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Heikki Kauppi

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. Heikki Kauppi & Pentti Saikkonen, 2008. "Predicting U.S. Recessions with Dynamic Binary Response Models," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 777-791, November.

    Mentioned in:

    1. Predicting U.S. Recessions with Dynamic Binary Response Models (REStat 2008) in ReplicationWiki ()

Working papers

  1. Heikki Kauppi, 2010. "Yield-Curve Based Probability Forecasts of U.S. Recessions: Stability and Dynamics," Discussion Papers 57, Aboa Centre for Economics.

    Cited by:

    1. Chan, Felix & Pauwels, Laurent L. & Wongsosaputro, Johnathan, 2013. "The impact of serial correlation on testing for structural change in binary choice model: Monte Carlo evidence," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 175-189.
    2. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 02/2013, University of Sydney Business School, Discipline of Business Analytics.

  2. Widgren, Mika & Kauppi, Heikki, 2009. "The Excess Power Puzzle of the EU Budget," CEPR Discussion Papers 7220, C.E.P.R. Discussion Papers.

    Cited by:

    1. Massimo Bordignon & Simona Scabrosetti, 2016. "The Political Economy of Financing the EU budget," Working papers 42, Società Italiana di Economia Pubblica.

  3. Kauppi, Heikki & Widgrén, Mika, 2008. "Do Benevolent Aspects Have Room Explaining EU Bydget Receipts?," Discussion Papers 1161, The Research Institute of the Finnish Economy.

    Cited by:

    1. Peter Schmidt, 2016. "Internal migration and EU regional policy transfer payments: A panel data analysis for the EU-28 member countries," ERSA conference papers ersa16p172, European Regional Science Association.

  4. Widgren, Mika & Kauppi, Heikki, 2008. "Do Benevolent Aspects Have Room in Explaining EU Budget Receipts?," CEPR Discussion Papers 6778, C.E.P.R. Discussion Papers.

    Cited by:

    1. Widgren, Mika & Kauppi, Heikki, 2009. "The Excess Power Puzzle of the EU Budget," CEPR Discussion Papers 7220, C.E.P.R. Discussion Papers.
    2. Widgrén, Mika, 2008. "The Impact of Council Voting Rules on EU Decision-Making," Discussion Papers 1162, The Research Institute of the Finnish Economy.
    3. Peter Schmidt, 2016. "Internal migration and EU regional policy transfer payments: A panel data analysis for the EU-28 member countries," ERSA conference papers ersa16p172, European Regional Science Association.

  5. Heikki Kauppi, 2008. "Yield-Curve Based Probit Models for Forecasting U.S. Recessions: Stability and Dynamics," Discussion Papers 31, Aboa Centre for Economics.

    Cited by:

    1. Henri Nyberg, 2010. "Dynamic probit models and financial variables in recession forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 215-230.
    2. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    3. Fokianos, Konstantinos & Moysiadis, Theodoros, 2017. "Binary time series models driven by a latent process," Econometrics and Statistics, Elsevier, vol. 2(C), pages 117-130.
    4. Christiansen, Charlotte & Eriksen, Jonas Nygaard & Møller, Stig Vinther, 2014. "Forecasting US recessions: The role of sentiment," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 459-468.
    5. Christiansen, Charlotte & Eriksen, Jonas N. & Møller, Stig V., 2019. "Negative house price co-movements and US recessions," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 382-394.
    6. Ng, Eric C.Y., 2012. "Forecasting US recessions with various risk factors and dynamic probit models," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 112-125.
    7. Moysiadis, Theodoros & Fokianos, Konstantinos, 2014. "On binary and categorical time series models with feedback," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 209-228.
    8. Ratcliff, Ryan, 2013. "The “probability of recession”: Evaluating probabilistic and non-probabilistic forecasts from probit models of U.S. recessions," Economics Letters, Elsevier, vol. 121(2), pages 311-315.
    9. Henri Nyberg, 2010. "Testing an autoregressive structure in binary time series models," Economics Bulletin, AccessEcon, vol. 30(2), pages 1460-1473.

  6. Widgren, Mika & Kauppi, Heikki, 2005. "Voting Rules and Budget Allocation in an Enlarged EU," CEPR Discussion Papers 5134, C.E.P.R. Discussion Papers.

