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Unobserved components with stochastic volatility: Simulation‐based estimation...
The unobserved components time series model with stochastic volatility has gained much interest in econometrics, especially for the purpose of modelling and forecasting... -
Multivariate fractional integration tests allowing for conditional heterosked...
We introduce a new joint test for the order of fractional integration of a multivariate fractionally integrated vector autoregressive (FIVAR) time series based on applying the... -
Bayesian estimation of the exact affine Stone index demand system: Replicatin...
This paper proposes a Bayesian approach to perform inference in the exact affine Stone index (EASI) demand system that was proposed by Lewbel and Pendakur (2009), while taking... -
Migration in China: To work or to wed? (replication data)
This paper develops a model encompassing both matching and hedonic models, studies its properties, and provides identification and estimation strategies. We bring the model to... -
Efficient minimum distance estimation of Pareto exponent from top income shar...
We propose an efficient estimation method for the income Pareto exponent when only certain top income shares are observable. Our estimator is based on the asymptotic theory of... -
Dynamic shrinkage in time‐varying parameter stochastic volatility in mean mod...
Successful forecasting models strike a balance between parsimony and flexibility. This is often achieved by employing suitable shrinkage priors that penalize model complexity... -
Nonlinear effects of government spending shocks in the USA: Evidence from sta...
This paper uses state-level data to estimate the effect of government spending shocks during expansions and recessions. By employing a mixed-frequency framework, we are able to... -
Common correlated effect cross‐sectional dependence corrections for nonlinear...
This paper provides an approach to estimation and inference for nonlinear conditional mean panel data models, in the presence of cross-sectional dependence. We modify Pesaran's... -
Cointegration and control: Assessing the impact of events using time series d...
Control groups can provide counterfactual evidence for assessing the impact of an event or policy change on a target variable. We argue that fitting a multivariate time series... -
Real‐time detection of regimes of predictability in the US equity premium (re...
We propose new real-time monitoring procedures for the emergence of end-of-sample predictive regimes using sequential implementations of standard (heteroskedasticity-robust)... -
Robust political economy correlates of major product and labor market reforms...
The political economy literature has put forward a multitude of hypotheses regarding the drivers of structural reforms, but few, if any, empirically robust findings have emerged... -
Fixed effects demeaning in the presence of interactive effects in treatment e...
The present paper shows that cross-section demeaning with respect to time fixed effects is more useful than commonly appreciated, in that it enables consistent and... -
Testing for overconfidence statistically: A moment inequality approach (repli...
We propose a moment inequality approach to test for the presence of overconfidence using data from ranking experiments where subjects rank themselves relative to other... -
Direct and indirect effects of continuous treatments based on generalized pro...
This paper proposes semi- and nonparametric methods for disentangling the total causal effect of a continuous treatment on an outcome variable into its natural direct effect and... -
The evolution of the US family income–schooling relationship and educational ...
We estimate a dynamic model of schooling on two cohorts of the National Longitudinal Survey of Youth and find that, contrary to conventional wisdom, the effects of real (as... -
Composite likelihood methods for large Bayesian VARs with stochastic volatili...
Adding multivariate stochastic volatility of a flexible form to large vector autoregressions (VARs) involving over 100 variables has proved challenging owing to computational... -
Forecasting stock returns with model uncertainty and parameter instability (r...
We compare several representative sophisticated model averaging and variable selection techniques of forecasting stock returns. When estimated traditionally, our results confirm... -
Endogeneity and non‐response bias in treatment evaluation – nonparametric ide...
This paper proposes a nonparametric method for evaluating treatment effects in the presence of both treatment endogeneity and attrition/non-response bias, based on two... -
Prediction regions for interval‐valued time series (replication data)
We approximate probabilistic forecasts for interval-valued time series by offering alternative approaches. After fitting a possibly non-Gaussian bivariate vector autoregression... -
Comparing predictive accuracy in small samples using fixed‐smoothing asymptot...
We consider fixed-smoothing asymptotics for the Diebold and Mariano (Journal of Business and Economic Statistics, 1995, 13(3), 253-263) test of predictive accuracy. We show that...
