“Energy Consumption of Mexican Households,” by Ignacio César Cruz Islas

8/13/2019 Energy Consumption of Mexican Households, by Ignacio Csar Cruz Islas

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THE JOURNAL OF ENERGY

AND DEVELOPMENT

Ignacio Csar Cruz Islas,

Energy Consumption of Mexican Households,

Volume 38, Number 2

Copyright 2013


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ENERGY CONSUMPTION OF

MEXICAN HOUSEHOLDS

Ignacio Cesar Cruz Islas*

Background

In recent decades there has been a significant and widespread increase in energyconsumption. This increase is due to the intensification of productive activities,but also to growing population energy usage for daily activities, both indoors and

outdoors, such as transportation, lighting, and entertainment, among others. This

trend of rising energy consumption has a number of developmental and envi-

ronmental implications.

Energy consumption is associated with greenhouse gas (GHG) emissions.

These are long-lived gases, whose concentration in the earths atmosphere in-

creases when the volume of gas emitted exceeds the natural capacity of absorptionprocesses that exist on the planet. Many of these gases are produced by fossil fuels

used as energy sources. With detectable increases in the earths average temper-

ature and irregular seasonal weather conditions occurring, GHG emissions have

become linked with a phenomenon referred to as climate change (CC) or global

warming.

Given that these changes are linked to human activity, there is concern about

CC in various public and private spheres. For that reason, it is a phenomenon that

is being studied from various perspectivesmany of which address the quanti-

tative aspectsand a macro-level approach is commonly used.

*Ignacio Cesar Cruz Islas, research professor at El Colegio del Estado de Hidalgo, in Pachuca,

Mexico, holds a masters degree in population studies from the Universidad Autonoma del Estado de

Hidalgo, and a Ph.D. in the same field from El Colegio de Mexico. The author focuses his academic

research on sustainable development and social vulnerability.

The Journal of Energy and Development, Vol. 38, Nos. 1 and 2

Copyright 2013 by the International Research Center for Energy and Economic Development(ICEED). All rights reserved.

189


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Thus, countries and regions are the main population reference of energy con-

sumption and greenhouse gas emissions in available studies. However, the micro-

social approach is becoming more widely considered for general social research. In

the arena of population studies, the development of this line of research is emerging.

To conduct a study with a micro-social approach, a first consideration is thathumans consume energy both individually and in groups, depending upon their

daily activities. In that sense, domestic space intimacy is an ideal place to see first-

hand population attitudes and energy consumption practices.

To conduct a study, as presented in this paper, that utilizes a micro-social

approach and analyzes activities taking place in the domestic space has both its

pros and cons. The main advantage we have for this work is that there are various

sources of information for Mexico where the analysis unit is households. Among

these are income and spending surveys. The most notable disadvantage is the lack

of information sources about energy consumption that would allow us to capture

attitudes and practices surrounding daily life analysis.

Household energy consumption is related to daily activities such as cooking,

hot water use, and home lighting. It also is linked to the supply of goods and

services and the transport of household members.1 Although it is important to

study energy use linked to both sources, in this article we focus on energy con-

sumption arising from everyday activities within households. It should be noted

that it is somewhat more difficult to estimate energy consumption for household

member transport and the provision of goods and services.To explain consumption from a macroeconomic perspective, various theories

focus on household income. The propensity to consume depends on household

disposable income at a moment along a time line.2 But it depends, too, on long-

term expected income and thus involving loan financing probabilities.3

Other theories suggest that the propensity for household consumption is de-

termined not only by income but by sociocultural elements, which must also come

into consideration. For example, there is a social comparison effect that exists

between members of the same socioeconomic environment.4

Because disposable income varies according to the social mobility possibilitiesof individuals and their needs along the life cycle, A. Ando and F. Modigliani

suggest that household consumption is determined by income evolution.5 Under

this view, the propensity to consume also involves household factors, such as age

of household head, assets accumulated, and more than one income earner.6

The microeconomic approach addresses the fact that households are not a ho-

mogeneous unit. It is recognized that there is a dynamic within each household

leading to its own style of consumption. Therefore, the propensity to consume

involves individual preferences, the interaction of household members in decision

making, and internal household income distribution.7

In summary, although income is the main determinant of household con-

sumption, it also is mediated by other factors. Some of these factors are individual

THE JOURNAL OF ENERGY AND DEVELOPMENT190


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and family objectives, resource management for household spending, the compar-

ison with other families or social groups, and the level of satisfaction or dissatis-

faction of household members with their consumption-satisfaction-comfort ideal.8

Thus, there is a distinction between traditional economic theory and the so-

ciological approach regarding consumption. Economic theory usually assumesthat individuals behave rationally and optimize consumption based on cost-effective

decisions. The sociological approach refers to desires, attitudes, and aspirations of

individuals as relevant factors in consumption decisions.9

Both approaches can be combined to better predict economic decisions.10 On

the one hand, this involves considering subjective factors such as memory, mo-

tivation, and family relationship dynamics. These perceptions influence prefer-

ences of household members and affect consumption choices. Furthermore, we

should take into account aspects such as household budget constraints, household

size, gender and age of its members, housing size, and its equipment, as examples.

In the case of socio-demographic factors, it should be noted that energy con-

sumption patterns vary from place and time from one another depending upon

each households characteristics. Thus, energy consumption intensity involves

issues such as population aging, family organizational patterns, and social in-

equality, among others.11

Size and structure of households are among main determinants of residential

energy demand.12 In fact, household size naturally is linked with total energy

consumption. Moreover, we must consider consumption per household member interms of economies of scale.

Age composition of households, in addition, determines energy consumption

patterns.13 For example, a young parent family with small children has a different

consumption pattern than an elderly couple whose children have left the home.

The social transformations that have occurred within households over the past

decades are another important aspect. In Mexico, this transformation is charac-

terized by womens integration into the labor market, changes in family ar-

rangements due to poverty and emigration, and the growing relative importance of

one-person households. It could be said that these changes have led to new energyconsumption patterns.

Household energy consumption varies from one country to another, is different

for each region of a country, and changes if the household belongs to an urban or

non-urban context. In this regard, we should expand our focus to the urbanization

process that has occurred in recent decades. In fact, use of energy resources is more

intense in cities because of the features and characteristics of urban daily activities.14

Income differentials between rural and urban areas also would be linked with

different patterns of energy consumption. The life-style in each environment is

a further aspect.15

With technological change and globalization, the structuralprocess of recent decades has been expanding and diversifying consumption

possibilities.16

ENERGY CONSUMPTION & MEXICAN HOUSEHOLDS 191


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Thus, the set of above mentioned factors related to household energy con-

sumption implies that the analysis task we have proposed is complex. Therefore, it

is necessary to establish what analysis level is suitable for our purpose. We must

take into account not only related factors but also the scope of available

information.The study of the socio-demographic determinants of household energy con-

sumption is incipient. In many developing countries the main sources of in-

formation on energy consumption predominantly provide aggregate data. That is

why this paper proposes to use available household income and expenditure

surveys.

To study these determinants and systematically analyze information, a pro-

posed structure is suggested that incorporates contextual factors, such as geographic

household location. Additionally, we study factors related to socio-demographic

characteristics, including household income, size, and its composition by age and

gender.

