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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...

摘要暂缺

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 (...

摘要暂缺

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…

评论AI 解读

Professor Diebold's personal reflections about the history of the DM test remind us that this test was originally designed to compare the accuracy of model-free forecasts such as judgmental forecas...

评论AI 解读

While it is known that pseudo-out-of-sample methods are not optimal for comparing models, they are nevertheless often used to test predictability in population. In this comment, I elaborate on the ...

Copula 模型设定的光滑检验AI 解读

We present a family of smooth tests for the goodness of fit of semiparametric multivariate copula models. The proposed tests are distribution free and can be easily implemented. They are diagnostic and constructive in the sense that when a null distribution is rejected, the test provides useful pointers to alternative copula distributions. We then propose a method of copula density construction, which can be viewed as a multivariate extension of Efron and Tibshirani. We…

丰富数据环境下经济变量的分布预测AI 解读

This article investigates the relevance of considering a large number of macroeconomic indicators to forecast the complete distribution of a variable. The baseline time series model is a semiparametric specification based on the quantile autoregressive (QAR) model that assumes that the quantiles depend on the lagged values of the variable. We then augment the time series model with macroeconomic information from a large dataset by including principal components or a subset…

回归设定下大型协方差矩阵的对角性检验AI 解读

In multivariate analysis, the covariance matrix associated with a set of variables of interest (namely response variables) commonly contains valuable information about the dataset. When the dimension of response variables is considerably larger than the sample size, it is a nontrivial task to assess whether there are linear relationships between the variables. It is even more challenging to determine whether a set of explanatory variables can explain those relationships. To…

非线性非高斯状态空间模型的数值加速重要性抽样AI 解读

We propose a general likelihood evaluation method for nonlinear non-Gaussian state-space models using the simulation-based method of efficient importance sampling. We minimize the simulation effort by replacing some key steps of the likelihood estimation procedure by numerical integration. We refer to this method as numerically accelerated importance sampling. We show that the likelihood function for models with a high-dimensional state vector and a low-dimensional signal…

波动率过程依赖结构的灵活建模AI 解读

This article proposes a novel stochastic volatility (SV) model that draws from the existing literature on autoregressive SV models, aggregation of autoregressive processes, and Bayesian nonparametric modeling to create a SV model that can capture long-range dependence. The volatility process is assumed to be the aggregate of autoregressive processes, where the distribution of the autoregressive coefficients is modeled using a flexible Bayesian approach. The model provides…

拟合优度：一种公理化方法AI 解读

An axiomatic approach is used to develop a one-parameter family of measures of divergence between distributions. These measures can be used to perform goodness-of-fit tests with good statistical properties. Asymptotic theory shows that the test statistics have well-defined limiting distributions which are, however, analytically intractable. A parametric bootstrap procedure is proposed for implementation of the tests. The procedure is shown to work very well in a set of…

无条件协方差非恒定时的瞬时因果关系检验AI 解读

This article investigates the problem of testing instantaneous causality between vector autoregressive (VAR) variables with time-varying unconditional covariance. It is underlined that the standard test does not control the Type I errors, while the tests with White and heteroscedastic autocorrelation consistent (HAC) corrections can suffer from a severe loss of power when the covariance is not constant. Consequently, we propose a modified test based on a bootstrap procedure.…

条件平均处理效应的估计AI 解读

We consider a functional parameter called the conditional average treatment effect (CATE), designed to capture heterogeneity of a treatment effect across subpopulations when the unconfoundedness assumption applies. In contrast to quantile regressions, the subpopulations of interest are defined in terms of the possible values of a set of continuous covariates rather than the quantiles of the potential outcome distributions. We show that the CATE parameter is nonparametrically…

全球金融危机期间的央行宏观预测：欧洲央行与纽约联储的经验AI 解读

This article documents macroeconomic forecasting during the global financial crisis by two key central banks: the European Central Bank and the Federal Reserve Bank of New York. The article is the result of a collaborative effort between staff at the two institutions, allowing us to study the time-stamped forecasts as they were made throughout the crisis. The analysis does not exclusively focus on point forecast performance. It also examines methodological contributions,…

评论AI 解读

According to a famous saying, one “should never ask what's inside a sausage and an economic forecast.” We still do not dare to ask how a bratwurst is made, but the authors are to be commended for h...

评论AI 解读

The article by Alessi, Ghysels, Onorante, Peach, and Potter (henceforth AGOPP) covers a lot of important ground on the themes of central bank forecasting and its evolution in the light of the finan...

存在内生回归变量时的加性非参数回归AI 解读

In this article we consider nonparametric estimation of a structural equation model under full additivity constraint. We propose estimators for both the conditional mean and gradient which are consistent, asymptotically normal, oracle efficient, and free from the curse of dimensionality. Monte Carlo simulations support the asymptotic developments. We employ a partially linear extension of our model to study the relationship between child care and cognitive outcomes. Some of…

采用 Box–Cox 变换的已实现随机波动率模型AI 解读

This article presents a new class of realized stochastic volatility model based on realized volatilities and returns jointly. We generalize the traditionally used logarithm transformation of realized volatility to the Box–Cox transformation, a more flexible parametric family of transformations. A two-step maximum likelihood estimation procedure is introduced to estimate this model on the basis of Koopman and Scharth (Citation2013). Simulation results show that the two-step…

用于估计风险价值的变系数期望分位数模型AI 解读

This article develops a nonparametric varying-coefficient approach for modeling the expectile-based value at risk (EVaR). EVaR has an advantage over the conventional quantile-based VaR (QVaR) of being more sensitive to the magnitude of extreme losses. EVaR can also be used for calculating QVaR and expected shortfall (ES) by exploiting the one-to-one mapping from expectiles to quantiles, and the relationship between VaR and ES. Previous studies on conditional EVaR estimation…

联立方程网络模型的识别与有效估计AI 解读

This article considers identification and estimation of social network models in a system of simultaneous equations. We show that, with or without row-normalization of the social adjacency matrix, the network model has different equilibrium implications, needs different identification conditions, and requires different estimation strategies. When the adjacency matrix is not row-normalized, the variation in the Bonacich centrality across nodes in a network can be used as an…

鞅假设检验AI 解读

We propose new tests of the martingale hypothesis based on generalized versions of the Kolmogorov–Smirnov and Cramér–von Mises tests. The tests are distribution-free and allow for a weak drift in the null model. The methods do not require either smoothing parameters or bootstrap resampling for their implementation and so are well suited to practical work. The article develops limit theory for the tests under the null and shows that the tests are consistent against a wide…

回应评论AI 解读

I would like to start by expressing my sincere gratitude for the time and effort the reviewers spent on their thoughtful and constructive comments. It is a rare opportunity to have one’s work publi...