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Papeles de Población

ISSN: 1405-7425

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Universidad Autónoma del Estado de México

México

Damián, Araceli

Los problemas de comparabilidad de las ENIGH y su efecto en la medición de la pobreza

Papeles de Población, vol. 13, núm. 51, enero-marzo, 2007, pp. 111-146

Universidad Autónoma del Estado de México

Toluca, México

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100

CIEAP/UAEMPapeles de POBLACIÓN No. 51

Araceli DamiánEl Colegio de México

Resumen

La principal fuente para medir la pobreza enMéxico es la Encuesta Nacional de Ingresos yGastos de los Hogares (ENIGH). A pesar de sugeneralizado uso, la encuesta presenta seriasdeficiencias en materia de captación ycomparabilidad de la información, lo quedistorsiona los cálculos de pobreza. En laprimera mitad de la presente década, la pobreza,medida con las ENIGH y el método de mediciónutilizado por el gobierno federal, disminuye apesar de la contracción económica y la falta deempleo. En este trabajo se presentan y discutenlos elementos que pueden estar detrás de lasupuesta reducción de la pobreza (cambios en elmarco muestral, en la definición de variables,en los cuestionarios, problemas de captación delingreso, inconsistencias en la evolución de lasfuentes de ingreso, tamaño de hogar, número deocupados y en otras variables relacionadas conla habitabilidad). Lo que se persigue esexplicitar cuáles son las limitaciones de laENIGH como fuente de información para medirla pobreza.

Palabras clave: pobreza, medición de lapobreza, Encuesta Nacional de Ingreso y Gastode los Hogares, México.

Abstract

Comparability problems of ENIGH and theireffects in the measurement of poverty

The main source to measure poverty in Mexicois the Encuesta Nacional de Ingresos y Gastosde Hogares (ENIGH). Despite its generalizeduse, the survey presents some deficienciesregarding the gathering and comparison ofinformation. In the first half of this decade,poverty, measured with the ENIGH and themeasuring method used by the FederalGovernment, decreases in spite of theeconomic contraction and lack of employment.In this work we present and argue the elementsthat may be behind the presumed reduction ofpoverty (changes in the sampling framework,in the definition of variables, questionnaires,problems in the income reception,inconsistencies in the evolution of the incomesources, the size of the household, number ofmembers and other variables related to thedwelling). Here we are attempting to achieve isthe explanation of which are the limitations ofENIGH as an information source to measurepoverty.

Key words: poverty, poverty measurement,National Households’ Income and OutcomeSurvey, Mexico.

Comparability problems of ENIGHand their effects in the measurement

of poverty

overty measurement always involves two elements: one of them, thedescription of the situation observed in the households and people; and theother, the establishment of rules by means of which it is determined whoP

is poor and who is not.1 When poverty is measured it is necessary to have reliableinformation sources. The main source of information to measure poverty in1 These rules express the minimum lowest beneath which we consider human life loses its dignity, itis, human life is degraded.

101 January/March 2007

Comparability problems of ENIGH and their effectsComparability problems of ENIGH and their effectsComparability problems of ENIGH and their effectsComparability problems of ENIGH and their effectsComparability problems of ENIGH and their effects

in the measurement of poverty in the measurement of poverty in the measurement of poverty in the measurement of poverty in the measurement of poverty / A. Damián

Mexico is the National Survey of Incomes and Expenditures of the Households(Encuesta Nacional de Ingresos y Gastos de los Hogares ENIGH).This and other similar surveys before it have been carried out as from the 1950’sdecade, at regular intervals, between one and seven years, as from 1992 everytwo years, and consecutively in 2004 and 2005.2 Despite the general use of thissurvey3, there are serious doubts whether it is an adequate instrument to evaluatepoverty’s evolution. If we answer no, we would be discarding a long tradition andexperience in the production of statistical data. However, see it as the idealinstrument, disregarding their weaknesses, would lead us to mistaken conclusionsand in some cases to nonsense.

It is particularly important to analyze the methodological changes performedupon the 2002 and 2004 ENIGH, since the results derived from these surveyshave generated serious doubts on the reliability and comparability (see, forinstance, Boltvinik, 2003a and 2003b; Damián, 2003a and 2003b; ECLAC, 2003).According to figures of the Ministry of Social Development (Secretaría deDesarrollo Social SEDESOL),4 patrimonial poverty was reduced from 53.7percent in 2000 to 50.8 percent in 2002 and to 47 percent of the population in 2004,respectively. Nonetheless, said results go in the opposite direction of the variablethat measures economic development. For instance, the per capita GrossDomestic Product was reduced in 1.4 percent yearly, between 2000 and 2002(taking the value of the third quarter of each year for it is the period when the2 At the time of delivering this article (June 2006) the 2005 ENIGH had not been published by the INEGI.3 ECLAC, several years; Cortés, 1997; Boltvinik, 1999, 2005; Damián, 2002, 2006; Damián andBoltvinik, 2003; Hernández-Laos, 1992; INEGI/ECLAC, 1993; Levy, 1994; Lustig and Székely, 1997;Lustig and Mitchell, 1994; Pánuco-Laguette and Székely, 1996; Technical Committee, 2002.4 In 2002, SEDESOL assembled a group of seven researchers, grouped in what was called the TechnicalCommittee (TC) for the measurement of poverty, so that it proposed an official method to do so.The TC proposed as official method that of Poverty Line (PL), supposing with it that the currentincome is the only explanatory variable of the poverty (it left aside other variables such as education,health, housing, etc.). The variant of the PL method used was that of the Canasta NormativaAlimentaria (CNA). The TC retook the methodology followed by ECLAC for two decades. However,the TC calculated the poverty doing some methodological modifications to the original method; thisled to underestimate the three poverty lines proposed (for an in-depth view of the TC method andfor a criticism to it see Boltvinik and Damián, 2003).The Federal government did not respect the TC’s poverty line calculation, but it established as officialline the committee’s intermediate line (PL 2). Separately, SEDESOL called this PL «patrimonial» andallegedly it affords feeding, health, education, transport, clothing and housing necessities. This povertymeasure leaves aside the satisfaction of numberless necessities, such as having durable goods, tools,cleaning products, etc. (for a detailed list of the necessities covered by this PL see Boltvinik and Damián,2003).On other side, federal government, following the TC methodology, calculated a PL (not identified bythe TC) that it called «Capacities» PL, which affords, supposedly, feeding needs (only raw food),education (supposing attendance to public school) and health. This PL was set to identify the objectivepopulation of the Oportunidades program. SEDESOL called TC’s PL1 «alimentary» poverty, andcorresponds to that commonly associated to extreme poverty.

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most of the surveys are carried out), and it was barely increased in 1.1 percentyearly up to 2004. Separately, according to the National Surveys of Employment(Encuestas Nacionales de Empleo, ENE), unemployment raised from 1.9 to2.2 and to 2.9 percent of the national Economically Active Population betweenthe 2000 third quarter and the corresponding to 2002 and 2004. Another fact thatshows the economy’s inability to generate employment is the decrease in thenumber of the workers enrolled in the IMSS between 2000 and 2002 (a figurethat decreased around 351 thousand between the months of November of thoseyears), and even though the number people with social security rights increasesby 2004, the figure only rises in 148 thousand jobs.5 Given the reduction in povertyin adverse economic conditions, it becomes fundamental to evaluate at whichextent the ENIGH can give us an account of the evolution of the population’swellbeing levels, or if the changes in the levels of poverty come from comparabilityproblems among them.

Sample frameworks and the ENIGH sample size

The validity loss of the sample frameworks according to censual year (or morerecently of counting) constitutes one of the most frequent problems in thehousehold surveys’ design, and it is not privative of the ENIGH. For instance,when displacing the sample frameworks of 1984 to 1989, or of 1992 to 1994, orof 2000 to 2004, etc., since they become obsolete due to different demographicand spatial phenomena (migration, new neighborhoods development, etc.). Inaddition to this problem there is yet another of reliability in the population censusand counting. Sharpest criticisms were done around the 1980 General Census ofPopulation and Housing, where even the total population was largely overestimated,particularly, in some places such a Mexico City (Camposortega, 1992: 3).6

An additional problem which makes the ENIGH comparability difficult isderived from the increment of sample size which reduces sampling errors. Forexample, in 1984 the number of households of the sample was 542, whereas in1989 it was 1973, ever since, the sample size changed to more than ten thousandhouseholds as from 1992, having slight fluctuations until 2000, being increased to19856 in 2002 and to more than 25000 in 2004.7

5 To exemplify the little dynamism of the employment, I took November because it was the last forsurveys to be carried out. However, it is worth mentioning that the same behavior is shown in theevolution of the workers ensured by the IMSS in the months of August to October.6 For a detailed description of this problem and how it affects the sample framework, see Damián, 2002.7 Information from the methodological documents from the ENIGH (INEGI)




Even if ENIGH changes the expansion factors in order to make sure that thesample units’ representation is correct, there is evidence in the sense that thechanges improve the information’s quality.8 This Change can bring along veryserious consequences for poverty’s evolution analysis for this can be reduceddue to a better income collection at the households rather than to an improvementin its real levels.

