This study examines the poverty indicators in Northeast region of Thailand by adopting the global Multidimensional Poverty Index (MPI) methodology and the national survey of Minimum Basic Needs (MBN) of Thailand. Data are collected from three different districts in Khon Kaen province namely: Khok Po Chai, Sam Sung, and Nam Pong. The sample size is 187 households. Data analysis uses Ordinary Least Square (OLS) regression approach and includes 7 dimensions of poverty (health, environment, education, economy, Thai value, asset? empowerment, and digital literacy) with a total of 41 indicators. This study has found that poverty indicators in Khon Kaen province remains centered around the aspects of health and employment dimensions. While a change of family structure in the Thai society since 1960s reduces the family size, household saving substantially increases over the years. The effects of health dimension in poverty, on the other hand, appears on the other poverty dimension of Thai value, which include (1) a bad living habit of head of household (smoke or alcohol consumption) that links with illness and disease, (2) religious practice, and (3) chronic illness. Lastly, there are income gaps of different careers in the area, which suggests the issue of income inequality.

Abstract
1. Introduction
2. Literature Review
    2.1. Health
    2.2. Environment (Standard of Living)
    2.3. Education
    2.4. Economy
    2.5. Thai Value
    2.6. Assets (Property Ownership and Land Use)
    2.7. Empowerment
    2.8. Digital Literacy
3. Methodological Framework
    3.1. Linear Regression
    3.2. Income Confidence Intervals Inference
4. Data
5. Results
    5.1. Regression Analysis
    5.2. Income Confidence Intervals Inference
6. Conclusion
Reference

• Ajirapa PIENKHUNTOD(Research Group on Local Affairs Administration and Smart City, College of Local Administration, Khon Kaen University)
• Chainarong AMORNBUNCHORNVEI(National Electronics and Computer Technology Center)
• Phouthakannha NANTHARATH(Research Group on Local Affairs Administration and Smart City, College of Local Administration, Khon Kaen University) Corresponding Author