Zusmelia, Ansofino, Melinda Noer, Iswandi, Momon, Lovelly Dwinda Dahen, Nilma Desri Rosya
This study analysis the impact of regional development disparities that occurred before and during the Corona Virus Disease (Covid-19) pandemic, and its effects on strategies to improve regional economic development. The research method used is the spatial lag model (SLM), and the spatial error model (SEM). The data used is the inequality of per capita income in the province of West Sumatra, Indonesia from 2003-2019. The results showed that the convergence of per capita income in West Sumatra, Indonesia has positive spatial autocorrelation, there are two regions, namely Padang City and Agam Districts as the centre of the cluster. The districts, and cities of West Sumatra are not yet fully integrated with each other, there are seven districts, and cities which are categorized as neighbourless for all groups of economic variables, physical, and social variable groups. The group of economic variables that most significantly affect the reduction of inequality, such as the number of MSME businesses, and investment in the form of gross fixed capital formation, these seven regions have no spatial integrated with their neighbouring areas. Spatial autocorrelation in each variable used for analysis shows that autocorrelation clustering only occurs in nine districts, meaning that spatial autocorrelation has not fully occurred in districts, and cities in West Sumatra, the implication is that spatial interactions between these areas are in economic, physical development. Regional, and social, it has not happened, and has not been able to encourage the creation of agglomeration. The strategy for managing development inequality during the Covid-19 pandemic is a high priority starting with improving the health of mothers and children, increasing the transportation of people, and goods between regions, increasing the ratio of road length to area, increasing agglomeration between regions, and increasing the role and, participation of women in development to support increased life expectancy. If this can be done, it will be followed effectively by an increase in MSME business, and investment, which in turn can lead to an increase in the skills of the productive age population.