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Sune Karlsson

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Andrén, Daniela & Clark, Andrew E & D´Ambrosio, Conchita & Karlsson, Sune & Pettersson, Nicklas, 2017. "Subjective and physiological measures of well-being: an exploratory analysis using birth-cohort data," Working Papers 2017:8, Örebro University, School of Business.

    Mentioned in:

    1. Subjective and physiological measures of well-being: an exploratory analysis using birth-cohort data
      by maximorossi in NEP-LTV blog on 2018-02-21 12:41:45
  2. Andrén, Daniela & Clark, Andrew E. & D’Ambrosio, Conchita & Karlsson, Sune & Pettersson, Nicklas, 2019. "New ways to measure well-being? A first joint analysis of subjective and objective measures," Working Papers 2018:13, Örebro University, School of Business.

    Mentioned in:

    1. New ways to measure well-being? A first joint analysis of subjective and objective measures
      by maximorossi in NEP-LTV blog on 2019-05-14 14:44:11
  3. Author Profile
    1. Volunteer recognition: Thomas Krichel
      by Christian Zimmermann in RePEc blog on 2008-02-21 22:30:00
    2. Volunteer recognition: Sune Karlsson
      by Christian Zimmermann in RePEc blog on 2008-04-19 21:30:00
    3. EconPapers and LogEc on new hardware
      by Christian Zimmermann in RePEc blog on 2009-08-12 07:35:50
    4. MPRA, the Munich Personal RePEc Archive
      by Ekkehart Schlicht in RePEc blog on 2009-08-28 04:29:29
    5. RePEcFB – An integration of your RePEc data into your Facebook profile
      by Christian Zimmermann in RePEc blog on 2009-09-10 01:56:55
    6. How abstract views and downloads are counted
      by Christian Zimmermann in RePEc blog on 2009-09-19 07:25:52

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897, Elsevier.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.

    Mentioned in:

    1. NUMERICAL METHODS FOR ESTIMATION AND INFERENCE IN BAYESIAN VAR‐MODELS (Journal of Applied Econometrics 1997) in ReplicationWiki ()
    2. NUMERICAL METHODS FOR ESTIMATION AND INFERENCE IN BAYESIAN VAR-MODELS (Journal of Applied Econometrics 1997) in ReplicationWiki ()

Working papers

  1. Sune Karlsson & Stepan Mazur & Hoang Nguyen, 2021. "Vector autoregression models with skewness and heavy tails," Papers 2105.11182, arXiv.org.

    Cited by:

    1. Katarzyna Budnik & Gerhard Rünstler, 2023. "Identifying structural VARs from sparse narrative instruments: Dynamic effects of US macroprudential policies," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 186-201, March.
    2. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2022. "The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area," Finance Research Letters, Elsevier, vol. 46(PA).
    3. Guljanov, Gaygysyz & Mutschler, Willi & Trede, Mark, 2022. "Pruned Skewed Kalman Filter and Smoother: With Application to the Yield Curve," Dynare Working Papers 78, CEPREMAP.
    4. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    5. Kiss, Tamas & Nguyen, Hoang & Österholm, Pär, 2022. "Modelling Okun’s Law – Does non-Gaussianity Matter?," Working Papers 2022:1, Örebro University, School of Business.
    6. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    7. Florian Huber & Massimiliano Marcellino, 2023. "Coarsened Bayesian VARs -- Correcting BVARs for Incorrect Specification," Papers 2304.07856, arXiv.org, revised May 2023.
    8. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang, 2022. "Predicting returns and dividend growth — The role of non-Gaussian innovations," Finance Research Letters, Elsevier, vol. 46(PA).
    9. Andrea Renzetti, 2023. "Modelling and Forecasting Macroeconomic Risk with Time Varying Skewness Stochastic Volatility Models," Papers 2306.09287, arXiv.org, revised Nov 2023.

  2. Karlsson, Sune & Mazur, Stepan & Muhinyuza, Stanislas, 2020. "Statistical Inference for the Tangency Portfolio in High Dimension," Working Papers 2020:10, Örebro University, School of Business.

    Cited by:

    1. Alfelt, Gustav & Mazur, Stepan, 2020. "On the mean and variance of the estimated tangency portfolio weights for small samples," Working Papers 2020:8, Örebro University, School of Business.
    2. Javed, Farrukh & Mazur, Stepan & Thorsén, Erik, 2021. "Tangency portfolio weights under a skew-normal model in small and large dimensions," Working Papers 2021:13, Örebro University, School of Business.

  3. Karlsson, Sune & Mazur, Stepan, 2020. "Flexible Fat-tailed Vector Autoregression," Working Papers 2020:5, Örebro University, School of Business.

    Cited by:

    1. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    2. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2021. "Vector autoregression models with skewness and heavy tails," Working Papers 2021:8, Örebro University, School of Business.
    3. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.

  4. Karlsson, Sune & Österholm, Pär, 2019. "The Relation between the Corporate Bond-Yield Spread and the Real Economy: Stable or TimeVarying?," Working Papers 2019:7, Örebro University, School of Business.

    Cited by:

    1. Apergis Nicholas, 2021. "Forecasting US overseas travelling with univariate and multivariate models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 963-976, September.
    2. Kiss, Tamás & Österholm, Pär, 2020. "Fat tails in leading indicators," Economics Letters, Elsevier, vol. 193(C).
    3. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2022. "The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area," Finance Research Letters, Elsevier, vol. 46(PA).
    4. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    5. Edvinsson, Rodney & Karlsson, Sune & Österholm, Pär, 2023. "Does Money Growth Predict Inflation? Evidence from Vector Autoregressions Using Four Centuries of Data," Working Papers 2023:3, Örebro University, School of Business.
    6. Sedegah Kordzo & Odhiambo Nicholas M., 2021. "A Review of the Impact of External Shocks on Monetary Policy Effectiveness in Non-WAEMU Countries," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 31(3), pages 37-59, September.

  5. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.

    Cited by:

    1. Pham, Binh Thai & Sala, Hector, 2021. "Cross-Country Connectedness in Inflation and Unemployment: Measurement and Macroeconomic Consequences," IZA Discussion Papers 14212, Institute of Labor Economics (IZA).
    2. Sune Karlsson & Pär Österholm, 2023. "Is the US Phillips curve stable? Evidence from Bayesian vector autoregressions," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(1), pages 287-314, January.
    3. Unn Lindholm & Marcus Mossfeldt & Pär Stockhammar, 2020. "Forecasting inflation in Sweden," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(1), pages 39-68, April.

  6. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.

    Cited by:

    1. Derek Zweig, 2020. "Market Power, NAIRU, and the Phillips Curve," Abstract and Applied Analysis, Hindawi, vol. 2020, pages 1-18, December.
    2. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    3. Chan, Joshua C.C. & Eisenstat, Eric, 2018. "Comparing hybrid time-varying parameter VARs," Economics Letters, Elsevier, vol. 171(C), pages 1-5.
    4. Aquino, Juan, 2019. "The Small Open Economy New-Keynesian Phillips Curve: Specification, Structural Breaks and Robustness," Working Papers 2019-019, Banco Central de Reserva del Perú.
    5. Beechey, Meredith & Österholm, Pär & Poon, Aubrey, 2023. "Estimating the US trend short-term interest rate," Finance Research Letters, Elsevier, vol. 55(PA).
    6. Fu, Bowen, 2020. "Is the slope of the Phillips curve time-varying? Evidence from unobserved components models," Economic Modelling, Elsevier, vol. 88(C), pages 320-340.

  7. Karlsson, Sune, 2012. "Conditional posteriors for the reduced rank regression model," Working Papers 2012:11, Örebro University, School of Business.

    Cited by:

    1. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.

  8. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.

    Cited by:

