Introduction
The right to decent, adequate and decent housing has been recognized since 1948 in the Universal Declaration of Human Rights, in article 25, which states: every person has the right to an adequate standard
of living that ensures for themselves and their family, health, well-being, and especially
food, clothing, housing, medical care, and necessary social services.
Regarding the issue of housing, the United Nations (UN-Habitat, 2010). establishes seven basic elements to have adequate housing:
-
Legal security of tenure for housing. It means conditions that guarantee legal protection
for its occupants against forced eviction, harassment, and other threats.
-
Availability of services, materials, facilities, and infrastructure. It refers to
the provision of drinking water, adequate sanitary facilities, energy for cooking,
heating, and lighting, food preservation, waste disposal, and emergency services.
-
Affordability. It means that the cost of housing must be such that all people can
access it without endangering the enjoyment of other basic satisfactions.
-
Habitability of housing. It means the existence of structural and design elements
that guarantee physical safety and protection for its occupants against environmental
hazards and health threats, as well as sufficient habitable space and protection against
cold, moisture, heat, and rain, among others.
-
Accessibility. It refers to the fact that the design and materiality of housing must
consider the specific needs of disadvantaged and marginalized groups, particularly
people with disabilities.
-
Location. It means that the location must offer access to employment opportunities,
health services, schools, daycare centers, and other social services and facilities,
and be located outside of risky or contaminated areas.
-
Cultural adaptation. It refers to the fact that the expression of the cultural identity
of its occupants must be respected and taken into account.
For some authors (Kowaltowski et al, 2006; Ortiz, 2012; Hernández-Rejón, 2010; Córdova-Canela, 2021, Forrest et al, 2021), housing can be understood in two ways: as a commodity, which is recorded in the
dynamics of supply and demand, and as a social and human right. Regarding the first,
it means that housing is a high-cost finished product and is aimed at those who can
pay for it, and concerning to housing as a social and human right, it means that it
is fundamental for the adequate development of individuals.
In this sense, it can be said that housing plays a decisive role in people’s quality
of life, and in most cases, leads to access to services today considered essential
to achieve minimum levels of well-being. Having said the above, satisfaction with
housing can become a parameter that makes it possible to quantify people’s quality
of life. Measuring home satisfaction implies a subset of attributes, including the
physical elements of the building and the necessary accessories for its habitability
(water supply, electricity, etc.).
In this sense, the main objective of this research is to analyze the principal elements
that determine housing satisfaction, as well as to calculate the probability that
a home can be satisfied with it.
Based on the background and literature review, we can determine the following hypotheses.
-
Hypothesis 1: There is a positive correlation between socioeconomic level and satisfaction with
housing, that is, as socioeconomic level increases, housing satisfaction also increases.
-
Hypothesis 2: There is a positive correlation between the size of the dwelling, and the level of
satisfaction, meaning that as a dwelling has more space, satisfaction also increases.
-
Hypothesis 3: Experiencing issues such as cracks, subsidence and fissures decreases satisfaction
with the home.
-
Hypothesis 4: Having amenities such as a garden, patio, and a good environment close to the home
increases satisfaction with it.
The present is only an exercise to be taken as a reference regarding the subject.
The relevance of taking these statistical approaches lies in the fact that they become
a tool that facilitates the targeting of housing policy, allowing adequate management
of programs and projects associated with improving the quality of life.
Materials and methods
The objective of this research is to estimate an econometric model that explains the
probability of satisfaction with the dwelling as a function of the characteristics
of the dwelling itself and its surrounding environment. Particularly, it seeks to
validate the proposed hypotheses and visualize the issue of residential satisfaction
in Mexico by socioeconomic level.
For the purposes of this research, the socio-economic levels index of the Mexican
Association of Market Research Agencies (AMAI, 2022) is used as a reference. This index is based on a statistical model that allows Mexican
households to be grouped and classified into seven levels according to their ability
to meet the needs of their members. The index considers the following six household
characteristics: educational level of the head of household, number of employed persons
in the household, internet access, proportion of household expenses, and number of
automobiles.
The classification of socioeconomic levels is presented in the following table, which
is classified into letters from A/B to E, the latter being the lowest and equivalent
to households in extreme poverty, which may earn up to $2000 Mexican pesos per month
of work income.
Table 1
Description of socioeconomic levels.
|
NSE
|
Description
|
household
type
|
|
A/B
|
It is made up mostly of households in which the head of the family has professional
or postgraduate studies (80%). 67% have at least two cars. Practically all of them
have internet (99%).
|
Upper class
|
|
C+
|
72% of household heads have at least a high school education. 30% have at least two
cars and 97% have fixed internet at home.
|
Upper middle class
|
|
C.
|
82% of households have a head with a high school education or more. 91% have fixed
internet at home and 37% of spending is used for food. 14% have at least two cars.
|
Middle class
|
|
C-
|
63% of households are headed by a family leader with a maximum education level of
middle school. Eight out of 10 households (78%) have fixed internet at home. About
40% of spending is allocated to food and 18% to transportation.
|
Medium- low class
|
|
D+
|
74% of households are headed by a family leader with studies up to the secondary level.
