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Lasse Bork

Personal Details

First Name:Lasse
Middle Name:
Last Name:Bork
Suffix:
RePEc Short-ID:pbo460
[This author has chosen not to make the email address public]
http://lassebork.dk
Aalborg University Department of Business and Management http://personprofil.aau.dk/profil/123645?lang=en Fibigerstraede 2 DK-9220 Aalborg East T: +45 9940 2707

Affiliation

Institut for Økonomi og Ledelse
Aalborg Universitet

Aalborg, Denmark
http://www.business.aau.dk/

: (+45) 96 35 82 20
(+45) 98 15 35 05
Fibigerstræde 4 , DK-9220 Aalborg Øst
RePEc:edi:ieaucdk (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2016. "A New Index of Housing Sentiment," CREATES Research Papers 2016-32, Department of Economics and Business Economics, Aarhus University.
  2. Lasse Bork & Stig V. Møller, 2012. "Housing price forecastability: A factor analysis," CREATES Research Papers 2012-27, Department of Economics and Business Economics, Aarhus University.
  3. Lasse Bork & Hans Dewachter & Romain Houssa, 2009. "Identification of Macroeconomic Factors in Large Panels," CREATES Research Papers 2009-43, Department of Economics and Business Economics, Aarhus University.
  4. Lasse Bork, 2009. "Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach," CREATES Research Papers 2009-11, Department of Economics and Business Economics, Aarhus University.

Articles

  1. Bork, Lasse & Møller, Stig V., 2015. "Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection," International Journal of Forecasting, Elsevier, vol. 31(1), pages 63-78.

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. Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2016. "A New Index of Housing Sentiment," CREATES Research Papers 2016-32, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Christophe André & Petre Caraiani & Adrian Cantemir Čalin & Rangan Gupta, 2018. "Can Monetary Policy Lean against Housing Bubbles?," Working Papers 201877, University of Pretoria, Department of Economics.
    2. Bauer, Gregory H., 2017. "International house price cycles, monetary policy and credit," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 88-114.
    3. Christina Christou & Rangan Gupta & Wendy Nyakabawo, 2018. "Time-Varying Impact of Uncertainty Shocks on the US Housing Market," Working Papers 201870, University of Pretoria, Department of Economics.
    4. Rangan Gupta & Chi Keung Marco Lau & Wendy Nyakabawo, 2018. "Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment," Working Papers 201866, University of Pretoria, Department of Economics.

  2. Lasse Bork & Stig V. Møller, 2012. "Housing price forecastability: A factor analysis," CREATES Research Papers 2012-27, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Theodore Panagiotidis & Panagiotis Printzis, 2016. "On the macroeconomic determinants of the housing market in Greece: a VECM approach," International Economics and Economic Policy, Springer, vol. 13(3), pages 387-409, July.
    2. Paul E. Carrillo & Erik Robert De Wit & William D. Larson, 2012. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the U.S. and the Netherlands," Working Papers 2012-11, The George Washington University, Institute for International Economic Policy.
    3. Paul E. Carrillo & Eric R. Wit & William Larson, 2015. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 43(3), pages 609-651, September.
    4. Mehmet Balcilar & Elie Bouri & Rangan Gupta & Mark E. Wohar, 2018. "Mortgage Default Risks and High-Frequency Predictability of the US Housing Market: A Reconsideration," Working Papers 201875, University of Pretoria, Department of Economics.
    5. Charles Rahal, 2015. "House Price Forecasts with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    6. Bork, Lasse & Møller, Stig V., 2015. "Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection," International Journal of Forecasting, Elsevier, vol. 31(1), pages 63-78.
    7. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.

  3. Lasse Bork & Hans Dewachter & Romain Houssa, 2009. "Identification of Macroeconomic Factors in Large Panels," CREATES Research Papers 2009-43, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Pegoraro, F. & Siegel, A. F. & Tiozzo Pezzoli, L., 2014. "Specification Analysis of International Treasury Yield Curve Factors," Working papers 490, Banque de France.
    2. Modugno, Michele & D'Agostino, Antonello & Osbat, Chiara, 2015. "A Global Trade Model for the Euro Area," Finance and Economics Discussion Series 2015-13, Board of Governors of the Federal Reserve System (US).
    3. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    4. Lasse Bork, 2009. "Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach," CREATES Research Papers 2009-11, Department of Economics and Business Economics, Aarhus University.
    5. Poncela, Pilar & Ruiz, Esther, 2015. "Small versus big-data factor extraction in Dynamic Factor Models: An empirical assessment," DES - Working Papers. Statistics and Econometrics. WS ws1502, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Piyachart Phiromswad & Takeshi Yagihashi, 2016. "Empirical identification of factor models," Empirical Economics, Springer, vol. 51(2), pages 621-658, September.
    7. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.

