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不稳定环境中的预测比较AI 解读

Abstract We propose new methods for comparing the out‐of‐sample forecasting performance of two competing models in the presence of possible instabilities. The main idea is to develop a measure of the relative local forecasting performance for the two models, and to investigate its stability over time by means of statistical tests. We propose two tests (the Fluctuation test and the One‐Time Reversal test) that analyze the evolution of the models' relative performance over…

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…

利用时变多元模型带通滤波提取稳健的美国商业周期AI 解读

Abstract We develop a flexible business cycle indicator that accounts for potential time variation in macroeconomic variables. The coincident economic indicator is based on a multivariate trend cycle decomposition model and is constructed from a moderate set of US macroeconomic time series. In particular, we consider an unobserved components time series model with a common cycle that is shared across different time series but adjusted for phase shift and amplitude. The…

美联储工作人员、简单简约式模型与 DSGE 模型的预测表现比较AI 解读

Abstract This paper considers the ‘real‐time’ forecast performance of the Federal Reserve staff, time‐series models, and an estimated dynamic stochastic general equilibrium (DSGE) model—the Federal Reserve Board's Estimated, Dynamic, Optimization‐based (Edo) model. We evaluate forecast performance using out‐of‐sample predictions from 1996 to 2004. We find that the Edo model can provide forecasts that are competitive with those of Federal Reserve staff. Taken together with…

Euro-sting：欧元区增长的短期指标AI 解读

Abstract We set out a model to compute short‐term forecasts of the euro area GDP growth in real time. To allow for forecast evaluation, we construct a real‐time dataset that changes for each vintage date and includes the exact information that was available at the time of each forecast. With this dataset we show that our simple factor model algorithm, which uses an easy‐to‐replicate methodology, is able to forecast the euro area GDP growth as well as professional forecasters…

预测路径的评价AI 解读

Abstract A path forecast refers to the sequence of forecasts 1 to H periods into the future. A summary of the range of possible paths the predicted variable may follow for a given confidence level requires construction of simultaneous confidence regions that adjust for any covariance between the elements of the path forecast. This paper shows how to construct such regions with the joint predictive density and Scheffé's S‐method of 1953. In addition, the joint predictive…

不确定不稳定性下的 VAR 预测密度组合AI 解读

Abstract Recursive‐weight forecast combination is often found to an ineffective method of improving point forecast accuracy in the presence of uncertain instabilities. We examine the effectiveness of this strategy for forecast densities using (many) vector autoregressive (VAR) and autoregressive (AR) models of output growth, inflation and interest rates. Our proposed recursive‐weight density combination strategy, based on the recursive logarithmic score of the forecast…

电视观看对儿童认知发展的动态处理效应分析AI 解读

Abstract We investigate whether TV watching at ages 6–7 and 8–9 affects cognitive development measured by math and reading scores at ages 8–9, using a rich childhood longitudinal sample from NLSY79. Dynamic panel data models are estimated to handle the unobserved child‐specific factor, endogeneity of TV watching, and dynamic nature of the causal relation . A special emphasis is placed on the last aspect, where TV watching affects cognitive development, which in turn affects…

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家庭投资组合的均值—方差计量分析AI 解读

Abstract We investigate households' portfolio choice using a microeconometric approach derived from mean–variance optimization. We assume that households have heterogeneous expectations on the distribution of excess returns and that they cannot take short positions in risky assets. Assuming two such assets, we derive an explicit solution of the model characterized by four possible portfolio regimes, which are analyzed using two structural probit and tobit specifications with…

以实际支出为基础的消费者需求系统半参数估计AI 解读

Abstract Microdata concerning consumer demand typically show considerable variation in real expenditures, but very little variation in prices. We propose a semiparametric strategy for the consumer demand problem in which expenditure share equations are estimated nonparametrically in the real expenditure direction and estimated parametrically (with fixed or varying coefficients) in price directions. In our model, Engel curves are unrestricted: demands may have any rank.…

