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Johannes Tang Kristensen

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Personal Details

First Name:Johannes
Middle Name:Tang
Last Name:Kristensen
Suffix:
RePEc Short-ID:pkr133
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Affiliation

(50%) Center for Research in Econometric Analysis of Time Series (CREATES)
Institut for Økonomi
Aarhus Universitet

Aarhus, Denmark
http://www.creates.au.dk/
RePEc:edi:creaudk (more details at EDIRC)

(50%) Institut for Økonomi
Aarhus Universitet

Aarhus, Denmark
http://econ.au.dk/
RePEc:edi:ifoaudk (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Laurent Callot & Johannes Tang Kristensen, 2015. "Regularized Estimation of Structural Instability in Factor Models: The US Macroeconomy and the Great Moderation," Tinbergen Institute Discussion Papers 15-069/III, Tinbergen Institute.
  2. Laurent Callot & Johannes Tang Kristensen, 2014. "Vector Autoregressions with Parsimoniously Time Varying Parameters and an Application to Monetary Policy," CREATES Research Papers 2014-41, Department of Economics and Business Economics, Aarhus University.
  3. Johannes Tang Kristensen, 2013. "Diffusion Indexes with Sparse Loadings," CREATES Research Papers 2013-22, Department of Economics and Business Economics, Aarhus University.
  4. Malene Kallestrup-Lamb & Anders Bredahl Kock & Johannes Tang Kristensen, 2013. "Lassoing the Determinants of Retirement," CREATES Research Papers 2013-21, Department of Economics and Business Economics, Aarhus University.
  5. Johannes Tang Kristensen, 2012. "Factor-Based Forecasting in the Presence of Outliers: Are Factors Better Selected and Estimated by the Median than by The Mean?," CREATES Research Papers 2012-28, Department of Economics and Business Economics, Aarhus University.
  6. Stefan Holst Bache & Christian M. Dahl & Johannes Tang, "undated". "Headlights on tobacco road to low birthweight outcomes - Evidence from a battery of quantile regression estimators and a heterogeneous panelCreation-Date: 20080508," CREATES Research Papers 2008-20, Department of Economics and Business Economics, Aarhus University.

Articles

  1. Kristensen Johannes Tang, 2014. "Factor-based forecasting in the presence of outliers: Are factors better selected and estimated by the median than by the mean?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 309-338, May.
  2. Stefan Bache & Christian Dahl & Johannes Kristensen, 2013. "Headlights on tobacco road to low birthweight outcomes," Empirical Economics, Springer, vol. 44(3), pages 1593-1633, June.

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. Laurent Callot & Johannes Tang Kristensen, 2014. "Vector Autoregressions with Parsimoniously Time Varying Parameters and an Application to Monetary Policy," CREATES Research Papers 2014-41, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Laurent Callot & Johannes Tang Kristensen, 2016. "Regularized Estimation of Structural Instability in Factor Models: The US Macroeconomy and the Great Moderation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 437-479, Emerald Group Publishing Limited.
    2. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    3. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.

  2. Johannes Tang Kristensen, 2013. "Diffusion Indexes with Sparse Loadings," CREATES Research Papers 2013-22, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kyosuke Chikamatsu, Naohisa Hirakata, Yosuke Kido, Kazuki Otaka, 2018. "Nowcasting Japanese GDPs," Bank of Japan Working Paper Series 18-E-18, Bank of Japan.
    2. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," PSE Working Papers halshs-02235543, HAL.
    3. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    4. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    5. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," Working Papers halshs-02235543, HAL.

  3. Malene Kallestrup-Lamb & Anders Bredahl Kock & Johannes Tang Kristensen, 2013. "Lassoing the Determinants of Retirement," CREATES Research Papers 2013-21, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Mehmet Caner & Anders Bredahl Kock, 2013. "Oracle Inequalities for Convex Loss Functions with Non-Linear Targets," CREATES Research Papers 2013-51, Department of Economics and Business Economics, Aarhus University.

  4. Johannes Tang Kristensen, 2012. "Factor-Based Forecasting in the Presence of Outliers: Are Factors Better Selected and Estimated by the Median than by The Mean?," CREATES Research Papers 2012-28, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    2. González-Rivera, Gloria, 2018. "Growth in Stress," DES - Working Papers. Statistics and Econometrics. WS 26623, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.
    4. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Hallin, Marc, 2020. "Robustness and the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Textos para discussão 521, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    5. Johannes Tang Kristensen, 2013. "Diffusion Indexes with Sparse Loadings," CREATES Research Papers 2013-22, Department of Economics and Business Economics, Aarhus University.

  5. Stefan Holst Bache & Christian M. Dahl & Johannes Tang, "undated". "Headlights on tobacco road to low birthweight outcomes - Evidence from a battery of quantile regression estimators and a heterogeneous panelCreation-Date: 20080508," CREATES Research Papers 2008-20, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Hope Corman & Dhaval M. Dave & Nancy E. Reichman, 2017. "Evolution of the Infant Health Production Function," Working Papers id:12331, eSocialSciences.
    2. Christian M. Dahl & Daniel le Maire & Jakob R. Munch, 2011. "Wage Dispersion and Decentralization of Wage Bargaining," CREATES Research Papers 2011-48, Department of Economics and Business Economics, Aarhus University.
    3. Barrientos, Armando & Debowicz, Darío & Woolard, Ingrid, 2016. "Heterogeneity in Bolsa Família outcomes," The Quarterly Review of Economics and Finance, Elsevier, vol. 62(C), pages 33-40.

