IDEAS home Printed from https://ideas.repec.org/r/tpr/restat/v90y2008i4p777-791.html
   My bibliography  Save this item

Predicting U.S. Recessions with Dynamic Binary Response Models

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Fornari, Fabio & Lemke, Wolfgang, 2010. "Predicting recession probabilities with financial variables over multiple horizons," Working Paper Series 1255, European Central Bank.
  2. 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.
  3. Hashmat Khan & Santosh Upadhayaya, 2020. "Does business confidence matter for investment?," Empirical Economics, Springer, vol. 59(4), pages 1633-1665, October.
  4. Liu, Jiadong & Papailias, Fotis & Quinn, Barry, 2021. "Direction-of-change forecasting in commodity futures markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. Poon, Aubrey & Zhu, Dan, 2022. "Do Recessions Occur Concurrently Across Countries? A Multinomial Logistic Approach," Working Papers 2022:11, Örebro University, School of Business.
  19. 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.
  20. Adrian Pagan & Don Harding, 2011. "Econometric Analysis and Prediction of Recurrent Events," NCER Working Paper Series 75, National Centre for Econometric Research.
  21. 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.
  22. 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).
  23. 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.
  24. 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.
  25. Xing, Kai & Yang, Xiaoguang, 2020. "Predicting default rates by capturing critical transitions in the macroeconomic system," Finance Research Letters, Elsevier, vol. 32(C).
  26. Harri Pönkä, 2018. "Sentiment and sign predictability of stock returns," Economics Bulletin, AccessEcon, vol. 38(3), pages 1676-1684.
  27. Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.
  28. 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).
  29. 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.
  30. 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.
  31. Döpke, Jörg & Fritsche, Ulrich & Pierdzioch, Christian, 2017. "Predicting recessions with boosted regression trees," International Journal of Forecasting, Elsevier, vol. 33(4), pages 745-759.
  32. 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.
  33. Igor Kheifets & Carlos Velasco, 2012. "Model Adequacy Checks for Discrete Choice Dynamic Models," Working Papers w0170, New Economic School (NES).
  34. 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.
  35. 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.
  36. 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.
  37. 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).
  38. Stein, Tobias, 2024. "Forecasting the equity premium with frequency-decomposed technical indicators," International Journal of Forecasting, Elsevier, vol. 40(1), pages 6-28.
  39. Jylhä, Petri & Lof, Matthijs, 2022. "Mind the Basel gap," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
  40. Ahmed, Jameel & Straetmans, Stefan, 2015. "Predicting exchange rate cycles utilizing risk factors," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 112-130.
  41. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
  42. Ang, James & Smedema, Adam, 2011. "Financial flexibility: Do firms prepare for recession?," Journal of Corporate Finance, Elsevier, vol. 17(3), pages 774-787, June.
  43. 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.
  44. Pönkä, Harri, 2016. "Real oil prices and the international sign predictability of stock returns," Finance Research Letters, Elsevier, vol. 17(C), pages 79-87.
  45. repec:zbw:bofrdp:2007_005 is not listed on IDEAS
  46. 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.
  47. 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.
  48. 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.
  49. 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.
  50. Ginker, Tim & Lieberman, Offer, 2017. "Robustness of binary choice models to conditional heteroscedasticity," Economics Letters, Elsevier, vol. 150(C), pages 130-134.
  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. Daniel Ofori-Sasu & Emmanuel Sarpong-Kumankoma & Saint Kuttu & Elikplimi Komla Agbloyor & Joshua Yindenaba Abor, 2024. "Risk-taking and systemic banking crisis in Africa: do regulatory policy framework provide new insight in threshold models?," Risk Management, Palgrave Macmillan, vol. 26(2), pages 1-37, May.
  54. Allaj, Erindi & Sanfelici, Simona, 2023. "Early Warning Systems for identifying financial instability," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1777-1803.
  55. Jean-Baptiste Hasse, 2022. "Systemic risk: a network approach," Empirical Economics, Springer, vol. 63(1), pages 313-344, July.
  56. Peláez, Rolando F., 2015. "A biannual recession-forecasting model," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 384-393.
