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非平稳回归中的有效工具变量估计AI 解读

A limit theory for instrumental variables (IV) estimation that allows for possibly nonstationary processes was developed in Kitamura and Phillips (1992, Fully Modified IV, GIVE, and GMM Estimation with Possibly Non-stationary Regressors and Instruments, mimeo, Yale University). This theory covers a case that is important for practitioners, where the nonstationarity of the regressors may not be of full rank, and shows that the fully modified (FM) regression procedure of…

部分协整向量预先给定时的协整检验AI 解读

Many economic models imply that ratios, simple differences, or “spreads” of variables are I(0). In these models, cointegrating vectors are composed of 1's, 0's, and —1's and contain no unknown parameters. In this paper, we develop tests for cointegration that can be applied when some of the cointegrating vectors are prespecified under the null or under the alternative hypotheses. These tests are constructed in a vector error correction model and are motivated as Wald tests…

单整与协整系统中极大似然估计渐近理论的困难AI 解读

Problems with the asymptotic theory of nonlinear maximum likelihood estimation in integrated and cointegrated systems are discussed in this paper. One problem is that standard proofs of consistency generally do not apply; another one is that, even if the consistency has been established, it can be difficult to deduce the limiting distribution of a maximum likelihood estimator from a conventional Taylor series expansion of the score vector. It is argued in this paper that the…

使用前馈与循环神经网络预测汇率AI 解读

Abstract In this paper we investigate the out‐of‐sample forecasting ability of feedforward and recurrent neural networks based on empirical foreign exchange rate data. A two‐step procedure is proposed to construct suitable networks, in which networks are selected based on the predictive stochastic complexity (PSC) criterion, and the selected networks are estimated using both recursive Newton algorithms and the method of nonlinear least squares. Our results show that PSC is a…

基于典型相关分析的协整检验AI 解读

Critical values are provided for four new tests for cointegration based on the canonical correlations and variates of a development of the Box-Tiao procedure. It is found that in finite samples the power of three of these tests, unlike the power of Johansen's and Engle and Yoo's tests, is highly robust to the correlation between the disturbances in the cointegrating relationships and those generating the common trends. The proposed tests perform well against these…

修正工具变量单位根检验的功效AI 解读

In this paper we investigate the power of Hall's (1989) instrumental variables tests for unit roots. A slight modification is made to Hall's t statistic so that the modified t statistic can be applied directly without encountering the possible negative standard error problem of Hall's original t statistic. The major finding is that the power curves of the instrumental variables tests are not monotonic functions of the autoregressive coefficient of the unit root models when…

小波方差的估计AI 解读

The wavelet variance decomposes the variance of a time series into components associated with different scales. We consider two estimators of the wavelet variance: the first based upon the discrete wavelet transform, and the second, called the maximal-overlap estimator, based upon a filtering interpretation of wavelets. We determine the large sample distribution for both estimators and show that the maximal-overlap estimator is more efficient for a class of processes of…

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贝叶斯模型选择与预测及其实证应用AI 解读

This paper builds on some recent work by the author and Werner Ploberger (1991, 1994) on the development of ‘Bayes models’ for time series and on the authors' model selection criterion ‘PIC’. The PIC criterion is used in this paper to determine the lag order, the trend degree and the presence or absence of a unit root in an autoregression with deterministic trend. A new forecast-encompassing test for Bayes models is developed which allows one Bayes model to be compared with…

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非平稳波动率下的回归AI 解读

A new asymptotic theory of regression is introduced for possibly nonstationary time series. The regressors are assumed to be generated by a linear process with martingale difference innovations. The conditional variances of these martingale differences are specified as autoregressive stochastic volatility processes with autoregressive roots that are local to unity. The author finds conditions under which the least squares estimates are consistent and asymptotically normal. A…

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…

针对随机序增大备择的稳健序贯监测方案AI 解读

We sequentially observe independent observations $X_1, X_2,\ldots$ such that initially they have distribution $G_0$; at some unknown time $\nu$ they become stochastically larger, having distribution $G_1$. Neither $G_0$ nor $G_1$ is fully specified. We wish to detect that a change has taken place as soon as possible after its occurrence, subject to a constraint on the rate of false alarms. We derive a family of nonparametric sequential procedures based on ranks, with…

重尾随机变量归一化和的移动区块自助法渐近行为AI 解读

This paper studies the performance of the moving block bootstrap procedure for normalized sums of dependent random variables. Suppose that $X_1, X_2,\ldots$ are stationary $\rho$-mixing random variables with $\sum \rho (2^i) < \infty$. Let $T_n = (X_1 + \cdots + X_n - b_n)/a_n$, for some suitable constants $a_n$ and $b_n$, and let $T^\ast_{m,n}$ denote the moving block bootstrap version of $T_n$ based on a bootstrap sample of size $m$. Under certain regularity conditions, it…

周期协整：表示与推断AI 解读

This paper considers a new approach to the analysis of stable relationships between nonstationary seasonal time series. The basis of this approach is an error correction model in which both long-run effects and adjustment parameters are allowed to vary per season. First, we discuss theoretical arguments for such a periodic error correction model. We define periodic cointegration and compare this to the concept of seasonal cointegration. Next, we analyze statistical inference…

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伪结构突变AI 解读

A quasi-maximum likelihood estimator of the break date is analyzed. Consistency of the estimator is demonstrated under very general conditions, provided that the data-generating process is not integrated. However, the asymptotic distribution of the estimator is quite different for time series that are integrated of order one. In that case, when there is no break, the analyst can be spuriously led to the estimation of a break near the middle of the time series.

不规则采样、控制变量与缺失值下连续时间随机过程的解析得分函数AI 解读

The unknown structural parameters of a continuous/discrete state space model are estimated by maximum likelihood in the presence of irregular sampling, missing values, and cross-sections of time series (panel data). Exogenous (control) variables are included, and the sampling scheme and missing data pattern can be different for each variable and system. Furthermore, the derived non-linear optimization algorithm with analytical score function can be used for the discrete time…