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异方差与自相关稳健检验中的最优带宽选择AI 解读

In time series regressions with nonparametrically autocorrelated errors, it is now standard empirical practice to use kernel-based robust standard errors that involve some smoothing function over the sample autocorrelations. The underlying smoothing parameter b, which can be defined as the ratio of the bandwidth (or truncation lag) to the sample size, is a tuning parameter that plays a key role in determining the asymptotic properties of the standard errors and associated…

多重变点与混合创新模型的高效贝叶斯推断AI 解读

Time series subject to parameter shifts of random magnitude and timing are commonly modeled with a change-point approach using Chib's algorithm to draw the break dates. We outline some advantages of an alternative approach in which breaks come through mixture distributions in state innovations, and for which the sampler of Gerlach, Carter, and Kohn allows reliable and efficient inference. We show how the same sampler can be used to model shifts in variance that occur…

贝叶斯与信息论模型平均在预测中的应用AI 解读

Model averaging often improves forecast accuracy over individual forecasts. It may also be seen as a means of forecasting in data-rich environments. Bayesian model averaging methods have been widely advocated, but a neglected frequentist approach is to use information-theoretic-based weights. We consider the use of information-theoretic model averaging in forecasting U.K. inflation, with a large dataset, and find that it can be a powerful alternative to Bayesian averaging…

稳健非嵌套检验与货币需求AI 解读

Nonnested hypothesis testing procedures recently have been extended to dynamic nonnested models. We propose robust tests that generalize the J test and the F test for nonnested dynamic models with unknown serial correlation and conditional heteroscedasticity in errors and regressors. We investigate the finite-sample properties of our test statistics and propose to use bootstrap methods or the fixed-b asymptotics developed by Kiefer and Vogelsang to improve the asymptotic…

二项自回归移动平均模型及其在美国经济衰退中的应用AI 解读

Binary Autoregressive Moving Average (BARMA) models provide a modeling technology for binary time series analogous to the classic Gaussian ARMA models used for continuous data. BARMA models mitigate the curse of dimensionality found in long lag Markov models and allow for non-Markovian persistence. The autopersistence function (APF) and autopersistence graph (APG) provide analogs to the autocorrelation function and correlogram. Parameters of the BARMA model may be estimated…

多条时间序列的模型聚类AI 解读

We propose to pool multiple time series into several groups using finite-mixture models. Within each group, the same econometric model holds. We estimate the groups of time series simultaneously with the group-specific model parameters using Bayesian Markov chain Monte Carlo simulation methods. We discuss model identification and base model selection on marginal likelihoods. With a simulation study, we document the efficiency gains in estimation and forecasting realized…

混合面板非平稳性的简单检验AI 解读

This article proposes a simple estimator that is consistent for the fraction of a panel that has an autoregressive unit root. Given such an estimate, , we can test the null hypothesis that θ = θ0 for any value of θ0 ϵ (0, 1]. The test is asymptotically standard normal and is valid whether or not the panel is cross-sectionally correlated. The main insight is that in a panel in which some units are stationary and some have unit roots, the cross-sectional variance of the mixed…

产出缺口的贝叶斯分析AI 解读

Our objective is to build output gap estimates that benefit from information provided by Phillips curve theory and business cycle studies. For this, we develop a Bayesian analysis of the bivariate Phillips curve model proposed by Kuttner for estimating potential output. Given our priors, we obtain samples from parameters and state variables joint posterior distribution following a Gibbs sampling strategy. We sample the state variables given parameters using the Carter–Kohn…

识别多重结构变化的潜在陷阱及其在购买力平价中的应用AI 解读

We investigate the empirical performance of the Bai and Perron multiple structural change tests and show that the use of their critical values may cause severe size distortions in persistent series. To correct these size distortions while maintaining a good power, we implement the Bai structural change test and extend it in two directions, developing a new procedure to choose the number of breaks and a restricted version that specifically models breaks that imply mean or…

商业周期定年方法实时表现的比较AI 解读

We evaluate the ability of formal rules to establish U.S. business cycle turning point dates in real time. We consider two approaches, a nonparametric algorithm and a parametric Markov-switching dynamic-factor model. Using a new “real-time” dataset of coincident monthly variables, we find that both approaches would have accurately identified the NBER business cycle chronology had they been in use over the past 30 years, with the Markov-switching model most closely matching…

国际动态风险分担AI 解读

Abstract In this paper we examine the implications of international risk sharing among a set of countries in the presence of market frictions which complicate the instantaneous adjustment to the first‐order conditions. We suggest approximating the consumption streams of countries belonging to the risk sharing coalition in terms of a disequilibrium dynamic model embodying forward‐looking adjustment. Econometric methods for estimating and testing the model are discussed.…

