Re-examination of the predictability of economic activity using the yield spread: a nonlinear approach

Venetis, Ioannis A.; Paya, Iván; Peel, David

doi:10.1016/s1059-0560(02)00147-8

Cited by 38 publications

(27 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The F test uniformly and strongly rejects the null of equal parameters above and below the threshold for all series. This result confirms the asymmetry of the predicting power of the spread pointed out earlier in the literature regarding the real GDP-yield spread link (see Galbraith and Tkacz, 2000;and Venetis et al, 2001). In the case of the US, most of the estimated threshold values are around 1.4 percent, except for consumption and non-durable goods where the threshold is almost half.…”

Section: Econometric Resultssupporting

confidence: 89%

“…Tkacz (2001) employs neural network models and documents the improved forecast accuracy (in terms of lower forecast errors) that can be achieved using nonlinear models to link the yield spread to aggregate output change. Venetis et al, (2001) examine the strength of the link between the yield spread and aggregate output change over the last forty years. This study confirms that threshold effects exist for a number of forecasting horizons affecting the power of the spread as a leading indicator in the case of the US, Canada and UK.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Asymmetry in the link between the yield spread and industrial production: threshold effects and forecasting

Paya

Venetis

Peel

2004

Journal of Forecasting

Self Cite

View full text Add to dashboard Cite

We analyze the nonlinear behavior of the information content in the spread for future real economic activity. The spread linearly predicts one year ahead real growth in nine industrial production sectors of the US and four of the UK over the last forty years. However, recent investigations on the spread-real activity relation have questioned both its linear nature and its time-invariant framework. Our, in-sample, empirical evidence suggests that the spread real activity relationship exhibits asymmetries that allow for different predictive power of the spread when past spread values were above or below some threshold value. We then measure the out-of-sample forecast performance of the nonlinear model using predictive accuracy tests. The results show that significant improvement in forecasting accuracy, at least for onestep ahead forecasts, can be obtained over the linear model.

show abstract

Section: Econometric Resultssupporting

confidence: 89%

mentioning

confidence: 99%

Asymmetry in the link between the yield spread and industrial production: threshold effects and forecasting

Paya

Venetis

Peel

2004

Journal of Forecasting

Self Cite

View full text Add to dashboard Cite

show abstract

“…where in both cases Venetis et al (2003), the choice can be made empirically by testing the following sequence of null hypotheses: H , then the exponential function is chosen, otherwise the logistic specification of G is preferred.…”

Section: Literature Overviewmentioning

confidence: 99%

Economic activity and recession probabilities: information content and predictive power of the term spread in Italy

Brunetti¹,

Torricelli²

2009

Applied Economics

View full text Add to dashboard Cite

The aim of the present paper is to examine the information content of the Italian term spread as for real economic growth rates and recession probabilities and to test its predictive power in forecasting regime probabilities. To this end the relationship between the term spread and economic growth rates is modelled as a nonlinear one and specifically the Logistic Smooth Transition model is used, while a probit model is implemented to forecast recession probabilities. Specific to this paper is the use of the OECD business cycle chronology, which was never used before to this end for the Italian case. Overall evidence supports the informative content of the spread in Italy over the whole period 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 AbstractThe aim of the present paper is to examine the information content of the Italian term spread as for real economic growth rates and recession probabilities and to test its predictive power in forecasting regime probabilities. To this end the relationship between the term spread and economic growth rates is modelled as a nonlinear one and specifically the Logistic Smooth Transition model is used, while a probit model is implemented to forecast recession probabilities. Specific to this paper is the use of the OECD business cycle chronology, which was never used before to this end for the Italian case. Overall evidence supports the informative content of the spread in Italy over the whole period although results are more satisfactory as from 1992. In particular, recession forecasts are generally better than those obtained with other chronologies previously adopted for the Italian case (ISAE and ECRI).

show abstract

“…A plethora of research activity says that yield spread should have information for predicting future output and inflation. A large number of these empirical studies verify the predictive power of the spread in forecasting future GDP growth (see [1][2][3][4][5][6][7][8]). Another strand of literature focuses on the use of probit models to verify whether the term spread generates reliable probabilities concerning future recessions (see [3,4,[9][10][11][12]).…”

Section: Introductionmentioning

confidence: 98%

In Search of Leading Indicator Property of Yield Spread for India: An Approach Based on Quantile and Wavelet Regression

Dar

Shah

2015

Economics Research International

View full text Add to dashboard Cite

The leading indicator ability of yield spread for future output growth and inflation is tested for India. Using the yields on securities with maturities ten years and three months to construct yield spread, we study the predictive power of yield spread for output growth and inflation. Our results based on regression of future inflation and output on yield spreads indicate that there is no information in the yield spread about future economic activity and inflation in India. Further, the predictive power of yield spread is analyzed over different quantiles of inflation and output growth using quantile regression; we find that there is again no evidence of predictive information in the yield spreads. Using multiscale wavelet based regression, predictive power is however unveiled at higher time scales for output growth only.

show abstract

Re-examination of the predictability of economic activity using the yield spread: a nonlinear approach

Cited by 38 publications

References 14 publications

Asymmetry in the link between the yield spread and industrial production: threshold effects and forecasting

Asymmetry in the link between the yield spread and industrial production: threshold effects and forecasting

Economic activity and recession probabilities: information content and predictive power of the term spread in Italy

In Search of Leading Indicator Property of Yield Spread for India: An Approach Based on Quantile and Wavelet Regression

Contact Info

Product

Resources

About