González Laxe, Fernando and Da Rocha Alvarez, Jose Maria and Armesto Pina, José Francisco and Sanchez-Fernandez, Patricio and Lago-Peñas, Santiago (2020): Economía de Galicia tras el COVID-19: prospectiva de escenarios. Published in: Informe de Conxuntura Socioeconómica de Galicia , Vol. 2, No. I (8 May 2020): pp. 1-20.
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Abstract
This work estimates the impact of COVID-19 in the year 2020, drawing possible recovery scenarios in the medium term. For this purpose, two methodologies are combined: on the one hand, it anticipates the quarterly evolution throughout 2020 of the 30 branches of activity; on the other, scenario simulation is based on a dynamic general equilibrium model that anticipates the reaction of an economy to an exogenous shock. The results for the Galician economy show that the contraction in economic activity ranges between 8.5% of GDP in an optimistic scenario and 12.7% in a pessimistic one.
Item Type: | MPRA Paper |
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Original Title: | Economía de Galicia tras el COVID-19: prospectiva de escenarios. |
English Title: | Economy of Galicia after COVID-covid-19: prospective forecastings. |
Language: | Spanish |
Keywords: | COVID-19, economic impact, forecasting, GDP, Galicia |
Subjects: | A - General Economics and Teaching > A1 - General Economics > A10 - General C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods E - Macroeconomics and Monetary Economics > E0 - General > E00 - General E - Macroeconomics and Monetary Economics > E0 - General > E01 - Measurement and Data on National Income and Product Accounts and Wealth ; Environmental Accounts R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R11 - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes |
Item ID: | 100483 |
Depositing User: | Patricio Sanchez-Fernandez |
Date Deposited: | 19 May 2020 07:08 |
Last Modified: | 19 May 2020 07:08 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/100483 |