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Forecasting U.S. Recessions with a Large Set of Predictors. (2015). Fornaro, Paolo.
In: MPRA Paper.
RePEc:pra:mprapa:62973.

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Cited: 8

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Cites: 17

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Cocites: 50

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Coauthors: 0

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Citations

Citations received by this document

  1. Equity premium predictability over the business cycle. (2021). Stein, Tobias ; Monch, Emanuel.
    In: Discussion Papers.
    RePEc:zbw:bubdps:252021.

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  2. The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model. (2021). Zhang, Dan ; Seip, Knut Lehre.
    In: Forecasting.
    RePEc:gam:jforec:v:3:y:2021:i:2:p:25-436:d:564333.

    Full description at Econpapers || Download paper

  3. Do credit booms predict US recessions?. (2020). Mihai, Marius M.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:39:y:2020:i:6:p:887-910.

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  4. Machine Learning, the Treasury Yield Curve and Recession Forecasting. (2020). Tucker, Adam ; Puglia, Michael.
    In: Finance and Economics Discussion Series.
    RePEc:fip:fedgfe:2020-38.

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  5. Forecasting the state of the Finnish business cycle*. (2020). Pönkä, Harri ; Stenborg, Markku.
    In: Finnish Economic Papers.
    RePEc:fep:journl:v:29:y:2020:i:1:p:81-99.

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  6. Forecasting the state of the Finnish business cycle. (2018). Pönkä, Harri ; Stenborg, Markku.
    In: MPRA Paper.
    RePEc:pra:mprapa:91226.

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  7. IDENTIFYING US BUSINESS CYCLE REGIMES USING FACTOR AUGMENTED NEURAL NETWORK MODELS. (2017). Soybilgen, Baris .
    In: Working Papers.
    RePEc:bli:wpaper:1703.

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  8. Using Confidence Data to Forecast the Canadian Business Cycle. (2016). Moran, Kevin ; Nono, Simplice Aime.
    In: Cahiers de recherche.
    RePEc:lvl:crrecr:1606.

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References

References cited by this document

  1. A. Zellner (1971): An Introduction to Bayesian Inference in Econometrics. Wiley Classics Library, Wiley.
    Paper not yet in RePEc: Add citation now

  2. Arturo Estrella (1998). A New Measure of Fit for Equations with Dichotomous Dependent Variables, Journal of Business and Economic Statistics, 16(2), 198–205.

  3. Charlotte Christiansen, Jonas N. Eriksen, and Stig V. Møller (2014): Forecasting US recessions: The role of sentiment, Journal of Banking and Finance, 49 (C), 459–468.

  4. Christine De Mol, Domenico Giannone, and Lucrezia Reichlin (2008): Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?, Journal of Econometrics, 146(2), 318–328.

  5. Henri Nyberg (2010): Dynamic probit models and financial variables in recession forecasting, Journal of Forecasting, 29(1-2), 215–230.

  6. Henri Nyberg (2014): A bivariate autoregressive probit model: Business cycle linkages and transmission of recession probabilities, Macroeconomic Dynamics, 18, 838–862.

  7. James H. Albert and Siddhartha Chib (1993): Bayesian analysis of binary and polychotomous response data, Journal of the American Statistical Association, 88(422), 669–679.
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  8. James H. Stock and Mark W. Watson (2002): Macroeconomic forecasting using diffusion indexes, Journal of Business and Economic Statistics, 20(2), 147–62.

  9. James H. Stock and Mark W. Watson (2012): Generalized Shrinkage Methods for Forecasting Using Many Predictors, Journal of Business and Economic Statistics, 30(4), 481–493.

  10. Jonathan H. Wright (2006): The yield curve and predicting recessions, Finance and Economics Discussion Series 2006-07, Board of Governors of the Federal Reserve System (U.S.).
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  11. Jushuan Bai and Serena Ng (2002): Determining the Number of Factors in Approximate Factor Models, Econometrica, 70(1), 191–221.

  12. Marcelle Chauvet and Simon Potter (2005): Forecasting recessions using the yield curve, Journal of Forecasting, 24(2), 77–103.

  13. Marta Banbura, Domenico Giannone, and Lucrezia Reichlin (2010): Large Bayesian Vector Auto Regressions, Journal of Applied Econometrics, 25(1), 71–92.

  14. Massimiliano Marcellino, James H. Stock, and Mark W.Watson (2006): A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series, Journal of Econometrics, 135(1-2), 499–526.

  15. Michael Dueker (1997). Strengthening the case for the yield curve as a predictor of U.S. recessions, Federal Reserve Bank of St. Louis Review, 79, 41–51.

  16. Richard Startz (2008): Binomial Autoregressive Moving Average Models With an Application to U.S. Recessions, Journal of Business and Economic Statistics, 26, 1–8.

  17. Zhihong Chen, Azharand Iqbal, and Huiwen Lai (2011): Forecasting the probability of US recessions: a Probit and dynamic factor modelling approach, Canadian Journal of Economics, 44(2), 651–672.

Cocites

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  1. The Role of Credit in Predicting US Recessions. (2015). Pönkä, Harri.
    In: CREATES Research Papers.
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  3. QR-GARCH-M Model for Risk-Return Tradeoff in U.S. Stock Returns and Business Cycles. (2010). Nyberg, Henri.
    In: MPRA Paper.
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  4. Testing an autoregressive structure in binary time series models. (2010). Nyberg, Henri.
    In: Economics Bulletin.
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  5. Comparison of performance measures for multivariate discrete models. (2009). Meinel, Nina .
    In: AStA Advances in Statistical Analysis.
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  7. Yield-Curve Based Probit Models for Forecasting U.S. Recessions: Stability and Dynamics. (2008). Kauppi, Heikki.
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