It is so in the third CT communication, stating:

…the 2002 ENIGH had a considerable increment in the household sample in respectto the year 2000, as for income stratum and regions. Because of the enlargement inthe number of observations, sample errors of the 2002 ENIGH are less serious thanthose of the 2000 ENIGH, particularly for the strata with the smallest incomes, whichmeans that the current measurements of poverty, from the statistical perspective, aremore precise than those of the year 2000 (Comité Técnico, 2003).

ECLAC also questioned the 2000-2002 ENIGH comparability and points outin the Social Panorama of Latin America, 2002-2003, that «probably the figurescorresponding to the year 2002 would not be fully comparable to those of the year2000, specially in rural areas, owing to the changes in sample design, relative tosize and distribution of the sample» (ECLAC, 2003: 5 and 58). ECLAC extendstheir criticisms in the table 1.4 of the said publication, which we will retake alongthe present article.

Changes in definitions of the urban/rural (high and lowdensity)

Another of the problems, derived from the alterations in the design of the sampleand which makes the comparison among some ENIGH difficult, is the changesin the size threshold to define urban and rural localities. For instance, between1984 and 1989, the definitions were done according to high/low density,considering the 15000-inhabitant threshold. However, while the 1984 ENIGHcriteria are clear, in 1989 ENIGH there is a contradiction in the low densitydefinition.9 Between 1992 and 2004, the urban/rural threshold definition has beenthat of the larger/smaller than 2500 inhabitants’ towns. In 2000 and 2002 the8 Nevertheless, the quality in the information collection in the recent surveys could have beendeteriorated because of the significant increment in the size of the sample, since additionalinexperienced staff had to be hired in order to carry it out in the same period as the previous ENIGH.9 On the one side, in the publication where the results appear (INEGI, 1992a), these are presentedaccording to high and low density, which in the terms’ glossary are defined in an identical manner as

104


in 1984 ENIGH. Nonetheless, the exception was made that the rural proportion of nineteenmunicipalities was classified as low density, complying with the criteria of only having localities withless than 2500 inhabitants and/or where the fields are used with agricultural ends, or where the areaspreserve their natural conditions (p. 287).

survey included in its sample framework the metropolitan areas of the NationalSurvey of Urban Employment (Encuesta Nacional de Empleo Urbano,ENEU), however, the methodological document of the year 2004 does not clarifyif these are still in use.

The 2002 survey underwent another change in the sample framework, it triesnot only to achieve the urban/rural representation but also to achieve the strataof the 2000 marginalization index of the National Council of Population (ConsejoNacional de Población) (for the urban/rural operational definitions of theENIGH see Table 1). Apart from this, in that same year (as the following year)SEDESOL partially financed the ENIGH, asking to achieve the representationof the households benefited by the Oportunidades social program.

The change of the towns’ size definition affects both the results of the povertymeasuring by regions (urban/rural) and national totals, mainly those researchesthat used poverty thresholds significantly different for urban and rural population,for instance, such as ECLAC does (including the 1993 INEGI/ECLAC study);and the Technical Committee (2002). For instance, the rural poverty line (PL)the government uses, that of patrimony represented 66.7, 70.6 67.2 percent ofthe urban one in the years 2000, 2002 and 2004, respectively.

The threshold size established by CT to distinguish the urban and rural is15000 imhabitants. However, this delimitation does no correspond to the profileand intensity of the shortages in the MMIP different components (income, timeand basic necessities, including housing and its services, education, health anddurable goods) according to town size. Empirically, it is demonstrated that thepopulation residing in towns with less than 2500 inhabitants has a necessities’satisfaction level radically inferior to that of the population of larger towns.Hence, in order to measure poverty, this threshold is recommended (see Damián,2006).

Nevertheless, CT did not evaluated the convenience to use the 2500-inhabitant threshold (despite Oportinidades program is ruled by it) and comparedthe resident population’s income in populations with between 2500 and 15000inhabitants, which INEGI classifies as urban, with a lower poverty line (the ruralone), thus underestimating the poverty in them and in the national total. In thesetowns lived 13.7 percent of the national population in the year 2000.




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106


Changes in definition of the urban and rural, combined with those of thesample framework, give as a result an absurd evolution of the urban and ruralpopulation in Mexico. As it can be seen in Table 2, the evolution of the rural andurban population during 1984-1989, 1989-1992, 2000-2004 is not coherent. In1984-1989 the total populations’ growth is classified as low density/rural. This isdue to the fact that in 1989 not all of the population of the municipalities definedas high density was classified as such (it was the case in 1984), but only that partof the population who lived in towns with more than 2500 inhabitants. This impliesan underestimation of the high density population.

The 1989 real definition, being so far from the one adopted in 1992, causeda dramatic raise in «urban» population (of 12.4 millions between 1989 and 1992),whereas the rural population decreased in more than seven millions. Between1992 and 1998 there are no important observable changes in the distribution ofthe urban and rural population, as though there would have been a stagnation,product of the net migration between both areas, which once again wouldcontradict, the country’s progressive tendency to urbanization. Apparently, thatyear’s ENIGH modified the trend in 2000 (when the rural population decreasesto 52.4 percent of the total, see Table 2). This brought along that between 1998and 2000 the rural population was reduced in absolute terms of almost a millionpeople, whereas the urban population was increased in more than 3 millionpeople. As form the year 2000 a constant advancement in the urban proportionof the country is observed. However, the absolute rural population, after havingbeen contracted between 1998 and 2000, begins to increase in absolute terms(although not in relative). Consequently, for it is common practice in Mexico andLatin America to use different poverty threshold levels for the urban and ruralareas, the problems of the population distribution in the ENIGH substantiallyaffect the poverty measurement.10

10 The study INEGI/ECLAC (1993) realized different adjustments with the intention of making thesurveys comparable. Nevertheless, their correction implied that the Mexican rural populationpercentage decreased from 61.8 percent to 59.2 percent in 1992, so poverty was underestimated. Inthis study poverty thresholds significantly different among areas were used (rural PL represented 74.3percent if the urban PL in 1992). Lustig and Székely (1997) retake the INEGI/ECLAC correction, aswell as their poverty lines, so they produce the same error.




TABLE 2RURAL AND URBAN POPULATION’S EVOLUTION ACCORDING TO ENIGH AND

PERCENTAGE OF THE TOTAL POPULATION, 1984-2004

Year National population Urban /

High density (%) Rural/

Low density (%) 1984 76.22 48.28 (63.3) 27.95 (36.7) 1989 79.14 48.92 (61.8) 30.22 (38.2) 1992 84.34 61.30 (72.7) 23.04 (27.3) 1994 89.81 65.61 (73.1) 24.20 (26.9) 1996 92.98 67.65 (72.8) 25.32 (27.2) 1998 95.74 69.89 (72.9) 25.81 (27.1) 2000 98.01 73.81 (74.6) 24.84 (25.4) 2002 101.52 76.47 (75.3) 25.05 (24.7) 2004 104.18 78.93 (75.8) 25.24 (24.2)

Source: Percentages calculated based on INEGI (1989, 1992b, and databases 1992-2004).

Underestimation of the households’ income andadjustment of national accounts

The information from the ENIGH has another sort of problem, whose nature isindependent from the already mentioned ones. The fact is that the households’total income reported in the surveys would seem to largely underestimate theirreal income.11 This underestimation comes, at least, from three phenomena. Inthe first place, it is what could be called demographic underestimation. At theextent in which ENIGH underestimates the total households’ numbers and,consequently those of the total population, the total households’ income isunderestimated. In the second place, it is the truncation phenomenon, which isrelated to the exclusion of the wealthiest population in the ENIGH (see Cortés,1997: 133-142), since very wealthy people tend to refuse every kind of survey,but particularly the ones dealing with their incomes.12

11 According to Cortés (1997: table 4.21: 135) this underestimation was 46.7 percent in 1984, 42.7in 1989 percent in 1992. In other words, the income the total income of the households accordingto ENIGH represented 53.3 percent of the total households’ income estimated in the NA. Accordingto the technical committee for the measurement of poverty (2002: 45), the total income of thehouseholds of the ENIGH represented 53.3 and 50.2 percent in 1996 and 1998, this shows the sub-registration increased in respect to the previous surveys.12 Javier Gutiérrez, INEGI’s General Director of Statistics, confirmed this phenomenon in a reunionheld in El Colegio de México on August 16th 2004.

