Introduction

• Author: Efrem Castelnuovo
• DOI: http://doi.org/10.1111/1467-8462.12344
• Published date: 01 September 2019
• Date: 01 September 2019

The Australian Economic Review, vol. 52, no. 3, pp. 321–322 DOI: 10.1111/1467-8462.12344

Policy Forum: Uncertainty and the Business Cycle —Some New

Findings

Introduction

Efrem Castelnuovo*

Uncertainty has been a pretty hot topic among

academics and economists working in policy

circles since the global financial crisis. I

believe we now know a lot more about its

effects on the business cycles of a variety of

countries than we knew before the crisis.

Uncertainty tends to be recessionary, it exerts

stronger effects when the economy is already

experiencing difficulties from an aggregate

standpoint, or when financial markets operate

less smoothly, and it tends to harm

macroeconomic policies’effectiveness.

In spite of the impressive amount of knowl-

edge accumulated so far, gaps in the literature are

still present. First, we do not know much about

how long term rates respond to uncertainty

shocks. While dynamic stochastic general equili-

brium models approximated at third order offer

predictions on how the term structure responds to

uncertainty shocks, the literature has not yet

produced many model‐free reduced‐form types

of regressions on the link between uncertainty

and long rates. This is a big hole, given the

relevance of long rates on consumption and

investment decisions. Second, we need to

sharpen our understanding of monetary policy

risk management. Uncertainty is clearly relevant

from a policy standpoint. But do policymakers

systematically monitor uncertainty? Moreover,

do they disagree on the economic outlook, and if

so,doesthisinfluence their decisions? Third, we

need proxies for uncertainty for a broader set of

countries than the G7. For example, how does

uncertainty evolve in a country like New Zealand

as opposed to, say, the United States?

This special issue addresses all these ques-

tions. The first paper, ‘Yield curve and financial

uncertainty: Evidence based on US data’,

estimates the response of the US yield curve

to a jump in financial uncertainty. I address this

question by conducting a local projection

analysis with US monthly data from

1962–2018. I find both ends of the yield curve

respond negatively and significantly. The

response of the short end of the yield curve is

stronger than that of the long end, that is, 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.

Turning to the impact of uncertainty on policy

decisions, Natalia Ponomareva, Jeffrey Sheen

and Ben Zhe Wang construct a novel measure of

uncertainty using expert monetary policy re-

commendation data for Australia. Their results

suggest that the Reserve Bank of Australia tends

to lower the cash rate when expert uncertainty is

high. This result, which is robust to using other

uncertainty measures, points to the possibility of

a risk management‐type approach by Australian

monetary policymakers.

Last but not least, Trung Duc Tran, Tugrul

Vehbi and Benjamin Wong construct two

novel uncertainty indices for New Zealand by

exploiting two separate data‐rich environ-

ments. The first index follows a data‐rich

approach to construct an estimate of uncer-

tainty based on a large New Zealand macro

dataset. The second index is built using freely

accessible and real‐time Google Trends data

* University of Melbourne, Melbourne, Victoria 3010

Australia and University of Padova Centre for Applied

Macroeconomic Analysis, Padova 35123 Italy; email

<efrem.castelnuovo@unimelb.edu.au>.

© 2019 The University of Melbourne, Melbourne Institute: Applied Economic & Social Research,

Faculty of Business and Economics

Published by John Wiley & Sons Australia, Ltd