55% have a fixed internet connection and spend 42% on food.
|
Lower class
|
|
D.
|
In 53% of households, the head has completed elementary school. Only 14% have fixed
internet at home. Just under half of their spending goes to food (48%).
|
Poverty
|
|
E
|
Most households (82%) have a head with no more than primary education. Internet ownership
in the home is very low (0.3%) More than half of spending is allocated to food (52%)
and only 1% to education.
|
Extreme poverty
|
Table 2
Definition of socioeconomic level by monthly income
|
NSE
|
Income
|
Max
|
|
A/B
|
$64,901
|
Onwards
|
|
C+
|
$34,901
|
$64,900
|
|
C
|
$22,901
|
$34,900
|
|
C-
|
$10,501
|
$22,900
|
|
D+
|
$4,791
|
$10,500
|
|
D
|
$2,001
|
$4,790
|
|
E
|
Less than $2,000
|
$2,000
|
Table 3
Distribution of SES in Mexico.
|
NSE
|
A/B
|
C+
|
C
|
C-
|
D+
|
D
|
E
|
|
Percentage
|
7%
|
14%
|
17%
|
17%
|
14%
|
24%
|
8%
|
DATABASE AND VARIABLES
The data used in this research comes from the 2020 National Housing Survey in Mexico
(ENVI, 2020) conducted by the National Institute of Statistics and Geography. The purpose of
this survey is to produce statistical information about the characteristics of housing
in Mexico, which allows generating a comprehensive overview of the housing situation
in the country, as well as the needs and demands of the population in this regard.
The model that we will use to estimate the probability of housing satisfaction is
an Ordered Probit Model. The definition of the dependent variable used in the model
is based on the following question: On a scale from 0 to 10, tell me, how satisfied
are you with the house?
While the explanatory variables, based on which the probabilities of satisfaction
are estimated are the following:
-
Variables in the immediate environment of the home. These variables refer to the exterior
close to the home, that is, the conditions that each family faces during their day-today:
problems with excessive noise from neighbors, garbage is thrown in the streets, lack
of wheelchair ramps, robberies, and assaults.
-
Individual and internal variables to the dwelling. These variables are the ones that
define the internal characteristics of the house, meters that measure the land of
the house, household income, age of the unit, amenities (garden, garage, water tank,
dining room), humidity problems, subsidence, cracks, and fissures.
The variables are briefly described below, and the nomenclature used for them is indicated.
-
Income (log_ing). This variable is included to capture the effect of income on housing satisfaction;
Some authors such as Addo (2016), Alnsour and Hyasat (2016), Reategui (2018), Ibem et al (2019), Chang and Wong (2022), and Kshetrimayum et al (2020) have addressed the issue, finding that low-income households tend to be the least
satisfied with their homes. This is logical in the sense that the poorest households,
since they do not have enough income, do not have the economic capacity to pay for
a home that meets certain characteristics that influence their satisfaction.
-
Square meters (P4_21_1). The use that is given to a house and the number of inhabitants end up defining the
size of the house. In the first hypothesis, the size becomes important in the satisfaction
of the dwelling, since it is expected that there will be less overcrowding and greater
capacity for space distribution regarding the needs of each home. In the case of this
variable, usually as the square meters of a home increase, its price also increases
(Zhang and Hudson, 2018; Poeta et al, 2019; Urrea and Cardenas, 2019; Duan et al, 2021), so it is expected that the households with lower incomes tend to have smaller dwellings
and are therefore more dissatisfied with the size.
-
Garden (P4_23_3), garage (P4_23_6), dining room (P4_23_1), laundry room (P4_22_1). The internal characteristics of the house are other kinds of satisfaction measures,
in the case of the garden, it can provide a series of ecosystem benefits that affect
well-being and satisfaction, such as improving air quality, reducing noise that comes
from the street to inside the house, protects the house from ultraviolet rays and
lowers the ambient temperature (Dunnet and Qasim, 2000; Lampert et al, 2021; Andini et al, 2021; White et al, 2019). In the case of the garage, it allows for safe parking and space, which can be used
for various uses. On the other hand, the function of the dining room is essential
for a key meeting point for the members of the household, meaning, the dining room
is the space for family gatherings, around the table not only food, is consumed, but
also conversations and important decisions are made (Amerio et al, 2020).