Scheme Analysis

Household energy consumption is closely linked to domestic activities, the

social and economic status of people, and practices that surround their daily

productivity. The objective of this proposal is to study energy consumption pat-terns in Mexican households at a moment in time, looking at the following levels

of analysis: (1) the link between household energy consumption belonging to

a particular geographical contexturban and non-urban areasand different

country regions and (2) the relationship between energy consumption and socio-

demographic household characteristics.

In order to answer key questions about household energy consumption patterns,

data from the Encuesta Nacional de Ingresos y Gastos de los Hogares 2008

(ENIGH) were used. This survey contains extensive information about household

spending on electricity and fuel.Using the ENIGH data, we constructed a proxy for household energy con-

sumption. To obtain this proxy we used electricity and fuel spending and then

calculated energy units according to their energy content. We considered varia-

tions in fuel prices and electricity tariffs across Mexico.

Based on this proxy, we first present a descriptive analysis of the average

energy consumption per household (in kilowatt-hours). It is calculated for total

energy consumption and energy consumption of electricity, natural gas, and

firewood.

To conclude, we provide the results from two logistic regression models wedeveloped. In these models we use energy consumption per household and per

household member as dependent variables, respectively.



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Data

There are various methods to collect information on energy consumption. Each

of them has advantages and disadvantages depending upon the object of analysis

and aggregation degree required.17 In the case of Mexico, the ENIGH is available.This survey is representative for the country as well as for four locality sizes. It is

also representative of states such as Sonora, Estado de Mexico, and the Distrito

Federal (Federal District) that includes Mexico City. The surveys main aim is to

gather information on trends in income and household spending.

This survey does not have a specific module for measuring energy consump-

tion. Thus, energy consumption analysis must be performed using a proxy of

household spending on electricity and fuel. Another disadvantage is that results

depend on the degree of accuracy of the interviewees responses and, thus, in-

terviewee reliability. Additionally, it is difficult to estimate energy consumption

associated with fuels that are collected or provided as non-cash expenses.

ENIGH results are obtained from a probabilistic poly-stage stratified cluster

sampling. Housing is used as the unit selection and the household is the analysis

unit.18

The limitations of this information source are the underestimation of real in-

come and the exclusion of higher- and lower-income households.19 This un-

derestimation occurs due to the refusal of some households to be interviewed. We

also should consider the low probability of being selected in the sample, especiallyon a sample frame with such a large proportion of the rural population.20

With respect to expenditure items, there has not been a systematic evaluation of

the data quality. Considering this, it was necessary to assess data quality on energy

expenditures. We compared published data of total expenditures on electricity and

fuel with another calculated from a different data source. Our purpose was to

verify the equality between the two variables in all sample households.

With respect to ENIGH, the comparison reveals that the published data are

valid in 88.1 percent of households (missing data at 11.9 percent). Meanwhile,

calculations with the alternative data source indicate a similar relationship: 88 to12 percent, respectively.

This lack of information suggests that there are errors in data collection on

household spending. Such errors could have been corrected with a mathematical

adjustment procedure. However, it is important to note that we are probably

underestimating energy consumption related to spending on electricity and fuels.

Nevertheless, ENIGH offers different advantages. First, this survey has been

held biannually since 1984. Second, the data have been given the status of public

information; thus, they are easily accessible to users. Third, given the accumulated

experience in gathering information, we consider that this energy consumptionproxy is accurate enough to allow for a proper study of household energy con-

sumption determinants.



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Mexican Household Energy Consumption

According to the available information, between 1990 and 2008 total energy

consumption grew just over 43 percent in Mexico and has a growth rate higher than

its population size. This trend also is seen in the residential sector. Between 2005 and2008 residential energy consumption grew 2.04 percent per year. Meanwhile, the

population growth rate was 1.8 percent per year for the 2005 to 2010 period. The

main energy sources in the residential sector are electricity, natural gas, and firewood.

Below are the results of this analysis according to the proposed scheme analysis.

Geographical ContextRegion: There are significant differences within the

regional social and economic development levels within Mexico. It might be

inferred that different development stages are associated with a variety of energy

consumption patterns.

To investigate how household energy consumption patterns change from one

region to another, a problem we face is how to build a suitable regionalization for

the country. Regions do not exist per se but are constructed from aspects that could

be highlighted as special scientific interest.

Although it is assumed that a region is associated with a territory, it is required

to establish territorial boundaries and contents that distinguish them. Therefore, it

is useful to begin our analysis of household energy consumption behavior based on

regions constructed with sufficiently correlated attributes. In this case, we mustconsider Mexicos unequal integration pattern into the global economy, which has

been observed over recent decades.21

By integrating information in this manner, we expect to preserve ENIGHs

sample representativeness. The following is the breakdown of Mexicos states into

three regions and the Distrito Federal: Northern regionBaja California, Baja

California Sur, Chihuahua, Coahuila, Durango, Nuevo Leon, San Luis Potosi,

Sinaloa, Sonora, Tamaulipas, and Zacatecas; Central regionAguascalientes,

Colima, Estado de Mexico, Guanajuato, Hidalgo, Jalisco, Michoacan, Nayarit,

Morelos, Queretaro, and Tlaxcala; andSouthern region Campeche, Chiapas,Guerrero, Oaxaca, Puebla, Quintana Roo, Tabasco, Veracruz, and Yucatan.22

Figure 1 shows that the average energy consumption per household is higher

in the Northern region, followed by households in Distrito Federal, then the

Central region, and, finally, the Southern region. While household average en-

ergy consumption in the Northern region is 67 percent higher than the Southern

region and 29 percent higher than the Central region, it is quite similar to the

Distrito Federal.

Household energy consumption is positively related to the socioeconomic

development for the regions under study, but not when compared to the DistritoFederal. This is due to the high electricity consumption in households in the

Northern region. This may be associated with behavioral and climatic factors.



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Figure 1 also shows that the average energy consumption for gas usage is

higher in the Distrito Federal, followed by the Central, Northern, and Southern

regions. The differences are not as remarkable as those for electricity use. Since in

Northern region households there is an extensive use of electric heaters, an as-

sociation between gas consumption and regional development can be noted.

However, in the case of firewood there is a clear associationalthough

negativebetween average energy consumption and regional development. Results

suggest that it is essential to address dimensions related to the geographical context

for the study of household energy consumption determinants. There are contextualelements like weather or domestic technology availability and other household

characteristics to be taken into account.

If we consider the relationship between energy consumption per household

member and region, table 1 shows that households where energy consumption is

low are more common in the Southern region (30.5 percent) and least common in

the Distrito Federal (6.6 percent). Meanwhile, households where energy con-

sumption per household member is high have a greater presence in the Distrito Federal

and Northern region38.5 and 36.9 percent, respectivelyand are less common in

Southern region (16.3 percent). This is a statistically significant relationship.As a preliminary conclusion, we can say that there is a relationship between

regional development and energy consumption patterns in Mexican households.

Figure 1MEXICO: AVERAGE ENERGY CONSUMPTION

PER HOUSEHOLD BY REGION

(in kilowatts-hours)

Source: Authors calculations based onEncuesta Nacional de Ingresos y Gastos de los Hogares

2008 (ENIGH).



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According to our analysis design, this suggests that the analysis of household

energy consumption has to address dimensions related to geographical context.

There are contextual factors like weather or availability of domestic technology

that must also be taken into account.

