The Role of Credit in Predicting US Recessions

Pönkä, Harri

doi:10.1002/for.2448

Cited by 23 publications

(16 citation statements)

References 41 publications

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“…Gilchrist and Zakrajšek (2012) evaluate the relationship between credit spread and real economic activity and find that CS has good predictive power for US business cycle fluctuations. Ponka (2017b) shows that CS has significant predictive power for US recessions.…”

Section: Investment Downturnsmentioning

confidence: 97%

Does business confidence matter for investment?

Khan

Upadhayaya

2019

Empir Econ

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Business confidence is a well-known leading indicator of future output. Whether it has information about future investment is, however, unclear. We determine how informative business confidence is for investment growth independently of other variables using US business confidence survey data for 1955Q1-2016Q4. Our main findings are: (i) business confidence leads US business investment growth by one quarter, and structures investment by two quarters; (ii) business confidence has predictive ability for investment growth; (iii) remarkably, business confidence has superior forecasting power, relative to conventional predictors, for investment downturns over 1-3 quarter forecast horizons and for the sign of investment growth over a 2-quarter forecast horizon; and (iv) exogenous shifts in business confidence reflect short-lived non-fundamental factors, consistent with the 'animal spirits' view of investment. Our findings have implications for improving investment forecasts, developing new business cycle models, and studying the role of social and psychological factors determining investment growth.

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Section: Investment Downturnsmentioning

confidence: 97%

Does business confidence matter for investment?

Khan

Upadhayaya

2019

Empir Econ

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“…This is a little longer than the phase shift of 12 months used by, for example, Ang et al [18] in their Fig 2, and the lead times cited by Rudebusch and Williams [38]. We also tried to lag the GDP relative to the FF and the T, but in contrast to Ponka [39] and Wang, Nie [40], lagged variables did not improve the predictions.…”

Section: Hypothesis 4 (H4)mentioning

confidence: 95%

The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model

Seip

Zhang²

2021

Forecasting

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Previous studies have shown that the treasury yield curve, T, forecasts upcoming recessions when it obtains a negative value. In this paper, we try to improve the yield curve model while keeping its parsimony. First, we show that adding the federal funds rate, FF, to the model, GDP = f(T,FF), gives seven months vs. five months warning time, and it gives a higher prediction skill for the recessions in the out-of-sample test set. Second, we find that including the quadratic term of the yield curve and the federal funds rate improves the prediction of the 1990 recession, but not the other recessions in the period 1977 to 2019. Third, the T caused a pronounced false peak in GDP for the test set. Restricting the learning set to periods where T and FF were leading the GDP in the learning set did not improve the forecast. In general, recessions are predicted better than the general movement in the economy. A “horse race” between GDP = f(T,FF) and the Michigan consumer sentiment index suggests that the first beats the latter by being a leading index for the observed GDP for more months (50% vs. 6%) during the first test year.

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“…Measurement of the financial cycle, in relation to the prediction of its turning point and the associated recession risk, has therefore attracted growing interest in the literature. For instance, the predicting power of various proxy for the financial cycle, such as credit spreads, credit growth, balance sheet conditions, residential property prices, debt service ratio, has recently been investigated in Liu and Monch (2016), Christiansen et al (2017), Ponka (2017), Guender (2018), Borio et al (2019).…”

Section: Introductionmentioning

confidence: 99%

A new macro-financial condition index for the euro area

Morana

2024

Econometrics and Statistics

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RCEA aims to further independent, advanced research in Economics, Econometrics and related fields and to promote contact between economists, econometricians and scientists from other fields all over the world. Research at RCEA is conducted to enlighten scientific and public debate on economic issues, and not to advance any economic, political or social agenda. In this respect, RCEA mission is particularly concerned with raising awareness and stimulating discussion on the changes required to make capitalism sustainable along its economic, environmental, human, social and political dimensions

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The Role of Credit in Predicting US Recessions

Cited by 23 publications

References 41 publications

Does business confidence matter for investment?

Does business confidence matter for investment?

The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model

A new macro-financial condition index for the euro area

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