-
Cracks (P4_25_1), subsidence (P4_25_3), humidity (P4_25_4), pipes (P4_25_7). In the case of cracks, these can cause major problems, not just aesthetic or structural.
In some cases, water can leak through them, causing moisture inside. Additionally,
repairing them requires an extra cost to the home. As for humidity, it produces bacteria,
which not only put the health of household members at risk but also end up ruining
the aesthetics and structural quality of the house, since they manifest themselves
through dark spots (Zhang and Yoshino, 2010; Hamehkasi, 2016).
Table 4
Description of the variables used in the Ordered Probit Model
|
Variable
|
Description
|
Measurement
|
|
satisfaction (P6_8)
|
On a scale from 0 to 10, tell me, how satisfied are you with the house?
|
Continuous values (min = 0; max = 10)
|
|
logarithm of income (log_ing)
|
How much do you earn or receive monthly for your work or activity?
|
Continuous values (min = 3.6; max = 12.8)
|
|
Age of housing (P4_19_1)
|
How long ago was this house built?
|
Continuous values (min = 1; max = 97)
|
|
Square meters (P4_21_1)
|
How many square meters does the housing land measure?
|
Continuous values (min = 39; max = 997)
|
|
laundry room (P4_22_1)
|
Is this house equipped with a laundry room?
|
Binary variable 0, no (14.92%); 1, yes (85.08%)
|
|
water tank (P4_22_2)
|
Is this house equipped with a water tank?
|
Binary variable 0, no (34.47%); 1, yes (65.53%)
|
|
dining room (P4_23_1)
|
Does this house have a dining room?
|
Binary variable 0, no (31.71%); 1, yes (68.29%)
|
|
garden (P4_23_3)
|
Does this house have a garden?
|
Binary variable 0, no (65.86%); 1, yes (34.14%)
|
|
garage (P4_23_6)
|
Does this house have a garage?
|
Binary variable 0, no (57.72%); 1, yes (42.28%)
|
|
cracks (P4_25_1)
|
Do you have problems with cracks or fissures in roofs or walls?
|
Binary variable 0, no (54.94%); 1, yes (44.06%)
|
|
subsidence (P4_25_3)
|
Do you have problems with subsidence?
|
Binary variable 0, no (83.58%); 1, yes (16.42%)
|
|
humidity (P4_25_4)
|
Do you have problems with humidity or water leaks in foundations, walls, or roofs?
|
Binary variable 0, no (51.08%); 1, yes (48.92%)
|
|
pipes (P4_25_7)
|
Do you have problems with the water pipes or sewer system inside the house?
|
Binary variable 0, no (91.47%); 1, yes (8.53%)
|
|
ramps (P6_9_1)
|
Do you have a problem due to the lack of ramps (or elevators) for people with disabilities?
|
Binary variable 0, no (42.09%); 1, yes (57.91%)
|
|
noise (P6_9_2)
|
Do you have a problem with excessive noise from neighbors or from outside?
|
Binary variable 0, no (62.07%); 1, yes (37.93%)
|
|
trash (P6_9_3)
|
Do you have a problem with garbage thrown in the streets?
|
Binary variable 0, no (50.55%); 1, yes (49.45%)
|
|
robberies (P6_9_7)
|
Do you have a problem with robberies or assaults?
|
Binary variable 0, no (58.92%); 1, yes (41.08%)
|
Empirical analysis: ordered probit model
The econometric model that we propose explains the probability of housing satisfaction
as a function of its characteristics and a set of variables related to the housing
environment. In particular, we used an ordered response model, with a standard normal
distribution, commonly known as the Ordered Probit Model. The estimation of marginal
effects allows us to analyze the influence of variables on the probability of satisfaction.
Due to their characteristics, these types of models allow the following purposes:
-
Quantify the importance of the relationship between each of the covariates and the
dependent variable.
-
Determine through the marginal effects, which variables carry more weight to increase
or decrease the probability of an event or occurrence.
Following Cameron and Trivedi (2005), Munkin and Trivedi (2008) and Baltagi (2021) for this research we denote,
the level of housing satisfaction, which is an unobservable continuous random variable,
same that dependent on the immediate environment conditions of the housing and its
characteristics, this can be expressed as:
where:
household housing satisfaction i.
row vector (1 xk) containing the set of explanatory variables that influence housing
satisfaction.
column vector (kx1) of parameters associated to the explanatory variables.
residual
In the case of the model, the variable
increases from unknown thresholds according to the ordering of the alternatives.
It can be defined as follows:
For a model with m alternatives
y
, then:
F is a cumulative distribution function ( cdf ) of ei. The β are
obtained through maximum likelihood and their sign identifies the direction of
the
impact.