    Cited by:

    1. Deniz Aksoy, 2010. "Who gets what, when, and how revisited: Voting and proposal powers in the allocation of the EU budget," European Union Politics, , vol. 11(2), pages 171-194, June.
    2. Antonakakis, Nikolaos & Badinger, Harald & Reuter, Wolf Heinrich, 2014. "From Rome to Lisbon and Beyond: Member States' Power, Efficiency, and Proportionality in the EU Council of Ministers," Department of Economics Working Paper Series 175, WU Vienna University of Economics and Business.
    3. Kóczy, L.Á., 2005. "Strategic aspects of the 1995 and 2004 EU enlargements," Research Memorandum 044, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    4. Zaporozhets, Vera & García-Valiñas, María & Kurz, Sascha, 2016. "Key drivers of EU budget allocation: Does power matter?," European Journal of Political Economy, Elsevier, vol. 43(C), pages 57-70.
    5. Kaniovski, Serguei & Mueller, Dennis C., 2011. "How representative is the European Union Parliament?," European Journal of Political Economy, Elsevier, vol. 27(1), pages 61-74, March.
    6. Mika Widgrén, 2008. "The Impact of Council’s Internal Decision-Making Rules on the Future EU," CESifo Working Paper Series 2195, CESifo.
    7. J. Alonso-Meijide & C. Bowles & M. Holler & S. Napel, 2009. "Monotonicity of power in games with a priori unions," Theory and Decision, Springer, vol. 66(1), pages 17-37, January.
    8. Widgren, Mika & Kauppi, Heikki, 2009. "The Excess Power Puzzle of the EU Budget," CEPR Discussion Papers 7220, C.E.P.R. Discussion Papers.
    9. Widgren, Mika & Kauppi, Heikki, 2005. "Voting Rules and Budget Allocation in an Enlarged EU," CEPR Discussion Papers 5134, C.E.P.R. Discussion Papers.
    10. García-Valiñas, Maria A. & Zaporozhets, Vera, 2015. "Key-drivers of EU budget allocation: Does power matter?," TSE Working Papers 15-548, Toulouse School of Economics (TSE).
    11. Widgrén, Mika, 2008. "The Impact of Council Voting Rules on EU Decision-Making," Discussion Papers 1162, The Research Institute of the Finnish Economy.
    12. Badinger, Harald & Mühlböck, Monika & Nindl, Elisabeth & Reuter, Wolf Heinrich, 2014. "Theoretical vs. empirical power indices: Do preferences matter?," European Journal of Political Economy, Elsevier, vol. 36(C), pages 158-176.
    13. van Gruisen, Philippe & Crombez, Christophe, 2021. "The Commission and the Council Presidency in the European Union: Strategic interactions and legislative powers," European Journal of Political Economy, Elsevier, vol. 70(C).
    14. Massimo Bordignon & Simona Scabrosetti, 2016. "The Political Economy of Financing the EU budget," Working papers 42, Società Italiana di Economia Pubblica.
    15. Heikki Kauppi & Mika Widgrén, 2008. "Do Benevolent Aspects Have Room in Explaining EU Budget Receipts?," Discussion Papers 38, Aboa Centre for Economics.
    16. Zineb Abidi & Matthieu Leprince & Vincent Merlin, 2020. "Power Inequality in Inter-communal Structures: The Simulated Impact of a Reform in the Case of the Municipalities in Western France," Post-Print halshs-02996998, HAL.
    17. Kauppi, Heikki & Widgrén, Mika, 2008. "Do Benevolent Aspects Have Room Explaining EU Bydget Receipts?," Discussion Papers 1161, The Research Institute of the Finnish Economy.
    18. Diego Varela & Javier Prado-Dominguez, 2012. "Negotiating the Lisbon Treaty: Redistribution, Efficiency and Power Indices," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 6(2), pages 107-124, July.
    19. Běla Plechanovová, 2011. "The EU Council enlarged: North-South-East or core-periphery?," European Union Politics, , vol. 12(1), pages 87-106, March.
    20. Loek Groot & Erik Zonneveld, 2013. "European Union Budget Contributions and Expenditures: A Lorenz Curve Approach," Journal of Common Market Studies, Wiley Blackwell, vol. 51(4), pages 649-666, July.
    21. Vera Zaporozhets & Mar'ia Garc'ia-Vali~nas & Sascha Kurz, 2015. "Key drivers of EU budget allocation: Does power matter?," Papers 1512.01267, arXiv.org.
    22. de Mouzon, Olivier & Laurent, Thibault & Le Breton, Michel, 2020. "One Man, One Vote Part 2: Measurement of Malapportionment and Disproportionality and the Lorenz Curve," TSE Working Papers 20-1089, Toulouse School of Economics (TSE).

