TY - JOUR
T1 - The Impact of ICT on Economic Growth in the Fourth Industrial Revolution
T2 - Modeling Using Principal Component Panel Regression
AU - Wibowo, Wahyu
AU - INyoman Budiantara, I.
AU - Wilantari, Regina Niken
AU - Amara, Vira Desita
N1 - Publisher Copyright:
© 2020 Universiti Tun Hussein Onn Malaysia Publisher’s Office
PY - 2020
Y1 - 2020
N2 - In the fourth industrial revolution, information and communication technology (ICT) has posed a paradox. On the one hand, ICT plays an important role in human life, not only as information and communication devices but also as the booster of economic activities to enhance revenue. On the other hand, ICT has also created disruption in various aspects of life which resulting in disadvantages to some groups in the society. This study aims to examine whether technology still has a positive effect on the economy. To achieve this objective, it took a case study from East Java Province, Indonesia. The data is panel consisting of gross regional product and the number of ICT users in East Java. More specifically, the number of ICT users consists of several variables, i.e. the number of the mobile phone users, the number of computer users, the number of internet users, the number of internet users for transactions of goods and services, and the number of the internet users for financial facilities. The analysis employed least square panel regression with gross regional product as the response variable and the number of ICT users as a predictor variable. However, there was a high correlation between the predictor variables that caused the model regression not proper. This problem was solved by combining least square panel regression with Principal Component Analysis (PCA). Using PCA method, the dimension of the variable was reduced to be one principal component. This principal component is a linear combination of the predictor variables. Then, this principal component was regressed with the gross regional product. The best panel regression model is the Fixed Effect Model. This model shows that all predictor variables have positive coefficients. It means that ICT still has a positive impact on economic growth.
AB - In the fourth industrial revolution, information and communication technology (ICT) has posed a paradox. On the one hand, ICT plays an important role in human life, not only as information and communication devices but also as the booster of economic activities to enhance revenue. On the other hand, ICT has also created disruption in various aspects of life which resulting in disadvantages to some groups in the society. This study aims to examine whether technology still has a positive effect on the economy. To achieve this objective, it took a case study from East Java Province, Indonesia. The data is panel consisting of gross regional product and the number of ICT users in East Java. More specifically, the number of ICT users consists of several variables, i.e. the number of the mobile phone users, the number of computer users, the number of internet users, the number of internet users for transactions of goods and services, and the number of the internet users for financial facilities. The analysis employed least square panel regression with gross regional product as the response variable and the number of ICT users as a predictor variable. However, there was a high correlation between the predictor variables that caused the model regression not proper. This problem was solved by combining least square panel regression with Principal Component Analysis (PCA). Using PCA method, the dimension of the variable was reduced to be one principal component. This principal component is a linear combination of the predictor variables. Then, this principal component was regressed with the gross regional product. The best panel regression model is the Fixed Effect Model. This model shows that all predictor variables have positive coefficients. It means that ICT still has a positive impact on economic growth.
KW - Information and communication technology
KW - economic growth
KW - panel regression
KW - principal component
UR - http://www.scopus.com/inward/record.url?scp=85098194296&partnerID=8YFLogxK
U2 - 10.30880/ijie.2020.12.07.017
DO - 10.30880/ijie.2020.12.07.017
M3 - Article
AN - SCOPUS:85098194296
SN - 2229-838X
VL - 12
SP - 151
EP - 159
JO - International Journal of Integrated Engineering
JF - International Journal of Integrated Engineering
IS - 7
ER -