Risk management-driven policy rate gap

Section: Introductionsupporting

confidence: 89%

Does Monetary Policy Respond to Uncertainty? Evidence from Australia

Ponomareva

Sheen

Wang

2019

“…One natural interpretation of this response is that, due to its recessionary effects, uncertainty shocks call for an indirect policy response to uncertainty. However, a direct response to uncertainty, consistent with risk management strategies, has been documented for the US by Evans et al () and Caggiano, Castelnuovo and Nodari (). Disentangling direct and indirect responses by the RBNZ to hikes in uncertainty is material for future research…”

Section: Discussionsupporting

confidence: 55%

“…Our results suggest that uncertainty shocks are relevant drivers of the New Zealand business cycle. As discussed by Castelnuovo, Lim and Pellegrino (), there might be three reasons behind such a sizeable contribution. First, according to the Economic Cycle Research Institute, New Zealand experienced two recessions during the investigated periods, i.e., from November 2007 to May 2009 and from May to October 2010.…”

Section: Discussionmentioning

confidence: 96%

Measuring Uncertainty for New Zealand Using Data‐Rich Approach

Tran

Vehbi

Wong

2019

This paper develops two state-of-the-art uncertainty indices for New Zealand by exploiting two separate data-rich environments. The first index follows the methodology outlined in Jurado, Ludvigson and Ng (2015) to construct an estimate of uncertainty based on a large New Zealand macro dataset. The second index is constructed based on freely accessible and real time Google Trends data to provide a real-time and freely-accessible measure of uncertainty as in Castelnuovo and Tran (2017) and Shields and Tran (2018). Both indices do a reasonable job measuring uncertainty in New Zealand. VAR evidence documents significant impacts of uncertainty shocks on GDP in New Zealand.

“…Our findings are consistent with the ‘risk‐management hypothesis’ put forth by Greenspan (), that is, the impact of (different forms of) uncertainty on US monetary policy decision making. Taylor‐rule based investigations considering proxies for risk have been proposed by Castelnuovo (), Castelnuovo (), Evans et al (), Caggiano, Castelnuovo and Nodari (), Caldara and Herbst (), and Ponomareva, Sheen and Wang (); quantile‐regression frameworks linking policy rates to risk have been estimated by Giglio, Kelly, and Pruitt (); nonlinear VARs connecting uncertainty shocks and policy rates have been estimated by Caggiano, Castelnuovo and Nodari (). Our paper confirms, with a different empirical strategy such as local projections, that the response of the short end of the term structure is indeed consistent with the risk‐management hypothesis postulated by Greenspan ().…”

Section: Introductionmentioning

confidence: 99%

Yield Curve and Financial Uncertainty: Evidence Based on US Data

Castelnuovo

2019

Self Cite

How do short-and long-term interest rates respond to a jump in financial uncertainty? We address this question by conducting a local projections analysis with US monthly data, period: 1962-2018. The state-of-the-art financial uncertainty measure proposed by Ludvigson, Ma and Ng (2019) is found to predict movements in interest rates at different maturities. In particular, an increase in financial uncertainty is found to trigger a negative and significant response of both short-and long-term interest rates. The response of the short end of the yield curve (i.e., of short-term interest rates) is found to be stronger than that of the long end (i.e., of longterm ones). In other words, a financial uncertainty shock causes a temporary steepening of the yield curve. This result is consistent, among other interpretations, with medium-term expectations of a recovery in real activity after a financial uncertainty shock.