The Guanajuato Multidimensional Poverty Index (MPI) was created using the multidimensional measurement method of Alkire and Foster (AF). Which is an index of acute multidimensional poverty used to compare poverty across over 100 countries. It is computed using data from the most recent available Demographic and Health Surveys. The MPI measures three dimensions through 10 indicators as illustrated in figure 1. Each dimension is equally weighted, and indicators within a dimension are also equally weighted. See table A.1 of the appendix for a better comprehension of dimensions and their indicators.
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| Figure 1. Structure of the Global MPI |
The global Multidimensional Poverty Index (MPI) was created using the multidimensional measurement method of Alkire and Foster (AF). The global MPI is an index of acute multidimensional poverty that covers over 100 countries. It is computed using data from the most recent Demographic and Health Surveys (DHS). The MPI has three dimensions and 10 indicators. Each dimension is equally weighted, and each indicator within a dimension is also equally weighted. Any person who fails to meet the deprivation cutoff is identified as deprived in that indicator.
In the global MPI, a person is identified as multidimensionally poor or MPI poor if they are deprived in at least one third of the weighted MPI indicators. In other words, a person is MPI poor if the person’s weighted deprivation score is equal to or higher than the poverty cutoff of 33.33%. Following the AF methodology, the MPI is calculated by multiplying the incidence of poverty (H) and the average intensity of poverty (A). More specifically, H is the proportion of the population that is multidimensionally poor, while A is the average proportion of dimensions in which poor people are deprived. So, MPI = H × A, reflects both the share of people in poverty and the degree to which they are deprived.
| Area | MPI | H | A | Vulnerable | Severe Poverty |
Population Share |
| Mexico | 0.020 | 5.00% | 39.8% | 3.1% | 0.9% | |
| Guanajuato | 0.010 | 2.75% | 35.9% | 2.7% | 0.0% | 100.0% |
| Urban | 0.011 | 3.19% | 35.9% | 1.5% | 0.0% | 72.0% |
| Rural | 0.006 | 1.63% | 35.7% | 5.7% | 0.0% | 28.0% |
Table 1. MPI in Mexico and Guanajuato
A headcount ratio is also estimated for two other ranges of poverty cutoffs. A person is identified as vulnerable to poverty if they are deprived in 20–33.33% of the weighted indicators. Concurrently, a person is identified as living in severe poverty if they are deprived in 50–100% of the weighted indicators. A summary of the MPI statistics is presented in table 1 for national, state, state rural, and state urban areas. We follow the Alkire, Kanagaratnam and Suppa (2024a,b) for specific decisions and methodology for disaggregation. The estimates underlying this briefing have been produced using the Stata package mpitb developed by Suppa (2023).
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| Figure 2. Headcount Ratios by Poverty Measures |
Poverty Headcount Ratios
Figure 2 compares the headcount ratios of the MPI with some monetary poverty measures. The height of the first bar shows the percentage of people who are MPI poor in Guanajuato. The second and third bars represent the percentage of people who are poor in Mexico according to the World Bank’s $2.15 a day and $3.65 a day poverty line. The final bar denotes the percentage of people who are poor according to the national income or consumption and expenditure poverty measures.
Sources: for global MPI Alkire, Kanagaratnam and Suppa (2024a) based on ENSANUT, year 2022. Monetary poverty measures are the most recent estimates from World Bank (Azevedo, 2011). Monetary poverty measure refer to 2022 ($2.15 a day), 2022 ($3.65 a day), and 2022 (national measure). CONEVAL: 36.3.
Figure 3
Figure 3 shows the percentage of people who are MPI poor in Mexico. The percentage of people who are MPI poor is shown in beige. While the darker height shows the percentage of people who are severe poor. Intensity of Multidimensional Poverty Recall that the intensity of poverty (A) is the average proportion of weighted indicators in which poor people are deprived. A person who is deprived in 90% of the weighted indicators has a greater intensity of deprivation than someone deprived in 40% of the weighted indicators. Figure 4 shows the percentage of MPI poor people who experience different intensities of deprivation. For example, the first slice of the pie chart shows deprivation intensities of greater than 33.33% but strictly less than 40%.
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| Figure 4. Intensity of Deprivation among MPI Poor |
In contrast, the bar graph in figure 5 reports the proportion of the population in a country that is poor in that percentage of indicators or more. For example, the number over the 40%+ bar represents the percentage of people who are deprived in 40% or more of weighted indicators. For example, people who are deprived in 50% or more of the indicators are the subset of MPI poor people who are identified as living in severe poverty.
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| Figure 5. Share of People by Minimum Deprivation Score |
Analyzing the Composition of Multidimensional Poverty
Dimensional Breakdown.
