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Markku Lanne

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.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Markku Lanne, 2000. "Near unit roots, cointegration, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 513-529.

    Mentioned in:

    1. Near unit roots, cointegration, and the term structure of interest rates (Journal of Applied Econometrics 2000) in ReplicationWiki ()
  2. Markku Lanne, 2006. "Nonlinear dynamics of interest rate and inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1157-1168.

    Mentioned in:

    1. Nonlinear dynamics of interest rate and inflation (Journal of Applied Econometrics 2006) in ReplicationWiki ()

Working papers

  1. Markku Lanne & Jani Luoto, 2016. "Data-Driven Inference on Sign Restrictions in Bayesian Structural Vector Autoregression," CREATES Research Papers 2016-04, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Tölö, Eero & Miettinen, Paavo, 2018. "How do shocks to bank capital affect lending and growth?," Bank of Finland Research Discussion Papers 25/2018, Bank of Finland.
    2. Yanlin Shi, 2023. "A new unique impulse response function in linear vector autoregressive models," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 460-468, June.
    3. Thomas Chuffart & Cyril Dell'Eva, 2020. "The role of carry trades on the effectiveness of Japan's quantitative easing," Post-Print hal-03157207, HAL.
    4. Ivan Mendieta-Munoz & Mengheng Li, 2019. "The Multivariate Simultaneous Unobserved Compenents Model and Identification via Heteroskedasticity," Working Paper Series, Department of Economics, University of Utah 2019_06, University of Utah, Department of Economics.
    5. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    6. Puonti, Päivi, 2019. "Data-driven structural BVAR analysis of unconventional monetary policy," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    7. Zulfiqar Ali Wagan & Zhang Chen & Hakimzadi Wagan, 2019. "A Factor-Augmented Vector Autoregressive Approach to Analyze the Transmission of Monetary Policy," Prague Economic Papers, Prague University of Economics and Business, vol. 2019(6), pages 709-728.

  2. Markku Lanne & Jani Luoto, 2015. "Estimation of DSGE Models under Diffuse Priors and Data-Driven Identification Constraints," CREATES Research Papers 2015-37, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Baştürk, N. & Grassi, S. & Hoogerheide, L. & van Dijk, H.K., 2016. "Parallelization experience with four canonical econometric models using ParMitISEM," Research Memorandum 013, Maastricht University, Graduate School of Business and Economics (GSBE).
    2. Morris, Stephen D., 2017. "DSGE pileups," Journal of Economic Dynamics and Control, Elsevier, vol. 74(C), pages 56-86.

  3. Markku Lanne & Mika Meitz & Pentti Saikkonen, 2015. "Identification and estimation of non-Gaussian structural vector autoregressions," CREATES Research Papers 2015-16, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    2. Stephan B. Bruns & Alessio Moneta & David I. Stern, 2019. "Estimating the Economy-Wide Rebound Effect Using Empirically Identified Structural Vector Autoregressions," LEM Papers Series 2019/27, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Tölö, Eero & Miettinen, Paavo, 2018. "How do shocks to bank capital affect lending and growth?," Bank of Finland Research Discussion Papers 25/2018, Bank of Finland.
    4. Rupam Bhattacharyya & Sheo Rama & Atul Kumar & Indrajit Banerjee, 2021. "Dynamic Structural Impact of the COVID-19 Outbreak on the Stock Market and the Exchange Rate: A Cross-country Analysis Among BRICS Nations," Papers 2102.05554, arXiv.org.
    5. Olli Palm'en, 2022. "Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach," Papers 2202.10834, arXiv.org.
    6. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    7. Moneta, Alessio & Pallante, Gianluca, 2022. "Identification of Structural VAR Models via Independent Component Analysis: A Performance Evaluation Study," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    8. Jan R. Magnus & Enrique Sentana, 2020. "Zero-diagonality as a linear structure," Tinbergen Institute Discussion Papers 20-039/III, Tinbergen Institute.
    9. Nunes, Clemens Vinicius & Doi, Jonas & Fernandes, Marcelo, 2017. "Disagreement in Inflation Forecasts and Inflation Risk Premia in Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(1), May.
    10. Alain Guay, 2020. "Identification of Structural Vector Autoregressions Through Higher Unconditional Moments," Working Papers 20-19, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    11. Herwartz, Helmut & Lange, Alexander & Maxand, Simone, 2019. "Statistical identification in SVARs - Monte Carlo experiments and a comparative assessment of the role of economic uncertainties for the US business cycle," University of Göttingen Working Papers in Economics 375, University of Goettingen, Department of Economics.
    12. Giovanni Angelini & Marco M. Sorge, 2021. "Under the same (Chole)sky: DNK models, timing restrictions and recursive identification of monetary policy shocks," Working Papers wp1160, Dipartimento Scienze Economiche, Universita' di Bologna.
    13. Guido Turnip, 2017. "Identification of Small Open Economy SVARs via Markov-Switching Heteroskedasticity," The Economic Record, The Economic Society of Australia, vol. 93(302), pages 465-483, September.
    14. Olli Palm'en, 2020. "Inflation Dynamics of Financial Shocks," Papers 2006.03301, arXiv.org.
    15. Guay, Alain, 2021. "Identification of structural vector autoregressions through higher unconditional moments," Journal of Econometrics, Elsevier, vol. 225(1), pages 27-46.
    16. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    17. Sune Karlsson & Stepan Mazur & Hoang Nguyen, 2021. "Vector autoregression models with skewness and heavy tails," Papers 2105.11182, arXiv.org.
    18. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    19. Ciarli, Tommaso & Coad, Alex & Moneta, Alessio, 2023. "Does exporting cause productivity growth? Evidence from Chilean firms," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 228-239.
    20. Thorsten Drautzburg, 2020. "A narrative approach to a fiscal DSGE model," Quantitative Economics, Econometric Society, vol. 11(2), pages 801-837, May.
    21. Georgiadis, Georgios & Jarociński, Marek, 2023. "Global spillovers from multi-dimensional US monetary policy," Working Paper Series 2881, European Central Bank.
    22. Alfan Mansur, 2023. "Simultaneous identification of fiscal and monetary policy shocks," Empirical Economics, Springer, vol. 65(2), pages 697-728, August.
    23. HAFNER Christian, & HERWARTZ Helmut, & MAXAND Simone,, 2018. "Identification of structural multivariate GARCH models," LIDAM Discussion Papers CORE 2018020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    24. Philippe Andrade & Filippo Ferroni & Leonardo Melosi, 2023. "Identification Using Higher-Order Moments Restrictions," Working Paper Series WP 2023-28, Federal Reserve Bank of Chicago.
    25. Gouriéroux, Christian & Monfort, Alain & Renne, Jean-Paul, 2017. "Statistical inference for independent component analysis: Application to structural VAR models," Journal of Econometrics, Elsevier, vol. 196(1), pages 111-126.
    26. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2020. "Modelling Returns in US Housing Prices – You’re the One for Me, Fat Tails," Working Papers 2020:13, Örebro University, School of Business.
    27. Marco Capasso & Alessio Moneta, 2016. "Macroeconomic responses to an independent monetary policy shock: a (more) agnostic identification procedure," LEM Papers Series 2016/36, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    28. Bernoth, Kerstin & Herwartz, Helmut, 2021. "Exchange rates, foreign currency exposure and sovereign risk," Journal of International Money and Finance, Elsevier, vol. 117(C).
    29. Dalheimer, Bernhard & Herwartz, Helmut & Lange, Alexander, 2021. "The threat of oil market turmoils to food price stability in Sub-Saharan Africa," Energy Economics, Elsevier, vol. 93(C).
    30. Herwartz, Helmut & Maxand, Simone & Rohloff, Hannes, 2018. "Lean against the wind or float with the storm? Revisiting the monetary policy asset price nexus by means of a novel statistical identification approach," University of Göttingen Working Papers in Economics 354, University of Goettingen, Department of Economics.
    31. Berner, Anne & Bruns, Stephan B. & Moneta, Alessio & Stern, David I., 2021. "Do energy efficiency improvements reduce energy use? Empirical evidence on the economy-wide rebound effect in Europe and the United States," University of Göttingen Working Papers in Economics 422, University of Goettingen, Department of Economics.
    32. Thomas Chuffart & Cyril Dell'Eva, 2020. "The role of carry trades on the effectiveness of Japan's quantitative easing," Post-Print hal-03157207, HAL.
    33. Gabriele Fiorentini & Enrique Sentana, 2018. "Consistent Non-Gaussian Pseudo Maximum Likelihood Estimators," Working Papers wp2018_1802, CEMFI.
    34. Gabriele Fiorentini & Enrique Sentana, 2020. "Discrete Mixtures of Normals Pseudo Maximum Likelihood Estimators of Structural Vector Autoregressions," Working Papers wp2020_2023, CEMFI.
    35. Karamysheva, Madina & Skrobotov, Anton, 2022. "Do we reject restrictions identifying fiscal shocks? identification based on non-Gaussian innovations," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    36. Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2020. "Proxy SVAR identification of monetary policy shocks: MonteCarlo evidence and insights for the US," University of Göttingen Working Papers in Economics 404, University of Goettingen, Department of Economics.
    37. Konstantin A. Kholodilin & Aleksei Netsunajev, 2016. "Crimea and Punishment: The Impact of Sanctions on Russian and European Economies," Discussion Papers of DIW Berlin 1569, DIW Berlin, German Institute for Economic Research.
    38. Drautzburg, Thorsten & Wright, Jonathan H, 2021. "Refining Set-Identification in VARs through Independence," Economics Working Paper Archive 64575, The Johns Hopkins University,Department of Economics.
    39. Andrea Giovanni Gazzani & Alejandro Vicondoa, 2019. "Proxy-SVAR as a Bridge for Identification with Higher Frequency Data," 2019 Meeting Papers 855, Society for Economic Dynamics.
    40. Reinhold Heinlein & Scott M. R. Mahadeo, 2023. "Oil and US stock market shocks: Implications for Canadian equities," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(1), pages 247-287, February.
    41. Jan R. Magnus & Henk G. J. Pijls & Enrique Sentana, 2020. "The Jacobian of the Exponential Function," Working Papers wp2020_2005, CEMFI.
    42. Zema, Sebastiano Michele, 2022. "Directed acyclic graph based information shares for price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    43. Braun, Robin, 2021. "The importance of supply and demand for oil prices: evidence from non-Gaussianity," Bank of England working papers 957, Bank of England.
    44. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
    45. Giulio Ecchia & Francesca Gagliardi & Caterina Giannetti, 2018. "Social Investment and youth labour market participation: a EU regional analysis," Discussion Papers 2018/236, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    46. Alex Coad & Dominik Janzing & Paul Nightingale, 2018. "Tools for causal inference from cross-sectional innovation surveys with continuous or discrete variables: Theory and applications," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 37(75), pages 779-808, March.
    47. Herwartz, Helmut & Wang, Shu, 2023. "Point estimation in sign-restricted SVARs based on independence criteria with an application to rational bubbles," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    48. Aramayis Dallakyan, 2021. "Nonparanormal Structural VAR for Non-Gaussian Data," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1093-1113, April.
    49. Sascha A. Keweloh, 2023. "Uncertain Prior Economic Knowledge and Statistically Identified Structural Vector Autoregressions," Papers 2303.13281, arXiv.org.
    50. Keweloh, Sascha A. & Hetzenecker, Stephan & Seepe, Andre, 2023. "Monetary policy and information shocks in a block-recursive SVAR," Journal of International Money and Finance, Elsevier, vol. 137(C).
    51. Uhrin, Gábor B. & Herwartz, Helmut, 2016. "Monetary policy shocks, set-identifying restrictions, and asset prices: A benchmarking approach for analyzing set-identified models," University of Göttingen Working Papers in Economics 295, University of Goettingen, Department of Economics.
    52. Andrea Cipollini & Fabio Parla, 2023. "Climate risk and investment in equities in Europe: a Panel SVAR approach," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0093, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    53. Mario Martinoli & Alessio Moneta & Gianluca Pallante, 2022. "Calibration and Validation of Macroeconomic Simulation Models by Statistical Causal Search," LEM Papers Series 2022/33, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    54. Geert Bekaert & Eric Engstrom & Andrey Ermolov, 2020. "Aggregate Demand and Aggregate Supply Effects of COVID-19: A Real-time Analysis," Finance and Economics Discussion Series 2020-049, Board of Governors of the Federal Reserve System (U.S.).
    55. Sebastiano Michele Zema, 2023. "A non-Normal framework for price discovery: The independent component based information shares measure," LEM Papers Series 2023/03, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    56. Marina Marena & Andrea Romeo & Patrizia Semeraro, 2022. "Non-maturing deposits modelling in a Ornstein-Uhlenbeck framework," Papers 2209.13314, arXiv.org.
    57. Bernd Funovits, 2020. "Identifiability and Estimation of Possibly Non-Invertible SVARMA Models: A New Parametrisation," Papers 2002.04346, arXiv.org, revised Feb 2021.
    58. Geert Bekaert & Eric Engstrom & Andrey Ermolov, 2017. "Macro Risks and the Term Structure of Interest Rates," Finance and Economics Discussion Series 2017-058, Board of Governors of the Federal Reserve System (U.S.).
    59. Petrova, Katerina, 2022. "Asymptotically valid Bayesian inference in the presence of distributional misspecification in VAR models," Journal of Econometrics, Elsevier, vol. 230(1), pages 154-182.
    60. Dobromił Serwa & Piotr Wdowiński, 2017. "Modeling Macro-Financial Linkages: Combined Impulse Response Functions in SVAR Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(4), pages 323-357, December.
    61. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhuang, Xin-Tian, 2019. "Non-Gaussian VARMA model with stochastic volatility and applications in stock market bubbles," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 129-136.
    62. Puonti, Päivi, 2019. "Data-driven structural BVAR analysis of unconventional monetary policy," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    63. Bernd Funovits, 2019. "Identification and Estimation of SVARMA models with Independent and Non-Gaussian Inputs," Papers 1910.04087, arXiv.org.
    64. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "Moment tests of independent components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 429-474, May.
    65. Kerstin Bernoth & Helmut Herwartz & Lasse Trienens, 2023. "The Impacts of Global Risk and US Monetary Policy on US Dollar Exchange Rates and Excess Currency Returns," Discussion Papers of DIW Berlin 2037, DIW Berlin, German Institute for Economic Research.
    66. Tommaso Ciarli & Alex Coad & Alessio Moneta, 2019. "Exporting and productivity as part of the growth process: Causal evidence from a data-driven structural VAR," LEM Papers Series 2019/39, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    67. Kalli, Maria & Griffin, Jim E., 2018. "Bayesian nonparametric vector autoregressive models," Journal of Econometrics, Elsevier, vol. 203(2), pages 267-282.
    68. Brancaccio, Emiliano & Califano, Andrea & Lopreite, Milena & Moneta, Alessio, 2020. "Nonperforming loans and competing rules of monetary policy: A statistical identification approach," Structural Change and Economic Dynamics, Elsevier, vol. 53(C), pages 127-136.
    69. Sascha A. Keweloh & Mathias Klein & Jan Pruser, 2023. "Estimating Fiscal Multipliers by Combining Statistical Identification with Potentially Endogenous Proxies," Papers 2302.13066, arXiv.org, revised Feb 2024.
    70. Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2022. "Proxy SVAR identification of monetary policy shocks - Monte Carlo evidence and insights for the US," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    71. Maxand, Simone, 2020. "Identification of independent structural shocks in the presence of multiple Gaussian components," Econometrics and Statistics, Elsevier, vol. 16(C), pages 55-68.
    72. Markku Lanne & Jani Luoto, 2016. "Data-Driven Inference on Sign Restrictions in Bayesian Structural Vector Autoregression," CREATES Research Papers 2016-04, Department of Economics and Business Economics, Aarhus University.
    73. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 16(2), pages 316-339.
    74. Helmut Herwartz, 2022. "Modelling interaction patterns in a predator-prey system of two freshwater organisms in discrete time: an identified structural VAR approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 63-85, March.
    75. Sebastiano Michele Zema, 2020. "Directed Acyclic Graph based Information Shares for Price Discovery," LEM Papers Series 2020/28, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    76. Miguel Cabello, 2022. "Robust Estimation of the non-Gaussian Dimension in Structural Linear Models," Papers 2212.07263, arXiv.org, revised Sep 2023.
    77. Francesco Cordoni & Nicolas Doremus & Alessio Moneta, 2023. "Identification of Vector Autoregressive Models with Nonlinear Contemporaneous Structure," LEM Papers Series 2023/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  4. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    2. Ülkü, Numan & Kuruppuarachchi, Duminda & Kuzmicheva, Olga, 2017. "Stock market's response to real output shocks in Eastern European frontier markets: A VARwAL model," Emerging Markets Review, Elsevier, vol. 33(C), pages 140-154.

  5. Markku Lanne & Jani Luoto, 2014. "Noncausal Bayesian Vector Autoregression," CREATES Research Papers 2014-07, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Numan Ülkü & Kexing Wu, 2023. "Stock Market's Response to Real Output Shocks in China: A VARwAL Estimation," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 31(5), pages 1-25, September.
    2. Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
    3. Nelimarkka, Jaakko, 2017. "Evidence on News Shocks under Information Deficiency," MPRA Paper 80850, University Library of Munich, Germany.
    4. Baştürk, N. & Grassi, S. & Hoogerheide, L. & van Dijk, H.K., 2016. "Parallelization experience with four canonical econometric models using ParMitISEM," Research Memorandum 013, Maastricht University, Graduate School of Business and Economics (GSBE).
    5. Ülkü, Numan & Kuruppuarachchi, Duminda & Kuzmicheva, Olga, 2017. "Stock market's response to real output shocks in Eastern European frontier markets: A VARwAL model," Emerging Markets Review, Elsevier, vol. 33(C), pages 140-154.
    6. Nelimarkka, Jaakko, 2017. "The effects of government spending under anticipation: the noncausal VAR approach," MPRA Paper 81303, University Library of Munich, Germany.

  6. Markku Lanne & Henri Nyberg, 2014. "Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models," CREATES Research Papers 2014-17, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Pierre Mabille, 2019. "Aggregate Precautionary Savings Motives," 2019 Meeting Papers 344, Society for Economic Dynamics.
    2. Mumtaz, Haroon & Theodoridis, Konstantinos, 2018. "Dynamic Effects of Monetary Policy Shocks on Macroeconomic Volatility," Cardiff Economics Working Papers E2018/21, Cardiff University, Cardiff Business School, Economics Section.
    3. Maximilian Böck & Martin Feldkircher & Florian Huber, 2020. "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R," Globalization Institute Working Papers 395, Federal Reserve Bank of Dallas.
    4. Pierre L Siklos, 2019. "US monetary policy since the 1950s and the changing content of FOMC minutes," CAMA Working Papers 2019-69, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Caggiano, Giovanni & Castelnuovo, Efrem & Figueres, Juan Manuel, 2017. "Economic policy uncertainty and unemployment in the United States: A nonlinear approach," Economics Letters, Elsevier, vol. 151(C), pages 31-34.
    6. Cui, Yu & Khan, Sufyan Ullah & Sauer, Johannes & Kipperberg, Gorm & Zhao, Minjuan, 2023. "Agricultural carbon footprint, energy utilization and economic quality: What causes what, and where?," Energy, Elsevier, vol. 278(PA).
    7. Härdle, Wolfgang Karl & Chen, Shi & Liang, Chong & Schienle, Melanie, 2018. "Time-varying Limit Order Book Networks," IRTG 1792 Discussion Papers 2018-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Feldkircher, Martin & Lukmanova, Elizaveta & Tondl, Gabriele, 2019. "Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment," Department of Economics Working Paper Series 289, WU Vienna University of Economics and Business.
    9. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Fed’s unconventional monetary policy and risk spillover in the US financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 42-52.
    10. Liu, Jianing & Man, Yuanyuan & Dong, Xiuliang, 2023. "Tail dependence and risk spillover effects between China's carbon market and energy markets," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 553-567.
    11. Nhlangwini, Pamela & Mongale, Itumeleng Pleasure, 2019. "Mining Production and Economic Growth Nexus," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 53(3), pages 103-116.
    12. Giovanni Pellegrino & Federico Ravenna & Gabriel Züllig, 2021. "The Impact of Pessimistic Expectations on the Effects of COVID‐19‐Induced Uncertainty in the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 841-869, August.
    13. Bettendorf, Timo & Heinlein, Reinhold, 2019. "Connectedness between G10 currencies: Searching for the causal structure," Discussion Papers 06/2019, Deutsche Bundesbank.
    14. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    15. Chen, Shi & Härdle, Wolfgang & Schienle, Melanie, 2021. "High-dimensional statistical learning techniques for time-varying limit order book networks," IRTG 1792 Discussion Papers 2021-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    16. Giovanni Caggiano & Efrem Castelnuovo & Juan Manuel Figueres, 2018. "Economic policy uncertainty spillovers in booms and busts," CAMA Working Papers 2018-27, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Efrem Castelnuovo & Giovanni Caggiano & Giovanni Pellegrino, 2015. "Estimating the Real Effects of Uncertainty Shocks at the Zero Lower Bound," "Marco Fanno" Working Papers 0200, Dipartimento di Scienze Economiche "Marco Fanno".
    18. Frédéric Karamé, 2015. "Asymmetries and Markov-switching structural VAR," Post-Print hal-02296101, HAL.
    19. Strobel, Johannes & Lee, Gabriel & Dorofeenko, Victor & Salyer, Kevin, 2019. "Time-Varying Risk Shocks and the Zero Lower Bound," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203491, Verein für Socialpolitik / German Economic Association.
    20. Donadelli, Michael & Grüning, Patrick, 2021. "Innovation dynamics and fiscal policy: Implications for growth, asset prices, and welfare," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    21. Michael Donadelli & Marcus Jüppner & Antonio Paradiso & Christian Schlag, 2019. "Temperature Volatility Risk," Working Papers 2019:05, Department of Economics, University of Venice "Ca' Foscari".
    22. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Aygun, Gurcan & Wohar, Mark E., 2021. "Effectives of Monetary Policy under the High and Low Economic Uncertainty States: Evidence from the Major Asian Economies," IZA Discussion Papers 14420, Institute of Labor Economics (IZA).
    23. Thiem, Christopher, 2018. "Cross-category, trans-Pacific spillovers of policy uncertainty and financial market volatility," Ruhr Economic Papers 782, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    24. Rashid Sbia & Sahel Alrousan, 2016. "Does Financial Development Induce Economic Growth in UAE? The Role of Capitalization and Foreign Direct Investment," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 703-710.
    25. Caloia, Francesco Giuseppe & Cipollini, Andrea & Muzzioli, Silvia, 2019. "How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study," Energy Economics, Elsevier, vol. 84(C).
    26. Gian Paulo Soave, 2023. "A panel threshold VAR with stochastic volatility-in-mean model: an application to the effects of financial and uncertainty shocks in emerging economies," Applied Economics, Taylor & Francis Journals, vol. 55(4), pages 397-431, January.
    27. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Spillover effects in oil-related CDS markets during and after the sub-prime crisis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    28. Mr. Jorge A Chan-Lau, 2017. "Variance Decomposition Networks: Potential Pitfalls and a Simple Solution," IMF Working Papers 2017/107, International Monetary Fund.
    29. Pierre L. Siklos & Martin Stefan & Claudia Wellenreuther, 2020. "Metal prices made in China? A network analysis of industrial metal futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(9), pages 1354-1374, September.
    30. Nalban, Valeriu & Smădu, Andra, 2021. "Asymmetric effects of uncertainty shocks: Normal times and financial disruptions are different," Journal of Macroeconomics, Elsevier, vol. 69(C).
    31. Gaysset, Isabelle & Lagoarde-Segot, Thomas & Neaime, Simon, 2019. "Twin deficits and fiscal spillovers in the EMU's periphery. A Keynesian perspective," Economic Modelling, Elsevier, vol. 76(C), pages 101-116.
    32. Böhl, Gregor & Strobel, Felix, 2020. "US business cycle dynamics at the zero lower bound," Discussion Papers 65/2020, Deutsche Bundesbank.
    33. Beckmann, Joscha & Davidson, Sharada Nia & Koop, Gary & Schüssler, Rainer, 2023. "Cross-country uncertainty spillovers: Evidence from international survey data," Journal of International Money and Finance, Elsevier, vol. 130(C).
    34. Yoshihiko Hogen & Yoshiyasu Koide & Yuji Shinozaki, 2022. "Rise of NBFIs and the Global Structural Change in the Transmission of Market Shocks," Bank of Japan Working Paper Series 22-E-14, Bank of Japan.
    35. Balcilar, Mehmet & Roubaud, David & Usman, Ojonugwa & Wohar, Mark E., 2021. "Moving out of the linear rut: A period-specific and regime-dependent exchange rate and oil price pass-through in the BRICS countries," Energy Economics, Elsevier, vol. 98(C).
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    39. Kyriaki-Argyro Tsioptsia & Eleni Zafeiriou & Dimitrios Niklis & Nikolaos Sariannidis & Constantin Zopounidis, 2022. "The Corporate Economic Performance of Environmentally Eligible Firms Nexus Climate Change: An Empirical Research in a Bayesian VAR Framework," Energies, MDPI, vol. 15(19), pages 1-16, October.
    40. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
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    44. Luis Alberto Delgado-de-la-Garza & Gonzalo Adolfo Garza-Rodríguez & Daniel Alejandro Jacques-Osuna & Alejandro Múgica-Lara & Carlos Alberto Carrasco, 2021. "Does the use of a big data variable improve monetary policy estimates? Evidence from Mexico," Economics and Business Letters, Oviedo University Press, vol. 10(4), pages 383-393.
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    49. Ahmed, Khalid & Ur Rehman, Mujeeb & Ozturk, Ilhan, 2016. "What drives carbon dioxide emissions in the long-run? Evidence from selected South Asian Countries," MPRA Paper 75420, University Library of Munich, Germany.
    50. Tyler Atkinson & Michael D. Plante & Alexander W. Richter & Nathaniel A. Throckmorton, 2020. "Complementarity and Macroeconomic Uncertainty," Working Papers 2009, Federal Reserve Bank of Dallas.
    51. Li Wang & Jinyang Tang & Mengqian Tang & Mengying Su & Lili Guo, 2022. "Scale of Operation, Financial Support, and Agricultural Green Total Factor Productivity: Evidence from China," IJERPH, MDPI, vol. 19(15), pages 1-18, July.
    52. Timo Bettendorf & Reinhold Heinlein, 2023. "Connectedness between G10 currencies: Searching for the causal structure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3938-3959, October.
    53. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Transmission of US and EU Economic Policy Uncertainty Shock to Asian Economies in Bad and Good Times," IZA Discussion Papers 13274, Institute of Labor Economics (IZA).
    54. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.
    55. Wu, Gabriel Shui Tang & Leung, Pak Ho, 2023. "Do asset-backed stablecoins spread crypto volatility to traditional financial assets? Evidence from Tether," Economics Letters, Elsevier, vol. 229(C).
    56. Kang, Sang Hoon & Maitra, Debasish & Dash, Saumya Ranjan & Brooks, Robert, 2019. "Dynamic spillovers and connectedness between stock, commodities, bonds, and VIX markets," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    57. Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir & Gurcan Aygun & Mark E. Wohar, 2022. "Effectiveness of monetary policy under the high and low economic uncertainty states: evidence from the major Asian economies," Empirical Economics, Springer, vol. 63(4), pages 1741-1769, October.
    58. Lorenzo Bretscher & Alex Hsu & Andrea Tamoni, 2017. "Level and Volatility Shocks to Fiscal Policy: Term Structure Implications," 2017 Meeting Papers 258, Society for Economic Dynamics.
    59. Stolbov, Mikhail & Shchepeleva, Maria & Karminsky, Alexander, 2022. "When central bank research meets Google search: A sentiment index of global financial stress," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    60. Lyu, Yongjian & Yi, Heling & Cao, Jin & Yang, Mo, 2022. "Time-varying monetary policy shocks and the dynamics of Chinese commodity prices," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    61. Raul Ibarra, 2016. "How important is the credit channel in the transmission of monetary policy in Mexico?," Applied Economics, Taylor & Francis Journals, vol. 48(36), pages 3462-3484, August.
    62. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
    63. David Ubilava, 2018. "The Role of El Niño Southern Oscillation in Commodity Price Movement and Predictability," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(1), pages 239-263.
    64. Nam, Kyungsik, 2021. "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, vol. 96(C).
    65. Nyholm, Ken, 2016. "US-euro area term structure spillovers, implications for central banks," Working Paper Series 1980, European Central Bank.
    66. Hamill, Philip A. & Li, Youwei & Pantelous, Athanasios A. & Vigne, Samuel A. & Waterworth, James, 2021. "Was a deterioration in ‘connectedness’ a leading indicator of the European sovereign debt crisis?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    67. Yépez, Carlos & Dzikpe, Francis, 2022. "Accounting for real exchange rates in emerging economies: The role of commodity prices," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 476-492.
    68. Clausen Volker & Schlösser Alexander & Thiem Christopher, 2019. "Economic Policy Uncertainty in the Euro Area: Cross-Country Spillovers and Macroeconomic Impact," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(5-6), pages 957-981, October.
    69. Zahra Naoar Masih, 2017. "Causality between Defence Spending and Economic Growth in Sub-Saharan Africa: Evidence on a Controversial Empirical Issue," International Journal of Economics and Financial Issues, Econjournals, vol. 7(5), pages 169-177.
    70. Taifeng Yang & Xuetao Huang & Yue Wang & Houjian Li & Lili Guo, 2022. "Dynamic Linkages among Climate Change, Mechanization and Agricultural Carbon Emissions in Rural China," IJERPH, MDPI, vol. 19(21), pages 1-24, November.
    71. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    72. Joshua Bernstein & Michael D. Plante & Alexander W. Richter & Nathaniel A. Throckmorton, 2021. "Countercyclical Fluctuations in Uncertainty are Endogenous," Working Papers 2109, Federal Reserve Bank of Dallas.
    73. Martin Feldkircher & Pierre L. Siklos, 2018. "Global inflation dynamics and inflation expectations," CAMA Working Papers 2018-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    74. Houjian Li & Xiaolei Zhou & Mengqian Tang & Lili Guo, 2022. "Impact of Population Aging and Renewable Energy Consumption on Agricultural Green Total Factor Productivity in Rural China: Evidence from Panel VAR Approach," Agriculture, MDPI, vol. 12(5), pages 1-19, May.
    75. Xingwei Hu, 2021. "Decoding Causality by Fictitious VAR Modeling," Papers 2111.07465, arXiv.org, revised Nov 2021.
    76. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.
    77. Donal Smith, 2016. "The International Impact of Financial Shocks: A Global VAR and Connectedness Measures Approach," Discussion Papers 16/07, Department of Economics, University of York.
    78. SBIA, Rashid & Al Rousan, Sahel, 2015. "Does Financial Development Induce Economic Growth in UAE? The Role of Foreign Direct Investment and Capitalization," MPRA Paper 64599, University Library of Munich, Germany.
    79. Lili Guo & Shuang Zhao & Yuting Song & Mengqian Tang & Houjian Li, 2022. "Green Finance, Chemical Fertilizer Use and Carbon Emissions from Agricultural Production," Agriculture, MDPI, vol. 12(3), pages 1-18, February.
    80. Namahoro, J.P. & Wu, Q. & Zhou, N. & Xue, S., 2021. "Impact of energy intensity, renewable energy, and economic growth on CO2 emissions: Evidence from Africa across regions and income levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    81. Sharada Nia Davidson, 2022. "Regional Integration and Decoupling in the Asia Pacific: A Bayesian Panel VAR Approach," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(4), pages 773-807, December.
    82. Namahoro, Jean Pierre & Wu, Qiaosheng & Hui, Su, 2023. "Asymmetric linkage between copper-cobalt productions and economic growth: Evidence from Republic Democratic of Congo," Resources Policy, Elsevier, vol. 83(C).
    83. Michael Donadelli & Marcus Jüppner & Antonio Paradiso & Christian Schlag, 2021. "Computing Macro-Effects and Welfare Costs of Temperature Volatility: A Structural Approach," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 347-394, August.
    84. Maria Bolboaca & Sarah Fischer, 2019. "News Shocks: Different Effects in Boom and Recession?," Working Papers 19.01, Swiss National Bank, Study Center Gerzensee.