Geographical ContextUrban and Non-Urban Locations: In Mexico there are

large cities such as Mexico City, Monterrey, and Guadalajara. Additionally, thereare cities with more than one million inhabitants including Puebla-Tlaxcala,

Toluca, Tijuana, Leon, Ciudad Juarez, and La Laguna, along with many other smaller

urban areas. In 2010 there were 630 cities with 15,000 inhabitants or more. They

housed 62.5 percent of the Mexican population.23

On the other hand, land occupation in the country also is characterized by

a pattern of population dispersion in thousands of small towns. In 2010, there were

188,594 towns in Mexico with less than 2,500 inhabitants. These communities

were where 23.2 percent of the population lived.24

This population concentration-dispersion pattern makes it extremely importantto distinguish between urban and non-urban households in evaluating their energy

consumption practices. How to distinguish what is considered urban from rural is

a question that can be addressed from a variety of perspectives. It can be made by

taking into account territorial/land or population aspects. Additionally, one can

differentiate urban versus rural by looking at production dynamics, social and

family organizations, land and property ownership, and culture. The shift from rural

to urban living is part of a historical process. This process refers to various trans-

formations and, hence, is necessarily linked with different consumer practices.25

But the urbanization process is not merely quantitative. Population growth andresource accumulation associated with production are insufficient to explain

qualitative issues such as life-style and social interaction. For that reason, the

Table 1MEXICO: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS BY PER-CAPITA

ENERGY CONSUMPTION AND REGION, 2008a

Per-Capita Energy

Consumption

Region

Distrito Federal Northern Central Southern Total

Low 6.6 12.0 16.1 30.5 17.7

Medium 54.9 51.1 60.8 53.2 55.6

High 38.5 36.9 23.1 16.3 26.7

Total 100.0 100.0 100.0 100.0 100.0

(N) 2,507 6,994 9,316 6,522 25,339

a p < .01.


2008 (ENIGH).



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urban-rural dichotomy stands in opposition to an alternative view of a continuum

going from the most rural or least urbanized to the most urban or least ruralized.26

Based on the abovementioned, it is complex to establish the variables that

allow us to attribute a greater or lesser degree of urbanity and, thereby, distinguish

different energy consumption patterns. For that reason, the distinction betweenrural and urban areas depends on arbitrary or conventional boundaries.

The boundaries most used are those with a population approach attached to

a specific geographical area.27 In this work, we proposed additional variables

including the population size as population employed in non-agricultural activi-

ties, education, and employee population.28 We designate urban as 15,000 or more

inhabitants and non-urban with less than 15,000 inhabitants.

Figure 2 shows that household average energy consumption in urban areas is

higher than non-urban households, both for total consumption (48 percent) and for

electricity and gas use (57 and 20 percent, respectively). In contrast, energy

consumption of firewood is higher in non-urban area households by 49 percent.

It is important to note that the distinctions between urban and non-urban house-

hold energy consumption standards are observed in all cases. Since this does not

occur for the regions under study, it can be asserted that the degree of urbanization is

the best determinant of energy consumption patterns in Mexican households.

We also confirmed observed inequalities between urban and rural areas. Among

others factors were differences in health and education as well as fertility rates and

mortality. In the case of energy consumption, it is more decisive that a household issited in an urban area compared to households in a non-urban location.

Table 2 shows that households with low energy consumption per household

member are more common among non-urban households (30.7 percent) than their

urban counterparts (11.7 percent). Conversely, one is more likely to find house-

holds with high consumption per household member in urban areas (31.5 percent)

than in non-urban locations (16.4 percent). There is a statistically significant re-

lationship reflecting the influence of urbanization on household energy con-

sumption patterns.

Demographic Household Characteristics: To conduct a study that focuses on

household energy use one should take into consideration that people consume

energy individually and in groups. It depends on their daily activities, specifically,

the dynamics of domestic life. Thus, households can be seen as an ideal place to

observe first-hand population energy consumption practices.

A phenomenon of particular interest to our research is the internal restructuring

of Mexican households that has occurred over recent decades. This process has

had a significant influence on the relationships and exchanges among household

members as well as their practices and attitudes.The main indication of this reshaping of the Mexican households is seen in the

decline in mortality and fertility rates. Other key elements are the aging of the



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population, the change in marriage patterns, and increased participation of womenin economic activity. Together, these changes have led to a process of social

change and greater diversity of family structures.29

In Mexico, the incidence of poverty and economic inequality are additional

issues to contemplate. Usually households with lower income levels are grouped

Figure 2MEXICO: AVERAGE ENERGY CONSUMPTION PER HOUSEHOLD

BY URBAN AND NON-URBAN LOCATION

(in kilowatt-hours)


2008 (ENIGH).

Table 2MEXICO: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS BY PER-CAPITA ENERGY

CONSUMPTION AND URBAN AND NON-URBAN LOCATION, 2008a

Per-Capita Energy

Consumption Urban Non-Urban Total

Low 11.7 30.7 17.7

Medium 56.8 52.9 55.6

High 31.5 16.4 26.7

Total 100.0 100.0 100.0

(N) 17,283 8,056 25,339

a p < .01.


2008 (ENIGH).



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in extended family arrangements. Furthermore, migration also modifies household

structure.30

A central question is whether it can be said that those transformations have

a connection with energy consumption patterns. There is a degree of similarity

with consumption patterns arising from the Western development model. How-ever, household energy consumption patterns are disrupted by a different family

reorganization process in Mexico.Household Income: Income distribution determines the likelihood of households

having access to energy and meeting their basic energy requirements without

compromising their satisfaction for other needs. Furthermore, income provides

a measure of how affordable energy is for households.31 Income also indicates

whether the household is likely to use energy more efficiently because it is asso-

ciated with access to modern energy sources and the latest domestic technologies.

In this paper we have grouped households into five income strata (quintiles). The

goal is to verify if higher incomes are associated with higher energy consumption.

As expected, figure 3 shows that the average energy consumption per house-

hold increases with income. The difference between households in the highest

income stratums average energy consumption and the rest of the households is

remarkable. On average, Quintile V households (the highest income level) con-

sumed 66 percent more energy than Quintile IV households and 3.4 times more

than Quintile I households (the lowest income level).

In the case of energy consumption of electricity and gas, there is also a positive

relationship with income. Note that Quintile V household consumption values for

electricity and gas are very close, but this is not the case with the other income

strata. This indicates that electricity is the main energy consumption component in

households with higher incomes.

Figure 3 also shows that households with higher incomes have a higher energy

consumption of firewood. Differences range from 58 to 91 percent relative to other

income strata. This probably has to do with firewoods use as a second fuel for the

highest income households.

A preliminary conclusion can be established if there is a positive relationshipbetween income and household energy consumption, but, in this case, it is ob-

scured by the fuel type used for domestic energy needs. However, as is shown in

table 3, the relationship between energy consumption per household member and

income is statistically significant. It is more likely to find households with higher

consumption standards in the fifth income quintile (47.7 percent) and less likely to

be found in the first quintile (16.1 percent). In contrast, the proportion of house-

holds consuming less energy per household member is higher in the first quintile

(34.4 percent) and lowest in the fifth quintile (5.9 percent).

In conclusion it can be said that there is a positive relationship between incomeand energy consumption. However, we believe there is an effect linking the type of

fuel used and the household size.



