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Change Detection and the Casual Impact of the Yield Curve

Author

Listed:
  • Stan Hurn

    (QUT)

  • Peter C B Phillips

    (Yale)

  • Shuping Shi

    (Macquarie)

Abstract
Causal relationships in econometrics are typically based on the concept of predictability and are established in terms of tests for Granger causality. These causal relationships are susceptible to change, especially during times of financial turbulence, making the real-time detection of instability an important practical issue. This paper develops a test for detecting changes in causal relationships based on a recursive rolling window, which is analogous to the procedure used in recent work on financial bubble detection. The limiting distribution of the test takes a simple form under the null hypothesis and is easy to implement in conditions of homoskedasticity, conditional heteroskedasticity and unconditional heteroskedasticity. Simulation experiments compare the efficacy of the proposed test with two other commonly used tests, the forward recursive and the rolling window tests. The results indicate that both the rolling and the recursive rolling approaches offer good finite sample performance in situations where there are one or two changes in the causal relationship over the sample period. The testing strategies are illustrated in an empirical application that explores the causal impact of the slope of the yield curve on output and inflation in the U.S. over the period 1985-2013.

Suggested Citation

  • Stan Hurn & Peter C B Phillips & Shuping Shi, 2015. "Change Detection and the Casual Impact of the Yield Curve," NCER Working Paper Series 107, National Centre for Econometric Research.
    • Handle: RePEc:qut:auncer:2015_05
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    File URL: http://www.ncer.edu.au/papers/documents/WP107.pdf
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    More about this item

    Keywords

    Causality; Forward recursion; Hypothesis testing; Inflation; Output; Recursvie rolling test; Rolling Window; Yield curve;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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