    1. Pedro Costa Ferreira & Raíra Marotta B. Vieira & Felipi Bruno Silva & Ingrid C. L. Oliveira, 2019. "Measuring Brazilian Economic Uncertainty," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(1), pages 25-40, April.
    2. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    3. Lutz Kilian & Xiaoqing Zhou, 2021. "The Impact of Rising Oil Prices on U.S. Inflation and Inflation Expectations in 2020-23," CESifo Working Paper Series 9455, CESifo.
    4. Luc Bauwens & Guillaume Chevillon & Sébastien Laurent, 2023. "We modeled long memory with just one lag!," Post-Print hal-04185755, HAL.
    5. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    6. Silvia Miranda-Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Documents de Travail de l'OFCE 2018-18, Observatoire Francais des Conjonctures Economiques (OFCE).
    7. Máximo Camacho & Matías Pacce & Gabriel Pérez-Quirós, 2020. "Spillover effects in international business cycles," Working Papers 2034, Banco de España.
    8. Lai, Wei-Ting & Chen, Ray-Bing & Chen, Ying & Koch, Thorsten, 2022. "Variational Bayesian inference for network autoregression models," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    9. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2022. "An automated prior robustness analysis in Bayesian model comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 583-602, April.
    10. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    11. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    12. Diab, Sara & Karaki, Mohamad B., 2023. "Do increases in gasoline prices cause higher food prices?," Energy Economics, Elsevier, vol. 127(PB).
    13. Thu, Le Ha & Leon-Gonzalez, Roberto, 2021. "Forecasting macroeconomic variables in emerging economies," Journal of Asian Economics, Elsevier, vol. 77(C).
    14. Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse VAR models," Papers 1608.02740, arXiv.org, revised Oct 2018.
    16. Epstein, Brendan & Finkelstein Shapiro, Alan & González Gómez, Andrés, 2019. "Global financial risk, aggregate fluctuations, and unemployment dynamics," Journal of International Economics, Elsevier, vol. 118(C), pages 351-418.
    17. Kilian, Lutz & Inoue, Atsushi, 2020. "The Role of the Prior in Estimating VAR Models with Sign Restrictions," CEPR Discussion Papers 15545, C.E.P.R. Discussion Papers.
    18. Louzis Dimitrios P., 2016. "Steady-state priors and Bayesian variable selection in VAR forecasting," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(5), pages 495-527, December.
    19. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    20. Sebastian Ankargren & Mårten Bjellerup & Hovick Shahnazarian, 2017. "The importance of the financial system for the real economy," Empirical Economics, Springer, vol. 53(4), pages 1553-1586, December.
    21. Florian Huber & Tamas Krisztin & Philipp Piribauer, 2014. "Forecasting Global Equity Indices using Large Bayesian VARs," Department of Economics Working Papers wuwp184, Vienna University of Economics and Business, Department of Economics.
    22. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2016. "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1371-1391, November.
    23. Joshua C. C. Chan, 2019. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," CAMA Working Papers 2019-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    24. Giannone, Domenico & Banbura, Marta & Lenza, Michele, 2014. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," CEPR Discussion Papers 9931, C.E.P.R. Discussion Papers.
    25. Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2012. "Prior Selection for Vector Autoregressions," CEPR Discussion Papers 8755, C.E.P.R. Discussion Papers.
    26. Florian Huber & Jesus Crespo-Cuaresma & Martin Feldkircher, 2014. "Forecasting with Bayesian Global Vector Autoregressions," ERSA conference papers ersa14p25, European Regional Science Association.
    27. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
    28. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
    29. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
    30. Karamanis, Dimitrios & Kechrinioti, Alexandra, 2023. "The Greek-Turkish rivalry: A Bayesian VAR approach," MPRA Paper 116827, University Library of Munich, Germany.
    31. Katarzyna Budnik & Gerhard Rünstler, 2023. "Identifying structural VARs from sparse narrative instruments: Dynamic effects of US macroprudential policies," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 186-201, March.
    32. Sinan Q. Salih & Intisar Alakili & Ufuk Beyaztas & Shamsuddin Shahid & Zaher Mundher Yaseen, 2021. "Prediction of dissolved oxygen, biochemical oxygen demand, and chemical oxygen demand using hydrometeorological variables: case study of Selangor River, Malaysia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 8027-8046, May.
    33. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2019. "Priors for the Long Run," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 565-580, April.
    34. Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2022. "Nowcasting with large Bayesian vector autoregressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 500-519.
    35. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    36. Dieppe, Alistair & van Roye, Björn & Legrand, Romain, 2016. "The BEAR toolbox," Working Paper Series 1934, European Central Bank.
    37. Oğuz, Fuat & Akkemik, K. Ali & Göksal, Koray, 2015. "Toward a wider market definition in broadband: The case of Turkey," Utilities Policy, Elsevier, vol. 37(C), pages 111-119.
    38. Aleksandra Bezborodova & Yuri Mihalenok, 2015. "Analysis of the monetary policy transmission mechanism in the Republic of Belarus: Bayesian approach (in Russian)," Quantile, Quantile, issue 13, pages 41-61, May.
    39. Oskar Gustafsson & Mattias Villani & Pär Stockhammar, 2023. "Bayesian optimization of hyperparameters from noisy marginal likelihood estimates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 577-595, June.
    40. Joshua C.C. Chan & Liana Jacobi & Dan Zhu, 2018. "How sensitive are VAR forecasts to prior hyperparameters? An automated sensitivity analysis," CAMA Working Papers 2018-25, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    41. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.
    42. Tomasz Wozniak, 2016. "Rare Events and Risk Perception: Evidence from Fukushima Accident," Department of Economics - Working Papers Series 2021, The University of Melbourne.
    43. Hajargasht, Gholamreza & Rao, D.S. Prasada, 2019. "Multilateral index number systems for international price comparisons: Properties, existence and uniqueness," Journal of Mathematical Economics, Elsevier, vol. 83(C), pages 36-47.
    44. Ciobotaru, Corina & Mazza, Christian, 2022. "Consistency and asymptotic normality of M-estimates of scatter on Grassmann manifolds," Journal of Multivariate Analysis, Elsevier, vol. 190(C).
    45. Carrera, Cesar & Ledesma, Alan, 2015. "Proyección de la inflación agregada con modelos de vectores autorregresivos bayesianos," Working Papers 2015-003, Banco Central de Reserva del Perú.
    46. Joshua C.C. Chan, 2015. "Large Bayesian VARs: A flexible Kronecker error covariance structure," CAMA Working Papers 2015-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    47. Misha van Beek, 2020. "Consistent Calibration of Economic Scenario Generators: The Case for Conditional Simulation," Papers 2004.09042, arXiv.org.
    48. Anastasios Evgenidis & Apostolos Fasianos, 2019. "Monetary Policy and Wealth Inequalities in Great Britain: Assessing the role of unconventional policies for a decade of household data," Papers 1912.09702, arXiv.org.
    49. Petrella, Ivan & Antolin-Diaz, Juan & Rubio-Ramírez, Juan Francisco, 2018. "Structural Scenario Analysis with SVARs," CEPR Discussion Papers 12579, C.E.P.R. Discussion Papers.
    50. Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    51. Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.
    52. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
    53. Mikosch, Heiner & Neuwirth, Stefan, 2015. "Real-time forecasting with a MIDAS VAR," BOFIT Discussion Papers 13/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    54. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2021. "Vector autoregression models with skewness and heavy tails," Working Papers 2021:8, Örebro University, School of Business.
    55. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High Dimensional Vector Autoregressive Models," CEIS Research Paper 534, Tor Vergata University, CEIS, revised 24 Mar 2022.
    56. Michal Franta, 2015. "Rare Shocks vs. Non-linearities: What Drives Extreme Events in the Economy? Some Empirical Evidence," Working Papers 2015/04, Czech National Bank.
    57. Andrejs Zlobins, 2019. "Country-Level Effects of the ECB's Expanded Asset Purchase Programme," Working Papers 2019/02, Latvijas Banka.
    58. Prüser Jan & Hanck Christoph, 2021. "A Comparison of Approaches to Select the Informativeness of Priors in BVARs," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 241(4), pages 501-525, August.
    59. Crespo Cuaresma, Jesús & Huber, Florian & Onorante, Luca, 2020. "Fragility and the effect of international uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 108(C).
    60. Akbar, Muhammad & Iqbal, Farhan & Noor, Farzana, 2019. "Bayesian analysis of dynamic linkages among gold price, stock prices, exchange rate and interest rate in Pakistan," Resources Policy, Elsevier, vol. 62(C), pages 154-164.
    61. Janda, Karel & Kravec, Peter, 2022. "VECM Modelling of the Price Dynamics for Fuels, Agricultural Commodities and Biofuels," EconStor Preprints 259404, ZBW - Leibniz Information Centre for Economics.
    62. Pop, Raluca-Elena, 2017. "A small-scale DSGE-VAR model for the Romanian economy," Economic Modelling, Elsevier, vol. 67(C), pages 1-9.
    63. Cesar Carrera & Alan Ledesma, 2015. "Aggregate Inflation Forecast with Bayesian Vector Autoregressive Models," Working Papers 50, Peruvian Economic Association.
    64. Jamie L. Cross & Chenghan Hou & Gary Koop, 2021. "Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs," Working Papers No 04/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    65. Pirschel, Inske, 2016. "Forecasting euro area recessions in real-time," Kiel Working Papers 2020, Kiel Institute for the World Economy (IfW Kiel).
    66. Tobias S. Blattner & Michael A. S. Joyce, 2020. "The Euro Area Bond Free Float and the Implications for QE," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(6), pages 1361-1395, September.
    67. Anttonen, Jetro, 2018. "Nowcasting the Unemployment Rate in the EU with Seasonal BVAR and Google Search Data," ETLA Working Papers 62, The Research Institute of the Finnish Economy.
    68. Lodge, David & Soudan, Michel, 2019. "Credit, financial conditions and the business cycle in China," Working Paper Series 2244, European Central Bank.
    69. Koop, Gary, 2014. "Forecasting with dimension switching VARs," International Journal of Forecasting, Elsevier, vol. 30(2), pages 280-290.
    70. Follett, Lendie & Yu, Cindy, 2019. "Achieving parsimony in Bayesian vector autoregressions with the horseshoe prior," Econometrics and Statistics, Elsevier, vol. 11(C), pages 130-144.
    71. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.
    72. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Large Vector Autoregressions with Stochastic Volatility and Flexible Priors," Working Papers (Old Series) 1617, Federal Reserve Bank of Cleveland.
    73. 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.
    74. Samuel N. Cohen & Silvia Lui & Will Malpass & Giulia Mantoan & Lars Nesheim & 'Aureo de Paula & Andrew Reeves & Craig Scott & Emma Small & Lingyi Yang, 2023. "Nowcasting with signature methods," Papers 2305.10256, arXiv.org.
    75. Ankargren, Sebastian & Shahnazarian, Hovick, 2019. "The Interaction Between Fiscal and Monetary Policies: Evidence from Sweden," Working Paper Series 365, Sveriges Riksbank (Central Bank of Sweden), revised 01 Apr 2019.
    76. Damian Stelmasiak & Grzegorz Szafrański, 2016. "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 21-42, March.
    77. Cross, Jamie L. & Hou, Chenghan & Nguyen, Bao H., 2021. "On the China factor in the world oil market: A regime switching approach11We thank Hilde Bjørnland, Tatsuyoshi Okimoto, Ippei Fujiwara, Knut Aastveit, Leif Anders Thorsrud, Francesco Ravazzolo, Renee ," Energy Economics, Elsevier, vol. 95(C).
    78. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2014. "Forecasting with Bayesian Global Vector Autoregressive Models: A Comparison of Priors," Working Papers 189, Oesterreichische Nationalbank (Austrian Central Bank).
    79. Meilina Retno Hapsari & Suci Astutik & Loekito Adi Soehono, 2020. "Estimation of VECM Parameter Using Bayesian Approach: An Application to Analysis of Macroeconomic Variables," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 9(6), pages 113-113, November.
    80. Laurynas Narusevicius & Tomas Ramanauskas & Laura Gudauskaitė & Tomas Reichenbachas, 2019. "Lithuanian house price index: modelling and forecasting," Bank of Lithuania Occasional Paper Series 28, Bank of Lithuania.
    81. Tomasz Woźniak, 2016. "Bayesian Vector Autoregressions," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 49(3), pages 365-380, September.
    82. Valeriu Nalban, 2015. "Do Bayesian Vector Autoregressive models improve density forecasting accuracy? The case of the Czech Republic and Romania," International Journal of Economic Sciences, International Institute of Social and Economic Sciences, vol. 4(1), pages 60-74, March.
    83. Apostolos Ampountolas, 2019. "Forecasting hotel demand uncertainty using time series Bayesian VAR models," Tourism Economics, , vol. 25(5), pages 734-756, August.
    84. Julius Stakenas, 2018. "Slicing up inflation: analysis and forecasting of Lithuanian inflation components," Bank of Lithuania Working Paper Series 56, Bank of Lithuania.
    85. Paci, Lucia & Consonni, Guido, 2020. "Structural learning of contemporaneous dependencies in graphical VAR models," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    86. Mikhail Mamonov & Anna Pestova, 2021. ""Sorry, You're Blocked." Economic Effects of Financial Sanctions on the Russian Economy," CERGE-EI Working Papers wp704, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    87. James P. LeSage & Daniel Hendrikz, 2019. "Large Bayesian vector autoregressive forecasting for regions: A comparison of methods based on alternative disturbance structures," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 563-599, June.
    88. Dimitris P. Louzis, 2014. "Macroeconomic and credit forecasts in a small economy during crisis: A large Bayesian VAR approach," Working Papers 184, Bank of Greece.
    89. Petrevski, Goran & Exterkate, Peter & Tevdovski, Dragan & Bogoev, Jane, 2015. "The transmission of foreign shocks to South Eastern European economies: A Bayesian VAR approach," Economic Systems, Elsevier, vol. 39(4), pages 632-643.
    90. MAMATZAKIS, emmanuel & MAMATZAKIS, E, 2022. "Understanding the impact of travel on wellbeing: evidence for Great Britain during the pandemic," MPRA Paper 112974, University Library of Munich, Germany.
    91. Copaciu, Mihai & Nalban, Valeriu & Bulete, Cristian, 2015. "R.E.M. 2.0, An estimated DSGE model for Romania," Dynare Working Papers 48, CEPREMAP.

