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若干长期宏观预测的实证评价AI 解读

We use long-run annual cross-country data for 10 macroeconomic variables to evaluate the long-horizon forecast distributions of six forecasting models. The variables we use range from ones having little serial correlation to ones having persistence consistent with unit roots. Our forecasting models include simple time series models and frequency domain models developed in Müller and Watson (2016). For plausibly stationary variables, an AR(1) model and a frequency domain…

随机游走预测平稳过程的样本平均误差较小AI 解读

We study the use of a misspecified overdifferenced model to forecast the level of a stationary scalar time series. Let xt be the series, and let bias be the sample average of a series of forecast errors. Then, the bias of forecasts of xt generated by a misspecified overdifferenced ARMA model for Δxt will tend to be smaller in magnitude than the bias of forecasts of xt generated by a correctly specified model for xt. Formally, let P be the number of forecasts. The bias from…

对Lazarus等《HAR推断：实践建议》的评论AI 解读

This excellent paper proposes two methods for computing a long-run variance: equally weighted cosines (EWC) and Bartlett/Newey-West (NW). The methods by assumption are not data-dependent; the user ...

贴现因子接近一时现值模型的计量分析AI 解读

This paper develops asymptotic econometric theory to help understand data generated by a present value model with a discount factor near one. A leading application is to exchange rate models. A key assumption of the asymptotic theory is that the discount factor approaches one as the sample size grows. The finite sample approximation implied by the asymptotic theory is quantitatively congruent with the modest departures from random walk behavior that are typically found and…

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小规模嵌套模型集合的预测评价AI 解读

Abstract We propose two new procedures for comparing the mean squared prediction error (MSPE) of a benchmark model to the MSPEs of a small set of alternative models that nest the benchmark. Our procedures compare the benchmark to all the alternative models simultaneously rather than sequentially, and do not require re‐estimation of models as part of a bootstrap procedure. Both procedures adjust MSPE differences in accordance with Clark and West ( 2007 ); one procedure then…

嵌套模型预测准确性相等的近似正态检验AI 解读

Forecast evaluation often compares a parsimonious null model to a larger model that nests the null model. Under the null that the parsimonious model generates the data, the larger model introduces noise into its forecasts by estimating parameters whose population values are zero. We observe that the mean squared prediction error (MSPE) from the parsimonious model is therefore expected to be smaller than that of the larger model. We describe how to adjust MSPEs to account for…

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预测能力的渐近推断AI 解读

This paper develops procedures for inference about the moments of smooth functions of out-of-sample predictions and prediction errors when there is a long time series of predictions and realizations. The aim is to provide tools for analysis of predictive accuracy and efficiency and, more generally, of predictive ability. The paper allows for nonnested and nonlinear models as well as for possible dependence of predictions and prediction errors on estimated regression…

动态线性模型中不同工具变量估计量的比较AI 解读

Using a dynamic linear equation that has a conditionally homoskedastic moving average disturbance, the authors compare two parameterizations of a commonly used instrumental variables estimator (Hansen (1982)) to one that is asymptotically optimal in a class of estimators that includes the conventional one (Hansen (1985)). They find that for some plausible data generating processes, the optimal one is distinctly more efficient asymptotically. Simulations indicate that, in…

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回归变量具有单位根时的渐近正态性AI 解读

Under fairly general conditions, ordinary least squares and linear instrumental variables estimators are asymptotically normal when a regression equation has nonstationary right hand side variables. Standard formulas may be used to calculate a consistent estimate of the asymptotic variance-covariance matrix of the estimated parameter vector, even if the disturbances are conditionally heteroskedastic and autocorrelated. So inference may proceed in the usual way. The key…

股利创新与股票价格波动AI 解读

A standard efficient markets model states that a stock price equals the expected present discounted valu e of its dividends, with a constant discount rate. This is shown to i mply that the variance of the innovation in the stock price is smalle r than that of a stock-price forecast made from a subset of the marke t's information set. The implication follows even if prices and divid ends require differencing to induce stationarity. The relation betwee n the variances appears…

一种简单、半正定的异方差与自相关一致协方差矩阵估计方法AI 解读

This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions.

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