  57. 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.
  58. 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.
  59. Marius M. Mihai, 2020. "Do credit booms predict US recessions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 887-910, September.
  60. 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.
  61. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
  62. Algieri, Bernardina & Leccadito, Arturo, 2019. "Ask CARL: Forecasting tail probabilities for energy commodities," Energy Economics, Elsevier, vol. 84(C).
  63. 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.
  64. 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.
  65. 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.
  66. 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.
  67. Jean-Baptiste Hasse, 2020. "Systemic Risk: a Network Approach," Working Papers halshs-02893780, HAL.
  68. Davig, Troy & Hall, Aaron Smalter, 2019. "Recession forecasting using Bayesian classification," International Journal of Forecasting, Elsevier, vol. 35(3), pages 848-867.
  69. 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.
  70. 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.
  71. 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.
  72. 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.
  73. 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.
  74. Bell go, C. & Laurent Ferrara, 2009. "Forecasting Euro-area recessions using time-varying binary response models for financial," Working papers 259, Banque de France.
  75. 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).
  76. 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.
  77. 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).
  78. 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.
  79. 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.
  80. 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.
  81. 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.
  82. 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.
  83. Christophe Bellégo & Laurent Ferrara, 2010. "A factor-augmented probit model for business cycle analysis," Working Papers hal-04140915, HAL.
  84. Troy Davig & Aaron Smalter Hall, 2016. "Recession forecasting using Bayesian classification," Research Working Paper RWP 16-6, Federal Reserve Bank of Kansas City.
  85. 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.
  86. 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.
  87. Nalewaik, Jeremy J., 2011. "Incorporating vintage differences and forecasts into Markov switching models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 281-307.
  88. Hasse, Jean-Baptiste & Lecourt, Christelle & Siagh, Souhila, 2024. "Setting up a sovereign wealth fund to reduce currency crises," Emerging Markets Review, Elsevier, vol. 62(C).
  89. 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).
  90. 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.
  91. 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.
  92. 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.
  93. 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.
  94. Peláez, Rolando F., 2015. "Market-timing the business cycle," Review of Financial Economics, Elsevier, vol. 26(C), pages 55-64.
  95. Hansen, Anne Lundgaard, 2024. "Predicting recessions using VIX–yield curve cycles," International Journal of Forecasting, Elsevier, vol. 40(1), pages 409-422.
  96. 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.
  97. Naceur, Sami Ben & Candelon, Bertrand & Lajaunie, Quentin, 2019. "Taming financial development to reduce crises," Emerging Markets Review, Elsevier, vol. 40(C), pages 1-1.
  98. 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.
  99. 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.
  100. 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.
  101. 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.
  102. Pan Tang & Yuwei Zhang, 2024. "China's business cycle forecasting: a machine learning approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2783-2811, November.
  103. 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.
  104. 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.
  105. 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.).
  106. Rafael R. S. Guimaraes, 2022. "Deep Learning Macroeconomics," Papers 2201.13380, arXiv.org.
  107. 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.
  108. Natasia Engeline S & Salomo Posmauli Matondang, 2016. "Early Warning System And Currency Volatility Management In Emerging Market," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 19(2), pages 129-152, October.
  109. Fokianos, Konstantinos & Moysiadis, Theodoros, 2017. "Binary time series models driven by a latent process," Econometrics and Statistics, Elsevier, vol. 2(C), pages 117-130.
  110. 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).
  111. 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).
  112. 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.
  113. 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.
  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.
  115. 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.
  116. 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).
  117. Fokianos, Konstantinos & Truquet, Lionel, 2019. "On categorical time series models with covariates," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3446-3462.
  118. 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.
  119. Patrick De lamirande & Jason Stevens, 2016. "Predicting events with an unidentified time horizon," Economics Bulletin, AccessEcon, vol. 36(2), pages 729-735.
  120. 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.
  121. Pascal Michaillat, 2025. "Early and Accurate Recession Detection Using Classifiers on the Anticipation-Precision Frontier," Papers 2506.09664, arXiv.org.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.