DAPATKAH TEKNOLOGI INFORMASI MEMENGARUHI KINERJA PEREKONOMIAN? (SEBUAH KAJIAN SPILLOVER DI PULAU SUMATERA)

Mastery of information technology and improvement of human quality is one of the efforts to increase economic output in a region. This study aims to see the effect of information technology on the performance of economic's achievement in Sumatera with the quality of population as a variable control, as well as the possibility of spatial effects between regions in it. The analysis uses panel data covering 154 districts/cities in Sumatera from 2011-2021. Scatterplot analysis and correlation matrix show a positive and strong correlation between the variables of information technology and HDI on economic performance. The results of the Global Moran and Local Moran tests also show a significant spatial effect in terms of the use of information technology and the GRDP per capita of districts/cities in Sumatera. In addition, hot-spots (high-high clusters), cold-spots (low-low clusters), and spatial outliers are formed and show a persistent pattern in 2011 and 2021. The spatial and nonspatial economic performance modeling also shows that computer use is a vital factor affecting regional performance in Sumatera. The spills-over effect that causes positive spatial interactions also indicates that economic progress in an area will affect economic progress in adjacent areas.

DAPATKAH TEKNOLOGI INFORMASI MEMENGARUHI KINERJA PEREKONOMIAN? (SEBUAH KAJIAN SPILLOVER DI PULAU SUMATERA)

Mastery of information technology and improvement of human quality is one of the efforts to increase economic output in a region. This study aims to see the effect of information technology on the performance of economic's achievement in Sumatera with the quality of population as a variable control, as well as the possibility of spatial effects between regions in it. The analysis uses panel data covering 154 districts/cities in Sumatera from 2011-2021. Scatterplot analysis and correlation matrix show a positive and strong correlation between the variables of information technology and HDI on economic performance. The results of the Global Moran and Local Moran tests also show a significant spatial effect in terms of the use of information technology and the GRDP per capita of districts/cities in Sumatera. In addition, hot-spots (high-high clusters), cold-spots (low-low clusters), and spatial outliers are formed and show a persistent pattern in 2011 and 2021. The spatial and nonspatial economic performance modeling also shows that computer use is a vital factor affecting regional performance in Sumatera. The spills-over effect that causes positive spatial interactions also indicates that economic progress in an area will affect economic progress in adjacent areas.

Happiness and air quality: microdata analysis in Indonesia

Abstract Background While economics is growing in Indonesia, its Happiness Index remains steady. Regarding the average concentration of dissolved particles, Indonesia is ranked sixth globally. Many factors can affect happiness. Environmental conditions, especially air quality, are considered to influence individual happiness. Therefore, this research investigates the impact of air quality and health on happiness. Methods Data used in this study is the microdata of Indonesia’s Happiness Survey (SPTK) in 2021. With more than 70,000 respondents, the study uses Ordered Probit as an analysis method with subjective happiness as the dependent variable. The independent variables used in this study are air quality, age, gender, housing area per capita, marital status, and health status. All independent variables except age are categorical. The variable of interest, air quality, is coded “1” if the IKU achieves the Strategic Plan’s target of 84.2 and “0” otherwise. IKU is a regional air quality index that combines two substances. Results At a significance level of 5%, there is a positive relationship between subjective happiness and air quality. In other words, if air quality (IKU) meets the Strategic Plan target (≥ 84.2), then a person is more likely to have a higher level of happiness. It can be explained more with the marginal effect. The marginal effect concludes that if the target is achieved, the probability of having a lower level of happiness decreases by up to 2.8%, and a very high level of happiness rises by 5.1%. Regarding health status, the rarer someone gets sick, the happier she/he is. Conclusion The study finds that air pollution could lower happiness, while better health increases happiness. Therefore, it is important to meet the target of IKU and to improve public health. Some good practices can be adopted to achieve this goal