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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 & Hangyu Lee, 2015. "Macroeconomic Shocks and Dynamics of Labor Markets in Korea," Working Papers 2015-26, Economic Research Institute, Bank of Korea.
  2. 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.
  3. Ching Wai Chiu & Bjorn Eraker & Andrew T. Foerster & Tae Bong Kim & Hernan D. Seoane, 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. Lee, Hangyu & Kim, Tae Bong, 2023. "The effectiveness of labor market indicators for conducting monetary policy: Evidence from the Korean economy," Economic Modelling, Elsevier, vol. 118(C).
  2. Tae Bong Kim & Keunhyeong Park, 2020. "Business Cycle Analysis on Korean Youth Labor Market using Alternative Unemployment Measures (in Korean)," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 26(2), pages 43-71, June.
  3. Tae Bong Kim, 2019. "Reconciling Output and Unemployment Fiscal Multipliers," Global Economic Review, Taylor & Francis Journals, vol. 48(4), pages 378-395, October.
  4. Kim, Yong-seong & Kim, Taebong, 2017. "The Effects of Institutions on the Labour Market Outcomes: Cross-country Analysis," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 39(4), pages 69-94.
  5. 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.
  6. Bjørn Eraker & Ching Wai (Jeremy) Chiu & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2015. "Bayesian Mixed Frequency VARs," Journal of Financial Econometrics, Oxford University Press, 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. Tae Bong Kim & Hangyu Lee, 2015. "Macroeconomic Shocks and Dynamics of Labor Markets in Korea," Working Papers 2015-26, Economic Research Institute, Bank of Korea.

    Cited by:

    1. Jong-seok Oh, 2023. "Stabilizing the Macroeconomy with Labor Market Policies," Korean Economic Review, Korean Economic Association, vol. 39, pages 205-240.
    2. DongIk Kang & Jinhee Woo, 2022. "How Effective are Automatic Stabilizers in Reducing Aggregate Volatility in Korea?," Korean Economic Review, Korean Economic Association, vol. 38, pages 5-42.
    3. Kang, Hyunju & Suh, Hyunduk, 2017. "Macroeconomic Dynamics in Korea during and after the Global Financial Crisis: A Bayesian DSGE Approach," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 386-421.
    4. Lee, Hangyu & Kim, Tae Bong, 2023. "The effectiveness of labor market indicators for conducting monetary policy: Evidence from the Korean economy," Economic Modelling, Elsevier, vol. 118(C).
    5. Yao Li & Yugang He & Renhong Wu, 2023. "Traversing the Macroeconomic Terrain: An Exploration of South Korea’s Economic Responsiveness to Cross-Border E-Commerce Production Technology Alterations in the Global Arena," Sustainability, MDPI, vol. 15(15), pages 1-20, July.

  2. 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.

    Cited by:

    1. Aleksandra Babii, 2019. "Exchange Rates Co-movement and International Trade," 2019 Meeting Papers 1150, Society for Economic Dynamics.

