اثر ویروس کرونا بر بخش‌های کشاورزی، صنعت و خدمات در چارچوب مدل DSGE

نوع مقاله : مقاله پژوهشی

نویسنده

هیأت علمی گروه بانکداری پژوهشکده پولی و بانکی

چکیده

ارزیابی اثر ویروس کرونا بر بخش‌های مختلف اقتصادی با نا اطمینانی همراه است. به‌طوری‌که برای سیاست‌گذاران اقتصادی اتخاذ سیاست مناسب اقتصاد کلان مشکل است. آن‌چه اهمیت دارد، پیش‌بینی شدت و عمق این اثرات است تا بتوان سیاست مناسب را برای ممانعت از ایجاد بحران اتخاذ نمود. در این مقاله با بکارگیری مدل SIR در چارچوب DSGE اثر بیماری کرونا بر بخش‌های مختلف اقتصادی اعم از کشاورزی، صنعت و خدمات بررسی شده است. به ‌همین منظور 5 بخش خانوار، بنگاه، دولت، بانک مرکزی و بخش نفت در نظر گرفته شده است. در بخش خانوار عرضه نیروی کار به سه قسمت، افراد بیمار، افراد ناقل و افراد تعیین تکلیف‌ شده ‌(فوت‌شده، بهبود‌یافته و سالم) تقسیم شده‌اند. بنگاه‌ها نیز به سه بخش کشاورزی، صنعت و خدمات تقسیم شده‌اند. نتایج بررسی، حاکی از کاهش تولید، سرمایه‌گذاری، مصرف و اشتغال در بخش‌های مختلف اقتصادی است. علاوه بر آن تولید در بخش صنعت بیش از سایر بخش‌ها کاهش خواهد یافت. همچنین اثرات مثبت شوک مثبت درآمد نفتی به دلیل همراهی با شوک ویروس کرونا، کاهش خواهد یافت.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

The effect of the corona virus on agriculture, industry and services in the DSGE model

نویسنده [English]

  • Azam Ahmadyan
Assistant Professor, Faculty in Banking Department, Monetary and Banking Research Institute, Tehran, Iran
چکیده [English]