  9. Andersson, Michael K & Karlsson, Sune, 2007. "Bayesian Forecast Combination for VAR Models," Working Papers 2007:13, Örebro University, School of Business.

    Cited by:

    1. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
    2. Gary Koop, 2013. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Working Papers 1303, University of Strathclyde Business School, Department of Economics.
    3. Maik H. Wolters, 2015. "Evaluating Point and Density Forecasts of DSGE Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 74-96, January.
    4. Wolters, Maik H., 2011. "Forecasting under Model Uncertainty," VfS Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48723, Verein für Socialpolitik / German Economic Association.
    5. David Bolder & Yuliya Romanyuk, 2008. "Combining Canadian Interest-Rate Forecasts," Staff Working Papers 08-34, Bank of Canada.
    6. Anders Warne & Günter Coenen & Kai Christoffel, 2017. "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 103-119, January.
    7. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    8. James H. Stock & Mark W. Watson, 2012. "Generalized Shrinkage Methods for Forecasting Using Many Predictors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 481-493, June.
    9. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2009. "Does forecast combination improve Norges Bank inflation forecasts?," Working Paper 2009/01, Norges Bank.
    10. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    11. Dimitris Korobilis, 2008. "Forecasting in vector autoregressions with many predictors," Advances in Econometrics, in: Bayesian Econometrics, pages 403-431, Emerald Group Publishing Limited.
    12. Markus Jochmann & Gary Koop & Rodney W. Strachan, 2008. "Bayesian Forecasting using Stochastic Search Variable Selection in a VAR Subject to Breaks," Working Paper series 19_08, Rimini Centre for Economic Analysis.
    13. Dimitris Korobilis & Davide Pettenuzzo, 2017. "Adaptive Hierarchical Priors for High-Dimensional Vector Autoregessions," Working Papers 115, Brandeis University, Department of Economics and International Business School.
    14. Hugo Gerard & Kristoffer Nimark, 2008. "Combining Multivariate Density Forecasts Using Predictive Criteria," RBA Research Discussion Papers rdp2008-02, Reserve Bank of Australia.
    15. Dr. James Mitchell, 2009. "Macro Modelling with Many Models," National Institute of Economic and Social Research (NIESR) Discussion Papers 337, National Institute of Economic and Social Research.
    16. Mirriam Chitalu Chama-Chiliba & Rangan Gupta & Nonophile Nkambule & Naomi Tlotlego, 2011. "Forecasting Key Macroeconomic Variables of the South African Economy Using Bayesian Variable Selection," Working Papers 201132, University of Pretoria, Department of Economics.
    17. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working papers 2012-38, University of Connecticut, Department of Economics, revised Dec 2013.
    18. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    19. Tomáš Jeřábek & Radka Šperková, 2015. "A Predictive Likelihood Approach to Bayesian Averaging," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(4), pages 1269-1276.
    20. Jakub Ryšánek, 2010. "Combining VAR Forecast Densities Using Fast Fourier Transform," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2010(5), pages 72-88.

  10. Karlsson, Sune & Lundin, Nannan & Sjöholm, Fredrik & He, Ping, 2007. "FDI and Job Creation in China," Working Paper Series 723, Research Institute of Industrial Economics.

    Cited by:

    1. Samuel Ajayi-Obe, 2020. "Key Determinants of Job Creation: A Comparative analysis between OECD Countries and Emerging Economies," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 4, pages 619-647, December.
    2. Ramesh Chandra Das & Kamal Ray, 2022. "Linkages Between Employment and Net FDI Inflow: Insights from Individual as Well as Panel Data for Emerging South Asian Labour Market," Global Business Review, International Management Institute, vol. 23(3), pages 785-803, June.
    3. Njangang, Henri & Nembot Ndeffo, Luc & Noubissi Domguia, Edmond & Fosto Koyeu, Prevost, 2018. "The long-run and short-run effects of foreign direct investment, foreign aid and remittances on economic growth in African countries," MPRA Paper 89747, University Library of Munich, Germany.
    4. Simon Wong, Chak Keung & Gladys Liu, Fung Ching, 2011. "A study of pre-trip use of travel guidebooks by leisure travelers," Tourism Management, Elsevier, vol. 32(3), pages 616-628.
    5. Tung Son Ha & Vu Tuan Chu & Mai Tuyet Thi Nguyen & Dung Hoai Thi Nguyen & Anh Ngoc Thi Nguyen, 2021. "The impact of Greenfield investment on domestic entrepreneurship," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-16, December.
    6. Tsai Chang-hsien, 2011. "International Jurisdictional Competition under Globalization: From the U.S. Regulation of Foreign Private Issuers to Taiwan's Restrictions on Outward Investment in Mainland China," Asian Journal of Law and Economics, De Gruyter, vol. 2(1), pages 1-102, April.
    7. Taotao Chen & Afonso Fleury & Maria Tereza Fleury & Xiao Chen, 2020. "Government, MNEs and Industry Development: A Perspective of Game Theory," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 19(1), pages 1-26, June.

  11. Eklund, Jana & Karlsson, Sune, 2007. "Computational Efficiency in Bayesian Model and Variable Selection," Working Papers 2007:4, Örebro University, School of Business.

    Cited by:

    1. Jesús Crespo-Cuaresma & Gernot Doppelhofer & Martin Feldkircher, 2009. "The Determinants of Economic Growth in European Regions," CESifo Working Paper Series 2519, CESifo.

  12. Eklund, Jana & Karlsson, Sune, 2007. "An Embarrassment of Riches: Forecasting Using Large Panels," Working Papers 2007:1, Örebro University, School of Business.

    Cited by:

    1. Cheung, Yin-Wong & He, Shi, 2019. "Truths and myths about RMB misalignment: A meta-analysis," BOFIT Discussion Papers 3/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
    2. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.

  13. Hultblad, Brigitta & Karlsson, Sune, 2006. "Bayesian simultaneous determination of structural breaks and lag lengths," SSE/EFI Working Paper Series in Economics and Finance 630, Stockholm School of Economics.

    Cited by:

    1. Luoto, Jani, 2011. "Aggregate infrastructure capital stock and long-run growth: Evidence from Finnish data," Journal of Development Economics, Elsevier, vol. 94(2), pages 181-191, March.
    2. Meligkotsidou, Loukia & Tzavalis, Elias & Vrontos, Ioannis, 2017. "On Bayesian analysis and unit root testing for autoregressive models in the presence of multiple structural breaks," Econometrics and Statistics, Elsevier, vol. 4(C), pages 70-90.