  7. Markku Lanne, 2013. "Noncausality and Inflation Persistence," Discussion Papers of DIW Berlin 1286, DIW Berlin, German Institute for Economic Research.

    Cited by:

    1. Dimitrakopoulos, Stefanos, 2017. "Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility," Economics Letters, Elsevier, vol. 150(C), pages 10-14.
    2. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.

  8. Lanne, Markku & Luoto, Jani, 2012. "Does Output Gap, Labor's Share or Unemployment Rate Drive Inflation?," MPRA Paper 41820, University Library of Munich, Germany.

    Cited by:

    1. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    2. Narayan, Seema & Cirikisuva, Salote & Naivutu, Revoni, 2023. "A hybrid NKPC inflation model for the small Island state of Fiji," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 873-886.
    3. Dustin Chambers & Courtney A. Collins & Alan Krause, 2019. "How do federal regulations affect consumer prices? An analysis of the regressive effects of regulation," Public Choice, Springer, vol. 180(1), pages 57-90, July.
    4. Narayan, Paresh Kumar & Narayan, Seema & Eki Rahman, R. & Setiawan, Iwan, 2019. "Bitcoin price growth and Indonesia's monetary system," Emerging Markets Review, Elsevier, vol. 38(C), pages 364-376.

  9. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.

    Cited by:

    1. Ooft, Gavin & Bhaghoe, Sailesh & Hans Franses, Philip, 2021. "Forecasting annual inflation in Suriname," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    2. Carlos Medel, 2015. "Inflation Dynamics and the Hybrid Neo Keynesian Phillips Curve: The Case of Chile," Working Papers Central Bank of Chile 769, Central Bank of Chile.
    3. Markku Lanne & Jani Luoto, 2019. "A comment on ‘on inflation expectations in the NKPC model’," Empirical Economics, Springer, vol. 57(6), pages 1865-1867, December.
    4. Zhang, Chengsi & Murasawa, Yasutomo, 2011. "Output gap measurement and the New Keynesian Phillips curve for China," Economic Modelling, Elsevier, vol. 28(6), pages 2462-2468.
    5. Alain Hecq & Li Sun, 2019. "Identification of Noncausal Models by Quantile Autoregressions," Papers 1904.05952, arXiv.org.
    6. Nyberg, Henri & Saikkonen, Pentti, 2014. "Forecasting with a noncausal VAR model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 536-555.
    7. Alain Hecq & Sean Telg & Lenard Lieb, 2017. "Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?," Econometrics, MDPI, vol. 5(4), pages 1-22, October.
    8. Kramkov, Viacheslav & Maksimov, Andrey, 2020. "Loan market markups and noncausal autoregressions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 60, pages 48-69.
    9. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    10. Philip Hans Franses, 2019. "On inflation expectations in the NKPC model," Empirical Economics, Springer, vol. 57(6), pages 1853-1864, December.
    11. Weifeng Jin, 2023. "Quantile Autoregression-based Non-causality Testing," Papers 2301.02937, arXiv.org.
    12. Phiri, Andrew, 2015. "Examining asymmetric effects in the South African Philips curve: Evidence from logistic smooth transition regression (LSTR) models," MPRA Paper 64487, University Library of Munich, Germany.
    13. Alain Hecq & Joao Issler & Elisa Voisin, 2022. "A short term credibility index for central banks under inflation targeting: an application to Brazil," Papers 2205.00924, arXiv.org, revised Jul 2022.
    14. Hecq Alain & Sun Li, 2021. "Selecting between causal and noncausal models with quantile autoregressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(5), pages 393-416, December.
    15. Hecq, Alain & Issler, João Victor & Telg, Sean, 2017. "Mixed Causal-Noncausal Autoregressions with Strictly Exogenous Regressors," MPRA Paper 80767, University Library of Munich, Germany.

  10. Lanne, Markku & Nyberg, Henri & Saarinen, Erkka, 2011. "Forecasting U.S. Macroeconomic and Financial Time Series with Noncausal and Causal AR Models: A Comparison," MPRA Paper 30254, University Library of Munich, Germany.

    Cited by:

    1. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
    2. Henri Nyberg & Markku Lanne & Erkka Saarinen, 2012. "Does noncausality help in forecasting economic time series?," Economics Bulletin, AccessEcon, vol. 32(4), pages 2849-2859.
    3. Gourieroux, Christian & Jasiak, Joann, 2018. "Misspecification of noncausal order in autoregressive processes," Journal of Econometrics, Elsevier, vol. 205(1), pages 226-248.

  11. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2010. "Optimal Forecasting of Noncausal Autoregressive Time Series," MPRA Paper 23648, University Library of Munich, Germany.

    Cited by:

    1. Francisco Blasques & Siem Jan Koopman & Gabriele Mingoli, 2023. "Observation-Driven filters for Time-Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics," Tinbergen Institute Discussion Papers 23-065/III, Tinbergen Institute.
    2. Hecq, A.W. & Lieb, L.M. & Telg, J.M.A., 2015. "Identification of Mixed Causal-Noncausal Models : How Fat Should We Go?," Research Memorandum 035, Maastricht University, Graduate School of Business and Economics (GSBE).
    3. Karapanagiotidis, Paul, 2013. "Empirical evidence for nonlinearity and irreversibility of commodity futures prices," MPRA Paper 56801, University Library of Munich, Germany.
    4. Saikkonen, Pentti & Sandberg, Rickard, 2013. "Testing for a unit root in noncausal autoregressive models," Bank of Finland Research Discussion Papers 26/2013, Bank of Finland.
    5. Matthijs Lof, 2014. "GMM Estimation with Non-causal Instruments under Rational Expectations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 279-286, April.
    6. Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
    7. Dimitrakopoulos, Stefanos, 2017. "Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility," Economics Letters, Elsevier, vol. 150(C), pages 10-14.
    8. Lof, Matthijs, 2011. "Noncausality and Asset Pricing," MPRA Paper 30519, University Library of Munich, Germany.
    9. Lanne, Markku & Luoto, Jani, 2012. "Has US inflation really become harder to forecast?," Economics Letters, Elsevier, vol. 115(3), pages 383-386.
    10. Cubadda, Gianluca & Hecq, Alain & Telg, Sean, 2017. "Detecting Co-Movements in Noncausal Time Series," MPRA Paper 77254, University Library of Munich, Germany, revised 02 Mar 2017.
    11. Lanne, Markku & Saikkonen, Pentti, 2009. "Noncausal vector autoregression," Bank of Finland Research Discussion Papers 18/2009, Bank of Finland.
    12. Alain Hecq & Daniel Velasquez-Gaviria, 2022. "Spectral estimation for mixed causal-noncausal autoregressive models," Papers 2211.13830, arXiv.org.
    13. Christian Gourieroux & Andrew Hencic & Joann Jasiak, 2021. "Forecast performance and bubble analysis in noncausal MAR(1, 1) processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 301-326, March.
    14. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.
    15. Alain Hecq & Elisa Voisin, 2019. "Predicting crashes in oil prices during the COVID-19 pandemic with mixed causal-noncausal models," Papers 1911.10916, arXiv.org, revised May 2022.
    16. Akhter Mohiuddin Rather & V. N. Sastry & Arun Agarwal, 2017. "Stock market prediction and Portfolio selection models: a survey," OPSEARCH, Springer;Operational Research Society of India, vol. 54(3), pages 558-579, September.
    17. Alain Hecq & Li Sun, 2019. "Identification of Noncausal Models by Quantile Autoregressions," Papers 1904.05952, arXiv.org.
    18. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    19. Nyberg, Henri & Saikkonen, Pentti, 2014. "Forecasting with a noncausal VAR model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 536-555.
    20. Alain Hecq & Sean Telg & Lenard Lieb, 2017. "Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?," Econometrics, MDPI, vol. 5(4), pages 1-22, October.
    21. Lanne Markku, 2015. "Noncausality and inflation persistence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 469-481, September.
    22. Lanne, Markku & Nyberg, Henri & Saarinen, Erkka, 2011. "Forecasting U.S. Macroeconomic and Financial Time Series with Noncausal and Causal AR Models: A Comparison," MPRA Paper 30254, University Library of Munich, Germany.
    23. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    24. Henri Nyberg & Markku Lanne & Erkka Saarinen, 2012. "Does noncausality help in forecasting economic time series?," Economics Bulletin, AccessEcon, vol. 32(4), pages 2849-2859.
    25. Hecq, Alain & Voisin, Elisa, 2021. "Forecasting bubbles with mixed causal-noncausal autoregressive models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 29-45.
    26. Meitz, Mika & Saikkonen, Pentti, 2013. "Maximum likelihood estimation of a noninvertible ARMA model with autoregressive conditional heteroskedasticity," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 227-255.
    27. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    28. Karapanagiotidis, Paul, 2014. "Dynamic modeling of commodity futures prices," MPRA Paper 56805, University Library of Munich, Germany.
    29. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    30. Lanne Markku & Saikkonen Pentti, 2011. "Noncausal Autoregressions for Economic Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-32, October.
    31. Weifeng Jin, 2023. "Quantile Autoregression-based Non-causality Testing," Papers 2301.02937, arXiv.org.
    32. Demetrescu, Matei & Kruse, Robinson, 2015. "Testing heteroskedastic time series for normality," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113221, Verein für Socialpolitik / German Economic Association.
    33. Fries, Sébastien, 2018. "Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds," MPRA Paper 97353, University Library of Munich, Germany, revised Nov 2019.
    34. Christian Gourieroux & Joann Jasiak & Michelle Tong, 2021. "Convolution‐based filtering and forecasting: An application to WTI crude oil prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1230-1244, November.
    35. Alain Hecq & Joao Issler & Elisa Voisin, 2022. "A short term credibility index for central banks under inflation targeting: an application to Brazil," Papers 2205.00924, arXiv.org, revised Jul 2022.
    36. Gourieroux, Christian & Jasiak, Joann, 2018. "Misspecification of noncausal order in autoregressive processes," Journal of Econometrics, Elsevier, vol. 205(1), pages 226-248.
    37. Lof, Matthijs, 2013. "Essays on Expectations and the Econometrics of Asset Pricing," MPRA Paper 59064, University Library of Munich, Germany.
    38. Hecq, Alain & Issler, João Victor & Telg, Sean, 2017. "Mixed Causal-Noncausal Autoregressions with Strictly Exogenous Regressors," MPRA Paper 80767, University Library of Munich, Germany.
    39. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.

  12. Lanne, Markku & Saikkonen, Pentti, 2010. "Noncausal Vector Autoregression," MPRA Paper 23717, University Library of Munich, Germany.

    Cited by:

    1. Gianluca Cubadda & Alain Hecq & Elisa Voisin, 2023. "Detecting Common Bubbles in Multivariate Mixed Causal-noncausal Models," CEIS Research Paper 555, Tor Vergata University, CEIS, revised 27 Feb 2023.
    2. Saikkonen, Pentti & Sandberg, Rickard, 2013. "Testing for a unit root in noncausal autoregressive models," Bank of Finland Research Discussion Papers 26/2013, Bank of Finland.
    3. Moneta, Alessio & Pallante, Gianluca, 2022. "Identification of Structural VAR Models via Independent Component Analysis: A Performance Evaluation Study," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    4. Numan Ülkü & Kexing Wu, 2023. "Stock Market's Response to Real Output Shocks in China: A VARwAL Estimation," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 31(5), pages 1-25, September.
    5. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
    6. Frédérique Bec & Heino Bohn Nielsen & Sarra Saïdi, 2020. "Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1413-1428, December.
    7. Francesco Giancaterini & Alain Hecq, 2020. "Inference in mixed causal and noncausal models with generalized Student's t-distributions," Papers 2012.01888, arXiv.org, revised Nov 2022.
    8. Helmut Lütkepohl, 2012. "Fundamental Problems with Nonfundamental Shocks," Discussion Papers of DIW Berlin 1230, DIW Berlin, German Institute for Economic Research.
    9. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    10. Stefano Soccorsi, 2016. "Measuring Nonfundamentalness for Structural VARs," Working Papers ECARES ECARES 2016-01, ULB -- Universite Libre de Bruxelles.
    11. Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
    12. Alj, Abdelkamel & Jónasson, Kristján & Mélard, Guy, 2016. "The exact Gaussian likelihood estimation of time-dependent VARMA models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 633-644.
    13. Lof, Matthijs, 2011. "Noncausality and Asset Pricing," MPRA Paper 30519, University Library of Munich, Germany.
    14. Abhimanyu Gupta & Javier Hidalgo, 2022. "Nonparametric prediction with spatial data," STICERD - Econometrics Paper Series 621, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    15. Nelimarkka, Jaakko, 2017. "Evidence on News Shocks under Information Deficiency," MPRA Paper 80850, University Library of Munich, Germany.
    16. Sanjiwani Jayant KUMAR & Hitesh PUNJABI & Ashish MAHADIK, 2018. "Study of Relationship between Large-Cap Equity Funds Returns in India and Benchmark Returns," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 3, pages 47-56.
    17. Hidalgo, Javier & Seo, Myung Hwan, 2015. "Specification tests for lattice processes," LSE Research Online Documents on Economics 66104, London School of Economics and Political Science, LSE Library.
    18. Gianluca Cubadda & Francesco Giancaterini & Alain Hecq & Joann Jasiak, 2023. "Optimization of the Generalized Covariance Estimator in Noncausal Processes," Papers 2306.14653, arXiv.org, revised Jan 2024.
    19. Paul Beaudry & Franck Portier, 2014. "News Driven Business Cycles: Insights and Challenges," 2014 Meeting Papers 289, Society for Economic Dynamics.
    20. Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2020. "Proxy SVAR identification of monetary policy shocks: MonteCarlo evidence and insights for the US," University of Göttingen Working Papers in Economics 404, University of Goettingen, Department of Economics.
    21. Brendan K. Beare & Massimo Franchi & Phil Howlett, 2024. "The general solution to an autoregressive law of motion," Papers 2402.01966, arXiv.org.
    22. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    23. Nyberg, Henri & Saikkonen, Pentti, 2014. "Forecasting with a noncausal VAR model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 536-555.
    24. Lanne Markku, 2015. "Noncausality and inflation persistence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 469-481, September.
    25. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    26. Giurcanu, Mihai C., 2015. "A simulation algorithm for non-causal VARMA processes," Statistics & Probability Letters, Elsevier, vol. 98(C), pages 65-72.
    27. Chen, Rong & Xiao, Han & Yang, Dan, 2021. "Autoregressive models for matrix-valued time series," Journal of Econometrics, Elsevier, vol. 222(1), pages 539-560.
    28. Bernd Funovits, 2020. "The Dimension of the Set of Causal Solutions of Linear Multivariate Rational Expectations Models," Papers 2002.04369, arXiv.org.
    29. Alain Hecq & Joao Victor Issler & Sean Telg, 2020. "Mixed causal–noncausal autoregressions with exogenous regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 328-343, April.
    30. Davis, Richard A. & Song, Li, 2020. "Noncausal vector AR processes with application to economic time series," Journal of Econometrics, Elsevier, vol. 216(1), pages 246-267.
    31. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    32. Bernd Funovits, 2020. "Identifiability and Estimation of Possibly Non-Invertible SVARMA Models: A New Parametrisation," Papers 2002.04346, arXiv.org, revised Feb 2021.
    33. Lanne Markku & Saikkonen Pentti, 2011. "Noncausal Autoregressions for Economic Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-32, October.
    34. Anders Rygh Swensen, 2022. "On causal and non‐causal cointegrated vector autoregressive time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(2), pages 178-196, March.
    35. Demetrescu, Matei & Kruse, Robinson, 2015. "Testing heteroskedastic time series for normality," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113221, Verein für Socialpolitik / German Economic Association.
    36. Fries, Sébastien, 2018. "Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds," MPRA Paper 97353, University Library of Munich, Germany, revised Nov 2019.
    37. Gourieroux, Christian & Jasiak, Joann, 2017. "Noncausal vector autoregressive process: Representation, identification and semi-parametric estimation," Journal of Econometrics, Elsevier, vol. 200(1), pages 118-134.
    38. Hamidi Sahneh, Mehdi, 2017. "News, Noise, and Tests of Present Value Models," MPRA Paper 82715, University Library of Munich, Germany.
    39. Gourieroux, Christian & Jasiak, Joann, 2018. "Misspecification of noncausal order in autoregressive processes," Journal of Econometrics, Elsevier, vol. 205(1), pages 226-248.
    40. Ülkü, Numan & Kuruppuarachchi, Duminda & Kuzmicheva, Olga, 2017. "Stock market's response to real output shocks in Eastern European frontier markets: A VARwAL model," Emerging Markets Review, Elsevier, vol. 33(C), pages 140-154.
    41. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.
    42. Nelimarkka, Jaakko, 2017. "The effects of government spending under anticipation: the noncausal VAR approach," MPRA Paper 81303, University Library of Munich, Germany.
    43. Puonti, Päivi, 2016. "Fiscal multipliers in a structural VEC model with mixed normal errors," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 144-154.
    44. Christian Gouriéroux & Yang Lu, 2023. "Noncausal affine processes with applications to derivative pricing," Mathematical Finance, Wiley Blackwell, vol. 33(3), pages 766-796, July.

  13. Lanne, Markku & Luoto, Jani, 2010. "Has U.S. Inflation Really Become Harder to Forecast?," MPRA Paper 29992, University Library of Munich, Germany.

    Cited by:

    1. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
    2. Alain Hecq & Daniel Velasquez-Gaviria, 2022. "Spectral estimation for mixed causal-noncausal autoregressive models," Papers 2211.13830, arXiv.org.
    3. Bao Yong & Zhang Ru, 2013. "Estimation Bias and Feasible Conditional Forecasts from the First-Order Moving Average Model," Journal of Time Series Econometrics, De Gruyter, vol. 6(1), pages 63-80, July.
    4. Lanne Markku, 2015. "Noncausality and inflation persistence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 469-481, September.
    5. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.

  14. Lanne, Markku & Saikkonen, Pentti, 2010. "Noncausal autoregressions for economic time series," MPRA Paper 32943, University Library of Munich, Germany.

    Cited by:

    1. Francisco Blasques & Siem Jan Koopman & Gabriele Mingoli, 2023. "Observation-Driven filters for Time-Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics," Tinbergen Institute Discussion Papers 23-065/III, Tinbergen Institute.
    2. Hecq, A.W. & Lieb, L.M. & Telg, J.M.A., 2015. "Identification of Mixed Causal-Noncausal Models : How Fat Should We Go?," Research Memorandum 035, Maastricht University, Graduate School of Business and Economics (GSBE).
    3. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
    4. Matthijs Lof, 2014. "GMM Estimation with Non-causal Instruments under Rational Expectations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 279-286, April.
    5. Frédérique Bec & Heino Bohn Nielsen & Sarra Saïdi, 2020. "Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1413-1428, December.
    6. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers CWP21/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Francesco Giancaterini & Alain Hecq, 2020. "Inference in mixed causal and noncausal models with generalized Student's t-distributions," Papers 2012.01888, arXiv.org, revised Nov 2022.
    8. Stefano Soccorsi, 2016. "Measuring Nonfundamentalness for Structural VARs," Working Papers ECARES ECARES 2016-01, ULB -- Universite Libre de Bruxelles.
    9. Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
    10. Dimitrakopoulos, Stefanos, 2017. "Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility," Economics Letters, Elsevier, vol. 150(C), pages 10-14.
    11. Francesco Giancaterini & Alain Hecq & Claudio Morana, 2022. "Is climate change time reversible?," Working Paper series 22-08, Rimini Centre for Economic Analysis, revised Dec 2022.
    12. Lof, Matthijs, 2011. "Noncausality and Asset Pricing," MPRA Paper 30519, University Library of Munich, Germany.
    13. Lanne, Markku & Luoto, Jani, 2012. "Has US inflation really become harder to forecast?," Economics Letters, Elsevier, vol. 115(3), pages 383-386.
    14. Abhimanyu Gupta & Javier Hidalgo, 2022. "Nonparametric prediction with spatial data," STICERD - Econometrics Paper Series 621, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    15. Markku Lanne & Mika Meitz & Pentti Saikkonen, 2012. "Testing for Predictability in a Noninvertible ARMA Model," Koç University-TUSIAD Economic Research Forum Working Papers 1225, Koc University-TUSIAD Economic Research Forum.
    16. Strohsal, Till & Winkelmann, Lars, 2015. "Assessing the anchoring of inflation expectations," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 33-48.
    17. Cubadda, Gianluca & Hecq, Alain & Telg, Sean, 2017. "Detecting Co-Movements in Noncausal Time Series," MPRA Paper 77254, University Library of Munich, Germany, revised 02 Mar 2017.
    18. Lanne, Markku & Saikkonen, Pentti, 2009. "Noncausal vector autoregression," Bank of Finland Research Discussion Papers 18/2009, Bank of Finland.
    19. Hidalgo, Javier & Seo, Myung Hwan, 2015. "Specification tests for lattice processes," LSE Research Online Documents on Economics 66104, London School of Economics and Political Science, LSE Library.
    20. Alain Hecq & Daniel Velasquez-Gaviria, 2022. "Spectral estimation for mixed causal-noncausal autoregressive models," Papers 2211.13830, arXiv.org.
    21. Gianluca Cubadda & Francesco Giancaterini & Alain Hecq & Joann Jasiak, 2023. "Optimization of the Generalized Covariance Estimator in Noncausal Processes," Papers 2306.14653, arXiv.org, revised Jan 2024.
    22. Paul Beaudry & Franck Portier, 2014. "News Driven Business Cycles: Insights and Challenges," 2014 Meeting Papers 289, Society for Economic Dynamics.
    23. Christian Gourieroux & Andrew Hencic & Joann Jasiak, 2021. "Forecast performance and bubble analysis in noncausal MAR(1, 1) processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 301-326, March.
    24. Markku Lanne & Jani Luoto, 2019. "A comment on ‘on inflation expectations in the NKPC model’," Empirical Economics, Springer, vol. 57(6), pages 1865-1867, December.
    25. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.
    26. Frédérique Bec & Alain Guay, 2020. "A simple unit root test consistent against any stationary alternative," THEMA Working Papers 2020-10, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    27. Alain Hecq & Elisa Voisin, 2019. "Predicting crashes in oil prices during the COVID-19 pandemic with mixed causal-noncausal models," Papers 1911.10916, arXiv.org, revised May 2022.
    28. Mehdi Hamidi Sahneh, 2015. "Testing for Noncausal Vector Autoregressive Representation," Proceedings of Economics and Finance Conferences 2204921, International Institute of Social and Economic Sciences.
    29. Alain Hecq & Li Sun, 2019. "Identification of Noncausal Models by Quantile Autoregressions," Papers 1904.05952, arXiv.org.
    30. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    31. Alain Hecq & Daniel Velasquez-Gaviria, 2023. "Spectral identification and estimation of mixed causal-noncausal invertible-noninvertible models," Papers 2310.19543, arXiv.org.
    32. Nyberg, Henri & Saikkonen, Pentti, 2014. "Forecasting with a noncausal VAR model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 536-555.
    33. Alain Hecq & Sean Telg & Lenard Lieb, 2017. "Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?," Econometrics, MDPI, vol. 5(4), pages 1-22, October.
    34. Lanne Markku, 2015. "Noncausality and inflation persistence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 469-481, September.
    35. Xuanling Yang & Dong Li & Ting Zhang, 2024. "A simple stochastic nonlinear AR model with application to bubble," Papers 2401.07038, arXiv.org.
    36. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    37. Kramkov, Viacheslav & Maksimov, Andrey, 2020. "Loan market markups and noncausal autoregressions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 60, pages 48-69.
    38. Lanne, Markku & Nyberg, Henri & Saarinen, Erkka, 2011. "Forecasting U.S. Macroeconomic and Financial Time Series with Noncausal and Causal AR Models: A Comparison," MPRA Paper 30254, University Library of Munich, Germany.
    39. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    40. Marco M. Sorge, 2013. "On the Fundamentalness of Nonfundamentalness in DSGE Models," CSEF Working Papers 340, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    41. Javier Hidalgo & Myung Hwan Seo, 2013. "Specification For Lattice Processes," STICERD - Econometrics Paper Series 562, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    42. Henri Nyberg & Markku Lanne & Erkka Saarinen, 2012. "Does noncausality help in forecasting economic time series?," Economics Bulletin, AccessEcon, vol. 32(4), pages 2849-2859.
    43. Hecq, Alain & Voisin, Elisa, 2021. "Forecasting bubbles with mixed causal-noncausal autoregressive models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 29-45.
    44. Meitz, Mika & Saikkonen, Pentti, 2013. "Maximum likelihood estimation of a noninvertible ARMA model with autoregressive conditional heteroskedasticity," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 227-255.
    45. Alain Hecq & Joao Victor Issler & Sean Telg, 2020. "Mixed causal–noncausal autoregressions with exogenous regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 328-343, April.
    46. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    47. Ricco, Giovanni & Ellahie, Atif, 2012. "Government Spending Reloaded: Fundamentalness and Heterogeneity in Fiscal SVARs," MPRA Paper 42105, University Library of Munich, Germany.
    48. Demetrescu, Matei & Kruse, Robinson, 2015. "Testing heteroskedastic time series for normality," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113221, Verein für Socialpolitik / German Economic Association.
    49. Kindop, Igor, 2021. "Ubiquitous multimodality in mixed causal-noncausal processes," MPRA Paper 109594, University Library of Munich, Germany, revised 04 Sep 2021.
    50. Christian Gourieroux & Joann Jasiak & Michelle Tong, 2021. "Convolution‐based filtering and forecasting: An application to WTI crude oil prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1230-1244, November.
    51. Gourieroux, Christian & Jasiak, Joann, 2017. "Noncausal vector autoregressive process: Representation, identification and semi-parametric estimation," Journal of Econometrics, Elsevier, vol. 200(1), pages 118-134.
    52. Fei Ma & Fei Liu & Qipeng Sun & Wenlin Wang & Xiaodan Li, 2018. "Measuring and Spatio-Temporal Evolution for the Late-Development Advantage in China’s Provinces," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
    53. Alain Hecq & Joao Issler & Elisa Voisin, 2022. "A short term credibility index for central banks under inflation targeting: an application to Brazil," Papers 2205.00924, arXiv.org, revised Jul 2022.
    54. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.
    55. Hecq, Alain & Issler, João Victor & Telg, Sean, 2017. "Mixed Causal-Noncausal Autoregressions with Strictly Exogenous Regressors," MPRA Paper 80767, University Library of Munich, Germany.
    56. Brandes, Dirk-Philip & Lindner, Alexander, 2014. "Non-causal strictly stationary solutions of random recurrence equations," Statistics & Probability Letters, Elsevier, vol. 94(C), pages 113-118.
    57. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers 21/13, Institute for Fiscal Studies.
    58. Frederique Bec & Alain Guay, 2020. "A Simple Unit Root Test Consistent Against Any Stationary Alternative," Working Papers 20-20, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.

  15. Laakkonen, Helinä & Lanne, Markku, 2009. "The Relevance of Accuracy for the Impact of Macroeconomic News on Volatility," MPRA Paper 23718, University Library of Munich, Germany.

    Cited by:

    1. Christopher J. Neely, 2011. "A survey of announcement effects on foreign exchange volatility and jumps," Review, Federal Reserve Bank of St. Louis, vol. 93(Sep), pages 361-385.

  16. Lanne, Markku & Saikkonen, Pentti, 2009. "GMM Estimation with Noncausal Instruments," MPRA Paper 23649, University Library of Munich, Germany.

    Cited by:

    1. Matthijs Lof, 2014. "GMM Estimation with Non-causal Instruments under Rational Expectations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 279-286, April.
    2. Al-Faryan, Mamdouh Abdulaziz Saleh, 2021. "The Effect of Board Composition and Managerial Pay on Saudi Firm Performance," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Online fi.
    3. Lof, Matthijs, 2011. "Noncausality and Asset Pricing," MPRA Paper 30519, University Library of Munich, Germany.
    4. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.
    5. Lanne, Markku & Nyberg, Henri & Saarinen, Erkka, 2011. "Forecasting U.S. Macroeconomic and Financial Time Series with Noncausal and Causal AR Models: A Comparison," MPRA Paper 30254, University Library of Munich, Germany.
    6. Hecq Alain & Sun Li, 2021. "Selecting between causal and noncausal models with quantile autoregressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(5), pages 393-416, December.

  17. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2009. "Bayesian Model Selection and Forecasting in Noncausal Autoregressive Models," MPRA Paper 23646, University Library of Munich, Germany.

    Cited by:

    1. Saikkonen, Pentti & Sandberg, Rickard, 2013. "Testing for a unit root in noncausal autoregressive models," Bank of Finland Research Discussion Papers 26/2013, Bank of Finland.
    2. Frédérique Bec & Heino Bohn Nielsen & Sarra Saïdi, 2020. "Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1413-1428, December.
    3. Joshua C.C. Chan & Angelia L. Grant, 2015. "Pitfalls of Estimating the Marginal Likelihood Using the Modified Harmonic Mean," CAMA Working Papers 2015-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
    5. Lof, Matthijs, 2011. "Noncausality and Asset Pricing," MPRA Paper 30519, University Library of Munich, Germany.
    6. Lanne, Markku & Luoto, Jani, 2012. "Has US inflation really become harder to forecast?," Economics Letters, Elsevier, vol. 115(3), pages 383-386.
    7. Frédérique Bec & Alain Guay & Heino Bohn Nielsen & Sarra Saïdi, 2022. "Power of unit root tests against nonlinear and noncausal alternatives," THEMA Working Papers 2022-14, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    8. Christian Gourieroux & Andrew Hencic & Joann Jasiak, 2021. "Forecast performance and bubble analysis in noncausal MAR(1, 1) processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 301-326, March.
    9. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.
    10. Nyberg, Henri & Saikkonen, Pentti, 2014. "Forecasting with a noncausal VAR model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 536-555.
    11. Lanne Markku, 2015. "Noncausality and inflation persistence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 469-481, September.
    12. Lanne, Markku & Nyberg, Henri & Saarinen, Erkka, 2011. "Forecasting U.S. Macroeconomic and Financial Time Series with Noncausal and Causal AR Models: A Comparison," MPRA Paper 30254, University Library of Munich, Germany.
    13. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    14. Henri Nyberg & Markku Lanne & Erkka Saarinen, 2012. "Does noncausality help in forecasting economic time series?," Economics Bulletin, AccessEcon, vol. 32(4), pages 2849-2859.
    15. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    16. Christian Gourieroux & Joann Jasiak & Michelle Tong, 2021. "Convolution‐based filtering and forecasting: An application to WTI crude oil prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1230-1244, November.
    17. Jean-Baptiste MICHAU, 2019. "Helicopter Drops of Money under Secular Stagnation," Working Papers 2019-10, Center for Research in Economics and Statistics.
    18. Lof, Matthijs, 2013. "Essays on Expectations and the Econometrics of Asset Pricing," MPRA Paper 59064, University Library of Munich, Germany.

  18. Markku Lanne & Helmut Luetkepohl & Katarzyna Maciejowska, 2009. "Structural Vector Autoregressions with Markov Switching," Economics Working Papers ECO2009/06, European University Institute.