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Separately, there are elements to determine what the probability of beinginterviewed for the highest strata is, given the wide variation in their incomesrange. Table 3 contains the maximum and minimum values, median and mean ofthe net monthly income per person of the percentile and milil of households in therural an urban areas, in 2000, 2002 and 2004. In the first place, it is observed that,despite the minimum values of the percentiles do not present important variations(these have a downward tendency in the urban area, where there is the mostresistance to answer surveys, and an upward tendency in the rural area), thevariation of the maximum values observed in the survey is very wide, this givesan account of the heterogeneity of the income levels perceived in the highest part,this makes a problem of sample design evident.

The fluctuations at the top of the income pyramid provoke drastic changes inthe mean income. For instance, the monthly mean income per person of the urbanmilil changed from thirty-six thousand Mexican pesos to twenty-five thousandMexican pesos and to forty-three thousand Mexican pesos in the years 2000,2002 and 2004 respectively. The same situation is observed in the rural milil (table3). Nevertheless, the medians allow us to see that the wealthiest people inMexico are underrepresented. Hence, the «wealthiest» households have amedian of twenty-seven thousand four hundred Mexican pesos per person amonth in the urban area and of eight thousand eight hundred Mexican pesos inthe rural area in 2004.13 It is worth noticing, apart from this, the enormousfluctuations of the maximum values of the survey from one year to the next (table3). The highest income per person in the urban area in the year 2000 was slightlymore than one hundred and ten thousand Mexican pesos, but it falls to fifty-fivethousand in 2002, and increases almost to one million two hundred thousand in2004. The proportion of these fluctuations is also present in the rural environment.

The households selected for the ENIGH are considered representative ofother households with similar incomes/expenditures’ characteristics. Hence,when extrapolating the sample to the total population, each interviewed householdis considered as hundreds or thousands. The problem with wealthy householdslies in the fact that they do not represent any group nor can they be represented.

13 In January 2005, Forbes magazine included in its five hundred multimillionaire list eleven Mexicans.Obviously these people do not appear in the INEGI surveys. According to the publication, the incomeof the eleven wealthiest people in Mexico grew 48 percent in two years, this is equivalent to eleventhousand five hundred million American dollars between 2002 and 2004. Hence, grosso modo, thesepeople had a monthly income of almost four hundred and sixty million Mexican pesos; compare thisfigure with the average income or the median in the centiles and mililes of the ENIGH.




TABLE 3MINIMUM, MAXIMUM AND MEAN VALUES OF THE MONTHLY PER CAPITA

INCOME OF THE WEALTHIEST CENTILE AND MILILOF THE URBAN AND RURAL ZONES, 2000, 2002 AND 2004 (2004 =100)

Centile Milil 2000 2002 2004 2000 2002 2004 Urban Minimum 6 500 6 441 6 310 23 182 19 890 20 815 Mean 13 300 12 216 13 420 36 417 26 595 43 647 Median 10 269 9 953 9 346 27 201 26 324 27 408 Maximum 110 367 54 848 1 198 613 110 367 54 848 1 198 613 Rural Minimum 2 218 2 454 2 755 6 992 8 868 7 277 Mean 4 263 5 630 4 953 11 833 18 907 12 737 Median 3 196 3 702 3 885 8 593 13 389 8 867 Maximum 89 369 819 586 237 691 89 369 819 586 237 691 Source: Own elaboration based upon microdata from ENIGH.

They are special cases. So, ideally, wealthy households must be selected withprobability equal to one. Since due to budget problems this can not be so, it isrecommended to widen the sample in the upper part of the strata, this would allowreducing the gathering errors. A third problem of survey underestimation is to befound in the fact that interviewees tend to sub-declare their incomes andexpenditures. This sub-declaration is usually sharp in a country such as Mexico,where a very high proportion of the population avoids tax-paying and supposesthe survey is related to fiscal authorities.

In order to try to correct part of the income’s underestimation in the surveys,in some poverty studies, not only in Mexico but in all of the Latin Americancountries, the data from the income surveys are commonly conciliated with thedata from the National Accountancy (NA) so that comparisons with differentyears can be made (for instance, Hernández Laos, 1992; Boltvinik, 1999; INEGI/ECLAC, 1993; World Bank, 1993; Lustig and Szekely, 1997; Damián, 2002).14

14 In Mexico, NA does not estimate the households’ income. Thus, in the NA the variable more closelylinked to the income is private consumption. With the aim to estimate the households’ income theconsumption of the non-profit organizations (since these figures are included in private consumption)must be subtracted from private consumption, and later household’s savings must be estimated and addedto private consumption.

110


Obviously, the income figures conciliation with the NA is a procedure thatimplicitly supposes the NA information reliability. This ignores several problemsthe NA has, among them the highly probable fact that the NA would also tendto underestimate the households’ income for it does not identify certain informalactivities.

Another problem to conciliate the income figures with the NA is related to thecoefficients used for this conciliation. For instance, in order to conciliate the self-employed workers’ income and the entrepreneurs’ revenue with the NA whenthe same coefficient is used can overestimate the self-employed people’sincome and underestimate poverty’s level. This problem has been partiallyovercome for currently the NA includes the revenues’ apportionments accordingto establishment size.

The uneven underestimation of the households’ income inside the ENIGHexplains why the households’ income evolution turns out to be different,depending on whether the figures on income information from the NA becomeconciliated or not. For instance, while in the NA the per capita income decreases5.4 percent between 1984 and 1989, in the ENIGH it increases twenty percentin the same period (Lustig and Székely, 1997: 47). So the poverty measurementwith the ENIGH original raw data would give as a result a diminution in povertybetween 1984 and 1989, a proposal that most of the researchers and internationalorganisms do not accept for these were the years of an economic recession inMexico. A similar situation took place between 2000 and 2002, years ofeconomic stagnation, however, when calculating poverty without adjusting toNA, this is reduced. The latter has become particularly controversial because ithas been established as official poverty method that does not adjusts to NA (seeComité Técnico, 2002).15 The fact of not adjusting to NA makes it difficult the

15 Pánuco and Székely (1996: 192), for instance, support that the main discrepancies between theENIGH and the NA appear in the enterprises’ incomes and revenues associated, which seem to havedisproportionately risen according to the ENIGH. Nevertheless, according to these authors «it is notpossible to determine if the discrepancy is due to lack of precision in the NA or the ENIGH». Theprevious declaration is clearly dubious. If the discrepancies were petty, it would be feasible to doubt wherethe imprecise facts are; but the ENIGH present a functional distribution of the income totally inverseto that of the NA. Whereas in the NA wages and salaries represent less than a third part of the currentincome, in the ENIGH they represent around 60 percent. On the contrary, the utilities (that in theENIGH are called enterprise revenues) represent more than a half of the current income of thehouseholds in the NA and less that a fourth part in the ENIGH surveys. Apart from this, accordingto both sources, the total estimation of wages and salaries is similar. Hence, if in the NA there wereimprecise facts in relation to utilities, this would imply that such utilities are overestimated, a fact thatthus far no one has questioned or proved. In this sense, the conclusion reached by Cortés (1997: 139)is correct «evidently the ENIGH underestimate the relative participation of the income theindependent activities generate, such as entrepreneurs or self-employed people».




evolution of poverty, mainly when changes are performed into informationgathering methodologies, since, as we already explained, the income can beincreased at the extent the gathering quality improves, rather than being just areflection of reality.

Inconsistencies in the evolution of the income variables,2000-2004

Among the changes performed into the ENIGH, the increment in the number ofquestions that gather the households’ income from thirty-six in 2000 to forty-eightin 2002 and to 61 in 2004 is noteworthy. The latter can bring along a better incomegathering (or even duplicity between similar concepts), but not represent a realincome increment. As a matter of fact, in 2000 there was only one question thatgathered the income from grants or donations from governmental and non-governmental institutions, including the ones from Progresa-Oportunidadesprogram; in 2002, the number of questions on this topic was increased to three(including one to identify those who receive something from Oportunidades), andin 2004, to five. Likewise, the number of questions on work remunerations’income rose from ten to twenty-eight between 2000 and 2004.