  14. Eklund, Jana & Karlsson, Sune, 2005. "Forecast Combination and Model Averaging Using Predictive Measures," CEPR Discussion Papers 5268, C.E.P.R. Discussion Papers.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Andersson, Michael K & Karlsson, Sune, 2007. "Bayesian Forecast Combination for VAR Models," Working Papers 2007:13, Örebro University, School of Business.
    3. Adam J. Check & Anna K Nolan & Tyler C. Schipper, 2019. "Forecasting GDP Growth using Disaggregated GDP Revisions," Economics Bulletin, AccessEcon, vol. 39(4), pages 2580-2588.
    4. Nalan Basturk & Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2012. "The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation," Tinbergen Institute Discussion Papers 12-096/III, Tinbergen Institute.
    5. Abdymomunov, Azamat & Kang, Kyu Ho & Kim, Ki Jeong, 2016. "Can credit spreads help predict a yield curve?," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 39-61.
    6. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It's all about volatility of volatility: evidence from a two-factor stochastic volatility model," Studies in Economics 1404, School of Economics, University of Kent.
    7. Chevillon, Guillaume, 2009. "Multi-step forecasting in emerging economies: An investigation of the South African GDP," International Journal of Forecasting, Elsevier, vol. 25(3), pages 602-628, July.
    8. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
    9. Evanthia Chatzitzisi & Stilianos Fountas & Theodore Panagiotidis, 2019. "Another Look at Calendar Anomalies," Discussion Paper Series 2019_02, Department of Economics, University of Macedonia, revised Feb 2019.
    10. Maik H. Wolters, 2015. "Evaluating Point and Density Forecasts of DSGE Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 74-96, January.
    11. Wolters, Maik H., 2011. "Forecasting under Model Uncertainty," VfS Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48723, Verein für Socialpolitik / German Economic Association.
    12. Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
    13. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
    14. Scharnagl, Michael & Schumacher, Christian, 2007. "Reconsidering the role of monetary indicators for euro area inflation from a Bayesian perspective using group inclusion probabilities," Discussion Paper Series 1: Economic Studies 2007,09, Deutsche Bundesbank.
    15. Gelper, Sarah & Stremersch, Stefan, 2014. "Variable selection in international diffusion models," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 356-367.
    16. David Bolder & Yuliya Romanyuk, 2008. "Combining Canadian Interest-Rate Forecasts," Staff Working Papers 08-34, Bank of Canada.
    17. Anders Warne & Günter Coenen & Kai Christoffel, 2017. "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 103-119, January.
    18. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    19. Anastasia Dimiski, 2020. "Factors that affect Students’ performance in Science: An application using Gini-BMA methodology in PISA 2015 dataset," Working Papers 2004, University of Guelph, Department of Economics and Finance.
    20. Eliana González, 2010. "Bayesian Model Averaging. An Application to Forecast Inflation in Colombia," Borradores de Economia 7015, Banco de la Republica.
    21. Ravazzolo, F. & van Dijk, H.K. & Verbeek, M.J.C.M., 2007. "Predictive gains from forecast combinations using time-varying model weights," Econometric Institute Research Papers EI 2007-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    22. Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2011. "A Class of Adaptive EM-based Importance Sampling Algorithms for Efficient and Robust Posterior and Predictive Simulation," Tinbergen Institute Discussion Papers 11-004/4, Tinbergen Institute.
    23. John M. Maheu & Thomas H. McCurdy, 2007. "How useful are historical data for forecasting the long-run equity return distribution?," Working Paper series 19_07, Rimini Centre for Economic Analysis.
    24. Cobb, Marcus P A, 2017. "Joint Forecast Combination of Macroeconomic Aggregates and Their Components," MPRA Paper 76556, University Library of Munich, Germany.
    25. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    26. James H. Stock & Mark W. Watson, 2012. "Generalized Shrinkage Methods for Forecasting Using Many Predictors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 481-493, June.
    27. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
    28. Pysarenko, Sergiy & Alexeev, Vitali & Tapon, Francis, 2019. "Predictive blends: Fundamental Indexing meets Markowitz," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 28-42.
    29. Todd E. Clark & Michael W. McCracken, 2007. "Averaging forecasts from VARs with uncertain instabilities," Finance and Economics Discussion Series 2007-42, Board of Governors of the Federal Reserve System (U.S.).
    30. George Kapetanios & Vincent Labhard & Simon Price, 2006. "Forecasting Using Predictive Likelihood Model Averaging," Working Papers 567, Queen Mary University of London, School of Economics and Finance.
    31. Lukasz Gatarek & Lennart Hoogerheide & Koen Hooning & Herman K. van Dijk, 2013. "Censored Posterior and Predictive Likelihood in Left-Tail Prediction for Accurate Value at Risk Estimation," Tinbergen Institute Discussion Papers 13-060/III, Tinbergen Institute, revised 06 Mar 2014.
    32. David Ardia & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2010. "A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihood," Tinbergen Institute Discussion Papers 10-059/4, Tinbergen Institute.
    33. Melo, Luis F. & Loaiza, Rubén A. & Villamizar-Villegas, Mauricio, 2016. "Bayesian combination for inflation forecasts: The effects of a prior based on central banks’ estimates," Economic Systems, Elsevier, vol. 40(3), pages 387-397.
    34. Nima Nonejad, 2013. "A Mixture Innovation Heterogeneous Autoregressive Model for Structural Breaks and Long Memory," CREATES Research Papers 2013-24, Department of Economics and Business Economics, Aarhus University.
    35. Jana Eklund & George Kapetanios, 2008. "A Review of Forecasting Techniques for Large Data Sets," Working Papers 625, Queen Mary University of London, School of Economics and Finance.
    36. Hilde Bjørnland & Karsten Gerdrup & Christie Smith & Anne Sofie Jore & Leif Anders Thorsrud, 2010. "Weights and pools for a Norwegian density combination," Working Paper 2010/06, Norges Bank.
    37. Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2012. "A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation," Tinbergen Institute Discussion Papers 12-026/4, Tinbergen Institute.
    38. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    39. Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2015. "The R-package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference," Tinbergen Institute Discussion Papers 15-042/III, Tinbergen Institute, revised 04 Jul 2017.
    40. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    41. Hugo Gerard & Kristoffer Nimark, 2008. "Combining Multivariate Density Forecasts Using Predictive Criteria," RBA Research Discussion Papers rdp2008-02, Reserve Bank of Australia.
    42. Martin Feldkircher & Florian Huber & Josef Schreiner & Marcel Tirpák & Peter Tóth & Julia Wörz, 2015. "Bridging the information gap: small-scale nowcasting models of GDP growth for selected CESEE countries," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 56-75.
    43. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    44. Baihua He & Yanyan Liu & Guosheng Yin & Yuanshan Wu, 2023. "Model aggregation for doubly divided data with large size and large dimension," Computational Statistics, Springer, vol. 38(1), pages 509-529, March.
    45. Chun Liu & John M Maheu, 2008. "Forecasting Realized Volatility: A Bayesian Model Averaging Approach," Working Papers tecipa-313, University of Toronto, Department of Economics.
    46. Grammig, Joachim & Kehrle, Kerstin, 2008. "A new marked point process model for the federal funds rate target: Methodology and forecast evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2370-2396, July.
    47. Kim, Dongwhan & Kang, Kyu Ho, 2021. "Conditional value-at-risk forecasts of an optimal foreign currency portfolio," International Journal of Forecasting, Elsevier, vol. 37(2), pages 838-861.
    48. Kapetanios, G. & Labhard, V. & Price, S., 2007. "Forecasting using Bayesian and information theoretic model averaging: an application to UK inflation," Working Papers 07/15, Department of Economics, City University London.
    49. Anthony Garratt & James Mitchell & Shaun P. Vahey & Elizabeth C. Wakerly, 2009. "Real-time Inflation Forecast Densities from Ensemble Phillips Curves," Birkbeck Working Papers in Economics and Finance 0910, Birkbeck, Department of Economics, Mathematics & Statistics.
    50. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
    51. Martin Feldkircher & Florian Huber & Josef Schreiner & Julia Woerz & Marcel Tirpak & Peter Toth, 2015. "Small-scale nowcasting models of GDP for selected CESEE countries," Working and Discussion Papers WP 4/2015, Research Department, National Bank of Slovakia.
    52. Stefano Grassi & Nima Nonejad & Paolo Santucci de Magistris, 2014. "Forecasting with the Standardized Self-Perturbed Kalman Filter," CREATES Research Papers 2014-12, Department of Economics and Business Economics, Aarhus University.
    53. Arnold Zellner & Tomohiro Ando & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2011. "Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo," Tinbergen Institute Discussion Papers 11-137/4, Tinbergen Institute.
    54. Wolden Bache, Ida & Sofie Jore, Anne & Mitchell, James & Vahey, Shaun P., 2011. "Combining VAR and DSGE forecast densities," Journal of Economic Dynamics and Control, Elsevier, vol. 35(10), pages 1659-1670, October.
    55. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    56. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2013. "Predictive likelihood comparisons with DSGE and DSGE-VAR models," Working Paper Series 1536, European Central Bank.
    57. Huber Florian, 2016. "Forecasting exchange rates using multivariate threshold models," The B.E. Journal of Macroeconomics, De Gruyter, vol. 16(1), pages 193-210, January.
    58. Chris McDonald & Leif Anders Thorsrud, 2011. "Evaluating density forecasts: model combination strategies versus the RBNZ," Reserve Bank of New Zealand Discussion Paper Series DP2011/03, Reserve Bank of New Zealand.
    59. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    60. De Pooter, Michiel & Ravazzolo, Francesco & van Dijk, Dick, 2006. "Predicting the term structure of interest rates incorporating parameter uncertainty, model uncertainty and macroeconomic information," MPRA Paper 2512, University Library of Munich, Germany, revised 03 Mar 2007.
    61. Ando, Tomohiro & Tsay, Ruey, 2010. "Predictive likelihood for Bayesian model selection and averaging," International Journal of Forecasting, Elsevier, vol. 26(4), pages 744-763, October.
    62. Zeugner, Stefan & Feldkircher, Martin, 2015. "Bayesian Model Averaging Employing Fixed and Flexible Priors: The BMS Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i04).
    63. Erengul Dodd & Jonathan J. Forster & Jakub Bijak & Peter W. F. Smith, 2018. "Smoothing mortality data: the English Life Tables, 2010–2012," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 717-735, June.
    64. McAdam, Peter & Warne, Anders, 2020. "Density forecast combinations: the real-time dimension," Working Paper Series 2378, European Central Bank.