  7. Kauppi, Heikki & Koskela, Erkki & Stenbacka, Rune, 2004. "Equilibrium Unemployment and Investment Under Product and Labour Market Imperfections," IZA Discussion Papers 1058, Institute of Labor Economics (IZA).

    Cited by:

    1. Mikko Puhakka, 2005. "Equilibrium dynamics under lump-sum taxation in an exchange economy with skewed endowments," Macroeconomics 0508033, University Library of Munich, Germany.
    2. Kai Leitemo & Ulf Soderstrom, 2004. "Robust Monetary Policy in the New-Keynesian Framework," Working Papers 273, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    3. Antti Suvanto & Juhana Hukkinen, 2005. "Stable price level and changing prices," Macroeconomics 0508034, University Library of Munich, Germany.
    4. Joanna Tyrowicz, 2009. "When Eastern Labour Markets Enter Western Europe CEECs. Labour Market Institutions upon Euro Zone Accession," Working Papers 2009-03, Faculty of Economic Sciences, University of Warsaw.
    5. Mälkönen, Ville, 2004. "The efficiency implications of financial conglomeration," Bank of Finland Research Discussion Papers 17/2004, Bank of Finland.

  8. Heikki Kauppi & Erkki Koskela & Rune Stenbacka, 2004. "Equilibrium Unemployment and Capital Intensity Under Product and Labor Market Imperfections," CESifo Working Paper Series 1343, CESifo.

    Cited by:

    1. Karanassou, Marika & Sala, Hector & Snower, Dennis J., 2006. "The Macroeconomics of the Labor Market: Three Fundamental Views," IZA Discussion Papers 2480, Institute of Labor Economics (IZA).
    2. Helge Berger & Stephan Danninger, 2006. "The Employment Effects of Labor and Product Markets Deregulation and their Implications for Structural Reform," CESifo Working Paper Series 1709, CESifo.
    3. Mr. Helge Berger & Mr. Stephan Danninger, 2005. "Labor and Product Market Deregulation: Partial, Sequential, or Simultaneous Reform?," IMF Working Papers 2005/227, International Monetary Fund.

  9. Heikki Kauppi & Markus Haavio, 2003. "Housing Markets and Labor Mobility," Computing in Economics and Finance 2003 164, Society for Computational Economics.

    Cited by:

    1. Amihai Glazer & Vesa Kanniainen & Panu Poutvaara, 2003. "Income Taxes, Property Values, and Migration," CESifo Working Paper Series 1075, CESifo.
    2. Wasmer, Etienne & Zenou, Yves, 2005. "Equilibrium Search Unemployment with Explicit Spatial Frictions," IZA Discussion Papers 1465, Institute of Labor Economics (IZA).
    3. Indermit Gill & Johannes Koettl & Truman Packard, 2013. "Full employment: a distant dream for Europe," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-34, December.

  10. Markus Haavio and Heikki Kauppi, 2001. "Housing Markets, Liquidity Constraints and Labor Mobility," Computing in Economics and Finance 2001 186, Society for Computational Economics.

    Cited by:

    1. Rady, Sven & Ortalo-Magné, François, 2002. "Homeownership," Discussion Papers in Economics 28, University of Munich, Department of Economics.
    2. François Ortalo-Magné & Sven Rady, "undated". "Homeownership: Volatile Housing Prices, Low Labor Mobility and High Income Dispersion," Wisconsin-Madison CULER working papers 02-04, University of Wisconsin Center for Urban Land Economic Research.
    3. Francois Ortalo-Magne & Sven Rady, 2002. "Homeownership: Low Household Mobility, Volatile Housing Prices, High Income Dispersion," CESifo Working Paper Series 823, CESifo.
    4. Cristina Barceló, 2003. "Housing Tenure and Labour Mobility: A Comparison Across European Countries," Working Papers wp2003_0302, CEMFI.
    5. Trond Husby & Henri L. F. de Groot & Marjan W. Hofkes & Tatiana Filatova, 2018. "Flood protection and endogenous sorting of households: the role of credit constraints," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(2), pages 147-168, February.

