Tae Bong Kim

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  • Bjørn Eraker, Ching Wai, Jeremy Chiu, Andrew Foerster, Tae Bong Kim, Hernan Seoane
  • 2008
Economic data can be collected at a variety of frequencies. Typically, estimation is done using the coarser frequency data. This paper discusses how to combine data of different frequencies in estimating Vector Autoregressions (VAR's). The method is based on Bayesian Gibbs sampling using a missing data formulation for coarsely observed data. In an example,(More)
PURPOSE Laparoscopy-assisted distal gastrectomy for early gastric cancer has gained acceptance and popularity worldwide. However, laparoscopy-assisted distal gastrectomy for advanced gastric cancer is still controversial. Therefore, we propose this prospective randomized controlled multi-center trial in order to evaluate the safety and feasibility of(More)
  • Ching Wai, Jeremy Chiu, Bjørn Eraker, Andrew T Foerster, Tae Bong Kim, Hernán D Seoane
  • 2012
Economic data are collected at various frequencies but econometric estimation typically uses the coarsest frequency. This paper develops a Gibbs sampler for estimating VAR models with mixed and irregularly sampled data. The approach allows e¢ cient likelihood inference even with irregular and mixed frequency data. The Gibbs sampler uses simple conjugate(More)
This paper asks whether frequency misspeci…cation of a New Keynesian model results in temporal aggregation bias of the Calvo parameter. First, when a New Keyne-sian model is estimated at a quarterly frequency while the true data generating process is the same but at a monthly frequency, the Calvo parameter is upward biased and hence implies longer average(More)
  • Tae Bong Kim, Juan Rubio-Ramirez, Craig Burnside, Francesco Bianchi, Tao Zha
  • 2011
This dissertation asks whether frequency misspecification of a New Keynesian model results in temporal aggregation bias of the Calvo parameter. First, when a New Keynesian model is estimated at a quarterly frequency while the true data generating process is the same but at a monthly frequency, the Calvo parameter is upward biased and hence implies longer(More)
In this paper, we present an alternative strategy for estimation of DSGE models when data is available at di¤erent time intervals. Our method is based on a data augmentation technique within Bayesian estimation of structural models and allows us to jointly use data at di¤erent frequencies. The bene…ts achieved via this methodology will be twofold,(More)
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