The AF methodology has a property that makes the global MPI even more useful—dimensional breakdown. This property makes it possible to compute the percentage of the population who are multidimensionally poor and simultaneously deprived in each indicator. This is known as the censored headcount ratio of an indicator. Figure 6 shows the censored headcount ratio of each indicator at national and state levels. Poverty information, however, becomes even more valuable when it is disaggregated by urban and rural areas. Figure 7 illustrates the state indicator and the breakdown by urban and rural areas. This analysis shows the contribution of different indicators to poverty in different areas, which can reveal structural differences in urban and rural poverty. This in turn could mean different policy responses in different areas, making the MPI useful for monitoring the effects of policy shifts and program changes.
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| Figure 6. Rural Censored Headcount Ratios |
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| Figure 6. Urban Censored Headcount Ratios |
Percentage Contribution.
The censored headcount ratio shows the extent of deprivations among the poor but does not reflect the relative value of the indicators. Two indicators may have the same censored headcount ratios but different contributions to overall poverty, because the contribution depends both on the censored headcount ratio and on the weight assigned to each indicator. As such, a complementary analysis to the censored headcount ratio is the percentage contribution of each indicator to overall multidimensional poverty.
Figure 8 contains two bar graphs that compare the percentage contribution of each indicator to state, rural and urban poverty. In the bar graph on the left-hand side, colors denote the percentage contribution of each indicator to the overall MPI, and all bars add up to 100%. In the bar graph on the right, the height of each bar shows the absolute contribution of each indicator to MPI, and the height of each bar is the MPI value. This enables an immediate visual comparison of the composition of poverty across areas.
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| Figure 8. Indicator Contribution to Overall Poverty |
Changes over Time
This section describes trends in multidimensional poverty for Mexico between 2012 and 2022 using a harmonised version of the global Multidimensional Poverty Index (MPI). Harmonisation produces comparable MPI(T) estimations within a region, over time.
Goal 1 of the Sustainable Development Goals (SDGs) proposes an end to poverty in all its forms everywhere, and Target 1.2 sets an aim for countries to reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions by 2030. Tracking this target requires over-time comparisons, like those we present here.
Table 2
National Trends.
Table 2 shows the levels and changes in MPI(T) values, incidence and intensity of poverty between 2020 and 2022 for Guanajuato. This gives an indication of the speed of poverty reduction in the state. The absolute reduction in poverty is calculated by subtracting one measure of poverty from another and the annualised absolute change is this change divided by the number of years between surveys.
Appendix
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| Table A.1 |
Notes: For more details see Alkire, Kanagaratnam and Suppa (2024a); the global MPI is related to the following SDGs: No Poverty (SDG 1), Zero Hunger (SDG 2), Health & Well-being (SDG 3), Quality Education (SDG 4), Clean Water & Sanitation (SDG 6), Affordable & Clean Energy (SDG 7), Sustainable Cities & Communities (SDG 11).
1 Children under 5 years (60 months and younger) are considered undernourished if their z-score of either height-for-age (stunting) or weight-for-age (underweight) is below minus two standard deviations from the median of the reference population. Children 5–19 years (61–228 months) are identified as deprived if their age-specific BMI cutoff is below minus two standard deviations. Adults older than 19 to 70 years (229–840 months) are considered undernourished if their Body Mass Index (BMI) is below 18.5 kg/m2 .
2 The child mortality indicator of the global MPI is based on birth history data provided by mothers aged 15–49. In most surveys, men have provided information on occurrence of child mortality as well but this lacks the date of birth and death of the child. Hence, the indicator is constructed solely from mothers. However, if the data from the mother is missing, and if the male in the household reported no child mortality, then we identify no occurrence of child mortality in the household.
3 If all individuals in the household are in an age group where they should have formally completed 6 or more years of schooling, but none have this achievement, then the household is deprived. However, if any individuals aged 10 years and older reported 6 years or more of schooling, the household is not deprived.
4 Data source for the age children start compulsory primary school: DHS or MICS survey reports; or http://data.uis.unesco.org/
5 If survey report uses other definitions of solid fuel, we follow the survey report.
6 A household is considered non-deprived in sanitation if it has some type of flush toilet or latrine, or ventilated improved pit or composting toilet, provided that they are not shared. If the survey report uses other definitions of improved sanitation, we follow the survey report.
7 A household is considered non-deprived in drinking water if the water source is any of the following types: piped water, public tap, borehole or pump, protected well, protected spring, or rainwater. It must also be within a 30-minute walk, round trip. If the survey report uses other definitions of improved drinking water, we follow the survey report.
8 A small number of countries do not collect data on electricity because of 100% coverage. In such cases, we identify all households in the country as non-deprived in electricity.
9 Deprived if floor is made of natural materials or if dwelling has no roof or walls or if either the roof or walls are constructed using natural or rudimentary materials. The definition of natural and rudimentary materials follows the classification used in countryspecific DHS or MICS questionnaires.
