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日期精度:到日 2342 篇 · 到月 6077 篇 · 到年 470 篇 · 未提供 6 篇
Testing slope homogeneity in large panels
大规模面板中的斜率同质性检验
This paper proposes a modified version of Swamy’s test of slope homogeneity for panel data models where the cross section dimension (N) could be large relative to the time series dimension (T). We exploit the cross section dispersion of individual slopes weighted by their relative precision. Using Monte Carlo experiments, we show that the test has the correct size and satisfactory power in panels with strictly exogenous regressors for various combinations of N and T. For…
Optimal Bandwidth Selection in Heteroskedasticity–Autocorrelation Robust Testing
异方差与自相关稳健检验中的最优带宽选择
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…
Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models
多重变点与混合创新模型的高效贝叶斯推断
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…
Forecasting Using Bayesian and Information-Theoretic Model Averaging
贝叶斯与信息论模型平均在预测中的应用
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…
Robust Nonnested Testing and the Demand for Money
稳健非嵌套检验与货币需求
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…
Binomial Autoregressive Moving Average Models With an Application to U.S. Recessions
二项自回归移动平均模型及其在美国经济衰退中的应用
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…
Model-Based Clustering of Multiple Time Series
多条时间序列的模型聚类
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…
A Simple Test for Nonstationarity in Mixed Panels
混合面板非平稳性的简单检验
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…
Bayesian Analysis of the Output Gap
产出缺口的贝叶斯分析
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…
Potential Pitfalls in Determining Multiple Structural Changes With an Application to Purchasing Power Parity
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
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…
A Comparison of the Real-Time Performance of Business Cycle Dating Methods
商业周期定年方法实时表现的比较
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…
International dynamic risk sharing
国际动态风险分担
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.…
Structural breaks and GARCH models of exchange rate volatility
汇率波动率 GARCH 模型中的结构突变
Abstract We investigate the empirical relevance of structural breaks for GARCH models of exchange rate volatility using both in‐sample and out‐of‐sample tests. We find significant evidence of structural breaks in the unconditional variance of seven of eight US dollar exchange rate return series over the 1980–2005 period—implying unstable GARCH processes for these exchange rates—and GARCH(1,1) parameter estimates often vary substantially across the subsamples defined by the…
A unified approach to standardized‐residuals‐based correlation tests for GARCH‐type models
GARCH 类模型标准化残差相关检验的统一方法
Abstract In this paper, we propose a unified approach to generating standardized‐residuals‐based correlation tests for checking GARCH‐type models. This approach is valid in the presence of estimation uncertainty, is robust to various standardized error distributions, and is applicable to testing various types of misspecifications. By using this approach, we also propose a class of power‐transformed‐series (PTS) correlation tests that provides certain robustifications and…
Manipulability of Future-Independent Tests
不依赖未来的检验的可操纵性
The difficulties in properly anticipating key economic variables may encourage decision makers to rely on experts' forecasts. Professional forecasters, however, may not be reliable and so their forecasts must be empirically tested. This may induce experts to forecast strategically in order to pass the test. A test can be ignorantly passed if a false expert, with no knowledge of the data-generating process, can pass the test. Many tests that are unlikely to reject correct…
Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise
噪声下测度股票价格事后变差的已实现核设计
This paper shows how to use realized kernels to carry out efficient feasible inference on the ex post variation of underlying equity prices in the presence of simple models of market frictions. The weights can be chosen to achieve the best possible rate of convergence and to have an asymptotic variance which equals that of the maximum likelihood estimator in the parametric version of this problem. Realized kernels can also be selected to (i) be analyzed using endogenously…
Comment on: Threshold Autoregressions With a Unit Root
关于《含单位根的门限自回归》的评论
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…
Testing Models of Low-Frequency Variability
低频波动模型的检验
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.…
Semiparametric Power Envelopes for Tests of the Unit Root Hypothesis
单位根假设检验的半参数功效包络
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.…
Spline-backfitted kernel smoothing of nonlinear additive autoregression model
非线性加性自回归模型的样条回拟合核平滑
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…
A simple, robust and powerful test of the trend hypothesis
一种简单、稳健且高功效的线性趋势检验
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…
A theory of robust long-run variance estimation
稳健长期方差估计理论
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…
Confidence sets for the date of a single break in linear time series regressions
线性时间序列回归中单一突变日期的置信集
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…