Analyses of the causes and the characteristics of poverty at micro levels provide more efficient strategies for the attainment of main Sustainable Development Goals. This study aimed to analyze the extent to which the characteristics of individuals, households, and communities influence the probability of household poverty status. The 2019 Social Welfare Integrated Data and Village Potential Data of Kediri City were analyzed using an ordered logit regression model and then interpreted based on marginal effect calculation. The study found that household heads’ squared-age, household members’ education, household members’ occupation, household head gender (female), ownership of assets, access to the internet, access to proper sanitation, and access to financial institutions reduced the probability of households being categorized as very poor and poor. This finding indicated that household productivity influenced by the household head’s characteristics in managing productive assets, supported by access to infrastructure, could increase the household's welfare. However, the household head’s age and marital status, dependency ratio, and access to health facilities increased household’s probability of being very poor and poor. Policies regarding poverty must be adjusted to the poverty characteristics and status. Improving access, equalizing education, and improving job opportunity and infrastructure management that ensure accessibility and enhancement in service quality need to be made to increase the status of households with the lowest 40% welfare in Kediri City. Policies regarding poverty should be focused more on social programs for very poor and poor households. Meanwhile, those near-poor and vulnerable-to-poor need more empowering programs.

Indonesia has long struggled with a high rate of unemployment. Export, one of the aggregate demand’s components, typically affects the unemployment rate as argued by Keynes. Therefore, this study attempts to evaluate the asymmetric response of unemployment rate to export shock in Indonesia. Employing a Local Projection method, the analysis incorporates three important features: the asymmetric effects of export shock (positive or negative), business cycle (boom or slump), and educational attainment of workers (highly-educated or less-educated). Dataset consisted of province-level annual panel data of 18 provinces in Indonesia where the main ports for export activity are located, spanning from the years of 1990 to 2019. This study finds significant differences in the unemployment rate dynamics between less-educated and highly-educated workers. A positive export shock during the boom reduced the unemployment rate for less-educated workers, and the effect is more persistent. In contrast, highly-educated unemployment rate decreased when a positive export shock occurs during the slump period, and the effect was rather in the short run. These results suggest some policy implications such as strengthening the domestic market, relaxing export regulation on labor-intensive industries, and diversifying export products to enlarge job opportunities for highly-educated workers with varied qualifications.JEL Classification E24; I25; O24