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COMPARISON OF MODEL AVERAGING TECHNIQUES: ASSESSING GROWTH DETERMINANTS

模型平均方法比较:评估经济增长的决定因素

SUMMARY This paper investigates the replicability of three important studies on growth theory uncertainty that employed Bayesian model averaging tools. We compare these results with estimates obtained using alternative, recently developed model averaging techniques. Overall, we successfully replicate all three studies, find that the sign and magnitude of these new estimates are reasonably close to those produced via traditional Bayesian methods and deploy a novel strategy to…

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INDIVIDUAL VERSUS AGGREGATE INCOME ELASTICITIES FOR HETEROGENEOUS POPULATIONS

异质人群的个体与总体需求收入弹性

SUMMARY This paper deals with different concepts of income elasticities of demand for a heterogeneous population and the relationship between individual and aggregate elasticities. In general, the aggregate elasticity is not equal to the mean of individual elasticities. The difference depends on the heterogeneity of the population and is quantified by a covariance term. Sign and magnitude of this term are determined by an empirical analysis based on the UK Family Expenditure…

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A PANEL DATA APPROACH FOR PROGRAM EVALUATION: MEASURING THE BENEFITS OF POLITICAL AND ECONOMIC INTEGRATION OF HONG KONG WITH MAINLAND CHINA

项目评估的面板数据方法:衡量香港与内地政治及经济融合的收益

SUMMARY We propose a simple‐to‐implement panel data method to evaluate the impacts of social policy. The basic idea is to exploit the dependence among cross‐sectional units to construct the counterfactuals. The cross‐sectional correlations are attributed to the presence of some (unobserved) common factors. However, instead of trying to estimate the unobserved factors, we propose to use observed data. We use a panel of 24 countries to evaluate the impact of political and…

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A RANK‐ORDERED LOGIT MODEL WITH UNOBSERVED HETEROGENEITY IN RANKING CAPABILITIES

考虑排序能力不可观测异质性的排序 Logit 模型

Abstract To study preferences, respondents to a survey are usually asked to select their most preferred option from a set. Preferences can be estimated more efficiently if respondents are asked to rank all alternatives. When some respondents are unable to perform the ranking task, using the complete ranking may lead to a substantial bias. We introduce a model which endogenously describes the ranking capabilities of individuals. Estimated preferences based on this model are…

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WEIGHTED SMOOTH TRANSITION REGRESSIONS

加权平滑转换回归

SUMMARY A new procedure is proposed for modelling nonlinearity of a smooth transition form, by allowing the transition variable to be a weighted function of lagged observations. This function depends on two unknown parameters and requires specification of the maximum lag only. Nonlinearity testing for this specification uses a search over a plausible set of weight function parameters, combined with bootstrap inference. Finite‐sample results show that the recommended wild…

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BAYESIAN MODEL SELECTION AND FORECASTING IN NONCAUSAL AUTOREGRESSIVE MODELS

非因果自回归模型中的贝叶斯模型选择与预测

SUMMARY In this paper, we propose a Bayesian estimation and forecasting procedure for noncausal autoregressive (AR) models. Specifically, we derive the joint posterior density of the past and future errors and the parameters, yielding predictive densities as a by‐product. We show that the posterior model probabilities provide a convenient model selection criterion in discriminating between alternative causal and noncausal specifications. As an empirical application, we…

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The impact of data revisions on the robustness of growth determinants—a note on ‘determinants of economic growth: Will data tell?’

数据修订如何影响增长决定因素的稳健性:一则回应

SUMMARY Ciccone and Jarociński ( American Economic Journal: Macroeconomics 2010; 2 : 222–246) show that inference in Bayesian model averaging (BMA) can be highly sensitive to small data perturbations. In particular, they demonstrate that the importance attributed to potential growth determinants varies tremendously over different revisions of international income data. They conclude that ‘agnostic’ priors appear too sensitive for this strand of growth empirics. In response,…

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The political economy of financial reform: How robust are huang's findings?

金融改革的政治经济学:Huang 的发现有多稳健?

SUMMARY Using new data on financial liberalization taken from Abiad et al . (2008, IMF Working Papers, No. 08/266) for 62 countries over the period 1975–2005, we show that some of the main findings of Huang's (2009, Journal of Applied Econometrics 24 : 1207–1213) replication study on the drivers of financial liberalization are not robust. Major changes concern the effect of democracy on financial reform and the supposed relationship between the desired level of financial…

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An identification‐robust test for time‐varying parameters in the dynamics of energy prices

能源价格动态中时变参数的识别稳健检验

SUMMARY We test for the presence of time‐varying parameters (TVP) in the long‐run dynamics of energy prices for oil, natural gas and coal, within a standard class of mean‐reverting models. We also propose residual‐based diagnostic tests and examine out‐of‐sample forecasts. In‐sample LR tests support the TVP model for coal and gas but not for oil, though companion diagnostics suggest that the model is too restrictive to conclusively fit the data. Out‐of‐sample analysis…

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A blocking and regularization approach to high‐dimensional realized covariance estimation

高维已实现协方差估计的分块与正则化方法

SUMMARY We introduce a blocking and regularization approach to estimate high‐dimensional covariances using high‐frequency data. Assets are first grouped according to liquidity. Using the multivariate realized kernel estimator of Barndorff‐Nielsen et al. (2010), the covariance matrix is estimated block‐wise and then regularized. The performance of the resulting blocking and regularization (‘RnB’) estimator is analyzed in an extensive simulation study mimicking the liquidity…

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A simple, flexible estimator for count and other ordered discrete data