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Household Size: One consequence of demographic changes that have occurred in

Mexico during the past decadesprimarily lower fertility ratesis the change in

the average size of Mexican households. Average household size fell from about

4.3 members in 2000 to 3.9 members in 2010.32

This decline changed the dynamics within households in a variety of ways; thus,

household size is a key indicator for the analytical exercise performed in this paper.

However, Mexican household size is diverse and the ENIGH data scope is limited.

To facilitate their study and not to lose sample data representation, the fol-

lowing groups were selected based upon the average size of Mexican householdsas the demarcation point: (1) up to four members and (2) more than four members.

As postulated in the literature, figure 4 shows that energy consumption increases

with increasing household size. According to this chart, larger households consumed

19 percent more energy. In regard to energy consumption of electricity and gas, the

difference is 16 and 18 percent, respectively. Energy consumption of firewood,

meanwhile, is 2.8 times higher in households with more than four members.

From the aforementioned, it can be said that, indeed, there is a positive associ-

ation between energy consumption and household size. However, it should be noted

that household size appears to be less decisive than income. Firewood consumptionis an important aspect. As discussed in previous sections, firewood use is most

noticeable in the Southern region and in non-urban locations. Since there also is an


PER HOUSEHOLD BY INCOME QUINTILEa

(in kilowatt-hours)

aQuintile I to V ranges from lowest to highest income.


2008 (ENIGH).



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association between development and demographic transition, we expect to have

larger average household size in the less-developed regions and smaller locations.

In fact, it is more likely to find households with higher consumption standards

per capita in smaller household sizes (35.5 percent) than in larger households (11

percent). It is more common to find households consuming less energy per capita

among larger household sizes (24.1 percent) than households with fewer members(14.2 percent), as is shown in table 4, where the relationship is statistically

significant.

It should be noted that household size is strongly correlated with energy

consumption standards: larger households use more energy. However, there is

a consistent behavior of economies of scale: per-capita energy consumption is

greater in smaller households.Household Type: Household internal dynamics are conditioned by customs,

norms, values, and the behavior of its members. In a household with a complex

structure, interrelationships among its members are also more diverse. Therefore,household energy consumption patterns do not fit into a single model.

In 1990, 74.9 percent of Mexican households were nuclear and 19.6 percent

expanded or extended. A decade later the relative importance of nuclear house-

holds dropped to 69.1 percent and we began to see a noticeable trend in one-person

households with 6.4 percent. In 2010, 64.3 percent of households were nuclear,

expanded households represented 24.0 percent, and one-person households made up

8.8 percent.33

Considering these issues, since the data source is a survey, it is necessary to

take care not to lose representation. This requires using an appropriate typologyfor available information without overlooking the associated energy consumption

behaviors.

Table 3MEXICO: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS BY PER-CAPITA

ENERGY CONSUMPTION AND INCOME QUINTILE, 2008a

Per-Capita Energy

Consumption

Income Quintile

TotalI II III IV V

Low 34.4 22.6 15.9 13.0 5.9 17.8

Medium 49.4 59.3 62.0 60.0 46.4 55.6

High 16.1 18.2 22.0 27.0 47.7 26.7

Total 100.0 100.0 100.0 100.0 100.0 100.0

(N) 4,465 4,945 5,258 5,341 5,330 25,339

a p < .01. Quintile I to V ranges from lowest to highest income.


2008 (ENIGH).



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The household typology of ENIGH is extensive. Using it as is, very likely may

result in a representation loss of less common household types. Therefore, for this

paper we chose to aggregate information on: one-person households, nuclear

households, and extended households.


CONSUMPTION AND HOUSEHOLD SIZE, 2008a

Per-Capita Energy

Consumption Up to 4 Members More than 4 Members Total

Low 14.2 24.1 17.7

Medium 50.3 64.9 55.6

High 35.5 11.0 26.7

Total 100.0 100.0 100.0

(N) 16,247 9,091 25,338

a p < .01


2008 (ENIGH).


PER HOUSEHOLD BY HOUSEHOLD SIZEa

(in kilowatt-hours)

aHousehold size weighted average.

Source: Authors calculations based on Encuesta Nacional de Ingresos y Gastos de los Hogares

2008 (ENIGH).



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To answer what is the relationship between household energy consumption and

household type, we also used weighted-average consumption by household size.

Remember that the relative importance of one-person households grows using this

approach. In addition, other household types do not have enough representation in

the ENIGH sample and are excluded from this analysis.Figure 5 illustrates that extended households average energy consumption is

25 percent higher than that of nuclear households. Moreover, it is 2.5 times higher

than that observed in one-person households. This mainly is explained by average

household size.

In the case of electricity usage, extended households consumed 22 and 124

percent more energy than nuclear and one-person households, respectively. For

gas usage the difference is 25 and 153 percent for nuclear and one-person

households, respectively. For firewood usage the most significant difference is ob-

served (77 percent and 10.2 times more likely, respectively), indicating that the main

consumers of firewood are larger households, which are more common in rural areas.

It is worth mentioning that one-person households are more common in urban

areas. In Mexico these households are composed predominantly of elderly people.

Therefore, it is very likely that they have special energy consumption needs such

as home lighting, hot water use, food preparation, and entertainment. In addition, it

is linked to time use of its members.

Figure 5

MEXICO: AVERAGE ENERGY CONSUMPTIONPER HOUSEHOLD BY HOUSEHOLD TYPE

a

(in kilowatt-hours)

a Household size weighted average.

Source: Authors calculations based on Encuesta Nacional de Ingresos y Gastos de los Hogares

2008 (ENIGH).



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Since the relative importance of one-person households has increased in recent

decades and this trend is expected to continue in the future, it is a particular

household group of interest for future research in this field.

Table 5 shows that among households consuming more energy per capita are

single-person households (55.9 percent) followed by nuclear households (26.8percent) and extended households (17.9 percent). In contrast, extended and nu-

clear households are among the households that consume less energy per member

(20.6 percent and 17.6 percent, respectively), while 8.6 percent of one-person

households are among the least energy-consuming overall.Household Life Cycle and Economic Dependents: Energy needs of household

members change over time. In this sense, the age of household members is another

feature that, to some extent, determines energy consumption patterns. Age

composition of households, however, is an attribute with a certain degree of

complexity.

By the nature of the available data, in this paper we have decided to use the

household life-cycle perspective to facilitate analysis.34 As roles of household

members are somehow linked to age, the life-cycle notion of stages allows us to

conceive of households as structured by age strata.35

There are four aspects that we believe may be linked to household energy

consumption patterns utilizing this approach. First, work activity is associated

with values hierarchy and social status, just as with consumption capability. 36

Second, resources and household needs are not constant. In initial and final stages

of their life cycle, households are more vulnerable to an adverse economic and

social context.37 The third concerns the availability and quality of household as-

sets, particularly everyday goods such as water heaters and appliances.38 Fourth,

there is a relationship between household life-cycle stages and the historical


CONSUMPTION AND HOUSEHOLD TYPE, 2008a

Per-Capita Energy

Consumption

Household Type

TotalOne-Person Nuclear Extended

Low 8.6 17.6 20.6 17.8

Medium 35.5 55.6 61.4 55.6

High 55.9 26.8 17.9 26.7

Total 100.0 100.0 100.0 100.0

(N) 1,923 16,635 6,561 25,340

a p < .01.


