Remittances have grown in measurement and importance. While such inflows can improve economic growth, they may additionally also reason domestic foreign money to respect and hurt exports -an aspect of impact generally referred to as the Dutch disease. Statistics exhibit that remittances influx to Indonesia grew from 1% of GDP in 1984 to over 9% of GDP in 2020. Theoretically, such a massive influx of overseas foreign money into an economy may lead to Dutch diseases.Methodology: For this purpose, they learn about employing the Autoregressive Distributed Lag Model (ARDL) to observe the impact of migrant remittances on the actual fantastic exchange charge spanning the duration from 1984 to 2020. Findings: In the long run, they find out about finds an effective relationship between migrants' remittances and the real high-quality change rate, which means that evidence of Dutch Disease risk in Indonesia. This grasp of the Indonesia rupiah relative to different competing countries encourages import and discourages export, leading to the Dutch disease effect. Originality/Value: This study, therefore, investigated whether the large inflow of remittances into the economic system reasons Dutch disease.
This study examined the response of stock prices on the China Stock Exchange (SSE) and Real Estate prices to COVID-19 using an event study approach and the GARCH model. Methodology: In this study, the dimensions and key components of the use of large data obtained from the Internet of Things (IoT) in an industry's supply chain are investigated as a case study. Finally, a model for implementing an agile and lean supply chain based on IoT data analysis to improve the supply chain performance of these industries during emergency drug distribution during critical conditions is presented. Findings: We measure volatility spillovers by defining the volatility of each sector in the SSE index. In this study, we investigate the volatility of China stock market. Furthermore, we analyze the dynamic connectedness during COVID-19 pandemic periods to identify the changes in their relationship following the two categories. These empirical findings have several important implications for portfolio managers, policymakers, and investors. Originality/Value: This paper focuses on investigating the impacts of the novel coronavirus (COVID-19) on the China stock market volatility from a GHARCH and VAR model point of view. The GHARCH model used proves that during the COVID-19 pandemic, stock price volatility and real estate price volatility increases and lead to a decrease in abnormal returns. The empirical findings also validate the efficient market hypothesis theory related to the study of events and the theory of financial behavior related to uncertainty.
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