  15. Mickael Salabasis & Sune Karlsson, 2004. "Seasonality, Cycles and Unit Roots," Econometric Society 2004 Australasian Meetings 268, Econometric Society.

    Cited by:

    1. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2007. "A simple, robust and powerful test of the trend hypothesis," Journal of Econometrics, Elsevier, vol. 141(2), pages 1302-1330, December.

  16. Ericsson, Johan & Karlsson, Sune, 2003. "Choosing Factors in a Multifactor Asset Pricing Model: A Bayesian Approach," SSE/EFI Working Paper Series in Economics and Finance 524, Stockholm School of Economics, revised 12 Feb 2004.

    Cited by:

    1. Patrick Mumo Muinde & James Mwangi Karanja, 2017. "Kenya Commercial Banks are Star Performers: Myth or Truth? Exploratory Empirical Evidence from Nairobi Securities Exchange," International Journal of Economics and Financial Issues, Econjournals, vol. 7(1), pages 340-350.
    2. Muinde Patrick Mumo, 2017. "The Determinants of Stock Returns in the Emerging Market of Kenya: An Empirical Evidence," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(9), pages 8-21, September.

  17. Jacobson, Tor & Karlsson, Sune, 2002. "Finding Good Predictors for Inflation: A Bayesian Model Averaging Approach," Working Paper Series 138, Sveriges Riksbank (Central Bank of Sweden).

    Cited by:

    1. Andersson, Michael K & Karlsson, Sune, 2007. "Bayesian Forecast Combination for VAR Models," Working Papers 2007:13, Örebro University, School of Business.
    2. Magnus, J.R. & Wang, W. & Zhang, Xinyu, 2012. "WALS Prediction," Discussion Paper 2012-043, Tilburg University, Center for Economic Research.
    3. Scharnagl, Michael & Schumacher, Christian, 2007. "Reconsidering the role of monetary indicators for euro area inflation from a Bayesian perspective using group inclusion probabilities," Discussion Paper Series 1: Economic Studies 2007,09, Deutsche Bundesbank.
    4. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2011. "Bayesian VARs: specification choices and forecast accuracy," Working Papers (Old Series) 1112, Federal Reserve Bank of Cleveland.
    5. Oxana Babetskaia-Kukharchuk, 2007. "Transmission of Exchange Rate Shocks into Domestic Inflation: The Case of the Czech Republic," Working Papers 2007/12, Czech National Bank.
    6. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    7. Eliana González, 2010. "Bayesian Model Averaging. An Application to Forecast Inflation in Colombia," Borradores de Economia 7015, Banco de la Republica.
    8. Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
    9. Timmermann Allan & Capistrán Carlos, 2006. "Forecast Combination with Entry and Exit of Experts," Working Papers 2006-08, Banco de México.
    10. Thomas Brenner & Claudia Werker, 2007. "A Taxonomy of Inference in Simulation Models," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 227-244, October.
    11. James H. Stock & Mark W. Watson, 2012. "Generalized Shrinkage Methods for Forecasting Using Many Predictors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 481-493, June.
    12. Jennifer Castle & Xiaochuan Qin & W. Robert Reed, 2011. "Using Model Selection Algorthims to Obtain Reliable Coefficient Estimates," Working Papers in Economics 11/03, University of Canterbury, Department of Economics and Finance.
    13. Peter J. Danaher & Michael S. Smith, 2011. "Rejoinder--Estimation Issues for Copulas Applied to Marketing Data," Marketing Science, INFORMS, vol. 30(1), pages 25-28, 01-02.
    14. Todd E. Clark & Michael W. McCracken, 2009. "Combining Forecasts from Nested Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 303-329, June.
    15. Jan R. Magnus & Wendun Wang & Xinyu Zhang, 2016. "Weighted-Average Least Squares Prediction," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1040-1074, June.
    16. Jana Eklund & Sune Karlsson, 2007. "An Embarrassment of Riches: Forecasting Using Large Panels," Economics wp34, Department of Economics, Central bank of Iceland.
    17. Mr. Alin T Mirestean & Mr. Charalambos G Tsangarides & Huigang Chen, 2009. "Limited Information Bayesian Model Averaging for Dynamic Panels with Short Time Periods," IMF Working Papers 2009/074, International Monetary Fund.
    18. Tumala, Mohammed M & Olubusoye, Olusanya E & Yaaba, Baba N & Yaya, OlaOluwa S & Akanbi, Olawale B, 2017. "Investigating Predictors of Inflation in Nigeria: BMA and WALS Techniques," MPRA Paper 88773, University Library of Munich, Germany, revised Feb 2018.
    19. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    20. Chun Liu & John M Maheu, 2008. "Forecasting Realized Volatility: A Bayesian Model Averaging Approach," Working Papers tecipa-313, University of Toronto, Department of Economics.
    21. Cogley, Timothy & de Paoli, Bianca & Matthes, Christian & Nikolov, Kalin & Yates, Tony, 2011. "A Bayesian approach to optimal monetary policy with parameter and model uncertainty," Bank of England working papers 414, Bank of England.
    22. Wen-Hsien Liu & Shu-Shih Weng, 2018. "On predicting the semiconductor industry cycle: a Bayesian model averaging approach," Empirical Economics, Springer, vol. 54(2), pages 673-703, March.
    23. Ebersberger, Bernd & Galia, Fabrice & Laursen, Keld & Salter, Ammon, 2021. "Inbound Open Innovation and Innovation Performance: A Robustness Study," Research Policy, Elsevier, vol. 50(7).
    24. Kapetanios, George & Labhard, Vincent & Price, Simon, 2008. "Forecast combination and the Bank of England's suite of statistical forecasting models," Economic Modelling, Elsevier, vol. 25(4), pages 772-792, July.
    25. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
    26. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
    27. Chin, Kuo-Hsuan & Li, Xue, 2019. "Bayesian forecast combination in VAR-DSGE models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 278-298.
    28. Jana Eklund & Sune Karlsson, 2007. "Computational Efficiency in Bayesian Model and Variable Selection," Economics wp35, Department of Economics, Central bank of Iceland.
    29. Miguel A. Negrín & Francisco J. Vázquez-Polo & María Martel & Elías Moreno & Francisco J. Girón, 2010. "Bayesian Variable Selection in Cost-Effectiveness Analysis," IJERPH, MDPI, vol. 7(4), pages 1-20, April.
    30. Magnus, J.R. & Wang, W. & Zhang, Xinyu, 2012. "WALS Prediction," Other publications TiSEM 7715e942-b446-4985-8216-f, Tilburg University, School of Economics and Management.
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  18. Skoglund, Jimmy & Karlsson, Sune, 2001. "Specification and estimation of random effects models with serial correlation of general form," SSE/EFI Working Paper Series in Economics and Finance 0433, Stockholm School of Economics.

    Cited by:

    1. Paolo, Foschi, 2005. "Estimating regressions and seemingly unrelated regressions with error component disturbances," MPRA Paper 1424, University Library of Munich, Germany, revised 07 Sep 2006.

  19. Sune Karlsson & Jimmy Skoglund, 2000. "Maximum-Likelihood Based Inference in the Two-Way Random Effects Model with Serially Correlated Time Effects," Econometric Society World Congress 2000 Contributed Papers 1178, Econometric Society.