The 2004 World Bank report on Poverty in Mexico states that the increasein such questions, between 2000 and 2002, does not affect the evolution ofpoverty, since they only represent 0.9 percent pf the households’ total income.Nonetheless, only the grants and donations’ entry, including Oportunidades,increased from 8 to 15 percent in the poorest rural deciles (see Table A.1 toA.9).16 apart from this, the income from Oportunidades increased in real termsin the survey more than 100 percent between 2002 and 2002, whereas theadministrative data report an increment of 59 percent in the same period. (Fox,2003, annex).16 The deciles presented in this article’s tables are for people not households as INEGI does. One ofthe advantages of using people’s deciles is that each one is constituted by 10 percent of the population,whereas the households’ deciles do not represent a homogeneous population proportion, since thepoorest households (concentrated in the lowest deciles) tend to have a larger number of people.Moreover, the deciles I analyze are ordered according to the equivalent income per adult and notaccording to household’ per capita income, such as the extinct Technical Committee for theMeasurement of Poverty does. The latter allows a better deciles organization in accordance to thepopulation’s level of life, since the equivalent income per adult is constructed considering the goods’requirements (principally food), in respect to the age of each member of the household. So, the costof a satisfying goods set is inferior for a household integrated by two adults and two children to thatfor a family with four adults, however, in the deciles organization according to household’s per capitaincome the said cost is considered the same for both cases.There are tables with the apportionments of the monthly income per person per capita in percentages.The analysis hereby presented is not exhaustive. The tables with the absolute values can be requestedat: [email protected]

112


There were also inconsistencies detected among the other sources of incomeof the survey and official administrative data. For instance, in the ENIGH, theincome from Procampo increased 123 percent between 2000 and 2002, althoughits budget was reduced in 2 percent in real terms in the same period (Fox, 2003,annex). These sorts of examples are particularly important, since it is not possibleto deduce from the ENIGH information at which extent the poorest householdshave effectively a better income level, or if the increment in the number ofquestions (combined with the change in the sample framework) allowed a bettergathering of the income from the different income sources. The reliability of theENIGH can also be questioned if we consider that the incomes form remittancesdecrease 16 percent between 2000 and 2002, and only increase in 20 percentbetween 2002 and 2004, when the Bank of Mexico reported a 50-percent growth(from 6600 million American Dollars to 9900) only in the first biennium.

Between 2000 and 2004, the total current income per person at a national levelis increased in 2.1 percent; the monetary increases in 5.6 percent and the non-monetary decreases (table 4). Inside each one of these aggregates, notwithstanding,there is a great variability which has a result serious doubts on the surveys’reliability. In the monetary entries, salaries increase 9.7 percent; self-employmentincomes decrease 23.5 percent, incomes from property leasing increase 202.4percent and the monetary transferences increase 19.2 percent.

The worst of the panoramas is found if we analyze the movements for eachdecile. Total current income increases in all of the deciles except in the decile I,where it increases 17.6 percent an in the decile X, which remains almost constant(it only increases 0.5 percent). Something similar happens to the monetaryincome, it is, it goes down in the decile I, whereas the one with the lesser growthis the X. Conversely, the salaries growth dramatically increases in the deciles Ito V (with increments between 20 and 80 percent),17 whereas in the X they arealmost stagnant (with an 0.3 percent increment).18 Incomes from enterprisesdecrease in almost all of the deciles (except in the VII), but sharply in the decilesI and II. In the incomes from transferences (so are called the incomes not earnedfrom employment nor property), where the first decile has an increment of 72percent, and those of the deciles II and IV fluctuates from 15 to 36 percent (table4).17 It is surprising the increment in the income from work remunerations in the lowest deciles, sinceduring this decade’s first four years there was no employment generation, and we will see further inthe text, the number of employed people in the survey disproportionately grows when it is comparedto other sources.18 In this respect, ECLAC (2003: 58) is also surprised when realizing that the «rural families’ real incomefrom remunerations would have increased 17.5 percent and the ones from transferences from thePrograma de Apoyos Directos al Campo 34.6 percent, even though this program’s budget does notreveal noticeable modifications in the biennium».




In the case of the non-monetary income the chaos is similar or worse. Evenif this only increases in the deciles I to III and decreases in all of the rest, it isobserved that the largest decrease is experienced by the last three. This is largelyexplained by what takes place in the revenues attributed to the owned tenement(which represents 63 percent of the non-monetary income), and at a lesserextent, from gifts and presents. Incomes form tenement revenues increases intwo hundred and sixty million Mexican pesos, in the decile II, as an example. Itis hardly explainable that this entry increases in all of the deciles, except in thedeciles XI and X (table 4). We would have to suppose that while the real estatemarket contracts, that of huts, circular rooms and barracks expands. We cansuppose that if the 2004 INEGH has a sample which did not manage to surveysectors with higher strata (because of their rejection to be interviewed, aspreviously explained), the decrease in the value of the tenement revenues in thedeciles IX and X is the result of it. Besides, it is worth noticing that another virtualincome, that of the gifts and presents enormously increases in the poorest decile(40.7 percent).

For the effects of the poverty measurements, both the revenues and gifts andpresents must be left aside from the households, but the Technical Committeeto Calculate Feeding or Capacities Poverty inappropriately adds them.19 This isdue to the fact that, on the one side, both incomes are virtual and are subjectivelycalculated,20 on the other, households can not transform the tenement revenuesinto current expenditures in order to satisfy other necessities (for instance, theycan not sell or eat their house’s bricks to satisfy their feeding necessities).

Likewise, the increment in the households’ virtual income is not necessarilyrelated to the success or failure in the economic activity, however, when it isconsidered as a part of the total current income, it reflects the false idea of theincome’s real evolution. It has been showed, as a matter of fact, that the revenueattributed to tenement favored the decrease in both the feeding and capacitiespoverty (Damián, 2003b).

19 The alimentary PL only includes raw food, whereas the one of Capacities supposedly adds education(supposing attendance to public school) and health expenditures.20 To tenement owners, as well as those who receive gifts and presents when they are asked how muchthey would have paid for them.

114

CIEAP/UAEMPapeles de POBLACIÓN No. 51TA

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Notwithstanding, even if the ENIGH are scarcely reliable as for incomeinformation gathering, it is noticeable that they show a general fall in the incomesfrom enterprises, this would lead us to conclude that the economic policies of thisadministration have taken most of our country’s enterprisers (large and small)to bankruptcy. Apart from this, despite the decrease in poverty, a deteriorationof the life conditions of the poorest people in the country was observed (decileI, made up by more than 10 million people). Table 4 shows that this populationwas the one who experienced the greatest fall in the total current income perperson on a monthly basis (17.6 percent) between 2000 and 2004. This took placein spite of the impressive increment in this decile of the employment retribution(almost 80 precent), which did not compensate the decrement in the income fromenterprises. If we consider this conclusion as valid, then we have to confirm thatthese households’ (1.7 million) survival became progressively dependent on theirworkforce sale, whereas the precarious enterprises they depend upon wheredestroyed. Likewise, it is distinguishable that monetary transfers received by thisdecile, through social programs such as Oportunidades, did not achieve acontribution to poverty’s overcoming in those households, since they wereinsufficient to compensate the decreases in the incomes from enterprises.21

Inconsistencies in the change of household size

Given the fact that SEDESOL measures poverty using the households’ percapita income, not only is important the income per household, the size (numberof people) of the household is also. The smallest the number of people at ahousehold, the greater per capita income can be achieved at the same constantincome level. ECLAC (2003: 58) expresses doubts in respect to the household’ssize derived from the 2002 ENIGH. According to the organization, the expectedreduction between the households with the lowest incomes in respect to the sizeobserved in the year 2000 would have been two decimals; however, thehousehold size is reduced in six decimals (changing from 5.9 to 5.3 members perhousehold).

21 It must be added that in 2004 slightly more than half of the households in this decile (54 percent)received benefits from Oportunidades, despite being the poorest in the country.

116


In terms of the household size, we face once again fluctuation of aconsiderable magnitude. Between the years 2000 and 2002 a sharp incrementin the number of households in the rural area is observed (8 percent), higherabove the growth of urban households (4 percent), when the rural populationgrows slightly less than 1 percent. Conversely, between 2002 and 2004, thegrowth of the household size was 1.8 percent, an increment inferior to the urban(5.8 percent, see table 5).

Since the last ENIGH in the 1990’s decade there has been a fast decrementin the households’ mean size: from 4.2 people in 1992 to 4.12 in 2002. but between2000 and 2002, even though the national average size does not descendconsiderably (from 4.16 to 4.12), for it rises in the urban area (from 4.02 to 4.06),in the rural area it sharply descends (from 4.62 to 4.30). With this the breachbetween the two areas had been narrowed from 4.62 versus 4.02 to 4.30 versus4.06. It is evident the trend which leads to a serious underestimation of the meanhousehold size in the rural area.

