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评论：多预测期限制与预测理性检验AI 解读

Patton and Timmermann (2011) propose new and creative forecast rationality tests based on multi-horizon restrictions. The novelty is to consider the implications of forecast rationality jointly acr...

评论：多预测期固定目标预测的理性AI 解读

I enjoyed reading yet another article by Patton and Timmermann (PT hereafter) and feel that it has broken new ground in testing the rationality of a sequence of multi-horizon fixed-target forecasts...

评论：预测理性的多维刻画AI 解读

In the forecasting literature, researchers often seek to determine stylized facts, such as: Are forecasts rational? But forecasts can be characterized in many dimensions and answering the question ...

基于多预测期限界限的预测理性检验AI 解读

Forecast rationality under squared error loss implies various bounds on second moments of the data across forecast horizons. For example, the mean squared forecast error should be increasing in the horizon, and the mean squared forecast should be decreasing in the horizon. We propose rationality tests based on these restrictions, including new ones that can be conducted without data on the target variable, and implement them via tests of inequality constraints in a…

利用异方差识别与估计含误测及内生回归变量的模型AI 解读

This article proposes a new method of obtaining identification in mismeasured regressor models, triangular systems, and simultaneous equation systems. The method may be used in applications where other sources of identification, such as instrumental variables or repeated measurements, are not available. Associated estimators take the form of two-stage least squares or generalized method of moments. Identification comes from a heteroscedastic covariance restriction that is…

嵌套预测模型的现实检验与比较AI 解读

This article develops a simple bootstrap method for simulating asymptotic critical values for tests of equal forecast accuracy and encompassing among many nested models. Our method combines elements of fixed regressor and wild bootstraps. We first derive the asymptotic distributions of tests of equal forecast accuracy and encompassing applied to forecasts from multiple models that nest the benchmark model—that is, reality check tests. We then prove the validity of the…

非零阈值 Tobit 模型中的聚焦信息准则、模型选择与模型平均AI 解读

Claeskens and Hjort (2003) have developed a focused information criterion (FIC) for model selection that selects different models based on different focused functions with those functions tailored to the parameters singled out for interest. Hjort and Claeskens (2003) also have presented model averaging as an alternative to model selection, and suggested a local misspecification framework for studying the limiting distributions and asymptotic risk properties of post-model…

一为众、众为一：多回归变量下的回归模型检验AI 解读

We develop a novel approach to building checks of parametric regression models when many regressors are present, based on a class of sufficiently rich semiparametric alternatives, namely single-index models. We propose an omnibus test based on the kernel method that performs against a sequence of directional nonparametric alternatives as if there was only one regressor whatever the number of regressors. This test can be viewed as a smooth version of the integrated…

CPI 自有住房等价租金的公用事业费用调整会扭曲通胀测度吗？AI 解读

The Consumer Price Index (CPI) is an important social index number, central to monetary policy, well being measurement, optimal pricing, and tax and contract escalation. Shelter costs have a large weight in the CPI, so their movements receive much attention. The CPI incorporates two shelter indexes: Rent, covering renters, and Owners’ Equivalent Rent (OER), covering owners. Between 1999 and 2006, Rent and OER inflation twice diverged markedly; this occurred again recently.…

双曲 GARCH 模型的得分检验AI 解读

Davidson (2004) recently proposed the hyperbolic GARCH model to capture the phenomenon of long-range dependence in volatility, with the extent of such dependence measured by the geometric or hyperbolic decay of the coefficients in an ARCH(∞) model. In this article, we reinterpret the hyperbolic GARCH model by building a link with the common GARCH model, and construct a simplified score test to check the presence of the hyperbolic decay. We derive the asymptotic of the test…

时变波动率与相关性的动态多元厚尾模型AI 解读

We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate Student t distribution. The key novelty of our proposed model concerns the weighting of lagged squared innovations for the estimation of future correlations and volatilities. When we…

非连续价格调整：微观计量分析AI 解读

Based on a reduced-form state-dependent pricing model with random thresholds, we specify and estimate a nonlinear panel data model with an unobserved factor representing the common cost or demand components of the unobserved optimal price. Using this model, we are able to assess the relative importance of common and idiosyncratic shocks in explaining the frequency and magnitude of price changes in the case of a wide variety of consumer products in Belgium and France. We find…

非平稳半参数模型的数据驱动带宽选择AI 解读

This article extends the asymptotic results of the traditional least squares cross-validatory (CV) bandwidth selection method to semiparametric regression models with nonstationary data. Two main findings are that (a) the CV-selected bandwidth is stochastic even asymptotically and (b) the selected bandwidth based on the local constant method converges to 0 at a different speed than that based on the local linear method. Both findings are in sharp contrast to existing results…