计数及其他有序离散数据的简便灵活估计器

SUMMARY This paper examines a flexible way to model empirically discrete data outcomes using ‘hazard rate’ decompositions. It presents a general data‐generating mechanism based on potential outcomes to describe why the approach should work for almost any discrete distribution. Monte Carlo evidence indicates that these models estimate well the impacts of covariates on expected counts when the data follow a Poisson distribution. With data from more complex processes, these…

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Probabilistic forecasting of output growth, inflation and the balance of trade in a GVAR framework

GVAR 框架下产出增长、通胀与贸易差额的概率预测

SUMMARY We apply a global vector autoregressive (GVAR) model to the analysis of inflation, output growth and global imbalances among a group of 33 countries (26 regions). We account for structural instability by use of country‐specific intercept shifts, the timings of which are identified taking into account both statistical evidence and our knowledge of historic economic conditions and events. Using this model, we compute both central forecasts and scenario‐based…

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Lose weight for a raise only if overweight: Marginal integration for semi‐linear panel models

仅超重时减重才可能提高工资:半线性面板模型的边际积分

SUMMARY Some studies have shown that body mass index (BMI), weight (kg)/height (m) 2 , has a negative (or no) effect on wage. But BMI representing obesity is a tightly specified function of weight and height, and there is a room for weight given height (i.e. obesity given height) to better explain wage when the tight specification gets relaxed. In this paper, we address the question of weight effect on wage given height, employing two‐wave panel data for white females and…

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Estimation of nonlinear models with mismeasured regressors using marginal information

利用边际分布信息估计解释变量误测的非线性模型

Abstract We consider the estimation of nonlinear models with mismeasured explanatory variables, when information on the marginal distribution of the true values of these variables is available. We derive a semi‐parametric MLE that is shown to be $\sqrt{n}$ consistent and asymptotically normally distributed. In a simulation experiment we find that the finite sample distribution of the estimator is close to the asymptotic approximation. The semi‐parametric MLE is applied to a…

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Modelling heterogeneity and dynamics in the volatility of individual wages

个体工资波动的异质性与动态建模

Abstract This paper presents a model for the heterogeneity and dynamics of the conditional mean and conditional variance of individual wages. A bias‐corrected likelihood approach, which reduces the estimation bias to a term of order 1/ T 2 , is used for estimation and inference. The small‐sample performance of the proposed estimator is investigated in a Monte Carlo study. The simulation results show that the bias of the maximum likelihood estimator is substantially corrected…

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Improved instrumental variables estimation of simultaneous equations under conditionally heteroskedastic disturbances

条件异方差扰动下联立方程工具变量估计的改进

Abstract In this paper we develop estimation techniques and a specification test for the validity of instrumental variables allowing for conditionally heteroskedastic disturbances. We propose modified two‐stage least squares (2SLS) and modified 3SLS procedures where the conditional heteroskedasticity is taken into account, which are natural extensions of the traditional 2SLS and 3SLS estimators and which achieve a lower variance. We recommend the use of these modified 2SLS…

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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 dependence using skew t copulas: Bayesian inference and applications

偏斜 t Copula 的依赖建模:贝叶斯推断与应用

Abstract We construct a copula from the skew t distribution of Sahu et al. ( 2003 ). This copula can capture asymmetric and extreme dependence between variables, and is one of the few copulas that can do so and still be used in high dimensions effectively. However, it is difficult to estimate the copula model by maximum likelihood when the multivariate dimension is high, or when some or all of the marginal distributions are discrete‐valued, or when the parameters in the…

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Nonparametric estimation of the impact of taxes on female labor supply

税收对女性劳动供给影响的非参数估计

Abstract This paper proposes a simple extension of nonparametric estimation methods for nonlinear budget‐set models derived in Blomquist and Newey ( 2002 ) to censored dependent variables. The nonparametric method is applied to estimate female labor supply elasticities using data on married women from the 1985 and 1989 waves of the Panel Study of Income Dynamics, exploiting the substantial variation in budget sets caused by the Tax Reform Act of 1986 as a source of…

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Estimation of sample selection models with spatial dependence

具有空间依赖的样本选择模型估计

SUMMARY We consider the estimation of a sample selection model that exhibits spatial autoregressive errors (SAE). Our methodology is motivated by a two‐step strategy where in the first step we estimate a spatial probit model and in the second step (outcome equation) we include an estimated inverse Mills ratio (IMR) as a regressor to control for selection bias. Since the appropriate IMR under SAE depends on a parameter from the second step, both steps are jointly estimated…

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Dynamic stochastic copula models: estimation, inference and applications

动态随机 Copula 模型:估计、推断与应用

SUMMARY We propose a new dynamic copula model in which the parameter characterizing dependence follows an autoregressive process. As this model class includes the Gaussian copula with stochastic correlation process, it can be viewed as a generalization of multivariate stochastic volatility models. Despite the complexity of the model, the decoupling of marginals and dependence parameters facilitates estimation. We propose estimation in two steps, where first the parameters of…

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Specification and testing of models estimated by quadrature

采用数值求积估计的模型:设定与检验

SUMMARY This paper proposes a test to check the specification of models with unobserved individual effects integrated out by quadrature and also a simple way of increasing the flexibility of this type of model. The results of a Monte Carlo study and an application using a well‐known dataset illustrate the finite sample properties of the proposed methods and their implementation in practice. Copyright © 2010 John Wiley & Sons, Ltd.

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Alternative technical efficiency measures: Skew, bias and scale

替代性技术效率度量:偏斜、偏差与尺度

SUMMARY In the fixed‐effects stochastic frontier model an efficiency measure relative to the best firm in the sample is universally employed. This paper considers a new measure relative to the worst firm in the sample. We find that estimates of this measure have smaller bias than those of the traditional measure when the sample consists of many firms near the efficient frontier. Moreover, a two‐sided measure relative to both the best and the worst firms is proposed.…

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