A Re-examination of the Predictability of Economic Activity Using the Yield Spread

Hamilton, James D.; Kim, Dong Heon

doi:10.2139/ssrn.245584

Cited by 66 publications

(77 citation statements)

References 42 publications

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“…Also, we obtain accurate parameter estimates for both the United States and Japan. Our empirical results for the United States are basically consistent with existing literature such as Harvey (1991) or Hamilton and Kim (2002). Harvey could not obtain significant parameter estimate for Japan, but we could successfully obtain the significant parameter estimate within the framework of the endogenous switching model.…”

Section: Resultssupporting

confidence: 87%

“…Harvey (1991) find that the estimate of φ is 1.269 and is statistically significant using the US data for the period between 1970 and 1989 in the single regime model. Hamilton and Kim (2002) also find that the parameter φ is estimated to be within a range between 0.108 and 1.029 and most of them are statistically significant for the United States. Our empirical results are basically consistent with Harvey (1991) or Hamilton and Kim (2002).…”

Section: Model Implied Relationshipmentioning

confidence: 73%

“…Hamilton and Kim (2002) also find that the parameter φ is estimated to be within a range between 0.108 and 1.029 and most of them are statistically significant for the United States. Our empirical results are basically consistent with Harvey (1991) or Hamilton and Kim (2002). Harvey also find that the estimate of φ is 0.227 but not statistically significant using the Japanese data for the period between 1970 and 1989.…”

Section: Model Implied Relationshipmentioning

confidence: 73%

“…Haubrich and Dombrosky (1996) and Hamilton and Kim (2002), for example, extend the model to include the lagged economic growth rate as an additional explanatory variable. These authors note that the yield spread still provides additional information beyond that contained in the lagged growth rates.…”

mentioning

confidence: 99%

“…Other investigators test whether they can alter the relevance of the yield spread for predicting future economic activities by including variables to proxy monetary policy or short rate volatility. Some of the main references in this context are Estrella and Hardouvelis (1991), Plosser and Rouwenhorst (1994), Estrella and Mishkin (1997), and Hamilton and Kim (2002).…”

mentioning

confidence: 99%

See 4 more Smart Citations

Analysing Yield Spread and Output Dynamics in an Endogenous Markov Switching Regression Framework

Bhar

Hamori

2007

Asia-Pacific Finan Markets

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In this article we analyse the relationship between yield spread and the economic activity by allowing the parameters of the regression to be driven by an endogenous Markov chain. Using the endogenous model, we could obtain accurate parameter estimates and the specification of our model is empirically supported. Our empirical results may indicate that people with low risk tolerance more likely to prefer a low volatility state over a high volatility one, while people with high risk tolerance are more likely to prefer a high volatility state over a low volatility one.

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Section: Resultssupporting

confidence: 87%

Section: Model Implied Relationshipmentioning

confidence: 73%

Section: Model Implied Relationshipmentioning

confidence: 73%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Analysing Yield Spread and Output Dynamics in an Endogenous Markov Switching Regression Framework

Bhar

Hamori

2007

Asia-Pacific Finan Markets

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Predicting GDP growth with stock and bond markets: Do they contain different information?

McMillan

2020

Int. J Fin Econ

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This paper examines the ability of bond and stock markets to predict subsequent GDP growth over a range of horizons for 12 international countries. The results, using linear, probit, time‐ and regime‐varying in‐sample regressions and out‐of‐sample forecasting, confirm the view that both financial markets exhibit predictive power for future output growth. Moreover, there is notable variation within the strength of the predictive relation, for example, predictive power increases during the financial crisis period. Results suggest that while the term structure arguably exhibits stronger predictive power, both series contain distinct predictive information. Notably, predictive power emanating from the stock return series appears stronger over shorter (up to four‐quarter) time horizons, while the term structure series exhibits more consistent predictive power over a range of horizons. Considering different regimes, we observe that the bond market exhibits greater predictive power for a flatter yield curve and lower stock prices relative to fundamentals, while the stock market exhibits greater predictive power for a steeper yield curve and higher relative stock prices. This suggests that the two financial markets exhibit different information content for future output growth. This view is further supported by forecast results whereby a model that includes both financial series outperforms a model that only includes one. Forecast encompassing tests further support the view that stock returns contain additional information over that presented by the term structure alone.

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Weighted Smooth Transition Regressions

Becker

Osborn

2010

J of Applied Econometrics

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SUMMARYA new procedure is proposed for modelling nonlinearity of a smooth transition form, by allowing the transition variable to be a weighted function of lagged observations. This function depends on two unknown parameters and requires specification of the maximum lag only. Nonlinearity testing for this specification uses a search over a plausible set of weight function parameters, combined with bootstrap inference. Finite-sample results show that the recommended wild bootstrap heteroskedasticity-robust testing procedure performs well, for both homoskedastic and heteroskedastic data-generating processes. Forecast comparisons relative to linear models and other nonlinear specifications of the smooth transition form confirm that the new WSTR model delivers good performance.

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A Re-examination of the Predictability of Economic Activity Using the Yield Spread

Cited by 66 publications

References 42 publications

Analysing Yield Spread and Output Dynamics in an Endogenous Markov Switching Regression Framework

Analysing Yield Spread and Output Dynamics in an Endogenous Markov Switching Regression Framework

Predicting GDP growth with stock and bond markets: Do they contain different information?

Weighted Smooth Transition Regressions

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