    Cited by:

    1. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    2. Jan Philipp Fritsche & Mathias Klein & Malte Rieth, 2020. "Government Spending Multipliers in (Un)certain Times," Discussion Papers of DIW Berlin 1901, DIW Berlin, German Institute for Economic Research.
    3. Helmut Herwartz & Martin Plödt, 2016. "Simulation Evidence on Theory-based and Statistical Identification under Volatility Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 94-112, February.
    4. Sun, Hang & Bos, Jaap W.B. & Li, Zhuo, 2017. "In the Nick of Time: A Heteroskedastic SVAR Model and Its Application to the Crude Oil Futures Market," Research Memorandum 019, Maastricht University, Graduate School of Business and Economics (GSBE).
    5. Anton Velinov, 2013. "Can Stock Price Fundamentals Properly be Captured?: Using Markov Switching in Heteroskedasticity Models to Test Identification Schemes," Discussion Papers of DIW Berlin 1350, DIW Berlin, German Institute for Economic Research.
    6. Helmut Lütkepohl & Thore Schlaak, 2017. "Choosing between Different Time-Varying Volatility Models for Structural Vector Autoregressive Analysis," Discussion Papers of DIW Berlin 1672, DIW Berlin, German Institute for Economic Research.
    7. Pérez-Quirós, Gabriel & Camacho, Máximo, 2013. "Commodity prices and the business cycle in Latin America: Living and dying by commodities?," CEPR Discussion Papers 9367, C.E.P.R. Discussion Papers.
    8. Moneta, Alessio & Pallante, Gianluca, 2022. "Identification of Structural VAR Models via Independent Component Analysis: A Performance Evaluation Study," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    9. Jordi Brandts & Sabrine El Baroudi & Stefanie Huber & Christina Rott, 2022. "Gender Differences in Private and Public Goal Setting," Tinbergen Institute Discussion Papers 22-008/II, Tinbergen Institute.
    10. Boris Blagov & Michael Funke & Richhild Moessner, 2015. "Modelling the time-variation in euro area lending spreads," BIS Working Papers 526, Bank for International Settlements.
    11. Kohonen, Anssi, 2012. "On detection of volatility spillovers in simultaneously open stock markets," MPRA Paper 37504, University Library of Munich, Germany.
    12. Herwartz, Helmut & Lange, Alexander & Maxand, Simone, 2019. "Statistical identification in SVARs - Monte Carlo experiments and a comparative assessment of the role of economic uncertainties for the US business cycle," University of Göttingen Working Papers in Economics 375, University of Goettingen, Department of Economics.
    13. Haroon Mumtaz & Gabor Pinter & Konstantinos Theodoridis, 2018. "What Do Vars Tell Us About The Impact Of A Credit Supply Shock?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(2), pages 625-646, May.
    14. Guido Turnip, 2017. "Identification of Small Open Economy SVARs via Markov-Switching Heteroskedasticity," The Economic Record, The Economic Society of Australia, vol. 93(302), pages 465-483, September.
    15. Guérin, Pierre & Maurin, Laurent & Mohr, Matthias, 2015. "Trend-Cycle Decomposition Of Output And Euro Area Inflation Forecasts: A Real-Time Approach Based On Model Combination," Macroeconomic Dynamics, Cambridge University Press, vol. 19(2), pages 363-393, March.
    16. Guay, Alain, 2021. "Identification of structural vector autoregressions through higher unconditional moments," Journal of Econometrics, Elsevier, vol. 225(1), pages 27-46.
    17. Netsunajev, Aleksei, 2013. "Reaction to technology shocks in Markov-switching structural VARs: Identification via heteroskedasticity," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 51-62.
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  19. Markku Lanne & Helmut Luetkepohl, 2008. "A Statistical Comparison of Alternative Identification Schemes for Monetary Policy Shocks," Economics Working Papers ECO2008/23, European University Institute.

    Cited by:

    1. Greg Hannsgen, 2010. "Infinite-variance, Alpha-stable Shocks in Monetary SVAR," Economics Working Paper Archive wp_596, Levy Economics Institute.
    2. Helmut Lütkepohl & Anton Velinov, 2014. "Structural Vector Autoregressions: Checking Identifying Long-run Restrictions via Heteroskedasticity," CESifo Working Paper Series 4651, CESifo.
    3. Baldi, Guido & Lange, Alexander, 2019. "The Interest Rate Sensitivity of Investment," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 52(2), pages 173-190.

  20. Markku Lanne & Pentti Saikkonen, 2008. "Modeling Expectations with Noncausal Autoregressions," Economics Working Papers ECO2008/20, European University Institute.

    Cited by:

    1. Karapanagiotidis, Paul, 2013. "Empirical evidence for nonlinearity and irreversibility of commodity futures prices," MPRA Paper 56801, University Library of Munich, Germany.
    2. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
    3. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2009. "Bayesian Model Selection and Forecasting in Noncausal Autoregressive Models," MPRA Paper 23646, University Library of Munich, Germany.
    4. Francesco Giancaterini & Alain Hecq, 2020. "Inference in mixed causal and noncausal models with generalized Student's t-distributions," Papers 2012.01888, arXiv.org, revised Nov 2022.
    5. Markku Lanne & Pentti Saikkonen, 2011. "GMM Estimation with Non‐causal Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 581-592, October.
    6. Lanne, Markku & Luoto, Jani, 2012. "Has US inflation really become harder to forecast?," Economics Letters, Elsevier, vol. 115(3), pages 383-386.
    7. Lanne, Markku & Saikkonen, Pentti, 2009. "Noncausal vector autoregression," Bank of Finland Research Discussion Papers 18/2009, Bank of Finland.
    8. Davis, Richard A. & Song, Li, 2020. "Noncausal vector AR processes with application to economic time series," Journal of Econometrics, Elsevier, vol. 216(1), pages 246-267.
    9. Karapanagiotidis, Paul, 2014. "Dynamic modeling of commodity futures prices," MPRA Paper 56805, University Library of Munich, Germany.

  21. Laakkonen, Helinä & Lanne, Markku, 2008. "Asymmetric News Effects on Volatility: Good vs. Bad News in Good vs. Bad Times," MPRA Paper 8296, University Library of Munich, Germany.

    Cited by:

    1. Sirimon Treepongkaruna & Robert Brooks & Stephen Gray, 2012. "Do trading hours affect volatility links in the foreign exchange market?," Australian Journal of Management, Australian School of Business, vol. 37(1), pages 7-27, April.
    2. Walid Ben Omrane & Robert Welch & Xinyao Zhou, 2020. "The dynamic effect of macroeconomic news on the euro/US dollar exchange rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 84-103, January.
    3. Li, Hong & Shi, Yanlin, 2021. "A new unique information share measure with applications on cross-listed Chinese banks," Journal of Banking & Finance, Elsevier, vol. 128(C).
    4. Laivi Laidroo & Zana Grigaliuniene, 2012. "Testing for asymmetries in price reactions to quarterly earnings announcements on Tallinn, Riga and Vilnius Stock Exchanges during 2000-2009," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 12(1), pages 61-86, July.
    5. Vortelinos, Dimitrios I. & Koulakiotis, Athanasios & Tsagkanos, Athanasios, 2017. "Intraday analysis of macroeconomic news surprises and asymmetries in mini-futures markets," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 150-168.
    6. Chou, Ke-Hsin & Day, Min-Yuh & Chiu, Chien-Liang, 2023. "Do bitcoin news information flow and return volatility fit the sequential information arrival hypothesis and the mixture of distribution hypothesis?," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 365-385.
    7. Ben Omrane, Walid & Tao, Yusi & Welch, Robert, 2017. "Scheduled macro-news effects on a Euro/US dollar limit order book around the 2008 financial crisis," Research in International Business and Finance, Elsevier, vol. 42(C), pages 9-30.
    8. Bartsch, Zachary, 2019. "Economic policy uncertainty and dollar-pound exchange rate return volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    9. Shi, Yanlin & Ho, Kin-Yip & Liu, Wai-Man, 2016. "Public information arrival and stock return volatility: Evidence from news sentiment and Markov Regime-Switching Approach," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 291-312.
    10. Dmitrij Celov & Žana Grigaliuniene, 2010. "Economic Forces, Sentiment and Emerging Eastern European Stock Markets," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 2(2).
    11. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2020. "News and return volatility of Chinese bank stocks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 1095-1105.
    12. Christophe Blot & Paul Hubert & Fabien Labondance, 2020. "The asymmetric effects of monetary policy on stock price bubbles," Documents de Travail de l'OFCE 2020-12, Observatoire Francais des Conjonctures Economiques (OFCE).
    13. Nusair, Salah A. & Al-Khasawneh, Jamal A., 2022. "Impact of economic policy uncertainty on the stock markets of the G7 Countries:A nonlinear ARDL approach," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    14. Weber, Christoph S., 2019. "The effect of central bank transparency on exchange rate volatility," Journal of International Money and Finance, Elsevier, vol. 95(C), pages 165-181.
    15. Ben Omrane, Walid & Savaşer, Tanseli, 2017. "Exchange rate volatility response to macroeconomic news during the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 130-143.
    16. Salah A. Nusair & Jamal A. Al-Khasawneh, 2022. "On the relationship between Asian exchange rates and stock prices: a nonlinear analysis," Economic Change and Restructuring, Springer, vol. 55(1), pages 361-400, February.
    17. Diamantis Petropoulos Petalas & Hein van Schie & Paul Hendriks Vettehen, 2017. "Forecasted economic change and the self-fulfilling prophecy in economic decision-making," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-18, March.
    18. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
    19. Shi, Yanlin & Liu, Wai-Man & Ho, Kin-Yip, 2016. "Public news arrival and the idiosyncratic volatility puzzle," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 159-172.

  22. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2008. "A Naïve Sticky Information Model of Households’ Inflation Expectations," MPRA Paper 8663, University Library of Munich, Germany.

    Cited by:

    1. Pfajfar, D. & Santoro, E., 2012. "News on Inflation and the Epidemiology of Inflation Expectations," Other publications TiSEM 515ee09e-b946-439f-afff-d, Tilburg University, School of Economics and Management.
    2. Camille Cornand & Cheick Kader M'Baye, 2016. "Band or Point Inflation Targeting? An Experimental Approach," Working Papers halshs-01313095, HAL.
    3. Carrera, César, 2012. "Estimating Information Rigidity using Firms’ Survey Data," Working Papers 2012-004, Banco Central de Reserva del Perú.
    4. Cornand, Camille & Hubert, Paul, 2020. "On the external validity of experimental inflation forecasts: A comparison with five categories of field expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    5. Olivier Armantier & Scott Nelson & Giorgio Topa & Wilbert van der Klaauw & Basit Zafar, 2016. "The Price Is Right: Updating Inflation Expectations in a Randomized Price Information Experiment," The Review of Economics and Statistics, MIT Press, vol. 98(3), pages 503-523, July.
    6. Paul Hubert, 2014. "FOMC Forecasts as a Focal Point for Private Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(7), pages 1381-1420, October.
    7. Yingying XU & Zhixin LIU & Jaime ORTIZ, 2018. "Actual and Expected Inflation in the U.S.: A Time-Frequency View," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 42-62, December.
    8. Camille Cornand & Paul Hubert, 2020. "On the external validity of experimental inflation forecasts," SciencePo Working papers Main hal-02894262, HAL.
    9. Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco, 2019. "Beliefs formation and the puzzle of forward guidance power," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 20-32.
    10. Marine Charlotte André & Meixing Dai, 2017. "Learning, optimal monetary delegation and stock prices dynamics," Working Papers of BETA 2017-37, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    11. Camille Cornand & Paul Hubert, 2019. "On the external validity of experimental inflation forecasts: A comparison with five categories of field expectations: A comparison with five categories of field expectations," Sciences Po publications 03, Sciences Po.
    12. Xu, Yingying & Chang, Hsu-Ling & Lobonţ, Oana-Ramona & Su, Chi-Wei, 2016. "Modeling heterogeneous inflation expectations: empirical evidence from demographic data?," Economic Modelling, Elsevier, vol. 57(C), pages 153-163.
    13. Guzman, Giselle C., 2011. "The case for higher frequency inflation expectations," MPRA Paper 36656, University Library of Munich, Germany.
    14. Mitja Steinbacher & Matthias Raddant & Fariba Karimi & Eva Camacho Cuena & Simone Alfarano & Giulia Iori & Thomas Lux, 2021. "Advances in the agent-based modeling of economic and social behavior," SN Business & Economics, Springer, vol. 1(7), pages 1-24, July.
    15. OKIMOTO Tatsuyoshi, 2018. "Trend Inflation and Monetary Policy Regimes in Japan," Discussion papers 18024, Research Institute of Economy, Trade and Industry (RIETI).
    16. Easaw Joshy & Golinelli Roberto, 2010. "Households Forming Inflation Expectations: Active and Passive Absorption Rates," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, November.
    17. J. Easaw & R. Golinelli & M. Malgarini, 2012. "Do Households Anchor their Inflation Expectations? Theory and Evidence from a Household Survey," Working Papers wp842, Dipartimento Scienze Economiche, Universita' di Bologna.
    18. Charles Bellemare & Rolande Kpekou Tossou & Kevin Moran, 2020. "The Determinants of Consumers' Inflation Expectations: Evidence from the US and Canada," Staff Working Papers 20-52, Bank of Canada.
    19. Paul Hubert & Harun Mirza, 2019. "The role of forward- and backward-looking information for inflation expectations formation," Post-Print hal-03403616, HAL.
    20. Easaw, Joshy & Golinelli, Roberto & Malgarini, Marco, 2013. "What determines households inflation expectations? Theory and evidence from a household survey," European Economic Review, Elsevier, vol. 61(C), pages 1-13.
    21. Yingying Xu & Zhixin Liu & Xing Zhang, 2017. "Heterogeneous Or Homogeneous Inflation Expectation Formation Models: A Case Study Of Chinese Households And Financial Participants," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 62(04), pages 859-874, September.
    22. Guzman, Giselle C., 2010. "An inflation expectations horserace," MPRA Paper 36511, University Library of Munich, Germany.
    23. Easaw, Joshy, 2015. "Household Forming Inflation Expectations: Why Do They Overreact ?," Cardiff Economics Working Papers E2015/14, Cardiff University, Cardiff Business School, Economics Section.
    24. Li, You & Tay, Anthony, 2021. "The role of macroeconomic and policy uncertainty in density forecast dispersion," Journal of Macroeconomics, Elsevier, vol. 67(C).
    25. Yingying Xu & Zhi-Xin Liu & Hsu-Ling Chang & Adelina Dumitrescu Peculea & Chi-Wei Su, 2017. "Does self-fulfilment of the inflation expectation exist?," Applied Economics, Taylor & Francis Journals, vol. 49(11), pages 1098-1113, March.

  23. Markku Lanne & Helmut Lütkepohl, 2008. "Stock Prices and Economic Fluctuations: A Markov Switching Structural Vector Autoregressive Analysis," CESifo Working Paper Series 2407, CESifo.

    Cited by:

    1. Adel Bosch & Franz Ruch, 2012. "An Alternative Business Cycle Dating Procedure for South Africa," Working Papers 5210, South African Reserve Bank.
    2. Paul Beaudry & Franck Portier, 2014. "News Driven Business Cycles: Insights and Challenges," 2014 Meeting Papers 289, Society for Economic Dynamics.
    3. YANG, Yukai, 2014. "Testing constancy of the error covariance matrix in vector models against parametric alternatives using a spectral decomposition," LIDAM Discussion Papers CORE 2014017, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  24. Ahoniemi, Katja & Lanne, Markku, 2007. "Joint Modeling of Call and Put Implied Volatility," MPRA Paper 6318, University Library of Munich, Germany.

    Cited by:

    1. Lockwood, Jimmy & Lockwood, Larry & Miao, Hong & Ramchander, Sanjay & Yang, Dongxiao, 2022. "The information content of ETF options," Global Finance Journal, Elsevier, vol. 53(C).
    2. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2013. "Semiparametric Vector Mem," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1067-1086, November.
    3. Cipollini, Fabrizio & Gallo, Giampiero M., 2010. "Automated variable selection in vector multiplicative error models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2470-2486, November.
    4. Panayiotis Andreou & Chris Charalambous & Spiros Martzoukos, 2014. "Assessing the performance of symmetric and asymmetric implied volatility functions," Review of Quantitative Finance and Accounting, Springer, vol. 42(3), pages 373-397, April.
    5. Ng, F.C. & Li, W.K. & Yu, Philip L.H., 2016. "Diagnostic checking of the vector multiplicative error model," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 86-97.
    6. Yanhui Chen & Kin Lai & Jiangze Du, 2014. "Modeling and forecasting Hang Seng index volatility with day-of-week effect, spillover effect based on ARIMA and HAR," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 4(2), pages 113-132, December.
    7. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    8. Lanne, Markku & Ahoniemi, Katja, 2008. "Implied Volatility with Time-Varying Regime Probabilities," MPRA Paper 23721, University Library of Munich, Germany.

  25. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.

    Cited by:

    1. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
    2. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
    3. Mohanty, Roshni & P, Srinivasan, 2014. "The Time-Varying Risk and Return Trade Off in Indian Stock Markets," MPRA Paper 55660, University Library of Munich, Germany.
    4. Michelfelder, Richard A., 2015. "Empirical analysis of the generalized consumption asset pricing model: Estimating the cost of capital," Journal of Economics and Business, Elsevier, vol. 80(C), pages 37-50.
    5. Arshanapalli, Bala & Fabozzi, Frank J. & Nelson, William, 2013. "The role of jump dynamics in the risk–return relationship," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 212-218.
    6. Richard A. Michelfelder, 2014. "Asset characteristics of solar renewable energy certificates: market solution to encourage environmental sustainability," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 4(3), pages 280-296, July.
    7. Jiranyakul, Komain, 2011. "On the Risk-Return Tradeoff in the Stock Exchange of Thailand: New Evidence," MPRA Paper 45583, University Library of Munich, Germany.
    8. Pauline Ahern & Frank Hanley & Richard Michelfelder, 2011. "New approach to estimating the cost of common equity capital for public utilities," Journal of Regulatory Economics, Springer, vol. 40(3), pages 261-278, December.

  26. Markku Lanne & Helmut Lütkepohl, 2006. "Identifying Monetary Policy Shocks via Changes in Volatility," CESifo Working Paper Series 1744, CESifo.

    Cited by:

    1. Markku Lanne & Helmut Luetkepohl, 2008. "A Statistical Comparison of Alternative Identification Schemes for Monetary Policy Shocks," Economics Working Papers ECO2008/23, European University Institute.
    2. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    3. Lütkepohl, Helmut & Schlaak, Thore, 2019. "Bootstrapping impulse responses of structural vector autoregressive models identified through GARCH," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 41-61.
    4. Massimo Guidolin & Manuela Pedio, 2019. "Does the Cost of Private Debt Respond to Monetary Policy? Heteroskedasticity-Based Identification in a Model with Regimes," BAFFI CAREFIN Working Papers 19118, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    5. Helmut Herwartz & Martin Plödt, 2016. "Simulation Evidence on Theory-based and Statistical Identification under Volatility Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 94-112, February.
    6. Sun, Hang & Bos, Jaap W.B. & Li, Zhuo, 2017. "In the Nick of Time: A Heteroskedastic SVAR Model and Its Application to the Crude Oil Futures Market," Research Memorandum 019, Maastricht University, Graduate School of Business and Economics (GSBE).
    7. Helmut Lütkepohl & Thore Schlaak, 2017. "Choosing between Different Time-Varying Volatility Models for Structural Vector Autoregressive Analysis," Discussion Papers of DIW Berlin 1672, DIW Berlin, German Institute for Economic Research.
    8. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel Vector Autoregressive Models: A Survey," CEPR Discussion Papers 9380, C.E.P.R. Discussion Papers.
    9. Fratzscher, Marcel & Rieth, Malte, 2015. "Monetary policy, bank bailouts and the sovereign-bank risk nexus in the euro area," CEPR Discussion Papers 10370, C.E.P.R. Discussion Papers.
    10. Markku Lanne, Helmut Luetkepohl, 2006. "Identifying Monetary Policy Shocks via Changes in Volatility," Economics Working Papers ECO2006/23, European University Institute.
    11. Herwartz, Helmut & Lange, Alexander & Maxand, Simone, 2019. "Statistical identification in SVARs - Monte Carlo experiments and a comparative assessment of the role of economic uncertainties for the US business cycle," University of Göttingen Working Papers in Economics 375, University of Goettingen, Department of Economics.
    12. Helmut Lütkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo.
    13. Halvorsen, Jørn I. & Jacobsen, Dag Henning, 2016. "The bank-lending channel empirically revisited," Journal of Financial Stability, Elsevier, vol. 27(C), pages 95-105.
    14. Guido Turnip, 2017. "Identification of Small Open Economy SVARs via Markov-Switching Heteroskedasticity," The Economic Record, The Economic Society of Australia, vol. 93(302), pages 465-483, September.
    15. Lütkepohl, Helmut & Milunovich, George & Yang, Minxian, 2020. "Inference in partially identified heteroskedastic simultaneous equations models," Journal of Econometrics, Elsevier, vol. 218(2), pages 317-345.
    16. Netsunajev, Aleksei, 2013. "Reaction to technology shocks in Markov-switching structural VARs: Identification via heteroskedasticity," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 51-62.
    17. Heike Schenkelberg & Sebastian Watzka, 2011. "Real Effects of Quantitative Easing at the Zero-Lower Bound: Structural VAR-based Evidence from Japan," CESifo Working Paper Series 3486, CESifo.
    18. Erdenebat Bataa & Denise R.Osborn & Marianne Sensier, 2016. "China's Increasing Global Influence: Changes in International Growth Spillovers," Centre for Growth and Business Cycle Research Discussion Paper Series 221, Economics, The University of Manchester.
    19. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    20. Nave, Juan M. & Ruiz, Javier, 2015. "Risk aversion and monetary policy in a global context," Journal of Financial Stability, Elsevier, vol. 20(C), pages 14-35.
    21. Elien Meuleman & Rudi Vander Vennet, 2022. "Macroprudential Policy, Monetary Policy, and Euro Zone Bank Risk," International Journal of Central Banking, International Journal of Central Banking, vol. 18(4), pages 1-52, October.
    22. Jolanta Tamošaitienė & Vahidreza Yousefi & Hamed Tabasi, 2021. "Project Portfolio Construction Using Extreme Value Theory," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    23. Greg Hannsgen, 2011. "Infinite-variance, Alpha-stable Shocks in Monetary SVAR: Final Working Paper Version," Economics Working Paper Archive wp_682, Levy Economics Institute.
    24. Arampatzidis, Ioannis & Dergiades, Theologos & Kaufmann, Robert K. & Panagiotidis, Theodore, 2021. "Oil and the U.S. stock market: Implications for low carbon policies," Energy Economics, Elsevier, vol. 103(C).
    25. Thore Schlaak & Malte Rieth & Maximilian Podstawski, 2023. "Monetary policy, external instruments, and heteroskedasticity," Quantitative Economics, Econometric Society, vol. 14(1), pages 161-200, January.
    26. Alexander Kriwoluzky, 2009. "Matching Theory and Data: Bayesian Vector Autoregression and Dynamic Stochastic General Equilibrium Models," Economics Working Papers ECO2009/29, European University Institute.
    27. Wenjuan Chen & Aleksei Netsunajev, 2015. "On the Long-run Neutrality of Demand Shocks," SFB 649 Discussion Papers SFB649DP2015-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    28. Helmut Lütkepohl & Anton Velinov, 2014. "Structural Vector Autoregressions: Checking Identifying Long-run Restrictions via Heteroskedasticity," CESifo Working Paper Series 4651, CESifo.
    29. Kaelo Mpho Ntwaepelo, 2021. "The Effects of Macroprudential and Monetary Policy Shocks in BRICS economies," Economics Discussion Papers em-dp2021-20, Department of Economics, University of Reading.
    30. Helmut Lütkepohl & Aleksei Netšunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticy," SFB 649 Discussion Papers SFB649DP2015-015, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    31. Martien Lamers & Frederik Mergaerts & Elien Meuleman & Rudi Vander Vennet, 2016. "The trade-off between monetary policy and bank stability," Working Paper Research 308, National Bank of Belgium.
    32. Kilian, Lutz, 2011. "Structural Vector Autoregressions," CEPR Discussion Papers 8515, C.E.P.R. Discussion Papers.
    33. Helmut Lütkepohl & Aleksei Netsunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticity: A Comparison of Different Volatility Models," Discussion Papers of DIW Berlin 1464, DIW Berlin, German Institute for Economic Research.
    34. Markku Lanne & Helmut Luetkepohl & Katarzyna Maciejowska, 2009. "Structural Vector Autoregressions with Markov Switching," Economics Working Papers ECO2009/06, European University Institute.
    35. Dmitry Kulikov & Aleksei Netsunajev, 2013. "Identifying monetary policy shocks via heteroskedasticity: a Bayesian approach," Bank of Estonia Working Papers wp2013-9, Bank of Estonia, revised 09 Dec 2013.
    36. Herwartz, Helmut & Roestel, Jan, 2022. "Asset prices, financial amplification and monetary policy: Structural evidence from an identified multivariate GARCH model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    37. Emanuele BACCHIOCCHI & Riccardo Jack LUCCHETTI, 2015. "Structure-Based SVAR Identification," Departmental Working Papers 2015-11, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    38. Helmut Herwartz & Alexander Lange, 2024. "How certain are we about the role of uncertainty in the economy?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 126-149, January.
    39. Forti Grazzini, Caterina & Rieth, Malte, 2017. "Interest Rates and Exchange Rates in Normal and Crisis Times," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168281, Verein für Socialpolitik / German Economic Association.
    40. Nicolas Soenen & Rudi Vander Vennet, 2020. "ECB Monetary Policy and Bank Default Risk," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 20/997, Ghent University, Faculty of Economics and Business Administration.
    41. Ulrichs Magdalena, 2018. "Identification of Financial and Macroeconomic Shocks in a Var Model of the Polish Economy. A Stability Analysis," Economics and Business Review, Sciendo, vol. 4(1), pages 29-43, April.
    42. Karamysheva, Madina & Skrobotov, Anton, 2022. "Do we reject restrictions identifying fiscal shocks? identification based on non-Gaussian innovations," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    43. Fabio Canova & Fernando J. Pérez Forero, 2012. "Estimating Overidentified, Nonrecursive Time-Varying Coefficients Structural VARs," Working Papers 637, Barcelona School of Economics.
    44. Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2020. "Proxy SVAR identification of monetary policy shocks: MonteCarlo evidence and insights for the US," University of Göttingen Working Papers in Economics 404, University of Goettingen, Department of Economics.
    45. Hattori, Masazumi & Shim, Ilhyock & Sugihara, Yoshihiko, 2021. "Cross-stock market spillovers through variance risk premiums and equity flows," Journal of International Money and Finance, Elsevier, vol. 119(C).
    46. Tom Beernaert & Nicolas Soenen & Rudi Vander Vennet, 2023. "ECB Monetary Policy and the Term Structure of Bank Default Risk," JRFM, MDPI, vol. 16(12), pages 1-22, December.
    47. Helmut Lütkepohl & Aleksei NetŠunajev, 2014. "Disentangling Demand And Supply Shocks In The Crude Oil Market: How To Check Sign Restrictions In Structural Vars," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 479-496, April.
    48. YAMAMOTO, Yohei & 山本, 庸平, 2018. "Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances," Discussion paper series HIAS-E-72, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    49. Gerti Shijaku, 2015. "The Macroeconomic Pass-through Effects of Monetary Policy through Sign Restrictions Approach: In the Case of Albania," IHEID Working Papers 11-2015, Economics Section, The Graduate Institute of International Studies.
    50. Pierre Perron & Yohei Yamamoto, 2022. "The great moderation: updated evidence with joint tests for multiple structural changes in variance and persistence," Empirical Economics, Springer, vol. 62(3), pages 1193-1218, March.
    51. Miguel Fernandes & João S. Andrade & Adelaide Duarte & Marta Simões, 2022. "Inequality and growth in Portugal: A reappraisal for the period 1986–2017," Poverty & Public Policy, John Wiley & Sons, vol. 14(1), pages 25-49, March.
    52. Katarzyna Maciejowska, 2010. "Estimation Methods Comparison of SVAR Models with a Mixture of Two Normal Distributions," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 2(4), pages 279-314, September.
    53. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2016. "Measuring Uncertainty and Its Impact on the Economy," Working Papers (Old Series) 1622, Federal Reserve Bank of Cleveland.
    54. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
    55. Emanuele BACCHIOCCHI, 2011. "Identification in structural VAR models with different volatility regimes," Departmental Working Papers 2011-39, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    56. Christoph Große Steffen & Maximilian Podstawski, 2016. "Ambiguity and Time-Varying Risk Aversion in Sovereign Debt Markets," Discussion Papers of DIW Berlin 1602, DIW Berlin, German Institute for Economic Research.
    57. Herwartz, Helmut, 2014. "Structural analysis with independent innovations," University of Göttingen Working Papers in Economics 208, University of Goettingen, Department of Economics.
    58. Hafedh Bouakez & Badye Omar Essid & Michel Normandin, 2010. "Stock Returns and Monetary Policy: Are There Any Ties ?," Cahiers de recherche 1026, CIRPEE.
    59. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    60. Helmut Lütkepohl, 2013. "Reducing confidence bands for simulated impulse responses," Statistical Papers, Springer, vol. 54(4), pages 1131-1145, November.
    61. Emanuele BACCHIOCCHI, 2015. "On the Identification of Interdependence and Contagion of Financial Crises," Departmental Working Papers 2015-12, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    62. Marcel Fratzscher & Daniel Schneider & Ine Van Robays, 2013. "Oil Prices, Exchange Rates and Asset Prices," CESifo Working Paper Series 4264, CESifo.
    63. Soenen, Nicolas & Vander Vennet, Rudi, 2022. "ECB monetary policy and bank default risk☆," Journal of International Money and Finance, Elsevier, vol. 122(C).
    64. Emanuele BACCHIOCCHI, 2011. "Identification through heteroskedasticity: a likelihood-based approach," Departmental Working Papers 2011-19, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    65. Emanuele Bacchiocchi, 2017. "On the Identification of Interdependence and Contagion of Financial Crises," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(6), pages 1148-1175, December.
    66. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with smooth transition in variances," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 43-57.
    67. Jørn Inge Halvorsen & Dag Henning Jacobsen, 2009. "Are bank lending shocks important for economic fluctuations?," Working Paper 2009/27, Norges Bank.
    68. Helmut Lütkepohl & Aleksei Netsunajev, 2014. "Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction between U.S. Monetary Policy and the Stock Market," Discussion Papers of DIW Berlin 1388, DIW Berlin, German Institute for Economic Research.
    69. Elton Beqiraj & Valeria Patella & Massimiliano Tancioni, 2019. "Regime-switches in the Rollover of Sovereign Risk," Working Papers in Public Economics 191, University of Rome La Sapienza, Department of Economics and Law.
    70. Mirela Miescu, 2022. "Forward guidance shocks," Working Papers 352591340, Lancaster University Management School, Economics Department.
    71. Karin Klieber, 2023. "Non-linear dimension reduction in factor-augmented vector autoregressions," Papers 2309.04821, arXiv.org.
    72. Dobromił Serwa & Piotr Wdowiński, 2017. "Modeling Macro-Financial Linkages: Combined Impulse Response Functions in SVAR Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(4), pages 323-357, December.
    73. Kohonen, Anssi, 2012. "Transmission of Government Default Risk in the Eurozone," MPRA Paper 43823, University Library of Munich, Germany.
    74. Halvorsen, Jørn I. & Jacobsen, Dag Henning, 2014. "How important can bank lending shocks be for economic fluctuations?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 104-123.
    75. Matthys, Thomas & Meuleman, Elien & Vander Vennet, Rudi, 2020. "Unconventional monetary policy and bank risk taking," Journal of International Money and Finance, Elsevier, vol. 109(C).
    76. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    77. Helmut Herwartz & Alexander Lange & Simone Maxand, 2022. "Data‐driven identification in SVARs—When and how can statistical characteristics be used to unravel causal relationships?," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 668-693, April.
    78. Dmitry Kulikov & Aleksei Netsunajev, 2016. "Identifying Shocks in Structural VAR models via heteroskedasticity: a Bayesian approach," Bank of Estonia Working Papers wp2015-8, Bank of Estonia, revised 19 Feb 2016.
    79. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2016. "Structural analysis with Multivariate Autoregressive Index models," Journal of Econometrics, Elsevier, vol. 192(2), pages 332-348.
    80. Winkelmann, Lars & Netsunajev, Aleksei, 2015. "International Transmissions of Inflation Expectations in a Markov Switching Structural VAR Model," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112900, Verein für Socialpolitik / German Economic Association.
    81. Kerstin Bernoth & Helmut Herwartz & Lasse Trienens, 2023. "The Impacts of Global Risk and US Monetary Policy on US Dollar Exchange Rates and Excess Currency Returns," Discussion Papers of DIW Berlin 2037, DIW Berlin, German Institute for Economic Research.
    82. Emanuele BACCHIOCCHI & Luca FANELLI, 2012. "Identification in structural vector autoregressive models with structural changes," Departmental Working Papers 2012-16, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    83. Helmut Luetkepohl & George Milunovich, 2015. "Testing for Identification in SVAR-GARCH Models," SFB 649 Discussion Papers SFB649DP2015-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    84. Emanuele Bacchiocchi & Efrem Castelnuovo & Luca Fanelli, 2014. "Gimme a break! Identification and estimation of the macroeconomic effects of monetary policy shocks in the U.S," "Marco Fanno" Working Papers 0181, Dipartimento di Scienze Economiche "Marco Fanno".
    85. Michael Hachula & Malte Rieth, 2017. "Identifying Speculative Demand Shocks in Commodity Futures Markets through Changes in Volatility," Discussion Papers of DIW Berlin 1646, DIW Berlin, German Institute for Economic Research.
    86. Helmut Lütkepohl & George Milunovich, 2015. "Testing for Identification in SVAR-GARCH Models: Reconsidering the Impact of Monetary Shocks on Exchange Rates," Discussion Papers of DIW Berlin 1455, DIW Berlin, German Institute for Economic Research.
    87. Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2022. "Proxy SVAR identification of monetary policy shocks - Monte Carlo evidence and insights for the US," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    88. Efrem Castelnuovo, 2016. "Monetary policy shocks and Cholesky VARs: an assessment for the Euro area," Empirical Economics, Springer, vol. 50(2), pages 383-414, March.
    89. Helmut Lütkepohl, 2012. "Identifying Structural Vector Autoregressions via Changes in Volatility," Discussion Papers of DIW Berlin 1259, DIW Berlin, German Institute for Economic Research.
    90. Maxand, Simone, 2020. "Identification of independent structural shocks in the presence of multiple Gaussian components," Econometrics and Statistics, Elsevier, vol. 16(C), pages 55-68.
    91. Audi, Marc & Ali, Amjad & Fayad Hamadeh, Hani, 2022. "Nexus among innovations, financial development and economic growth in developing countries," MPRA Paper 115220, University Library of Munich, Germany.
    92. Martin Ademmer & Wolfram Horn & Josefine Quast, 2022. "Stock market dynamics and the relative importance of domestic, foreign, and common shocks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3911-3923, October.
    93. Michael Hachula & Malte Rieth, 2020. "Estimating the Impact of Financial Investments on Agricultural Futures Prices using Changes in Volatility," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(3), pages 759-785, May.
    94. Puonti, Päivi, 2016. "Fiscal multipliers in a structural VEC model with mixed normal errors," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 144-154.
    95. Helmut Herwartz, 2022. "Modelling interaction patterns in a predator-prey system of two freshwater organisms in discrete time: an identified structural VAR approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 63-85, March.
    96. Beqiraj, Elton & Patella, Valeria & Tancioni, Massimiliano, 2021. "Fiscal stance and the sovereign risk pass-through," Economic Modelling, Elsevier, vol. 102(C).
    97. S Ouliaris & A R Pagan, 2015. "A New Method for Working With Sign Restrictions in SVARs," NCER Working Paper Series 105, National Centre for Econometric Research.
    98. Francesco Cordoni & Nicolas Doremus & Alessio Moneta, 2023. "Identification of Vector Autoregressive Models with Nonlinear Contemporaneous Structure," LEM Papers Series 2023/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  27. Markku Lanne, 2006. "Forecasting Realized Volatility by Decomposition," Economics Working Papers ECO2006/20, European University Institute.