2008 (ENIGH).



18/32

moment in which they exist. The social, economic, and political context affects the

behavior of each household in different ways.39

For purposes of analysis, the age of the household head is used as a marker to

distinguish the following three groups: household head up to 40 years old; house-

hold head between 40 and 60 years old; and household head more than 60 years old.According to figure 6, the average energy consumption is highest in households

whose head is 40 to 60 years of age. It is 10 percent higher than households with

older heads (more than 60 years old) and 41 percent higher than households with

younger heads (up to 40 years old).

Figure 6 shows similar patterns for electricity and firewood consumption. In

the first case, households with heads aged 40 to 60 years consume 20 and 46

percent more energy, respectively. In the second case, the difference is 2 and 23

percent, for electricity and firewood usage, respectively.

Regarding gas use, households with heads aged over 60 years consume more

energy than households headed by persons 40 to 60 years of age (2 percent). Also,

they consume 29 percent more energy than households with heads up to 40 years of

age. This may be related to patterns observed in one-person households. Moreover,

it may be associated with the empty nest household energy consumption pattern.

Additionally, these differences are seen in the relationship that is displayed in table

6. Households that consume more energy per capita are most common among


PER HOUSEHOLD BY AGE OF HOUSEHOLD HEAD

(in kilowatt-hours)


2008 (ENIGH).



19/32

households with heads aged 60 years or more (38.5 percent) and least common among

households with heads aged 40 or less (17.3 percent). Instead, it is more likely to find

households that consume less energy per capita among households with younger

heads (23 percent) and less likely among households with older heads (13.9 percent).

As shown, the life-cycle stage of the household is a determinant of energy

consumption. In this study we found that more energy per household is consumed inconsolidated households headed by members in the age category of 40 to 60 years.

This group is followed in its per-capita energy consumption by aging households

(heads over 60 years of age).

In the first case, the main factor is electricity consumption, probably associated with

the presence of adolescents and youth. In the second case, energy consumption prac-

tices of older adults and the presence of obsolete technology appear as likely causes.

Age of household members is a useful category to observe energy consumption

patterns. Therefore, pointing to the variety of family arrangements and diverse

energy consumption practices, the analysis considers economic dependents too.The central idea is to relate household energy consumption patterns with the

presence or absence of children and elderly in the household structure. The fol-

lowing four household groups are considered: no economic dependents under

12 years old or above 64 years old; economic dependents under 12 years old;

economic dependents above 64 years old; and both types of economic dependents.

Figure 7 shows that the average energy consumption per household is higher in

those with both types of economic dependents. This is due to household size and

households are likely to be extended. These households consume 20 percent more

energy than households without dependents. Additionally, they consume moreenergy than households with dependents over 64 years old (25 percent) and than

households with dependents under 12 years (31 percent), respectively.


CONSUMPTION AND AGE OF HOUSEHOLD HEAD, 2008a

Per-Capita Energy

Consumption

Age of Household Head

Total

Up to 40

Years Old 40 to 60 Years Old

More than 60

Years Old

Low 23.0 15.4 13.9 17.8

Medium 59.8 56.2 47.6 55.6

High 17.3 28.4 38.5 26.7

Total 100.0 100.0 100.0 100.0

(N) 8,978 10,708 5,652 25,338

a p < .01.


2008 (ENIGH).



20/32

Households with dependents in both ages also consumed more energy from the

use of electricity, gas, and firewood. Observed patterns, however, are not homo-

geneous. It is likely that in these households, grandparents and grandchildren

could be living together and their household heads are middle aged. They could

also be households where children and their families are returning to a parental

home. These phenomena are related to family culture in Mexico or are related to

family survival strategies for those facing adverse circumstances.

In table 7, one can observe that it is more likely to find high per-capita energy

consumption in households with dependents over 64 years of age (43.4 percent)and those households without dependents in the ages studied (40.2 percent). It is

less likely to find high per-capita energy consumption in households with de-

pendent children (13 percent). On the other hand, households with low per-capita

energy consumption are more common when they have dependents under 12 years

of age (23.4 percent) and least common among those households with no children

or older adults (11.6 percent).

It can be said that households with high per-capita energy consumption

are, indeed, households on the advanced stages of the life cycle (with seniors)

and consolidated households (with young people). Moreover, the importanceof considering the effect of economies of scale on the analysis is readily

apparent.


PER HOUSEHOLD BY DEPENDENTS

(in kilowatt-hours)


2008 (ENIGH).



21/32

Gender Issues: There are a variety of analytical perspectives on the concept of

gender. A distinction must be made between biological sex and social gender, that

is, the concept that relations between men and women are socially constructed.

This social construction leads to the existence of particular ideas about femininity

and masculinity that result in different concepts of what constitutes these roles.Finally, gender can be understood as a structuring principle that cuts across the

material and symbolic societal organization.

Between 2000 and 2010, households headed by women increased from 20.6 to

24.6 percent in Mexico.40 This trend also is associated with increased poverty,

unemployment, job insecurity, and the decline of male participation in the labor

market. Furthermore, because of migrant household heads prolonged absence,

Mexican women have acquired new roles.

Roles played by men and women in everyday domestic life are an essential

expression of energy consumption practices. In Mexico it is more common formen to have a supplier role. Women, however, are considered predominately

responsible for domestic activities. Therefore, it is likely that there are differences

in household consumption patterns by gender member.

There are three aspects that seem most likely to be seen in light of a gender

perspective. These are domestic work, decision making, and time used in domestic

life. Thus, we propose to measure energy consumption by grouping households as

those headed by women and those headed by men.

Figure 8 shows that households headed by men, on average, consumed 9

percent more energy than households headed by women. Male-headed householdconsumption of electricity, gas, and firewood is also higher at 11, 4, and 16

percent, respectively.


CONSUMPTION AND DEPENDENTS, 2008a

Per-Capita Energy

Consumption

Dependents

TotalNone

Less than 12

Years Old

More than 64

Years Old Both

Low 11.6 23.4 11.9 23.3 17.7

Medium 48.2 63.6 44.7 61.9 55.6

High 40.2 13.0 43.4 14.8 26.7

Total 100.0 100.0 100.0 100.0 100.0

(N) 8,372 11,762 3,838 1,366 25,338

a p < .01.


2008 (ENIGH).



22/32

Compared with those observed in previous sections, differences between these

two household types are reduced in all cases. Since women-headed households

have lower average size, this suggests that the witnessed patterns are more closely

linked to household size.

According to data in table 8, one is more likely to find high energy con-sumption per household member in female-headed households (32.5 percent) than

male-headed households (24.8 percent). In contrast, among households that con-

sume less energy per capita a higher proportion are male-headed households (18.6

percent) versus female-headed households (15.3 percent).

However, when we used household head as a marker we are likely to lose sight

of another energy consumption determinant related to gender. Thus, we decided to

focus the analysis on the gender composition of the household members and made

the following three distinctions: men only households; women only households;

and households with both genders.

Figure 9 shows that energy consumption is higher in households with both

genders. This is related to household size. But if we compare men only households

versus women only households, the latter group consumes more energy.

In the case of total energy consumption, the women only households consumed

28 percent more energy than the men only households. In terms of electricity, gas,

and firewood consumption, the differences are 15, 21, and 3 percent, respectively.