According to the ENIGH, between 1996 and 2002 there was a diminution of0.82 people per household in the rural area; wheras, according to the respectivecensus, the descent in five years (1995-2000) was of only 0.42 people. Theunderestimation of the mean household size descent in the rural area in theENIGH is evident. Projecting to the year 2002 the censual tendency of thehousehold size an average size of 4.51 and 4.09 are obtained for the rural andurban areas, respectively. The 2002 ENIGH underestimates these sizes in 0.2people in the rural area and 0.1 in the urban area. A underestimation of 4.4percent in the rural area and 2.4 percent in urban area. Then, the household’ percapita income is overestimated in the same proportion. Hence, there was no needfor an increment in the households’ income in order to reduce poverty. Thisunderestimation of the households’ size would have been enough to achieve it.

Besides, the reduction of the households’ size between 2000 and 2004 (mainlyin the first biennium), was unevenly produced among incomes’ deciles. Althoughin the rural area the household size decreased in all of the deciles, the decrementwas dramatic (up to 24 percent) in the first five, where the most importantdecrement of the poverty takes place according to official figures, stressing theconclusion that the drastic demographic changes the ENIGH present largelyexplain the poverty decrement (table 6).




TABLE 5TOTAL OF HOUSEHOLDS AND POPULATION. ABSOLUTE VALUES AND

PERCENTAGE OF CHANGE . NATIONAL URBAN AND RURAL,2000, 2002, 2004, ENIGH

Absolute Percentage of change

2000 2002 2004 2000 2002

2002 2004

2000 2004

Households Total 23 484 752 24 650 169 25 845 081 4.96 4.85 10.0505 Rural 5 382 993 5 820 215 5 924 067 8.12 1.78 10.0515 Urban 18 101 759 18 829 954 19 921 014 4.02 5.79 10.0502 Population

Total 97 651 635 101 522 414 104 175

825 3.96 2.61 6.6811 Rural 24 843 681 25 052 285 25 242 000 0.84 0.76 1.6033 Urban 72 807 954 76 470 129 78 933 825 5.03 3.22 8.4137 Source: Own elaboration based upon microdata from the ENIGH.

TABLE 6HOUSEHOLD SIZE AND PERCENTAGE OF CHANGE

BY NATIONAL, URBAN, AND RURAL DECILES*, 2000, 2002 AND 2004

National Household size Percentage of change Deciles 2000 2002 2004 2000-2002 2002-2004 2000-2004 I 5.63 5.35 5.32 -5.13 -0.40 -5.5 II 5.44 5.27 5.02 -3.08 -4.72 -7.7 III 4.89 4.96 4.77 1.57 -3.80 -2.3 IV 4.62 4.62 4.44 -0.07 -3.90 -4.0 V 4.40 4.28 4.31 -2.73 0.88 -1.9 VI 4.14 4.08 4.14 -1.46 1.56 0.1 VII 3.90 4.00 3.87 2.45 -3.28 -0.9 VIII 3.82 3.74 3.56 -2.25 -4.77 -6.9 IX 3.33 3.40 3.31 1.98 -2.56 -0.6 X 2.99 2.92 2.91 -2.05 -0.62 -2.6 Total 4.16 4.12 4.03 -0.95 -2.13 -3.1 PTO

118


Urban Household size Percentage of change Deciles 2000 2002 2004 2000-2002 2002-2004 2000-2004 I 5.37 5.41 5.30 0.60 -2.03 -1.4 II 4.91 5.45 5.03 11.00 -7.67 2.5 III 4.93 4.79 4.48 -2.93 -6.52 -9.3 IV 4.30 4.39 4.49 2.11 2.11 4.3 V 4.25 4.23 4.33 -0.33 2.33 2.0 VI 3.96 4.10 4.01 3.57 -2.26 1.2 VII 3.92 3.95 3.73 0.70 -5.56 -4.9 VIII 3.70 3.67 3.54 -0.87 -3.42 -4.3 IX 3.20 3.37 3.24 5.35 -3.70 1.5 X 2.98 2.82 2.85 -5.33 1.08 -4.3 Total 4.02 4.06 3.96 0.97 -2.43 -1.5

Rural Household size Percentage of change Deciles 2000 2002 2004 2000-2002 2002-2004 2000-2004 I 6.14 5.85 6.06 -4.73 3.64 -1.3 II 5.59 5.05 5.22 -9.63 3.41 -6.6 III 6.07 4.56 4.61 -24.95 1.07 -24.1 IV 5.54 4.86 4.90 -12.28 0.75 -11.6 V 5.01 4.75 4.44 -5.16 -6.67 -11.5 VI 4.73 4.33 4.48 -8.43 3.38 -5.3 VII 4.46 4.32 4.40 -3.26 1.97 -1.4 VIII 4.17 4.08 3.73 -2.10 -8.79 -10.7 IX 3.71 3.65 3.47 -1.53 -4.91 -6.4 X 2.98 3.19 2.97 7.00 -7.07 -0.6 Total 4.62 4.30 4.26 -6.74 -1.01 -7.7 * Declies of people ordered by net income per equivalent adult.Source: Own elaboration based upon microdata from the ENIGH.

Continues

TABLE 6HOUSEHOLD SIZE AND PERCENTAGE OF CHANGE BY NATIONAL, URBAN,

AND RURAL DECILES*, 2000, 2002 AND 2004 (CONTINUATION)

TABLE 6HOUSEHOLD SIZE AND PERCENTAGE OF CHANGE BY NATIONAL, URBAN,

AND RURAL DECILES*, 2000, 2002 AND 2004 (CONTINUATION)




In 2004, the household size in the urban area, which had risen between 2000and 2002, decreased between 2002 and 2004. At the end of the period (2004) wefind that the household size at national level was reduced, mainly due to thereduction in the rural area, where poverty is reduced in a larger proportion.

This conclusion agrees with that of the ECLAC (2003: 58) in respect to themethodological changes in the 2002 ENIGH:

…it is evident that the mentioned factors could have an important effect on the resultsof poverty and income distribution. As an example, if the size of the households withthe lesser incomes would have evolved as it had been foreseen —for instance, adiminution of two decades in respect to the 2000 value (5.9 people)— the extremepoverty rate would be located around 18 percent, a figure superior to the estimationderived from the 2002 ENIGH data.

In this manner, poverty in our country would have been located at a similarlevel to that observed in 1989 (18.7 percent). However, ECLAC (2003), in itstable 1.4, presents the poverty level derived for Mexico from the ENIGH, withoutcorrecting the errors the organization refers to the survey of the year 2002.

Overestimation of employment and decrement in thehousehold dependents

Another of the inconsistencies in the 2002 ENIGH is the disproportionedincrement in the number of employed people in respect to the year 2000. ECLACstates…

…the average of employed people increased 6.3 percent and that of the employmentpeople who received an income almost 3 percent; the most notable variations areconcentrated in the rural areas and, mainly in the groups with the lesser resources,in the rural areas the average of employed people in the second decile of per capitaincome (corresponding to extreme poverty) increased from 1.79 to 1.92, and thenumber of family members decreased from 5.9 to 5.3.

These two forces alone can explain the descent in poverty, mainly in the ruralarea, where according to official figures the largest descent took place.

The 2002 ENIGH shows a yearly increment of 1.4 million positions comparedto 2000, a datum that contradicts all the evidence that points to a slow growth inemployment in our country during this period. According to national employment

120


surveys (ENE, whose sample size is between six and seven times larger than thatof the ENIGH), between the third quarter of the year 2000 and the correspondingin 2002 (trimester when the ENIGH are carried out) there was a yearlyincrement in the employment of only five hundred and fifty thousand employedpeople, less than 40 percent of the ENIGH registrations (table 7). Conversely,between 2002 and 2004, the ENIGH registers an increment inferior to that of theENE, since in the first the number of employed people increases in slightly morethan four hundred thousand employed people, whereas the second does it in morethan eight hundred and eighty thousand employed people, this narrows the breachbetween both surveys, nevertheless, the increment along the four years wasgreater in the ENIGH.

Another noteworthy datum, when the evolution of the employment accordingto ENE and ENIGH are compared is that between 2000 and 2002, while in thefirst the participation rate (division of the economically active population betweenthe population of 12 years of age and older) decrases from 55.54 to 54.75 percent,in the ENIGH it rises from 55.94 to 56.91 percent (table 7).

One of the consequences of employment growth, at the same time that thedecrease in the number of people per household, caused mainly in the rural areathat the number of dependents (household’s members) per employed persondrastically decreased, this alone could have caused the decrease in poverty (table8).

