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Tae Bong Kim

Personal Details

First Name:Tae Bong
Middle Name:
Last Name:Kim
Suffix:
RePEc Short-ID:pki339
[This author has chosen not to make the email address public]

Affiliation

Department of Economics
Ajou University

Suwon, South Korea
http://econ.ajou.ac.kr/

:


RePEc:edi:deajokr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Tae Bong Kim, 2013. "Monetary Policy in Korea through the lense of Taylor Rule in DSGE model," 2013 Meeting Papers 746, Society for Economic Dynamics.
  2. Andrew T. Foerster & Tae Bong Kim & Hernan D. Seoane & Ching Wai (Jeremy) Chiu & Bjørn Eraker, 2011. "Estimating VAR's sampled at mixed or irregular spaced frequencies : a Bayesian approach," Research Working Paper RWP 11-11, Federal Reserve Bank of Kansas City.

Articles

  1. Tae Bong Kim & Hangyu Lee, 2016. "Macroeconomic Shocks and Dynamics of Labor Markets in Korea," Korean Economic Review, Korean Economic Association, vol. 32, pages 101-136.
  2. Bjørn Eraker & Ching Wai (Jeremy) Chiu & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2015. "Bayesian Mixed Frequency VARs," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 13(3), pages 698-721.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Andrew T. Foerster & Tae Bong Kim & Hernan D. Seoane & Ching Wai (Jeremy) Chiu & Bjørn Eraker, 2011. "Estimating VAR's sampled at mixed or irregular spaced frequencies : a Bayesian approach," Research Working Paper RWP 11-11, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Qian, Hang, 2012. "Essays on statistical inference with imperfectly observed data," ISU General Staff Papers 201201010800003618, Iowa State University, Department of Economics.
    2. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
    3. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.
    4. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
    5. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
    6. Massimiliano Marcellino & Andrea Carriero & Todd E. Clark, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland, revised 2012.
    7. Fady Barsoum, 2015. "Point and Density Forecasts Using an Unrestricted Mixed-Frequency VAR Model," Working Paper Series of the Department of Economics, University of Konstanz 2015-19, Department of Economics, University of Konstanz.
    8. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    9. Anna Samarina & Anh D.M. Nguyen, 2019. "Does monetary policy affect income inequality in the euro area?," DNB Working Papers 626, Netherlands Central Bank, Research Department.
    10. Bluwstein, Kristina & Canova, Fabio, 2015. "Beggar-thy-neighbor? The international effects of ECB unconventional monetary policy measures," CEPR Discussion Papers 10856, C.E.P.R. Discussion Papers.
    11. Daniel L. Millimet & Ian K. McDonough, 2017. "Dynamic Panel Data Models With Irregular Spacing: With an Application to Early Childhood Development," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 725-743, June.
    12. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
    13. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2016. "Structural analysis with mixed frequencies: monetary policy, uncertainty and gross capital flows," Working Papers 2016-04, Joint Research Centre, European Commission (Ispra site).
    14. Guy P. Nason & Ben Powell & Duncan Elliott & Paul A. Smith, 2017. "Should we sample a time series more frequently?: decision support via multirate spectrum estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 353-407, February.
    15. Thomas B. Götz & Alain W. Hecq, 2019. "Granger Causality Testing in Mixed‐Frequency VARs with Possibly (Co)Integrated Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(6), pages 914-935, November.
    16. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
    17. Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018. "Mixed frequency models with MA components," Discussion Papers 02/2018, Deutsche Bundesbank.
    18. Götz, Thomas B. & Hecq, Alain & Smeekes, Stephan, 2015. "Testing for Granger causality in large mixed-frequency VARs," Discussion Papers 45/2015, Deutsche Bundesbank.
    19. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
    20. Michal Franta & David Havrlant & Marek Rusnak, 2014. "Forecasting Czech GDP Using Mixed-Frequency Data Models," Working Papers 2014/08, Czech National Bank.
    21. Qian, Hang, 2016. "A computationally efficient method for vector autoregression with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 433-437.
    22. Born, Benjamin & Pfeifer, Johannes, 2016. "Uncertainty-driven business cycles: assessing the markup channel," Annual Conference 2016 (Augsburg): Demographic Change 145608, Verein für Socialpolitik / German Economic Association.
    23. Sergio Afonso Lago Alves & Angelo Marsiglia Fasolo, 2015. "Not Just Another Mixed Frequency Paper," Working Papers Series 400, Central Bank of Brazil, Research Department.
    24. Jan Klacso, 2015. "The Effects of the Euro Area Entrance on the Monetary Transmission Mechanism in Slovakia in Light of the Global Economic Recession," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 55-83, January.
    25. Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-07, Economic Statistics Centre of Excellence (ESCoE).
    26. Mayer, Eric & Maas, Daniel & Rüth, Sebastian, 2016. "Current Account Dynamics and the Housing Cycle in Spain," Annual Conference 2016 (Augsburg): Demographic Change 145824, Verein für Socialpolitik / German Economic Association.
    27. Peter A. Zadrozny, 2016. "Extended Yule-Walker Identification of Varma Models with Single- or Mixed-Frequency Data," CESifo Working Paper Series 5884, CESifo Group Munich.
    28. Benjamin Born & Johannes Pfeifer, 2017. "Uncertainty-driven Business Cycles: Assessing the Markup Channel," CESifo Working Paper Series 6303, CESifo Group Munich.
    29. Baumeister, Christiane & Guérin, Pierre & Kilian, Lutz, 2015. "Do high-frequency financial data help forecast oil prices? The MIDAS touch at work," International Journal of Forecasting, Elsevier, vol. 31(2), pages 238-252.
    30. Maas, Daniel & Mayer, Eric & Rüth, Sebastian, 2015. "Current account dynamics and the housing boom and bust cycle in Spain," W.E.P. - Würzburg Economic Papers 94, University of Würzburg, Chair for Monetary Policy and International Economics.
    31. Foroni, Claudia & Marcellino, Massimiliano, 2014. "A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates," International Journal of Forecasting, Elsevier, vol. 30(3), pages 554-568.
    32. Zadrozny, Peter A., 2015. "Extended Yule-Walker identification of Varma models with single- or mixed frequency data," CFS Working Paper Series 526, Center for Financial Studies (CFS).
    33. Qian, Hang, 2013. "Vector Autoregression with Mixed Frequency Data," MPRA Paper 47856, University Library of Munich, Germany.
    34. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    35. Peter Broer & Jürgen Antony, 2013. "Financial Shocks and Economic Activity in the Netherlands," CPB Discussion Paper 260, CPB Netherlands Bureau for Economic Policy Analysis.
    36. Claudia Foroni & Massimiliano Marcellino, 2014. "Mixed frequency structural VARs," Working Paper 2014/01, Norges Bank.
    37. Sebastian Ankargren & Måns Unosson & Yukai Yang, 2018. "A mixed-frequency Bayesian vector autoregression with a steady-state prior," CREATES Research Papers 2018-32, Department of Economics and Business Economics, Aarhus University.
    38. Trujillo-Barrera, Andres & Pennings, Joost M.E., 2013. "Energy and Food Commodity Prices Linkage: An Examination with Mixed-Frequency Data," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150465, Agricultural and Applied Economics Association.

