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Revealing the preferences of the US Federal Reserve

揭示美联储的政策偏好

Abstract We use Bayesian methods to estimate changes in US post‐war monetary policy in the Smets and Wouters model. We perform the estimations by allowing for a break in monetary policy at the time of Volcker's appointment as chairman. This enables us to capture changes in the monetary policy regime introduced by Volcker during the Volcker–Greenspan period. We find support for the assumption that monetary policy in the Volcker–Greenspan period performed optimally under…

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Modelling the distribution of the cluster maxima of exceedances of subasymptotic thresholds

非渐近高阈值超越簇最大值的分布建模

A standard approach to model the extreme values of a stationary process is the peaks over threshold method, which consists of imposing a high threshold, identifying clusters of exceedances of this threshold and fitting the maximum value from each cluster using the generalized Pareto distribution. This approach is strongly justified by underlying asymptotic theory. We propose an alternative model for the distribution of the cluster maxima that accounts for the subasymptotic…

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Testing for a unit root in a random coefficient panel data model

随机系数面板模型中的单位根检验

This paper proposes new unit root tests in the context of a random autoregressive coefficient panel data model, in which the null of a unit root corresponds to the joint restriction that the autoregressive coefficient has unit mean and zero variance. The asymptotic distributions of the test statistics are derived and simulation results are provided to suggest that they perform very well in small samples.

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On the least squares estimation of multiple-regime threshold autoregressive models

多区制门槛自回归模型的最小二乘估计

This paper studies the least squares estimator (LSE) of the multiple-regime threshold autoregressive (TAR) model and establishes its asymptotic theory. It is shown that the LSE is strongly consistent. When the autoregressive function is discontinuous over each threshold, the estimated thresholds are n-consistent and asymptotically independent, each of which converges weakly to the smallest minimizer of a one-dimensional two-sided compound Poisson process. The remaining…

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Unit root testing under a local break in trend

局部趋势突变下的单位根检验

Recent approaches to testing for a unit root when uncertainty exists over the presence and timing of a trend break employ break detection methods, so that a with-break unit root test is used only if a break is detected by some auxiliary statistic. While these methods achieve near asymptotic efficiency in both fixed trend break and no trend break environments, in finite samples pronounced “valleys” in the power functions of the tests (when mapped as functions of the break…

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The dynamics of US inflation: Can monetary policy explain the changes?

美国通胀动态:货币政策能否解释其变化?

We investigate the relationship between monetary policy and inflation dynamics in the US using a medium scale structural model. The specification is estimated with Bayesian techniques and fits the data reasonably well. Policy shocks account for a part of the decline in inflation volatility; they have been less effective in triggering inflation responses over time and qualitatively account for the rise and fall in the level of inflation. A number of structural parameter…

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Estimation for spatial dynamic panel data with fixed effects: The case of spatial cointegration

固定效应空间动态面板的估计:空间协整情形

Yu et al. (2008) establish asymptotic properties of quasi-maximum likelihood estimators for a stable spatial dynamic panel model with fixed effects when both the number of individuals n and the number of time periods T are large. This paper investigates unstable cases where there are unit roots generated by temporal and spatial correlations. We focus on the spatial cointegration model where some eigenvalues of the data generating process are equal to 1 and the outcomes of…

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Block Bootstraps for Time Series With Fixed Regressors

固定回归变量时间序列的区块自助法

This article examines block bootstrap methods in linear regression models with weakly dependent error variables and nonstochastic regressors. Contrary to intuition, the tapered block bootstrap (TBB) with a smooth taper not only loses its superior bias properties but may also fail to be consistent in the regression problem. A similar problem, albeit at a smaller scale, is shown to exist for the moving and the circular block bootstrap (MBB and CBB, respectively). As a remedy,…

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Modeling Waves of Extreme Temperature: The Changing Tails of Four Cities

极端温度波动建模:四座城市变化中的尾部

Heat waves are a serious threat to society, the environment, and the economy. Estimates of the recurrence probabilities of heat waves may be obtained following the successful modeling of daily maximum temperature, but working with the latter is difficult as we have to recognize, and allow for, not only a time trend but also seasonality in the mean and in the variability, as well as serial correlation. Furthermore, as the extreme values of daily maximum temperature have a…

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Using Conditional Kernel Density Estimation for Wind Power Density Forecasting

利用条件核密度估计进行风电功率密度预测

Of the various renewable energy resources, wind power is widely recognized as one of the most promising. The management of wind farms and electricity systems can benefit greatly from the availability of estimates of the probability distribution of wind power generation. However, most research has focused on point forecasting of wind power. In this article, we develop an approach to producing density forecasts for the wind power generated at individual wind farms. Our…

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Identification and frequency domain quasi-maximum likelihood estimation of linearized dynamic stochastic general equilibrium models

线性化动态随机一般均衡模型的识别与频域准极大似然估计

This paper considers issues related to identification, inference, and computation in linearized dynamic stochastic general equilibrium (DSGE) models. We first provide a necessary and sufficient condition for the local identification of the structural parameters based on the (first and) second order properties of the process. The condition allows for arbitrary relations between the number of observed endogenous variables and structural shocks, and is simple to verify. The…

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Simultaneous confidence bands for Yule–Walker estimators and order selection

Yule–Walker估计量的同时置信带与阶数选择

Let {Xk, k ∈ ℤ} be an autoregressive process of order q. Various estimators for the order q and the parameters Θq = (θ1, …, θq)T are known; the order is usually determined with Akaike’s criterion or related modifications, whereas Yule–Walker, Burger or maximum likelihood estimators are used for the parameters Θq. In this paper, we establish simultaneous confidence bands for the Yule–Walker estimators θ̂i; more precisely, it is shown that the limiting distribution of…

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Covariance matrix estimation for stationary time series