生产函数参数估计的新方法：难以确定的资本—劳动替代弹性AI 解读

Parameters of taste and technology are central to a wide variety of economic models and issues. This article proposes a simple method for estimating production function parameters from panel data, with a particular focus on the elasticity of substitution between capital and labor. Elasticity estimates have varied widely, and a consensus estimate remains elusive. Our estimation strategy exploits long-run variation and thus avoids several pitfalls, including…

波动率函数的倾斜非参数估计及实证应用AI 解读

This article proposes a novel positive nonparametric estimator of the conditional variance function without reliance on logarithmic or other transformations. The estimator is based on an empirical likelihood modification of conventional local-level nonparametric regression applied to squared residuals of the mean regression. The estimator is shown to be asymptotically equivalent to the local linear estimator in the case of unbounded support but, unlike that estimator, is…

计件锦标赛中的同质与异质参赛者：理论与实证分析AI 解读

In this article we show that sorting different ability contestants in piece rate tournaments into more homogenous groups alters agents’ incentives to exert effort. We propose a method for structurally estimating the piece rate tournament game with heterogenous players and apply it to the payroll data from a broiler production contract. Our counterfactual analysis shows that under reasonable assumptions, both the principal and the growers can gain when the tournament groups…

时间变换无限活动衍生品定价模型的序贯贝叶斯分析AI 解读

This article investigates time-changed infinite activity derivatives pricing models from the sequential Bayesian perspective. It proposes a sequential Monte Carlo method with the proposal density generated by the unscented Kalman filter. This approach overcomes to a large extent the particle impoverishment problem inherent to the conventional particle filter. Simulation study and real applications indicate that (1) using the underlying alone cannot capture the dynamics of…

用于金融市场风险价值预测的贝叶斯时变分位数模型AI 解读

Recently, advances in time-varying quantile modeling have proven effective in financial Value-at-Risk forecasting. Some well-known dynamic conditional autoregressive quantile models are generalized to a fully nonlinear family. The Bayesian solution to the general quantile regression problem, via the Skewed-Laplace distribution, is adapted and designed for parameter estimation in this model family via an adaptive Markov chain Monte Carlo sampling scheme. A simulation study…

共同价值二价拍卖结构模型的贝叶斯推断AI 解读

Structural econometric auction models with explicit game-theoretic modeling of bidding strategies have been quite a challenge from a methodological perspective, especially within the common value framework. We develop a Bayesian analysis of the hierarchical Gaussian common value model with stochastic entry introduced by Bajari and Hortaçsu. A key component of our approach is an accurate and easily interpretable analytical approximation of the equilibrium bid function,…

含随机波动率的贝叶斯向量自回归实时密度预测AI 解读

Central banks and other forecasters are increasingly interested in various aspects of density forecasts. However, recent sharp changes in macroeconomic volatility, including the Great Moderation and the more recent sharp rise in volatility associated with increased variation in energy prices and the deep global recession—pose significant challenges to density forecasting. Accordingly, this paper examines, with real-time data, density forecasts of U.S. GDP growth,…

识别伪长记忆的检验AI 解读

This paper proposes a test statistic for the null hypothesis that a given time series is a stationary long-memory process against the alternative hypothesis that it is affected by regime change or a smoothly varying trend. The proposed test is in the frequency domain and is based on the derivatives of the profiled local Whittle likelihood function in a degenerating neighborhood of the origin. The assumptions used are mild, allowing for non-Gaussianity or conditional…

通过贝叶斯随机搜索选择多元随机波动率模型AI 解读

We propose a Bayesian stochastic search approach to selecting restrictions on multivariate regression models where the errors exhibit deterministic or stochastic conditional volatilities. We develop a Markov chain Monte Carlo (MCMC) algorithm that generates posterior restrictions on the regression coefficients and Cholesky decompositions of the covariance matrix of the errors. Numerical simulations with artificially generated data show that the proposed method is effective…

产出增长与通胀的可预测性：多期限调查方法AI 解读

We develop an unobserved-components approach to study surveys of forecasts containing multiple forecast horizons. Under the assumption that forecasters optimally update their beliefs about past, current, and future state variables as new information arrives, we use our model to extract information on the degree of predictability of the state variable and the importance of measurement errors in the observables. Empirical estimates of the model are obtained using survey…

波动率跳跃AI 解读

The article undertakes a nonparametric analysis of the high-frequency movements in stock market volatility using very finely sampled data on the VIX volatility index compiled from options data by the CBOE. We derive theoretically the link between pathwise properties of the latent spot volatility and the VIX index, such as presence of continuous martingale and/or jumps, and further show how to make statistical inference about them from the observed data. Our empirical results…