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标量扩散模型的完全非参数估计AI 解读

We propose a functional estimation procedure for homogeneous stochastic differential equations based on a discrete sample of observations and with minimal requirements on the data generating process. We show how to identify the drift and diffusion function in situations where one or the other function is considered a nuisance parameter. The asymptotic behavior of the estimators is examined as the observation frequency increases and as the time span lengthens. We prove almost…

Band spectral regression with both deterministic and stochastic trends is considered. It is shown that trend removal by regression in the time domain prior to band spectral regression can lead to biased and inconsistent estimates in models with frequency dependent coefficients. Both semiparametric and nonparametric regression formulations are considered, the latter including general systems of two-sided distributed lags such as those arising in lead and lag regressions. The…

短期利率连续时间模型的高斯估计方法AI 解读

This paper proposes a Gaussian estimator for nonlinear continuous time models of the short-term interest rate. The approach is based on a stopping time argument that produces a normalizing transformation facilitating the use of a Gaussian likelihood. A Monte Carlo study shows that the finite-sample performance of the proposed procedure offers an improvement over the discrete approximation method proposed by Nowman (1997). An em-pirical application to US and British interest…

计量经济学会青年学者密集研讨会AI 解读

This inaugural Workshop for Young Scholars was arranged under the auspices of and with financial support from the Econometric Society and the Econometric Society Australasian Standing Committee (ESASC). Twenty-five scholars met for two days in Hamilton, New Zealand immediately following the Econometric Society Australasian Meeting which was held in Auckland over July 6–8. (A report by Les Oxley on these Econometric Society Meetings, entitled “2001 Econometric Society…

重新审视远期贴水异象：计量经济学证据AI 解读

Abstract Using both semiparametric and parametric estimation methods, this paper corroborates earlier findings of fractionally integrated behaviour in the forward premium. Two new explanations are also proposed to help reconcile earlier conflicting empirical evidence on the time series properties of the forward premium. Traditional regression approaches used to test the forward rate unbiasedness hypothesis are then evaluated, including regression in levels, in returns…

含协整与确定性趋势解释变量的非线性计量模型AI 解读

This paper develops an asymptotic theory for a general class of nonlinear non-stationary regressions, extending earlier work by Phillips and Hansen (1990) on linear coin-tegrating regressions.The model considered accommodates a linear time trend and stationary regressors, as well as multiple I(1) regressors. We establish consistency and derive the limit distribution of the nonlinear least squares estimator. The estimator is consistent under fairly general conditions but the…

非平稳时间序列的描述性计量方法及实证示例AI 解读

Abstract Recent work by the author on methods of spatial density analysis for time series data with stochastic trends is reviewed. The methods are extended to include processes with deterministic trends, formulae for the mean spatial density are given, and the limits of sample moments of non‐stationary data are shown to take the form of moments with respect to the underlying spatial density, analogous to population moments of a stationary process. The methods are illustrated…

含单整时间序列的非线性回归AI 解读

An asymptotic theory is developed for nonlinear regression with integrated processes. The models allow for nonlinear effects from unit root time series and therefore deal with the case of parametric nonlinear cointegration. The theory covers integrable and asymptotically homogeneous functions. Sufficient conditions for weak consistency are given and a limit distribution theory is provided. The rates of convergence depend on the properties of the nonlinear regression…

非平稳二元选择AI 解读

This paper develops an asymptotic theory for time series binary choice models with nonstationary explanatory variables generated as integrated processes. Both logit and probit models are covered. The maximum likelihood (ML) estimator is consistent but a new phenomenon arises in its limit distribution theory. The estimator consists of a mixture of two components, one of which is parallel to and the other orthogonal to the direction of the true parameter vector, with the…

非平稳面板数据的线性回归极限理论AI 解读

This paper develops a regression limit theory for nonstationary panel data with large numbers of cross section and time series observations. The limit theory allows for both sequential limits and joins limits, and the relationship between these multidimensional limits is explored. The panel structures considered allow for no time series cointegration, heterogeneous cointegration, homogeneous cointegration, and near-homogeneous cointegration. The paper explores the existence…

理解伪回归的新工具AI 解读

Some new tools for analyzing spurious regressions are presented. The theory utilizes the general representation of a stochastic process in terms of an orthonormal system and provides an extension of the Weierstrass theorem to include the approximation of continuous functions and stochastic processes by Wiener processes. The theory is applied to two classic examples of spurious regressions: regressions of stochastic trends on time polynomials and regressions among independent…