Table 8 has, besides the number of dependent per employed person in ahousehold, the percentage of people experiencing feeding poverty in the ruraldeciles in 2000 and 2004. in this tale it can be seen that the decrement in this lastvariable was of a considerable magnitude in the deciles where the number ofdependent per employed person decreased (III to VI). Despite the decrease inpoverty took place in the decile III it was only of 8.5 percent, in the deciles IVto VI the decrement was severe, for instance in the VI the percentage of peopleliving in poverty decreased from 88 to 8.3 percent, it is, a 90.6 percent decrementin only four years, a reduction of little reliability given the null economic growthof the sector during the same period.22

22 Nonetheless, it can be seen in table 8, that in spite of the decrement in the number of dependentsper employed person per household for the decile II, alimentary poverty increases.




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122


TABLE 8NUMBER OF DEPENDENTS PER EMPLOYED PERSON IN THE HOUSEHOLD AND

PERCENTAGE OF ALIMENTARY POOR IN EACH DECILE.RURAL AREA, 2000-2004

Dependents per employed person % of alimentary poor Deciles 2000 2004 2000-2004 2000 2004 2000-2004 I 3.52 3.74 6.2 94.5 100.0 5.8 II 3.59 3.17 -11.7 95.4 100.0 4.9 III 3.51 2.67 -23.8 97.9 89.5 -8.5 IV 3.29 2.81 -14.5 96.6 34.5 -64.3 V 2.98 2.50 -16.2 88.0 8.3 -90.6 VI 2.84 2.56 -9.8 32.9 4.0 -87.9 VII 2.57 2.57 0.1 11.0 1.2 -89.0 VIII 2.42 2.21 -8.7 6.0 1.9 -68.9 IX 2.40 2.10 -12.2 5.1 1.4 -73.0 X 2.02 1.98 -2.3 1.1 0.1 -87.5 Total 2.81 2.55 -9.3 52.8 34.1 -35.4 Source: Own elaboration based upon microdata from ENIGH.

Sudden habitability improvement in the rural area

I would like to conclude this article with an analysis of some of the variables thatalso had a strange evolution between 2000 and 2004 in the rural area. As Ipreviously mentioned, the survey from 2004 experienced new modifications thatquestion its comparability. These changes seem to have provoked a sensibleimprovement in the conditions of habitability in the rural area. For instance, from2000 to 2002 the percentage of people with an indoor running-water bathroomchanged from 15.2 to 16.4 and by 2004 the percentage reached 35.3 percent. Itis, in the first biennial the percentage increment was only 8.0 percent and in thesecond 115 percent, something that can hardly take place in a period so short.This sudden improvement is also observed in other goods such as refrigerator,washing machine, cooking gas, built-in running water (table 9). This unexpectedimprovement could be due, on the one side, to a different consideration of thepopulation by means of the expansion factors, which could have given a greaterweight to households with better life conditions. It is evident that the 2004 ENIGHpresents a rural world magically different to that observed in 2000 and 2002. Allof the inconsistencies of the ENIGH thus far analyzed favor the statisticalexpression of a poverty reduction.




TABLE 9CHANGE IN THE AVAILABILITY OF SOME HOUSING SATISFIERS,

RURAL AREAS, 2000, 2002, 2004

2000 2002 2004 2000 2002

2002 2004

2000 2004

Refrigerator 41.8 47.1 58.9 12.6 25.0 40.8 Washing machine 23.3 27.8 42.2 19.5 51.8 81.4 Cooking gas 43.1 44.5 70.2 3.2 57.6 62.6 Firewood 56.4 54.8 29.4 -2.7 -46.4 -47.89 In-house piped water 18.2 19.0 40.3 4.1 112.3 121.0 Flushing toilet 15.2 16.4 35.3 8.2 115.4 133.0 No sanitary services 26.6 21.0 12.0 -21.1 -42.9 -54.9 Sewerage connection 9.1 12.4 30.6 36.4 146.7 236.5 Garbage burning 74.8 74.3 46.9 -0.7 -36.9 -37.3 Private or public garbage collection service 14.4 16.7 37.3 15.9 123.0 158.4 * Deciles of people ordered according to net income per equivalent adult.Source: Own elaboration based upon microdata from ENIGH.

Final reflections

In order to produce reliable poverty data it is necessary to make explicit what thelimitations of the information sources used are (independently from the parametersto determine the poverty thresholds and methods). Based upon the developedanalysis, it is important to emphasize the need to do not underestimate the effectof the methodological changes of the surveys in the measurement of poverty (inthe questionnaire or in the methodological procedures to select the samples)because when the information gathering quality is modified the poverty evolutionanalysis is limited.

124


As it was demonstrated, there is a severe inconsistency in the informationcollected by the surveys, in respect to the changes observed in other economicindicators (such as GDP, social expenditure, employment, etc.) one of the maincomparability problems of the ENIGH was to determine at what extent theincome change of the households was a result of the methodological changes.It was detected that in several cases the evolution of diverse sources on incomedoes not correspond to the information obtained from other administrativeresources; separately, the change of the demographic variables (occupation,household size, demographic growth), present serious inconsistencies in respectto the expected evolution (based on the tendencies of the same surveys, as wellas the ones from the census and population counting).

We point out that apart from the unexpected increase of the work income(mainly in the deciles with the lesser income, given the economic recessionexperienced between 2000 and 2002, and the low growth between 2002 and2004), the income not derived from the productive activity (transfers) did notevolved in agreement with other information sources. Hence, it is fundamentalto make those discrepancies evident when poverty data are presented, in additionto search for alternative ways to adjust them.

As for the poverty data production, the aspects that had been signaledbecome fundamental since the official poverty measurement method identifiespoor households with a single variable: income per person. In this method, thechanges observed in the income, occupation and household size variables arecrucial to measure and determine the evolution of poverty.




TAB

LE A

. 1CO

MPO

SITI

ON

OF T

HE

TOTA

L IN

COM

E BY

SOU

RCE

AN

D N

ATI

ON

AL

DEC

ILES

2000

(PER

CEN

TAG

ES)

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iles

of p

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e so

rted

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g to

net

inco

me

per e

quiv

alen

t adu

lt.**

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y th

ree

entri

es a

re d

isag

greg

ated

: gra

nts

and

orga

nism

s’ d

onat

ions

(inc

ludi

ng O

portu

nida

des)

, rem

ittan

ces

and

Proc

ampo

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urce

: Ow

n el

abor

atio

n ba

sed

upon

EN

IGH

.

Nat

iona

l dec

iles

I

II

III

IV

V

VI

VII

V

III

IX

X

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al

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al n

et c

urre

nt in

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e 10

0.0

100.

010

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0 10

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100.

0 10

0.0

100.

0 10

0.0

100.

010

0.0

Mon

etar

y in

com

e 81

.4

79.1

79.5

79.6

79

.0

78.6

78

.7

78.3

76

.577

.478

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bor r

emun

erat

ions

18

.5

38.8

48.4

55.6

54

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58.6

58

.1

55.1

52

.050

.351

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com

e fr

om o

wn

busi

ness

55

.2

29.3

21.8

16.2

17

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14.4

14

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17.0

18

.320

.319

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oper

ty le

asin

g

0.2

0.3

0.2

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0.3

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2.4

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Tot

al tr

ansf

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ces*

* 7.

6 10

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37.

8 7.

2 5.

6 6.

3 6.

1 6.

36.

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7G

rant

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ns (i

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ding

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port

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81.

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32.

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18.6

20

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Self

-con

sum

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Paym

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0.

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81.

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9 3.

3 3.

41.

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ent a

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ent

10.8

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ents

3.

9 6.

36.

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3 6.

1 7.

6 6.

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74.

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7

126


*Dec

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: Ow

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n ba

sed

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IGH

.

TAB

LE A

. 2TO

TAL

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ME

COM

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TIO

N B

Y SO

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ND

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L D

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)

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al n

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Mon

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e 77

.9

78.0

79.3

80.1

79.0

77.2

78

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78

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Labo

r rem

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23.3

45

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56.9

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46

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7.6

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and

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7.7

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0.7

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Rem

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82.

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mon

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20.7

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71.

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75.6

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40.4

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18.8

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10

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1.6

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13.8

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e en

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are

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ce: O

wn

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base

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NIG

H.

TAB

LE A

. 3TO

TAL

INCO

ME

COM

POSI

TIO

N B

Y SO

URC

E A

ND

NA

TIO

NA

L D

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ES 20

04 (P

ERCE

NTA

GES

)

128


Urb

an d

ecile

s I

II

III

IV

V

VI

VII

V

III

IX

X

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l

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tal n

et c

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com

e 10

0.0

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0 10

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Mon

etar

y in

com

e

75.3

76

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78.4

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bor r

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24

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52.0

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54.3

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59.6

56

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53.5

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Inco

mes

from

ow

n bu

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ss

49.3

18

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ty le

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Tota

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rant

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ns (i

nclu

des

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s)

0.5

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Rem

ittan

ces

0.8

1.4

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0.