Introduction: The corona virus was detected in Iran in the winter of 2019. Since then, certain decisions have been made such as keeping social distance, reducing traffic, closing schools, reducing office hours and locking jobs down such as restaurants, stadiums and other high-risk jobs. All these have led to a decrease in production and employment in Iran. But, this effect has been different in different economic sectors. The industry sector is affected by the corona virus, with the intensification of arrears of production units (such as bank debts, social security insurance and taxes), contract problems of project-oriented companies in epidemic conditions, ‌ reduced access to export markets, and reduced production due to reduced imports of required intermediaries. The agricultural sector is also affected in the supply chain, demand and liquidity, firms, supply of labor, consumption of goods and services, and especially income of consumers and producers of agricultural products. In the short and long terms, on the household economies are and will be affected. In the service sector, the jobs that are most likely to spread the disease, such as transportation, restaurants and hotels and clothing, face a decrease in employment and income. Therefore, it is important is to measure the intensity and extent of the corona effect on different economic sectors separately.
Methodology: The framework in this study is based on the New Keynesian standard model and according to the studies of Toda (2020), Pochum et al. (2020), Bartik et al. (2020), Mensa et al. (2008), and Agnor et al. (2012) adjusted to expand to the corona shock. The model consists of five sections: households, enterprises, government, oil and monetary affairs. According to the purpose of this article, which examines the vulnerability of different economic sectors versus the outbreak of coronavirus, three economic sectors including agriculture, industry and services are explored. In this article, to design a household sector, the standard DSGE model has been used. Then, using the SIR model such as Toda study (2020), labor force is divided into three groups including susceptible, infected and recovered people. A shock is considered for the corona virus, and its effect on production cost is investigated.
Results and Discussion: The analysis of corona disease shock on consumption and employment in different economic sectors indicates that employment in the agricultural sector is increasing, but it is declining in industry and services. At the same time, the decrease in employment in the service sector is more than that in the industrial sector. Despite the corona shock, the consumption of agricultural goods has decreased, but the consumption of industrial goods and services has risen, and the consumption of service goods has increased more than the goods of industry.
The study of corona shock on investment and production indicates that investment in the agricultural sector is increasing, but it is declining in industry and services. The decline of the investment in industry is greater than that in services. The study of these effects on the production of various economic sectors also shows that production has increased in the agricultural sector but has decreases in the industrial and service sectors. The decline of production in the industrial sector is more than that in the service sector.
With a positive oil revenue shock, consumption and employment in various sectors of the economy has increased, but it is less than before the corona virus spread. Consumption in the industrial sector is also increasing more than in the other two sectors. However, employment in the service sector has increased more than in the other sectors due to the corona shock, and its decrease is more than that in the other sectors.
A positive oil revenue shock without a corona shock will lead to lower prices in various sectors of the economy, improved investment, reduced production costs and improved production, but the combination of this shock with the negative shock of the corona virus reduces the positive effects.
Conclusion: The results of the study indicate an increase in prices and production costs and a decrease in production, employment, investment and consumption. The study of the effect of corona shock on various economic sectors shows that, although production, investment and consumption in the industrial and service sectors are declining, these variables are improving in the agricultural sector. In addition, the rate of decrease in production, investment and consumption in the industrial sector is more than that in the other sectors. The study of the effect of positive oil revenue shock shows that, in the absence of corona virus shock, positive oil revenue shock would lead to lower prices, wages and production costs in various economic sectors. It would also lead to increased investment and production in different economic sectors. However, a combination of this shock and the negative shock of the corona virus has reduced its positive effects. Prices and production costs have increased in various economic sectors due to the reduction of investment, production, consumption and employment. At the same time, these negative effects on the industrial sector will be even more on the sectors of services and agriculture.
Corona shock on different sectors of the economy, which coincided with the conditions of sanctions, has intensified the economic recession. It is, thus, recommended to accurately measure the adverse effects based on the field of activity in different sectors of the economy. Then, according to the amount of damage inflicted on different sectors of the economy, support packages such as tax reduction or exemption and increase subsidies should be taken into account. Appropriate policies are also needed to strengthen investment in various sectors of the economy. This requires stability in monetary and fiscal policies. Credit protection policies such as offering low-cost facilities, either with long-term repayments or with delays, should be considered by policymakers. Given the current situation, it is better to reinforce electronic services.

کلیدواژه‌ها [English]