    Cited by:

    1. Basel M. A. Awartani, 2008. "Forecasting volatility with noisy jumps: an application to the Dow Jones Industrial Average stocks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 267-278.
    2. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    3. Milan Ficura & Jiri Witzany, 2016. "Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 278-301, August.
    4. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.

  28. Markku Lanne & Helmut Lütkepohl, 2006. "Structural Vector Autoregressions with Nonnormal Residuals," CESifo Working Paper Series 1651, CESifo.

    Cited by:

    1. Markku Lanne & Helmut Luetkepohl, 2008. "A Statistical Comparison of Alternative Identification Schemes for Monetary Policy Shocks," Economics Working Papers ECO2008/23, European University Institute.
    2. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    3. Jan Philipp Fritsche & Mathias Klein & Malte Rieth, 2020. "Government Spending Multipliers in (Un)certain Times," Discussion Papers of DIW Berlin 1901, DIW Berlin, German Institute for Economic Research.
    4. Helmut Herwartz & Martin Plödt, 2016. "Simulation Evidence on Theory-based and Statistical Identification under Volatility Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 94-112, February.
    5. Sun, Hang & Bos, Jaap W.B. & Li, Zhuo, 2017. "In the Nick of Time: A Heteroskedastic SVAR Model and Its Application to the Crude Oil Futures Market," Research Memorandum 019, Maastricht University, Graduate School of Business and Economics (GSBE).
    6. Helmut Lütkepohl & Thore Schlaak, 2017. "Choosing between Different Time-Varying Volatility Models for Structural Vector Autoregressive Analysis," Discussion Papers of DIW Berlin 1672, DIW Berlin, German Institute for Economic Research.
    7. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2010. "Testing for co-integration in vector autoregressions with non-stationary volatility," Journal of Econometrics, Elsevier, vol. 158(1), pages 7-24, September.
    8. Pérez-Quirós, Gabriel & Camacho, Máximo, 2013. "Commodity prices and the business cycle in Latin America: Living and dying by commodities?," CEPR Discussion Papers 9367, C.E.P.R. Discussion Papers.
    9. Moneta, Alessio & Pallante, Gianluca, 2022. "Identification of Structural VAR Models via Independent Component Analysis: A Performance Evaluation Study," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    10. Jordi Brandts & Sabrine El Baroudi & Stefanie Huber & Christina Rott, 2022. "Gender Differences in Private and Public Goal Setting," Tinbergen Institute Discussion Papers 22-008/II, Tinbergen Institute.
    11. Boris Blagov & Michael Funke & Richhild Moessner, 2015. "Modelling the time-variation in euro area lending spreads," BIS Working Papers 526, Bank for International Settlements.
    12. Kohonen, Anssi, 2012. "On detection of volatility spillovers in simultaneously open stock markets," MPRA Paper 37504, University Library of Munich, Germany.
    13. Herwartz, Helmut & Lange, Alexander & Maxand, Simone, 2019. "Statistical identification in SVARs - Monte Carlo experiments and a comparative assessment of the role of economic uncertainties for the US business cycle," University of Göttingen Working Papers in Economics 375, University of Goettingen, Department of Economics.
    14. Haroon Mumtaz & Gabor Pinter & Konstantinos Theodoridis, 2018. "What Do Vars Tell Us About The Impact Of A Credit Supply Shock?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(2), pages 625-646, May.
    15. Guido Turnip, 2017. "Identification of Small Open Economy SVARs via Markov-Switching Heteroskedasticity," The Economic Record, The Economic Society of Australia, vol. 93(302), pages 465-483, September.
    16. Guay, Alain, 2021. "Identification of structural vector autoregressions through higher unconditional moments," Journal of Econometrics, Elsevier, vol. 225(1), pages 27-46.
    17. Helmut Lütkepohl, 2012. "Fundamental Problems with Nonfundamental Shocks," Discussion Papers of DIW Berlin 1230, DIW Berlin, German Institute for Economic Research.
    18. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    19. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    20. Dungey, Mardi & Milunovich, George & Thorp, Susan & Yang, Minxian, 2012. "Endogenous crisis dating and contagion using smooth transition structural GARCH," Working Papers 15030, University of Tasmania, Tasmanian School of Business and Economics, revised 29 Aug 2012.
    21. Marek A. Dąbrowski & Łukasz Kwiatkowski & Justyna Wróblewska, 2020. "Sources of Real Exchange Rate Variability in Central and Eastern European Countries: Evidence from Structural Bayesian MSH-VAR Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(4), pages 369-412, December.
    22. Grammig, Joachim G. & Peter, Franziska J., 2008. "International price discovery in the presence of market microstructure effects," CFR Working Papers 08-10, University of Cologne, Centre for Financial Research (CFR).
    23. Alexandre Lucas & Konstantinos Pegios & Evangelos Kotsakis & Dan Clarke, 2020. "Price Forecasting for the Balancing Energy Market Using Machine-Learning Regression," Energies, MDPI, vol. 13(20), pages 1-16, October.
    24. Jolanta Tamošaitienė & Vahidreza Yousefi & Hamed Tabasi, 2021. "Project Portfolio Construction Using Extreme Value Theory," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    25. Alessio Moneta & Doris Entner & Patrik O. Hoyer & Alex Coad, 2013. "Causal Inference by Independent Component Analysis: Theory and Applications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(5), pages 705-730, October.
    26. Gabriel Rodríguez & Paulo Chávez, 2022. "Time Changing Effects of External Shocks on Macroeconomic Fluctuations in Peru: Empirical Application Using Regime-Switching VAR Models with Stochastic Volatility," Documentos de Trabajo / Working Papers 2022-509, Departamento de Economía - Pontificia Universidad Católica del Perú.
    27. Frédéric Karamé, 2015. "Asymmetries and Markov-switching structural VAR," Post-Print hal-02296101, HAL.
    28. Lütkepohl, Helmut & Meitz, Mika & Netšunajev, Aleksei & Saikkonen, Pentti, 2021. "Testing identification via heteroskedasticity in structural vector autoregressive models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 24(1), pages 1-22.
    29. Alexander Kriwoluzky, 2009. "Matching Theory and Data: Bayesian Vector Autoregression and Dynamic Stochastic General Equilibrium Models," Economics Working Papers ECO2009/29, European University Institute.
    30. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    31. Helmut Lütkepohl & Anton Velinov, 2014. "Structural Vector Autoregressions: Checking Identifying Long-run Restrictions via Heteroskedasticity," CESifo Working Paper Series 4651, CESifo.
    32. Helmut Lütkepohl & Aleksei Netšunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticy," SFB 649 Discussion Papers SFB649DP2015-015, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    33. Alali, Walid Y. & Ellalee, Haider, 2018. "The Brexit Impact on Inward FDI in the UK," EconStor Preprints 274655, ZBW - Leibniz Information Centre for Economics.
    34. Kilian, Lutz, 2011. "Structural Vector Autoregressions," CEPR Discussion Papers 8515, C.E.P.R. Discussion Papers.
    35. Ben J. Heijdra & Jenny Ligthart, 2006. "The Transitional Dynamics of Fiscal Policy in Small Open Economies," CESifo Working Paper Series 1777, CESifo.
    36. Marinela Adriana Finta & Bart Frijns & Alireza Tourani-Rad, 2019. "Time-varying contemporaneous spillovers during the European Debt Crisis," Empirical Economics, Springer, vol. 57(2), pages 423-448, August.
    37. Nautz, Dieter & Strohsal, Till & Netšunajev, Aleksei, 2019. "The Anchoring Of Inflation Expectations In The Short And In The Long Run," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1959-1977, July.
    38. Savi Virolainen, 2021. "Gaussian and Student's $t$ mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks in the Euro area," Papers 2109.13648, arXiv.org, revised Jun 2022.
    39. Helmut Lütkepohl & Aleksei Netsunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticity: A Comparison of Different Volatility Models," Discussion Papers of DIW Berlin 1464, DIW Berlin, German Institute for Economic Research.
    40. Klinger, Sabine & Weber, Enzo, 2016. "Detecting unemployment hysteresis: A simultaneous unobserved components model with Markov switching," Economics Letters, Elsevier, vol. 144(C), pages 115-118.
    41. Jahn, Elke & Weber, Enzo, 2012. "Identifying the Substitution Effect of Temporary Agency Employment," University of Regensburg Working Papers in Business, Economics and Management Information Systems 463, University of Regensburg, Department of Economics.
    42. Markku Lanne & Helmut Luetkepohl, 2008. "Stock Prices and Economic Fluctuations: A Markov Switching Structural Vector Autoregressive Analysis," Economics Working Papers ECO2008/29, European University Institute.
    43. Markku Lanne & Helmut Luetkepohl & Katarzyna Maciejowska, 2009. "Structural Vector Autoregressions with Markov Switching," Economics Working Papers ECO2009/06, European University Institute.
    44. Jahn, Elke & Weber, Enzo, 2013. "Zeitarbeit: Zusätzliche Jobs, aber auch Verdrängung (The substitution effect of temporary agency employment)," IAB-Kurzbericht 201302, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    45. Lütkepohl, Helmut, 2020. "Structural vector autoregressive models with more shocks than variables identified via heteroskedasticity," Economics Letters, Elsevier, vol. 195(C).
    46. Gabriele Fiorentini & Enrique Sentana, 2020. "Discrete Mixtures of Normals Pseudo Maximum Likelihood Estimators of Structural Vector Autoregressions," Working Papers wp2020_2023, CEMFI.
    47. Karamysheva, Madina & Skrobotov, Anton, 2022. "Do we reject restrictions identifying fiscal shocks? identification based on non-Gaussian innovations," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    48. Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2020. "Proxy SVAR identification of monetary policy shocks: MonteCarlo evidence and insights for the US," University of Göttingen Working Papers in Economics 404, University of Goettingen, Department of Economics.
    49. Ivan Mendieta-Munoz & Mengheng Li, 2019. "The Multivariate Simultaneous Unobserved Compenents Model and Identification via Heteroskedasticity," Working Paper Series, Department of Economics, University of Utah 2019_06, University of Utah, Department of Economics.
    50. Helmut Lütkepohl, 2020. "Structural Vector Autoregressive Models with More Shocks than Variables Identified via Heteroskedasticity," Discussion Papers of DIW Berlin 1871, DIW Berlin, German Institute for Economic Research.
    51. Paolo Guarda & Abdelaziz Rouabah & John Theal, 2011. "An MVAR Framework to Capture Extreme Events in Macroprudential Stress Tests," BCL working papers 63, Central Bank of Luxembourg.
    52. Helmut Lütkepohl & Aleksei NetŠunajev, 2014. "Disentangling Demand And Supply Shocks In The Crude Oil Market: How To Check Sign Restrictions In Structural Vars," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 479-496, April.
    53. Gong, Xu & Chen, Liqiang & Lin, Boqiang, 2020. "Analyzing dynamic impacts of different oil shocks on oil price," Energy, Elsevier, vol. 198(C).
    54. Savi Virolainen, 2020. "Structural Gaussian mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks," Papers 2007.04713, arXiv.org, revised Oct 2022.
    55. Lukas Hoesch & Adam Lee & Geert Mesters, 2022. "Robust inference for non-Gaussian SVAR models," Economics Working Papers 1847, Department of Economics and Business, Universitat Pompeu Fabra.
    56. Katarzyna Maciejowska, 2010. "Estimation Methods Comparison of SVAR Models with a Mixture of Two Normal Distributions," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 2(4), pages 279-314, September.
    57. Lukas Boer & Lukas Menkhoff & Malte Rieth, 2023. "The multifaceted impact of US trade policy on financial markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 388-406, April.
    58. Kohonen, Anssi, 2013. "On detection of volatility spillovers in overlapping stock markets," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 140-158.
    59. Dieter Nautz & Aleksei Netsunajev & Till Strohsal, 2016. "Aggregate Employment, Job Polarization and Inequalities: A Transatlantic Perspective," SFB 649 Discussion Papers SFB649DP2016-015, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    60. Simos G. Meintanis & Joseph Ngatchou-Wandji & James Allison, 2018. "Testing for serial independence in vector autoregressive models," Statistical Papers, Springer, vol. 59(4), pages 1379-1410, December.
    61. Zema, Sebastiano Michele, 2022. "Directed acyclic graph based information shares for price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    62. Jan Pablo Burgard & Matthias Neuenkirch & Matthias Nöckel, 2016. "State-Dependent Transmission of Monetary Policy in the Euro Area," Research Papers in Economics 2016-15, University of Trier, Department of Economics.
    63. Braun, Robin, 2021. "The importance of supply and demand for oil prices: evidence from non-Gaussianity," Bank of England working papers 957, Bank of England.
    64. Helmut Lütkepohl & Thore Schlaak, 2020. "Heteroskedastic Proxy Vector Autoregressions," Discussion Papers of DIW Berlin 1876, DIW Berlin, German Institute for Economic Research.
    65. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
    66. Aleksei Netšunajev & Lars Winkelmann, 2016. "International dynamics of inflation expectations," SFB 649 Discussion Papers SFB649DP2016-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    67. Emanuele BACCHIOCCHI, 2011. "Identification in structural VAR models with different volatility regimes," Departmental Working Papers 2011-39, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    68. Christoph Große Steffen & Maximilian Podstawski, 2016. "Ambiguity and Time-Varying Risk Aversion in Sovereign Debt Markets," Discussion Papers of DIW Berlin 1602, DIW Berlin, German Institute for Economic Research.
    69. Herwartz, Helmut, 2014. "Structural analysis with independent innovations," University of Göttingen Working Papers in Economics 208, University of Goettingen, Department of Economics.
    70. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    71. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    72. Degras, David & Ting, Chee-Ming & Ombao, Hernando, 2022. "Markov-switching state-space models with applications to neuroimaging," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
    73. Noel Gaston & Gulasekaran Rajaguru, 2015. "A Markov-switching structural vector autoregressive model of boom and bust in the Australian labour market," Empirical Economics, Springer, vol. 49(4), pages 1271-1299, December.
    74. Podstawski, Maximilian & Velinov, Anton, 2018. "The state dependent impact of bank exposure on sovereign risk," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 88, pages 63-75.
    75. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    76. Sascha A. Keweloh, 2023. "Uncertain Prior Economic Knowledge and Statistically Identified Structural Vector Autoregressions," Papers 2303.13281, arXiv.org.
    77. Keweloh, Sascha A. & Hetzenecker, Stephan & Seepe, Andre, 2023. "Monetary policy and information shocks in a block-recursive SVAR," Journal of International Money and Finance, Elsevier, vol. 137(C).
    78. Emanuele BACCHIOCCHI, 2015. "On the Identification of Interdependence and Contagion of Financial Crises," Departmental Working Papers 2015-12, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    79. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.
    80. Emanuele BACCHIOCCHI, 2011. "Identification through heteroskedasticity: a likelihood-based approach," Departmental Working Papers 2011-19, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    81. Emanuele Bacchiocchi, 2017. "On the Identification of Interdependence and Contagion of Financial Crises," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(6), pages 1148-1175, December.
    82. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with smooth transition in variances," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 43-57.
    83. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2016. "Bayesian Vector Autoregressions with Non-Gaussian Shocks," CReMFi Discussion Papers 5, CReMFi, School of Economics and Finance, QMUL.
    84. Juan Carlos Cuestas & Bo Tang, 2015. "Exchange Rate Changes and Stock Returns in China: A Markov Switching SVAR Approach," Working Papers 2015024, The University of Sheffield, Department of Economics.
    85. Helmut Lütkepohl & Aleksei Netsunajev, 2014. "Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction between U.S. Monetary Policy and the Stock Market," Discussion Papers of DIW Berlin 1388, DIW Berlin, German Institute for Economic Research.
    86. Arčabić, Vladimir & Škrinjarić, Tihana, 2021. "Sharing is caring: Spillovers and synchronization of business cycles in the European Union," Economic Modelling, Elsevier, vol. 96(C), pages 25-39.
    87. Velinov, Anton, 2016. "On the importance of testing structural identification schemes and the potential consequences of incorrectly identified models," VfS Annual Conference 2016 (Augsburg): Demographic Change 145581, Verein für Socialpolitik / German Economic Association.
    88. Martin Bruns & Helmut Luetkepohl, 2022. "Heteroskedastic Proxy Vector Autoregressions: Testing for Time-Varying Impulse Responses in the Presence of Multiple Proxies," University of East Anglia School of Economics Working Paper Series 2022-02, School of Economics, University of East Anglia, Norwich, UK..
    89. Helmut Lütkepohl & Aleksei Netšunajev, 2018. "The Relation between Monetary Policy and the Stock Market in Europe," Econometrics, MDPI, vol. 6(3), pages 1-14, August.
    90. Sun, Hang, 2016. "Crisis-Contingent Dynamics of Connectedness: An SVAR-Spatial-Network “Tripod” Model with Thresholds," Research Memorandum 032, Maastricht University, Graduate School of Business and Economics (GSBE).
    91. Dobromił Serwa & Piotr Wdowiński, 2017. "Modeling Macro-Financial Linkages: Combined Impulse Response Functions in SVAR Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(4), pages 323-357, December.
    92. Kohonen, Anssi, 2012. "Transmission of Government Default Risk in the Eurozone," MPRA Paper 43823, University Library of Munich, Germany.
    93. Podstawski, Maximilian & Velinov, Anton, 2018. "The state dependent impact of bank exposure on sovereign risk," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 63-75.
    94. Velinov, Anton, 2018. "On the importance of testing structural identification schemes and the potential consequences of incorrectly identified models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 2(1), pages 106-126.
    95. Vicente E. Montano & Rosalia T. Gabronino & Restie E. Torres, 2019. "The curious relationship between agricultural and energy price index: A Vector Error Correction Model (VECM) analysis approach," Journal of Administrative and Business Studies, Professor Dr. Usman Raja, vol. 5(3), pages 161-177.
    96. Herwartz, Helmut & Lütkepohl, Helmut, 2014. "Structural vector autoregressions with Markov switching: Combining conventional with statistical identification of shocks," Journal of Econometrics, Elsevier, vol. 183(1), pages 104-116.
    97. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    98. Anton Velinov & Wenjuan Chen, 2014. "Are There Bubbles in Stock Prices?: Testing for Fundamental Shocks," Discussion Papers of DIW Berlin 1375, DIW Berlin, German Institute for Economic Research.
    99. Fengler, Matthias & Polivka, Jeannine, 2021. "Identifying structural shocks to volatility through a proxy-MGARCH model," Economics Working Paper Series 2103, University of St. Gallen, School of Economics and Political Science, revised May 2021.
    100. Helmut Herwartz & Alexander Lange & Simone Maxand, 2022. "Data‐driven identification in SVARs—When and how can statistical characteristics be used to unravel causal relationships?," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 668-693, April.
    101. Dmitry Kulikov & Aleksei Netsunajev, 2016. "Identifying Shocks in Structural VAR models via heteroskedasticity: a Bayesian approach," Bank of Estonia Working Papers wp2015-8, Bank of Estonia, revised 19 Feb 2016.
    102. Emanuele Bacchiocchi & Toru Kitagawa, 2020. "Locally- but not globally-identified SVARs," CeMMAP working papers CWP40/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    103. Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute.
    104. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2016. "Structural analysis with Multivariate Autoregressive Index models," Journal of Econometrics, Elsevier, vol. 192(2), pages 332-348.
    105. Winkelmann, Lars & Netsunajev, Aleksei, 2015. "International Transmissions of Inflation Expectations in a Markov Switching Structural VAR Model," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112900, Verein für Socialpolitik / German Economic Association.
    106. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "Moment tests of independent components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 429-474, May.
    107. Stefan Bruder, 2018. "Inference for structural impulse responses in SVAR-GARCH models," ECON - Working Papers 281, Department of Economics - University of Zurich.
    108. Vladimir Dombrovskii & Tatyana Obyedko, 2014. "Dynamic Investment Portfolio Optimization under Constraints in the Financial Market with Regime Switching using Model Predictive Control," Papers 1410.1136, arXiv.org.
    109. Kalli, Maria & Griffin, Jim E., 2018. "Bayesian nonparametric vector autoregressive models," Journal of Econometrics, Elsevier, vol. 203(2), pages 267-282.
    110. Emanuele BACCHIOCCHI & Luca FANELLI, 2012. "Identification in structural vector autoregressive models with structural changes," Departmental Working Papers 2012-16, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    111. Helmut Luetkepohl & George Milunovich, 2015. "Testing for Identification in SVAR-GARCH Models," SFB 649 Discussion Papers SFB649DP2015-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    112. Bierbaumer, Daniel & Rieth, Malte & Velinov, Anton, 2021. "The state-dependent trading behavior of banks in the oil futures market," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 1011-1024.
    113. Emanuele Bacchiocchi & Efrem Castelnuovo & Luca Fanelli, 2014. "Gimme a break! Identification and estimation of the macroeconomic effects of monetary policy shocks in the U.S," "Marco Fanno" Working Papers 0181, Dipartimento di Scienze Economiche "Marco Fanno".
    114. Pervin, Shahida, 2018. "Dynamics and Interactions of Monetary Policy and Macroeconomic Variables: Empirical Investigation in the UK Economy with Bayesian VAR," MPRA Paper 91816, University Library of Munich, Germany.
    115. Daniel Bierbaumer & Malte Rieth & Anton Velinov, 2018. "Nonlinear Intermediary Pricing in the Oil Futures Market," Discussion Papers of DIW Berlin 1722, DIW Berlin, German Institute for Economic Research.
    116. Helmut Lütkepohl & George Milunovich, 2015. "Testing for Identification in SVAR-GARCH Models: Reconsidering the Impact of Monetary Shocks on Exchange Rates," Discussion Papers of DIW Berlin 1455, DIW Berlin, German Institute for Economic Research.
    117. Sascha A. Keweloh & Mathias Klein & Jan Pruser, 2023. "Estimating Fiscal Multipliers by Combining Statistical Identification with Potentially Endogenous Proxies," Papers 2302.13066, arXiv.org, revised Feb 2024.
    118. Gong, Xu & Guan, Keqin & Chen, Liqing & Liu, Tangyong & Fu, Chengbo, 2021. "What drives oil prices? — A Markov switching VAR approach," Resources Policy, Elsevier, vol. 74(C).
    119. Efrem Castelnuovo, 2016. "Monetary policy shocks and Cholesky VARs: an assessment for the Euro area," Empirical Economics, Springer, vol. 50(2), pages 383-414, March.
    120. Ellalee, Haider & Alali, Walid Y., 2018. "The Brexit Impact on Inward FDI in the UK," MPRA Paper 117510, University Library of Munich, Germany, revised 20 May 2018.
    121. Lukas Hoesch & Adam Lee & Geert Mesters, 2022. "Locally Robust Inference for Non-Gaussian SVAR Models," Working Papers 1367, Barcelona School of Economics.
    122. Kangogo, Moses & Volkov, Vladimir, 2022. "Detecting signed spillovers in global financial markets: A Markov-switching approach," International Review of Financial Analysis, Elsevier, vol. 82(C).
    123. Markku Lanne & Jani Luoto, 2016. "Data-Driven Inference on Sign Restrictions in Bayesian Structural Vector Autoregression," CREATES Research Papers 2016-04, Department of Economics and Business Economics, Aarhus University.
    124. Maddalena Cavicchioli, 2021. "OLS Estimation of Markov switching VAR models: asymptotics and application to energy use," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(3), pages 431-449, September.
    125. Martin Ademmer & Wolfram Horn & Josefine Quast, 2022. "Stock market dynamics and the relative importance of domestic, foreign, and common shocks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3911-3923, October.
    126. Marianna Oliskevych & Iryna Lukianenko, 2020. "European unemployment nonlinear dynamics over the business cycles: Markov switching approach," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 22(4), pages 375-401.
    127. Daniel J Lewis, 2021. "Identifying Shocks via Time-Varying Volatility [First Order Autoregressive Processes and Strong Mixing]," Review of Economic Studies, Oxford University Press, vol. 88(6), pages 3086-3124.
    128. Velinov, Anton & Chen, Wenjuan, 2015. "Do stock prices reflect their fundamentals? New evidence in the aftermath of the financial crisis," Journal of Economics and Business, Elsevier, vol. 80(C), pages 1-20.
    129. Puonti, Päivi, 2016. "Fiscal multipliers in a structural VEC model with mixed normal errors," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 144-154.
    130. Donald Lien & Zijun Wang, 2016. "Estimation of Market Information Shares: A Comparison," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(11), pages 1108-1124, November.
    131. Sebastiano Michele Zema, 2020. "Directed Acyclic Graph based Information Shares for Price Discovery," LEM Papers Series 2020/28, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    132. Miguel Cabello, 2022. "Robust Estimation of the non-Gaussian Dimension in Structural Linear Models," Papers 2212.07263, arXiv.org, revised Sep 2023.
    133. Francesco Cordoni & Nicolas Doremus & Alessio Moneta, 2023. "Identification of Vector Autoregressive Models with Nonlinear Contemporaneous Structure," LEM Papers Series 2023/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    134. Philip Arestis & Michail Karoglou & Kostas Mouratidis, 2016. "Monetary Policy Preferences of the EMU and the UK," Manchester School, University of Manchester, vol. 84(4), pages 528-550, July.

  29. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Economics Working Papers ECO2006/3, European University Institute.

    Cited by:

    1. Chen, Ray-Bing & Chen, Ying & Härdle, Wolfgang K., 2014. "TVICA—Time varying independent component analysis and its application to financial data," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 95-109.
    2. Driton Kuçi, 2015. "Contemporary Models of Organization of Power and the Macedonian Model of Organization of Power," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, September.
    3. Heejoon Han & Myung D. Park & Shen Zhang, 2015. "A Multiplicative Error Model with Heterogeneous Components for Forecasting Realized Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(3), pages 209-219, April.
    4. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    5. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," MPRA Paper 93802, University Library of Munich, Germany.
    6. Daniel Preve, "undated". "Linear programming-based estimators in nonnegative autoregression," GRU Working Paper Series GRU_2016_001, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    7. Ahoniemi, Katja & Lanne, Markku, 2007. "Joint Modeling of Call and Put Implied Volatility," MPRA Paper 6318, University Library of Munich, Germany.
    8. Swasti R. Khuntia & Jose L. Rueda & Mart A.M.M. Van der Meijden, 2018. "Long-Term Electricity Load Forecasting Considering Volatility Using Multiplicative Error Model," Energies, MDPI, vol. 11(12), pages 1-19, November.
    9. Aknouche, Abdelhakim & Almohaimeed, Bader & Dimitrakopoulos, Stefanos, 2020. "Periodic autoregressive conditional duration," MPRA Paper 101696, University Library of Munich, Germany, revised 08 Jul 2020.
    10. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    11. Markku Lanne, 2006. "Forecasting Realized Volatility by Decomposition," Economics Working Papers ECO2006/20, European University Institute.
    12. Ng, F.C. & Li, W.K. & Yu, Philip L.H., 2016. "Diagnostic checking of the vector multiplicative error model," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 86-97.
    13. Abdelhakim Aknouche & Bader Almohaimeed & Stefanos Dimitrakopoulos, 2022. "Periodic autoregressive conditional duration," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 5-29, January.
    14. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    15. Lanne, Markku, 2007. "Forecasting realized exchange rate volatility by decomposition," International Journal of Forecasting, Elsevier, vol. 23(2), pages 307-320.
    16. Giovanni De Luca & Giampiero Gallo, 2010. "A Time-varying Mixing Multiplicative Error Model for Realized Volatility," Econometrics Working Papers Archive wp2010_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    17. Arnaud Dufays & Maciej Augustyniak & Luc Bauwens, 2016. "A new approach to volatility modeling: the High-Dimensional Markov model," Cahiers de recherche 1609, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    18. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
    19. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    20. Christian T. Brownlees & Giampiero M. Gallo, 2010. "Comparison of Volatility Measures: a Risk Management Perspective," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 8(1), pages 29-56, Winter.
    21. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    22. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    23. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2010. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," SFB 649 Discussion Papers SFB649DP2010-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    25. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.
    26. Lanne, Markku & Ahoniemi, Katja, 2008. "Implied Volatility with Time-Varying Regime Probabilities," MPRA Paper 23721, University Library of Munich, Germany.
    27. Xu, Yongdeng, 2022. "The Exponential HEAVY Model: An Improved Approach to Volatility Modeling and Forecasting," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
    28. Ke, Rui & Lu, Wanbo & Jia, Jing, 2021. "Evaluating multiplicative error models: A residual-based approach," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).