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on m

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ary

inco

me

24.7

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.9

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21

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22.0

Se

lf-co

nsum

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n

1.1

1.1

0.7

1.6

0.8

0.9

0.7

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0.5

0.4

0.7

Paym

ent w

ith g

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0.

4 0.

8 1.

5 2.

4 2.

3 3.

1 3.

2 4.

4 2.

2 0.

9 2.

0 Re

nt a

ssoc

iate

d to

ow

n te

nem

ent

9.7

11.7

11

.2

10.2

10

.6

10.8

11

.0

11.5

14

.0

17.5

13

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Pres

ents

13

.6

10.3

9.

1 9.

5 7.

1 8.

3 5.

8 5.

7 4.

9 2.

7 5.

4 *D

ecile

s of

peo

ple

sorte

d ac

cord

ing

to n

et in

com

e pe

r equ

ival

ent a

dult.

** O

nly

thre

e en

tries

are

dis

aggr

egat

ed: g

rant

s an

d or

gani

sms’

don

atio

ns (i

nclu

ding

Opo

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s), r

emitt

ance

s an

d Pr

ocam

po.

Sour

ce: O

wn

elab

orat

ion

base

d up

on E

NIG

H.

TAB

LE A

. 4TO

TAL

INCO

ME

COM

POSI

TIO

N B

Y SO

URC

E A

ND

URB

AN

DEC

ILES

2000

(PER

CEN

TAG

ES)




TAB

LE A

. 5TO

TAL

INCO

ME

COM

POSI

TIO

N B

Y SO

URC

E A

ND

URB

AN

DEC

ILES

2002

(PER

CEN

TAG

ES)

Urb

an d

ecile

s I

II

III

IV

V

VI

VII

VII

I IX

X

To

tal

Tota

l net

cur

rent

inco

me

100.

0 10

0.0

100.

0 10

0.0

100.

0 10

0.0

100.

0 10

0.0

100.

0 10

0.0

100.

0 M

onet

ary

inco

me

75.3

77

.1

77.0

77

.0

77.2

79

.5

77.7

78

.8

79.3

81

.2

79.3

La

bor r

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ion

30.0

54

.3

57.1

57

.6

54.1

59

.9

58.5

53

.6

56.2

50

.2

53.5

In

com

e fro

m o

wn

busi

ness

41

.6

17.9

14

.2

14.6

15

.1

13.6

13

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17

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erty

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ing

0.

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2 0.

3 1.

0 0.

5 0.

6 0.

8 1.

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6 2.

2 To

tal t

rans

fere

nces

**

3.4

4.4

5.4

4.3

7.0

5.4

5.1

5.4

7.6

6.3

6.0

Gra

nts a

nd d

onat

ions

(inc

ludi

ng

Opo

rtuni

dade

s)

2.0

0.8

0.5

0.1

0.1

0.0

0.0

0.0

0.1

0.0

0.1

Rem

ittan

ces

0.5

0.8

0.9

1.2

1.6

1.3

0.8

0.8

0.7

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Proc

ampo

0.

3 0.

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0 0.

0 0.

1 0.

0 0.

1 0.

1 O

ther

cur

rent

inco

mes

0.

0 0.

0 0.

0 0.

0 0.

1 0.

0 0.

1 0.

0 0.

0 0.

0 0.

0 N

on-m

onet

ary

inco

me

24.7

22

.9

23.0

23

.0

22.8

20

.5

22.3

21

.2

20.7

18

.8

20.7

Se

lf-co

nsum

ptio

n 1.

5 0.

6 1.

1 0.

7 0.

9 0.

8 0.

7 1.

3 0.

5 0.

3 0.

7 Pa

ymen

t with

woo

ds

0.3

0.9

1.1

1.6

2.0

2.0

2.2

2.4

2.0

1.9

1.9

Rent

ass

ocia

ted

to o

wn

tene

men

t 10

.2

10.9

10

.9

11.1

12

.7

11.7

12

.6

12.3

12

.8

13.1

12

.5

Pres

ents

12

.7

10.4

9.

9 9.

5 7.

1 6.

0 6.

8 5.

2 5.

4 3.

5 5.

7 *D

ecile

s of

peo

ple

sorte

d ac

cord

ing

to n

et in

com

e pe

r equ

ival

ent a

dult.

** O

nly

thre

e en

tries

are

dis

aggr

egat

ed: g

rant

s an

d or

gani

sms’

don

atio

ns (i

nclu

ding

Opo

rtuni

dade

s), r

emitt

ance

s an

d Pr

ocam

po.

Sour

ce: O

wn

elab

orat

ion

base

d up

on E

NIG

H.

130


BLE

A. 6

TOTA

L IN

COM

E CO

MPO

SITI

ON

BY

SOU

RCES

AN

D U

RBA

N D

ECIL

ES 20

04 (P

ERCE

NTA

GES

)

Urb

an d

ecile

s I

II

III

IV

V

VI

VII

V

III

IX

X

Tota

l

To

tal n

et c

urre

nt in

com

e 10

0.0

100.

0 10

0.0

100.

0 10

0.0

100.

010

0.0

100.

0 10

0.0

100.

0 10

0.0

Mon

etar

y in

com

e 81

.4

82.2

82

.482

.8

81.7

81

.682

.080

.9

81.2

79

.6

80.9

La

bor r

emun

erat

ions

57

.2

60.4

61

.764

.4

62.5

63

.161

.758

.7

59.2

49

.7

56.6

In

com

e fro

m o

wn

busin

ess

17.1

14

.2

14.3

12.1

12

.2

11.9

13.8

13.1

13

.3

14.1

13

.5

Prop

erty

leas

ing

0.3

0.2

0.3

1.0

0.6

0.6

0.9

1.3

2.0

8.9

4.1

Tota

l tra

nsfe

renc

es**

6.

8 7.

3 6.

15.

2 6.

4 6.

05.

57.

8 6.

6 6.

9 6.

6 G

rant

s and

don

atio

ns (i

nclu

des

Opo

rtuni

dade

s)

4.3

1.7

0.8

0.6

0.4

0.5

0.4

0.4

0.2

0.3

0.5

Rem

ittan

ces

1.2

0.8

1.4

1.0

1.0

1.6

1.0

1.1

1.2

1.0

1.1

Proc

ampo

0.

5 0.

2 0.

10.

1 0.

0 0.

00.

00.

1 0.

0 0.

0 0.

0 O

ther

cur

rent

inco

mes

0.

0 0.

1 0.

00.

1 0.

1 0.

00.

00.

0 0.

1 0.

0 0.

0 N

on-m

onet

ary

inco

me

18.6

17

.8

17.6

17.2

18

.3

18.4

18.0

19.1

18

.8

20.4

19

.1

Self-

cons

umpt

ion

0.

7 0.

8 0.

50.

5 0.

5 0.

50.

40.

5 0.

7 0.

3 0.

4 Pa

ymen

t with

goo

ds

0.5

0.9

0.7

0.9

1.3

1.3

1.4

1.5

1.6

2.1

1.6

Rent

ass

ocia

ted

to o

wn

tene

men

t 12

.2

11.2

12

.211

.5

12.5

12

.112

.213

.1

12.8

14

.2

13.1

Pr

esen

ts

5.2

4.8

4.2

4.2

3.9

4.5

4.0

4.1

3.7

3.8

4.0

*Dec

iles

of p

eopl

e so

rted

acco

rdin

g to

net

inco

me

per e

quiv

alen

t adu

lt.**

Onl

y th

ree

entri

es a

re d

isag

greg

ated

: gra

nts

and

orga

nism

s’ d

onat

ions

(inc

ludi

ng O

portu

nida

des)

, rem

ittan

ces

and

Proc

ampo

.So

urce

: Ow

n el

abor

atio

n ba

sed

upon

EN

IGH

.




TAB

LE A

. 7TO

TAL

INCO

ME

COM

POSI

TIO

N B

Y SO

URC

E A

ND

RU

RAL

DEC

ILES

2000

(PER

CEN

TAG

ES)

Rur

al d

ecile

s I

II

III

IV

V

VI

VII

V

III

IX

X

Tota

l

To

tal n

et c

urre

nt in

com

e 10

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

0 10

0.0

100.