Marginal effects
Once the model parameters have been estimated, it is convenient and interesting to
analyze the marginal effects, which indicate the impact of each explanatory variable
on the probability that a household is satisfied with its home. In other words, how
does the partial change of any of the explanatory variables affect the probability
of satisfaction.
To quantify the marginal effects, the following equation is used:
In other words, the marginal effect indicates the effect that a one-unit change in
explanatory variable has on the probability of different discrete outcomes. More detailed
interpretations and derivations of marginal effects can be found in prior work (Greene 2005; and Wang and Kockelman 2005).
Descriptive statistics and empirical analysis
In this section, some of the descriptive statistics regarding housing satisfaction
are presented. One of the facts to highlight is that the mean satisfaction level is
8.2, which may indicate a moderate level of satisfaction. Table 5 shows the frequency of responses from the survey participants, noticing that 86 percent
fall within the 7-10 range of satisfaction level.
Table 5
Level of housing satisfaction
|
|
On a scale from 0 to 10, tell me, how satisfied are you with the house?
|
|
Satisfaction |
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
|
Percentage |
0.34%
|
0.24%
|
0.41%
|
0.66%
|
0.88%
|
6.77%
|
4.56%
|
10.97%
|
28.34%
|
16.40%
|
30.43%
|
Table 6 shows the level of satisfaction with the home by socioeconomic level. When analyzing
it in terms of socioeconomic level, it was found that the least satisfied groups are
levels D and E, that is, those who are in poverty. These results are consistent with
studies conducted by Hernández-Rejón (2010) and Souza (2010), which argue that dominant groups (upper and upper-middle classes) usually choose
the best places for settlement, leaving lower classes in peripheral and vulnerable
areas - suburbs with multiple requirements, forgotten and lagging behind urban development
(where even land prices are lower) - thus, they are the groups that inhabit these
areas with low levels of housing satisfaction and quality of life.
Table 6
On a scale from 0 to 10, tell me how satisfied are you with this home?
|
NSE
|
Min
|
Max.
|
Median
|
mean
|
SD
|
|
A/B |
5
|
10
|
10
|
9,318
|
0.99
|
|
C+ |
0
|
10
|
9
|
8,679
|
1.34
|
|
C. |
0
|
10
|
9
|
8,777
|
1.30
|
|
C- |
0
|
10
|
9
|
8,846
|
1.36
|
|
D+ |
0
|
10
|
8
|
8,323
|
1.66
|
|
D. |
0
|
10
|
8
|
8,022
|
1.83
|
|
E |
0
|
10
|
8
|
7,879
|
1.93
|
Housing related issues
Having a home not only means having a roof to live in, but it is a place that requires
maintenance, and addressing problems that are difficult to solve (cracks, fissures,
humidity, subsidence, among others) and, sometimes, are impossible to repair, being
resolved only temporarily. Among the main structural problems analyzed in this research
are moisture, cracks or fissures, and subsidence.
Humidity
According to data from the National Housing Survey (2020) of the National Institute of Statistics and Geography, the biggest structural problem
that occurs in homes nationwide is humidity or water leaks at 44.2%, followed by cracks
and fissures at 40.8. %. In the case of humidity, Martínez et al (2005) mention that it causes health problems or discomfort in people, damages and injuries
in the house, favors the development of pathological processes such as efflorescence
on walls and floors, generates the appearance of germs that contaminate the environment,
corrosion and rotting of metallic and wooden elements, respectively, and the reduction
of thermal insulation.
Exploring the data from our analysis, Table 7 shows the percentage of homes that declared having at least problems with moisture
in foundations, walls, and ceilings. Once again, the socioeconomic levels with the
greatest humidity problems are D and E, although the humidity problem is present in
all homes, eliminating, reducing and controlling the formation of damp and subsequent
mold on walls and ceilings, it requires preventive and corrective maintenance, which
are usually of high-cost that the poorest households cannot afford.
Table 7
Problems with humidity in foundations, walls and ceilings
|
|
Does this house have problems with humidity or water leaks in the foundations, walls
or ceilings?
|
|
|
A/B
|
C+
|
C
|
C-
|
D+
|
D
|
E
|
|
1 = yes |
19%
|
25%
|
30%
|
35%
|
45%
|
54%
|
59%
|
|
0 = No |
81%
|
75%
|
70%
|
65%
|
55%
|
46%
|
41%
|
Cracks
Among other problems that can be generated inside homes are cracks or fissures. These
refer to cracks that appear on the surface of the concrete of the house, they are
mainly due to incorrect consolidation, finishing, curing procedures, and sometimes
to over-vibration (Méndez et al, 2012). In the case of analyzed data, problems such as cracks or fractures, as in the case
of humidity, are concentrated in socioeconomic levels D+, D, and E, leading to a possible
reality of housing precariousness in the poorest households, being these the most
vulnerable.