  30. Markku Lanne & Timo Vesalay, 2005. "The Effect of a Transaction Tax on Exchange Rate Volatility," Economics Working Papers ECO2005/19, European University Institute.

    Cited by:

    1. Danuse Nerudova, 2011. "Taxing the financial sector in the European Union," MENDELU Working Papers in Business and Economics 2011-16, Mendel University in Brno, Faculty of Business and Economics.
    2. Olivier Damette, 2016. "Mixture distribution hypothesis and the impact of a Tobin tax on exchange rate volatility : a reassessment," Post-Print hal-01601393, HAL.
    3. Francis Bismans & Olivier Damette, 2012. "La taxe Tobin : une synthèse des travaux basés sur la théorie des jeux et l’économétrie," Working Papers of BETA 2012-09, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    4. Deng, Yongheng & Liu, Xin & Wei, Shang-Jin, 2018. "One fundamental and two taxes: When does a Tobin tax reduce financial price volatility?," Journal of Financial Economics, Elsevier, vol. 130(3), pages 663-692.
    5. Olivier Damette & Stéphane Goutte, 2015. "Tobin tax and trading volume tightening: a reassessment," Post-Print hal-01203841, HAL.
    6. Olivier Damette & Beum-Jo Park, 2015. "Tobin Tax and Volatility: A Threshold Quantile Autoregressive Regression Framework," Review of International Economics, Wiley Blackwell, vol. 23(5), pages 996-1022, November.
    7. Taeyoon Sung & Danbee Park & Ki Young Park, 2014. "Short-Term External Debt and Foreign Exchange Rate Volatility in Emerging Economies: Evidence from the Korea Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(S6), pages 138-157, November.
    8. Sirnes Espen, 2022. "Estimating the Effect of Transaction Costs Using the Tick Size as a Proxy," Review of Economics, De Gruyter, vol. 73(1), pages 57-77, April.
    9. Hvozdyk, Lyudmyla & Rustanov, Serik, 2016. "The effect of financial transaction tax on market liquidity and volatility: An Italian perspective," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 62-78.
    10. Neil McCulloch & Grazia Pacillo, 2010. "The Tobin Tax A Review of the Evidence," Working Paper Series 1611, Department of Economics, University of Sussex Business School.
    11. Alonso, Miguel A. & Rallo, Juan Ramón & Romero, Alberto, 2013. "El efecto de los impuestos a las transacciones financieras en la estabilidad de los mercados de capital. Un debate sin resolver," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(317), pages 207-231, enero-mar.
    12. Peter Gomber & Martin Haferkorn & Kai Zimmermann, 2016. "Securities Transaction Tax and Market Quality – the Case of France," European Financial Management, European Financial Management Association, vol. 22(2), pages 313-337, March.

  31. Markku Lanne & Pentti Saikkonen, 2005. "Modeling Conditional Skewness in Stock Returns," Economics Working Papers ECO2005/14, European University Institute.

    Cited by:

    1. Dark Jonathan Graeme, 2010. "Estimation of Time Varying Skewness and Kurtosis with an Application to Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-50, March.
    2. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    3. Changli He & Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Parameterizing Unconditional Skewness in Models for Financial Time Series," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(2), pages 208-230, Spring.
    4. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    5. Simon Lalancette & Jean†Guy Simonato, 2017. "The Role of the Conditional Skewness and Kurtosis in VIX Index Valuation," European Financial Management, European Financial Management Association, vol. 23(2), pages 325-354, March.
    6. Ahmed, Walid M.A., 2020. "Is there a risk-return trade-off in cryptocurrency markets? The case of Bitcoin," Journal of Economics and Business, Elsevier, vol. 108(C).
    7. Jing-Yi Lai, 2012. "An empirical study of the impact of skewness and kurtosis on hedging decisions," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1827-1837, December.
    8. Lai, Jing-yi, 2012. "Shock-dependent conditional skewness in international aggregate stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 72-83.
    9. Lin, Chu-Hsiung & Changchien, Chang-Cheng & Kao, Tzu-Chuan & Kao, Wei-Shun, 2014. "High-order moments and extreme value approach for value-at-risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 421-434.
    10. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tédongap, 2016. "Which parametric model for conditional skewness?," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1237-1271, October.
    11. Matteo Grigoletto & Francesco Lisi, 2011. "Practical implications of higher moments in risk management," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 487-506, November.
    12. Wang, Tianyi & Liang, Fang & Huang, Zhuo & Yan, Hong, 2022. "Do realized higher moments have information content? - VaR forecasting based on the realized GARCH-RSRK model," Economic Modelling, Elsevier, vol. 109(C).
    13. Panayiotis Theodossiou & Christos S. Savva, 2016. "Skewness and the Relation Between Risk and Return," Management Science, INFORMS, vol. 62(6), pages 1598-1609, June.
    14. Christian Bauer, 2007. "A Better Asymmetric Model of Changing Volatility in Stock and Exchange Rate Returns: Trend-GARCH," The European Journal of Finance, Taylor & Francis Journals, vol. 13(1), pages 65-87.
    15. Shum, Wai Yan, 2020. "Modelling conditional skewness: Heterogeneous beliefs, short sale restrictions and market declines," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).

  32. Lanne, Markku & Saikkonen, Pentti, 2005. "A Multivariate Generalized Orthogonal Factor GARCH Model," MPRA Paper 23714, University Library of Munich, Germany.

    Cited by:

    1. Han, Chulwoo & Park, Frank C., 2022. "A geometric framework for covariance dynamics," Journal of Banking & Finance, Elsevier, vol. 134(C).
    2. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    3. Lütkepohl, Helmut & Schlaak, Thore, 2019. "Bootstrapping impulse responses of structural vector autoregressive models identified through GARCH," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 41-61.
    4. Alain Hecq & Franz C. Palm & Sébastien Laurent, 2016. "On the Univariate Representation of BEKK Models with Common Factors," Post-Print hal-01440307, HAL.
    5. Lucchetti, Riccardo & Palomba, Giulio, 2009. "Nonlinear adjustment in US bond yields: An empirical model with conditional heteroskedasticity," Economic Modelling, Elsevier, vol. 26(3), pages 659-667, May.
    6. Helmut Lütkepohl & Thore Schlaak, 2017. "Choosing between Different Time-Varying Volatility Models for Structural Vector Autoregressive Analysis," Discussion Papers of DIW Berlin 1672, DIW Berlin, German Institute for Economic Research.
    7. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2010. "Testing for co-integration in vector autoregressions with non-stationary volatility," Journal of Econometrics, Elsevier, vol. 158(1), pages 7-24, September.
    8. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    9. Chrétien, Stéphane & Ortega, Juan-Pablo, 2014. "Multivariate GARCH estimation via a Bregman-proximal trust-region method," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 210-236.
    10. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Tinbergen Institute Discussion Papers 14-037/III, Tinbergen Institute.
    11. Ahmadi, Maryam & Manera, Matteo & Sadeghzadeh, Mehdi, 2018. "Investment-Uncertainty Relationship in the Oil and Gas Industry," ETA: Economic Theory and Applications 273141, Fondazione Eni Enrico Mattei (FEEM).
    12. Herwartz, Helmut & Lange, Alexander & Maxand, Simone, 2019. "Statistical identification in SVARs - Monte Carlo experiments and a comparative assessment of the role of economic uncertainties for the US business cycle," University of Göttingen Working Papers in Economics 375, University of Goettingen, Department of Economics.
    13. Simon Hetland, 2020. "Spectral Targeting Estimation of $\lambda$-GARCH models," Papers 2007.02588, arXiv.org.
    14. Lütkepohl, Helmut & Milunovich, George & Yang, Minxian, 2020. "Inference in partially identified heteroskedastic simultaneous equations models," Journal of Econometrics, Elsevier, vol. 218(2), pages 317-345.
    15. Lanne, Markku & Lütkepohl, Helmut, 2010. "Structural Vector Autoregressions With Nonnormal Residuals," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 159-168.
    16. Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 12/06, University of Canterbury, Department of Economics and Finance.
    17. Arie Preminger & Christian M. Hafner, 2006. "Asymptotic Theory For A Factor Garch Model," Working Papers 0608, Ben-Gurion University of the Negev, Department of Economics.
    18. Francq, Christian & Zakoian, Jean-Michel, 2014. "Estimating multivariate GARCH and stochastic correlation models equation by equation," MPRA Paper 54250, University Library of Munich, Germany.
    19. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    20. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    21. Helmut Lütkepohl & Aleksei Netšunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticy," SFB 649 Discussion Papers SFB649DP2015-015, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Helmut Lütkepohl & Aleksei Netsunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticity: A Comparison of Different Volatility Models," Discussion Papers of DIW Berlin 1464, DIW Berlin, German Institute for Economic Research.
    23. Manabu Asai & Chia-Lin Chang & Michael McAleer & Laurent Pauwels, 2021. "Asymptotic and Finite Sample Properties for Multivariate Rotated GARCH Models," Econometrics, MDPI, vol. 9(2), pages 1-21, May.
    24. Herwartz, Helmut & Roestel, Jan, 2022. "Asset prices, financial amplification and monetary policy: Structural evidence from an identified multivariate GARCH model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    25. Noureldin, Diaa & Shephard, Neil & Sheppard, Kevin, 2014. "Multivariate rotated ARCH models," Scholarly Articles 34650305, Harvard University Department of Economics.
    26. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    27. K. Diamantopoulos & I. Vrontos, 2010. "A Student-t Full Factor Multivariate GARCH Model," Computational Economics, Springer;Society for Computational Economics, vol. 35(1), pages 63-83, January.
    28. Christian Francq & Jean-Michel Zakoïan, 2016. "Estimating multivariate volatility models equation by equation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 613-635, June.
    29. Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," Working Papers halshs-01944656, HAL.
    30. Masud Alam, 2021. "Time Varying Risk in U.S. Housing Sector and Real Estate Investment Trusts Equity Return," Papers 2107.10455, arXiv.org.
    31. Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
    32. Lucchetti, Riccardo & Palomba, Giulio, 2008. "Nonlinear Adjustment in US Bond Yields: an Empirical Analysis with Conditional Heteroskedasticity," MPRA Paper 11571, University Library of Munich, Germany.
    33. Braun, Robin, 2021. "The importance of supply and demand for oil prices: evidence from non-Gaussianity," Bank of England working papers 957, Bank of England.
    34. Nguyen, Hoang & Ausín Olivera, María Concepción & Galeano San Miguel, Pedro, 2017. "Parallel Bayesian Inference for High Dimensional Dynamic Factor Copulas," DES - Working Papers. Statistics and Econometrics. WS 24552, Universidad Carlos III de Madrid. Departamento de Estadística.
    35. Boswijk, H.P. & Weide, R. van der, 2006. "Wake me up before you GO-GARCH," CeNDEF Working Papers 06-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    36. LAURENT, Sébastien & ROMBOUTS, Jeroen V. K. & VIOLANTE, Francesco, 2010. "On the forecasting accuracy of multivariate GARCH models," LIDAM Discussion Papers CORE 2010025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    37. H. J. Turtle & Kainan Wang, 2014. "Modeling Conditional Covariances With Economic Information Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 217-236, April.
    38. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    39. Hafner, Christian M. & Linton, Oliver, 2010. "Efficient estimation of a multivariate multiplicative volatility model," Journal of Econometrics, Elsevier, vol. 159(1), pages 55-73, November.
    40. Lukas Boeckelmann & Arthur Stalla-Bourdillon, 2021. "Structural Estimation of Time-Varying Spillovers:an Application to International Credit Risk Transmission," Working Papers hal-03338209, HAL.
    41. HAFNER, Christian & PREMINGER, Arie, 2006. "Asymptotic theory for a factor GARCH model," LIDAM Discussion Papers CORE 2006071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    42. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
    43. Helmut Herwartz & Alexander Lange & Simone Maxand, 2022. "Data‐driven identification in SVARs—When and how can statistical characteristics be used to unravel causal relationships?," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 668-693, April.
    44. Xiaoning Kang & Xinwei Deng & Kam‐Wah Tsui & Mohsen Pourahmadi, 2020. "On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices," International Statistical Review, International Statistical Institute, vol. 88(3), pages 616-641, December.
    45. Fernanda Maria Müller & Marcelo Brutti Righi, 2024. "Comparison of Value at Risk (VaR) Multivariate Forecast Models," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 75-110, January.
    46. García-Ferrer, Antonio & González-Prieto, Ester & Peña, Daniel, 2008. "A multivariate generalized independent factor GARCH model with an application to financial stock returns," DES - Working Papers. Statistics and Econometrics. WS ws087528, Universidad Carlos III de Madrid. Departamento de Estadística.
    47. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    48. Stefan Bruder, 2018. "Inference for structural impulse responses in SVAR-GARCH models," ECON - Working Papers 281, Department of Economics - University of Zurich.
    49. Helmut Luetkepohl & George Milunovich, 2015. "Testing for Identification in SVAR-GARCH Models," SFB 649 Discussion Papers SFB649DP2015-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    50. Peter Boswijk, H. & van der Weide, Roy, 2011. "Method of moments estimation of GO-GARCH models," Journal of Econometrics, Elsevier, vol. 163(1), pages 118-126, July.
    51. Takashi Isogai, 2015. "An Empirical Study of the Dynamic Correlation of Japanese Stock Returns," Bank of Japan Working Paper Series 15-E-7, Bank of Japan.
    52. Helmut Lütkepohl & George Milunovich, 2015. "Testing for Identification in SVAR-GARCH Models: Reconsidering the Impact of Monetary Shocks on Exchange Rates," Discussion Papers of DIW Berlin 1455, DIW Berlin, German Institute for Economic Research.
    53. Daniel J Lewis, 2021. "Identifying Shocks via Time-Varying Volatility [First Order Autoregressive Processes and Strong Mixing]," Review of Economic Studies, Oxford University Press, vol. 88(6), pages 3086-3124.
    54. García-Ferrer, Antonio & González-Prieto, Ester & Peña, Daniel, 2012. "A conditionally heteroskedastic independent factor model with an application to financial stock returns," International Journal of Forecasting, Elsevier, vol. 28(1), pages 70-93.

  33. Pentti Saikkonen & Markku Lanne, 2004. "A Skewed GARCH-in-Mean Model: An Application to U.S. Stock Returns," Econometric Society 2004 North American Summer Meetings 469, Econometric Society.

    Cited by:

    1. Pelagatti Matteo M, 2009. "Modelling Good and Bad Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-20, March.

  34. Markku Lanne, 2004. "Nonlinear dynamics of interest rate and inflation," Macroeconomics 0405014, University Library of Munich, Germany.

    Cited by:

    1. Michal Brzoza-Brzezina, 2004. "The Information Content of the Natural Rate of Interest: The Case of Poland," Macroeconomics 0402007, University Library of Munich, Germany.
    2. Jeremy J. Nalewaik, 2016. "Non-Linear Phillips Curves with Inflation Regime-Switching," Finance and Economics Discussion Series 2016-078, Board of Governors of the Federal Reserve System (U.S.).
    3. Masudul Hasan Adil & Shadab Danish & Sajad Ahmad Bhat & Bandi Kamaiah, 2020. "Fisher Effect: An Empirical Re-examination in Case of India," Economics Bulletin, AccessEcon, vol. 40(1), pages 262-276.
    4. Tierney, Heather L.R., 2010. "Real-Time Data Revisions and the PCE Measure of Inflation," MPRA Paper 22387, University Library of Munich, Germany, revised Apr 2010.
    5. Kauko, Karlo, 2002. "Links between securities settlement systems: An oligopoly theoretic approach," Bank of Finland Research Discussion Papers 27/2002, Bank of Finland.
    6. Dong-Hyeon Kim & Shu-Chin Lin & Joyce Hsieh & Yu-Bo Suen, 2018. "The Fisher Equation: A Nonlinear Panel Data Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(1), pages 162-180, January.
    7. Onsurang Norrbin & Aaron D. Smallwood, 2011. "Mean Reversion in the Real Interest Rate and the Effects of Calculating Expected Inflation," Southern Economic Journal, John Wiley & Sons, vol. 78(1), pages 107-130, July.
    8. Kalliovirta, Leena & Meitz, Mika & Saikkonen, Pentti, 2016. "Gaussian mixture vector autoregression," Journal of Econometrics, Elsevier, vol. 192(2), pages 485-498.
    9. Jesús Clemente & María Dolores Gadea & Antonio Montañés & Marcelo Reyes, 2017. "Structural Breaks, Inflation and Interest Rates: Evidence from the G7 Countries," Econometrics, MDPI, vol. 5(1), pages 1-17, February.
    10. Peik Granlund, 2004. "Bank exit legislation in US, EU and Japanese financial centres," Finance 0405015, University Library of Munich, Germany.
    11. Tolga Omay & Ayşegül Çorakcı & Furkan Emirmahmutoglu, 2017. "Real interest rates: nonlinearity and structural breaks," Empirical Economics, Springer, vol. 52(1), pages 283-307, February.
    12. Oscar Bajo-Rubio & Carmen Díaz-Roldán & Vicente Esteve, 2003. "Testing the Fisher Effect in the Presence of Structural Change: A Case Study of the UK,1961-2001," Economic Working Papers at Centro de Estudios Andaluces E2003_22, Centro de Estudios Andaluces.
    13. Tom Pak-wing Fong & Chun-shan Wong, 2008. "Stress Testing Banks' Credit Risk Using Mixture Vector Autoregressive Models," Working Papers 0813, Hong Kong Monetary Authority.
    14. Katarzyna Maciejowska, 2010. "Estimation Methods Comparison of SVAR Models with a Mixture of Two Normal Distributions," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 2(4), pages 279-314, September.
    15. Philipp Sibbertsen & Robinson Kruse, 2009. "Testing for a break in persistence under long‐range dependencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 263-285, May.
    16. Panopoulou, Ekaterini & Pantelidis, Theologos, 2016. "The Fisher effect in the presence of time-varying coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 495-511.
    17. Ahmed Mehedi Nizam, 2020. "How the banking system is creating a two-way inflation in an economy," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-40, April.
    18. Michal Brzoza-Brzezina, 2005. "Lending Booms in Europe’s Periphery: South-Western Lessons for Central-Eastern Members," Macroeconomics 0502002, University Library of Munich, Germany.
    19. Michael ARTIS & Ana Beatriz C. GALVÃO & Massimiliano MARCELLINO, 2003. "The transmission mechanism in a changing world," Economics Working Papers ECO2003/18, European University Institute.
    20. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2016. "Bayesian Vector Autoregressions with Non-Gaussian Shocks," CReMFi Discussion Papers 5, CReMFi, School of Economics and Finance, QMUL.
    21. Brzoza-Brzezina, Michał, 2005. "Lending booms in the new EU Member States: will euro adoption matter?," Working Paper Series 543, European Central Bank.
    22. Kushal Banik Chowdhury & Srikanta Kundu & Nityananda Sarkar, 2018. "Regime‐dependent effects of uncertainty on inflation and output growth: evidence from the United Kingdom and the United States," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(4), pages 390-413, September.
    23. Jeremy J. Nalewaik, 2015. "Regime-Switching Models for Estimating Inflation Uncertainty," Finance and Economics Discussion Series 2015-93, Board of Governors of the Federal Reserve System (U.S.).
    24. Tsong, Ching-Chuan & Lee, Cheng-Feng, 2013. "Quantile cointegration analysis of the Fisher hypothesis," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 186-198.
    25. Kushal Banik Chowdhury & Nityananda Sarkar, 2015. "The Effect of Inflation on Inflation Uncertainty in the G7 Countries: A Double Threshold GARCH Model," International Econometric Review (IER), Econometric Research Association, vol. 7(1), pages 34-50, April.
    26. Huiqing Li & Yang Su, 2021. "The nonlinear causal relationship between short‐ and long‐term interest rates: An empirical assessment of the United States, the United Kingdom, and Japan," International Finance, Wiley Blackwell, vol. 24(3), pages 332-355, December.
    27. Maciejowska, Katarzyna, 2013. "Assessing the number of components in a normal mixture: an alternative approach," MPRA Paper 50303, University Library of Munich, Germany.
    28. Stephen Hall & George Hondroyiannis & P. Swamy & George Tavlas, 2010. "The Fisher Effect Puzzle: A Case of Non-Linear Relationship?," Open Economies Review, Springer, vol. 21(1), pages 91-103, February.
    29. Dimitris K. Christopoulos & Miguel A. Le√N-Ledesma, 2007. "A Long-Run Non-Linear Approach to the Fisher Effect," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(2-3), pages 543-559, March.
    30. Gil-Alana, Luis A. & Cunado, Juncal & Gupta, Rangan, 2017. "Evidence of persistence in U.S. short and long-term interest rates," Journal of Policy Modeling, Elsevier, vol. 39(5), pages 775-789.
    31. Giorgio Canarella & Luis A. Gil-Alana & Rangan Gupta & Stephen M. Miller, 2020. "The Behavior of Real Interest Rates: New Evidence from a ``Suprasecular" Perspective," Working Papers 202093, University of Pretoria, Department of Economics.

  35. Markku Lanne & Matti Liski, 2003. "Trends and Breaks in per-capita Carbon Dioxide Emissions, 1870-2028," Working Papers 0302, Massachusetts Institute of Technology, Center for Energy and Environmental Policy Research.

    Cited by:

    1. Mar'ia Jos'e Presno & Manuel Landajo & Paula Fern'andez Gonz'alez, 2024. "Stochastic convergence in per capita CO$_2$ emissions. An approach from nonlinear stationarity analysis," Papers 2402.00567, arXiv.org.
    2. Presno, María José & Landajo, Manuel & Fernández González, Paula, 2018. "Stochastic convergence in per capita CO2 emissions. An approach from nonlinear stationarity analysis," Energy Economics, Elsevier, vol. 70(C), pages 563-581.
    3. Mariam Camarero & Juana Castillo & Andrés J. Picazo-Tadeo & Cecilio Tamarit, 2011. "Eco-efficiency and convergence in OECD countries," Working Papers 1116, Department of Applied Economics II, Universidad de Valencia.
    4. Zerbo, Eléazar & Darné, Olivier, 2019. "On the stationarity of CO2 emissions in OECD and BRICS countries: A sequential testing approach," Energy Economics, Elsevier, vol. 83(C), pages 319-332.
    5. Luis A. Gil-Alana & Juncal Cunado & Rangan Gupta, 2017. "Persistence, Mean-Reversion and Non-linearities in $$\hbox {CO2}$$ CO2 Emissions: Evidence from the BRICS and G7 Countries," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 67(4), pages 869-883, August.
    6. Le Pen, Yannick & Sévi, Benoît, 2010. "On the non-convergence of energy intensities: Evidence from a pair-wise econometric approach," Ecological Economics, Elsevier, vol. 69(3), pages 641-650, January.
    7. Dong, Feng & Li, Xiaohui & Long, Ruyin & Liu, Xiaoyan, 2013. "Regional carbon emission performance in China according to a stochastic frontier model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 525-530.
    8. Acar, Sevil & Yeldan, A. Erinç, 2018. "Investigating patterns of carbon convergence in an uneven economy: The case of Turkey," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 96-106.
    9. Westerlund, Joakim & Basher, Syed A., 2007. "Testing for Convergence in Carbon Dioxide Emissions Using a Century of Panel Data," MPRA Paper 3262, University Library of Munich, Germany.
    10. Brantley Liddle & George Messinis, 2018. "Revisiting carbon Kuznets curves with endogenous breaks modeling: evidence of decoupling and saturation (but few inverted-Us) for individual OECD countries," Empirical Economics, Springer, vol. 54(2), pages 783-798, March.
    11. Apergis, Nicholas & Eleftheriou, Sofia & Payne, James E., 2013. "The relationship between international financial reporting standards, carbon emissions, and R&D expenditures: Evidence from European manufacturing firms," Ecological Economics, Elsevier, vol. 88(C), pages 57-66.
    12. Lee, Chien-Chiang & Chang, Chun-Ping, 2008. "New evidence on the convergence of per capita carbon dioxide emissions from panel seemingly unrelated regressions augmented Dickey–Fuller tests," Energy, Elsevier, vol. 33(9), pages 1468-1475.
    13. Firouz Fallahi, 2020. "Persistence and unit root in $$\text {CO}_{2}$$CO2 emissions: evidence from disaggregated global and regional data," Empirical Economics, Springer, vol. 58(5), pages 2155-2179, May.
    14. Kim, Sei-wan & Lee, Kihoon & Nam, Kiseok, 2010. "The relationship between CO2 emissions and economic growth: The case of Korea with nonlinear evidence," Energy Policy, Elsevier, vol. 38(10), pages 5938-5946, October.
    15. Mariam Camarero & Juana Castillo-Giménez & Andrés Picazo-Tadeo & Cecilio Tamarit, 2014. "Is eco-efficiency in greenhouse gas emissions converging among European Union countries?," Empirical Economics, Springer, vol. 47(1), pages 143-168, August.
    16. Belke, Ansgar & Dobnik, Frauke & Dreger, Christian, 2011. "Energy consumption and economic growth: New insights into the cointegration relationship," Energy Economics, Elsevier, vol. 33(5), pages 782-789, September.
    17. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "Stationarity properties of per capita CO2 emissions in the OECD in the very long-run: A replication and extension analysis," Energy Economics, Elsevier, vol. 90(C).
    18. Ivanovski, Kris & Awaworyi Churchill, Sefa, 2020. "Convergence and determinants of greenhouse gas emissions in Australia: A regional analysis," Energy Economics, Elsevier, vol. 92(C).
    19. Feng Dong & Ruyin Long & Hong Chen & Xiaohui Li & Qingliang Yang, 2013. "Factors Affecting Regional Per-Capita Carbon Emissions in China Based on an LMDI Factor Decomposition Model," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-10, December.
    20. Ross McKitrick, 2007. "Why did US air pollution decline after 1970?," Empirical Economics, Springer, vol. 33(3), pages 491-513, November.
    21. Marco Barassi & Matthew Cole & Robert Elliott, 2008. "Stochastic Divergence or Convergence of Per Capita Carbon Dioxide Emissions: Re-examining the Evidence," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 40(1), pages 121-137, May.
    22. Feng Dong & Ruyin Long & Zhengfu Bian & Xihui Xu & Bolin Yu & Ying Wang, 2017. "Applying a Ruggiero three-stage super-efficiency DEA model to gauge regional carbon emission efficiency: evidence from China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(3), pages 1453-1468, July.
    23. Chang, Chun-Ping & Wen, Jun & Dong, Minyi & Hao, Yu, 2018. "Does government ideology affect environmental pollutions? New evidence from instrumental variable quantile regression estimations," Energy Policy, Elsevier, vol. 113(C), pages 386-400.
    24. Ahmed, Mumtaz & Khan, Atif Maqbool & Bibi, Salma & Zakaria, Muhammad, 2017. "Convergence of per capita CO2 emissions across the globe: Insights via wavelet analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 86-97.
    25. Dobnik, Frauke, 2011. "Energy Consumption and Economic Growth Revisited: Structural Breaks and Cross-section Dependence," Ruhr Economic Papers 303, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    26. Lee, Chien-Chiang & Chang, Chun-Ping & Chen, Pei-Fen, 2008. "Energy-income causality in OECD countries revisited: The key role of capital stock," Energy Economics, Elsevier, vol. 30(5), pages 2359-2373, September.
    27. Yanan Chen & Sheng Lin, 2015. "Study on factors affecting energy-related per capita carbon dioxide emission by multi-sectoral of cities: a case study of Tianjin," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 833-846, June.
    28. Mariam Camarero & Yurena Mendoza & Javier Ordóñez, 2011. "Re-examining CO2 emissions. Is the assessment of convergence meaningless?," Working Papers 2011/06, Economics Department, Universitat Jaume I, Castellón (Spain).
    29. Ekaterini Panopoulou & Theologos Pantelidis, 2009. "Club Convergence in Carbon Dioxide Emissions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 44(1), pages 47-70, September.
    30. Romero-Ávila, Diego, 2008. "Convergence in carbon dioxide emissions among industrialised countries revisited," Energy Economics, Elsevier, vol. 30(5), pages 2265-2282, September.
    31. Carlos Ordás Criado & Jean-Marie Grether, 2010. "Convergence in per capita CO2 emissions: a robust distributional approach," CEPE Working paper series 10-70, CEPE Center for Energy Policy and Economics, ETH Zurich.
    32. Liddle, Brantley, 2012. "Breaks and trends in OECD countries' energy–GDP ratios," Energy Policy, Elsevier, vol. 45(C), pages 502-509.
    33. Marco Barassi & Matthew Cole & Robert Elliott, 2011. "The Stochastic Convergence of CO 2 Emissions: A Long Memory Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 49(3), pages 367-385, July.
    34. Hu, Haiqing & Wei, Wei & Chang, Chun-Ping, 2019. "Do shale gas and oil productions move in convergence? An investigation using unit root tests with structural breaks," Economic Modelling, Elsevier, vol. 77(C), pages 21-33.
    35. Tiwari, Aviral Kumar & Kyophilavong, Phouphet & Albulescu, Claudiu Tiberiu, 2016. "Testing the stationarity of CO2 emissions series in Sub-Saharan African countries by incorporating nonlinearity and smooth breaks," Research in International Business and Finance, Elsevier, vol. 37(C), pages 527-540.
    36. Chang, Chun Ping & Berdiev, Aziz N., 2011. "The political economy of energy regulation in OECD countries," Energy Economics, Elsevier, vol. 33(5), pages 816-825, September.
    37. Hongze Li & FengYun Li & Xinhua Yu, 2018. "China’s Contributions to Global Green Energy and Low-Carbon Development: Empirical Evidence under the Belt and Road Framework," Energies, MDPI, vol. 11(6), pages 1-32, June.
    38. Marco R. Barassi & Nicola Spagnolo & Yuqian Zhao, 2018. "Fractional Integration Versus Structural Change: Testing the Convergence of $$\hbox {CO}_{2}$$ CO 2 Emissions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(4), pages 923-968, December.
    39. Lee, Chien-Chiang & Chang, Chun-Ping, 2009. "Stochastic convergence of per capita carbon dioxide emissions and multiple structural breaks in OECD countries," Economic Modelling, Elsevier, vol. 26(6), pages 1375-1381, November.

