论文检索

Haavelmo 的实验方法论与协整向量自回归情景分析AI 解读

The paper provides a careful, analytical account of Trygve Haavelmo’s use of the analogy between controlled experiments common in the natural sciences and econometric techniques. The experimental analogy forms the linchpin of the methodology for passive observation that he develops in his famous monograph, The Probability Approach in Econometrics (1944). Contrary to some recent interpretations of Haavelmo’s method, the experimental analogy does not commit Haavelmo to a…

Haavelmo 的概率方法与协整 VARAI 解读

Some key econometric concepts and problems of great importance to Trygve Haavelmo and Ragnar Frisch are discussed within the general framework of a cointegrated VAR. The focus is on problems typical of time-series data such as multicollinearity, spurious correlation and regression, time dependent residuals, model selection, missing simultaneity, autonomy, and identification. The paper argues that the more recent development of unit root econometrics has been instrumental for…

Haavelmo 资本与投资市场模型的 VAR 解释AI 解读

In the paper attempts are made to integrate two parts of Trygve Haavelmo’s work: investment theory and dynamic econometric models of interrelated markets. Specifically, the duality in the representation of the capital service price and the capital quantity in relation to the investment price and quantity are brought to the forefront and confronted with elements from simultaneous equation modeling of vector autoregressive systems containing exogenous variables (VARX), using…

通过稀疏化二元分割检测高维时间序列的多个变点AI 解读

Summary Time series segmentation, which is also known as multiple-change-point detection, is a well-established problem. However, few solutions have been designed specifically for high dimensional situations. Our interest is in segmenting the second-order structure of a high dimensional time series. In a generic step of a binary segmentation algorithm for multivariate time series, one natural solution is to combine cumulative sum statistics obtained from local periodograms…

动态函数主成分AI 解读

Summary We address the problem of dimension reduction for time series of functional data (Xt:t∈Z). Such functional time series frequently arise, for example, when a continuous time process is segmented into some smaller natural units, such as days. Then each X t represents one intraday curve. We argue that functional principal component analysis, though a key technique in the field and a benchmark for any competitor, does not provide an adequate dimension reduction in a time…

有无不等式约束的非平稳时间序列回归推断AI 解读

Summary We consider statistical inference for time series linear regression where the response and predictor processes may experience general forms of abrupt and smooth non-stationary behaviours over time. Meanwhile, the regression parameters may be subject to linear inequality constraints. A simple and unified procedure for structural stability checks and parameter inference is proposed. In the case where the regression parameters are constrained, the methodology proposed…

非平稳时间序列的非线性回归AI 解读

This paper develops asymptotic theory for a nonlinear parametric cointegrating regression model. We establish a general framework for weak consistency that is easy to apply for various nonstationary time series, including partial sums of linear processes and Harris recurrent Markov chains. We provide limit distributions for nonlinear least square estimators, extending the previous works. We also introduce endogeneity to the model by allowing the error to be serially…

含内生解释变量的平滑结构变化建模与检验AI 解读

Modeling and detecting parameter stability of econometric models is a long standing problem. Most existing estimation and testing methods are designed for models without endogeneity. Little attention has been paid to models with endogeneous regressors, which may arise in many scenarios in economics. In this paper, we first consider a time-varying coefficient time series model with potential time-varying endogeneity. A local linear two stage least squared estimation is…

弱依赖数据下高维矩约束的广义经验似然AI 解读

This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the dimensions of the moment restrictions and the parameters diverge along with the sample size. The consistency with rates and the asymptotic normality of the GEL estimator are obtained by properly restricting the growth rates of the dimensions of the parameters and the moment…

含随机波动率的动态均衡模型估计AI 解读

This paper develops a particle filtering algorithm to estimate dynamic equilibrium models with stochastic volatility using a likelihood-based approach. The algorithm, which exploits the structure and profusion of shocks in stochastic volatility models, is versatile and computationally tractable even in large-scale models. As an application, we use our algorithm and Bayesian methods to estimate a business cycle model of the US economy with both stochastic volatility and…

多变量时间序列的二阶平稳性检验AI 解读

It is well known that the discrete Fourier transforms (DFTs) of a second order stationary time series between two distinct Fourier frequencies are asymptotically uncorrelated. In contrast for a large class of second order nonstationary time series, including locally stationary time series, this property does not hold. In this paper these starkly differing properties are used to define a global test for stationarity based on the DFT of a vector time series. It is shown that…

Bottazzi and Peri (Economic Journal 2007; 117: 486–511) show the existence of a cointegrating relationship between the domestic stock of knowledge, domestic R&D and the international knowledge stock for a panel of OECD countries and interpret it as evidence supporting the semi-endogenous versus the endogenous growth theory. We replicate the baseline specification of their study and we show that main results are robust to the use of a different estimation strategy (Bai et…