Articles

  1. Tae Bong Kim & Hangyu Lee, 2016. "Macroeconomic Shocks and Dynamics of Labor Markets in Korea," Korean Economic Review, Korean Economic Association, vol. 32, pages 101-136.

    Cited by:

    1. Hyunju Kang & Hyunduk Suh, 2017. "Macroeconomic Dynamics in Korea during and after the Global Financial Crisis: A Bayesian DSGE Approach," Inha University IBER Working Paper Series 2017-1, Inha University, Institute of Business and Economic Research, revised Mar 2017.

  2. Bjørn Eraker & Ching Wai (Jeremy) Chiu & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2015. "Bayesian Mixed Frequency VARs," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 13(3), pages 698-721.
    See citations under working paper version above.

More information

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Statistics

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Co-authorship network on CollEc

Featured entries

This author is featured on the following reading lists, publication compilations or Wikipedia entries:
  1. Korean Economists

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 2 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-CBA: Central Banking (1) 2014-01-10. Author is listed
  2. NEP-DGE: Dynamic General Equilibrium (1) 2014-01-10. Author is listed
  3. NEP-ECM: Econometrics (1) 2012-02-01. Author is listed
  4. NEP-ETS: Econometric Time Series (1) 2012-02-01. Author is listed
  5. NEP-MAC: Macroeconomics (1) 2014-01-10. Author is listed
  6. NEP-MON: Monetary Economics (1) 2014-01-10. Author is listed
  7. NEP-MST: Market Microstructure (1) 2012-02-01. Author is listed

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