  36. Lanne, Markku & Saikkonen, Pentti, 2002. "Nonlinear GARCH models for highly persistent volatility," SFB 373 Discussion Papers 2002,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Nagapetyan, Artur, 2019. "Precondition stock and stock indices volatility modeling based on market diversification potential: Evidence from Russian market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 56, pages 45-61.
    2. Ngozi G. Emenogu & Monday Osagie Adenomon & Nwaze Obini Nweze, 2020. "On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-25, December.
    3. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    4. Stan Hurn & Nicholas Johnson & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Transition from the Taylor rule to the zero lower bound," CREATES Research Papers 2018-31, Department of Economics and Business Economics, Aarhus University.
    5. Emmanuel Afuecheta & Idika E. Okorie & Saralees Nadarajah & Geraldine E. Nzeribe, 2024. "Forecasting Value at Risk and Expected Shortfall of Foreign Exchange Rate Volatility of Major African Currencies via GARCH and Dynamic Conditional Correlation Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 271-304, January.
    6. Levine, Michael & Li, Jinguang (Tony), 2012. "A simple additivity test for conditionally heteroscedastic nonlinear autoregression," Computational Statistics & Data Analysis, Elsevier, vol. 56(8), pages 2421-2429.
    7. Marcelo Cunha Medeiros & Alvaro Veiga, 2004. "Modelling multiple regimes in financial volatility with a flexible coefficient GARCH model," Textos para discussão 486, Department of Economics PUC-Rio (Brazil).
    8. Day-Yang Liu & Chun-Ming Chen & Yi-Kai Su, 2020. "The Impact of COVID-19 Pandemic on the Smooth Transition Dynamics of Broad-based Indices Volatilities in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(5), pages 1-14.
    9. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    10. Tobias A. Möller & Maria Eduarda Silva & Christian H. Weiß & Manuel G. Scotto & Isabel Pereira, 2016. "Self-exciting threshold binomial autoregressive processes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 369-400, October.
    11. Teräsvirta, Timo, 2006. "An introduction to univariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 646, Stockholm School of Economics.
    12. Silvennoinen, Annastiina & Teräsvirta, Timo, 2005. "Multivariate Autoregressive Conditional Heteroskedasticity with Smooth Transitions in Conditional Correlations," SSE/EFI Working Paper Series in Economics and Finance 577, Stockholm School of Economics, revised 01 Oct 2005.
    13. Léo Parent, 2022. "The EWMA Heston model," Post-Print hal-04431111, HAL.
    14. Subbotin, Alexandre, 2009. "Volatility Models: from Conditional Heteroscedasticity to Cascades at Multiple Horizons," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 15(3), pages 94-138.
    15. Michael Dueker & Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2009. "Contemporaneous-Threshold Smooth Transition GARCH Models," Department of Economics Working Papers 2009-06, Universidad Torcuato Di Tella.
    16. Monday Osagie Adenomon & Richard Adekola Idowu, 2022. "Modelling the Impact of the COVID-19 Pandemic on Some Nigerian Sectorial Stocks: Evidence from GARCH Models with Structural Breaks," FinTech, MDPI, vol. 2(1), pages 1-20, December.
    17. Annastiina Silvennoinen & Timo Teräsvirta, 2012. "Modelling conditional correlations of asset returns: A smooth transition approach," CREATES Research Papers 2012-09, Department of Economics and Business Economics, Aarhus University.
    18. Alexander Subbotin & Thierry Chauveau & Kateryna Shapovalova, 2009. "Volatility Models: from GARCH to Multi-Horizon Cascades," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00390636, HAL.
    19. Malmsten, Hans, 2004. "Evaluating exponential GARCH models," SSE/EFI Working Paper Series in Economics and Finance 564, Stockholm School of Economics, revised 03 Sep 2004.
    20. Adrian Cantemir Calin & Tiberiu Diaconescu & Oana – Cristina Popovici, 2014. "Nonlinear Models for Economic Forecasting Applications: An Evolutionary Discussion," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 2(1), pages 42-47, June.
    21. Day Yang Liu & Ming Chen Chun & Yi Kai Su, 2021. "The impacts of Covid-19 pandemic on the smooth transition dynamics of stock market index volatilities for the Four Asian Tigers and Japan," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(4), pages 183-194, June.
    22. Vito Polito, 2020. "Nonlinear Business Cycle and Optimal Policy: A VSTAR Perspective," CESifo Working Paper Series 8060, CESifo.
    23. Stein, Michael & Islami, Mevlud & Lindemann, Jens, 2012. "Identifying time variability in stock and interest rate dependence," Discussion Papers 24/2012, Deutsche Bundesbank.

  37. Lanne, Markku & Lütkepohl, Helmut & Saikkonen, Pentti, 2002. "Comparison of Unit Root Tests for Time Series with Level Shifts," MPRA Paper 76035, University Library of Munich, Germany.

    Cited by:

    1. Assaf, Ata, 2016. "MENA stock market volatility persistence: Evidence before and after the financial crisis of 2008," Research in International Business and Finance, Elsevier, vol. 36(C), pages 222-240.
    2. Jacques Jaussaud & Serge Rey, 2012. "Long-Run Determinants of Japanese Exports to China and the United States: A Sectoral Analysis," Post-Print hal-01885297, HAL.
    3. Ettore Gallo, 2019. "Investment, Autonomous Demand and Long Run Capacity Utilization: An Empirical Test for the Euro Area," Working Papers 1904, New School for Social Research, Department of Economics.
    4. Koi Nyen Wong & Tuck Cheong Tang, 2007. "New Evidence On The Causal Linkages Between Foreign Direct Investment, Exports And Imports In Malaysia," Monash Economics Working Papers 11-07, Monash University, Department of Economics.
    5. Lee, King Fuei, 2010. "An Empirical Study of Dividend Payout and Future Earnings in Singapore," MPRA Paper 23067, University Library of Munich, Germany.
    6. Ian Babetskii & Fabrizio Coricelli & Roman Horvath, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00643340, HAL.
    7. Craigwell, Roland & Greenidge, Kevin & Maynard, Tracy, 2009. "Exchange rate regimes and monetary autonomy: Empirical evidence from selected Caribbean countries," MPRA Paper 33437, University Library of Munich, Germany.
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    139. Kalaitzi, Athanasia S. & Chamberlain, Trevor W., 2020. "Merchandise exports and economic growth: multivariate time series analysis for the United Arab Emirates," LSE Research Online Documents on Economics 103781, London School of Economics and Political Science, LSE Library.
    140. Lucke, Bernd & Lutkepohl, Helmut, 2004. "On unit root tests in the presence of transitional growth," Economics Letters, Elsevier, vol. 84(3), pages 323-327, September.
    141. Borek Vasicek, 2009. "Inflation dynamics and the New Keynesian Phillips curve in EU-4," William Davidson Institute Working Papers Series wp971, William Davidson Institute at the University of Michigan.
    142. Klinger, Sabine & Weber, Enzo, 2014. "Decomposing Beveridge curve dynamics by correlated unobserved components: The impact of labour market reforms in Germany," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100499, Verein für Socialpolitik / German Economic Association.
    143. Lorde, Troy & Jackman, Mahalia & Thomas, Chrystol, 2009. "The macroeconomic effects of oil price fluctuations on a small open oil-producing country: The case of Trinidad and Tobago," Energy Policy, Elsevier, vol. 37(7), pages 2708-2716, July.
    144. António Afonso & Sérgio Gadelha & Agatha Silva, 2020. "Public Debt And Economic Growth In Brazil," Working Papers REM 2020/0148, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    145. Yugang He & Xiaodan Gao & Renhong Wu & Yinhui Wang & Baek-Ryul Choi, 2021. "How Does Sustainable Rural Tourism Cause Rural Community Development?," Sustainability, MDPI, vol. 13(24), pages 1-20, December.
    146. Eleftheriou, Maria, 2009. "Monetary policy in Germany: A cointegration analysis on the relevance of interest rate rules," Economic Modelling, Elsevier, vol. 26(5), pages 946-960, September.
    147. Mehdi Abid & Rafaa Mraihi, 2015. "Disaggregate Energy Consumption Versus Economic Growth in Tunisia: Cointegration and Structural Break Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 6(4), pages 1104-1122, December.
    148. Stefanescu, Razvan & Dumitriu, Ramona & Nistor, Costel, 2010. "Evolution of the Romanian exports and imports in the context of the European integration," MPRA Paper 36578, University Library of Munich, Germany, revised 10 Feb 2012.
    149. Inès ABDELKAFI, 2018. "The Relationship Between Public Debt, Economic Growth, and Monetary Policy: Empirical Evidence from Tunisia," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(4), pages 1154-1167, December.
    150. Kalaitzi, Athanasia Stylianou & Chamberlain, Trevor William, 2020. "Fuel-mining exports and growth in a developing state: the case of the UAE," LSE Research Online Documents on Economics 105207, London School of Economics and Political Science, LSE Library.
    151. Paul Alagidede & George Tweneboah & Anokye M. Adam, 2008. "Nominal Exchange Rates and Price Convergence in the West African Monetary Zone," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(3), pages 181-198, December.
    152. CHOY Keen Meng, 2009. "Trade Cycles in a Re-export Economy: The Case of Singapore," Economic Growth Centre Working Paper Series 0905, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    153. Pieroni, Luca, 2009. "Does defence expenditure affect private consumption? Evidence from the United States," Economic Modelling, Elsevier, vol. 26(6), pages 1300-1309, November.
    154. Claude Diebolt & Antoine Parent & Jamel Trabelsi, 2010. "Revisiting the 1929 Crisis: Was the Fed Pre-Keynesian? New Lessons from the Past," Working Papers 10-11, Association Française de Cliométrie (AFC).
    155. Ana S. Branca & Joaquim P. Pina & Margarida Catalão-Lopes, 2012. "Corporate Giving, Competition and the Economic Cycle," Working Papers Department of Economics 2012/15, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    156. Muhammad, Shahbaz & Faridul, Islam & Naveed, Aamir, 2011. "Is devaluation contractionary? empirical evidence for Pakistan," MPRA Paper 32520, University Library of Munich, Germany, revised 01 Aug 2011.
    157. Nanthakumar Loganathan & Ang Shy Han & Mori Kogid, 2013. "Demand for Indonesia, Singapore and Thailand Tourist to Malaysia:Seasonal Unit Root and Multivariate Analysis," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 1(2), pages 15-23, Februray.
    158. Lee Chin & M. Azali, 2012. "Testing the validity of the monetary model for ASEAN with structural break," Applied Economics, Taylor & Francis Journals, vol. 44(25), pages 3229-3236, September.
    159. Emmanuel Hache & Olivier Massol, 2016. "Sanctions against Iran: An assessment of their global impact through the lens of international methanol prices," Working Papers hal-02475557, HAL.
    160. Petar Sorić & Ivana Lolić, 2015. "A note on forecasting euro area inflation: leave- $$h$$ h -out cross validation combination as an alternative to model selection," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(1), pages 205-214, March.
    161. Panagiotidis, Theodore & Rutledge, Emilie, 2007. "Oil and gas markets in the UK: Evidence from a cointegrating approach," Energy Economics, Elsevier, vol. 29(2), pages 329-347, March.
    162. Assaf, Ata, 2008. "Nonstationarity in real exchange rates using unit root tests with a level shift at unknown time," International Review of Economics & Finance, Elsevier, vol. 17(2), pages 269-278.
    163. de Souza Ramser, Claudia Aline & Souza, Adriano Mendonça & Souza, Francisca Mendonça & da Veiga, Claudimar Pereira & da Silva, Wesley Vieira, 2019. "The importance of principal components in studying mineral prices using vector autoregressive models: Evidence from the Brazilian economy," Resources Policy, Elsevier, vol. 62(C), pages 9-21.
    164. Kauko, Karlo, 2010. "The feasibility of through-the-cycle ratings," Bank of Finland Research Discussion Papers 14/2010, Bank of Finland.
    165. Anthony N. Rezitis & Konstantinos S. Stavropoulos, 2010. "Supply response and price volatility in the Greek broiler market," Agribusiness, John Wiley & Sons, Ltd., vol. 26(1), pages 25-48.

  38. Lanne, Markku & Lütkepohl, Helmut & Saikkonen, Pentti, 2001. "Test procedures for unit roots in time series with level shifts at unknown time," SFB 373 Discussion Papers 2001,39, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Lee, King Fuei, 2010. "An Empirical Study of Dividend Payout and Future Earnings in Singapore," MPRA Paper 23067, University Library of Munich, Germany.
    2. BAAK, SaangJoon, 2008. "The bilateral real exchange rates and trade between China and the U.S," China Economic Review, Elsevier, vol. 19(2), pages 117-127, June.
    3. Claudio Detotto & Edoardo Otranto, 2010. "Does Crime Affect Economic Growth?," Post-Print hal-01972848, HAL.
    4. Changli He & Rickard Sandberg, 2006. "Dickey–Fuller Type of Tests against Nonlinear Dynamic Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 835-861, December.
    5. María Lorena Marí del Cristo & Marta Gómez-Puig, 2012. "“Pass-through in dollarized countries: should Ecuador abandon the U.S. Dollar?”," IREA Working Papers 201216, University of Barcelona, Research Institute of Applied Economics, revised Oct 2012.
    6. Noriega Antonio E. & Soria Luis M. & Velázquez Ramón, 2008. "International Evidence on Stochastic and Deterministic Monetary Neutrality," Working Papers 2008-04, Banco de México.
    7. Pedro Moncarz & Sergio Barone & Ricardo Descalzi, 2018. "Shocks to the international prices of agricultural commodities and the effects on welfare and poverty. A simulation of the ex ante long-run effects for Uruguay," International Economics, CEPII research center, issue 156, pages 136-155.
    8. Livanis, Grigorios T. & Moss, Charles B., 2005. "Price Transmission and Food Scares in the U.S. Beef Sector," 2005 Annual meeting, July 24-27, Providence, RI 19485, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Silva Lopes, Artur, 2020. "Revisiting income convergence with DF-Fourier tests: old evidence with a new test," MPRA Paper 102208, University Library of Munich, Germany.
    10. Melisso Boschi & Alessandro Girardi, 2008. "The Contribution Of Domestic, Regional And International Factors To Latin America'S Business Cycle," CAMA Working Papers 2008-33, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Chia-Lin Chang & Thanchanok Khamkaew & Roengchai Tansuchat & Michael McAleer, 2011. "Interdependence of International Tourism Demand and Volatility in Leading ASEAN Destinations," Tourism Economics, , vol. 17(3), pages 481-507, June.
    12. Houssem Eddine Chebbi & Marcelo Olarreaga, 2011. "Agricultural Trade Balance and Exchange Rate Depreciation: The Case of Tunisia," Working Papers 610, Economic Research Forum, revised 08 Jan 2011.
    13. Sandberg, Rickard, 2016. "Trends, unit roots, structural changes, and time-varying asymmetries in U.S. macroeconomic data: the Stock and Watson data re-examined," Economic Modelling, Elsevier, vol. 52(PB), pages 699-713.
    14. He, Changli & Sandberg, Rickard, 2005. "Testing for Unit Roots in Nonlinear Dynamic Heterogeneous Panels," SSE/EFI Working Paper Series in Economics and Finance 582, Stockholm School of Economics.
    15. Tiwari, Aviral Kumar & Dutta, Subhendu & Dash, Aruna Kumar, 2017. "Testing of the Seasonal Unit Root Hypothesis in the Price Indices of Agricultural Commodities in India," Asian Journal of Agriculture and Development, Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), vol. 14(2), December.
    16. Joseph P. Byrne & Jun Nagayasu, 2008. "Structural Breaks in the Real Exchange Rate and Real Interest Rate Relationship," Working Papers 2008_29, Business School - Economics, University of Glasgow.
    17. Silvana Bartoletto & Bruno Chiarini & Elisabetta Marzano, 2012. "The Sustainability of Fiscal Policy in Italy: A Long-Term Perspective," CESifo Working Paper Series 3812, CESifo.
    18. Jungmittag Andre & Grupp Hariolf, 2006. "Wechselwirkungen zwischen Innovations- und Wachstumsprozessen in Deutschland 1951-1999 im Vergleich zu 1850-1913 / Dynamic Relationships Between Innovation Activities and Per Capita Income in Germany ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(2), pages 180-207, April.
    19. Yin-Wong Cheung & Risto Herrala, 2013. "China's Capital Controls - Through the Prism of Covered Interest Differentials," Working Papers 142013, Hong Kong Institute for Monetary Research.
    20. Sven Schreiber, 2011. "Estimating the natural rate of unemployment in euro-area countries with co-integrated systems," Post-Print hal-00671241, HAL.
    21. Melisso Boschi & Alessandro Girardi, 2005. "Euro Area inflation: long-run determinants and short-run dynamics," ISAE Working Papers 60, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    22. Chan, Tze-Haw, 2008. "International Parities among China and Her Major Trading Partners in Asia Pacific," MPRA Paper 15504, University Library of Munich, Germany, revised 06 Apr 2009.
    23. Tuck Cheong Tang & Koi Nyen Wong, 2009. "Research Note: The SARS Epidemic and International Visitor Arrivals to Cambodia: Is the Impact Permanent or Transitory?," Tourism Economics, , vol. 15(4), pages 883-890, December.
    24. Chan, Tze-Haw & Baharumshah, Ahmad Zubaidi, 2012. "Financial Integration between China and Asia Pacific Trading Partners: Parities Evidence from the First- and Second-generation Panel Tests," MPRA Paper 37801, University Library of Munich, Germany.
    25. He, Changli & Sandberg, Rickard, 2005. "Dickey-Fuller Type of Tests against Nonlinear Dynamic Models," SSE/EFI Working Paper Series in Economics and Finance 580, Stockholm School of Economics.
    26. Taipalus, Katja, 2012. "Signaling asset price bubbles with time-series methods," Bank of Finland Research Discussion Papers 7/2012, Bank of Finland.
    27. Lopez, Claude, 2009. "GLS-detrending and regime-wise stationarity testing in small samples," Economics Letters, Elsevier, vol. 104(2), pages 99-101, August.
    28. Tiwari, Aviral, 2010. "Is trade deficit sustainable in India? An inquiry," MPRA Paper 24451, University Library of Munich, Germany.
    29. Dumitriu, Ramona & Stefanescu, Razvan & Nistor, Costel, 2010. "Exports as an engine for the economic growth: the case of Romania," MPRA Paper 36581, University Library of Munich, Germany, revised 10 Feb 2012.
    30. Silva Lopes, Artur C., 2021. "Most likely you go your way (and I'll go mine): non-convergent incomes with a new DF-Fourier test," MPRA Paper 107676, University Library of Munich, Germany, revised 19 Mar 2021.
    31. Nistor, Costel & Stefanescu, Razvan & Dumitriu, Ramona, 2009. "The impact of the US stock market on the Romanian stock market in the context of the financial crisis," MPRA Paper 36862, University Library of Munich, Germany, revised 22 Feb 2012.
    32. Dumitriu Ramona & Stefanescu Razvan, 2009. "Analysis Of The Romanian Current Account Sustainability," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 163-168, May.
    33. Caporale, Guglielmo Maria & Onorante, Luca & Paesani, Paolo, 2010. "Inflation and inflation uncertainty in the euro area," Working Paper Series 1229, European Central Bank.
    34. Mohsen Fardmanesh & Seymour Douglas, 2008. "Foreign Exchange Controls and the Parallel Market Premium," Review of Development Economics, Wiley Blackwell, vol. 12(1), pages 72-89, February.
    35. Hassler, Uwe & Rodrigues, Paulo M. M., 2002. "Seasonal Unit Root Tests under Structural Breaks," Darmstadt Discussion Papers in Economics 113, Darmstadt University of Technology, Department of Law and Economics.
    36. Lanne, Markku & Lütkepohl, Helmut & Saikkonen, Pentti, 2001. "Test procedures for unit roots in time series with level shifts at unknown time," SFB 373 Discussion Papers 2001,39, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    37. Kalou, Sofia & Paleologou, Suzanna-Maria, 2012. "The twin deficits hypothesis: Revisiting an EMU country," Journal of Policy Modeling, Elsevier, vol. 34(2), pages 230-241.
    38. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, June.
    39. Tilak Abeysinghe & Gulasekaran Rajaguru, 2010. "A Gaussian Test for Cointegration," Macroeconomics Working Papers 23040, East Asian Bureau of Economic Research.
    40. Felippe Cauê Serigati & Paulo Furquim De Azevedo & Mario Antonio Margarido, 2014. "How Integrated Are The Main Markets Ofethanol?," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 185, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    41. Suresh K G & Aviral Kumar Tiwari, 2012. "Long Run and Short Run Linkages between Stock Indices in Bombay Stock Exchange: A Structural Cointegration Approach," Journal of Quantitative Economics, The Indian Econometric Society, vol. 10(1), pages 177-181, January.
    42. Chan, Tze-Haw & Chong, Lee Lee & Khong, Wye Leong Roy, 2008. "Real Exchange Rate Behavior: New Evidence with Linear and Non-linear Endogenous Break(s)," MPRA Paper 3406, University Library of Munich, Germany.
    43. Kim, Dukpa & Perron, Pierre, 2009. "Unit root tests allowing for a break in the trend function at an unknown time under both the null and alternative hypotheses," Journal of Econometrics, Elsevier, vol. 148(1), pages 1-13, January.
    44. Silva Lopes, Artur C. & Florin Zsurkis, Gabriel, 2017. "Are linear models really unuseful to describe business cycle data?," MPRA Paper 79413, University Library of Munich, Germany.
    45. Stefanescu, Razvan & Dumitriu, Ramona, 2010. "Impact of the global crisis on the linkages between the interest rates and the stock prices in Romania," MPRA Paper 36716, University Library of Munich, Germany, revised 16 Feb 2011.
    46. Lusine Lusinyan & John Thornton, 2011. "Unit roots, structural breaks and cointegration in the UK public finances, 1750-2004," Applied Economics, Taylor & Francis Journals, vol. 43(20), pages 2583-2592.
    47. Lopes, Artur Silva & Zsurkis, Gabriel Florin, 2017. "Are linear models really unuseful to describe business cycle data?," Economics Discussion Papers 2017-5, Kiel Institute for the World Economy (IfW Kiel).
    48. Aviral Kumar Tiwari, 2012. "Reassessment of Sustainability of Current Account Deficit in India," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 10(1), pages 67-79.
    49. Tuck Cheong Tang, 2006. "Are Imports And Exports In The Oic Member Countries Cointegrated? A Reexamination," IIUM Journal of Economics and Management, IIUM Journal of Economis and Management, vol. 14(1), pages 49-79, December.
    50. Mylonidis, Nikolaos & Paleologou, Suzanna-Maria, 2011. "The real uncovered interest parity: The case of Canada and the USA," Journal of Policy Modeling, Elsevier, vol. 33(2), pages 255-267, March.
    51. Dumitriu, Ramona & Stefanescu, Razvan & Nistor, Costel, 2009. "Cointegration and causality between Romanian exports and imports," MPRA Paper 42091, University Library of Munich, Germany, revised 06 Aug 2009.
    52. António Portugal Duarte & João Sousa Andrade & Adelaide Duarte, 2012. "Exchange Rate Mean Reversion within a Target Zone: Evidence from a Country on the Periphery of the ERM," EcoMod2012 3720, EcoMod.
    53. Paleologou, Suzanna-Maria, 2013. "Asymmetries in the revenue–expenditure nexus: A tale of three countries," Economic Modelling, Elsevier, vol. 30(C), pages 52-60.
    54. Koi Nyen Wong & Tuck Cheong Tang, 2007. "Exchange Rate Variability And The Export Demand For Malaysia'S Semiconductors: An Empirical Study," Monash Economics Working Papers 13-07, Monash University, Department of Economics.
    55. Boschi, Melisso, 2007. "Foreign capital in Latin America: A long-run structural Global VAR perspective," Economics Discussion Papers 8918, University of Essex, Department of Economics.
    56. Joseph P. Byrne & Roger Perman, 2006. "Unit Roots and Structural Breaks: A Survey of the Literature," Working Papers 2006_10, Business School - Economics, University of Glasgow.
    57. Eleftheriou, Maria, 2009. "Monetary policy in Germany: A cointegration analysis on the relevance of interest rate rules," Economic Modelling, Elsevier, vol. 26(5), pages 946-960, September.
    58. Herrala, Risto, 2014. "Forward-looking reaction to bank regulation," Working Paper Series 1645, European Central Bank.
    59. Muhammad, Shahbaz & Faridul, Islam & Naveed, Aamir, 2011. "Is devaluation contractionary? empirical evidence for Pakistan," MPRA Paper 32520, University Library of Munich, Germany, revised 01 Aug 2011.
    60. Stefanescu, Răzvan & Dumitriu, Ramona & Nistor, Costel, 2010. "Impactul investitiilor straine directe asupra exporturilor din Romania [Impact of the foreign direct investment on Romanian exports]," MPRA Paper 36563, University Library of Munich, Germany, revised 09 Feb 2012.
    61. Dumitriu, Ramona & Stefanescu, Răzvan, 2013. "Romanian current account sustainability after the adhesion to European Union," MPRA Paper 51244, University Library of Munich, Germany, revised 05 Apr 2013.
    62. Stefanescu, Razvan & Dumitriu, Ramona & Nistor, Costel, 2009. "Analysis of the dynamic relation between the currency rates and the interest rates from Romania and euro area before and during the financial crisis," MPRA Paper 41744, University Library of Munich, Germany, revised 04 Mar 2010.
    63. Andrew Coleman & John Landon-Lane, 2007. "Housing Markets and Migration in New Zealand, 1962-2006," Reserve Bank of New Zealand Discussion Paper Series DP2007/12, Reserve Bank of New Zealand.
    64. Assaf, Ata, 2008. "Nonstationarity in real exchange rates using unit root tests with a level shift at unknown time," International Review of Economics & Finance, Elsevier, vol. 17(2), pages 269-278.
    65. de Souza Ramser, Claudia Aline & Souza, Adriano Mendonça & Souza, Francisca Mendonça & da Veiga, Claudimar Pereira & da Silva, Wesley Vieira, 2019. "The importance of principal components in studying mineral prices using vector autoregressive models: Evidence from the Brazilian economy," Resources Policy, Elsevier, vol. 62(C), pages 9-21.
    66. Kauko, Karlo, 2010. "The feasibility of through-the-cycle ratings," Bank of Finland Research Discussion Papers 14/2010, Bank of Finland.

  39. Lanne, Markku & Lütkepohl, Helmut, 2001. "Unit root tests for time series with level shifts: A comparison of different proposals," SFB 373 Discussion Papers 2001,5, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Assaf, Ata, 2016. "MENA stock market volatility persistence: Evidence before and after the financial crisis of 2008," Research in International Business and Finance, Elsevier, vol. 36(C), pages 222-240.
    2. Jacques Jaussaud & Serge Rey, 2012. "Long-Run Determinants of Japanese Exports to China and the United States: A Sectoral Analysis," Post-Print hal-01885297, HAL.
    3. Ettore Gallo, 2019. "Investment, Autonomous Demand and Long Run Capacity Utilization: An Empirical Test for the Euro Area," Working Papers 1904, New School for Social Research, Department of Economics.
    4. Ian Babetskii & Fabrizio Coricelli & Roman Horvath, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00643340, HAL.
    5. Shahbaz, Muhammad & Kumar Tiwari, Aviral & Nasir, Muhammad, 2013. "The effects of financial development, economic growth, coal consumption and trade openness on CO2 emissions in South Africa," Energy Policy, Elsevier, vol. 61(C), pages 1452-1459.
    6. Enzo Weber, 2007. "Regional and Outward Economic Integration in South-East Asia," SFB 649 Discussion Papers SFB649DP2007-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Dukhanina, Ekaterina & Massol, Olivier & Lévêque, François, 2019. "Policy measures targeting a more integrated gas market: Impact of a merger of two trading zones on prices and arbitrage activity in France," Energy Policy, Elsevier, vol. 132(C), pages 583-593.
    8. Shahbaz, Muhammad, 2013. "Does financial instability increase environmental degradation? Fresh evidence from Pakistan," Economic Modelling, Elsevier, vol. 33(C), pages 537-544.
    9. Nagayasu, Jun, 2007. "Putting the dividend-price ratio under the microscope," Finance Research Letters, Elsevier, vol. 4(3), pages 186-195, September.
    10. Shahbaz, Muhammad, 2011. "Does financial instability increase environmental pollution in Pakistan?," MPRA Paper 31530, University Library of Munich, Germany, revised 27 Mar 2011.
    11. Theodore Panagiotidis & Panagiotis Printzis, 2016. "On the macroeconomic determinants of the housing market in Greece: a VECM approach," International Economics and Economic Policy, Springer, vol. 13(3), pages 387-409, July.
    12. Khayat, Guillaume A., 2018. "The impact of setting negative policy rates on banking flows and exchange rates," Economic Modelling, Elsevier, vol. 68(C), pages 1-10.
    13. Changli He & Rickard Sandberg, 2006. "Dickey–Fuller Type of Tests against Nonlinear Dynamic Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 835-861, December.
    14. Korhonen, Iikka & Mehrotra, Aaron, 2009. "Real exchange rate, output and oil: case of four large energy producers," BOFIT Discussion Papers 6/2009, Bank of Finland Institute for Emerging Economies (BOFIT).
    15. María Lorena Marí del Cristo & Marta Gómez-Puig, 2012. "“Pass-through in dollarized countries: should Ecuador abandon the U.S. Dollar?”," IREA Working Papers 201216, University of Barcelona, Research Institute of Applied Economics, revised Oct 2012.
    16. Glauben, Thomas & Loy, Jens-Peter & Körner, Julia, 2007. "Der Einfluss der Euro-Einführung auf die Preisentwicklung bei frischen Lebensmitteln in Deutschland," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 127(3), pages 457-485.
    17. Bernstein, Ronald & Madlener, Reinhard, 2015. "Short- and long-run electricity demand elasticities at the subsectoral level: A cointegration analysis for German manufacturing industries," Energy Economics, Elsevier, vol. 48(C), pages 178-187.
    18. Nawaz, Saima & Iqbal, Nasir & Anwar, Saba, 2014. "Modelling electricity demand using the STAR (Smooth Transition Auto-Regressive) model in Pakistan," Energy, Elsevier, vol. 78(C), pages 535-542.
    19. Pedro Moncarz & Sergio Barone & Ricardo Descalzi, 2018. "Shocks to the international prices of agricultural commodities and the effects on welfare and poverty. A simulation of the ex ante long-run effects for Uruguay," International Economics, CEPII research center, issue 156, pages 136-155.
    20. Brümmer, B. & Zorya, S., 2006. "Analyse von Politikeingriffen auf den Märkten für Weizen und Weizenmehl in Ukraine anhand eines Markov-Switching Fehlerkorrekturmodells," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 41, March.
    21. Khaled Chnaina & Farid Makhlouf, 2012. "Impact des Transferts de Fonds sur le Taux de Change Réel Effectif en Tunisie," Working papers of CATT hal-01885155, HAL.
    22. Kyriakos Emmanouilidis & Christos Karpetis & Erotokritos Varelas & Spyros Zikos, 2017. "The dynamic evolution of the Greek regional net fixed capital time series," Economic Change and Restructuring, Springer, vol. 50(3), pages 211-238, August.
    23. Melisso Boschi & Alessandro Girardi, 2008. "The Contribution Of Domestic, Regional And International Factors To Latin America'S Business Cycle," CAMA Working Papers 2008-33, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    24. Jáilison W. Silveira & Marcelo Resende, 2017. "Competition in the International Niobium Market: An Econometric Study," CESifo Working Paper Series 6715, CESifo.
    25. Bruno Chiarini & Elisabetta Marzano, 2014. "Urbanization and Growth: Why Did the Splendor of the Italian Cities in the Sixteenth Century not Lead to Transition?," CESifo Working Paper Series 5038, CESifo.
    26. Chia-Lin Chang & Thanchanok Khamkaew & Roengchai Tansuchat & Michael McAleer, 2011. "Interdependence of International Tourism Demand and Volatility in Leading ASEAN Destinations," Tourism Economics, , vol. 17(3), pages 481-507, June.
    27. Houssem Eddine Chebbi & Marcelo Olarreaga, 2011. "Agricultural Trade Balance and Exchange Rate Depreciation: The Case of Tunisia," Working Papers 610, Economic Research Forum, revised 08 Jan 2011.
    28. Muhammad, Shahbaz & Tiwari, Aviral & Muhammad, Nasir, 2011. "The effects of financial development, economic growth, coal consumption and trade openness on environment performance in South Africa," MPRA Paper 32723, University Library of Munich, Germany, revised 10 Aug 2011.
    29. Ralf Brueggemann & Helmut Luetkepohl, 2004. "A Small Monetary System for the Euro Area Based on German Data," Economics Working Papers ECO2004/24, European University Institute.
    30. Joseph P. Byrne & Jun Nagayasu, 2008. "Structural Breaks in the Real Exchange Rate and Real Interest Rate Relationship," Working Papers 2008_29, Business School - Economics, University of Glasgow.
    31. Silvana Bartoletto & Bruno Chiarini & Elisabetta Marzano, 2012. "The Sustainability of Fiscal Policy in Italy: A Long-Term Perspective," CESifo Working Paper Series 3812, CESifo.
    32. Jungmittag Andre & Grupp Hariolf, 2006. "Wechselwirkungen zwischen Innovations- und Wachstumsprozessen in Deutschland 1951-1999 im Vergleich zu 1850-1913 / Dynamic Relationships Between Innovation Activities and Per Capita Income in Germany ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(2), pages 180-207, April.
    33. Yin-Wong Cheung & Risto Herrala, 2013. "China's Capital Controls - Through the Prism of Covered Interest Differentials," Working Papers 142013, Hong Kong Institute for Monetary Research.
    34. Grüner, Hans Peter & Gerling, Kerstin & Brückner, Markus, 2007. "Wealth Inequality and Credit Markets: Evidence from Three Industrialized Countries," CEPR Discussion Papers 6485, C.E.P.R. Discussion Papers.
    35. Chan, Tze-Haw, 2008. "International Parities among China and Her Major Trading Partners in Asia Pacific," MPRA Paper 15504, University Library of Munich, Germany, revised 06 Apr 2009.
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  40. Lanne, Markku & Lütkepohl, Helmut & Saikkonen, Pentti, 2001. "Unit root tests in the presence of innovational outliers," SFB 373 Discussion Papers 2001,82, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Jungmittag Andre & Grupp Hariolf, 2006. "Wechselwirkungen zwischen Innovations- und Wachstumsprozessen in Deutschland 1951-1999 im Vergleich zu 1850-1913 / Dynamic Relationships Between Innovation Activities and Per Capita Income in Germany ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(2), pages 180-207, April.

