1. Methodology
  2. Taxes and benefits
Download icon

A non-parametric microsimulation approach to assess changes in inequality and poverty

  1. Rob Vos  Is a corresponding author
  2. Marco V. Sánchez  Is a corresponding author
  1. United Nations Department of Economic and Social Affairs, United States
Research article
Volume 3(1) Spring 2010
Cite this article as: R. Vos, M. V. Sánchez; 2010; A non-parametric microsimulation approach to assess changes in inequality and poverty; International Journal of Microsimulation; 3(1); 8-23. doi: 10.34196/ijm.00021
6 tables

Tables

Table 1
Real GDP growth and labour-market, poverty and inequality results in the baseline scenario for Costa Rica, 2008–2012.
  2008 2010 2012
Real GDP (at factor cost) 2.6 2.2 4.4
Total unemployment rate (%) 6.0 5.9 5.9
Employment (in thousands of workers) 1,958 2,035 2,115
Labour income per worker a 239,984 242,083 254,820
Total poverty incidence (% of population) b 20.7 19.5 16.5
Extreme poverty incidence (% of population) b 4.3 4.1 3.6
Gini coefficient for labour income 0.461 0.456 0.447
Gini coefficient for per-capita household income 0.497 0.490 0.478

  1. Source: CGE model and microsimulation results for Costa Rica.

  2. a

    Real monthly labour income in colones, excluding social security contributions

  3. b

    Calculation based on a national poverty line.

Table 2
Real labour income of workers by skill, sex and occupational category, 2008–2012.
Real labour income per worker (colones) Relative remuneration (W1) a
2008 2010 2012 2008 2010 2012
Unskilled female workers
Wage earners 167,077 165,631 167,821 0.696 0.684 0.659
Non-wage earners 44,021 44,820 47,644 0.183 0.185 0.187
Unskilled male workers
Wage earners 243,219 258,632 293,963 1.013 1.068 1.154
Non-wage earners 160,052 166,719 190,108 0.667 0.689 0.746
Skilled female workers
Wage earners 396,095 388,726 389,430 1.651 1.606 1.528
Non-wage earners 90,935 84,048 81,142 0.379 0.347 0.318
Skilled male workers
Wage earners 390,806 383,148 384,967 1.628 1.583 1.511
Non-wage earners 165,769 155,686 158,703 0.691 0.643 0.623
Average labour income economy 239,984 242,083 254,820 1.000 1.000 1.000

  1. Source: Baseline estimates of CGE model for Costa Rica.

  2. a

    Changes in relative remuneration are similar across sector of activity.

Table 3
Sequential and cumulative effects for changes in the labour-market parameters for the baseline scenario for Costa Ricaa, 2008–2012.
Total poverty incidence (% of population)b Extreme poverty incidence (% of population) b Gini coefficient for labour income Gini coefficient for per-capita household income
2008
U 20.7 4.3 0.461 0.497
U+S 20.7 4.3 0.461 0.497
U+S+O 20.7 4.3 0.461 0.497
U+S+O+W1 20.7 4.3 0.461 0.497
U+S+O+W1+W2 20.7 4.3 0.461 0.497
U+S+O+W1+W2+M 20.7 4.3 0.461 0.497
2010
U 20.6 4.3 0.461 0.497
U+S 20.6 4.3 0.461 0.497
U+S+O 20.6 4.3 0.461 0.497
U+S+O+W1 19.8 4.1 0.456 0.491
U+S+O+W1+W2 19.6 4.1 0.456 0.491
U+S+O+W1+W2+M 19.5 4.1 0.456 0.490
2012
U 20.5 4.2 0.461 0.497
U+S 20.5 4.2 0.461 0.497
U+S+O 20.4 4.2 0.461 0.496
U+S+O+W1 18.1 3.8 0.447 0.479
U+S+O+W1+W2 16.6 3.6 0.447 0.479
U+S+O+W1+W2+M 16.5 3.6 0.447 0.478

  1. Source: CGE model and microsimulation results for Costa Rica.

  2. Key: Simulations present cumulative effects of changes in: U = unemployment; S = employment by sector; O = employment by occupational category; W1 = relative remuneration per worker; W2 = mean real remuneration per worker; M = skill level.

  3. a

    Sequential and cumulative effects are presented for changes in the type of labour market variables as explained in the text.

  4. b

    Calculation based on a national poverty line.