  • Corona virus
  • Economic sectors
  • DSGE model
Agenor, P.R. Alper, K. and Pereira Da Silva, L. A. (2012). "Capital Requirements and Business Cycles with Credit Market Imperfections". Journal of Macroeconomics 34(3): 687-705.
Anderson, R. M. Heesterbeek, H. Klinkenberg, D. and Hollingsworth, T. D. (2020). "How will Country-Based Mitigation Measures Influence the Course of the COVID-19 Epidemic?". Lancet 395(10228): 931-934.
Atta-Mensa, J. & Dib, A. (2008). "Bank Lending, Credit Shocks, and the Transmission of Canadian Monetary Policy". International Review of Economics and Finance 17(1): 159-176.
Attar, K. Fatahi, S. and Sohaili, K. (2019). "Investigating the Impact of Total Factor Productivity Shocks of Agricultural, Industrial and Services Sectors on the Macro and Sectoral Variables of Iran’s Economy: DSGE Approach". Applied Theories of Economics 6(1(20)): 129-148. (In Persian)
Baker, S. R. Bloom, N. Davis, S. J. and Terry, S. J. (2020). "COVID-Induced Economic Uncertainty". NBER Working Paper 26983: 1-16.
Barro, R. J. Ursua, J. F. and Weng, J. (2020). "The Coronovirus and the Great Influenza Pandemic: Lessons from the Spanish Flu for the Coronovirus’s Potential Effects on Mortality and Economic Activity". NBER Working Paper No. 26866: 1-26.
Bartik, A. W. Bertrand, M. Cullen, Z. B. Glaeser, Edward L. Luca, M. and Stanton, C. T. (2020). "How Are Small Businesses Adjusting to COVID-19? Early Evidence from a Survey". NBER Working Paper 26989: 1-35.
Bloom, N. Bunn, P. Chen, S. Minzen, P. and Smietanka, P. (2020). "The Economic Impact of Coronavirus on UK Businesses: Early Evidence from the Decision Maker Panel". https://voxeu.org/article/economic-impact-coronavirus-uk-businesses, accessed: 4/28/2020.
Brooks, S. P. and Gelman. A. (1998). "Alternative Methods for Monitoring Convergence of Iterative Simulations". Journal of Computational and Graphical Statistics 7: 434-455.
Buchheim, L. Dovern, J. Krolage, C. and Link, S. (2020). "Firm-Level Expectations and Behavior in Response to the COVID-19 Crisis". CESifo Working Paper No. 8304: 1-28.
Correia, S. Luck, S. and Verner, E. (2020). "Pandemics Depress the Economy, Public Health Interventions Do Not: Evidence from the 1918 Flu". SSRN Electronic Journal: 1-45.
Dingel, J. I. and Neiman, B. (2020). "How Many Jobs Can be Done at Home?". NBER Workinh Paper No. 26948: 1-19.
Dixit, A. K. and Stiglitz, J. E. (1977). "Monopolistic Competotion and Optimum Product Diversity". American Economic Review 67(3): 297-308.
Eichenbaum, M. S. Rebelo, S. and Trabandt, M. (2020). "The Macroeconomic of Epidemics". NBER Working Paper No. 26882: 1-48.
Gali, J. Smets, F. and Wouters, R. (2012). "Unemployment in an Estimated New Keynesian Model". NBER Working Paper No. 17084: 1-53.
Guerrieri, V. Lorenzoni, G. and Straub, Ludwig. W. I. (2020). "Macroeconomic Implications of Covid-19: Can Negative Supply Shocks Cause Demand Shortages?". NBER Working Paper No. 26918: 1-37.
Harko, T. Lobo, F. S. N. and Mak, M. K (2014). "Exact Analytical So- Lutions of the Susceptible-Infected-Recovered (SIR) Epidemic Model and of the SIR Model with Equal Death and Birth Rates". Applied Mathematics and Computation 236: 184-194.
Hassan, T. A. Hollander, S. Van Lent, L. and Tahoun, A. (2020). "Firm-Level Exposure to Epidemic Diseases: COVID-19 SARS, and H1N1". NBER Working Paper 26971: 1-67, National Bureau of Economic Research.
Kermack, W. O. and Mckendrick, A. G. (1927). "A Contribution to the Mathematical Theory of Epidemics". Proceedings of the Royal Society of London Series A 115(722): 700-721.
McKibbin, W. and Fernando, R. (2020). "The Global Macroeconomic Impacts of COVID-19: Seven Scenarios". Australia Research Council Centre of Excellence, CAMA Working Paper No.19/2020: 1-45.
Nejati, M. (2017). "The Role of Foreign Direct Investment in Iran's Economy Using the Computable General Equilibrium Model". The Journal of Economic Policy 9(18): 65-100. (In Persian)
Rotemberg, J. J. (1982). "Monopolistic Price Adjustment and Aggregate Output". Review of Economic Studies 49(4): 517-531.
Toda, A. A. (2020). "Susceptible-Infected-Recovered (SIR) Dynamics of Covid-19 and Economic Impact". Covid Economics, Vetted and Real- Time Papers (CEPR) 1: 1-15.
Zare, M. H. (2020). "Dynamic Effects of Tariff Reduction on the Value Added in Iran’s Main Economic Sectors". The Journal of Economic Policy 12(23): 79-319. (In Persian)