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Estimation and Inference in Two-Step Econometric Models

两步计量模型中的估计与推断

A commonly used procedure in a wide class of empirical applications is to impute unobserved regressors, such as expectations, from an auxiliary econometric model. This two-step (T-S) procedure fails to account for the fact that imputed regressors are measured with sampling error, so hypothesis tests based on the estimated covariance matrix of the second-step estimator are biased, even in large samples. We present a simple yet general method of calculating asymptotically…

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Bayesian Analysis of Stochastic Volatility Models

随机波动率模型的贝叶斯分析

New techniques for the analysis of stochastic volatility models in which the logarithm of conditional variance follows an autoregressive model are developed. A cyclic Metropolis algorithm is used to construct a Markov-chain simulation tool. Simulations from this Markov chain coverage in distribution to draws from the posterior distribution enabling exact finite-sample inference. The exact solution to the filtering/smoothing problem of inferring about the unobserved variance…

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Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis

大崩盘、石油价格冲击与单位根假说的进一步证据

Perron (1989) has carried out tests of the unit root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil price shock. Here a variation of Perron's test is considered in which the break point is estimated rather than fixed. The asymptotic distribution of the "estimated break point" test statistic is determined and the data considered by Perron are reanalyzed. The authors find…

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Tests for Unit Roots

单位根检验

Recent work by Said and Dickey (1984, 1985), Phillips (1987), and Phillips and Perron (1988) examines tests for unit roots in the autoregressive part of mixed autoregressive integrated moving average models (tests for stationarity). Monte Carlo experiments show that these unit-root tests have different finite-sample distributions from the unit-root tests developed by Fuller (1976) and Dickey and Fuller (1979, 1981) for autoregressive processes. In particular, the tests…

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Estimation for Autoregressive Time Series With a Root Near 1

根接近1的自回归时间序列参数估计

Estimators for the parameters of autoregressive time series are compared, emphasizing processes with a unit root or a root close to 1. The approximate bias of the sum of the autoregressive coefficients is expressed as a function of the test for a unit root. This expression is used to construct an estimator that is nearly unbiased for the parameter of the first-order scalar process. The estimator for the first-order process has a mean squared error that is about 40% of that…

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Bias From Classical and Other Forms of Measurement Error

经典及其他形式测量误差导致的偏差

We consider the implications of an alternative to the classical measurement-error model, in which the observed, mismeasured data are optimal predictions of the true values, given some information set. In this model, any measurement error is uncorrelated with the reported value and, by necessity, correlated with the true value of interest. In a regression model, such measurement error in the regressor does not lead to bias, whereas measurement error in the dependent variable…

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Markov Chain Monte Carlo Analysis of Correlated Count Data

相关计数数据的马尔可夫链蒙特卡洛分析

This article is concerned with the analysis of correlated count data. A class of models is proposed in which the correlation among the counts is represented by correlated latent effects. Special cases of the model are discussed and a tuned and efficient Markov chain Monte Carlo algorithm is developed to estimate the model under both multivariate normal and multivariate-t assumptions on the latent effects. The methods are illustrated with two real data examples of six and…

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Markov Regime Switching and Unit-Root Tests

马尔可夫状态转换与单位根检验

We investigate the power and size performance of unit-root tests when the data undergo Markov regime switching. All tests, including those robust to a single break in trend growth rate, have low power against a process with a Markov-switching trend. Under the null hypothesis, we find that previously documented size distortions in Dickey-Fuller-type tests caused by a single break in trend growth rate or variance do not generalize to most parameterizations of Markov switching…

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Testing Density Forecasts, With Applications to Risk Management

密度预测检验及其在风险管理中的应用

The forecast evaluation literature has traditionally focused on methods of assessing point forecasts. However, in the context of many models of financial risk, interest centers on more than just a single point of the forecast distribution. For example, value-at-risk models that are currently in extremely wide use form interval forecasts. Many other important financial calculations also involve estimates not summarized by a point forecast. Although some techniques are…

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Overcoming Nonadmissibility in ARIMA-Model-Based Signal Extraction

克服基于 ARIMA 模型的信号提取中分解不可容许的问题

We analyze the situation in which the decomposition of a time series into orthogonal balanced components as performed by the AR IMA-model-based (AMB) method is nonadmissible. We show that considering top-heavy models for the components can solve the problem. The top-heavy decomposition is derived and the improvement achieved is illustrated by an application to a class of models often encountered in practice. Two empirical applications allow us to draw a comparison with the…

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The Econometrics of Rational Addiction

理性成瘾的计量经济学

This article reexamines the econometric estimation of rational-addiction models considered by Becker, Grossman, and Murphy (BGM) for cigarette consumption. The rational-addiction model poses a number of additional econometric difficulties including endogeneity due to the presence of leads and lags of the dependent variable and serial correlation in the disturbances. BGM considered a fixed-effects two-stage least squares (2SLS) estimator. It is well known that this estimator…

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Structural Estimates of the U.S. Sacrifice Ratio

美国牺牲率的结构估计

This article investigates the statistical properties of the U.S. sacrifice ratio--the cumulative output loss arising from a permanent reduction in inflation. We derive estimates of the sacrifice ratio from three structural vector autoregression models and then conduct a series of simulation exercises to analyze their sampling distribution. We obtain point estimates of the sacrifice ratio that are consistent with results reported in earlier studies. However, the estimates are…

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Binary Choice With Binary Endogenous Regressors in Panel Data

面板数据中含二元内生解释变量的二元选择模型

This article considers the estimation of the causal effect of fertility on female-labor-force participation equations. My main concern is to examine two considerations, the endogeneity of fertility and the impact of controlling for unobserved heterogeneity and for predetermined existing children. Using PSID data, a switching binary panel-data model that accounts for selectivity bias as well as for other forms of time-invariant unobserved heterogeneity is estimated.…

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Interpreting Instrumental Variables Estimates of the Returns to Schooling

如何解释教育回报的工具变量估计

This article synthesizes economic insights from theoretical models of schooling choice based on individual benefits and econometric work interpreting instrumental variables estimates as weighted averages of individual-specific causal effects. Linkages are illustrated using college proximity to instrument for schooling. After characterizing groups differentially affected by the instrument according to family background, 1 directly compute weights underlying estimation of the…

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Spatially Disaggregated Real Estate Indices

按空间细分地区构建房地产指数

A spatial–temporal Markov random-field model is used to produce indices for residential real estate from repeat home sale data. A set of regions is represented by a graph in which neighboring regions are linked. This graph, repeated consecutively a number of times, with each region linked to the same region at adjacent times, defines a spatial–temporal graph that connects regions over space and time in which each node represents a region at a particular time. An index is…

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Rank Tests for Nonlinear Cointegration

非线性协整的秩检验

A test procedure based on ranks is suggested to test for nonlinear cointegration. For two (or more) time series it is assumed that monotonic transformations exist such that the normalized series can asymptotically be represented as Wiener processes. Rank-test procedures based on the difference between the sequences of ranks are suggested. If there is no cointegration between the time series, the sequences of ranks tend to diverge, whereas under cointegration the sequences of…

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