Table 8
Does your building have problems such as cracks or fractures in hallways?
|
|
Does your building have problems such as cracks or fractures in hallways?
|
|
|
A/B
|
C+
|
C
|
C-
|
D+
|
D
|
E
|
|
1 = yes |
10%
|
9%
|
19%
|
16%
|
25%
|
26%
|
30%
|
|
0 = No |
90%
|
91%
|
79%
|
84%
|
75%
|
73%
|
70%
|
Table 9
Does this house have problems with cracks or fissures in ceilings or walls?
|
|
Does this house have problems with cracks or fissures in ceilings or walls?
|
|
|
A/B
|
C+
|
C
|
C-
|
D+
|
D
|
E
|
|
1 = yes |
15%
|
20%
|
26%
|
31%
|
40%
|
49%
|
55%
|
|
0 = No |
85%
|
80%
|
74%
|
69%
|
60%
|
51%
|
45%
|
Pipelines
Pipes are a complex system of conduits that serve the purpose of transporting water
to homes. Each component plays a specific role in the system, and in most cases, problems
arise due to the wear of its materials or the presence of deteriorated facilities.
Table 10
Percentage of households that report having problems with water leaks in pipes
|
|
Does this house have problems with the water pipes or drainage inside the house?
|
|
|
A/B
|
C+
|
C
|
C-
|
D+
|
D
|
E
|
|
1 = yes |
7%
|
6%
|
5%
|
7%
|
8%
|
10%
|
10%
|
|
0 = No |
93%
|
94%
|
95%
|
93%
|
92%
|
90%
|
90%
|
In the case of pipe problems, this was not a serious problem for the homes under study,
at least in all socioeconomic levels, 90% stated that they did not have a problem
with the pipes inside their home.
Ground subsidence
The subsidences are generally caused by the construction of buildings in unsuitable
places. These can cause disasters as severe as those caused by earthquakes and floods,
putting the quality of life and integrity of the people who inhabit the house at risk.
Table 11
Does this dwelling have problems with rising or sinking of the floor?
|
|
Does this house have problems with rising or sinking of the floor?
|
|
|
A/B
|
C+
|
C
|
C-
|
D+
|
D
|
E
|
|
1 = yes |
5%
|
7%
|
8%
|
9%
|
14%
|
19%
|
24%
|
|
0 = No |
95%
|
93%
|
92%
|
91%
|
86%
|
81%
|
76%
|
In this matter of land subsidence, the most affected houses are those of levels D+,
D, and E, that is, homes in conditions of low class and poverty, as mentioned above,
homes in this socioeconomic range are characterized by being located on the urban
periphery, far from any center of activity, with little accessible to urban equipment
and poor quality soil.
Environmental problems outside the home
Among other problems that can affect the satisfaction and quality of life of people
who inhabit a home are those related to their immediate surroundings, particularly
negative externalities such as noise, problems with trash on the streets, theft, and
assaults.
Noise
Noise, often called noise pollution, is considered by the majority of the population
as a factor that mainly affects people’s quality of life. In particular, this is linked
to the affectation on hearing sensitivity, affecting the development of aspects such
as concentration, rest, and communication and even causing stress in people (Gidlöf-Gunnarsson and Öhrström, 2007; Kroesen et al, 2010; Firdaus, 2010; Merino et al, 2019).
Regarding whether homes have any kind of wall or window insulation to reduce excess
noise, we noticed that very few households have it. However, when contrasting with
the question of whether households in their district or neighborhood (locality) have
problems with excess noise from neighbors or the outside, households that reported
having that problem to a greater extent were found in the lower class and poverty.
Table 12
To reduce excess noise, does this dwelling have some type of insulation on the walls?
|
|
To reduce excess noise, does this house have some type of insulation in the walls?
|
|
|
A/B
|
C+
|
C-
|
C
|
D+
|
D
|
e
|
|
1 = yes |
5%
|
3%
|
1%
|
2%
|
1%
|
0%
|
0%
|
|
0 = No |
95%
|
97%
|
99%
|
98%
|
99%
|
100%
|
100%
|
Table 13
To reduce excess noise, does this dwelling have some type of window insulation?
|
|
To reduce excess noise, does this home have any type of window insulation?
|
|
|
A/B
|
C+
|
C
|
C-
|
D+
|
D
|
e
|
|
1 = yes |
5%
|
4%
|
3%
|
1%
|
0%
|
0%
|
0%
|
|
0 = No |
95%
|
96%
|
97%
|
99%
|
99%
|
100%
|
100%
|
Households that reported having some or a lot of noise problems caused by neighbors
were located at middle and low socioeconomic levels, while 72% of households in the
high socioeconomic level mentioned having little or no problems. This may reflect
a social reality where high socioeconomic levels tend to live in exclusive neighborhoods
where excess noise is not allowed or where large gatherings that can generate noise
and discomfort among neighbors are prohibited.
