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Confronting Price Endogeneity in a Duration Model of Residential Subdivision Development

住宅地块开发持续期模型中的价格内生性

Summary Spatial equilibrium implies that distant factors are correlated with local prices through market mechanisms. Using this logic, we develop a novel approach for handling price endogeneity in land use models. We combine a control function approach with a duration model to identify the impact of prices in influencing land conversion. We find that failure to control for endogeneity results in large differences in elasticities. Specifically, we find an elasticity of 2.06…

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The Millennium Peak in Club Convergence: A New Look at Distributional Changes in The Wealth of Nations

俱乐部趋同的千禧年高峰:国家财富分布变化的新观察

Summary This paper proposes an easy‐to‐use nonparametric indicator for club convergence, or convergence within clusters of countries: it measures whether the modes of the gross domestic product (GDP) per capita distribution become more pronounced over time. Relying on changes in the critical bandwidth for unimodality, the indicator is a dynamic extension of concepts from often‐used multimodality tests. Its evolution suggests the new empirical result of a ‘millennium peak’ in…

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Teacher Quality and Student Achievement: Evidence from a Sample of Dutch Twins

教师质量与学生成绩:荷兰双胞胎样本的证据

Summary This paper examines the causal link that runs from classroom quality to student achievement using data on twin pairs who entered the same school but were allocated to different classrooms in an exogenous way. In particular, we apply twin fixed‐effects estimation to assess the effect of teacher quality on student test scores from second through eighth grade of primary education, arguing that a change in teacher quality is probably the most important classroom…

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Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion

弱与强截面相关:国际技术扩散的面板数据分析

Summary This paper provides an econometric examination of technological knowledge spillovers among countries by focusing on the issue of error cross‐sectional dependence, particularly on the different ways—weak and strong—that this dependence may affect model specification and estimation. A preliminary analysis based on estimation of the exponent of cross‐sectional dependence provides a clear result in favor of strong cross‐sectional dependence. This result has relevant…

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Income and Democracy: A Smooth Varying Coefficient Redux

收入与民主:平滑变系数模型的重新考察

Summary Acemoglu et al. ( American Economic Review 2008; 98 : 808–842) find no effect of income on democracy when controlling for fixed effects in a dynamic panel model. Work by Moral‐Benito and Bartolucci ( Economics Letters 2012; 117 : 844–847) and Cervellati et al. ( American Economic Review 2014; 104 : 707–719) suggests that the original model might have been misspecified and proposes alternative specifications instead. We formally test these parametric specifications by…

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Testing for Predictability in panels with General Predictors

一般预测变量下的面板可预测性检验

Summary The difficulty of predicting returns has recently motivated researchers to start looking for tests that are either more powerful or robust to more features of the data. Unfortunately, the way that these tests work typically involves trading robustness for power or vice versa. The current paper takes this as its starting point to develop a new panel‐based approach to predictability that is both robust and powerful. Specifically, while the panel route to increased…

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Likelihood‐Based Inference and Prediction in Spatio‐Temporal Panel Count Models for Urban Crimes

城市犯罪时空面板计数模型的似然推断与预测

Summary We develop a panel count model with a latent spatio‐temporal heterogeneous state process for monthly severe crimes at the census‐tract level in Pittsburgh, Pennsylvania. Our dataset combines Uniform Crime Reporting data with socio‐economic data. The likelihood is estimated by efficient importance sampling techniques for high‐dimensional spatial models. Estimation results confirm the broken‐windows hypothesis whereby less severe crimes are leading indicators for…

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Empirical Bayesball Remixed: Empirical Bayes Methods for Longitudinal Data

经验贝叶斯棒球再论:纵向数据的经验贝叶斯方法

Summary Empirical Bayes methods for Gaussian and binomial compound decision problems involving longitudinal data are considered. A recent convex optimization reformulation of the nonparametric maximum likelihood estimator of Kiefer and Wolfowitz ( Annals of Mathematical Statistics 1956; 27 : 887–906) is employed to construct nonparametric Bayes rules for compound decisions. The methods are illustrated with an application to predict baseball batting averages, and the age…