    Cited by:

    1. Giorgio Calzolari & Laura Magazzini, 2009. "Autocorrelation and masked heterogeneity in panel data models estimated by maximum likelihood," Working Papers 53/2009, University of Verona, Department of Economics.
    2. Robert F. Phillips, 2012. "On computing generalized least squares and maximum-likelihood estimates of error-components models with incomplete panels and correlated disturbances," Economics Bulletin, AccessEcon, vol. 32(4), pages 3017-3024.
    3. Pardo Martínez, Clara Inés & Silveira, Semida, 2012. "Analysis of energy use and CO2 emission in service industries: Evidence from Sweden," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 5285-5294.
    4. Paolo, Foschi, 2005. "Estimating regressions and seemingly unrelated regressions with error component disturbances," MPRA Paper 1424, University Library of Munich, Germany, revised 07 Sep 2006.
    5. Olivier Armantier & Oliver Richard, 2008. "Domestic airline alliances and consumer welfare," RAND Journal of Economics, RAND Corporation, vol. 39(3), pages 875-904, September.
    6. Baltagi, Badi H., 2006. "Forecasting with panel data," Discussion Paper Series 1: Economic Studies 2006,25, Deutsche Bundesbank.
    7. Jimmy Skoglund & Sune Karlsson, 2002. "Asymptotics for random effects models with serial correlation," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 A6-1, International Conferences on Panel Data.
    8. Marcel die Dama & Boniface ngah Epo & Galex syrie Soh, 2013. "Developing a two way error component estimation model with disturbances following a special autoregressive (4) for quarterly data," Economics Bulletin, AccessEcon, vol. 33(1), pages 625-634.
    9. Pardo Martínez, Clara Inés, 2013. "An analysis of eco-efficiency in energy use and CO2 emissions in the Swedish service industries," Socio-Economic Planning Sciences, Elsevier, vol. 47(2), pages 120-130.
    10. Rendao Ye & Ya Lin, 2023. "Relationship Between Interest Rate and Risk of P2P Lending in China Based on the Skew-Normal Panel Data Model," SAGE Open, , vol. 13(4), pages 21582440231, October.

  20. Andersson, Michael K. & Karlsson, Sune, 1999. "Bootstrapping Error Component Models," SSE/EFI Working Paper Series in Economics and Finance 304, Stockholm School of Economics, revised 30 Jun 2000.

    Cited by:

    1. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2023. "Robust dynamic space-time panel data models using ?-contamination: An application to crop yields and climate change," CIRANO Working Papers 2023s-01, CIRANO.
    2. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2017. "Robust Linear Static Panel Data Models Using ε-Contamination," Center for Policy Research Working Papers 208, Center for Policy Research, Maxwell School, Syracuse University.
    3. Stanislav Anatolyev, 2007. "The basics of bootstrapping (in Russian)," Quantile, Quantile, issue 3, pages 1-12, September.

  21. Karlsson, Sune & Löthgren, Mickael, 1999. "On the power and interpretation of panel unit root tests," SSE/EFI Working Paper Series in Economics and Finance 299, Stockholm School of Economics.

    Cited by:

