Huigang Chen's Books

Constructing Forecast Confidence Bands During the Financial Crisis

By: Mr.Ondrej Kamenik,Marianne Johnson,Kevin Clinton,Huigang Chen,Mr.Douglas Laxton

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Constructing Forecast Confidence Bands During the Financial Crisis

By: Mr.Ondrej Kamenik,Marianne Johnson,Kevin Clinton,Huigang Chen,Mr.Douglas Laxton

We derive forecast confidence bands using a Global Projection Model covering the United States, the euro area, and Japan. In the model, the price of oil is a stochastic process, interest rates have a zero floor, and bank lending tightening affects the United States. To calculate confidence intervals that respect the zero interest rate floor, we employ Latin hypercube sampling. Derived confidence bands suggest non-negligible risks that U.S. interest rates might stay near zero for an extended period, and that severe credit conditions might persist.

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International Monetary Fund

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ISBN 10

1451873611

ISBN 13

9781451873610

Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model

By: Huigang Chen,Mr.Alin Mirestean,Mr.Charalambos G. Tsangarides

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Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model

By: Huigang Chen,Mr.Alin Mirestean,Mr.Charalambos G. Tsangarides

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation results suggest that asymptotically our methodology performs well both in Bayesian model averaging and selection. In particular, LIBMA recovers the data generating process well, with high posterior inclusion probabilities for all the relevant regressors, and parameter estimates very close to their true values. These findings suggest that our methodology is well suited for inference in short dynamic panel data models with endogenous regressors in the context of model uncertainty. We illustrate the use of LIBMA in an application to the estimation of a dynamic gravity model for bilateral trade.

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