  4. Lasse Bork, 2009. "Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach," CREATES Research Papers 2009-11, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Modugno, Michele & D'Agostino, Antonello & Osbat, Chiara, 2015. "A Global Trade Model for the Euro Area," Finance and Economics Discussion Series 2015-13, Board of Governors of the Federal Reserve System (US).
    2. Lasse Bork & Hans Dewachter & Romain Houssa, 2009. "Identification of Macroeconomic Factors in Large Panels," CREATES Research Papers 2009-43, Department of Economics and Business Economics, Aarhus University.
    3. Andrés Felipe Londoño & Jorge Andrés Tamayo & Carlos Alberto Velásquez, 2012. "Dinámica de la política monetaria e inflación objetivo en Colombia: una aproximación FAVAR," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República - ESPE, vol. 30(68), pages 14-71, June.
    4. Eugen Ivanov & Aleksey Min & Franz Ramsauer, 2017. "Copula-Based Factor Models for Multivariate Asset Returns," Econometrics, MDPI, Open Access Journal, vol. 5(2), pages 1-24, May.
    5. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    6. Kemal Bagzibagli, 2012. "Monetary Transmission Mechanism and Time Variation in the Euro Area," Discussion Papers 12-12, Department of Economics, University of Birmingham.
    7. André Binette & Tony Chernis & Daniel de Munnik, 2017. "Global Real Activity for Canadian Exports: GRACE," Discussion Papers 17-2, Bank of Canada.
    8. Hacioglu, Sinem & Tuzcuoglu, Kerem, 2016. "Interpreting the latent dynamic factors by threshold FAVAR model," Bank of England working papers 622, Bank of England.

Articles

  1. Bork, Lasse & Møller, Stig V., 2015. "Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection," International Journal of Forecasting, Elsevier, vol. 31(1), pages 63-78.

    Cited by:

    1. Jan Prüser, 2019. "Adaptive learning from model space," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(1), pages 29-38, January.
    2. Krzysztof Drachal, 2018. "Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework," Energies, MDPI, Open Access Journal, vol. 11(5), pages 1-24, May.
    3. Christou, Christina & Gupta, Rangan & Hassapis, Christis, 2017. "Does economic policy uncertainty forecast real housing returns in a panel of OECD countries? A Bayesian approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 50-60.
    4. Graefe, Andreas & Küchenhoff, Helmut & Stierle, Veronika & Riedl, Bernhard, 2015. "Limitations of Ensemble Bayesian Model Averaging for forecasting social science problems," International Journal of Forecasting, Elsevier, vol. 31(3), pages 943-951.
    5. Mehmet Balcilar & Elie Bouri & Rangan Gupta & Mark E. Wohar, 2018. "Mortgage Default Risks and High-Frequency Predictability of the US Housing Market: A Reconsideration," Working Papers 201875, University of Pretoria, Department of Economics.
    6. Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
    7. Christou, Christina & Gupta, Rangan & Nyakabawo, Wendy & Wohar, Mark E., 2018. "Do house prices hedge inflation in the US? A quantile cointegration approach," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 15-26.
    8. Wei, Yu & Cao, Yang, 2017. "Forecasting house prices using dynamic model averaging approach: Evidence from China," Economic Modelling, Elsevier, vol. 61(C), pages 147-155.
    9. Rangan Gupta & Chi Keung Marco Lau & Wendy Nyakabawo, 2018. "Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment," Working Papers 201866, University of Pretoria, Department of Economics.
    10. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.
    11. Krzysztof Drachal, 2018. "Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices," Sustainability, MDPI, Open Access Journal, vol. 10(8), pages 1-27, August.
    12. Girum D. Abate & Luc Anselin, 2016. "House price fluctuations and the business cycle dynamics," CREATES Research Papers 2016-06, Department of Economics and Business Economics, Aarhus University.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 6 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-MAC: Macroeconomics (5) 2009-03-22 2009-04-25 2009-10-10 2010-04-17 2016-11-20. Author is listed
  2. NEP-CBA: Central Banking (3) 2009-03-22 2009-04-25 2009-10-10
  3. NEP-URE: Urban & Real Estate Economics (2) 2012-06-13 2016-11-20
  4. NEP-BEC: Business Economics (1) 2009-10-10
  5. NEP-ECM: Econometrics (1) 2009-10-10
  6. NEP-ETS: Econometric Time Series (1) 2009-10-10
  7. NEP-FOR: Forecasting (1) 2012-06-13

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