    1. Paresh Kumar Narayan & Russell Smyth, 2005. "Are Shocks To Energy Consumption Permanent Or Temporary? Evidence From 182 Countries," Monash Economics Working Papers 06/05, Monash University, Department of Economics.
    2. Lee, Chien-Chiang & Lee, Jun-De, 2009. "Income and CO2 emissions: Evidence from panel unit root and cointegration tests," Energy Policy, Elsevier, vol. 37(2), pages 413-423, February.
    3. Carlos USABIAGA & Diego ROMERO-ÁVILA, 2008. "The Hypothesis of a Unit Root in OECD Inflation Revisited," EcoMod2008 23800146, EcoMod.
    4. R. Pala & E. Marrocu & R. Paci, 2000. "Estimation of total factor productivity for regions and sectors in Italy. A panel cointegration approach," Working Paper CRENoS 200016, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Xuguang Sheng & Jingyun Yang, 2013. "Truncated Product Methods for Panel Unit Root Tests," Working Papers 2013-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    6. Marcelo Mello & Roberto Guimaraes-Filho, 2007. "A note on fractional stochastic convergence," Economics Bulletin, AccessEcon, vol. 3(16), pages 1-14.
    7. Gu, Jianqiang & Yue, Xiao-Guang & Nosheen, Safia & Naveed -ul-Haq, & Shi, Lei, 2022. "Does more stringencies in government policies during pandemic impact stock returns? Fresh evidence from GREF countries, a new emerging green bloc," Resources Policy, Elsevier, vol. 76(C).
    8. Hooi Hooi Lean & Russell Smyth, 2012. "Will policies to promote renewable electricity generation be effective? Evidence from panel stationarity and unit root tests for 115 countries," Monash Economics Working Papers 15-12, Monash University, Department of Economics.
    9. Narayan, Paresh Kumar & Narayan, Seema & Smyth, Russell, 2008. "Are oil shocks permanent or temporary? Panel data evidence from crude oil and NGL production in 60 countries," Energy Economics, Elsevier, vol. 30(3), pages 919-936, May.
    10. Florian Verheyen, 2015. "The role of non-price determinants for export demand," International Economics and Economic Policy, Springer, vol. 12(1), pages 107-125, March.
    11. Lanzafame, Matteo, 2012. "Current account sustainability in advanced economies," MPRA Paper 42384, University Library of Munich, Germany.
    12. Raffaello Bronzini & Paolo Piselli, 2006. "Determinants of long-run regional productivity: the role of R&D, human capital and public infrastructure," Temi di discussione (Economic working papers) 597, Bank of Italy, Economic Research and International Relations Area.
    13. Mika Kortelainen & Simo Leppänen, 2013. "Public and private capital productivity in Russia: a non-parametric investigation," Empirical Economics, Springer, vol. 45(1), pages 193-216, August.
    14. Axel Grossmann & Marc Simpson & Teofilo Ozuna, 2014. "Investigating the PPP hypothesis using constructed U.S. dollar equilibrium exchange rate misalignments over the post-bretton woods period," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(2), pages 235-268, April.
    15. Jaunky, Vishal Chandr, 2013. "A cointegration and causality analysis of copper consumption and economic growth in rich countries," Resources Policy, Elsevier, vol. 38(4), pages 628-639.
    16. Julián Ramajo Hernández(1) & Montserrat Ferré Carracedo(2), "undated". "Testing For Long-Run Purchasing Power Parity In The Post Bretton Woods Era: Evidence From Old And New Tests," Working Papers 24-05 Classification-JEL , Instituto de Estudios Fiscales.
    17. Qaiser Munir & Sook Ching Kok & Kasim Mansur, 2019. "External Shocks, Structural Breaks And Unemployment Hysteresis In Selected Asian Countries," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(03), pages 575-600, June.
    18. Chletsos Michael & Roupakias Stelios, 2020. "The effect of military spending on income inequality: evidence from NATO countries," Empirical Economics, Springer, vol. 58(3), pages 1305-1337, March.
    19. Matteo Lanzafame, 2014. "The balance of payments-constrained growth rate and the natural rate of growth: new empirical evidence," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 38(4), pages 817-838.
    20. Chan, Tze-Haw & Baharumshah, Ahmad Zubaidi & Lau, Evan, 2005. "Real Financial Integration among the East Asian Economies: A SURADF Panel Approach," MPRA Paper 2021, University Library of Munich, Germany, revised Feb 2007.
    21. Smith, Constance, 2011. "External Balance Adjustment: An Intra-National and International Comparison," Working Papers 2011-13, University of Alberta, Department of Economics.
    22. Lau, Evan & Baharumshah, Ahmad Zubaidi & Haw, Chan Tze, 2006. "Current account: mean-reverting or random walk behavior?," Japan and the World Economy, Elsevier, vol. 18(1), pages 90-107, January.
    23. Mishra, Vinod & Smyth, Russell, 2010. "Female labor force participation and total fertility rates in the OECD: New evidence from panel cointegration and Granger causality testing," Journal of Economics and Business, Elsevier, vol. 62(1), pages 48-64, January.
    24. Ashworth, Paul & Byrne, Joseph P., 2003. "Some international evidence on price determination: a non-stationary panel approach," Economic Modelling, Elsevier, vol. 20(4), pages 809-838, July.
    25. Jaunky, Vishal Chandr, 2013. "Are Shocks To Aluminium Consumption Transitory Or Permanent?," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 9(1-2), January.
    26. Tuomas Malinen, 2012. "Estimating the long-run relationship between income inequality and economic development," Empirical Economics, Springer, vol. 42(1), pages 209-233, February.
    27. Gerdie Everaert & Hauke Vierke, 2016. "Demographics and Business Cycle Volatility: A Spurious Relationship?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1467-1477, November.
    28. Shahbaz, Muhammad & Nasreen, Samia & Ling, Chong Hui & Sbia, Rashid, 2014. "Causality between trade openness and energy consumption: What causes what in high, middle and low income countries," Energy Policy, Elsevier, vol. 70(C), pages 126-143.
    29. John T. Barkoulas & Christopher F. Baum & Atreya Chakraborty, 2000. "Forward Premiums and Market Efficiency: Panel Unit-root Evidence from the Term Structure of Forward Premiums," Boston College Working Papers in Economics 461, Boston College Department of Economics, revised 13 Jun 2001.
    30. Maican, Florin G. & Sweeney, Richard J., 2006. "Real Exchange Rate Adjustment In European Transition Countries," Working Papers in Economics 202, University of Gothenburg, Department of Economics.
    31. Elisa Gatto & Guido Signorino, 2011. "Long-run relationship between crop-biodiversity and cereal production under the CAP reform: evidence from Italian regions," ERSA conference papers ersa11p964, European Regional Science Association.
    32. César A. Calderón, 2002. "Real Exchange Rates in the Long and Short Run: A Panel Co-Integration Approach," Working Papers Central Bank of Chile 153, Central Bank of Chile.
    33. Landon, Stuart & Smith, Constance E., 2009. "Investment and the exchange rate: Short run and long run aggregate and sector-level estimates," Journal of International Money and Finance, Elsevier, vol. 28(5), pages 813-835, September.
    34. N. Vasudeva Murthy, 2009. "The Feldstein–Horioka puzzle in Latin American and Caribbean countries: a panel cointegration analysis," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 33(2), pages 176-188, April.
    35. Balvers, Ronald J. & Bergstrand, Jeffrey H., 2002. "Government expenditure and equilibrium real exchange rates," Journal of International Money and Finance, Elsevier, vol. 21(5), pages 667-692, October.
    36. Aurélie Lalanne & Martin Zumpe, 2020. "Time-Series Based Empirical Assessment of Random Urban Growth: New Evidence from France," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(4), pages 911-926, December.
    37. Borozan, Djula, 2017. "Testing for convergence in electricity consumption across Croatian regions at the consumer's sectoral level," Energy Policy, Elsevier, vol. 102(C), pages 145-153.
    38. Silvia Coderoni & Roberto Esposti, 2014. "Is There a Long-Term Relationship Between Agricultural GHG Emissions and Productivity Growth? A Dynamic Panel Data Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 58(2), pages 273-302, June.
    39. Clovis Rugemintwari, 2010. "Investigation on the Comparative Persistence and Convergence of Risk and Non-Risk Adjusted Bank Capital Ratios," Working Papers hal-00916749, HAL.
    40. Jönsson, Kristian, 2003. "Cross-sectional dependency and size distortion in a small-sample homogeneous panel-data unit root test," Working Papers 2003:10, Lund University, Department of Economics.
    41. Caporale, Guglielmo Maria & Cerrato, Mario, 2004. "Panel Data Tests of PPP. A Critical Overview," Economics Series 159, Institute for Advanced Studies.
    42. Bonte, Werner, 2004. "Spillovers from publicly financed business R&D: some empirical evidence from Germany," Research Policy, Elsevier, vol. 33(10), pages 1635-1655, December.
    43. Jack Strauss & Mark E. Wohar, 2004. "The Linkage between Prices, Wages, and Labor Productivity: A Panel Study of Manufacturing Industries," Southern Economic Journal, John Wiley & Sons, vol. 70(4), pages 920-941, April.
    44. Bronzini, Raffaello & Piselli, Paolo, 2009. "Determinants of long-run regional productivity with geographical spillovers: The role of R&D, human capital and public infrastructure," Regional Science and Urban Economics, Elsevier, vol. 39(2), pages 187-199, March.
    45. Lee, Hsiu-Yun & Wu, Jyh-Lin, 2001. "Mean Reversion of Inflation Rates: Evidence from 13 OECD Countries," Journal of Macroeconomics, Elsevier, vol. 23(3), pages 477-487, July.
    46. Simon C. Parker & Martin T. Robson, 2004. "Explaining International Variations in Self‐Employment: Evidence from a Panel of OECD Countries," Southern Economic Journal, John Wiley & Sons, vol. 71(2), pages 287-301, October.
    47. Sonali Das & Rangan Gupta & Patrick Agu Kaya, 2009. "Convergence of Metropolitan House Prices in South Africa: A Re-Examination Using Efficient Unit Root Tests," Working Papers 200922, University of Pretoria, Department of Economics.
    48. He, Huizhen & Ranjbar, Omid & Chang, Tsangyao, 2013. "Purchasing power parity in transition countries: Old wine with new bottle," Japan and the World Economy, Elsevier, vol. 28(C), pages 24-32.
    49. Christoph Hanck, 2009. "For which countries did PPP hold? A multiple testing approach," Empirical Economics, Springer, vol. 37(1), pages 93-103, September.
    50. Annette Zeilstra & Adam Elbourne, 2014. "Follow the leader? Public and private wages in the Netherlands," CPB Discussion Paper 274, CPB Netherlands Bureau for Economic Policy Analysis.
    51. Nautz, Dieter & Ruth, Karsten, 2005. "Monetary disequilibria and the Euro/Dollar exchange rate," Discussion Paper Series 1: Economic Studies 2005,18, Deutsche Bundesbank.
    52. Abdulnasser Hatemi-J & Manuchehr Irandoust, 2004. "Is Pricing to Market Behavior a Long-Run Phenomenon? A Non-Stationary Panel Analysis," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 31(1), pages 55-67, March.
    53. Muhammad Shahbaz & Samia Nasreen & Ilhan Ozturk, 2016. "FDI, Growth and CO2 Emissions Relationship: Evidence from High, Middle and Low Income Countries," Bulletin of Energy Economics (BEE), The Economics and Social Development Organization (TESDO), vol. 4(1), pages 54-69, March.
    54. Jaunky, Vishal Chandr, 2012. "Is there a material Kuznets curve for aluminium? evidence from rich countries," Resources Policy, Elsevier, vol. 37(3), pages 296-307.
    55. Bakas, Dimitrios & Papapetrou, Evangelia, 2014. "Unemployment in Greece: Evidence from Greek regions using panel unit root tests," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(4), pages 551-562.
    56. I‐Chun Tsai & Cheng‐Feng Lee, 2012. "The convergent behavior in REIT markets," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 30(1), pages 42-57, February.
    57. Jaroslava Hlouskova & Martin Wagner, 2005. "The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study," Diskussionsschriften dp0503, Universitaet Bern, Departement Volkswirtschaft.
    58. Dina Azhgaliyeva, 2013. "What Makes Oil Revenue Funds Effective," International Conference on Energy, Regional Integration and Socio-economic Development 6023, EcoMod.
    59. Hanck, Christoph, 2006. "For Which Countries did PPP hold? A Multiple Testing Approach," Technical Reports 2006,47, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    60. Del Monte, Alfredo & Papagni, Erasmo, 2003. "R&D and the growth of firms: empirical analysis of a panel of Italian firms," Research Policy, Elsevier, vol. 32(6), pages 1003-1014, June.
    61. Abdullahi Ahmed & Enjiang Cheng & George Messinis, 2011. "The role of exports, FDI and imports in development: evidence from Sub-Saharan African countries," Applied Economics, Taylor & Francis Journals, vol. 43(26), pages 3719-3731.
    62. Vishal Chandr Jaunky & Robert Lundmark, 2015. "Are Shocks to Wood Fuel Production Permanent? Evidence from the EU," Energies, MDPI, vol. 8(11), pages 1-11, November.
    63. Richard G. Anderson & Hailong Qian & Robert H. Rasche, 2006. "Analysis of panel vector error correction models using maximum likelihood, the bootstrap, and canonical-correlation estimators," Working Papers 2006-050, Federal Reserve Bank of St. Louis.
    64. Myint Moe Chit & Marian Rizov & Dirk Willenbockel, 2010. "Exchange Rate Volatility and Exports: New Empirical Evidence from the Emerging East Asian Economies," The World Economy, Wiley Blackwell, vol. 33(2), pages 239-263, February.
    65. Francis W. Ahking, 2002. "Efficient Unit Root Tests of real Exchange Rates in the Post-Bretton Woods Era," Working papers 2002-17, University of Connecticut, Department of Economics.
    66. Joakim Westerlund, 2009. "A note on the use of the LLC panel unit root test," Empirical Economics, Springer, vol. 37(3), pages 517-531, December.
    67. Eva Samakovlis, 2003. "The Relationship between Waste Paper and Other Inputs in the Swedish Paper Industry," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 25(2), pages 191-212, June.
    68. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
    69. Vishal Jaunky, 2013. "Democracy and economic growth in Sub-Saharan Africa: a panel data approach," Empirical Economics, Springer, vol. 45(2), pages 987-1008, October.
    70. César Calderón & Roberto Duncan, 2003. "Purchasing Power Parity in an Emerging Market Economy: A Long-Span Study for Chile," Working Papers Central Bank of Chile 215, Central Bank of Chile.
    71. Evan Lau & Ahmad Zubaidi Baharumshah & Shazali Abu Mansor & Chin-Hong Puah, 2009. "Testing Stationarity of Budgetary Position in Developing Countries," International Econometric Review (IER), Econometric Research Association, vol. 1(2), pages 77-87, April.
    72. Jaunky, Vishal Chandr, 2011. "The CO2 emissions-income nexus: Evidence from rich countries," Energy Policy, Elsevier, vol. 39(3), pages 1228-1240, March.
    73. Risso, Adrián, 2022. "El impacto de los programas de inversión pública en turismo sobre los ingresos por turismo en América Latina y el Caribe," IDB Publications (Working Papers) 12041, Inter-American Development Bank.
    74. Mr. Noriaki Kinoshita & Mr. Cameron McLoughlin, 2012. "Monetization in Low- and Middle-Income Countries," IMF Working Papers 2012/160, International Monetary Fund.
    75. Vishal Jaunky, 2013. "The Wealth-Health Nexus: New Global Evidence," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 41(2), pages 115-122, June.
    76. Joseph Byrne & Giorgio Fazio & Davide Piacentino, 2009. "Total Factor Productivity Convergence among Italian Regions: Some Evidence from Panel Unit Root Tests," Regional Studies, Taylor & Francis Journals, vol. 43(1), pages 63-76.
    77. Evangelia Papapetrou & Dimitrios Bakas, 2012. "Unemployment in Greece: evidence from Greek regions," Working Papers 146, Bank of Greece.
    78. Westerlund, J., 2006. "Some cautions on the use of the LLC panel unit root test," Research Memorandum 055, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    79. R. Paci & S. Saddi, 2002. "Capitale pubblico e produttività nelle regioni italiane," Working Paper CRENoS 200201, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    80. Jaunky, V.C., 2007. "Income Elasticities Of Electric Power Consumption: Evidence From African Countries, 1971-2002," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 7(2), pages 25-50.
    81. Skrobotov, Anton (Скроботов, Антон) & Turuntseva, Marina (Турунцева, Марина), 2017. "Testing the Hypothesis of a Unit Root for Independent Panels [Тестирование Гипотезы О Наличии Единичного Корня Для Независимых Панелей]," Working Papers 021707, Russian Presidential Academy of National Economy and Public Administration.
    82. Denise Fry & Andrea Saayman & Melville Saayman, 2010. "The Relationship Between Tourism And Trade In South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 78(3), pages 287-306, September.
    83. Malebogo Bakwena & Philip Bodman & Sandy Suardi, "undated". "Making Abundant Natural Resources Work for Developing Economies: The Role of Financial Institutions," MRG Discussion Paper Series 2108, School of Economics, University of Queensland, Australia.
    84. Luciano Gutierrez, 2002. "On the power of panel cointegration tests: A Monte Carlo comparison. Economics Letters, 80(1):105-111," Econometrics 0211003, University Library of Munich, Germany, revised 20 May 2003.
    85. Siklos, Pierre L., 2010. "Meeting Maastricht: Nominal convergence of the new member states toward EMU," Economic Modelling, Elsevier, vol. 27(2), pages 507-515, March.
    86. Jerry Coakley & Ana‐Maria Fuertes & Fabio Spagnolo, 2004. "Is the Feldstein–Horioka Puzzle History?," Manchester School, University of Manchester, vol. 72(5), pages 569-590, September.
    87. Pierre L. Siklos, 2008. "Determinants of Emerging Market Spreads: Domestic, Global Factors, and Volatility," Working Papers 182008, Hong Kong Institute for Monetary Research.
    88. Raffaello Bronzini & Paolo Piselli, 2005. "What determines productivity level in the long run? Evidence from Italians regions," ERSA conference papers ersa05p267, European Regional Science Association.
    89. Francis Ahking, 2010. "Non-parametric tests of real exchange rates in the post-Bretton Woods era," Empirical Economics, Springer, vol. 39(2), pages 439-456, October.
    90. Krystyna Strzała, 2012. "Panelowe testy kointegracji – teoria i zastosowania," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 27, pages 41-54.
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    92. Civan, Abdülkadir & Koksal, Bulent, 2007. "The Effect of Newer Drugs on Health Spending: Do They Really Increase the Costs?," MPRA Paper 6846, University Library of Munich, Germany.
    93. Lee, Cheng-Feng, 2010. "Testing for unemployment hysteresis in nonlinear heterogeneous panels: International evidence," Economic Modelling, Elsevier, vol. 27(5), pages 1097-1102, September.
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    100. Roberto ESPOSTI, 2008. "Why Should Regional Agricultural Productivity Growth Converge? Evidence from Italian Regions," Working Papers 319, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    101. Gutierrez, Luciano, 2003. "On the power of panel cointegration tests: a Monte Carlo comparison," Economics Letters, Elsevier, vol. 80(1), pages 105-111, July.
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    105. Shahbaz, muhammad & Solarin, Sakiru Adebola & Sbia, Rashid & Bibi, Sadia, 2015. "Does Energy Intensity Contribute to CO2 Emissions? A Trivariate Analysis in Selected African Countries," MPRA Paper 64335, University Library of Munich, Germany, revised 19 Mar 2015.
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    7. Ashwin Madhou & Tayushma Sewak & Imad Moosa & Vikash Ramiah, 2017. "GDP nowcasting: application and constraints in a small open developing economy," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3880-3890, August.
    8. Stelios D. Bekiros & Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2016. "Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a predictability analysis versus TVP-VARs," Open Access publications 10197/7323, School of Economics, University College Dublin.
    9. Andersson, Michael K & Karlsson, Sune, 2007. "Bayesian Forecast Combination for VAR Models," Working Papers 2007:13, Örebro University, School of Business.
    10. Pinter, Gabor & Theodoridis, Konstantinos & Yates, Tony, 2013. "Risk news shocks and the business cycle," Bank of England working papers 483, Bank of England.
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    Cited by:

