Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster

Jena, Pradyot Ranjan; Majhi, Ritanjali; Kalli, Rajesh; Managi, Shunsuke; Majhi, Babita

doi:10.1016/j.eap.2020.12.013

Cited by 111 publications

(65 citation statements)

References 15 publications

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“…The negative impact of the pandemic on the economies of various countries has already been acknowledged in both local [19][20][21] and global terms [22][23][24]. The first gross domestic product (GDP) forecasts have also been already provided [25]. It is believed that the decline of global economy stems from two primary factors [23].…”

Section: Introductionmentioning

confidence: 99%

The Impact of the SARS-CoV-19 Pandemic on the Global Gross Domestic Product

Korneta

Rostek

2021

IJERPH

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The rapid, unexpected, and large-scale expansion of the SARS-CoV-19 pandemic has led to a global health and economy crisis. However, although the crisis itself is a worldwide phenomenon, there have been considerable differences between respective countries in terms of SARS-CoV-19 morbidities and fatalities as well as the GDP impact. The object of this paper was to study the influence of the SARS-CoV-19 pandemic on global gross domestic product. We analyzed data relating to 176 countries in the 11-month period from February 2020 to December 2020. We employed SARS-CoV-19 morbidity and fatality rates reported by different countries as proxies for the development of the pandemic. The analysis employed in our study was based on moving median and quartiles, Kendall tau-b coefficients, and multi-segment piecewise-linear approximation with Theil–Sen trend lines. In the study, we empirically confirmed and measured the negative impact of the SARS-CoV-19 pandemic on the respective national economies. The relationship between the pandemic and the economy is not uniform and depends on the extent of the pandemic’s development. The more intense the pandemic, the more adaptive the economies of specific countries become.

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Section: Introductionmentioning

confidence: 99%

The Impact of the SARS-CoV-19 Pandemic on the Global Gross Domestic Product

Korneta

Rostek

2021

IJERPH

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“…Trade in intermediate inputs along global value chains might amplify the effects. By using a neural network approach calibrated for 8 large countries, Jena et al ( 2021 ) found double-digit losses in GDP growth. Because of oversimplified assumptions, the simulation evidence should be probably interpreted as an upper bound.…”

Section: Studies Of the Economic Impact Of Social Distancingmentioning

confidence: 99%

Lockdowns and the US Unemployment Crisis

Dreger

Gros

2021

EconDisCliCha

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The Covid-19 pandemic led to an unprecedented decline of economic activity at the globe scale. To slow down the spread of the virus, most governments reacted with various measures of social distancing, such as mobility controls, business and school closures, etc. We investigate the short-term impact of social distancing measures on the US labour market, using a panel threshold model with high frequency (weekly) data on unemployment across US states allowing for heteroscedasticity. Labour is a key input in production, and thus a good proxy for the state of the economy. We find that changes in the restrictiveness of mandated social distancing, as measured by the Oxford Stringency Index, exert a strong impact on unemployment. The bulk of the reaction of unemployment to a change in the social distancing restrictions does not arise immediately, but with a delay of 2–4 weeks. In addition, the impact is asymmetric. If the policies switch to tighter regulations, the increase in unemployment is quicker and higher in absolute value than a decrease after relaxation. The state of the pandemic, proxied by the number of new infections and fatalities, constitutes only a marginal factor.

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“…Assessing the magnitude of tax revenue losses due to a pandemic requires predicting them in the absence of a shock. To cope with this, scientists offer different methodological techniques: calculating expected changes in sales and using tax revenue elasticities (Chernick et al, 2020), building VAR models or artificial neural networks (Jena et al, 2021). In our research, we prefer constructing ARiMA models for stationary time series.…”

Section: Literature Reviewmentioning

confidence: 99%

How the 2020 pandemic affected tax revenues in Russian regions?

Малкина¹

2021

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Research background: The 2020 pandemic has proven to be stressful for regional tax systems. However, these systems reacted differently to lockdown and a decline in business activity, which was associated with both their structures and the specifics of their development. Purpose of the article: The aim of the article is to assess the impact of the 2020 pandemic on tax revenues of Russian regions, as well as to analyze the factors contributing to the resilience of regional tax systems to epidemiological crises. Methods: The study is based on monthly data from the Federal Tax Service of the Russian Federation on total tax revenues in 83 Russian regions for 2013?2020. For data up to March 2020, we construct stationary time series and plotted ARiMA regressions. Based on them, we forecast tax revenues for the period from April to December 2020, if there were no pandemic. The impact of the pandemic is calculated as the deviation of actual tax revenue from the forecast for the corresponding 9 months. Findings & value added: We find that the impact of the pandemic on tax revenues varies over time and space. The crisis hit the fiscal system most negatively in the first three full months of the lockdown (April?June 2020). Some mining regions of the Urals, Western and Eastern Siberia, specializing in the extraction of oil and gas, as well as non-ferrous metals, turned out to be the most vulnerable to the pandemic. The most resistant to it are the central and southern regions of the European part of Russia. Calculation of Pearson's correlations shows that the greatest drop in tax revenues occur in regions with a larger share of the mining industry in gross value added and MET in tax revenues, with a higher GRP per capita and an increased level of general economic instability. The smallest decline in tax revenue, or even its growth, is observed in regions with a larger share of personal income tax and property tax in tax revenues, a higher share of trade and processing industries, social sphere and public administration in gross value added, a higher degree of economic diversification and a larger share of small business in total turnover. The obtained results are applicable to manage the resilience of tax systems to epidemiological crises.

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Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster

Cited by 111 publications

References 15 publications

The Impact of the SARS-CoV-19 Pandemic on the Global Gross Domestic Product

The Impact of the SARS-CoV-19 Pandemic on the Global Gross Domestic Product

Lockdowns and the US Unemployment Crisis

How the 2020 pandemic affected tax revenues in Russian regions?

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