This research strives to prove whether village funds can effectively increase resilience in rural areas in the post-pandemic period, especially in alleviating rural poverty. There are two objectives in this study, namely: (i) to estimate the impact of village funds on poverty levels in rural areas; and (ii) to identify factors that influence growth. The Year 2021 is assumed to be the post-pandemic period because of improvement in economic growth. The analytical model applied in this research is three-stage least squares (3sls). This study has two endogenous variables: economic growth and poverty in rural areas. The results showed no effect of village funds on rural poverty. In addition, village funds have also not affected economic growth. The policy of refocusing the use of village funds in overcoming the covid pandemic is thought to be the most potent cause of the absence of village funds on poverty and economic growth.
The COVID-19 pandemic has shaken Indonesia's macroeconomy. The economic growth experienced a contraction accompanied by an increase in poverty and unemployment. On the other hand, the COVID-19 pandemic also provides an opportunity for the growth of the digital economy. Digitalization that goes well will increase economic activity due to greater accessibility. However, there has been a decline in income during the pandemic. Therefore, this research aims to learn whether digitalization can improve income levels by understanding the impact of having a cell phone and accessing the internet for economic activities towards revenues. Here, the treatment effect is conducted to estimate the magnitude of that impact and identify the factors determining digitalization (have a cell phone and access the internet for economic activities). This research uses secondary data obtained from the Indonesia family life survey fifth wave. The result shows that the income of someone who can digitize is higher than that of non-digitalization participants, indicating the digitalization significantly contributes to increased revenues. Moreover, object perception for having a cell phone and accessing the internet for economic activities supports people's interest in digitalization mainly due to happiness, subjective well-being, and marital status.
Import becomes one of the components to calculate economic growth. During 1981-2014, a series of variation in Indonesia import has occured. In addition, the increase of GDP, the occurrence of domestic economic shocks, the increase of inflation rate, the increase of population and the increase of total reserves were alleged to influence the variation of Indonesia import. This research aims to analyze the factors affecting Indonesia imports. The variables used in this research are GDP growth, domestic economic shocks, inflation rate, population, and total reserves. Econometric analysis model used in this research is Error Correction Model (ECM). The results of this research reveal several outcomes: (1) the data is stationary at first difference; (2) the data is cointegrated meaning that there is a connection in long-term parameters; and (3) ECT coefficient/speed of adjustment is -0.6881 and significant is at ? = 5% meaning that the model used is valid. The conclusions of this research are: (1) In the short term, domestic economic shocks, inflation rate, population, and total reserves have a significant effect on the Indonesia import; (2) In the long term, inflation rate, population, and total reserves have a significant effect on Indonesia import.
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