Table 14
Percentage of households that report having noise problems in their neighborhood
|
|
In your neighborhood (locality), how many problems do you have with excess noise from
neighbors or outside?
|
|
|
Many
|
Some
|
A few
|
None
|
|
A/B |
12%
|
16%
|
22%
|
50%
|
|
C+ |
16%
|
17%
|
22%
|
45%
|
|
C |
20%
|
18%
|
22%
|
40%
|
|
C- |
21%
|
19%
|
20%
|
40%
|
|
D+ |
22%
|
17%
|
21%
|
40%
|
|
D |
20%
|
16%
|
21%
|
43%
|
|
E |
20%
|
15%
|
22%
|
43%
|
Robberies
The effect of living in an insecure context has consequences in society such as decreased
life satisfaction and the erosion of social capital and happiness. In addition, the
perception of insecurity violates people’s quality of life, as they stop carrying
out daily activities such as going out at night, carrying cash, restricting minor
children from going out, not carrying debit or credit cards, taking taxis, visit relatives
or friends (Romero, 2014; Reid et al, 2020; Piroozfar et al, 2019), likewise, the perception of insecurity has negative effects on well-being, especially
negative subjective well-being (Charles-Leija et al, 2019; Janssen et al, 2021) because this type of well-being rises with the increase in the perception of insecurity.
In the case of analyzed households, regarding the question of whether in their locality
or neighborhood, they have robbery or assault problems, again the households in the
lower-class levels and a situation of poverty are the ones who experience this type
of problem. Analyzing more thoroughly, the places where these types of homes are located,
in many cases, are areas where the maintenance and lighting of public spaces (such
as parks or avenues) are absent, and therefore, there is a greater probability that
there is a crime and go unnoticed.
Table 15
Percentage of households that report having robbery problems in the neighborhood
|
|
In your neighborhood (locality), how many problems do you have with robberies or assaults?
|
|
|
Many
|
Some
|
A few
|
None
|
|
A/B |
13%
|
17%
|
19%
|
51%
|
|
C+ |
16%
|
17%
|
23%
|
44%
|
|
C |
17%
|
18%
|
23%
|
42%
|
|
C- |
19%
|
21%
|
22%
|
38%
|
|
D+ |
23%
|
19%
|
21%
|
37%
|
|
D |
23%
|
17%
|
21%
|
39%
|
|
E |
22%
|
17%
|
21%
|
40%
|
Trash
Waste exposure is a problem that affects human health, likewise, inadequate storage
or disposal of waste creates favorable environments for the reproduction of rodents
and insects (flies, cockroaches), many of which act as vectors in disease transmission.
In the case of the question: how many problems do you have with garbage thrown in
the streets? The socioeconomic levels that have this very marked problem are those
located in the lower middle class and poverty situation, generally, these population
groups do not have a regular home collection, and the waste produced is deposited
in the surroundings, which generates a deteriorated environment.
Table 16
In your neighborhood (locality), how many problems do you have with garbage thrown
on the streets?
|
|
In your neighborhood (locality), how many of a problem do you have with garbage thrown
in the streets?
|
|
|
Many
|
Some
|
A few
|
None
|
|
A/B
|
12%
|
14%
|
12%
|
63%
|
|
C+
|
15%
|
17%
|
20%
|
48%
|
|
C
|
18%
|
18%
|
21%
|
43%
|
|
C-
|
24%
|
19%
|
22%
|
35%
|
|
D+
|
31%
|
20%
|
21%
|
28%
|
|
D
|
31%
|
19%
|
22%
|
28%
|
|
E
|
32%
|
18%
|
23%
|
27%
|
Results of the econometric model
To carry out the statistical analysis, the RStudio (2020) programming language has been used in its latest version. The results estimation
of the Ordered Probit Model is presented in Table 17, in which it can be observed that the coefficients associated with the factors of
the immediate environment are statistically significant, and therefore they are variables
that do have an influence -according to the evidence - on the probabilities of housing
satisfaction. On the other hand, the coefficients associated with the internal variables
were statistically significant except for whether or not there was a laundry room.