    1. Gilles Dufrénot & Meryem Rhouzlane & Etienne Vaccaro-Grange, 2019. "Potential Growth and Natural Yield Curve in Japan," Working Papers halshs-02091035, HAL.

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    8. Chun, Sun Eae & Nagano, Mamoru & Lee, Min Hwan, 2010. "Ownership Structure and Risk-taking Behavior: Evidence from Banks in Korea and Japan," MPRA Paper 25334, University Library of Munich, Germany.
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    23. Keeling, Kathleen A. & McGoldrick, Peter J. & Sadhu, Henna, 2013. "Staff Word-of-Mouth (SWOM) and retail employee recruitment," Journal of Retailing, Elsevier, vol. 89(1), pages 88-104.
    24. Bo Chen & Yao Li & Yuming Yin, 2016. "FDI, Industry Heterogeneity and Employment Elasticity in China," Review of Development Economics, Wiley Blackwell, vol. 20(1), pages 189-200, February.
    25. Fabienne Fortanier & Selwyn Moons, 2011. "Foreign Investors in The Netherlands: Heterogeneous Employment and Productivity Effects," De Economist, Springer, vol. 159(4), pages 511-531, December.
    26. Mihai Mutascu & Scott Hegerty, 2023. "Predicting the contribution of artificial intelligence to unemployment rates: an artificial neural network approach," Post-Print hal-04273887, HAL.
    27. Paul Wabiga & Neil Rankin, 2023. "Foreign acquisition and firm performance in sub‐Saharan Africa: Empirical evidence from Ghana," South African Journal of Economics, Economic Society of South Africa, vol. 91(2), pages 242-269, June.

  7. Hultblad Brigitta & Karlsson Sune, 2008. "Bayesian Simultaneous Determination of Structural Breaks and Lag Lengths," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-29, September.
    See citations under working paper version above.
  8. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
    See citations under working paper version above.
  9. Sune Karlsson & Tor Jacobson, 2004. "Finding good predictors for inflation: a Bayesian model averaging approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(7), pages 479-496.
    See citations under working paper version above.
  10. Sune Karlsson & Jimmy Skoglund, 2004. "Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects," Empirical Economics, Springer, vol. 29(1), pages 79-88, January.
    See citations under working paper version above.
  11. Michael K. Andersson & Sune Karlsson, 2001. "Bootstrapping Error Component Models," Computational Statistics, Springer, vol. 16(2), pages 221-231, July.
    See citations under working paper version above.
  12. Karlsson, Sune & Lothgren, Mickael, 2000. "On the power and interpretation of panel unit root tests," Economics Letters, Elsevier, vol. 66(3), pages 249-255, March.
    See citations under working paper version above.
  13. Karlsson, Sune & Lothgren, Mickael, 2000. "Computationally efficient double bootstrap variance estimation," Computational Statistics & Data Analysis, Elsevier, vol. 33(3), pages 237-247, May.
    See citations under working paper version above.
  14. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    See citations under working paper version above.
  15. Edlund, Per-Olov & Karlsson, Sune, 1993. "Forecasting the Swedish unemployment rate VAR vs. transfer function modelling," International Journal of Forecasting, Elsevier, vol. 9(1), pages 61-76, April.

    Cited by:

    1. Schanne, N. & Wapler, R. & Weyh, A., 2010. "Regional unemployment forecasts with spatial interdependencies," International Journal of Forecasting, Elsevier, vol. 26(4), pages 908-926, October.
    2. Masayoshi Hayashi, 2012. "Forecasting Welfare Caseloads: The Case of the Japanese Public Assistance Program," CIRJE F-Series CIRJE-F-846, CIRJE, Faculty of Economics, University of Tokyo.
    3. Tanujit Chakraborty & Ashis Kumar Chakraborty & Munmun Biswas & Sayak Banerjee & Shramana Bhattacharya, 2021. "Unemployment Rate Forecasting: A Hybrid Approach," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 183-201, January.
    4. McCracken, Michael W., 2004. "Parameter estimation and tests of equal forecast accuracy between non-nested models," International Journal of Forecasting, Elsevier, vol. 20(3), pages 503-514.
    5. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    6. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    7. Wai-Sum Chan, 1999. "Exact joint forecast regions for vector autoregressive models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(1), pages 35-44.
    8. Katharina Hampel & Marcus Kunz & Norbert Schanne & Ruediger Wapler & Antje Weyh, 2006. "Regional Unemployment Forecasting Using Structural Component Models With Spatial Autocorrelation," ERSA conference papers ersa06p196, European Regional Science Association.
    9. Stanislav E. Shmelev & Nathan Lefievre & Nadim Saadi & Irina A. Shmeleva, 2023. "Interdisciplinary Linkages among Sustainability Dimensions in the Context of European Cities and Regions Research," Sustainability, MDPI, vol. 15(20), pages 1-28, October.
    10. Adriana AnaMaria Davidescu & Simona-Andreea Apostu & Liviu Adrian Stoica, 2021. "Socioeconomic Effects of COVID-19 Pandemic: Exploring Uncertainty in the Forecast of the Romanian Unemployment Rate for the Period 2020–2023," Sustainability, MDPI, vol. 13(13), pages 1-22, June.
    11. Muneeb Ahmad & Yousaf Ali Khan & Chonghui Jiang & Syed Jawad Haider Kazmi & Syed Zaheer Abbas, 2023. "The impact of COVID‐19 on unemployment rate: An intelligent based unemployment rate prediction in selected countries of Europe," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 528-543, January.

Software components

    Sorry, no citations of software components recorded.

Chapters

  1. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897, Elsevier.
    See citations under working paper version above.
  2. Michael K. Andersson & Sune Karlsson, 2008. "Bayesian forecast combination for VAR models," Advances in Econometrics, in: Bayesian Econometrics, pages 501-524, Emerald Group Publishing Limited.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
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