PER HOUSEHOLD BY GENDER OF HOUSEHOLD HEAD

(in kilowatt-hours)


2008 (ENIGH).



23/32

According to table 9, it is more likely to find high per-capita energy con-

sumption among households comprised only of women (49.1 percent) than in

households comprised only by men (47.3 percent). On the other hand, it also is

more likely that households with low energy consumption are composed only of

men (12.3 percent) than composed only by women (10.9 percent). Since we

consider the effects of economies of scale and the association is statistically sig-

nificant, similar odds point to other determinants.To analyze energy consumption patterns based on our studied determinants, it

is essential to point out the interferences among the set of socio-demographic

variables. We also must factor in the influence of the geographical context in

which the households are located. Therefore, it is necessary to conduct a multi-

variate analysis. The aim is to explore the interplay of energy consumption

determinants.

The following section presents the results of the logistic regression models. These

models are used to complement the statistical analysis performed up to this point.

Logistic Regression Models

This section presents logistic regression models of Mexican household energy

consumption. These models use household consumption and consumption per

household member as dependent variables. Other variables are grouped according

to the following: (1) households socio-demographic characteristics as in-

dependent variables and (2) geographical context as control variables. For pur-

poses of analysis, some of these have been regrouped.We decided to define high consumption households as those that consume

more than 2,000 kilowatt-hours (kWh) per household and more than 500 kWh per


CONSUMPTION AND GENDER OF HOUSEHOLD HEAD, 2008a

Per-Capita EnergyConsumption Male Female Total

Low 18.6 15.3 17.8

Medium 56.7 52.2 55.6

High 24.8 32.5 26.7

Total 100.0 100.0 100.0

(N) 19,077 6,263 25,340

a p < .01.

Source: Authors calculations based onEncuesta Nacional de Ingresos y Gastos de los Hogares2008 (ENIGH).



24/32

household member. To generate the models we tested linear correlations. Likewise

we ran bivariate logistic regression models to detect interactions among the variables.

The results of the per household energy consumption logistic regression model

are given in table 10. Based on the results, it is more likely to have high energy


PER HOUSEHOLD BY GENDER OF HOUSEHOLD MEMBERS

(in kilowatt-hours)


2008 (ENIGH).


CONSUMPTION AND GENDER OF HOUSEHOLD HEAD, 2008a

Per-Capita Energy

Consumption

Gender of Household Head

TotalOnly Males Only Females Both

Low 12.3 10.9 18.7 17.8

Medium 40.4 40.0 57.8 55.6

High 47.3 49.1 23.5 26.7

Total 100.0 100.0 100.0 100.0

(N) 1,284 1,956 22,099 25,339

a p < .01.


2008 (ENIGH).



25/32

consumption per household in the highest income quintile. Quintile V households

odds ratio is significantly higher than other quintiles. In the case of household size,

those households with more than 4 members are more likely to have high energy

consumption. Moreover, it is less likely to observe high energy consumption per

household in one-person households.The probability of finding high energy consumption per household is greater in

households with heads aged at least 60 years old, followed by households with

heads aged 40 to 60 years old. But it is more likely to observe high energy con-

sumption in households without children or older adults. This last result, however,

is not statistically significant.

With respect to gender of the household head, the probability of finding high

energy consumption per household is lower in female-headed households than in

male-headed ones. This confirms that there are gender-related practices that do

affect Mexican household energy consumption.

Finally, although the result is not statistically significant, it is more likely

to find high energy consumption per household in women-only households,

compared with other gender compositions. In this regard, it should be noted that

using the gender of the household head best explains energy consumption

patterns.

The results of the logistic regression model generated for energy consumption

per household member as a dependent variable is shown in table 11. According to

the findings in table 11, the probability of finding high energy consumption perhousehold member grows with household income. Here, too, is a remarkably high

probability associated with Quintile V households. Thus, it can be said that this

group of households is a priority for public policy aimed at encouraging less

energy-intensive practices.

In the case of household size, as opposed to energy consumption per household, you

are less likely to observe high energy consumption per household member in larger

households. This is due to the economies of scale effect on consumption patterns.

On the other hand, you are more likely to find high energy consumption per

household member in one-person households than in other households. Since thisis a growing group of households, it also requires priority attention to reduce GHG

emissions due to energy use.

In the case of household member ages, as shown in table 11, the likelihood of

high energy consumption per household member is higher in households with

heads over the age of 60 years, followed by households with heads aged 40 to 60

years. It is a similar pattern to that observed with energy consumption per

household but, in this case, it is linked to one-person households.

Regarding economic dependents, you are more likely to find high energy

consumption per capita in households without children or older adults. This isa statistically significant result suggesting that households with teenagers and

middle-aged people require top priority for climate change policy.



26/32

Table 10ODDS RATIOS OF LOGISTIC REGRESSION ANALYSIS ON WHETHER

ENERGY CONSUMPTION PER HOUSEHOLD IS HIGH

(High = more than 2,000 kilowatt-hours)a

(n = 25,088)

Without

Control

Variables

Controlling

by Region

Controlling

by Location

Controlling

by Region

and Location

Socio-demographic characteristics

Income Strata

(Quintile I) 1.000 1.000 1.000 1.000

Quintile II 2.120* 1.890* 1.950* 1.808*

Quintile III 3.522* 3.019* 3.104* 2.824*

Quintile IV 6.207* 5.246* 5.342* 4.844*

Quintile V 20.260* 17.067* 17.102* 15.598*

Household size

(Up to 4 members) 1.000 1.000 1.000 1.000

More than 4 members 1.337* 1.423* 1.371* 1.440*

Household type

(Other) 1.000 1.000 1.000 1.000

One person 0.491* 0.460* 0.477* 0.454*

Age of household head

(Up to 40 years old) 1.000 1.000 1.000 1.000

40 to 60 years old 1.606* 1.642* 1.617* 1.649*Over 60 years old 2.050* 2.107* 2.070* 2.121*

Dependents

(Less than 12 and over 64 years old) 1.000 1.000 1.000 1.000

None 1.036 1.032 1.022 1.025

Sex of household head

(Male) 1.000 1.000 1.000 1.000

Female 0.929 0.921 0.913 0.913*

Sex of household members

(Other) 1.000 1.000 1.000 1.000Only females 1.011 1.018 1.007 1.017

Control variables

Region

(Distrito Federal) 1.000* 1.000*

Northern 1.541* 1.587*

Central region 0.757* 0.788*

Southern 0.517* 0.550*

Location

(Non-urban) 1.000 1.000

Urban 1.397* 1.224*

(continued)



27/32

With respect to energy consumption behavior related to gender, we are less likely to

observe high energy consumption per household member in female-headed households

compared to male-headed households. But the result is not statistically significant.

On the other hand, one is more likely to find high energy consumption per household

member in households composed entirely of women compared to other householdgender composition. The latter result is statistically significant and, even though it is

possible to say that gender helps to determine household energy consumption patterns,

it is less relevant than other socio-demographic household characteristics.

Some Final Notes

The first thing that should be noted is that controlling for region and location

improves the models goodness of fit. For that reason, for the study of householdsenergy consumption determinants, it is essential to include these and, as far as

possible, other contextual factors.

