregressive models with exogenous variables and nonlinear artificial neural networks) appear to offer a useful and viable alternative to less flexible fixed specification linear models for a subset of the economic variables which we examine, particularly at forecast horizons greater than 1-step ahead. We speculate that one reason for this result is that the economy is evolving (rather slowly) over time. This feature cannot easily be captured by fixed specification linear models, however, and manifests itself in the form of evolving coefficient estimates. We also provide additional evidence supporting the claim that models which ‘win’ based on one model selection criterion (say a squared error measure) do not necessarily win when an alternative selection criterion is used (say a confusion rate measure), thus highlighting the importance of the particular cost function which is used by forecasters and ‘end-users’ to evaluate their models. A wide variety of different model selection criteria and statistical tests are used to illustrate our findings.