关于《含单位根的门限自回归》的评论AI 解读

In this paper we revisit the results in Caner and Hansen (2001), where the authors obtained novel limiting distributions of Wald type test statistics for testing for the presence of threshold nonlinearities in autoregressive models containing unit roots. Using the same framework, we obtain a new formulation of the limiting distribution of the Wald statistic for testing for threshold effects, correcting an expression that appeared in the main theorem presented by Caner and…

低频波动模型的检验AI 解读

We develop a framework to assess how successfully standard time series models explain low-frequency variability of a data series. The low-frequency information is extracted by computing a finite number of weighted averages of the original data, where the weights are low-frequency trigonometric series. The properties of these weighted averages are then compared to the asymptotic implications of a number of common time series models. We apply the framework to twenty U.S.…

单位根假设检验的半参数功效包络AI 解读

This paper derives asymptotic power envelopes for tests of the unit root hypothesis in a zero-mean AR(1) model. The power envelopes are derived using the limits of experiments approach and are semiparametric in the sense that the underlying error distribution is treated as an unknown infinite-dimensional nuisance parameter. Adaptation is shown to be possible when the error distribution is known to be symmetric and to be impossible when the error distribution is unrestricted.…

非线性加性自回归模型的样条回拟合核平滑AI 解读

Application of nonparametric and semiparametric regression techniques to high-dimensional time series data has been hampered due to the lack of effective tools to address the “curse of dimensionality.” Under rather weak conditions, we propose spline-backfitted kernel estimators of the component functions for the nonlinear additive time series data that are both computationally expedient so they are usable for analyzing very high-dimensional time series, and theoretically…

一种简单、稳健且高功效的线性趋势检验AI 解读

In this paper we develop a simple test procedure for a linear trend which does not require knowledge of the form of serial correlation in the data, is robust to strong serial correlation, and has a standard normal limiting null distribution under either I(0) or I(1) shocks. In contrast to other available robust linear trend tests, our proposed test achieves the Gaussian asymptotic local power envelope in both the I(0) and I(1) cases. For near-I(1) errors our proposed…

稳健长期方差估计理论AI 解读

Long-run variance estimation can typically be viewed as the problem of estimating the scale of a limiting continuous time Gaussian process on the unit interval. A natural benchmark model is given by a sample that consists of equally spaced observations of this limiting process. The paper analyzes the asymptotic robustness of long-run variance estimators to contaminations of this benchmark model. It is shown that any equivariant long-run variance estimator that is consistent…

线性时间序列回归中单一突变日期的置信集AI 解读

This paper considers the problem of constructing confidence sets for the date of a single break in a linear time series regression. We establish analytically and by small sample simulation that the currently standard method in econometrics to construct such confidence intervals has a coverage rate far below nominal levels when breaks are of moderate magnitude. Given that breaks of moderate magnitude are a theoretically and empirically highly relevant phenomenon, we proceed…

持续期驱动长程依赖过程的渐近理论AI 解读

We consider processes with second order long range dependence resulting from heavy tailed durations. We refer to this phenomenon as duration-driven long range dependence (DDLRD), as opposed to the more widely studied linear long range dependence based on fractional differencing of an iid process. We consider in detail two specific processes having DDLRD, originally presented in Taqqu and Levy (1986), and Parke (1999). For these processes, we obtain the limiting distribution…

同期门限自回归模型：估计、检验与预测AI 解读

This paper proposes a contemporaneous smooth transition threshold autoregressive model (C-STAR) as a modification of the smooth transition threshold autoregressive model surveyed in Teräsvirta (1998), in which the regime weights depend on the ex ante probability that a latent regime-specific variable will exceed a threshold value. We argue that the contemporaneous model is well-suited to rational expectations applications (and pricing exercises), in that it allows the…

季节性单位根假设的有效检验AI 解读

In this paper we derive, under the assumption of Gaussian errors with known error covariance matrix, asymptotic local power bounds for seasonal unit root tests for both known and unknown deterministic scenarios and for an arbitrary seasonal aspect. We demonstrate that the optimal test of a unit root at a given spectral frequency behaves asymptotically independently of whether unit roots exist at other frequencies or not. We also develop modified versions of the optimal tests…

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条件异方差下的广义秩估计量AI 解读

In this paper, we extend the classical idea of Rank-estimation of parameters from homoscedastic problems to heteroscedastic problems. In particular, we define a class of rank estimators of the parameters associated with the conditional mean function of an autoregressive model through a three-steps procedure and then derive their asymp- totic distributions. The class of models considered includes Engel’s ARCH model and the threshold heteroscedastic model. The class of…