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Who Does Not Respond in the Household Expenditure Survey

家庭支出调查中谁没有回应

A nonparametric multiple regression method, based on the extended Gini that depends on one parameter, v, is investigated. The parameter v enables production of infinite alternative linear approximations to the regression curve which differ in the weighting schemes applied to the slopes of the curve. The method allows the investigator to stress different sections of one independent variable while keeping the treatment of the other independent variables intact. As an…

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Marginal Comparisons With the Best and the Efficiency Measurement Problem

与最优总体的边际比较及效率测度问题

Consider a set of N populations ranked by an unknown scalar parameter, where a larger parameter value is better. An existing procedure, multiple comparisons with the best, constructs a set of upper and lower bounds for the N – 1 differences between the parameter value of the best population and the other populations, where these bounds hold jointly with a given probability. This article constructs the corresponding upper and lower bounds that hold marginally (for a single…

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Cromwell's Rule and the Role of the Prior in the Economic Metric

克伦威尔法则与经济意义度量中的先验作用

We show that using Bayesian decision theory to draw inference about the economic significance of a model requires careful specification of model uncertainty in the prior density. As an example, we use the Bayesian investor's portfolio allocation problem to show that failure to include probability point mass on the null hypothesis that returns are not predictable will overstate the economic significance of the predictive model. The dissonance between the statistical and…

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A Simulation-Based Specification Test for Diffusion Processes

基于模拟的扩散过程模型设定检验

This article makes two contributions. First, we outline a simple simulation-based framework for constructing conditional distributions for multifactor and multidimensional diffusion processes, for the case where the functional form of the conditional density is unknown. The distributions can be used, for example, to form predictive confidence intervals for time period t + τ, given information up to period t. Second, we use the simulation-based approach to construct a test…

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The Markov-Switching Multifractal Model of Asset Returns

资产收益的马尔可夫切换多重分形模型

Multifractal processes have recently been proposed as a new formalism for modeling the time series of returns in finance. The major attraction of these processes is their ability to generate various degrees of long memory in different powers of returns—a feature that has been found in virtually all financial data. Initial difficulties stemming from nonstationarity and the combinatorial nature of the original model have been overcome by the introduction of an iterative…

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True or Spurious Long Memory? A New Test

真实还是伪长记忆?一种新检验

It is well known that long memory characteristics observed in data can be generated by nonstationary structural-break or slow regime switching models. We propose a statistical test to distinguish between true long memory and spurious long memory based on invariance of the long memory parameter for temporal aggregates of the process under the null of true long memory. Geweke Porter-Hudak estimates of the long memory parameter obtained from different temporal aggregates of the…

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VARMA versus VAR for Macroeconomic Forecasting

宏观经济预测中的 VARMA 与 VAR 比较

In this article, we argue that there is no compelling reason for restricting the class of multivariate models considered for macroeconomic forecasting to vector autoregressive (VAR) models, given the recent advances in vector autoregressive moving average (VARMA) modeling methodology and improvements in computing power. To support this claim, we use real macroeconomic data, and show that VARMA models forecast macroeconomic variables more accurately than VARs.

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Explaining and Forecasting Online Auction Prices and Their Dynamics Using Functional Data Analysis

用函数型数据分析解释和预测在线拍卖价格及其动态

Online auctions have become increasingly popular in recent years, and as a consequence there is a growing body of empirical research on this topic. Most of that research treats data from online auctions as cross-sectional, and consequently ignores the changing dynamics that occur during an auction. In this article we take a different look at online auctions and propose to study an auction's price evolution and associated price dynamics. Specifically, we develop a dynamic…

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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…

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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…

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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…

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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…

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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…

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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…

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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…

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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…

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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…

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Foreign Technology Transfer and Productivity

外国技术转移与生产率

We examine the causal effects of alternative foreign technology transfer channels on the productivity of Turkish manufacturing plants, using propensity score matching techniques that limit implicit assumptions about plant homogeneity and self selection imbedded in standard estimates of such effects. We find positive impacts of technology transfer through foreign direct investment (FDI), exporting, and importing on both total factor and labor productivity, with FDI dominating…

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Moment-Based Copula Tests for Financial Returns

基于矩条件的金融收益 Copula 检验

We propose a class of moment-based tests for copulas in a parametric multivariate dynamic context for financial returns. The proposed method takes into account the effect of estimation uncertainty. This effect is quite important but often is ignored in related studies. Our method can be applied to generate various tests to detect copula misspecification in different directions. In particular, on the basis of the conditional probabilities of quantile exceedances (Kendall's…

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Estimation of Fractional Dependent Variables in Dynamic Panel Data Models With an Application to Firm Dividend Policy

动态面板中分数型因变量的估计及其在企业股利政策中的应用

Fractional dependent variables and models with state dependence arise in many economic applications; however, estimating models with fractional dependent variables is complicated by the presence of two corner solution outcomes. When coupled with a dynamic panel data setting, estimating quantities of interest can be quite complex or computationally difficult. This article demonstrates a method for estimating fractional response variables, which is easy to implement, and…

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On the Role of Risk Premia in Volatility Forecasting

风险溢价在波动率预测中的作用

I explain why at-the-money implied volatility is a biased and inefficient forecast of future realized volatility using the insights from the empirical option-pricing literature. First, I explain how the risk premia, which manifest themselves through disparity between objective and risk-neutral probability measures, lead to the disparity between realized and implied volatilities. Second, I show that this disparity is a function of the latent spot volatility, which I estimate…

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Local Whittle Analysis of Stationary Fractional Cointegration and the Implied–Realized Volatility Relation

平稳分数协整的局部 Whittle 分析及隐含与已实现波动率的关系

I consider local Whittle analysis of a stationary fractionally cointegrated model. The local Whittle quasi maximum likelihood estimator is proposed to jointly estimate the integration orders of the regressors, the integration order of the errors, and the cointegration vector. The proposed estimator is semiparametric in the sense that it employs local assumptions on the joint spectral density matrix of the regressors and the errors near the zero frequency. I show that the…

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Testing for Neglected Nonlinearity in Long-Memory Models

长记忆模型中遗漏非线性的检验

This article constructs tests for the presence of nonlinearity of unknown form in addition to a fractionally integrated, long-memory component in a time series process. The tests are based on artificial neural network approximations and do not restrict the parametric form of the nonlinearity. Some theoretical results for the new tests are obtained, and detailed simulation evidence on the power of the tests is presented. The new methodology is then applied to a wide variety…

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