计量经济模型的确定AI 解读

This paper is concerned with model determination methods and their use in the prediction of economic time series. The methods are Bayesian but they can be justified by classical arguments as well. The paper continues some recent work on Bayesian asymptotic, develops embedding techniques for vector martingales, and implements the modeling ideas in a multivariate regression framework that includes Bayesian vector autoregression (BVAR's) and reduced rank regressions (RRR's). It…

时间序列贝叶斯推断的渐近理论AI 解读

This paper develops an asymptotic theory of Bayesian inference for time series. A limiting representation of the Bayesian data density is obtained and shown to be of the same general exponential form for a wide class of likelihoods and prior distributions. Continuous time and discrete time cases are studied. In discrete time, an embedding theorem is given which shows how to embed the exponential density in a continuous time process. From the embedding we obtain a large…

远期外汇市场效率的稳健检验：来自20世纪20年代的证据AI 解读

This paper provides a robust statistical approach to testing the unbiasedness hypothesis in forward exchange market efficiency studies. The methods we use allow us to work explicitly with levels rather than differenced data. They are statistically robust to data distributions with heavy tails, and they can be applied to data sets where the frequency of observation and the futures maturity do not coincide. In addition, our methods allow for stochastic trend non-stationarity…

完全修正最小二乘与向量自回归AI 解读

This paper provides a general framework which makes it possible to study the asymptotic behavior of FM regression in models with I(1) and I(0) regressors, models with unit roots, and models with only stationary regressors. This framework enables us to consider the use of FM regression in the context of vector autoregressions with some unit roots and some cointegrating relations. The resulting FM-VAR regressions are shown to produce optimal estimates of the cointegration…

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误差修正模型中协整系数最大似然估计量的若干精确分布理论AI 解读

The author derives some exact finite sample disbibutions and characterizes the tail behavior of maximum likelihood estimators of the cointegrating coefficients in error correction models. The reduced rank regression estimator has a distribution with Cauchy-like tails and no finite moments of integer order. The maximum likelihood estimator of the coefficients in a particular triangular system representation has matrix t-distribution tails with finite integer moments to order…

向量自回归与因果性AI 解读

A limit theory for Wald tests of Granger causality in levels vector autoregressions (VAR's) and error correction models (ECM's) is developed, which allows for stochastic trends and cointegration. Earlier work is extended to the general case, thereby characterizing when these Wald tests are asymptotically valid as 'x'(superscript 2) criteria. Our results for inference from unrestricted levels VAR are not encouraging: the limit theory often involves nuisance parameters and…

线性过程的渐近理论AI 解读

A method of deriving asymptotics for linear processes is introduced which uses an explicit algebraic decomposition of the linear filter. The technique is closely related to Gordin's method but has some advantages over it, especially in terms of its range of application. The method offers a simple unified approach to strong laws, central limit theory and invariance principles for linear processes. Sample means and sample covariances are covered. The results accommodate both…

This paper studies the asymptotic properties of instrumental variable (IV) estimates of multivariate cointegrating regressions and allows for deterministic and stochastic regressors as well as quite general deterministic processes in the data-generating mechanism. It is found that IV regressions are consistent even when the instruments are stochastically independent of the regressors. This phenomenon, which contrasts with traditional theory for stationary time series, is a…

时间序列分析中的趋势与随机游走AI 解读

This paper studies the effects of spurious detrending in regression. The asymptotic behavior of traditional least squares estimators and tests are examined in the context of models where the generating mechanism is systematically misspecified by the presence of deterministic time trends. Most previous work on the subject has relied upon Monte Carlo studies to understand the issues involved in detrending data that is generated by integrated processes and our analytical…

时间序列回归中的单位根检验AI 解读

This paper proposes new tests for detecting the presence of a unit root in quite general time series models. Our approach is nonparametric with respect to nuisance parameters and thereby allows for a very wide class of weakly dependent and possibly heterogeneously distributed data. The tests accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend. The…

有界非对称损失下线性回归的最优中位数无偏估计AI 解读

This article considers optimal median-unbiased estimation in a linear regression model with the distribution of the errors lying in a subclass of the elliptically symmetric distributions. The generalized least squares (GLS) estimator is shown to be best for any monotone loss function, that is, any loss function that is nondecreasing as the magnitude of underestimation or overestimation increases. This includes bounded asymmetric loss functions. For the same loss functions, a…

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