  11. Kauppi, H., 1999. "Essays on Econometrics of Cointegration," University of Helsinki, Department of Economics 84, Department of Economics.

    Cited by:

    1. Kirstin Hubrich & Helmut Lutkepohl & Pentti Saikkonen, 2001. "A Review Of Systems Cointegration Tests," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 247-318.

Articles

  1. Heikki Kauppi, 2012. "Predicting the Direction of the Fed's Target Rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(1), pages 47-67, January.

    Cited by:

    1. Park, Byeong U. & Simar, Léopold & Zelenyuk, Valentin, 2017. "Nonparametric estimation of dynamic discrete choice models for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 97-120.
    2. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    3. Seibert, Armin & Sirchenko, Andrei & Müller, Gernot, 2021. "A model for policy interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 124(C).
    4. Fokianos, Konstantinos & Moysiadis, Theodoros, 2017. "Binary time series models driven by a latent process," Econometrics and Statistics, Elsevier, vol. 2(C), pages 117-130.
    5. Sjoerd van den Hauwe & Dick van Dijk & Richard Paap, 2011. "Bayesian Forecasting of Federal Funds Target Rate Decisions," Tinbergen Institute Discussion Papers 11-093/4, Tinbergen Institute.
    6. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    7. Pauwels, Laurent, 2019. "Predicting China’s Monetary Policy with Forecast Combinations," Working Papers BAWP-2019-07, University of Sydney Business School, Discipline of Business Analytics.
    8. Fokianos, Konstantinos & Truquet, Lionel, 2019. "On categorical time series models with covariates," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3446-3462.
    9. Dick van Dijk & Robin L. Lumsdaine & Michel van der Wel, 2014. "Market Set-Up in Advance of Federal Reserve Policy Decisions," NBER Working Papers 19814, National Bureau of Economic Research, Inc.
    10. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    11. Park, Byeong U. & Simar, Leopold & Zelenyuk, Valentin, 2013. "Non-Parametric Approach to Dynamic Time Series Discrete Choice Models," LIDAM Discussion Papers ISBA 2013052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  2. Heikki Kauppi & Pentti Saikkonen, 2008. "Predicting U.S. Recessions with Dynamic Binary Response Models," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 777-791, November.

    Cited by:

    1. Makram El-Shagi & Gregor von Schweinitz, 2016. "Qual VAR revisited: Good forecast, bad story," Journal of Applied Economics, Universidad del CEMA, vol. 19, pages 293-322, November.
    2. Hashmat Khan & Santosh Upadhayaya, 2017. "Does Business Confidence Matter for Investment?," Carleton Economic Papers 17-13, Carleton University, Department of Economics, revised 20 Mar 2019.
    3. Quentin LAJAUNIE, 2021. "Nonlinear Impulse Response Function for Dichotomous Models," LEO Working Papers / DR LEO 2852, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    4. Hammami, Yacine & Lindahl, Anna, 2014. "An intertemporal capital asset pricing model with bank credit growth as a state variable," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 14-28.
    5. Jean-Baptiste Hasse & Quentin Lajaunie, 2020. "Does the Yield Curve Signal Recessions? New Evidence from an International Panel Data Analysis," AMSE Working Papers 2013, Aix-Marseille School of Economics, France.
    6. Bofinger, Peter & Feld, Lars P. & Schmidt, Christoph M. & Schnabel, Isabel & Wieland, Volker, 2018. "Vor wichtigen wirtschaftspolitischen Weichenstellungen. Jahresgutachten 2018/19 [Setting the Right Course for Economic Policy. Annual Report 2018/19]," Annual Economic Reports / Jahresgutachten, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung, volume 127, number 201819.
    7. António R. Antunes & Diana Bonfim & Nuno Monteiro & Paulo M.M. Rodrigues, 2016. "Forecasting banking crises with dynamic panel probit models," Working Papers w201613, Banco de Portugal, Economics and Research Department.
    8. Elena-Ivona DUMITRESCU, 2011. "Backesting Value-at-Risk: From DQ (Dynamic Quantile) to DB (Dynamic Binary) Tests," LEO Working Papers / DR LEO 262, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    9. Poon, Aubrey & Zhu, Dan, 2022. "Do Recessions Occur Concurrently Across Countries? A Multinomial Logistic Approach," Working Papers 2022:11, Örebro University, School of Business.
    10. Christophe Schalck & Meryem Yankol-Schalck, 2021. "Predicting French SME failures: new evidence from machine learning techniques," Applied Economics, Taylor & Francis Journals, vol. 53(51), pages 5948-5963, November.
    11. Belkhir, Mohamed & Naceur, Sami Ben & Candelon, Bertrand & Wijnandts, Jean-Charles, 2022. "Macroprudential policies, economic growth and banking crises," Emerging Markets Review, Elsevier, vol. 53(C).
    12. Barrera-Chaupis, Carlos, 2014. "La relación entre los ciclos discretos en la inflación y el crecimiento: Perú 1993-2012 [The relationship between inflation's and growth's discrete cycles: Peru 1993-2012]," MPRA Paper 60959, University Library of Munich, Germany.
    13. Rebecca Stuart, 2020. "Monetary regimes, the term structure and business cycles in Ireland, 1972–2018," Manchester School, University of Manchester, vol. 88(5), pages 731-748, September.
    14. Shuaizhang Feng & Jiandong Sun, 2020. "Misclassification-Errors-Adjusted Sahm Rule for Early Identification of Economic Recession," Working Papers 2020-029, Human Capital and Economic Opportunity Working Group.
    15. Ahmed, Jameel & Straetmans, Stefan, 2015. "Predicting exchange rate cycles utilizing risk factors," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 112-130.
    16. Candelon, B. & Dumitrescu, E-I. & Hurlin, C., 2010. "Currency crises early warning systems: why they should be dynamic," Research Memorandum 047, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    17. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    18. Marius M. Mihai, 2020. "Do credit booms predict US recessions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 887-910, September.
    19. Miguel Ángel Morales Mosquera & Wilmar Cabrera & Laura Capera & Dairo Estrada, 2012. "Un Mapa de Riesgo de Crédito para el Sistema Financiero Colombiano," Temas de Estabilidad Financiera 068, Banco de la Republica de Colombia.
    20. Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578.
    21. Davig, Troy & Hall, Aaron Smalter, 2019. "Recession forecasting using Bayesian classification," International Journal of Forecasting, Elsevier, vol. 35(3), pages 848-867.
    22. Li, Haixi & Sheng, Xuguang Simon & Yang, Jingyun, 2021. "Monitoring recessions: A Bayesian sequential quickest detection method," International Journal of Forecasting, Elsevier, vol. 37(2), pages 500-510.
    23. Nissilä, Wilma, 2020. "Probit based time series models in recession forecasting – A survey with an empirical illustration for Finland," BoF Economics Review 7/2020, Bank of Finland.
    24. Michael W. McCracken & Joseph T. McGillicuddy & Michael T. Owyang, 2022. "Binary Conditional Forecasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1246-1258, June.
    25. Park, Byeong U. & Simar, Léopold & Zelenyuk, Valentin, 2017. "Nonparametric estimation of dynamic discrete choice models for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 97-120.
    26. Harri Ponka, 2017. "The Role of Credit in Predicting US Recessions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 469-482, August.
    27. Kevin Moran & Simplice Aime Nono, 2016. "Using Confidence Data to Forecast the Canadian Business Cycle," Cahiers de recherche 1606, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    28. Fernandez-Perez, Adrian & Fernández-Rodríguez, Fernando & Sosvilla-Rivero, Simón, 2014. "The term structure of interest rates as predictor of stock returns: Evidence for the IBEX 35 during a bear market," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 21-33.