Table 17
Estimation results: Ordered Probit Model
|
p6_8
|
coef.
|
Std. Err.
|
Z
|
P>z
|
[95% Conf.
|
Interval]
|
|
log_ing |
0.0645874***
|
0.01
|
6.15
|
0,000
|
0.044
|
0.085
|
|
p4_19_1 |
0.0062231***
|
0.0005
|
12.06
|
0,000
|
0.0052
|
0.0072
|
|
p4_21_1 |
0.0021663***
|
0.00009
|
21.72
|
0,000
|
0.0019
|
0.0023
|
|
Laundry |
-0.0050207
|
0.021
|
-0.24
|
0.814
|
-0.0467
|
0.036
|
|
water tank |
0.2238797***
|
0.016
|
13.63
|
0,000
|
0.191
|
0.256
|
|
dining room |
0.4219378***
|
0.018
|
23.17
|
0,000
|
0.386
|
0.457
|
|
Garden |
0.1137053***
|
0.016
|
7.09
|
0,000
|
0.082
|
0.145
|
|
Garage |
0.1615671***
|
0.016
|
9.59
|
0,000
|
0.128
|
0.194
|
|
Cracks |
‘-0.4315628***
|
0.017
|
-25.06
|
0,000
|
-0.465
|
-0.397
|
|
subsidence |
‘-0.4085419***
|
0.021
|
-18.78
|
0,000
|
-0.451
|
-0.365
|
|
Humidity |
‘-0.4425598***
|
0.016
|
-26.11
|
0,000
|
-0.475
|
-0.409
|
|
pipelines |
‘-0.4088982***
|
0.027
|
-15.04
|
0,000
|
-0.462
|
-0.355
|
|
Ramps |
‘-0.1208725***
|
0.015
|
-7.7
|
0,000
|
-0.151
|
-0.090
|
|
Noise |
´-0.2034674***
|
0.016
|
-12.38
|
0,000
|
-0.235
|
-0.171
|
|
Trash |
‘-0.1457108***
|
0.016
|
-8.96
|
0,000
|
-0.177
|
-0.113
|
|
robberies |
‘-0.1895659***
|
0.016
|
-11.76
|
0,000
|
-0.221
|
-0.157
|
|
/cut1 |
-5,304
|
0.115
|
|
|
-5,531
|
-5,076
|
|
/cut2 |
-4,769
|
0.106
|
|
|
-4,978
|
-4,561
|
|
/cut3 |
-4,225
|
0.1005
|
|
|
-4,422
|
-4,028
|
|
/cut4 |
-3,702
|
0.096
|
|
|
-3,892
|
-3,512
|
|
/cut5 |
-3,258
|
0.095
|
|
|
-3,444
|
-3,071
|
|
/cut6 |
-1.83
|
0.092
|
|
|
-2011
|
-1,649
|
|
/cut7 |
-1,348
|
0.092
|
|
|
-1,529
|
-1,167
|
|
/cut8 |
-0.559
|
0.092
|
|
|
-0.739
|
-0.378
|
|
/cut9 |
0.829
|
0.092
|
|
|
0.649
|
1,010
|
|
/cut10 |
1,602
|
0.092
|
|
|
1,421
|
1,782
|
The direction and magnitude in which these variables influence the probabilities of
mobility can be analyzed in greater detail in the context of the estimation of marginal
effects that are presented in the following subsection.
Estimation of marginal effects
As we have mentioned, an important part of this research consists of estimating the
marginal effects. To measure the impact of each explanatory variable on the probability
that a household is satisfied with their home. The results of the estimation of the
marginal effects are shown in Table 17.
The first thing we can notice in these results is that practically all the marginal
effects are statistically significant. Now, considering that analyzing the direction
and magnitude of these average marginal effects is very important to understand the
evidence against or in favor of some of the hypotheses proposed by the theoretical
review, we proceed to carry out this analysis in more detail.
-
Marginal effects of immediate environment variables: We can say that having problems with excessive noise from neighbors or the exterior
decreases the probability of satisfaction by 4.09 percentage points. On the other
hand, having problems with garbage thrown in the streets decreases satisfaction with
the housing by 2.9 percentage points.
-
Marginal effects of internal housing variables: It is stated that having a garden in the home increases the probability of satisfaction
by 2.28 percentage points, while the dining room does so by 8.4 percentage points.
Problems with humidity or water leakage in foundations, walls, or roofs, decrease
the probability of satisfaction by 8.2 percentage points, while cracks decrease by
8.6 percentage points and problems with water or sewer system inside the house by
8.2 percentage points.
Findings
The present investigation was the first econometric effort to measure residential
satisfaction, where each variable analyzed showed its particularities, however, to
expose some of the main findings in a very synthetic way, the following is mentioned:
The problem of excessive noise around the home decreases the probability of home satisfaction
by 4.09 percentage points, retaking the data, we find that this situation occurs particularly
with low-income homes, however, few homes reported having protection to inhibit noise
outside the house.
