Government Intervention of Market Economy in China During the COVID-19 Pandemic

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Research Paper on Government Intervention of Market Economy in China Under Special Circumstances (COVID-19)
Introduction
COVID-19 outbreak came as a shock event with unexpected unreliability concerning how the pandemic is and whether when the vaccination will be developed. In return, different governments in the entire continent struggled with emergency activities like restricting both local and international travels, establishing quarantines, testing, lockdowns, and market conglomerations. The major aim of the interventions was to assure individuals' social isolation to avoid further transmission of a contiguous pandemic while reducing adverse economic effects. However, these interventions brought additional variability concerning their efficiency and results. For example, the government saw the essence of lockdowns in reducing new infections; it raised distancing in economics as well as affecting the live hood and the revenues of millions of individuals across China. Despite that the long-lasting government intervention effects yet have to be identified, in this research, I observed the expected outcomes by visualizing the financial markets' reactions to these interventions. Like a series of opinionated and sophisticated investors, financial markets provide a stimulating survey of the future expected results. According to Liu, Lin, and Wu, the stock market provides vital information in fast, adaptable, and comprehensive situations (554).
However, I observed stock market response on the three types of government intervention: social isolation, containment, and medical reactions, and financial support conglomeration. Social isolation measure involves closing public places like schools, public transport, hotels, recreational grounds, workplaces, etc. Containment and medical reactions include government public awareness campaigns concerning the pandemic, quarantining, and testing policies. Furthermore, financial support aids include the country's financial assistance to the household in terms of dept reliefs, transfers of cash, or other utility payments.
These interventions have both directly or indirectly affected the stock market. For direct results, measures of social isolation may have specific adverse impacts on financial market reinstatement by consequently affecting market activities. On the contrary, the country's containments, health reactions, and income aids may lead to constructive economic reactions, thereby decreasing the negative effects of the economy due to the pandemic.
Indirectly, the effects of these intervention channels through a reduction in the pandemic strength. Strict and comprehensive government restrictions such as social distancing measures and strict segregation policies, testing aggressively, and government financial support might help reduce more infections. According to recent views, stock markets in China have responded to the pandemic with a strong negative comeback. Shen, Wu, and Chand argue that comprehensive actions of the government reduce the strength of spread locally, weakening the market negativity response to the increase in cases confirmed are weakened (282).
Datasets of financial market returns are used to analyze the government’s reaction and increase in confirmed cases from different regions of China throughout January to April 2020. After observing countries' stock market trends over the period, results show that isolation measures impact the return of stocks directly and positive effects indirectly by decreasing the extent to which cases confirmed rises. The results prove that the economy has priced due to government interventions.
Data Collection
For the importance of the research, I collected data from the following sources: I obtained data concerning daily stocks of market returns from the website. Next, I downloaded reports of China daily confirmed cases from the Coronavirus Resource Centre website. Furthermore, I obtained a government data reaction index from the dataset website of OxCGRT. Finally, I used selected samples from the beginning of January to mid-April because confirmed cases and government reactions were within this period. For instance, Liu, Lin, and Wu argue that the crucial period regarding economic reaction to the pandemic was from the beginning of 2020 to mid-April, the same year.
(561). However, global government reactions to the disease declined from mid-April onwards.
Methodology
Following Li, Wu, and Song, I specified pooled OLS model to observe directive effects of a country’s interventions on the trading economy (568).
Y c, t = αc + β1(∆Government response c, t) + β2 (COVID-19 c, t-1) + C-1C-1βcCc+t-1T-1ℇtDt+ℇc,t.
(Y) represents a dependable variable that calculates returns of the financial market in a particular country (c) represents a constant term, t represents the time of the day, and alpha c is used as a constant. Daily market returns are equal (value of index t – the value of index t-1). From the OxCGRT dataset, government reaction is shown by daily interchange in three consecutive country's pandemic indications. Inflexible index, control, and medical index, and financial aid index are among the variables. L...