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Tests of Predictive Ability for Vector Autoregressions Used for Conditional Forecasting

用于条件预测的向量自回归模型预测能力检验

Summary Many forecasts are conditional in nature. For example, a number of central banks routinely report forecasts conditional on particular paths of policy instruments. Even though conditional forecasting is common, there has been little work on methods for evaluating conditional forecasts. This paper provides analytical, Monte Carlo and empirical evidence on tests of predictive ability for conditional forecasts from estimated models. In the empirical analysis, we examine…

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Conventional Monetary Policy Transmission During Financial Crises: An Empirical Analysis

金融危机期间常规货币政策的传导:实证分析

Summary This paper studies the effects of a conventional monetary policy shock in the USA during times of high financial stress. The analysis is carried out by introducing a smooth transition factor model where the transition between states (‘normal’ and high financial stress) depends on a financial conditions index. Employing a quarterly dataset over the period 1970:Q1 to 2008:Q4 containing 108 US macroeconomic and financial time series, I find that a monetary policy shock…

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Spotting the Danger Zone: Forecasting Financial Crises With Classification Tree Ensembles and Many Predictors

识别危险区:用分类树集成与众多预测变量预测金融危机

Summary This paper introduces classification tree ensembles (CTEs) to the banking crisis forecasting literature. I show that CTEs substantially improve out‐of‐sample forecasting performance over best‐practice early‐warning systems. CTEs enable policymakers to correctly forecast 80% of crises with a 20% probability of incorrectly forecasting a crisis. These findings are based on a long‐run sample (1870–2011), and two broad post‐1970 samples which together cover almost all…

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Estimation and Solution of Models with Expectations and Structural Changes

含预期与结构变化模型的估计和求解

Summary In this paper, we develop solutions for linearized models with forward‐looking expectations and structural changes under a variety of assumptions regarding agents' beliefs about those structural changes. For each solution, we show how its associated likelihood function can be constructed by using a ‘backward–forward’ algorithm. We illustrate the techniques with two examples. The first considers an inflationary program in which beliefs about the inflation target…

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Subjective Well‐Being and Income: A Re‐Examination of Satiation Using the Regression Kink Model With an Unknown Threshold

主观幸福感与收入:用未知阈值回归折点模型重新检验饱和点

Summary A methodological challenge in testing Easterlin's paradox, which states that increasing income fails to boost happiness beyond a satiation point, lies in the determination of this threshold if it exists. In the existing literature, various levels of GDP per capita have been chosen based upon visual inspection of the scatter plots of the data. The estimated income–well‐being gradients are sensitive to the choice of such kink points. We first replicate the results in…

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Forecasting With the Standardized Self‐Perturbed Kalman Filter

使用标准化自扰动卡尔曼滤波器进行预测

Summary We propose and study the finite‐sample properties of a modified version of the self‐perturbed Kalman filter of Park and Jun ( Electronics Letters 1992; 28 : 558–559) for the online estimation of models subject to parameter instability. The perturbation term in the updating equation of the state covariance matrix is weighted by the estimate of the measurement error variance. This avoids the calibration of a design parameter as the perturbation term is scaled by the…

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Penalized Quantile Regression with Semiparametric Correlated Effects: An Application with Heterogeneous Preferences

具有半参数相关效应的惩罚分位数回归:异质性偏好应用

Summary This paper proposes new ℓ 1 ‐penalized quantile regression estimators for panel data, which explicitly allows for individual heterogeneity associated with covariates. Existing fixed‐effects estimators can potentially suffer from three limitations which are overcome by the proposed approach: (i) incidental parameters bias in nonlinear models with large N and small T ; (ii) lack of efficiency; and (iii) inability to estimate the effects of time‐invariant regressors. We…

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Differences Between Classical and Bayesian Estimates for Mixed Logit Models: A Replication Study