  3. Ching Wai Chiu & Bjorn Eraker & Andrew T. Foerster & Tae Bong Kim & Hernan D. Seoane, 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. 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.
    3. 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.
    4. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
    5. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    6. Peter A. Zadrozny, 2015. "Extended Yule-Walker Identification of Varma Models with Single- or Mixed- Frequency Data," Economic Working Papers 485, Bureau of Labor Statistics.
    7. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Reconciled Estimates of Monthly GDP in the US," Working Papers 22-01, Federal Reserve Bank of Cleveland.
    8. Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," JRC Working Papers in Economics and Finance 2021-01, Joint Research Centre, European Commission.
    9. Ahiadorme, Johnson Worlanyo, 2020. "Monetary policy transmission and income inequality in Sub-Saharan Africa," MPRA Paper 104084, University Library of Munich, Germany.
    10. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
    11. Canova, Fabio & Bluwstein, Kristina, 2015. "Beggar-thy-neighbor? The international effects of ECB unconventional monetary policy measures," CEPR Discussion Papers 10856, C.E.P.R. Discussion Papers.
    12. 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.
    13. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
    14. Gani Ramadani & Magdalena Petrovska & Vesna Bucevska, 2021. "Evaluation of mixed frequency approaches for tracking near-term economic developments in North Macedonia," Working Papers 2021-03, National Bank of the Republic of North Macedonia.
    15. Claudia Foroni & Francesco Ravazzolo & Luca Rossini, 2020. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Papers 2007.13566, arXiv.org, revised Dec 2022.
    16. Anna Samarina & Anh D.M. Nguyen, 2019. "Does monetary policy affect income inequality in the euro area?," Bank of Lithuania Working Paper Series 61, Bank of Lithuania.
    17. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
    18. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2018. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-14, Economic Statistics Centre of Excellence (ESCoE).
    19. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
    20. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates," Working Papers 22-06, Federal Reserve Bank of Cleveland.
    21. Dudda, Tom L. & Klein, Tony & Nguyen, Duc Khuong & Walther, Thomas, 2022. "Common Drivers of Commodity Futures?," QBS Working Paper Series 2022/05, Queen's University Belfast, Queen's Business School.
    22. Michal Franta & David Havrlant & Marek Rusnak, 2014. "Forecasting Czech GDP Using Mixed-Frequency Data Models," Working Papers 2014/08, Czech National Bank.
    23. Qian, Hang, 2016. "A computationally efficient method for vector autoregression with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 433-437.
    24. Born, Benjamin & Pfeifer, Johannes, 2016. "Uncertainty-driven business cycles: assessing the markup channel," VfS Annual Conference 2016 (Augsburg): Demographic Change 145608, Verein für Socialpolitik / German Economic Association.
    25. 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.
    26. 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).
    27. Maas, Daniel & Mayer, Eric & Rüth, Sebastian K., 2018. "Current account dynamics and the housing cycle in Spain," Journal of International Money and Finance, Elsevier, vol. 87(C), pages 22-43.
    28. Kilian, Lutz & Baumeister, Christiane, 2013. "Do High-Frequency Financial Data Help Forecast Oil Prices? The MIDAS Touch at Work," CEPR Discussion Papers 9768, C.E.P.R. Discussion Papers.
    29. 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.
    30. Sebastian Ankargren & Paulina Jon'eus, 2019. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Papers 1907.01075, arXiv.org.
    31. Michelle T. Armesto & Kristie M. Engemann & Michael T. Owyang, 2010. "Forecasting with mixed frequencies," Review, Federal Reserve Bank of St. Louis, vol. 92(Nov), pages 521-536.
    32. Camacho, Maximo & Perez-Quiros, Gabriel & Pacce, Matías, 2020. "Spillover effects in international business cycles," Working Paper Series 2484, European Central Bank.
    33. Claudia Foroni & Massimiliano Marcellino, 2014. "Mixed frequency structural VARs," Working Paper 2014/01, Norges Bank.
    34. Deborah Gefang & Gary Koop & Aubrey Poon, "undated". "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Discussion Papers in Economics 20/02, Division of Economics, School of Business, University of Leicester.
    35. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2016. "Testing for Granger causality with mixed frequency data," Journal of Econometrics, Elsevier, vol. 192(1), pages 207-230.
    36. Emanuele Bacchiocchi & Andrea Bastianin & Alessandro Missale & Eduardo Rossi, 2018. "Structural analysis with mixed-frequency data: A MIDAS-SVAR model of US capital flows," Papers 1802.00793, arXiv.org.
    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.
    39. Götz, T.B. & Hecq, A.W. & Smeekes, S., 2015. "Testing for Granger Causality in Large Mixed-Frequency VARs," Research Memorandum 036, Maastricht University, Graduate School of Business and Economics (GSBE).
    40. Hecq, Alain & Goetz, Thomas, 2018. "Granger causality testing in mixed-frequency Vars with possibly (co)integrated processes," MPRA Paper 87746, University Library of Munich, Germany.
    41. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    42. 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.
    43. 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.
    44. Seong, Byeongchan, 2020. "Smoothing and forecasting mixed-frequency time series with vector exponential smoothing models," Economic Modelling, Elsevier, vol. 91(C), pages 463-468.
    45. Jonas E. Arias & Minchul Shin, 2020. "Tracking U.S. Real GDP Growth During the Pandemic," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 5(3), pages 9-14, September.
    46. 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.
    47. Qiu, Yue, 2020. "Forecasting the Consumer Confidence Index with tree-based MIDAS regressions," Economic Modelling, Elsevier, vol. 91(C), pages 247-256.
    48. Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018. "Mixed frequency models with MA components," Discussion Papers 02/2018, Deutsche Bundesbank.
    49. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2020. "Structural analysis with mixed-frequency data: A model of US capital flows," Economic Modelling, Elsevier, vol. 89(C), pages 427-443.
    50. Ramadani Gani & Petrovska Magdalena & Bucevska Vesna, 2021. "Evaluation of Mixed Frequency Approaches for Tracking Near-Term Economic Developments in North Macedonia," South East European Journal of Economics and Business, Sciendo, vol. 16(2), pages 43-52, December.
    51. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
    52. Sergio Afonso Lago Alves & Angelo Marsiglia Fasolo, 2015. "Not Just Another Mixed Frequency Paper," Working Papers Series 400, Central Bank of Brazil, Research Department.
    53. Nuttanan Wichitaksorn, 2020. "Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach," PIER Discussion Papers 146, Puey Ungphakorn Institute for Economic Research.
    54. 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, Department of Economics.
    55. Qian, Hang, 2013. "Vector Autoregression with Mixed Frequency Data," MPRA Paper 47856, University Library of Munich, Germany.
    56. Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    57. Peter Broer & Jürgen Antony, 2013. "Financial Shocks and Economic Activity in the Netherlands," CPB Discussion Paper 260, CPB Netherlands Bureau for Economic Policy Analysis.
    58. Gary Koop & Stuart McIntyre & James Mitchell, 2020. "UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 91-119, January.
    59. Jürgen Antony & D. Broer, 2015. "Euro area financial shocks and economic activity in The Netherlands," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 571-595, August.
    60. Selma Toker & Nimet Özbay & Kristofer Månsson, 2022. "Mixed data sampling regression: Parameter selection of smoothed least squares estimator," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 718-751, July.

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.
    See citations under working paper version above.
  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, Oxford University Press, vol. 13(3), pages 698-721.
    See citations under working paper version above.Sorry, no citations of articles recorded.

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, Wikipedia, or ReplicationWiki 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
  2. NEP-DGE: Dynamic General Equilibrium (1) 2014-01-10
  3. NEP-ECM: Econometrics (1) 2012-02-01
  4. NEP-ETS: Econometric Time Series (1) 2012-02-01
  5. NEP-MAC: Macroeconomics (1) 2014-01-10
  6. NEP-MON: Monetary Economics (1) 2014-01-10
  7. NEP-MST: Market Microstructure (1) 2012-02-01

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