ORCID Profile
0000-0003-0265-4377
Current Organisation
University of Tasmania
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Publisher: Elsevier BV
Date: 2019
DOI: 10.2139/SSRN.3473524
Publisher: Wiley
Date: 03-06-2021
Abstract: Using daily data, we estimate a vector autoregression model to characterise the dynamic relationship between COVID‐19 infections in Australia and the performance of the Australian stock market, specifically the ASX‐200. Impulse response functions show that COVID‐19 infections in Australia have a significant positive effect on the performance of the stock market: a one standard deviation increase in new registered cases of COVID‐19 infections in Australia increases the daily growth rate of the ASX‐200 by around half a percentage point. This result is robust to alternative lag selections of the VAR model as suggested by alternative information criteria, including in the model control variables for stock market volatility, that is the ASX‐200 VIX the USD‐AUD exchange rate and the international oil price news by the World Health Organization regarding a COVID‐19 pandemic and public health emergency and the government‐imposed shutdown of parts of the Australian economy. We also present estimates of the dynamic relationship between the daily growth rate of the Dow Jones and daily new cases of COVID‐19 infections in the United States. The US data show, similar to the Australian data, that there is a significant positive effect of COVID‐19 infections on the performance of the stock market.
Publisher: Elsevier BV
Date: 2019
DOI: 10.2139/SSRN.3507151
Publisher: Elsevier BV
Date: 08-2016
Publisher: Elsevier BV
Date: 2017
DOI: 10.2139/SSRN.2963431
Publisher: Elsevier BV
Date: 2019
DOI: 10.2139/SSRN.3507158
Publisher: Elsevier BV
Date: 09-2016
Publisher: Elsevier BV
Date: 2020
DOI: 10.2139/SSRN.3684200
Publisher: Elsevier BV
Date: 08-2017
Publisher: Elsevier BV
Date: 07-2013
Publisher: Elsevier BV
Date: 10-2014
Publisher: Elsevier BV
Date: 2017
DOI: 10.2139/SSRN.2899963
Publisher: Wiley
Date: 12-06-2021
Abstract: Understanding the impact of economic uncertainty shocks at the industrial disaggregated level is critical for both fiscal and monetary policy response. We estimate an SVAR model using quarterly Australian data from 1987:2 to 2018:4. The results of this paper emphasise that in idual industries have a unique response to an economic uncertainty shock and do not necessarily reflect the response of the broader aggregate macroeconomy. We found the following stylised facts: (i) The construction industry is the most negatively impacted industry by an economic uncertainty shock in terms of investment, output and employment in Australia, (ii) The financial and insurance services industry also endures a substantial decline to the shock, particularly on investment and employment indicators, and (iii) Economic uncertainty is shown to have less impact on the mining, health care and social assistance and public administration and safety industries.
Publisher: Federal Reserve Bank of Dallas
Date: 2017
DOI: 10.24149/GWP311
Publisher: Informa UK Limited
Date: 26-04-2019
Publisher: Elsevier BV
Date: 2020
DOI: 10.2139/SSRN.3583295
Publisher: Elsevier BV
Date: 10-2013
Publisher: Informa UK Limited
Date: 20-07-2021
Publisher: Informa UK Limited
Date: 13-07-2017
Publisher: Elsevier BV
Date: 2017
DOI: 10.2139/SSRN.2992983
Publisher: Elsevier BV
Date: 06-2021
Publisher: Elsevier BV
Date: 04-2015
Publisher: Elsevier BV
Date: 12-2020
Publisher: Federal Reserve Bank of Dallas
Date: 2017
DOI: 10.24149/GWP306
Publisher: Wiley
Date: 25-04-2020
DOI: 10.1111/CAJE.12442
Abstract: This paper proposes world steel production as an indicator of global real economic activity. World steel production data is published with only a one‐month delay, thereby providing timely information for world real GDP forecasters. We find that world steel production and Lutz Kilian's (2009) index of global real economic activity generate large gains in forecasting world real GDP, relative to an autoregressive benchmark. A forecast combination of world steel production, Kilian's (2009) index of global real economic activity and an index of the industrial production of OECD countries plus six non‐OECD emerging economies produces significant gains in forecasting world real GDP, relative to an autoregressive benchmark
Publisher: Federal Reserve Bank of Dallas
Date: 2017
DOI: 10.24149/GWP303
Publisher: Federal Reserve Bank of Dallas
Date: 05-2020
DOI: 10.24149/GWP385
Publisher: Elsevier BV
Date: 03-2021
Publisher: Federal Reserve Bank of Dallas
Date: 05-2020
DOI: 10.24149/GWP388
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 2020
DOI: 10.2139/SSRN.3624676
Publisher: Elsevier BV
Date: 2020
DOI: 10.2139/SSRN.3750525
Publisher: Informa UK Limited
Date: 27-01-2022
Publisher: Elsevier BV
Date: 2017
DOI: 10.2139/SSRN.2908591
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 2018
DOI: 10.2139/SSRN.3283417
Publisher: Informa UK Limited
Date: 18-11-2022
Publisher: Elsevier BV
Date: 2017
DOI: 10.2139/SSRN.2942479
Publisher: Informa UK Limited
Date: 22-11-2019
Publisher: Elsevier BV
Date: 2016
Publisher: Federal Reserve Bank of Dallas
Date: 2017
DOI: 10.24149/GWP295
Publisher: Elsevier BV
Date: 2016
Publisher: Federal Reserve Bank of Dallas
Date: 12-2019
DOI: 10.24149/GWP376
Publisher: Elsevier BV
Date: 09-2013
Publisher: Federal Reserve Bank of Dallas
Date: 10-2019
DOI: 10.24149/GWP370
Publisher: Elsevier BV
Date: 10-2016
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 07-2015
Publisher: Wiley
Date: 03-2013
No related grants have been discovered for Joaquin Vespignani.