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Predicting U.S. Recessions with Dynamic Binary Response Models

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Cited by:

  1. Makram El-Shagi & Gregor Von Schweinitz, 2016. "Qual Var Revisited: Good Forecast, Bad Story," Journal of Applied Economics, Taylor & Francis Journals, vol. 19(2), pages 293-321, November.
  2. Hashmat Khan & Santosh Upadhayaya, 2020. "Does business confidence matter for investment?," Empirical Economics, Springer, vol. 59(4), pages 1633-1665, October.
  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. Hasse, Jean-Baptiste & Lajaunie, Quentin, 2022. "Does the yield curve signal recessions? New evidence from an international panel data analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 9-22.
  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. Antunes, António & Bonfim, Diana & Monteiro, Nuno & Rodrigues, Paulo M.M., 2018. "Forecasting banking crises with dynamic panel probit models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 249-275.
  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, Carlos, 2014. "La relación entre los ciclos discretos en la inflación y el crecimiento: Perú 1993 - 2012," Working Papers 2014-024, Banco Central de Reserva del Perú.
  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, Bertrand & Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2014. "Currency crisis early warning systems: Why they should be dynamic," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1016-1029.
  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. Herrala, Risto & Kauko, Karlo, 2007. "Household loan loss risk in Finland: estimations and simulations with micro data," Bank of Finland Research Discussion Papers 5/2007, Bank of Finland.
  29. 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.
  30. Christiansen, Charlotte, 2013. "Predicting severe simultaneous recessions using yield spreads as leading indicators," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1032-1043.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. Lennart Freitag, 2015. "Procyclicality and Path Dependence of Sovereign Credit Ratings: The Example of Europe," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 44(2), pages 309-332, July.
  36. Rafael R. S. Guimaraes, 2022. "Deep Learning Macroeconomics," Papers 2201.13380, arXiv.org.
  37. Fokianos, Konstantinos & Moysiadis, Theodoros, 2017. "Binary time series models driven by a latent process," Econometrics and Statistics, Elsevier, vol. 2(C), pages 117-130.
  38. 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).
  39. 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.
  40. 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.
  41. 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).
  42. 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.
  43. 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.
  44. Vesna Bucevska, 2015. "Currency Crises in EU Candidate Countries: An Early Warning System Approach," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 62(4), pages 493-510, September.
  45. 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.
  46. Adrian Pagan & Don Harding, 2011. "Econometric Analysis and Prediction of Recurrent Events," NCER Working Paper Series 75, National Centre for Econometric Research.
  47. 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).
  48. Harri Pönkä, 2018. "Sentiment and sign predictability of stock returns," Economics Bulletin, AccessEcon, vol. 38(3), pages 1676-1684.
  49. Jylhä, Petri & Lof, Matthijs, 2022. "Mind the Basel gap," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
  50. Pönkä, Harri, 2016. "Real oil prices and the international sign predictability of stock returns," Finance Research Letters, Elsevier, vol. 17(C), pages 79-87.
  51. 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.
  52. 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.
  53. Allaj, Erindi & Sanfelici, Simona, 2023. "Early Warning Systems for identifying financial instability," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1777-1803.
  54. 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.
  55. 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.
  56. 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).
  57. Troy Davig & Aaron Smalter Hall, 2016. "Recession forecasting using Bayesian classification," Research Working Paper RWP 16-6, Federal Reserve Bank of Kansas City.
  58. Nalewaik, Jeremy J., 2011. "Incorporating vintage differences and forecasts into Markov switching models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 281-307.
  59. Peláez, Rolando F., 2015. "Market-timing the business cycle," Review of Financial Economics, Elsevier, vol. 26(C), pages 55-64.
  60. 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.
  61. Jeremy J. Nalewaik, 2011. "Forecasting recessions using stall speeds," Finance and Economics Discussion Series 2011-24, Board of Governors of the Federal Reserve System (U.S.).
  62. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2012. "The yield curve and the macro-economy across time and frequencies," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1950-1970.
  63. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Finance, Presses universitaires de Grenoble, vol. 33(1), pages 79-112.
  64. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
  65. Jean-Baptiste Hasse, 2022. "Systemic risk: a network approach," Empirical Economics, Springer, vol. 63(1), pages 313-344, July.
  66. Fokianos, Konstantinos & Truquet, Lionel, 2019. "On categorical time series models with covariates," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3446-3462.
  67. 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.
  68. Patrick De lamirande & Jason Stevens, 2016. "Predicting events with an unidentified time horizon," Economics Bulletin, AccessEcon, vol. 36(2), pages 729-735.
  69. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
  70. Clements, A.E. & Herrera, R. & Hurn, A.S., 2015. "Modelling interregional links in electricity price spikes," Energy Economics, Elsevier, vol. 51(C), pages 383-393.
  71. 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.
  72. Pauwels, Laurent & Vasnev, Andrey, 2014. "Forecast combination for U.S. recessions with real-time data," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 138-148.
  73. Kheifets, Igor & Velasco, Carlos, 2017. "New goodness-of-fit diagnostics for conditional discrete response models," Journal of Econometrics, Elsevier, vol. 200(1), pages 135-149.
  74. Xing, Kai & Yang, Xiaoguang, 2020. "Predicting default rates by capturing critical transitions in the macroeconomic system," Finance Research Letters, Elsevier, vol. 32(C).
  75. Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.
  76. Chiang, Shu-hen & Chen, Chien-Fu, 2022. "From systematic to systemic risk among G7 members: Do the stock or real estate markets matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
  77. Ang, James & Smedema, Adam, 2011. "Financial flexibility: Do firms prepare for recession?," Journal of Corporate Finance, Elsevier, vol. 17(3), pages 774-787, June.