    29. Charlotte Christiansen, 2011. "Predicting Severe Simultaneous Recessions Using Yield Spreads as Leading Indicators," CREATES Research Papers 2011-20, Department of Economics and Business Economics, Aarhus University.
    30. Truquet, Lionel, 2023. "Strong mixing properties of discrete-valued time series with exogenous covariates," Stochastic Processes and their Applications, Elsevier, vol. 160(C), pages 294-317.
    31. James W. Taylor & Keming Yu, 2016. "Using auto-regressive logit models to forecast the exceedance probability for financial risk management," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1069-1092, October.
    32. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    33. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    34. Freitag, L., 2014. "Procyclicality and path dependence of sovereign credit ratings: The example of Europe," Research Memorandum 020, Maastricht University, Graduate School of Business and Economics (GSBE).
    35. Rafael R. S. Guimaraes, 2022. "Deep Learning Macroeconomics," Papers 2201.13380, arXiv.org.
    36. Fokianos, Konstantinos & Moysiadis, Theodoros, 2017. "Binary time series models driven by a latent process," Econometrics and Statistics, Elsevier, vol. 2(C), pages 117-130.
    37. Lyócsa, Štefan & Výrost, Tomáš & Plíhal, Tomáš, 2021. "A tale of tails : New evidence on the growth-return nexus," Finance Research Letters, Elsevier, vol. 38(C).
    38. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
    39. Giusto, Andrea & Piger, Jeremy, 2017. "Identifying business cycle turning points in real time with vector quantization," International Journal of Forecasting, Elsevier, vol. 33(1), pages 174-184.
    40. Eichler, M. & Grothe, O. & Manner, H. & Türk, D.D.T., 2012. "Modeling spike occurrences in electricity spot prices for forecasting," Research Memorandum 029, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    41. Vrontos, Spyridon D. & Galakis, John & Vrontos, Ioannis D., 2021. "Modeling and predicting U.S. recessions using machine learning techniques," International Journal of Forecasting, Elsevier, vol. 37(2), pages 647-671.
    42. 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.
    43. Gerlach, Stefan & Stuart, Rebecca, 2018. "The Slope of the Term Structure and Recessions: The Pre-Fed Evidence, 1857-1913," CEPR Discussion Papers 13013, C.E.P.R. Discussion Papers.
    44. Adrian Pagan & Don Harding, 2011. "Econometric Analysis and Prediction of Recurrent Events," CREATES Research Papers 2011-33, Department of Economics and Business Economics, Aarhus University.
    45. Straetmans, S.T.M. & Candelon, B. & Ahmed, J., 2012. "Predicting and capitalizing on stock market bears in the U.S," Research Memorandum 019, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    46. Harri Pönkä, 2018. "Sentiment and sign predictability of stock returns," Economics Bulletin, AccessEcon, vol. 38(3), pages 1676-1684.
    47. Jylhä, Petri & Lof, Matthijs, 2022. "Mind the Basel gap," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    48. Pönkä, Harri, 2015. "Real oil prices and the international sign predictability of stock returns," MPRA Paper 68330, University Library of Munich, Germany.
    49. Nalewaik, Jeremy J., 2011. "Incorporating vintage differences and forecasts into Markov switching models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 281-307, April.
    50. Pönkä, Harri & Zheng, Yi, 2019. "The role of oil prices on the Russian business cycle," Research in International Business and Finance, Elsevier, vol. 50(C), pages 70-78.
    51. Allaj, Erindi & Sanfelici, Simona, 2023. "Early Warning Systems for identifying financial instability," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1777-1803.
    52. Juan Laborda & Sonia Ruano & Ignacio Zamanillo, 2023. "Multi-Country and Multi-Horizon GDP Forecasting Using Temporal Fusion Transformers," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
    53. Mengya Liu & Fukang Zhu & Ke Zhu, 2022. "Modeling normalcy‐dominant ordinal time series: An application to air quality level," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 460-478, May.
    54. Feng, Shuaizhang & Sun, Jiandong, 2020. "Misclassification-errors-adjusted Sahm Rule for Early Identification of Economic Recession," GLO Discussion Paper Series 523, Global Labor Organization (GLO).
    55. Troy Davig & Aaron Smalter Hall, 2016. "Recession forecasting using Bayesian classification," Research Working Paper RWP 16-6, Federal Reserve Bank of Kansas City.
    56. Nalewaik, Jeremy J., 2011. "Incorporating vintage differences and forecasts into Markov switching models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 281-307.
    57. Peláez, Rolando F., 2015. "Market-timing the business cycle," Review of Financial Economics, Elsevier, vol. 26(C), pages 55-64.
    58. Christiansen, Charlotte & Eriksen, Jonas Nygaard & Møller, Stig Vinther, 2014. "Forecasting US recessions: The role of sentiment," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 459-468.
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