回归导数的多峰性检验及其在非参数增长回归中的应用AI 解读

Abstract This paper presents a method to test for multimodality of an estimated kernel density of derivative estimates from a nonparametric regression. The test is included in a study of nonparametric growth regressions. The results show that in the estimation of unconditional β‐convergence the distribution of the partial effects is multimodal, with one mode in the negative region (primarily OECD economies) and possibly two modes in the positive region (primarily non‐OECD…

利用高频波动率信息预测：HEAVY 模型AI 解读

Abstract This paper studies in some detail a class of high‐frequency‐based volatility (HEAVY) models. These models are direct models of daily asset return volatility based on realised measures constructed from high‐frequency data. Our analysis identifies that the models have momentum and mean reversion effects, and that they adjust quickly to structural breaks in the level of the volatility process. We study how to estimate the models and how they perform through the credit…

多元残差的有限样本序列相关与 ARCH 检验：资产定价应用AI 解读

Abstract In this paper, we propose several finite‐sample specification tests for multivariate linear regressions (MLR). We focus on tests for serial dependence and ARCH effects with possibly non‐Gaussian errors. The tests are based on properly standardized multivariate residuals to ensure invariance to error covariances. The procedures proposed provide: (i) exact variants of standard multivariate portmanteau tests for serial correlation as well as ARCH effects, and (ii)…

基于动态结构贝叶斯聚类的转折点定年与预测：奥地利应用AI 解读

Abstract The information contained in a large panel dataset is used to date historical turning points and to forecast future ones. We estimate groups of series with similar time series dynamics and link the groups with a dynamic structure. The dynamic structure identifies a group of leading and a group of coincident series. Robust results across data vintages are obtained when series‐specific information is incorporated in the design of the prior group probability…

连续时间模型、已实现波动率与日股票收益的可检验分布含义AI 解读

Abstract We provide an empirical framework for assessing the distributional properties of daily speculative returns within the context of the continuous‐time jump diffusion models traditionally used in asset pricing finance. Our approach builds directly on recently developed realized variation measures and non‐parametric jump detection statistics constructed from high‐frequency intra‐day data. A sequence of simple‐to‐implement moment‐based tests involving various…

贝叶斯分位数回归方法AI 解读

Abstract This paper is a study of the application of Bayesian exponentially tilted empirical likelihood to inference about quantile regressions. In the case of simple quantiles we show the exact form for the likelihood implied by this method and compare it with the Bayesian bootstrap and with Jeffreys' method. For regression quantiles we derive the asymptotic form of the posterior density. We also examine Markov chain Monte Carlo simulations with a proposal density formed…

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摘要暂缺

大型贝叶斯向量自回归AI 解读

Abstract This paper shows that vector auto regression (VAR) with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results of De Mol and co‐workers (2008) and show that, when the degree of shrinkage is set in relation to the cross‐sectional dimension, the forecasting performance of small monetary VARs can be improved by adding additional macroeconomic variables and sectoral information. In addition, we show that large VARs with shrinkage…

存在不确定不稳定性时的 VAR 预测平均AI 解读

Abstract Recent work suggests VAR models of output, inflation, and interest rates may be prone to instabilities. In the face of such instabilities, a variety of estimation or forecasting methods might be used to improve the accuracy of forecasts from a VAR. The uncertainty inherent in any single representation of instability could mean that combining forecasts from a range of approaches will improve forecast accuracy. Focusing on models of US output, prices, and interest…

DSGE模型的有限信息估计与评价AI 解读

Abstract We advance the proposition that dynamic stochastic general equilibrium (DSGE) models should not only be estimated and evaluated with full information methods. These require that the complete system of equations be specified properly. Some limited information analysis, which focuses upon specific equations, is therefore likely to be a useful complement to full system analysis. Two major problems occur when implementing limited information methods. These are the…

金融改革的政治经济学：Abiad 与 Mody 的结论是否成立？AI 解读

Abstract Motivated by the questions ‘Financial Reform: What Shakes It? What Shapes It?’ raised by Abiad and Mody ( 2005 ), this paper studies the forces that induce governments to undertake financial sector reform. Rather than their ordered logit technique, it uses a within groups approach allowing for error dependence across countries and over time. This analysis shows that some of the AM findings are not robust to error dependence and the estimation method. It has shed new…