Arturo Martinez
Biographic Data
| ID | 4265597 |
|---|---|
| NAME | Arturo Martinez |
| GIVEN NAMES | Arturo |
| FAMILY NAME | Martinez |
| SIGNATURE | MARTINEZ A |
| AFFILIATIONS | Asian Development Bank |
| ORCID | 0000-0002-3384-4061 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 9 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 2 |
Predicting Poverty Using Geospatial Data in Thailand
Poverty statistics are conventionally compiled using data from socioeconomic surveys. This study examines an alternative approach to estimating poverty by investigating whether readily available geospatial data can accurately predict the spatial distribution of poverty in Thailand. In particular, the geospatial data examined in this study include the intensity of night-time light (NTL), land cover, vegetation index, land surface temperature, buil…
The Dynamics of Multidimensional Poverty in Contemporary Australia
How Income Segmentation Affects Income Mobility: Evidence from Panel Data in the P hilippines
Despite vibrant economic growth, the Philippines confronts persistently high income inequality. Using household‐level panel data collected for the years 2003, 2006 and 2009, we investigate how income segmentation affects F ilipinos' income mobility prospects. The results of the multinomial logistic models suggest that if households are grouped according to initial income (in 2003), richer households had the lowest propensity to experience slow to…
Multiple job holding and income mobility in Indonesia
Multiple job holding and income mobility in Indonesia
How Income Segmentation Affects Income Mobility: Evidence from Panel Data in the P hilippines
Despite vibrant economic growth, the Philippines confronts persistently high income inequality. Using household‐level panel data collected for the years 2003, 2006 and 2009, we investigate how income segmentation affects F ilipinos' income mobility prospects. The results of the multinomial logistic models suggest that if households are grouped according to initial income (in 2003), richer households had the lowest propensity to experience slow to…
The Dynamics of Multidimensional Poverty in Contemporary Australia
Predicting Poverty Using Geospatial Data in Thailand
Poverty statistics are conventionally compiled using data from socioeconomic surveys. This study examines an alternative approach to estimating poverty by investigating whether readily available geospatial data can accurately predict the spatial distribution of poverty in Thailand. In particular, the geospatial data examined in this study include the intensity of night-time light (NTL), land cover, vegetation index, land surface temperature, buil…
Demographic economics (3 works) · Economics (3 works) · Geography (3 works) · Poverty (3 works) · Econometrics (2 works) · Economic growth (2 works) · Employment and Welfare Studies (2 works) · Gender, Labor, and Family Dynamics (2 works) · Income, Poverty, and Inequality (2 works) · Inequality (2 works)