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A comment on interest rate pass-through: a non-normal approach

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Abstract

This paper revisits the question of interest rate pass-through from the federal funds rate to bank and open market rates from the years 1987 to 2015. We employ cointegration tests with improved testing power by using information in non-normal errors. Using this approach, we find evidence of cointegration between the federal funds rate and the prime rate, the federal funds rate and the 3-month financial commercial paper rate, but no evidence of cointegration between the federal funds rate and the 30-year conventional mortgage rate. Moreover, we estimate the degree of long-run pass-through for both the prime and commercial paper rates to be less than one. Our results confirm that there is not only significant co-movement between the federal funds rate and short-term borrowing rates, but also that interest rate pass-through, in the long run, is incomplete.

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Fig. 1

Note Figure plots the federal funds rate and other market rates from February 1987 to February 2015. The shaded lines are NBER recession dates

Fig. 2

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Notes

  1. The purpose of unconventional monetary policy was to reduce long-term private sector interest rates. (See Kuttner (2018)).

  2. For related research, see Aas and Haff (2006), Bauwens and Laurent (2005), Hansen (1994), Jones and Faddy (2003), Patton (2004) and Venter and de Jongh (2002).

  3. In general, one may consider VAR(p) representation; we suppress \(\Delta y_{t - 1}\), \(\Delta y_{t - 2}\),…, \(\Delta y_{t - p}\) for ease of exposition.

  4. For example, see Li and Lee (2010) and Banerjee et al. (2017).

  5. Also known as the cointegration regression (Engle and Granger 1987).

  6. For example, see Freixas and Rochet (1997) and Payne and Waters (2008).

  7. Im and Schmidt (2008) introduced the procedure in the OLS framework, and the idea was adapted to tests for stationarity by Im et al. (2014) and Meng et al. (2013).

  8. The simulation results of Lee et al. (2015) show that the RALS ECM test shows size distortions and the power of the RALS ADL and RALS EG2 tests tends to dominate that of the RALS EG test; therefore, we only consider the RALS ADL and RALS EG2 test in our experiment.

  9. In case of RALS EG2 tests, the error terms (\(e\) and \(\nu\)) are to be replaced by to those of Eqs. (6) and (12), \(\varepsilon\) and \(\varsigma\).

  10. The exact critical values will be computed via interpolation using the nearest value of \(\rho^{2}\).

  11. For the 3-month AA financial commercial paper rate, we use the series collected from January 1997 due to its availability.

  12. Payne and Waters (2008) indicate that the transmission of monetary policy has changed since the early 1980s and throughout the 1990s as a result of the deregulation of the US banking system, the evolution of financial innovations and greater monetary policy transparency. To investigate the influence of these changes on the effectiveness of monetary policy, they set the starting period as 1987:02.

  13. Data obtained from Rudebusch (2009).

  14. On December 16, 2008, the Federal Open Market Committee established a target range for the federal funds rate of zero to a quarter percent.

  15. For a detailed analysis of the effectiveness of unconventional monetary policy, see Kuttner (2018) and Williamson (2015).

  16. See Pesavento (2004) for more details.

  17. See Lothian and Taylor (1996) and Mark (1990).

  18. The previous literature has shown that the MTAR model captures the possibility of asymmetrically sharp adjustments toward the long-run equilibrium between the prime rate and the federal funds rate. For more details, see Bohl and Siklos (2004) and Payne and Waters (2008).

  19. To describe the model, we use the prime rate (\(p_{t} )\) as a lending rate. The empirical tests have been implemented for all three lending rates.

  20. We use the critical value reported in Table 1 of GH (1996) to test the null hypothesis and list the value as shown in Table 3.

  21. Note that the testing regression of RALS EG2 can be obtained analogously. The only difference between the two tests is that the residual used to construct \(\hat{w}_{t}\) is computed from the residuals in (6).

  22. See de Bondt (2002) and Payne and Waters (2008).

  23. The first-step regression of the RALS EG2 test is the same as that of the EG test. To save space, we do not report the same estimation results in Table 2.

  24. For Eq. (11), the existence of cointegration between the two series confirms that the estimated \(\delta\) is not zero and there exists a nonzero value \(\lambda\) which implies the linear relationship of the two non-stationary variables is I(0). Accordingly, in cointegrated ADL testing regressions, the values of estimated coefficients are used to discuss economic issues, such as elasticity. For examples, see Fuinhas and Marques (2012) and Lee et al. (2018).

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Authors and Affiliations

  1. Department of Information Systems, Auburn University at Montgomery, Montgomery, AL, 36117, USA

    Dong-Yop Oh

  2. Accounting, Economics and Finance Department, Tuskegee University, Tuskegee, AL, 36083, USA

    Hyejin Lee

  3. Department of Economics, Wesleyan University, Middletown, CT, 06459, USA

    Karl David Boulware

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  1. Dong-Yop Oh
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  2. Hyejin Lee
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  3. Karl David Boulware
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Correspondence to Hyejin Lee.

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Oh, DY., Lee, H. & Boulware, K.D. A comment on interest rate pass-through: a non-normal approach. Empir Econ 59, 2017–2035 (2020). https://doi.org/10.1007/s00181-019-01696-3

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