Additionally, it is important to recognize that the models goodness of fit

improves when we use energy consumption per household member as a dependent

variable. This suggests that consumption per household member is a better in-

dicator when studying energy consumption patterns.

To use information from ENIGH allowed us to achieve the outlined goals in

this research. Its analysis was very useful for understanding key aspects of

household energy consumption.However, it should be noted that irregular or illegal connections to electricity

for domestic use is a significant issue in Mexico. These illegal practices affect

Table 10 (continued)ODDS RATIOS OF LOGISTIC REGRESSION ANALYSIS ON WHETHER

ENERGY CONSUMPTION PER HOUSEHOLD IS HIGH

(High = more than 2,000 kilowatt-hours)a

(n = 25,088)

Without

Control

Variables

Controlling

by Region

Controlling

by Location

Controlling

by Region

and Location

Constant 0.028* 0.034* 0.024* 0.03*

Cox & Snell R square 0.154 0.171 0.156 0.172

Nagelkerke R square 0.244 0.272 0.247 0.273

-2 Log Likelihood 20,887.3 20,357.2 20,830.4 20,338.0

df 11 14 12 15

a Omitted categories are presented in parentheses; * = p < .05.


2008 (ENIGH).



28/32

Table 11ODDS RATIOS OF LOGISTIC REGRESSION ANALYSIS ON

WHETHER ENERGY CONSUMPTION PER HOUSEHOLD MEMBER IS HIGH

(High = more than 500 kilowatt-hours)a

(n = 25,088)

Without

Control

Variables

Controlling

by Region

Controlling

by Location

Controlling

by Region

and Location

Socio-demographic characteristics

Income Strata

(Quintile I) 1.000 1.000 1.000 1.000

Quintile II 1.603* 1.426* 1.475* 1.368*

Quintile III 2.437* 2.095* 2.171* 1.977*

Quintile IV 3.549* 3.026* 3.090* 2.822*

Quintile V 10.076* 8.469* 8.606* 7.821*

Household size

(Up to 4 members) 1.000 1.000 1.000 1.000

More than 4 members 0.223* 0.227* 0.227* 0.229*

Household type

(Other) 1.000 1.000 1.000 1.000

One person 2.699* 2.560* 2.613* 2.518*

Age of household head

(Up to 40 years old) 1.000 1.000 1.000 1.000

40 to 60 years old 1.502* 1.519* 1.512* 1.524*Over 60 years old 3.003* 3.060* 3.038* 3.080*

Dependents

(Less than 12 and over 64 years old) 1.000 1.000 1.000 1.000

None 1.761* 1.776* 1.742* 1.765*

Sex of household head

(Male) 1.000 1.000 1.000 1.000

Female 0.997 0.986 0.980 0.978

Sex of household members

(Other) 1.000 1.000 1.000 1.000Only females 1.501* 1.542* 1.501* 1.542*

Control variables

Region

(Distrito Federal) 1.000* 1.000*

Northern 1.291* 1.328*

Central region 0.737* 0.766*

Southern 0.492* 0.522*

Location

(Non-urban) 1.000 1.000

Urban 1.373* 1.201*

(continued)



29/32

energy consumption estimates and also limit the scope for public intervention to

promote energy savings.

It is worth highlighting the fact that the fuel used in Mexican households is

associated with its distribution market. Natural gas distribution covers only spe-

cific areas of the country. Distribution of liquefied petroleum gas (LPG), mean-while, fails to reach a large number of small towns scattered throughout its ter-

ritory. If we factor in gas prices, this helps to explain why firewood continues to

have a strong presence among fuels used in Mexico.

Because electricity is an energy source available in almost all Mexican

households, we find that there is a distinction between the fuel types used for

cooking and heating water. On the one hand, we have households with better

social and economic development, where the main fuels are natural gas or liq-

uefied gas. On the other hand, there are households residing in poverty, which use

fuels such as firewood, coal, diesel, oil, paper, or cardboard.It can be said that these energy practices coexist, which may be called modern

and non-modern with the latter related to technological backwardness, poverty,

and socioeconomic inequality. However, there are indications that coal and fire-

wood are used as a second fuel in households with better living conditions.

To advance on this field of study, the next step is to consider other factors

associated with household energy consumption patterns. In the case of ENIGH,

there are data about household and housing equipment. Others variables to con-

sider are equipment age and its energy efficiency as well as household members

concern about daily energy consumption practices. Thus, data sources that addresstechnological change and peoples life-style fields focusing on household energy

consumption would be required.

Table 11 (continued)ODDS RATIOS OF LOGISTIC REGRESSION ANALYSIS ON

WHETHER ENERGY CONSUMPTION PER HOUSEHOLD MEMBER IS HIGH

(High = more than 500 kilowatt-hours)a

(n = 25,088)

Without

Control

Variables

Controlling

by Region

Controlling

by Location

Controlling

by Region

and Location

Constant 0.079* 0.107* 0.070* 0.095*

Cox & Snell R square 0.154 0.171 0.156 0.172

Nagelkerke R square 0.244 0.272 0.247 0.273

-2 Log Likelihood 20,887.3 20,357.2 20,830.4 20,338.0

df 11 14 12 15

a Omitted categories are presented in parentheses; * = p < .05.


2008 (ENIGH).



30/32

NOTES

1Henri Moll, Klaas Jan Noorman, Rixt Kok, Rebecka Engstrom, Harald Throne-Holst, and

Charlotte Clark, Pursuing More Sustainable Consumption by Analyzing Household Metabolism in

European Countries and Cities,Journal of Industrial Ecology, vol. 9, nos. 12 (2005), pp. 25975.2John Keynes, Teor a general de la ocupacio n, el interes y el dinero (Mexico City: Fondo de

Cultura Economica, 1951).

3Milton Friedman,Una teor a de la funcion del consumo(Madrid, Spain: Editorial Alianza, 1973).

4James Duesenberry, Income, Saving and the Theory of Consumer Behavior (Cambridge,

Massachusetts: Harvard University Press, 1949).

5Albert Ando and Franco Modigliani, The Life Cycle Hypothesis of Saving: Aggregate Im-

plications and Tests, American Economic Review, vol. 53, part 1 (1963), pp. 5584.

6Juan Hernandez, Revision de los determinantes macroeconomicos del consumo total de los

hogares para el caso colombiano (Bogota, Colombia: Banco de la Republica, Borradores de

Economa, 2006).

7Maria Chuiri, Individual Decisions and Household Demand for Consumption and Leisure,

Work Paper no. 26, Universita degli Studi di Salerno, Italy, 1999.

8Niklas Karlsson, Peter Dellgran, Birgitta Klingander, and Tommy Garling, Household Con-

sumption: Influences of Aspiration Level, Social Comparison, and Money Management, Journal

of Economic Psychology, vol. 25, no. 6 (2004), pp. 75369.

9Steffen Kallbekken, Jostein Rise, and Hege Westskog Combining Insights from Economics

and Social Psychology to Explain Environmentally Significant Consumption, Working Paper

no. 2, Center for International Climate and Environmental Research, Oslo, Norway, 2008.

10Daniel McFadden, Economic Choices, American Economic Review, vol. 91, no. 3 (2001),

pp. 35178.

11Lee Schipper, Life-styles and the Environment: The Case of Energy, in Technological

Trajectories and the Human Environment, eds. Jesse H. Ausubel and H. Dale Langford (Wash-

ington, D.C.: National Academies Press, 1997), pp. 89109.