  41. Markku Lanne & Pentti Saikkonen, 2001. "Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes," CeNDEF Workshop Papers, January 2001 PO5, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Leena Kalliovirta & Mika Meitz & Pentti Saikkonen, 2015. "A Gaussian Mixture Autoregressive Model for Univariate Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 247-266, March.
    2. Haas, Markus & Mittnik, Stefan & Mizrach, Bruce, 2005. "Assessing central bank credibility during the EMS crises: Comparing option and spot market-based forecasts," CFS Working Paper Series 2005/09, Center for Financial Studies (CFS).
    3. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    4. Arie Preminger & Uri Ben-zion & David Wettstein, 2007. "The extended switching regression model: allowing for multiple latent state variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 457-473.
    5. Mandler, Martin, 2007. "The Taylor rule and interest rate uncertainty in the U.S. 1955-2006," MPRA Paper 2340, University Library of Munich, Germany.
    6. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    7. Hubert Gabrisch, 2021. "GARCH Analyses of Risk and Uncertainty in the Theories of the Interest Rate of Keynes and Kalecki," wiiw Working Papers 191, The Vienna Institute for International Economic Studies, wiiw.
    8. Markku Lanne, 2006. "Nonlinear dynamics of interest rate and inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1157-1168.
    9. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    10. Maheu, John M & Yang, Qiao, 2015. "An Infinite Hidden Markov Model for Short-term Interest Rates," MPRA Paper 62408, University Library of Munich, Germany.
    11. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime Switching Garch Models," Working Papers 0605, Ben-Gurion University of the Negev, Department of Economics.
    12. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée.
    13. Nyberg, Henri, 2010. "QR-GARCH-M Model for Risk-Return Tradeoff in U.S. Stock Returns and Business Cycles," MPRA Paper 23724, University Library of Munich, Germany.
    14. Tom Pak-wing Fong & Chun-shan Wong, 2008. "Stress Testing Banks' Credit Risk Using Mixture Vector Autoregressive Models," Working Papers 0813, Hong Kong Monetary Authority.
    15. Saikkonen, Pentti, 2005. "Stability results for nonlinear error correction models," Journal of Econometrics, Elsevier, vol. 127(1), pages 69-81, July.
    16. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.
    17. Mandler, Martin, 2012. "Decomposing Federal Funds Rate forecast uncertainty using time-varying Taylor rules and real-time data," The North American Journal of Economics and Finance, Elsevier, vol. 23(2), pages 228-245.
    18. Badescu Alex & Kulperger Reg & Lazar Emese, 2008. "Option Valuation with Normal Mixture GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-42, May.
    19. Mohamed Saidane & Christian Lavergne, 2009. "Optimal Prediction with Conditionally Heteroskedastic Factor Analysed Hidden Markov Models," Computational Economics, Springer;Society for Computational Economics, vol. 34(4), pages 323-364, November.
    20. Abakah, Emmanuel Joel Aikins & Tiwari, Aviral Kumar & Alagidede, Imhotep Paul & Gil-Alana, Luis Alberiko, 2022. "Re-examination of risk-return dynamics in international equity markets and the role of policy uncertainty, geopolitical risk and VIX: Evidence using Markov-switching copulas," Finance Research Letters, Elsevier, vol. 47(PA).
    21. Arash Nademi & Rahman Farnoosh, 2014. "Mixtures of autoregressive-autoregressive conditionally heteroscedastic models: semi-parametric approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(2), pages 275-293, February.
    22. Meitz, Mika & Saikkonen, Pentti, 2021. "Testing for observation-dependent regime switching in mixture autoregressive models," Journal of Econometrics, Elsevier, vol. 222(1), pages 601-624.
    23. Lanne, Markku & Ahoniemi, Katja, 2008. "Implied Volatility with Time-Varying Regime Probabilities," MPRA Paper 23721, University Library of Munich, Germany.
    24. Carvalho, Alexandre & Skoulakis, Georgios, 2005. "Ergodicity and existence of moments for local mixtures of linear autoregressions," Statistics & Probability Letters, Elsevier, vol. 71(4), pages 313-322, March.

  42. Lanne, M., 2000. "Testing the Predictability of Stock Returns," University of Helsinki, Department of Economics 488, Department of Economics.

    Cited by:

    1. Hjalmarsson, Erik, 2008. "Interpreting long-horizon estimates in predictive regressions," Finance Research Letters, Elsevier, vol. 5(2), pages 104-117, June.
    2. David G McMillan, 2011. "Does the BEYR help predict UK sector returns?," Journal of Asset Management, Palgrave Macmillan, vol. 12(2), pages 146-156, June.
    3. Ayedi Ahmed & Marjène Gana & Stéphane Goutte & Khaled Guesmi, 2023. "Managing Portfolio Risk During the BREXIT Crisis: A Cross-Quantilogram Analysis of Stock Markets and Commodities Across European Countries, the US, and BRICS," Working Papers halshs-04068651, HAL.
    4. Ke-Li Xu & Junjie Guo, 2021. "A New Test for Multiple Predictive Regression," CAEPR Working Papers 2022-001 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    5. Narayan, Paresh Kumar & Sharma, Susan & Poon, Wai Ching & Westerlund, Joakim, 2014. "Do oil prices predict economic growth? New global evidence," Energy Economics, Elsevier, vol. 41(C), pages 137-146.
    6. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    7. Ferson, Wayne E. & Sarkissian, Sergei & Simin, Timothy, 2008. "Asset Pricing Models with Conditional Betas and Alphas: The Effects of Data Snooping and Spurious Regression," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(2), pages 331-353, June.
    8. Alex Maynard, 2006. "The forward premium anomaly: statistical artefact or economic puzzle? New evidence from robust tests," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 39(4), pages 1244-1281, November.
    9. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    10. Khurshid M. Kiani, 2016. "On Modelling and Forecasting Predictable Components in European Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 487-502, October.
    11. Michael Jansson & Marcelo J. Moreira, 2006. "Optimal Inference in Regression Models with Nearly Integrated Regressors," Econometrica, Econometric Society, vol. 74(3), pages 681-714, May.
    12. Guo, Hui & Savickas, Robert, 2006. "Idiosyncratic Volatility, Stock Market Volatility, and Expected Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 43-56, January.
    13. Paulo M.M. Rodrigues & Antonio Rubia, 2011. "A Class of Robust Tests in Augmented Predictive Regressions," Working Papers w201126, Banco de Portugal, Economics and Research Department.
    14. Mr. Guy M Meredith, 2003. "Medium-Term Exchange Rate Forecasting: What Can We Expect?," IMF Working Papers 2003/021, International Monetary Fund.
    15. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    16. Liyu Dou & Ulrich K. Müller, 2021. "Generalized Local‐to‐Unity Models," Econometrica, Econometric Society, vol. 89(4), pages 1825-1854, July.
    17. Erik Hjalmarsson, 2006. "Inference in Long-Horizon Regressions," International Finance Discussion Papers 853, Board of Governors of the Federal Reserve System (U.S.).
    18. Ioannis Kasparis & Elena Andreou & Peter C.B. Phillips, 2012. "Nonparametric Predictive Regression," Cowles Foundation Discussion Papers 1878, Cowles Foundation for Research in Economics, Yale University.
    19. Westerlund, J. & Smeekes, S., 2013. "Robust block bootstrap panel predictability tests," Research Memorandum 060, Maastricht University, Graduate School of Business and Economics (GSBE).
    20. Park, Cheolbeom, 2010. "When does the dividend-price ratio predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 81-101, January.
    21. David G. McMillan & Mark E. Wohar, 2010. "Stock return predictability and dividend-price ratio: a nonlinear approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 351-365.
    22. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "Is stock return predictability time-varying?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 152-172.
    23. Alsuhaibani, Waleed & Houmes, Robert & Wang, Daphne, 2023. "The evolution of financial reporting quality for companies listed on the Tadawul Stock Exchange in Saudi Arabia: New emerging markets' evidence," Emerging Markets Review, Elsevier, vol. 55(C).
    24. Alqahtani, Abdullah & Bouri, Elie & Vo, Xuan Vinh, 2020. "Predictability of GCC stock returns: The role of geopolitical risk and crude oil returns," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 239-249.
    25. Marekwica, Marcel & Stamos, Michael Z., 2010. "Optimal life cycle portfolio choice with housing market cycles," CFS Working Paper Series 2010/21, Center for Financial Studies (CFS).
    26. Brad S. Trinkle, 2005. "Forecasting annual excess stock returns via an adaptive network‐based fuzzy inference system," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 13(3), pages 165-177, July.
    27. David McMillan & Alan Speight, 2006. "Non-linear long horizon returns predictability: evidence from six south-east Asian markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 13(2), pages 95-111, June.
    28. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2019. "Structural instability and predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    29. Valkanov, Rossen, 2005. "Functional Central Limit Theorem approximations and the distribution of the Dickey-Fuller test with strongly heteroskedastic data," Economics Letters, Elsevier, vol. 86(3), pages 427-433, March.
    30. Charlotte S. Hansen & Bjorn E. Tuypens, 2004. "Long-Run Regressions: Theory and Application to US Asset Markets," Finance 0410018, University Library of Munich, Germany.
    31. Spierdijk, Laura & Umar, Zaghum, 2015. "Stocks, bonds, T-bills and inflation hedging: From great moderation to great recession," Journal of Economics and Business, Elsevier, vol. 79(C), pages 1-37.
    32. Eiji Kurozumi & Kohei Aono, 2011. "Estimation and Inference in Predictive Regressions," Global COE Hi-Stat Discussion Paper Series gd11-192, Institute of Economic Research, Hitotsubashi University.
    33. Guidolin, Massimo & McMillan, David G. & Wohar, Mark E., 2013. "Time varying stock return predictability: Evidence from US sectors," Finance Research Letters, Elsevier, vol. 10(1), pages 34-40.
    34. McMillan, David G., 2009. "Revisiting dividend yield dynamics and returns predictability: Evidence from a time-varying ESTR model," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 870-883, August.
    35. Fischer, Marcel & Kraft, Holger & Munk, Claus, 2013. "Asset allocation over the life cycle: How much do taxes matter?," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2217-2240.
    36. Wayne E. Ferson & Sergei Sarkissian & Timothy T. Simin, 2003. "Spurious Regressions in Financial Economics?," Journal of Finance, American Finance Association, vol. 58(4), pages 1393-1413, August.
    37. David G. McMillan, 2010. "Level‐shifts and non‐linearity in US financial ratios," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 9(2), pages 189-207, May.
    38. Nikolaos Mitianoudis & Theologos Dergiades, 2016. "Stock Prices Predictability at Long-horizons: Two Tales from the Time-Frequency Domain," Discussion Paper Series 2016_04, Department of Economics, University of Macedonia, revised Dec 2016.
    39. Katsumi Shimotsu & Alex Maynard, 2004. "Covariance-based orthogonality tests for regressors with unknown persistence," Econometric Society 2004 North American Summer Meetings 536, Econometric Society.
    40. Bianchi, Daniele & Tamoni, Andrea, 2016. "The dynamics of expected returns: evidence from multi-scale time series modelling," LSE Research Online Documents on Economics 118992, London School of Economics and Political Science, LSE Library.
    41. Westerlund, Joakim & Narayan, Paresh, 2016. "Testing for predictability in panels of any time series dimension," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1162-1177.
    42. Chevillon, Guillaume, 2017. "Robustness of Multistep Forecasts and Predictive Regressions at Intermediate and Long Horizons," ESSEC Working Papers WP1710, ESSEC Research Center, ESSEC Business School.
    43. Hjalmarsson, Erik, 2005. "On the Predictability of Global Stock Returns," Working Papers in Economics 161, University of Gothenburg, Department of Economics.
    44. Westerlund, Joakim & Narayan, Paresh Kumar, 2012. "Does the choice of estimator matter when forecasting returns?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2632-2640.
    45. Ventosa-Santaulària, Daniel & Noriega, Antonio E., 2015. "Long-run monetary neutrality under stochastic and deterministic trends," Economic Modelling, Elsevier, vol. 47(C), pages 372-382.

  43. Lanne, Markku & Saikkonen, Pentti, 2000. "Reducing size distortions of parametric stationarity tests," SFB 373 Discussion Papers 2000,12, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Vasco J. Gabriel, 2001. "Tests for the Null Hypothesis of Cointegration: a Monte Carlo Comparison," NIPE Working Papers 7/2001, NIPE - Universidade do Minho.
    2. Nunzio Cappuccio & Diego Lubian, 2010. "The fragility of the KPSS stationarity test," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(2), pages 237-253, June.
    3. Eiji Kurozumi & Shinya Tanaka, 2010. "Reducing the size distortion of the KPSS test," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 415-426, November.
    4. Jönsson, Kristian, 2006. "Finite-Sample Stability of the KPSS Test," Working Papers 2006:23, Lund University, Department of Economics.
    5. Wasel Shadat, 2011. "On the Nonparametric Tests of Univariate GARCH Regression Models," Economics Discussion Paper Series 1115, Economics, The University of Manchester.
    6. Kurozumi, Eiji, 2009. "Construction of Stationarity Tests with Less Size Distortions," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 50(1), pages 87-105, June.

  44. Lanne, M. & Saikkonen, P., 2000. "Threshold Autoregression for Strongly Autocorrelated Time Series," University of Helsinki, Department of Economics 489, Department of Economics.

    Cited by:

    1. Wolfgang Lemke & Theofanis Archontakis, 2008. "Bond pricing when the short-term interest rate follows a threshold process," Quantitative Finance, Taylor & Francis Journals, vol. 8(8), pages 811-822.
    2. Christoph Berninger & Almond Stöcker & David Rügamer, 2022. "A Bayesian time‐varying autoregressive model for improved short‐term and long‐term prediction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 181-200, January.
    3. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    4. Stanislav Anatolyev & Nikita Kobotaev, 2018. "Modeling and forecasting realized covariance matrices with accounting for leverage," Econometric Reviews, Taylor & Francis Journals, vol. 37(2), pages 114-139, February.
    5. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    6. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, Department of Economics and Business Economics, Aarhus University.
    7. Christoph Berninger & Almond Stocker & David Rugamer, 2020. "A Bayesian Time-Varying Autoregressive Model for Improved Short- and Long-Term Prediction," Papers 2006.05750, arXiv.org, revised Feb 2021.
    8. Jack Strauss & Mark E. Wohar, 2007. "Domestic‐Foreign Interest Rate Differentials: Near Unit Roots and Symmetric Threshold Models," Southern Economic Journal, John Wiley & Sons, vol. 73(3), pages 814-829, January.
    9. Jarkko Jääskelä, 2007. "More Potent Monetary Policy? Insights from a Threshold Model," RBA Research Discussion Papers rdp2007-07, Reserve Bank of Australia.
    10. Terence D.Agbeyegbe & Elena Goldman, 2005. "Estimation of threshold time series models using efficient jump MCMC," Economics Working Paper Archive at Hunter College 406, Hunter College Department of Economics, revised 2005.
    11. Theofanis Archontakis & Wolfgang Lemke, 2008. "Threshold Dynamics of Short‐term Interest Rates: Empirical Evidence and Implications for the Term Structure," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 37(1), pages 75-117, February.
    12. Timo Teräsvirta, 2017. "Nonlinear models in macroeconometrics," CREATES Research Papers 2017-32, Department of Economics and Business Economics, Aarhus University.
    13. Clive G. Bowsher & Roland Meeks, 2008. "Stationarity and the term structure of interest rates: a characterisation of stationary and unit root yield curves," Working Papers 0811, Federal Reserve Bank of Dallas.

  45. Markku Lanne, 2000. "Testing The Expectations Hypothesis Of The Term Structure Of Interest Rates In The Presence Of A Potential Regime Shift," Computing in Economics and Finance 2000 294, Society for Computational Economics.

    Cited by:

    1. Koukouritakis, Minoas, 2013. "Expectations hypothesis in the context of debt crisis: Evidence from five major EU countries," Research in Economics, Elsevier, vol. 67(3), pages 243-258.
    2. Osmani T. Guillen & Benjamin M. Tabak, 2008. "Characterizing the Brazilian Term Structure of Interest Rates," Working Papers Series 158, Central Bank of Brazil, Research Department.
    3. Minoas Koukouritakis, 2010. "Structural breaks and the expectations hypothesis of the term structure: evidence from Central European countries," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 145(4), pages 757-774, January.
    4. Harrathi Nizar & Alhoshan Hamed M., 2020. "Validity of the Expectations Hypothesis of the Term Structure of Interest Rates: The Case of Saudi Arabia," Review of Middle East Economics and Finance, De Gruyter, vol. 16(1), pages 1-18, April.
    5. Date, Paresh & Wang, Chieh, 2009. "Linear Gaussian affine term structure models with unobservable factors: Calibration and yield forecasting," European Journal of Operational Research, Elsevier, vol. 195(1), pages 156-166, May.
    6. Balázs Romhányi, 2005. "A learning hypothesis of the term structure of interest rates," Macroeconomics 0503001, University Library of Munich, Germany.
    7. Vides, José Carlos & Golpe, Antonio A. & Iglesias, Jesús, 2020. "The EHTS and the persistence in the spread reconsidered. A fractional cointegration approach," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 124-137.

Articles

  1. Markku Lanne & Keyan Liu & Jani Luoto, 2023. "Identifying Structural Vector Autoregression via Leptokurtic Economic Shocks," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1341-1351, October.

    Cited by:

    1. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.

  2. Markku Lanne & Jani Luoto, 2021. "GMM Estimation of Non-Gaussian Structural Vector Autoregression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 69-81, January.

    Cited by:

    1. Moneta, Alessio & Pallante, Gianluca, 2022. "Identification of Structural VAR Models via Independent Component Analysis: A Performance Evaluation Study," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    2. Jordi Brandts & Sabrine El Baroudi & Stefanie Huber & Christina Rott, 2022. "Gender Differences in Private and Public Goal Setting," Tinbergen Institute Discussion Papers 22-008/II, Tinbergen Institute.
    3. Ma, Cong & Cheok, Mui Yee & Chok, Nyen Vui, 2023. "Economic recovery through multisector management resources in small and medium businesses in China," Resources Policy, Elsevier, vol. 80(C).
    4. Allan W. Gregory & James McNeil & Gregor W. Smith, 2022. "US Fiscal Policy Shocks: Proxy-SVAR Overidentification via GMM," Working Paper 1461, Economics Department, Queen's University.
    5. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    6. Geert Mesters & Piotr Zwiernik, 2022. "Non-Independent Components Analysis," Working Papers 1358, Barcelona School of Economics.
    7. Alfan Mansur, 2023. "Simultaneous identification of fiscal and monetary policy shocks," Empirical Economics, Springer, vol. 65(2), pages 697-728, August.
    8. Karamysheva, Madina & Skrobotov, Anton, 2022. "Do we reject restrictions identifying fiscal shocks? identification based on non-Gaussian innovations," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    9. Dong, Chunlong & Wu, Hao & Zhou, Jianwen & Lin, Huifang & Chang, Lei, 2023. "Role of renewable energy investment and geopolitical risk in green finance development: Empirical evidence from BRICS countries," Renewable Energy, Elsevier, vol. 207(C), pages 234-241.
    10. Lukas Hoesch & Adam Lee & Geert Mesters, 2022. "Robust inference for non-Gaussian SVAR models," Economics Working Papers 1847, Department of Economics and Business, Universitat Pompeu Fabra.
    11. Zhang, Yonggang & Hyder, Mansoor & Baloch, Zulfiqar Ali & Qian, Chong & Berk Saydaliev, Hayot, 2022. "Nexus between oil price volatility and inflation: Mediating nexus from exchange rate," Resources Policy, Elsevier, vol. 79(C).
    12. Herwartz, Helmut & Wang, Shu, 2023. "Point estimation in sign-restricted SVARs based on independence criteria with an application to rational bubbles," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    13. Sascha A. Keweloh, 2023. "Uncertain Prior Economic Knowledge and Statistically Identified Structural Vector Autoregressions," Papers 2303.13281, arXiv.org.
    14. Keweloh, Sascha A. & Hetzenecker, Stephan & Seepe, Andre, 2023. "Monetary policy and information shocks in a block-recursive SVAR," Journal of International Money and Finance, Elsevier, vol. 137(C).
    15. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.
    16. Zhang, Shuzhi & Xie, Guangxiong, 2023. "Promoting green investment for renewable energy sources in China: Case study from autoregressive distributed Lagged in error correction approach," Renewable Energy, Elsevier, vol. 214(C), pages 359-368.
    17. Sascha A. Keweloh, 2023. "Structural Vector Autoregressions and Higher Moments: Challenges and Solutions in Small Samples," Papers 2310.08173, arXiv.org.
    18. Lukas Hoesch & Adam Lee & Geert Mesters, 2022. "Locally Robust Inference for Non-Gaussian SVAR Models," Working Papers 1367, Barcelona School of Economics.
    19. Li Zhe & Serhat Yüksel & Hasan Dinçer & Shahriyar Mukhtarov & Mayis Azizov, 2021. "The Positive Influences of Renewable Energy Consumption on Financial Development and Economic Growth," SAGE Open, , vol. 11(3), pages 21582440211, August.
    20. Francesco Cordoni & Nicolas Doremus & Alessio Moneta, 2023. "Identification of Vector Autoregressive Models with Nonlinear Contemporaneous Structure," LEM Papers Series 2023/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  3. Markku Lanne & Jani Luoto, 2020. "Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 425-452, April.

    Cited by:

    1. Olli Palm'en, 2022. "Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach," Papers 2202.10834, arXiv.org.
    2. Olli Palm'en, 2020. "Inflation Dynamics of Financial Shocks," Papers 2006.03301, arXiv.org.
    3. Alfan Mansur, 2023. "Simultaneous identification of fiscal and monetary policy shocks," Empirical Economics, Springer, vol. 65(2), pages 697-728, August.
    4. Braun, Robin & Brüggemann, Ralf, 2022. "Identification of SVAR models by combining sign restrictions with external instruments," Bank of England working papers 961, Bank of England.
    5. Drautzburg, Thorsten & Wright, Jonathan H, 2021. "Refining Set-Identification in VARs through Independence," Economics Working Paper Archive 64575, The Johns Hopkins University,Department of Economics.
    6. Robin Braun & Ralf Brüggemann, 2020. "Identification of SVAR Models by Combining Sign Restrictions With External Instruments," Working Paper Series of the Department of Economics, University of Konstanz 2020-01, Department of Economics, University of Konstanz.
    7. Braun, Robin, 2021. "The importance of supply and demand for oil prices: evidence from non-Gaussianity," Bank of England working papers 957, Bank of England.
    8. Herwartz, Helmut & Wang, Shu, 2023. "Point estimation in sign-restricted SVARs based on independence criteria with an application to rational bubbles," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    9. Sascha A. Keweloh, 2023. "Uncertain Prior Economic Knowledge and Statistically Identified Structural Vector Autoregressions," Papers 2303.13281, arXiv.org.
    10. Sascha A. Keweloh & Mathias Klein & Jan Pruser, 2023. "Estimating Fiscal Multipliers by Combining Statistical Identification with Potentially Endogenous Proxies," Papers 2302.13066, arXiv.org, revised Feb 2024.

  4. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.

    Cited by:

    1. Kaihatsu, Sohei & Nakajima, Jouchi, 2018. "Has trend inflation shifted?: An empirical analysis with an equally-spaced regime-switching model," Economic Analysis and Policy, Elsevier, vol. 59(C), pages 69-83.
    2. Yao, Yuan & Zhao, Yang & Li, Yan, 2022. "A volatility model based on adaptive expectations: An improvement on the rational expectations model," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Hecq Alain & Sun Li, 2021. "Selecting between causal and noncausal models with quantile autoregressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(5), pages 393-416, December.

  5. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    See citations under working paper version above.
  6. Markku Lanne & Henri Nyberg, 2016. "Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 595-603, August.
    See citations under working paper version above.
  7. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    See citations under working paper version above.
  8. Lanne Markku, 2015. "Noncausality and inflation persistence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 469-481, September.
    See citations under working paper version above.
  9. Markku Lanne & Jani Luoto, 2014. "Does Output Gap, Labour's Share or Unemployment Rate Drive Inflation?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 715-726, October.
    See citations under working paper version above.
  10. Lanne, Markku & Luoto, Jani, 2013. "Autoregression-based estimation of the new Keynesian Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 561-570.
    See citations under working paper version above.
  11. Markku Lanne & Mika Meitz & Pentti Saikkonen, 2013. "Testing for Linear and Nonlinear Predictability of Stock Returns," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 11(4), pages 682-705, September.

    Cited by:

    1. Bin Chen & Jinho Choi & Juan Carlos Escanciano, 2017. "Testing for fundamental vector moving average representations," Quantitative Economics, Econometric Society, vol. 8(1), pages 149-180, March.
    2. Alain Hecq & Daniel Velasquez-Gaviria, 2023. "Spectral identification and estimation of mixed causal-noncausal invertible-noninvertible models," Papers 2310.19543, arXiv.org.
    3. Weifeng Jin, 2023. "Quantile Autoregression-based Non-causality Testing," Papers 2301.02937, arXiv.org.
    4. Nyholm, Juho, 2017. "Residual-based diagnostic tests for noninvertible ARMA models," MPRA Paper 81033, University Library of Munich, Germany.

  12. Lanne, Markku & Saikkonen, Pentti, 2013. "Noncausal Vector Autoregression," Econometric Theory, Cambridge University Press, vol. 29(3), pages 447-481, June.
    See citations under working paper version above.
  13. HelinÄ LaakkOnen & Markku Lanne, 2013. "The Relevance Of Accuracy For The Impact Of Macroeconomic News On Exchange Rate Volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 18(4), pages 339-351, October.

    Cited by:

    1. Walid Ben Omrane & Robert Welch & Xinyao Zhou, 2020. "The dynamic effect of macroeconomic news on the euro/US dollar exchange rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 84-103, January.
    2. Yi, Chae-Deug, 2020. "Jump probability using volatility periodicity filters in US Dollar/Euro exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    3. Munazza Jabeen & Abdul Rashid & Hajra Ihsan, 2022. "The news effects on exchange rate returns and volatility: Evidence from Pakistan," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 745-769, January.
    4. Panagiotis Papaioannou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Netnomics, Springer, vol. 14(1), pages 47-68, November.

  14. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.

    Cited by:

    1. Driton Kuçi, 2015. "Contemporary Models of Organization of Power and the Macedonian Model of Organization of Power," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, September.
    2. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
    3. Gaurav Raizada & Vartika Srivastava & S. V. D. Nageswara Rao, 2020. "Shall One Sit “Longer” for a Free Lunch? Impact of Trading Durations on the Realized Variances and Volatility Spillovers," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(1), pages 1-28, March.
    4. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    5. Dohyun Chun & Donggyu Kim, 2021. "State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data," Papers 2102.13404, arXiv.org.
    6. Feng Ma & M. I. M. Wahab & Julien Chevallier & Ziyang Li, 2023. "A tug of war of forecasting the US stock market volatility: Oil futures overnight versus intraday information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 60-75, January.
    7. Meng, Xiaochun & Taylor, James W., 2018. "An approximate long-memory range-based approach for value at risk estimation," International Journal of Forecasting, Elsevier, vol. 34(3), pages 377-388.
    8. Marius Matei & Xari Rovira & Núria Agell, 2019. "Bivariate Volatility Modeling with High-Frequency Data," Econometrics, MDPI, vol. 7(3), pages 1-15, September.
    9. Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 5-31.
    10. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    11. Tianyi Wang & Sicong Cheng & Fangsheng Yin & Mei Yu, 2022. "Overnight volatility, realized volatility, and option pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1264-1283, July.
    12. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    13. Todorova, Neda & Souček, Michael, 2014. "Overnight information flow and realized volatility forecasting," Finance Research Letters, Elsevier, vol. 11(4), pages 420-428.
    14. Stavroula P. Fameliti & Vasiliki D. Skintzi, 2020. "Predictive ability and economic gains from volatility forecast combinations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 200-219, March.
    15. Luo, Jiawen & Wang, Shengquan, 2019. "The asymmetric high-frequency volatility transmission across international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 104-109.
    16. Dohyun Chun & Donggyu Kim, 2022. "State Heterogeneity Analysis of Financial Volatility using high‐frequency Financial Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 105-124, January.
    17. Lyócsa, Štefan & Todorova, Neda, 2020. "Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 628-645.
    18. Liu, Jing & Wei, Yu & Ma, Feng & Wahab, M.I.M., 2017. "Forecasting the realized range-based volatility using dynamic model averaging approach," Economic Modelling, Elsevier, vol. 61(C), pages 12-26.
    19. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.
    20. Dudley Gilder & Leonidas Tsiaras, 2020. "Volatility forecasts embedded in the prices of crude‐oil options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1127-1159, July.
    21. Jing Hao & Feng He & Feng Ma & Tong Fu, 2023. "Trading around the clock: Revisit volatility spillover between crude oil and equity markets in different trading sessions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 771-791, June.
    22. Vladimir Balash & Alexey Faizliev & Sergei Sidorov & Elena Chistopolskaya, 2021. "Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets," Mathematics, MDPI, vol. 9(19), pages 1-31, October.
    23. Wang, Cheng & Bouri, Elie & Xu, Yahua & Zhang, Dingsheng, 2023. "Intraday and overnight tail risks and return predictability in the crude oil market: Evidence from oil-related regular news and extreme shocks," Energy Economics, Elsevier, vol. 127(PB).
    24. Cathy W. S. Chen & Takaaki Koike & Wei-Hsuan Shau, 2024. "Tail risk forecasting with semi-parametric regression models by incorporating overnight information," Papers 2402.07134, arXiv.org.
    25. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    26. Oktay Ozkan, 2020. "Time-varying return predictability and adaptive markets hypothesis: Evidence on MIST countries from a novel wild bootstrap likelihood ratio approach," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(2), pages 101-113.
    27. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2016. "Forecasting stock volatility using after-hour information: Evidence from the Australian Stock Exchange," Economic Modelling, Elsevier, vol. 52(PB), pages 592-608.
    28. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
    29. Luo, Jiawen & Marfatia, Hardik A. & Ji, Qiang & Klein, Tony, 2023. "Co-volatility and asymmetric transmission of risks between the global oil and China's futures markets," Energy Economics, Elsevier, vol. 117(C).
    30. Liang, Chao & Li, Yan & Ma, Feng & Wei, Yu, 2021. "Global equity market volatilities forecasting: A comparison of leverage effects, jumps, and overnight information," International Review of Financial Analysis, Elsevier, vol. 75(C).
    31. Reinhard Ellwanger, 2017. "On the Tail Risk Premium in the Oil Market," Staff Working Papers 17-46, Bank of Canada.
    32. Chu, Xiaojun & Wan, Xinmin & Qiu, Jianying, 2023. "The relative importance of overnight sentiment versus trading-hour sentiment in volatility forecasting," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).

