The constant presence of natural and anthropogenic hazards in the social development processes suggests the need to take them into account when predicting its development. Today, due to the spread of the COVID-19 pandemic, various economic instruments have been implemented in most countries to support the population and stabilize the economy after taking emergency measures to prevent the incidence of coronavirus infection. Based on the expert survey, the authors have determined the socio-economic and macroeconomic impact of the COVID-19 pandemic, different approaches to respond in various life spheres of the population, as well as measures undertaken by different countries to support the population and national economy in the context of the COVID-19 pandemic.
The prime objective of the current study is to investigate the total sovereign debt on the economic growth of Thailand. Since domestic debt is considered to be an economic growth stimulator particularly during the period of recession, therefore, its instruments are intended to analyze in this research. In a country, the lack of funds may negatively influence economic growth, therefore, most countries like to use external debt to finance its expenditures, such as Thailand. This situation can be improved by focusing on these countries developmental research. In Thailand, the information scarcity regarding domestic debt acts as a policy constraint while designing an effective domestic debt mobilization policy. Thus, the present study predominantly aims to investigate the domestic debt effects on Thailand economic growth. The study has examined the domestic debt effects on the economic growth, during 1998-2018. The variables used in this study are extracted from the previous literature and the theoretical framework used in this study. The key variables analyzed are Treasury bills, Government securities, and Investment issues, not forgetting the loans mainly housing loans fund, market loans of Thailand. The study has used the Johansen and Juselius co-integration approach to examine the long run relationship while ECM approach was used to see the speed of adjustment in the short run. Furthermore, we have conducted the Lagrange Multiplier test to all variables to check the presence of autocorrelation. The results show that there is no autocorrelation in the variables. For the instrument of Government securities, we have found that all the variables which are financial sector, social security institutions, insurance companies, and financial sector show a statistically significant result in long run analysis. On the other hand, short run analysis based on ECM model shows that social security institution, insurance companies, financial sector and foreign holders turn to be significant while public sector show insignificant results. The result for ECM also shows that the model is well adjusted in the short run.