12Brian ONeill and Belinda Chen, Demographic Determinants of Household Energy Use in

the United States, Supplement: Population and Environment: Methods of Analysis, Population

and Development Review, vol. 28, no. 2 (2002), pp. 5388.

13Anne Pebley, Demography and the Environment, Demography, vol. 35, no. 4 (1998), pp. 37789.

14L. Schipper, op. cit.

15Agustn Canzani and Nicolas Somma, Publicos y estilos de vida (Montevideo, Uruguay:

Seminario Publicos, 2002).

16Erling Holden, Attitudes and Sustainable Household Consumption (Sogndal, Norway: West-

ern Norway Research Institute, 2005).



31/32

17Josef Leitman, How to Collect Data on Household Energy Consumption, Policy, Planning

and Research Working Papers, no. 108, World Bank, Washington, D.C., 1989.

18Instituto de Nacional de Geografa y Estadstica (INEGI), Encuesta Nacional de Ingresos y

Gastos de los Hogares 2008. Cambios y Adiciones (Mexico City: INEGI, 2009).

19Fernando Cortes, Acerca de la medicion oficial de la pobreza en Mexico en el ano 2000,

Estudios Sociologicos, vol. 21, no. 2 (2003), pp. 46370.

20Araceli Damian, Los problemas de comparabilidad de las ENIGH y su efecto en la medicion

de la pobreza, Papeles de Poblacio n, vol. 51 (2007), pp. 11146.

21Francisco Alba, Tendencias de la desigualdad regional en Mexico ante el TLC, in Creci-

miento con convergencia o divergencia en las regiones de Mexico. Asimetr a Centro-Periferia, eds.

Alejandro Daz-Bautista, Noe Aron Fuentes Flores, and Sarah Eva Martnez Pellegrini (Mexico

City: El Colegio de la Frontera Norte, 2003), pp. 15166.22The Distrito Federal shares few characteristics with other states in the country. It has the highest

rates of social and economic development. Distinctions may be useful as a benchmark. We must not

lose sight of the fact that the Metropolitan Area of Mexico City goes far beyond its political limits.

23Ignacio Cruz, Determinantes sociodemograficos del consumo de energa en los hogares, en

el marco de la Estrategia Nacional de Cambio Climatico, (Ph.D. dissertation, El Colegio de

Mexico, Mexico City, Mexico, 2012).

24I. Cruz, op. cit.

25Artemio Baigorri, De lo rural a lo urbano (Granada, Spain: V Congreso Espanol de Socio-

loga, 1995); Henri Lefebvre,De lo rural a lo urbano(Barcelona, Spain: Editorial Pennsula, 1978);

and P. Villalvazo, J. P. Corona-Medina, and S. Garca-Mora, Urbano-rural, constante busqueda de

fronteras conceptuales, Revista de Informacio n y Analisis, vol. 20 (2002), pp. 1724.

26A. Baigorri, op. cit., and Thierry Linck, El campo en la ciudad: reflexiones en torno a las

ruralidades emergentes, Relaciones, vol. 22, no. 85 (2001), pp. 86104.

27A. Baigorri, op. cit., and Consejo Nacional de Poblacion (CONAPO),Evolucio n de las ciu-

dades de Mexico, 1900-1990 (Mexico City: CONAPO, 1994).

28We believe that the conventional limit of 2,500 inhabitants neglects the rural-urban exchange

dynamics. Moreover, it represents only 23 percent of households in the ENIGH sample. See Luis

Unikel, Ensayo sobre una nueva clasificacion de poblacion rural y urbana en Mexico, Demo-

graf a y Econom a, vol. 11, no. 1 (1975), pp. 118.

29Marina Ariza and Orlandina de Oliveira, Familias en transicion y marcos conceptuales en

redefinicion, Papeles de Poblacio n, vol. 28 (2001), pp. 939; Julieta Quilodran, La familia,

referentes en transicion,Papeles de Poblacio n, vol. 37 (2003), pp. 5182; and Alfonso Velazquez

and Daniel Vega, Dinamica de los arreglos residenciales en Mexico 2000-2005, in Situacion

Demografica de Mexico 2006(Mexico City: Consejo Nacional de Poblacion, 2006), pp. 7587.

30Mariana Gabarrot, La migracion como estrategia de vida y su impacto en los hogares

migrantes: una perspectiva de genero para hacer propuestas de poltica publica, in Mujeres



32/32

afectadas por el fenomeno migratorio en Mexico. Una aproximacion desde la perspectiva de

genero(Mexico City: Instituto Nacional de las Mujeres, 2007), pp. 21724, and Mercedes Gonzalez,

From the Resources of Poverty to the Poverty of Resources? The Erosion of a Survival Model,

Latin American Perspectives, vol. 28, no. 4 (2001), pp. 72100.

31Organismo Internacional de Energa Atomica (OIEA), Indicadores energeticos del desarrollo

sostenible: directrices y metodolog a (Vienna: Organismo Internacional de Energa Atomica, 2008).

32I. Cruz, op. cit.

33Eunice Banuelos and Leonor Gomez, Cambios en los hogares mexicanos, Demos. Carta

Demografica sobre Mexico, vol. 10 (1997), pp. 246; Consejo Nacional de Poblacion (CONAPO),

Dinamica de los arreglos residenciales en Mexico 2000-2005, in Situacion demografica de

Mexico 2006(Mexico City: CONAPO, 2006), pp. 7587; and I. Cruz, op. cit.

34Stephen Hunt, The Life Course: A Sociological Introduction (Hampshire, United Kingdom:

Palgrave Macmillan, 2005), and Anton Kuijsten, Advances in Family Demography (The Hague,

Netherlands: Netherlands Interuniversity Demographic Institute, 1986).

35It is pertinent to mention that various classifications of family or household stages can be found.

See Salustiano and Mara Rodrguez Del Campo, La gran transformacion de la familia espanola

durante la segunda mitad del Siglo XX, Revista Espanola de Investigaciones Sociologicas, vol. 100

(2002), pp. 10365, and Organizacion Mundial de la Salud (OMS), Indices estad sticos de la salud de

la familia, Serie de Informes Tecnicos, 587(Geneva, Switzerland: OMS, 1976).

36Victor Marshall and Margaret Mueller, Life Course Concepts in North America, inThe Life

Course: Social Dynamic of Transitions, Institutions and Interrelations, eds. W. R. Heinz and V. M.Muller (New York: Aldyne/De Gruyter, 2003).

37Felix Acosta, Jefatura de hogar femenina y bienestar familiar en Mexico, (Ph.D. disser-

tation, El Colegio de Mexico, Mexico City, Mexico, 2000).

38Luis Hernandez and Pablo Slon, Tipologa de la pobreza segun la Teora del Ciclo de Vida,

inSimposio Costa Rica a la luz de la Encuesta de Ingresos y Gastos de los Hogares 2004 (San Jose,

Costa Rica: INIG, 2006), pp. 43353.

39Peter Uhlenberg, Changing Configurations of the Life Course, inTransitions: The Family and the

Life Course in Historical Perspective, ed. T. Hareven (New York: Academic Press, 1978), pp. 6597.

40I. Cruz, op. cit.


Documents

“Energy Consumption of Mexican Households,” by Ignacio César Cruz Islas