0 10

0.0

Mon

etar

y in

com

e 54

.466

.571

.7

76.6

79.0

78

.081

.4

79.2

81

.6

85.0

80

.2La

bor r

emun

erat

ions

19

.628

.141

.0

46.3

47.8

50

.851

.7

43.4

42

.8

41.4

43

.4In

com

e fro

m o

wn

busi

ness

13

.416

.015

.5

14.1

14.4

11

.211

.6

21.9

25

.9

22.6

19

.4Pr

oper

ty le

asin

g

0.0

0.7

0.2

0.1

1.7

0.2

0.4

1.1

0.8

2.9

1.4

Tota

l tra

nsfe

renc

es**

21

.421

.614

.7

16.0

15.1

15

.717

.7

12.7

11

.9

18.1

16

.0G

rant

s and

don

atio

ns (i

nclu

des

Opo

rtuni

dade

s)

15.9

10.9

8.6

5.9

4.3

4.0

2.1

2.7

1.4

0.5

2.9

Rem

ittan

ces

0.3

2.1

2.0

3.5

5.7

5.9

7.8

4.5

7.6

6.0

5.7

Proc

ampo

4.

34.

22.

7 2.

41.

8 2.

41.

7 2.

0 2.

8 4.

5 3.

1O

ther

cur

rent

inco

mes

0.

00.

00.

2 0.

10.

0 0.

10.

1 0.

0 0.

0 0.

1 0.

1N

on-m

onet

ary

inco

me

45.6

33.5

28.3

23

.421

.0

22.0

18.6

20

.8

18.4

15

.0

19.8

Self-

cons

umpt

ion

6.

84.

73.

3 3.

01.

5 1.

51.

8 2.

8 2.

1 2.

4 2.

4Pa

ymen

t with

goo

ds

0.0

0.1

0.2

0.3

0.3

1.5

0.6

0.8

1.8

1.8

1.2

Ren

t ass

ocia

ted

to o

wn

tene

men

t 12

.511

.911

.6

10.6

10.2

9.

49.

1 9.

7 8.

2 7.

1 8.

8Pr

esen

ts

26.3

16.8

13.2

9.

48.

9 9.

57.

2 7.

5 6.

3 3.

7 7.

3 *D

ecile

s of

peo

ple

sorte

d ac

cord

ing

to n

et in

com

e pe

r equ

ival

ent a

dult.

** O

nly

thre

e en

tries

are

dis

aggr

egat

ed: g

rant

s an

d or

gani

sms’

don

atio

ns (i

nclu

ding

Opo

rtuni

dade

s), r

emitt

ance

s an

d Pr

ocam

po.

Sour

ce: O

wn

elab

orat

ion

base

d up

on E

NIG

H.

132


BLE

A. 8

TOTA

L IN

COM

E CO

MPO

SITI

ON

BY

SOU

RCE

AN

D R

URA

L D

ECIL

ES 20

02 (P

ERCE

NTA

GES

)

Rura

l dec

iles

I II

III

IV

V

V

I V

II

VIII

IX

X

To

tal

Tota

l net

cur

rent

inco

me

100.

0 10

0.0

100.

010

0.0

100.

0 10

0.0

100.

0 10

0.0

100.

0 10

0.0

100.

0 M

onet

ary

inco

me

59

.2

65.4

68

.973

.6

75.3

74

.077

.3

78.8

77

.9

77.8

76

.0

Labo

r rem

uner

atio

ns

19.5

30

.9

31.8

36.0

42

.0

45.5

47.6

47

.6

40.6

47

.6

43.7

In

com

e fro

m o

wn

busi

ness

29

.5

15.4

19

.615

.1

13.8

13

.914

.3

15.4

20

.3

17.6

17

.2

Prop

erty

leas

ing

0.

0 0.

1 0.

40.

7 0.

1 0.

30.

3 1.

0 1.

9 1.

5 1.

1 To

tal t

rans

fere

nces

**

10.2

18

.9

16.9

21.6

19

.3

14.1

15.0

14

.6

15.0

9.

5 13

.3

Gra

nts a

nd d

onat

ions

(inc

lude

s O

portu

nida

des)

12

.8

12.1

8.

58.

0 6.

3 4.

74.

0 2.

8 1.

6 0.

2 3.

1 R

emitt

ance

s 0.

8 1.

1 1.

64.

9 7.

6 4.

55.

6 5.

6 7.

5 5.

5 5.

4 Pr

ocam

po

3.0

3.6

3.2

2.9

2.8

3.1

1.9

2.4

1.9

2.6

2.5

Oth

er c

urre

nt in

com

es

0.0

0.1

0.1

0.1

0.0

0.1

0.0

0.2

0.0

1.7

0.7

Non

-mon

etar

y in

com

e

40.8

34

.6

31.1

26.4

24

.7

26.0

22.7

21

.2

22.1

22

.2

24.0

Se

lf-co

nsum

ptio

n

5.6

5.7

5.6

3.9

3.5

3.9

2.9

2.1

3.1

1.8

2.8

Paym

ent w

ith g

oods

0.

1 0.

3 0.

10.

6 0.

7 0.

90.

9 1.

5 1.

8 2.

1 1.

5 R

ent a

ssoc

iate

d to

ow

n te

nem

ent

12.4

10

.1

10.6

10.2

9.

1 9.

09.

4 8.

3 9.

1 14

.8

11.6

Pr

esen

ts 22

.7

18.5

14

.811

.7

11.4

12

.39.

4 9.

3 8.

1 3.

5 8.

1 *D

ecile

s of

peo

ple

sorte

d ac

cord

ing

to n

et in

com

e pe

r equ

ival

ent a

dult.

** O

nly

thre

e en

tries

are

dis

aggr

egat

ed: g

rant

s an

d or

gani

sms’

don

atio

ns (i

nclu

ding

Opo

rtuni

dade

s), r

emitt

ance

s an

d Pr

ocam

po.

Sour

ce: O

wn

elab

orat

ion

base

d up

on E

NIG

H.




TAB

LE A

. 9TO

TAL

INCO

ME

COM

POSI

TIO

N B

Y SO

URC

E A

ND

RU

RAL

DEC

ILES

2004

(PER

CEN

TAG

ES)

Rura

l dec

iles

I II

III

IV

V

VI

VII

VIII

IX

X

To

tal

Tota

l net

cur

rent

inco

me

100.

0 10

0.0

100.

0 10

0.0

100.

0 10

0.0

100.

0 10

0.0

100.

0 10

0.0

100.

0 M

onet

ary

inco

me

68.3

69

.1

74.5

70

.2

72.5

76

.1

76.5

78

.4

76.4

80

.5

76.8

La

bor r

emun

erat

ion

10.6

24

.4

32.2

38

.1

40.6

37

.6

44.8

43

.0

42.7

37

.2

38.1

In

com

e fro

m o

wn

busin

ess

43.8

30

.4

21.5

17

.8

15.4

22

.8

16.8

21

.2

23.4

32

.8

25.7

Pr

oper

ty le

asin

g

0.0

0.2

0.4

0.5

0.1

0.3

0.3

0.3

0.6

0.7

0.5

Tota

l tra

nsfe

renc

es**

13

.9

14.3

20

.7

14.3

16

.2

15.6

14

.9

14.1

10

.1

10.0

12

.7

Gra

nts a

nd d

onat

ions

(inc

lude

s O

portu

nida

des)

8.

1 9.

0 9.

5 6.

6 5.

7 3.

0 2.

5 2.

1 1.

0 0.

3 2.

7 Re

mitt

ance

s 1.

2 0.

8 1.

8 4.

2 3.

1 4.

5 4.

7 6.

6 4.

3 5.

8 4.

7 Pr

ocam

po

2.8

2.2

1.6

1.3

1.9

1.7

2.2

1.1

1.2

1.5

1.6

Oth

er c

urre

nt in

com

es

0.0

0.0

0.1

0.0

0.3

0.1

0.0

0.0

0.2

0.5

0.2

Non

-mon

etar

y in

com

e 31

.7

30.9

25

.5

29.8

27

.5

23.9

23

.5

21.6

23

.6

19.5

23

.2

Self-

cons

umpt

ion

4.

8 5.

7 5.

8 3.

5 5.

7 4.

1 4.

5 3.

1 3.

8 2.

7 3.

7 Pa

ymen

t with

goo

ds

0.3

0.0

0.6

0.3

0.4

0.5

1.1

2.3

1.8

2.3

1.5

Rent

ass

ocia

ted

to o

wn

tene

men

t 11

.5

10.2

11

.0

9.5

10.4

10

.2

9.9

8.4

9.0

9.1

9.5

Pres

ents

15.0

14

.9

8.2

16.4

11

.0

9.1

8.1

7.8

9.0

5.5

8.5

*Dec

iles

of p

eopl

e so

rted

acco

rdin

g to

net

inco

me

per e

quiv

alen

t adu

lt.**

Onl

y th

ree

entri

es a

re d

isag

greg

ated

: gra

nts

and

orga

nism

s’ d

onat

ions

(inc

ludi

ng O

portu

nida

des)

, rem

ittan

ces

and

Proc

ampo

.So

urce

: Ow

n el

abor

atio

n ba

sed

upon

EN

IGH

.

134


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