Articles

  1. Kristensen Johannes Tang, 2014. "Factor-based forecasting in the presence of outliers: Are factors better selected and estimated by the median than by the mean?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 309-338, May.
    See citations under working paper version above.
  2. Stefan Bache & Christian Dahl & Johannes Kristensen, 2013. "Headlights on tobacco road to low birthweight outcomes," Empirical Economics, Springer, vol. 44(3), pages 1593-1633, June.

    Cited by:

    1. Fulvio Castellacci & Bart Los & Gaaitzen Vries, 2014. "Sectoral productivity trends: convergence islands in oceans of non-convergence," Journal of Evolutionary Economics, Springer, vol. 24(5), pages 983-1007, November.
    2. Damien Rousselière, 2017. "A flexible approach to age dependence in organizational mortality. Comparing the life duration for cooperative and non-cooperative enterprises using a Bayesian Generalized Additive Discrete Time Survi," Working Papers SMART 17-08, INRAE UMR SMART.
    3. Hope Corman & Dhaval M. Dave & Nancy E. Reichman, 2017. "Evolution of the Infant Health Production Function," Working Papers id:12331, eSocialSciences.
    4. Dariusz Wójcik & Eric Knight & Vladimír Pažitka, 2018. "What turns cities into international financial centres? Analysis of cross-border investment banking 2000–2014," Journal of Economic Geography, Oxford University Press, vol. 18(1), pages 1-33.
    5. Simona Mateut & Thanaset Chevapatrakul, 2017. "Customer financing, bargaining power and trade credit uptake," Discussion Papers 2017/04, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    6. Philip Kostov & Julie Le Gallo, 2015. "Convergence: A Story of Quantiles and Spillovers," Kyklos, Wiley Blackwell, vol. 68(4), pages 552-576, November.
    7. Christian M. Dahl & Daniel le Maire & Jakob R. Munch, 2011. "Wage Dispersion and Decentralization of Wage Bargaining," CREATES Research Papers 2011-48, Department of Economics and Business Economics, Aarhus University.
    8. Mahmoud Hassan & Walid Oueslati & Damien Rousselière, 2020. "Environmental taxes, reforms and economic growth: An empirical analysis of panel data," Post-Print hal-02503305, HAL.
    9. Pourya Valizadeh & Shu Wen Ng, 2021. "Would A National Sugar‐Sweetened Beverage Tax in the United States Be Well Targeted?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 961-986, May.
    10. Xavier Vollenweider, 2014. "A simple framework for the estimation of climate exposure," GRI Working Papers 158, Grantham Research Institute on Climate Change and the Environment.
    11. Bresson, Georges & Lacroix, Guy & Arshad Rahman, Mohammad, 2020. "Bayesian Panel Quantile Regression for Binary Outcomes with Correlated Random Effects: An Application on Crime Recidivism in Canada," IZA Discussion Papers 12928, Institute of Labor Economics (IZA).
    12. Yamada, Ken, 2016. "Tracing the impact of large minimum wage changes on household welfare in Indonesia," European Economic Review, Elsevier, vol. 87(C), pages 287-303.
    13. Geraci, Marco, 2019. "Modelling and estimation of nonlinear quantile regression with clustered data," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 30-46.
    14. Samiul Haque, 2022. "US federal farm payments and farm size: Quantile estimation on panel data," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 139-154, February.
    15. Nicky Lee Grant, 2016. "Correlated Random Effects Quantile Estimation of the Tax-Price Elasticity of Charitable Donations," Economics Bulletin, AccessEcon, vol. 36(3), pages 1729-1736.
    16. Sinem Koçak & Özge Barış-Tüzemen, 2022. "Impact of the COVID-19 on foreign direct investment inflows in emerging economies: evidence from panel quantile regression," Future Business Journal, Springer, vol. 8(1), pages 1-12, December.
    17. Anesu Gelfand Kuhudzai & Guido Van Hal & Stefan Van Dongen & Muhammad Ehsanul Hoque, 2022. "Modelling of South African Hypertension: Application of Panel Quantile Regression," IJERPH, MDPI, vol. 19(10), pages 1-10, May.
    18. Raffaele Miniaci & Paolo Panteghini, 2021. "On the Capital Structure of Foreign Subsidiaries: Evidence from a Panel Data Quantile Regression Model," CESifo Working Paper Series 9085, CESifo.
    19. Tilov, Ivan & Farsi, Mehdi & Volland, Benjamin, 2020. "From frugal Jane to wasteful John: A quantile regression analysis of Swiss households’ electricity demand," Energy Policy, Elsevier, vol. 138(C).
    20. Chin-Hsien Yu & Bruce A. McCarl, 2018. "The Water Implications of Greenhouse Gas Mitigation: Effects on Land Use, Land Use Change, and Forestry," Sustainability, MDPI, vol. 10(7), pages 1-22, July.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 8 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-ECM: Econometrics (5) 2008-06-27 2012-06-25 2013-07-15 2014-12-08 2015-06-13. Author is listed
  2. NEP-MAC: Macroeconomics (5) 2014-12-08 2014-12-13 2015-04-25 2015-06-13 2015-06-13. Author is listed
  3. NEP-ETS: Econometric Time Series (4) 2012-06-25 2014-12-08 2014-12-13 2015-04-25
  4. NEP-MON: Monetary Economics (3) 2014-12-08 2014-12-13 2015-04-25
  5. NEP-FOR: Forecasting (2) 2012-06-25 2013-07-15
  6. NEP-AGE: Economics of Ageing (1) 2013-07-05
  7. NEP-DEM: Demographic Economics (1) 2013-07-05
  8. NEP-EUR: Microeconomic European Issues (1) 2013-07-05
  9. NEP-HEA: Health Economics (1) 2008-06-27
  10. NEP-LAB: Labour Economics (1) 2013-07-05
  11. NEP-LMA: Labor Markets - Supply, Demand, and Wages (1) 2013-07-05

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