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The Aggregate Demand
Aggregate demand is an important macroeconomic term that identifies the total need for products and services at a selected period. The measurement is sensitive to the changes in production, politics, events, and innovations; thus, various projects have been developed and released when the world faces the shocking COVID-19 pandemic. The article “A model of endogenous risk intolerance and LSAPs: Asset prices and aggregate demand in a “Covid-19” shock” published by Caballero and Simsek in 2021 explores how the pandemic influenced the finance industry. Indeed, the aggregate demand for monetary assets significantly increased when the COVID-19 emergency disrupted most businesses. The article stated that large-scale investments became more in demand due to the government’s responsibility and assistance, decreasing endogenous risks (Caballero & Simsek, 2021). Quantifications were based on market elasticity or inelasticity and large-scale asset purchases (LSAP); consequently, the aggregate demand became the fundamental variable.
The aggregate demand in monetary support for multiple industries resulted in the increased volume of debt, the overhang of which influenced the prices and resulted in additional challenges. Indeed, Caballero and Simsek (2021) claim that “as LSAPs increase asset prices, they improve banks’ balance sheets, which further reduces the required Sharpe ratio and raises asset prices” (p. 5530). The article suggested that the aggregate demand must be boosted to support the monetary policies and decrease the risks faced after the pandemic’s shock for the worldwide economy.
The Aggregate Supply
Aggregate supply is the total provision of goods made for a market with a specific price at a selected period. The measurement is frequently applied to the countries’ economies as it reflects the need for expanding or narrowing production to address the demand. The article “The effect of imperfect information on aggregate supply: Case study the economy of Iran” written by Hosseini and Roshan explores Iranian markets and the changes in prices from 1966 to 2017. The influence of non-submitted and delayed information on the economic conditions was described by comparing the calibrated parameters with the actual data (Hosseini & Roshan, 2020). Aggregate supply changes with the updates in technologies, demand, and unexpected conditions occurrence, and the article concluded that the Iranian economy had multiple cases when the production did not have to adjust.
The scientists analyzed the prices’ change retrospectively to identify the markets’ reaction on partial and imperfect information structures to determine how the aggregate supply changed. Hosseini and Roshan (2020) concluded that “the introduced model can simulate the impact of shocks on macroeconomic variables” (p. 287). Aggregate supply was presented in the non-vertical form, which is flexible to diverse factors and responds to the demands of different periods of the Iranian economy.
The Simple Aggregate Expenditure Model
The simple aggregate expenditure model addresses how the gross domestic product (GDP) relates to planned spending and identifies how consumption, investments, and exports influence the rates. The structure is applicable for diverse industries, and the “Modelling distribution of aggregate expenditure on tourism” article published by Gómez–Déniz and Pérez–Rodríguez in 2019 used it for assessing tourists’ behaviors. Scientists studied the visitors’ length of stay at diverse locations to analyze their impact on the economy and a place’s GDP and develop a compound model of allocation.
The simple aggregate expenditure model can be applied through the statistical distribution to estimate multiple parameters simultaneously. In the study, the length of stay and location-based expenses were calculated together, revealing the compound growth of variables (Gómez–Déniz & Pérez–Rodríguez, 2019). The aggregate expenditure revealed that although the covariates might occur in the model implementation, it is applicable for studying tourism and its economic benefits for countries.
References
Caballero, R. J., & Simsek, A. (2021). A model of endogenous risk intolerance and LSAPs: Asset prices and aggregate demand in a “Covid-19” shock.The Review of Financial Studies, 34(11), 5522-5580. Web.
Gómez–Déniz, E., & Pérez–Rodríguez, J. V. (2019). Modelling distribution of aggregate expenditure on tourism.Economic Modelling, 78, 293-308. Web.
Hosseini, S. F. F., & Roshan, Y. E.., (2020). The Effect of imperfect information on aggregate supply: Case study the economy of Iran.Journal of Macroeconomics, 14(28), 261-290. Web.
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