  15. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
    See citations under working paper version above.
  16. Henri Nyberg & Markku Lanne & Erkka Saarinen, 2012. "Does noncausality help in forecasting economic time series?," Economics Bulletin, AccessEcon, vol. 32(4), pages 2849-2859.

    Cited by:

    1. Hecq, A.W. & Lieb, L.M. & Telg, J.M.A., 2015. "Identification of Mixed Causal-Noncausal Models : How Fat Should We Go?," Research Memorandum 035, Maastricht University, Graduate School of Business and Economics (GSBE).
    2. Frédérique Bec & Heino Bohn Nielsen & Sarra Saïdi, 2020. "Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1413-1428, December.
    3. Gouriéroux, Christian & Zakoian, Jean-Michel, 2016. "Local Explosion Modelling by Noncausal Process," MPRA Paper 71105, University Library of Munich, Germany.
    4. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    5. Nyberg, Henri & Saikkonen, Pentti, 2014. "Forecasting with a noncausal VAR model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 536-555.
    6. Alain Hecq & Sean Telg & Lenard Lieb, 2017. "Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?," Econometrics, MDPI, vol. 5(4), pages 1-22, October.
    7. Giurcanu, Mihai C., 2015. "A simulation algorithm for non-causal VARMA processes," Statistics & Probability Letters, Elsevier, vol. 98(C), pages 65-72.
    8. Hecq, Alain & Voisin, Elisa, 2021. "Forecasting bubbles with mixed causal-noncausal autoregressive models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 29-45.
    9. Fries, Sébastien, 2018. "Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds," MPRA Paper 97353, University Library of Munich, Germany, revised Nov 2019.
    10. Christian Gourieroux & Joann Jasiak & Michelle Tong, 2021. "Convolution‐based filtering and forecasting: An application to WTI crude oil prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1230-1244, November.
    11. Fries, Sébastien & Zakoian, Jean-Michel, 2017. "Mixed Causal-Noncausal AR Processes and the Modelling of Explosive Bubbles," MPRA Paper 81345, University Library of Munich, Germany.
    12. Jean-Baptiste MICHAU, 2019. "Helicopter Drops of Money under Secular Stagnation," Working Papers 2019-10, Center for Research in Economics and Statistics.
    13. Hecq, Alain & Issler, João Victor & Telg, Sean, 2017. "Mixed Causal-Noncausal Autoregressions with Strictly Exogenous Regressors," MPRA Paper 80767, University Library of Munich, Germany.
    14. Nyholm, Juho, 2017. "Residual-based diagnostic tests for noninvertible ARMA models," MPRA Paper 81033, University Library of Munich, Germany.

  17. Lanne, Markku & Luoto, Jani, 2012. "Has US inflation really become harder to forecast?," Economics Letters, Elsevier, vol. 115(3), pages 383-386.
    See citations under working paper version above.
  18. Markku Lanne & Arto Luoma & Jani Luoto, 2012. "Bayesian Model Selection And Forecasting In Noncausal Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 812-830, August.
    See citations under working paper version above.
  19. Lanne Markku & Saikkonen Pentti, 2011. "Noncausal Autoregressions for Economic Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-32, October.
    See citations under working paper version above.
  20. Markku Lanne & Pentti Saikkonen, 2011. "GMM Estimation with Non‐causal Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 581-592, October.
    See citations under working paper version above.
  21. Lanne, Markku & Lütkepohl, Helmut, 2010. "Structural Vector Autoregressions With Nonnormal Residuals," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 159-168.
    See citations under working paper version above.
  22. Lanne, Markku & Lütkepohl, Helmut & Maciejowska, Katarzyna, 2010. "Structural vector autoregressions with Markov switching," Journal of Economic Dynamics and Control, Elsevier, vol. 34(2), pages 121-131, February.
    See citations under working paper version above.
  23. Markku Lanne & Timo Vesala, 2010. "The effect of a transaction tax on exchange rate volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(2), pages 123-133.
    See citations under working paper version above.
  24. Ahoniemi, Katja & Lanne, Markku, 2009. "Joint modeling of call and put implied volatility," International Journal of Forecasting, Elsevier, vol. 25(2), pages 239-258.
    See citations under working paper version above.
  25. Markku Lanne, 2009. "Properties of Market-Based and Survey Macroeconomic Forecasts for Different Data Releases," Economics Bulletin, AccessEcon, vol. 29(3), pages 2231-2240.

    Cited by:

    1. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-003/4, Tinbergen Institute.
    2. Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2013. "Time-varying combinations of predictive densities using nonlinear filtering," Journal of Econometrics, Elsevier, vol. 177(2), pages 213-232.
    3. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-172/4, Tinbergen Institute.

  26. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2009. "A naïve sticky information model of households' inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1332-1344, June.
    See citations under working paper version above.
  27. Laakkonen Helinä & Lanne Markku, 2009. "Asymmetric News Effects on Exchange Rate Volatility: Good vs. Bad News in Good vs. Bad Times," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-38, December.
    See citations under working paper version above.
  28. Lanne, Markku & Luoto, Jani, 2008. "Robustness of the risk-return relationship in the U.S. stock market," Finance Research Letters, Elsevier, vol. 5(2), pages 118-127, June.
    See citations under working paper version above.
  29. Markku Lanne & Helmut L‹Tkepohl, 2008. "Identifying Monetary Policy Shocks via Changes in Volatility," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(6), pages 1131-1149, September.
    See citations under working paper version above.
  30. Lanne, Markku, 2007. "Forecasting realized exchange rate volatility by decomposition," International Journal of Forecasting, Elsevier, vol. 23(2), pages 307-320.

    Cited by:

    1. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    2. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    3. Lin, Xiaoqiang & Fei, Fangyu & Wang, Yudong, 2011. "Analysis of the efficiency of the Shanghai stock market: A volatility perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3486-3495.
    4. Ahoniemi, Katja & Lanne, Markku, 2007. "Joint Modeling of Call and Put Implied Volatility," MPRA Paper 6318, University Library of Munich, Germany.
    5. Yin Liao & Heather M. Anderson & Farshid Vahid, 2010. "Do Jumps Matter? Forecasting Multivariate Realized Volatility allowing for Common Jumps," Monash Econometrics and Business Statistics Working Papers 11/10, Monash University, Department of Econometrics and Business Statistics.
    6. Beum-Jo Park, 2011. "Forecasting Volatility in Financial Markets Using a Bivariate Stochastic Volatility Model with Surprising Information," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 37-58, September.
    7. Grossmann, Axel & Orlov, Alexei G., 2022. "Exchange rate misalignments, capital flows and volatility," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    8. J. Piplack & M. Beine & B. Candelon, 2009. "Comovements of Returns and Volatility in International Stock Markets: A High-Frequency Approach," Working Papers 09-10, Utrecht School of Economics.
    9. Grossmann, Axel & Orlov, Alexei G., 2012. "Exchange rate misalignments in frequency domain," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 185-199.
    10. Grossmann, Axel & Love, Inessa & Orlov, Alexei G., 2014. "The dynamics of exchange rate volatility: A panel VAR approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 1-27.
    11. Jian Zhou, 2017. "Forecasting REIT volatility with high-frequency data: a comparison of alternative methods," Applied Economics, Taylor & Francis Journals, vol. 49(26), pages 2590-2605, June.
    12. Gao, Shang & Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie, 2023. "Forecasting stock market volatility: The sum of the parts is more than the whole," Finance Research Letters, Elsevier, vol. 55(PA).

  31. Markku Lanne & Saikkonen Pentti, 2007. "Modeling Conditional Skewness in Stock Returns," The European Journal of Finance, Taylor & Francis Journals, vol. 13(8), pages 691-704.
    See citations under working paper version above.
  32. Lanne, Markku & Saikkonen, Pentti, 2007. "A Multivariate Generalized Orthogonal Factor GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 61-75, January.
    See citations under working paper version above.
  33. Lanne, Markku & Saikkonen, Pentti, 2006. "Why is it so difficult to uncover the risk-return tradeoff in stock returns?," Economics Letters, Elsevier, vol. 92(1), pages 118-125, July.

    Cited by:

    1. Jan Antell & Mika Vaihekoski, 2011. "Pricing currency risk in the stock market: Empirical evidence from Finland and Sweden 1970-2009," Discussion Papers 63, Aboa Centre for Economics.
    2. Emma M. Iglesias & Garry D. A. Phillips, 2012. "Estimation, Testing, and Finite Sample Properties of Quasi-Maximum Likelihood Estimators in GARCH-M Models," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 532-557, September.
    3. Wu, Shue-Jen & Lee, Wei-Ming, 2015. "Intertemporal risk–return relationships in bull and bear markets," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 308-325.
    4. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
    5. Esben Hedegaard & Robert J. Hodrick, 2014. "Estimating the Risk-Return Trade-off with Overlapping Data Inference," NBER Working Papers 19969, National Bureau of Economic Research, Inc.
    6. Naqi Shah, Sadia & Qayyum, Abdul, 2016. "Analyse Risk-Return Paradox: Evidence from Electricity Sector of Pakistan," MPRA Paper 85528, University Library of Munich, Germany.
    7. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam, 2019. "An empirical examination of the jump and diffusion aspects of asset pricing: Japanese evidence," Working Papers 2019-02, University of Tasmania, Tasmanian School of Business and Economics.
    8. Mohanty, Roshni & P, Srinivasan, 2014. "The Time-Varying Risk and Return Trade Off in Indian Stock Markets," MPRA Paper 55660, University Library of Munich, Germany.
    9. Cedric Okou & Eric Jacquier, 2014. "Horizon Effect in the Term Structure of Long-Run Risk-Return Trade-Offs," CIRANO Working Papers 2014s-36, CIRANO.
    10. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.
    11. Okou, Cédric & Jacquier, Éric, 2016. "Horizon effect in the term structure of long-run risk-return trade-offs," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 445-466.
    12. Michelfelder, Richard A., 2015. "Empirical analysis of the generalized consumption asset pricing model: Estimating the cost of capital," Journal of Economics and Business, Elsevier, vol. 80(C), pages 37-50.
    13. Nyberg, Henri, 2010. "QR-GARCH-M Model for Risk-Return Tradeoff in U.S. Stock Returns and Business Cycles," MPRA Paper 23724, University Library of Munich, Germany.
    14. Laakkonen, Helinä & Lanne, Markku, 2008. "Asymmetric News Effects on Volatility: Good vs. Bad News in Good vs. Bad Times," MPRA Paper 8296, University Library of Munich, Germany.
    15. Andrew Harvey & Rutger-Jan Lange, 2015. "Modeling the Interactions between Volatility and Returns," Cambridge Working Papers in Economics 1518, Faculty of Economics, University of Cambridge.
    16. Huang, Lin & Wang, Zijun, 2014. "Is the investment factor a proxy for time-varying investment opportunities? The US and international evidence," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 219-232.
    17. Guo, Hui & Neely, Christopher J., 2008. "Investigating the intertemporal risk-return relation in international stock markets with the component GARCH model," Economics Letters, Elsevier, vol. 99(2), pages 371-374, May.
    18. Perras, Patrizia & Wagner, Niklas, 2020. "Pricing equity-bond covariance risk: Between flight-to-quality and fear-of-missing-out," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).
    19. Esben Hedegaard & Robert J. Hodrick, 2014. "Measuring the Risk-Return Tradeoff with Time-Varying Conditional Covariances," NBER Working Papers 20245, National Bureau of Economic Research, Inc.
    20. Kanas, Angelos, 2012. "Modelling the risk–return relation for the S&P 100: The role of VIX," Economic Modelling, Elsevier, vol. 29(3), pages 795-809.
    21. Jiranyakul, Komain, 2011. "On the Risk-Return Tradeoff in the Stock Exchange of Thailand: New Evidence," MPRA Paper 45583, University Library of Munich, Germany.
    22. Licheng Sun & Liang Meng & Mohammad Najand, 2017. "The Role of U.S. Market on International Risk-Return Tradeoff Relations," The Financial Review, Eastern Finance Association, vol. 52(3), pages 499-526, August.
    23. Bandi, Federico M. & Perron, Benoît, 2008. "Long-run risk-return trade-offs," Journal of Econometrics, Elsevier, vol. 143(2), pages 349-374, April.
    24. Othieno, Ferdinand & Biekpe, Nicholas, 2019. "Estimating the conditional equity risk premium in African frontier markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 538-551.
    25. Pauline Ahern & Frank Hanley & Richard Michelfelder, 2011. "New approach to estimating the cost of common equity capital for public utilities," Journal of Regulatory Economics, Springer, vol. 40(3), pages 261-278, December.
    26. Andrew Harvey & Rutger‐Jan Lange, 2018. "Modeling the Interactions between Volatility and Returns using EGARCH‐M," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 909-919, November.
    27. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.

  34. Markku Lanne, 2006. "Nonlinear dynamics of interest rate and inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1157-1168.
    See citations under working paper version above.
  35. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(4), pages 594-616.
    See citations under working paper version above.
  36. Markku Lanne & Pentti Saikkonen, 2005. "Non-linear GARCH models for highly persistent volatility," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 251-276, July.
    See citations under working paper version above.
  37. Markku Lanne and Matti Liski, 2004. "Trends and Breaks in Per-Capita Carbon Dioxide Emissions, 1870-2028," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 41-66.
    See citations under working paper version above.
  38. Markku Lanne, 2003. "Testing the Expectations Hypothesis of the Term Structure of Interest Rates in the Presence of a Potential Regime Shift," Manchester School, University of Manchester, vol. 71(s1), pages 54-67, September. See citations under working paper version above.
  39. Markku Lanne & Pentti Saikkonen, 2003. "Reducing size distortions of parametric stationarity tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 423-439, July.
    See citations under working paper version above.
  40. Markku Lanne & Helmut Lütkepohl & Pentti Saikkonen, 2003. "Test Procedures for Unit Roots in Time Series with Level Shifts at Unknown Time," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(1), pages 91-115, February.
    See citations under working paper version above.
  41. Markku Lanne & Pentti Saikkonen, 2003. "Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 1(1), pages 96-125.
    See citations under working paper version above.
  42. Markku Lanne, 2002. "Testing The Predictability Of Stock Returns," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 407-415, August. See citations under working paper version above.
  43. Markku Lanne & Helmut Lütkepohl & Pentti Saikkonen, 2002. "Comparison of unit root tests for time series with level shifts," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(6), pages 667-685, November.
    See citations under working paper version above.
  44. Lanne, Markku & Saikkonen, Pentti, 2002. "Threshold Autoregressions for Strongly Autocorrelated Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 282-289, April. See citations under working paper version above.
  45. Lanne, Markku & Lutkepohl, Helmut, 2002. "Unit root tests for time series with level shifts: a comparison of different proposals," Economics Letters, Elsevier, vol. 75(1), pages 109-114, March.
    See citations under working paper version above.
  46. Markku Lanne, 2001. "Near unit root and the relationship between inflation and interest rates: A reexamination of the Fisher effect," Empirical Economics, Springer, vol. 26(2), pages 357-366.

    Cited by:

    1. Erik Hjalmarsson & Pär Österholm, 2010. "Testing for cointegration using the Johansen methodology when variables are near-integrated: size distortions and partial remedies," Empirical Economics, Springer, vol. 39(1), pages 51-76, August.
    2. Sophocles N. Brissimis & Petros M. Migiakis, 2013. "Inflation persistence and the rationality of inflation expectations," Working Papers 151, Bank of Greece.
    3. Dimitris A. Georgoutsos & Petros M. Migiakis, 2009. "Benchmark bonds interactions under regime shifts," Working Papers 103, Bank of Greece.
    4. Markku Lanne, 2006. "Nonlinear dynamics of interest rate and inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1157-1168.
    5. Jang, Tae-Seok & Sacht, Stephen, 2021. "Forecast heuristics, consumer expectations, and New-Keynesian macroeconomics: A Horse race," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 493-511.
    6. Harun UCAK & Ilhan OZTURK & Alper ASLAN, 2014. "An Examination of Fisher Effect for Selected New EU Member States," International Journal of Economics and Financial Issues, Econjournals, vol. 4(4), pages 956-959.
    7. Rajmund MIRDALA, 2015. "Decomposing Euro Area Sovereign Debt Yields into Inflation Expectations and Expected Real Interest Rates," Journal of Advanced Research in Law and Economics, ASERS Publishing, vol. 6(4), pages 714-737.
    8. Mpho Bosupeng, 2015. "The Fisher Effect Using Differences in The Deterministic Term," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 5(4), pages 1031-1031.
    9. Lai, Kon S., 2004. "On structural shifts and stationarity of the ex ante real interest rate," International Review of Economics & Finance, Elsevier, vol. 13(2), pages 217-228.
    10. Hüseyin Şen & Ayşe Kaya & Savaş Kaptan & Metehan Cömert, 2019. "Interest rates, inflation, and exchange rates in fragile EMEs: A fresh look at the long-run interrelationships," Working Papers halshs-02095652, HAL.
    11. Sofiane H. Sekioua, 2004. "Real interest parity (RIP) over the 20th century: New evidence based on confidence intervals for the dominant root and half-lives of shocks," Money Macro and Finance (MMF) Research Group Conference 2004 91, Money Macro and Finance Research Group.
    12. Nektarios Aslanidis & Selva Demiralp, 2020. "Has the Financial Crisis affected the Real Interest Rate Dynamics in Europe?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(1), pages 1-18, April.
    13. Jesús Clemente & María Dolores Gadea & Antonio Montañés & Marcelo Reyes, 2017. "Structural Breaks, Inflation and Interest Rates: Evidence from the G7 Countries," Econometrics, MDPI, vol. 5(1), pages 1-17, February.
    14. Soon, Siew-Voon & Baharumshah, Ahmad Zubaidi & Mohamad Shariff, Nurul Sima, 2017. "The persistence in real interest rates: Does it solve the intertemporal consumption behavior puzzle?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 36-51.
    15. Meredith J. Beechey & Erik Hjalmarsson & Pär Österholm, 2008. "Testing the expectations hypothesis when interest rates are near integrated," International Finance Discussion Papers 953, Board of Governors of the Federal Reserve System (U.S.).
    16. Georgoutsos, Dimitris A. & Migiakis, Petros M., 2013. "Heterogeneity of the determinants of euro-area sovereign bond spreads; what does it tell us about financial stability?," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4650-4664.
    17. Helen Louri & Petros M. Migiakis, 2016. "Bank Lending Margins in the Euro Area: The Effects of Financial Fragmentation and ECB Policies," LEQS – LSE 'Europe in Question' Discussion Paper Series 105, European Institute, LSE.
    18. Mustafa Kasim & Bentouir Naima, 2018. "The Relationship Between Inflation Rate and Nominal Interest Rate in Bolivarian Republic Of Venezuela: Revisiting Fisher’s Hypothesis," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 7(4), pages 214-224, November.
    19. Lai, Kon S., 2008. "The puzzling unit root in the real interest rate and its inconsistency with intertemporal consumption behavior," Journal of International Money and Finance, Elsevier, vol. 27(1), pages 140-155, February.
    20. Helen Louri & Petros M. Migiakis, 2015. "Determinants of euro-area bank lending margins: financial fragmentation and ECB policies," Working Papers 198, Bank of Greece.
    21. Bosupeng, Mpho, 2016. "The Effects of Chinese Interest Rates and Inflation: A Decomposition of The Fisher Effect," MPRA Paper 78160, University Library of Munich, Germany, revised 2016.
    22. Mirdala, Rajmund, 2012. "Interest Rates Determination and Crisis Puzzle (Empirical Evidence from the European Transition Economies)," MPRA Paper 43756, University Library of Munich, Germany.
    23. Bosupeng, Mpho, 2016. "On The Fisher Effect: A Review," MPRA Paper 77916, University Library of Munich, Germany, revised 2016.
    24. Dimitris A. Georgoutsos & Petros Migiakis, 2010. "European sovereign bond spreads: monetary unification, market conditions and financial integration," Working Papers 115, Bank of Greece.

  47. Markku Lanne, 2000. "Near unit roots, cointegration, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 513-529.

    Cited by:

    1. Erik Hjalmarsson & Pär Österholm, 2010. "Testing for cointegration using the Johansen methodology when variables are near-integrated: size distortions and partial remedies," Empirical Economics, Springer, vol. 39(1), pages 51-76, August.
    2. Hjalmarsson, Erik & Österholm, Pär, 2017. "Households’ Mortgage-Rate Expectations: More Realistic than at First Glance?," Working Papers 2017:9, Örebro University, School of Business.
    3. Sophocles N. Brissimis & Petros M. Migiakis, 2013. "Inflation persistence and the rationality of inflation expectations," Working Papers 151, Bank of Greece.
    4. Dimitris A. Georgoutsos & Petros M. Migiakis, 2009. "Benchmark bonds interactions under regime shifts," Working Papers 103, Bank of Greece.
    5. Ripamonti, Alexandre, 2013. "Rational Valuation Formula (RVF) and Time Variability in Asset Rates of Return," MPRA Paper 79460, University Library of Munich, Germany.
    6. Sarno, Lucio & Thornton, Daniel L, 2002. "The Dynamic Relationship Between the Federal Funds rate and the Treasury Bill Rate: An Empirical Investigation," CEPR Discussion Papers 3225, C.E.P.R. Discussion Papers.
    7. Silva Lopes, Artur C. B. da & Monteiro, Olga Susana, 2008. "Short and long run tests of the expectations hypothesis: the Portuguese case," MPRA Paper 12001, University Library of Munich, Germany.
    8. Fabrizio Iacone, 2009. "A Semiparametric Analysis of the Term Structure of the US Interest Rates," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(4), pages 475-490, August.
    9. Knezevic, David & Nordström, Martin & Österholm, Pär, 2019. "The Relation between Municipal and Government Bond Yields in an Era of Unconventional Monetary Policy," Working Papers 2019:6, Örebro University, School of Business.
    10. Meredith J. Beechey & Erik Hjalmarsson & Pär Österholm, 2008. "Testing the expectations hypothesis when interest rates are near integrated," International Finance Discussion Papers 953, Board of Governors of the Federal Reserve System (U.S.).
    11. Petros M. Migiakis, 2012. "Reviewing the proposals for common bond issuances by the euro-area sovereign under a long-term perspective," Economic Bulletin, Bank of Greece, issue 37, pages 43-54, December.
    12. Sarno, Lucio & Daniel l Thornton & Giorgio Valente, 2003. "Federal Funds Rate Prediction," Royal Economic Society Annual Conference 2003 183, Royal Economic Society.
    13. Chew Lian Chua & Chin Nam Low, 2007. "Permanent Structural Change in the US Short-Term and Long-Term Interest Rates," Melbourne Institute Working Paper Series wp2007n22, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    14. Zacharias Bragoudakis & Dimitrios Sideris, 2012. "Do retail gasoline prices adjust symmetrically to crude oil price changes? the case of the Greek oil market," Economic Bulletin, Bank of Greece, issue 37, pages 7-21, December.
    15. Silva Lopes, Artur C. & Monteiro, Olga Susana, 2007. "The Expectations Hypothesis of the Term Structure: Some Empirical Evidence for Portugal," MPRA Paper 6310, University Library of Munich, Germany, revised 14 Dec 2007.
    16. Vicente Esteve & Manuel Navarro-Ibáñez & Maria A. Prats, 2010. "The Spanish term structure of interest rates revisited: cointegration with multiple structural breaks, 1974-2010," Working Papers 1001, Department of Applied Economics II, Universidad de Valencia.
    17. Khalaf, Lynda & Urga, Giovanni, 2014. "Identification robust inference in cointegrating regressions," Journal of Econometrics, Elsevier, vol. 182(2), pages 385-396.
    18. Costas N. Kanellopoulos, 2012. "The Size and structure of uninsured employment," Economic Bulletin, Bank of Greece, issue 37, pages 23-41, December.
    19. Georgoutsos, Dimitris A. & Migiakis, Petros M., 2013. "Heterogeneity of the determinants of euro-area sovereign bond spreads; what does it tell us about financial stability?," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4650-4664.
    20. Nikitas Pittis & Christina Christou & Sarantis Kalyvitis & Christis Hassapis, 2009. "Long‐Run PPP under the Presence of Near‐to‐Unit Roots: The Case of the British Pound–US Dollar Rate," Review of International Economics, Wiley Blackwell, vol. 17(1), pages 144-155, February.
    21. Nagayasu, Jun, 2002. "On the term structure of interest rates and inflation in Japan," Journal of Economics and Business, Elsevier, vol. 54(5), pages 505-523.
    22. Karlsson, Sune & Österholm, Pär, 2019. "Volatilities, drifts and the relation between treasury yields and the corporate bond yield spread in australia," Finance Research Letters, Elsevier, vol. 30(C), pages 378-384.
    23. Singh, Manish K. & Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2021. "Quantifying sovereign risk in the euro area," Economic Modelling, Elsevier, vol. 95(C), pages 76-96.
    24. Lizardo Radhames A. & Mollick Andre Varella, 2011. "The Impact of Chinese Purchases of U.S. Government Debt on the Treasury Yield Curve," Global Economy Journal, De Gruyter, vol. 11(4), pages 1-23, December.
    25. Haug Alfred A & Siklos Pierre L, 2006. "The Behavior of Short-Term Interest Rates: International Evidence of Non-Linear Adjustment," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(4), pages 1-34, December.
    26. Dimitris A. Georgoutsos & Petros Migiakis, 2010. "European sovereign bond spreads: monetary unification, market conditions and financial integration," Working Papers 115, Bank of Greece.
    27. Lima, Luiz Renato & Xiao, Zhijie, 2007. "Do shocks last forever? Local persistency in economic time series," Journal of Macroeconomics, Elsevier, vol. 29(1), pages 103-122, March.
    28. Kosei Fukuda, 2011. "Cointegration rank switching model: an application to forecasting interest rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(5), pages 509-522, August.

  48. Markku Lanne, 1999. "Near Unit Roots And The Predictive Power Of Yield Spreads For Changes In Long-Term Interest Rates," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 393-398, August.

    Cited by:

    1. Sébastien Morin, 2004. "Ruptures structurelles sur les marchés action et obligataire américains : preuve empirique à partir de la méthode de Saikkönen," Economie & Prévision, La Documentation Française, vol. 166(5), pages 87-98.
    2. Peter Reinhard Hansen, 2000. "Structural Changes in the Cointegrated Vector Autoregressive Model," Working Papers 2000-20, Brown University, Department of Economics.
    3. Bulkley, George & Giordani, Paolo, 2011. "Structural breaks, parameter uncertainty, and term structure puzzles," Journal of Financial Economics, Elsevier, vol. 102(1), pages 222-232, October.
    4. Sarno, Lucio & Thornton, Daniel L, 2002. "The Dynamic Relationship Between the Federal Funds rate and the Treasury Bill Rate: An Empirical Investigation," CEPR Discussion Papers 3225, C.E.P.R. Discussion Papers.
    5. Martin T. Bohl & Pierre L. Siklos, 2004. "The Bundesbank's Inflation Policy and Asymmetric Behavior of the German Term Structure," Review of International Economics, Wiley Blackwell, vol. 12(3), pages 495-508, August.
    6. Markku Lanne, 2003. "Testing the Expectations Hypothesis of the Term Structure of Interest Rates in the Presence of a Potential Regime Shift," Manchester School, University of Manchester, vol. 71(s1), pages 54-67, September.
    7. Alfred A. Haug & Pierre L. Siklos, 2002. "The Term Spread International Evidence of Non-Linear Adjustment," Working Papers 2002_08, York University, Department of Economics, revised Jul 2004.
    8. Sarno, Lucio & Daniel l Thornton & Giorgio Valente, 2003. "Federal Funds Rate Prediction," Royal Economic Society Annual Conference 2003 183, Royal Economic Society.
    9. Guidolin, Massimo & Thornton, Daniel L., 2018. "Predictions of short-term rates and the expectations hypothesis," International Journal of Forecasting, Elsevier, vol. 34(4), pages 636-664.
    10. Frédérique BEC & Charbel BASSIL, 2008. "Federal Funds Rate Stationarity: New Evidence," THEMA Working Papers 2008-35, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    11. Sugita, Katsuhiro & 杉田, 勝弘, 2006. "Time Series Analysis of the Expectations Hypothesis for the Japanese Term Structure of Interest Rates in the Presence of Multiple Structural Breaks," Discussion Papers 2006-15, Graduate School of Economics, Hitotsubashi University.
    12. Peter Reinhard Hansen, 2000. "Structural Breaks in the Cointegrated Vector Autoregressive Model," Econometric Society World Congress 2000 Contributed Papers 1240, Econometric Society.
    13. Guidolin, Massimo & Timmermann, Allan, 2009. "Forecasts of US short-term interest rates: A flexible forecast combination approach," Journal of Econometrics, Elsevier, vol. 150(2), pages 297-311, June.
    14. Karsten Schweikert, 2022. "Detecting Multiple Structural Breaks in Systems of Linear Regression Equations with Integrated and Stationary Regressors," Papers 2201.05430, arXiv.org, revised Aug 2023.
    15. Haug Alfred A & Siklos Pierre L, 2006. "The Behavior of Short-Term Interest Rates: International Evidence of Non-Linear Adjustment," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(4), pages 1-34, December.
    16. Sébastien Morin, 2004. "Ruptures structurelles sur les marchés action et obligataire américains : preuve empirique à partir de la méthode de Saikkönen," Économie et Prévision, Programme National Persée, vol. 166(5), pages 87-98.
    17. Balázs Romhányi, 2005. "A learning hypothesis of the term structure of interest rates," Macroeconomics 0503001, University Library of Munich, Germany.

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