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Automatic estimation of multivariate spectra via smoothing splines

通过平滑样条自动估计多变量谱

The classical method for estimating the spectral density of a multivariate time series is to first calculate the periodogram, and then smooth it to obtain a consistent estimator. Typically, to ensure the estimate is positive definite, all the elements of the periodogram are smoothed the same way. There are, however, many situations for which different components of the spectral matrix have different degrees of smoothness, and hence require different smoothing parameters in…

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A generalized threshold mixed model for analyzing nonnormal nonlinear time series, with application to plague in Kazakhstan

分析非正态非线性时间序列的广义阈值混合模型:哈萨克斯坦鼠疫应用

We introduce the generalized threshold mixed model for piecewise-linear stochastic regression with possibly nonnormal time-series data. It is assumed that the conditional probability distribution of the response variable belongs to the exponential family, and the conditional mean response is linked to some piecewise-linear stochastic regression function. We study the particular case where the response variable equals zero in the lower regime. Some large-sample properties of…

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Regression coefficient and autoregressive order shrinkage and selection via the lasso

利用 lasso 收缩与选择回归系数及自回归阶数

Summary The least absolute shrinkage and selection operator (‘lasso’) has been widely used in regression shrinkage and selection. We extend its application to the regression model with autoregressive errors. Two types of lasso estimators are carefully studied. The first is similar to the traditional lasso estimator with only two tuning parameters (one for regression coefficients and the other for autoregression coefficients). These tuning parameters can be easily calculated…

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Nonparametric estimation in a nonlinear cointegration type model

非线性协整型模型中的非参数估计

We derive an asymptotic theory of nonparametric estimation for a time series regression model Zt=f(Xt)+Wt, where {Xt} and {Zt} are observed nonstationary processes and {Wt} is an unobserved stationary process. In econometrics, this can be interpreted as a nonlinear cointegration type relationship, but we believe that our results are of wider interest. The class of nonstationary processes allowed for {Xt} is a subclass of the class of null recurrent Markov chains. This…

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Convergence rates of posterior distributions for noniid observations

非独立同分布观测下后验分布的收敛速度

We consider the asymptotic behavior of posterior distributions and Bayes estimators based on observations which are required to be neither independent nor identically distributed. We give general results on the rate of convergence of the posterior measure relative to distances derived from a testing criterion. We then specialize our results to independent, nonidentically distributed observations, Markov processes, stationary Gaussian time series and the white noise model. We…

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Do High Birth Rates Hamper Economic Growth?

高出生率会阻碍经济增长吗?

This paper examines the impact of the birth rate on economic growth by using a panel data set of 28 provinces in China over twenty years. Because China's one-child policy applied only to the Han Chinese but not to minorities, this unique affirmative policy allows us to use the proportion of minorities in a province as an instrumental variable to identify the causal effect of the birth rate on economic growth. We find that the birth rate has a negative impact on economic…

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AN IMPROVED GENERALIZED SPECTRAL TEST FOR CONDITIONAL MEAN MODELS IN TIME SERIES WITH CONDITIONAL HETEROSKEDASTICITY OF UNKNOWN FORM

未知形式条件异方差下时间序列条件均值模型的改进广义谱检验

Dynamic economic theories usually have implications on and only on the conditional mean dynamics of economic processes. Using a generalized spectral derivative approach, Hong and Lee (2005, Review of Economic Studies 72, 499–541) recently proposed a new class of omnibus nonparametric specification tests for linear and nonlinear time series conditional mean models, where the dimension of the conditioning information set may be infinite. The tests can detect a wide range of…

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WIENER–KOLMOGOROV FILTERING, FREQUENCY-SELECTIVE FILTERING, AND POLYNOMIAL REGRESSION

维纳–柯尔莫哥洛夫滤波、频率选择滤波与多项式回归

Adaptations of the classical Wiener–Kolmogorov filters are described that enable them to be applied to short nonstationary sequences. Alternative filtering methods that operate in the time domain and the frequency domain are described. The frequency-domain methods have the advantage of allowing components of the data to be separated along sharp dividing lines in the frequency domain, without incurring any leakage. The paper contains a novel treatment of the start-up problem…

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LOCAL LINEAR FITTING UNDER NEAR EPOCH DEPENDENCE

近历元依赖条件下的局部线性拟合

Local linear fitting of nonlinear processes under strong (i.e., α-) mixing conditions has been investigated extensively. However, it is often a difficult step to establish the strong mixing of a nonlinear process composed of several parts such as the popular combination of autoregressive moving average (ARMA) and generalized autoregressive conditionally heteroskedastic (GARCH) models. In this paper we develop an asymptotic theory of local linear fitting for near epoch…

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PERMANENT-TRANSITORY DECOMPOSITIONS UNDER WEAK EXOGENEITY

弱外生性下的永久—暂时分解

This note shows that the orthogonal shocks obtained by imposing a recursive structure on the contemporaneous impacts of the errors in a vector-error correction model (VECM) are related to the orthogonal permanent-transitory shocks in a Gonzalo and Ng (2001, Journal of Economic Dynamics and Control 25, 1527–1546) decomposition provided some of the variables in the system are weakly exogenous. Specifically, when there are as many weakly exogenous variables as common trends and…

