Colombia’s 2012 Tax Reform : Poverty and Social Impact Analysis
This report summarizes the results of the PSIA and explains the three analyses used to determine the impact of the tax reform. The first analysis integrates data from administrative tax records with household statistics from the Gran Encuesta Integ...
| Main Author: | |
|---|---|
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2017
|
| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/224891505457246534/Colombia-s-2012-tax-reform-poverty-and-social-impact-analysis http://hdl.handle.net/10986/28530 |
| Summary: | This report summarizes the results of
the PSIA and explains the three analyses used to determine
the impact of the tax reform. The first analysis integrates
data from administrative tax records with household
statistics from the Gran Encuesta Integrada de Hogares
(GEIH) conducted by the Departamento Administrativo Nacional
de Estadística (DANE) to correct for the problem of
underrepresentation of high-income households that is
typical of household surveys. The second analysis, which is
based on consumption data from the Encuesta de Calidad de
Vida (ENCV) also conducted by DANE, follows the LATAX
micro-simulation technique and focuses on the effect of
taxes on income distribution and on government revenues on
the assumption that individuals’ purchasing habits remain
the same. The third analysis uses a general equilibrium
model of the labor market to estimate the impact of the tax
reforms on the labor market and on informality. The first
analysis shows that the effects of Colombia’s income tax
reform serve the intended purpose of reducing income
inequality. Results based on the constructed full income
distribution, which uses administrative tax records and
household survey data, indicate that the Gini coefficient
decreases from 0.586 to 0.579. Considering that the average
yearly reduction of the Gini coefficient in Latin America
over the last 10 years was 0.51 percentage points, the
estimated reduction in Colombia’s Gini coefficient is not
trivial. These results also demonstrate the importance of
using the full income distribution to calculate true
inequality in a country. |
|---|