Table 4
Macro-micro effects of simulating an increase in government cash transfers to poor households for Costa Ricaa, 2011–2012 (deviation with respect to the baseline). b
2011 2012
Gross capital formation −1.0 −1.0
Real GDP at market prices −0.2 −0.3
Government income −0.5 −0.6
Government expenditure 0.2 0.1
Fiscal deficit/GDP 0.1 0.1
Unemployment rate 0.1 0.2
Employment 0.0 0.0
 Wage-earners, unskilled women 0.2 0.2
 Non-wage earners, unskilled women 0.0 0.0
 Wage-earners, unskilled men 0.0 0.0
 Non-wage earners, unskilled men 0.0 0.0
 Wage-earners, skilled women −0.1 −0.2
 Non-wage-earners, skilled women 0.0 0.0
 Wage-earners, skilled men 0.1 0.0
 Non-wage earners, skilled men 0.0 0.0
Labour income −0.5 −0.6
 Wage-earners, unskilled women −0.4 −0.5
 Non-wage earners, unskilled women −1.2 −1.3
 Wage-earners, unskilled men −0.4 −0.5
 Non-wage earners, unskilled men −0.8 −0.9
 Wage-earners, skilled women −0.5 −0.6
 Non-wage-earners, skilled women −0.8 −1.0
 Wage-earners, skilled men −0.5 −0.5
 Non-wage earners, skilled men −0.5 −0.7

  1. Source: CGE model and microsimulation results for Costa Rica.

  2. a

    The performed simulation is explained in the text.

  3. b

    Percentage deviation for all variables except for fiscal deficit for which results are presented in percentage points of GDP, and poverty and inequality for which absolute changes of the indicator are used.

Table 5
Decomposition of the poverty and inequality effect of simulating an increase in government cash transfers to poor households for Costa Rica, 2011–2012 (Absolute deviation with respect to the baseline).
2011 2012
Direct effect CGE effect Total effect Direct effect CGE effect Total effect
Total poverty incidence a −1.6 0.0 −1.6 −1.5 0.1 −1.4
Extreme poverty incidence a −0.9 0.1 −0.8 −0.9 0.2 −0.7
Gini – labour income 0.000 0.000 0.000 0.000 0.000 0.000
Gini – per-capita household income −0.004 0.000 −0.004 −0.003 0.000 −0.004

  1. Source: CGE model and microsimulation results for Costa Rica.

  2. a

    Incidence as a percentage of the population. Calculation based on nationally defined poverty lines.

Table A.1
Sequential and cumulative effects and confidence intervals for changes in the labour-market parameters for the baseline scenario for Costa Ricaa, 2012.
Variable Obs. Mean Standard Error [95% Confidence Interval]
U
Total poverty incidence b 30 20.45249 0.00685 20.43850 20.46649
Extreme poverty incidence b 30 4.21342 0.00788 4.19730 4.22954
Gini – labour income 30 0.46117 0.00003 0.46111 0.46123
Gini – per-capita household income 30 0.49661 0.00003 0.49655 0.49668
U+S
Total poverty incidence b 30 20.48056 0.00658 20.46711 20.49402
Extreme poverty incidence b 30 4.22287 0.00857 4.20533 4.24040
Gini – labour income 30 0.46119 0.00005 0.46109 0.46129
Gini – per-capita household income 30 0.49662 0.00005 0.49652 0.49672
U+S+O
Total poverty incidence b 30 20.44773 0.00622 20.43501 20.46044
Extreme poverty incidence b 30 4.20806 0.00825 4.19119 4.22492
Gini – labour income 30 0.46098 0.00005 0.46088 0.46108
Gini – per-capita household income 30 0.49647 0.00005 0.49636 0.49657
U+S+O+Wa
Total poverty incidence b 30 18.12911 0.01060 18.10742 18.15079
Extreme poverty incidence b 30 3.76363 0.00698 3.74935 3.77790
Gini – labour income 30 0.44659 0.00005 0.44648 0.44669
Gini – per-capita household income 30 0.47856 0.00005 0.47845 0.47867
U+S+O+W1+W2
Total poverty incidence a 30 16.56747 0.01072 16.54556 16.58939
Extreme poverty incidence b 30 3.58093 0.00593 3.56881 3.59305
Gini – labour income 30 0.44667 0.00005 0.44656 0.44677
Gini – per-capita household income 30 0.47851 0.00005 0.47840 0.47862
U+S+O+W1+W2+M
Total poverty incidence b 30 16.52524 0.01902 16.48635 16.56413
Extreme poverty incidence b 30 3.59980 0.01135 3.57659 3.62302
Gini – labour income 30 0.44682 0.00007 0.44668 0.44696
Gini – per-capita household income 30 0.47790 0.00009 0.47771 0.47809

  1. Source: CGE model and microsimulation results for Costa Rica.

  2. a

    Sequential and cumulative effects are presented for changes in the labour market variables as explained in the text.

  3. b

    The poverty incidence is expressed as a percentage of the total population and was estimated using nationally defined poverty lines.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)