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COMMON STOCHASTIC TRENDS AND AGGREGATION IN HETEROGENEOUS PANELS

异质面板中的共同随机趋势与聚合

In nonstationary heterogeneous panels where the number of units is finite and where each unit cointegrates, a large number of conditions needs to be satisfied for cointegration to be preserved in the aggregate relationship. In reality, the conditions most likely will not hold. This paper takes a closer look at what happens when the conditions are violated. In this case, the question of whether an aggregate relationship is observationally equivalent to a cointegrating…

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Common Periodic Correlation Features and the Interaction of Stocks and Flows in Daily Airport Data

共同周期相关特征与机场日度数据中的存量和流量互动

We propose the multivariate representation of univariate and bivariate (possibly nonstationary) periodic models as a benchmark for the imposition of common periodic correlation (CPC) feature restrictions to obtain parameter parsimony. CPCs are short-run common dynamic features that co-vary across the different days of the week and possibly also across weeks and that can be common across different time series. We also show how periodic models can be used to describe…

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A Note on Common Cycles, Common Trends, and Convergence

关于共同周期、共同趋势与收敛的札记

This article compares and contrasts structural time series models and the common features methodology. The way in which trends are handled is highlighted by describing a recent structural time series model that allows convergence to a common growth path. Postsample data are used to test its forecasting performance for income per head in U.S. regions. A test for common cycles is proposed, its asymptotic distribution is given, and small-sample properties are studied by Monte…

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Co-Breaking

协同结构突变(Co-breaking)

This article has two aims. First, we provide a synopsis of the literature on co-breaking that has developed in several, seemingly disconnected, strands. We establish a consistent terminology, collect theoretical results, delimit co-breaking to cointegration and common features, and review recent contributions to co-breaking regressions and the budding analysis of co-breaking rank. Second, we present new results in the field, particularly, on the importance of co-breaking for…

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Determining the Number of Primitive Shocks in Factor Models

因子模型中原始冲击数量的确定

A widely held but untested assumption underlying macroeconomic analysis is that the number of shocks driving economic fluctuations, q, is small. In this article we associate q with the number of dynamic factors in a large panel of data. We propose a methodology to determineq without having to estimate the dynamic factors. We first estimate a VAR in r static factors, where the factors are obtained by applying the method of principal components to a large panel of data, then…

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A More Timely and Useful Index of Leading Indicators

更及时、更有用的先行指标指数

Effectively predicting cyclical movements in the economy is a major challenge. The U.S. leading index (LI) has long been used to analyze and predict economic fluctuations. We describe and test a new procedure for making the LI more timely. The new LI significantly outperforms its older counterpart. It offers substantial gains in real-time, out-of-sample forecasts of changes in aggregate economic activity (real GDP, the index of coincident indicators, and industrial…

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Consistent Estimation of the Number of Dynamic Factors in a Large N and T Panel

大 N、大 T 面板中动态因子数量的一致估计

Bai and Ng proposed a consistent estimator for the number of static factors in a large N and T approximate factor model. This article shows how the Bai–Ng estimator can be modified to consistently estimate the number of dynamic factors in a restricted dynamic factor model. The modification is straightforward: The standard Bai–Ng estimator is applied to residuals obtained by projecting the observed data onto lagged values of principal-components estimates of the static…

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Exploring the international linkages of the euro area: a global VAR analysis

欧元区的国际联系:全球 VAR 分析

Abstract This paper presents a quarterly global model combining individual country vector error‐correcting models in which the domestic variables are related to the country‐specific foreign variables. The global VAR (GVAR) model is estimated for 26 countries, the euro area being treated as a single economy, over the period 1979–2003. It advances research in this area in a number of directions. In particular, it provides a theoretical framework where the GVAR is derived as an…

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Nonlinear autoregressive leading indicator models of output in G‐7 countries

七国集团产出的非线性自回归领先指标模型

Abstract This paper studies linear and nonlinear autoregressive leading indicator models of business cycles in G‐7 countries. Our models use the spread between short‐term and long‐term interest rates as leading indicators for GDP. We examine data admissibility by determining whether these models have the ability to produce time series with classical cycles that resemble the observed classical cycles in the data, and then we ask whether this data admissibility lends itself to…

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Codependence in cointegrated autoregressive models

协整自回归模型中的共同依赖周期

Abstract This paper investigates codependent cycles, i.e., transitory components that react to common stimuli in a similar, although not necessarily synchronous fashion. Unlike previous studies, the methodology of this paper allows FIML estimation of the restricted VAR/VECM and therefore the extraction of the unobserved codependent cyclical components via a Beveridge‐Nelson decomposition. It is further shown that the number and order of cofeature combinations that yield the…

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An evaluation of the forecasts of the federal reserve: a pooled approach

美联储预测的评价:跨预测期限的合并方法

Abstract The Federal Reserve Greenbook forecasts of real GDP, inflation and unemployment are analysed for the period 1974–1997. We consider whether these forecasts exhibit systematic bias, and whether efficient use is made of information, that is, whether revisions to these forecasts over time are predictable. Rather than analyse the forecasts separately for each horizon of interest, we discuss and implement methods that pool information over horizons. We conclude that there…

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A Nonstationary Negative Binomial Time Series With Time-Dependent Covariates

含时变协变量的非平稳负二项时间序列模型

Boston Harbor has a history of poor water quality, including contamination by enteric pathogens. We conduct a statistical analysis of data collected by the Massachusetts Water Resources Authority (MWRA) between 1996 and 2002 to evaluate the effects of court-mandated improvements in sewage treatment. Motivated by the ineffectiveness of standard Poisson mixture models and their zero-inflated counterparts, we propose a new negative binomial model for time series of Enterococcus…

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