利用散射矩分析间歇性过程AI 解读

Scattering moments provide nonparametric models of random processes with stationary increments. They are expected values of random variables computed with a nonexpansive operator, obtained by iteratively applying wavelet transforms and modulus nonlinearities, which preserves the variance. First- and second-order scattering moments are shown to characterize intermittency and self-similarity properties of multiscale processes. Scattering moments of Poisson processes,…

基于图的变点检测AI 解读

We consider the testing and estimation of change-points—locations where the distribution abruptly changes—in a data sequence. A new approach, based on scan statistics utilizing graphs representing the similarity between observations, is proposed. The graph-based approach is nonparametric, and can be applied to any data set as long as an informative similarity measure on the sample space can be defined. Accurate analytic approximations to the significance of graph-based scan…

因子增强向量自回归模型的过度识别约束检验AI 解读

This paper develops tests for overidentifying restrictions in Factor-Augmented Vector Autoregressive (FAVAR) models. The identification of structural shocks in FAVAR can involve infinitely many restrictions as the number of cross sections goes to infinity. Our focus is to test the joint null hypothesis that all the restrictions are satisfied. Conventional tests cannot be used due to the large dimension. We transform the infinite-dimensional problem into a finite-dimensional…

积分阶数未知时水平与趋势突变日期的置信集合AI 解读

We propose methods for constructing confidence sets for the timing of a break in level and/or trend that have asymptotically correct coverage for both I(0) and I(1) processes. These are based on inverting a sequence of tests for the break location, evaluated across all possible break dates. We separately derive locally best invariant tests for the I(0) and I(1) cases; under their respective assumptions, the resulting confidence sets provide correct asymptotic coverage…

I(2) 环境中平稳协整的残差 ADF 检验AI 解读

We propose a residual-based augmented Dickey–Fuller (ADF) test statistic that allows for detection of stationary cointegration within a system that may contain both I(2) and I(1) observables. The test is also consistent under the alternative of multicointegration, where first differences of the I(2) observables enter the cointegrating relationships. We find the null limiting distribution of this statistic and justify why our proposal improves over related approaches.…

非平稳时间序列模型的设定检验AI 解读

In this paper, we consider a specification testing problem in nonlinear time series models with nonstationary regressors, and we propose using a nonparametric kernel‐based test statistic. The null asymptotics for the proposed nonparametric test statistic have been well developed in the existing literature. In this paper, we study the local asymptotics of the test statistic (i.e. the asymptotic properties of the test statistic under a sequence of general nonparametric local…

非线性动态模型的规格检验AI 解读

We propose a new adequacy test and a graphical evaluation tool for nonlinear dynamic models. The proposed techniques can be applied in any set‐up where parametric conditional distribution of the data is specified and, in particular, to models involving conditional volatility, conditional higher moments, conditional quantiles, asymmetry, Value at Risk models, duration models, diffusion models, etc. Compared to other tests, the new test properly controls the nonlinear dynamic…

平稳函数型时间序列的预测AI 解读

This article addresses the prediction of stationary functional time series. Existing contributions to this problem have largely focused on the special case of first-order functional autoregressive processes because of their technical tractability and the current lack of advanced functional time series methodology. It is shown here how standard multivariate prediction techniques can be used in this context. The connection between functional and multivariate predictions is…

分位数相关与分位数自回归建模AI 解读

In this article, we propose two important measures, quantile correlation (QCOR) and quantile partial correlation (QPCOR). We then apply them to quantile autoregressive (QAR) models, and introduce two valuable quantities, the quantile autocorrelation function (QACF) and the quantile partial autocorrelation function (QPACF). This allows us to extend the Box–Jenkins three-stage procedure (model identification, model parameter estimation, and model diagnostic checking) from…

评论（摘要涉及 Diebold–Mariano 预测评价检验）AI 解读

The Diebold-Mariano (1995) test has played an important role in the annals of forecast evaluation. Its simplicity—essentially amounting to computing a robust t-statistic—and its generality—applying...

评论（摘要涉及现代预测比较文献的早期发展）AI 解读

1. This interesting article provides an insider’s view of the early days of the “modern” forecast comparison literature, which might be dated as beginning with Diebold and Mariano (1995) and West (...

预测准确性比较二十年后：关于 Diebold–Mariano 检验使用与误用的个人观点AI 解读

The Diebold–Mariano (DM) test was intended for comparing forecasts; it has been, and remains, useful in that regard. The DM test was not intended for comparing models. Much of the large ensuing literature, however, uses DM-type tests for comparing models, in pseudo-out-of-sample environments. In that case, simpler yet more compelling full-sample model comparison procedures exist; they have been, and should continue to be, widely used. The hunch that pseudo-out-of-sample…