平稳时间序列的协方差矩阵估计

We obtain a sharp convergence rate for banded covariance matrix estimates of stationary processes. A precise order of magnitude is derived for spectral radius of sample covariance matrices. We also consider a thresholded covariance matrix estimator that can better characterize sparsity if the true covariance matrix is sparse. As our main tool, we implement Toeplitz [Math. Ann. 70 (1911) 351–376] idea and relate eigenvalues of covariance matrices to the spectral densities or…

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Statistical analysis of factor models of high dimension

高维因子模型的统计分析

This paper considers the maximum likelihood estimation of factor models of high dimension, where the number of variables (N) is comparable with or even greater than the number of observations (T). An inferential theory is developed. We establish not only consistency but also the rate of convergence and the limiting distributions. Five different sets of identification conditions are considered. We show that the distributions of the MLE estimators depend on the identification…

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Unit root tests for panel data with AR(1) errors and small T

具有AR(1)误差和短时间维度的面板单位根检验

We propose unit root tests for panel data with a small number of time periods, T, and increments that follow an AR(1) process under the null. The model is a fixed‐effect panel version of the augmented Dickey–Fuller regression of order 1. Individual‐specific linear trends may also be included. The test statistics are t‐type statistics based on least‐squares estimates from which the Nickell bias is removed. Their limiting distributions (for an increasing number of independent…

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Testing for common trends in semi‐parametric panel data models with fixed effects

固定效应半参数面板模型的共同趋势检验

This paper proposes a non‐parametric test for common trends in semi‐parametric panel data models with fixed effects based on a measure of non‐parametric goodness‐of‐fit (R2). We first estimate the model under the null hypothesis of common trends by the method of profile least squares, and obtain the augmented residual which consistently estimates the sum of the fixed effect and the disturbance under the null. Then we run a local linear regression of the augmented residuals…

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Break point estimators for a slope shift: levels versus first differences

斜率变化的断点估计:水平模型与一阶差分模型

This paper analyses two break point estimators: one for a univariate slope‐shift model under unit root errors, the other for its first difference (a mean shift model). The asymptotic theory is developed for the estimators under a specific Pitman drift, assuming the break magnitude is within a T−1/2 neighbourhood of zero. Compared to the existing asymptotics assuming a fixed break magnitude or a shrinking one converging at a slower rate than T1/2, the limiting distributions…

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Robust forecast combinations

稳健预测组合

Forecast outliers commonly occur in economic, financial, and other areas of forecasting applications. In the literature of forecast combinations, there have been only a few studies exploring how to deal with outliers. In this work, we propose two robust combining methods based on the AFTER algorithm (Yang, 2004a). Our approach utilizes robust loss functions in order to reduce the influence of outliers. Oracle inequalities for certain versions of these methods are obtained,…

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Distributional Tests in Multivariate Dynamic Models with Normal and Student- t Innovations

具有正态与Student-t新息的多元动态模型分布检验

We derive Lagrange multiplier and likelihood ratio specification tests for the null hypotheses of multivariate normal and Student-t innovations using the generalized hyperbolic distribution as our alternative hypothesis. We decompose the corresponding Lagrange multiplier-type tests into skewness and kurtosis components. We also obtain more powerful one-sided Kuhn-Tucker versions that are equivalent to the likelihood ratio test, whose asymptotic distribution we provide.…

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NULL RECURRENT UNIT ROOT PROCESSES

零常返单位根过程

The classical nonstationary autoregressive models are both linear and Markov. They include unit root and cointegration models. A possible nonlinear extension is to relax the linearity and at the same time keep general properties such as nonstationarity and the Markov property. A null recurrent Markov chain is nonstationary, and β -null recurrence is of vital importance for statistical inference in nonstationary Markov models, such as, e.g., in nonparametric estimation in…

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ANOTHER NUMERICAL METHOD OF FINDING CRITICAL VALUES FOR THE ANDREWS STABILITY TEST

计算Andrews稳定性检验临界值的另一种数值方法

We propose a method, alternative to that of Estrella (2003, Econometric Theory 19, 1128–1143), of obtaining exact asymptotic p -values and critical values for the popular Andrews (1993, Econometrica 61, 821–856) test for structural stability. The method is based on inverting an integral equation that determines the intensity of crossing a boundary by the asymptotic process underlying the test statistic. Further integration of the crossing intensity yields a p -value. The…

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DISCRETE TIME REPRESENTATION OF CONTINUOUS TIME ARMA PROCESSES

连续时间ARMA过程的离散时间表示

This paper derives exact discrete time representations for data generated by a continuous time autoregressive moving average (ARMA) system with mixed stock and flow data. The representations for systems comprised entirely of stocks or of flows are also given. In each case the discrete time representations are shown to be of ARMA form, the orders depending on those of the continuous time system. Three examples and applications are also provided, two of which concern the…

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TESTING FOR THE MARKOV PROPERTY IN TIME SERIES

时间序列马尔可夫性质的检验

The Markov property is a fundamental property in time series analysis and is often assumed in economic and financial modeling. We develop a new test for the Markov property using the conditional characteristic function embedded in a frequency domain approach, which checks the implication of the Markov property in every conditional moment (if it exists) and over many lags. The proposed test is applicable to both univariate and multivariate time series with discrete or…

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Testing for common trends in semiparametric panel data models with fixed effects

固定效应半参数面板模型的共同趋势检验

This paper proposes a non‐parametric test for common trends in semi‐parametric panel data models with fixed effects based on a measure of non‐parametric goodness‐of‐fit (R2). We first estimate the model under the null hypothesis of common trends by the method of profile least squares, and obtain the augmented residual which consistently estimates the sum of the fixed effect and the disturbance under the null. Then we run a local linear regression of the augmented residuals…

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