混合 Logit 模型中古典与贝叶斯估计的差异:复现研究

Summary The mixed logit model is widely used in applied econometrics. Researchers typically rely on the free choice between the classical and Bayesian estimation approach. However, empirical evidence of the similarity of their parameter estimates is sparse. The presumed similarity is mainly based on one empirical study that analyzes a single dataset (Huber J, Train KE. 2001. On the similarity of classical and Bayesian estimates of individual mean partworths. Marketing…

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Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump

透视水晶球:预测加油站汽油价格的新方法

Summary Appropriate real‐time forecasting models for the US retail price of gasoline yield substantial reductions in the mean‐squared prediction error (MSPE) at horizons up to 2 years as well as substantial increases in directional accuracy. Even greater MSPE reductions are possible by constructing a pooled forecast that assigns equal weight to five of the most successful forecasting models. Pooled forecasts have lower MSPE than the US Energy Information Administration…

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Wild Bootstrap Inference for Wildly Different Cluster Sizes

聚类规模悬殊时的野生自助法推断

Summary The cluster robust variance estimator (CRVE) relies on the number of clusters being sufficiently large. Monte Carlo evidence suggests that the ‘rule of 42’ is not true for unbalanced clusters. Rejection frequencies are higher for datasets with 50 clusters proportional to US state populations than with 50 balanced clusters. Using critical values based on the wild cluster bootstrap performs much better. However, this procedure fails when a small number of clusters is…

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Transitions at Different Moments in Time: A Spatial Probit Approach

不同时点的状态转变:空间probit方法

Summary This paper adopts a spatial probit approach to explain interaction effects among cross‐sectional units when the dependent variable takes the form of a binary response variable and transitions from state 0 to 1 occur at different moments in time. The model has two spatially lagged variables: one for units that are still in state 0 and one for units that had already transferred to state 1. The parameters are estimated on observations for those units that are still in…

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Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice

大型已实现协方差矩阵的建模、预测与投资组合选择

Summary We consider modeling and forecasting large realized covariance matrices by penalized vector autoregressive models. We consider Lasso‐type estimators to reduce the dimensionality and provide strong theoretical guarantees on the forecast capability of our procedure. We show that we can forecast realized covariance matrices almost as precisely as if we had known the true driving dynamics of these in advance. We next investigate the sources of these driving dynamics as…

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How to Identify and Forecast Bull and Bear Markets?

如何识别与预测牛市和熊市?

Summary Because the state of the equity market is latent, several methods have been proposed to identify past and current states of the market and forecast future ones. These methods encompass semi‐parametric rule‐based methods and parametric Markov switching models. We compare the mean‐variance utilities that result when a risk‐averse agent uses the predictions of the different methods in an investment decision. Our application of this framework to the S&P 500 shows that…

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Forecasting Tail Risks

尾部风险预测

Summary This paper presents an early warning system as a set of multi‐period forecasts of indicators of tail real and financial risks obtained using a large database of monthly US data for the period 1972:1–2014:12. Pseudo‐real‐time forecasts are generated from: (a) sets of autoregressive and factor‐augmented vector autoregressions (VARs), and (b) sets of autoregressive and factor‐augmented quantile projections. Our key finding is that forecasts obtained with AR and…

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Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models

线性高斯状态空间模型的边缘化预测似然比较:DSGE、DSGE-VAR与VAR应用

Summary The predictive likelihood is useful for ranking models in forecast comparison exercises using Bayesian inference. We discuss how it can be estimated, by means of marzginalization, for any subset of the observables in linear Gaussian state‐space models. We compare macroeconomic density forecasts for the euro area of a DSGE model to those of a DSGE‐VAR, a BVAR and a multivariate random walk over 1999:Q1–2011:Q4. While the BVAR generally provides superior forecasts, its…

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Estimation of Poverty Transition Matrices with Noisy Data

含噪数据下贫困转移矩阵的估计

Summary This paper investigates measurement error biases in estimated poverty transition matrices. We compare transition matrices based on survey expenditure data to transition matrices based on measurement‐error‐free simulated expenditure. The simulation model uses estimates that correct for measurement error in expenditure. We find that time‐varying measurement error in expenditure data magnifies economic mobility. Roughly 45 % of households initially in poverty at time t…

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