  78. Laurini, Márcio P. & Caldeira, João F., 2016. "A macro-finance term structure model with multivariate stochastic volatility," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 68-90.
  79. Peláez, Rolando F., 2015. "A biannual recession-forecasting model," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 384-393.
  80. 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.
  81. Algieri, Bernardina & Leccadito, Arturo, 2019. "Ask CARL: Forecasting tail probabilities for energy commodities," Energy Economics, Elsevier, vol. 84(C).
  82. Henri Nyberg, 2018. "Forecasting US interest rates and business cycle with a nonlinear regime switching VAR model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(1), pages 1-15, January.
  83. 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.
  84. Jean-Baptiste Hasse, 2020. "Systemic Risk: a Network Approach," Working Papers halshs-02893780, HAL.
  85. Matthew C. Li, 2014. "The US zero-coupon yield spread as a predictor of excess daily stock market volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 24(13), pages 889-906, July.
  86. Márcio Laurini & João Frois Caldeira, 2012. "Some Comments on a Macro-Finance Model with Stochastic Volatility," IBMEC RJ Economics Discussion Papers 2012-04, Economics Research Group, IBMEC Business School - Rio de Janeiro.
  87. Bellégo, C. & Ferrara, L., 2009. "Forecasting Euro-area recessions using time-varying binary response models for financial," Working papers 259, Banque de France.
  88. Dunsmuir, William T. M. & Scott, David J., 2015. "The glarma Package for Observation-Driven Time Series Regression of Counts," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i07).
  89. Bellégo, C. & Ferrara, L., 2012. "Macro-financial linkages and business cycles: A factor-augmented probit approach," Economic Modelling, Elsevier, vol. 29(5), pages 1793-1797.
  90. Neville Francis & Michael T. Owyang & Daniel Soques, 2022. "Business Cycles across Space and Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(4), pages 921-952, June.
  91. Romano, A.A. & Scandurra, G. & Carfora, A., 2015. "Probabilities to adopt feed in tariff conditioned to economic transition: A scenario analysis," Renewable Energy, Elsevier, vol. 83(C), pages 988-997.
  92. 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.
  93. Naceur, Sami Ben & Candelon, Bertrand & Lajaunie, Quentin, 2019. "Taming financial development to reduce crises," Emerging Markets Review, Elsevier, vol. 40(C), pages 1-1.
  94. Cem Çakmakli & Hamza Dem I˙rcani & Sumru Altug, 2021. "Modelling of Economic and Financial Conditions for Real‐Time Prediction of Recessions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 663-685, June.
  95. Igor Kheifets & Carlos Velasco, 2012. "Model Adequacy Checks for Discrete Choice Dynamic Models," Working Papers w0170, Center for Economic and Financial Research (CEFIR).
  96. Schreiber, Sven & Soldatenkova, Natalia, 2016. "Anticipating business-cycle turning points in real time using density forecasts from a VAR," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 166-187.
  97. Feng, Shuaizhang & Sun, Jiandong, 2020. "Misclassification-Errors-Adjusted Sahm Rule for Early Identification of Economic Recession," IZA Discussion Papers 13168, Institute of Labor Economics (IZA).
  98. Rebecca Stuart, 2020. "The term structure, leading indicators, and recessions: evidence from Switzerland, 1974–2017," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-17, December.
  99. 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.
  100. Fornari, Fabio & Lemke, Wolfgang, 2010. "Predicting recession probabilities with financial variables over multiple horizons," Working Paper Series 1255, European Central Bank.
  101. Liu, Jiadong & Papailias, Fotis & Quinn, Barry, 2021. "Direction-of-change forecasting in commodity futures markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
  102. Döpke, Jörg & Fritsche, Ulrich & Pierdzioch, Christian, 2017. "Predicting recessions with boosted regression trees," International Journal of Forecasting, Elsevier, vol. 33(4), pages 745-759.
  103. repec:zbw:bofrdp:2007_005 is not listed on IDEAS
  104. Evgenidis, Anastasios & Tsagkanos, Athanasios & Siriopoulos, Costas, 2017. "Towards an asymmetric long run equilibrium between stock market uncertainty and the yield spread. A threshold vector error correction approach," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 267-279.
  105. Ginker, Tim & Lieberman, Offer, 2017. "Robustness of binary choice models to conditional heteroscedasticity," Economics Letters, Elsevier, vol. 150(C), pages 130-134.
  106. Anna Pestova, 2015. "Leading Indicators of the Business Cycle: Dynamic Logit Models for OECD Countries and Russia," HSE Working papers WP BRP 94/EC/2015, National Research University Higher School of Economics.
  107. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
  108. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.
  109. Gugler, Klaus & Haxhimusa, Adhurim, 2019. "Market integration and technology mix: Evidence from the German and French electricity markets," Energy Policy, Elsevier, vol. 126(C), pages 30-46.
  110. Proaño, Christian R. & Theobald, Thomas, 2014. "Predicting recessions with a composite real-time dynamic probit model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 898-917.
  111. Christophe Bellégo & Laurent Ferrara, 2010. "A factor-augmented probit model for business cycle analysis," Working Papers hal-04140915, HAL.
  112. Sun, Jiandong & Feng, Shuaizhang & Hu, Yingyao, 2021. "Misclassification errors in labor force statuses and the early identification of economic recessions," Journal of Asian Economics, Elsevier, vol. 75(C).
  113. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions in Germany With Boosted Regression Trees," Macroeconomics and Finance Series 201505, University of Hamburg, Department of Socioeconomics.
  114. 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, April.
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