Place‐Based Policies and Nowcasting

• Published date: 01 September 2023
• Author: Ashton Silva,Maria Yanotti,Sarah Sinclair,Sveta Angelopoulos
• Date: 01 September 2023
• DOI: http://doi.org/10.1111/1467-8462.12526

The Australian Economic Review, vol. 56, no. 3, pp. 363–370 DOI: 10.1111/1467-8462.12526

Place‐Based Policies and Nowcasting

Ashton de Silva, Maria Yanotti, Sarah Sinclair and Sveta Angelopoulos*

Abstract

There is a growing need to gauge local economic

activity in real time. Localised economic chal-

lenges have been emphasised in the wake of the

COVID‐19 pandemic. Real‐time trackers (such

as OECD trackers) and other nowcasting

applications typically correspond to national or

highly aggregated regions. In this discussion

paper, we briefly explore how unconventional

data might be used to produce nowcasts of local

economies. We argue that in the absence of

traditional nowcasting metrics, efforts to nowcast

local economies need a local perspective, with

data capture tailored to address heterogeneity

across three domains: (1) resources, (2) people

and (3) life.

1. Introduction

The term ‘nowcasting’is not unique to

economics. Meteorologists, for example,

have used it to describe the quest for local

weather forecasts over very short (1 h)

horizons (e.g., Pielke 1977). Economists

apply the term differently, typically referring

to the challenge of measuring current, near

future or recent levels of activity when official

measures are characterised by long delays and

only available at low frequencies (Banbura,

Giannone and Reichlin 2010).

Early nowcasting applications typically

employed bridge equations (Bańbura

et al. 2013) which seeded the development

of mixed frequency data sampling (MIDAS)

regressions. Many studies now use a variety

of methods, including MIDAS (Ghysels,

Santa‐Clara and Valkanov 2004; Ghysels,

Hill and Motegi 2016), dynamic factor models

(Giannone, Reichlin and Small 2008; Aastveit

and Trovik 2012; Chernis and Sekkel 2017;

Dahlhaus, Guénette and Vasishtha 2017;

Bragoli and Fosten 2018), and even an

amalgamation of the two—factor MIDAS

(Marcellino and Schumacher 2010). These

have been complemented by approaches

drawing on Bayesian techniques (Owyang,

Piger and Wall 2015; Bok et al. 2018).

Our discussion is not a review of now-

casting techniques; rather we focus on a

conceptual aspect that we believe is crucial

for Australian policy analysts. Specifically,

we outline an approach that nowcasters may

use employing unconventional data in place‐

based

1

policy settings. This approach is also

* deSilva, Sinclair and Angelopoulos: School of

Economics, Finance and Marketing, RMIT University,

Melbourne, 3000, Victoria, Australia; Yanotti: Tasmanian

School of Business and Economics, University of

Tasmania, Launceston, Tasmania, Australia.

Corresponding author: de Silva, email ashton.desilva@

rmit.edu.au.

© 2023 The Authors. The Australian Economic Review publishedby John Wiley & Sons Australia, Ltd on behalf of The University of

Melbourne, MelbourneInstitute: Applied Economic & Social Research, Faculty of Businessand Economics.

This is an open access article underthe terms of the Creative Commons Attribution License, which permits use, distributionand

reproduction in any medium,provided the original work is properly cited.