Effects of the US monetary policy shocks during financial crises – a threshold vector autoregression approach

ABSTRACT

This article analyzes the impact of monetary policy during periods of low and high financial stress in the US economy using a threshold vector autoregression model. There is evidence that expansionary monetary policy is effective during periods of high financial stress with larger responses having a higher proportionate effect on output. The existence of a cost channel effect during periods of high financial stress implies the existence of a short run output-inflation trade off during financial crises. Large expansionary monetary shocks also increase the likelihood of moving the economy out of a high financial stress regime.

KEYWORDS:

• Monetary policy
• financial stress
• threshold vector autoregression models

JEL CLASSIFICATION:

• F44
• E44
• E52

Acknowledgments

We are grateful for comments from an anonymous referee, Warwick McKibbin, Ippei Fujiwara and seminar participants at The Australian National University and colleagues at the Reserve Bank of Australia during Zheng’s internship. Fry-McKibbin and Zheng acknowledge financial support from ARC grant #DP120103443. The findings, interpretations, and conclusions expressed in this article are entirely those of the authors. They do not necessarily represent the views of KPMG.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ This mechanism is not unrelated to Olivei and Tenreyro (2007) who show that impulse responses for output can differ across the year in response to the uneven staggering of wage contracts.

² http://www.federalreserve.gov/newsevents/testimony/bernanke20130522a.htm.

³ The federal funds rate hit the zero lower bound of 50 basis points since 2009Q1. The policy interest rate cannot be exactly zero as there would be various transaction costs detailed in Oda and Okina (2001). Krugman (1998) argues that a nominal rate of 0.43% is a good approximation of an economy that is facing liquidity trap conditions. Studies in the literature typically choose 50 basis points to be the zero lower bound (e.g. Iwata and Wu, 2006).

⁴ The impulse response functions for the alternative ordering of the variables are available on request.

⁵ The level of trimming of the grid is chosen arbitrarily. The standard level of trimming often used in the existing literature is between 15% and 20%.

⁶ The feature of the TVAR model is that there are two regimes (here, low and high stress), but the data can switch in and out of each regime through time. For example, inspection of Figure 1 shows that there are periods of high stress during the international banking crisis, the debt crisis, the savings and loan crisis, the Asian financial crisis and the subprime mortgage crisis, and during the rest of the time the level of financial stress is low. This means that a single demarcation date as would be identified by traditional structural break tests separating regimes is less applicable in the TVAR estimation.

⁷ An alternative method used in other papers is to arbitrarily fix the threshold value of the switching variable.

⁸ Note that the value of the threshold is estimated using the benchmark sample period from 1973Q1 to 2008Q4, but is plotted against the sample period in the sensitivity analysis which extends to 2015Q4.

⁹ Similar results hold for the contractionary monetary policy case.

¹⁰ See Appendices E and F in Fry-McKibbin and Zheng (2016).

Additional information

Funding

Fry-McKibbin and Zheng acknowledge financial support from ARC [grant number DP120103443].