Table 18
Estimated marginal effects
|
Variable
|
dy / dx
|
Std. Err
|
Z
|
P>z
|
[95% Conf.
|
Interval]
|
|
log_ing
|
0.0130001***
|
0.002
|
6.15
|
0,000
|
0.008
|
0.017
|
|
age of house (p4_19_1)
|
0.0012526***
|
0.0001
|
12.05
|
0,000
|
0.001
|
0.0014
|
|
M2 (p4_21_1)
|
0.000436***
|
0.00002
|
21.68
|
0,000
|
0.0003
|
0.0004
|
|
Laundry
|
-0.0010106
|
0.0042
|
-0.24
|
0.814
|
-0.009
|
0.007
|
|
water tank
|
0.0450622***
|
0.003
|
13.64
|
0,000
|
0.038
|
0.051
|
|
dining room
|
0.0849271***
|
0.003
|
23.2
|
0,000
|
0.077
|
0.092
|
|
Garden
|
0.0228864***
|
0.003
|
7.09
|
0,000
|
0.016
|
0.029
|
|
Garage
|
0.03252***
|
0.003
|
9.59
|
0,000
|
0.025
|
0.039
|
|
Cracks
|
-0.0868644****
|
0.003
|
-25.03
|
0,000
|
-0.093
|
-0.08
|
|
Subsidence
|
-0.0822308***
|
0.004
|
-18.78
|
0,000
|
-0.090
|
-0.073
|
|
Humidity
|
-0.0890779***
|
0.003
|
-26.07
|
0,000
|
-0.095
|
-0.082
|
|
Pipelines
|
-0.0823025***
|
0.005
|
-15.03
|
0,000
|
-0.093
|
-0.071
|
|
Ramps
|
-0.0243291***
|
0.003
|
-7.7
|
0,000
|
-0.030
|
-0.018
|
|
Noise
|
-0.0409536***
|
0.003
|
-12.37
|
0,000
|
-0.047
|
-0.034
|
|
Trash
|
-0.0293285***
|
0.003
|
-8.96
|
0,000
|
-0.035
|
-0.022
|
|
Robberies
|
-0.0381556***
|
0.003
|
-11.75
|
0,000
|
-0.044
|
-0.0317
|
Having a garden at home increases satisfaction by 2.8 percentage points. Having a
garden provides a fresh atmosphere at home, as well as being an amenity, it allows
one to relax and reduce stress. This result is similar to what has been mentioned
by Ruiz (2012). The garden is an element that provides ecosystem services to homes and is a determinant
of comfort.
Having humidity problems decreases satisfaction by 8.2 percentage points, we consider
that the intensity of this impact may be because its consequences are more visible
in the home since it generates the appearance of germs and bacteria, it is also noticeable
on the walls.
The problem of subsidence in housing decreases the probability of satisfaction by
8.2 percentage points.
As income increases, the probability of satisfaction increases by 1.3 percentage points.
On the other hand, the variables of house antiquity and square meters did not have
a significant impact on the satisfaction of the dwelling.
These are some of the findings obtained, however, it should be noted that this research
only focuses on the internal factors of the home and its immediate environment, social
factors (related to households), and macro issues (social conditions and cultural,
political, local, national) are not contemplated.
Conclusions
This research tried to highlight some variables and relationships that should be considered
when analyzing satisfaction with housing. The contributions of this study also demonstrate
the conditions in which some of the households in Mexico live, particularly those
with lower incomes, which present a series of structural problems in their homes,
referring to them as inadequate housing, mainly due to lack of functionality, insecurity
of construction systems and materials.
The importance that housing represents as one of the country’s priority problems is
that some indicators of the sustainable development objectives depend on it, particularly
objective 3, which guarantees a healthy life and promote well-being for all at all
ages. For this purpose, homes with adequate facilities contribute directly to the
reduction of diseases and the physical and mental well-being of their occupants. Similarly,
it contributes to objective 11, which aims to make cities more inclusive, safe, and
resilient. Adequate housing helps ensure access for all people to suitable, safe,
and affordable housing and basic services and improves slums.
Finally, it is necessary to reflect that housing is much more than a simple built
space. In addition, it entails the intervention of many actors, among them, public
institutions of the federal, state, and municipal government: investors, developers,
builders, material suppliers, and associations. Actually, in Mexico, the challenge
is to guarantee decent and adequate housing and improve the quality of life of all
people. To achieve this, it is necessary: first, to measure the current needs and,
second, to promote public policy strategies in housing matters. All this, ensures
people-centered approach.
Likewise, strategies for the implementation of an Official Standard on habitability
in housing and cultural adaptation must be carried out. Taking into consideration
the particular needs of each territory and integrating environmental variables. Having
this Official Standard can help not only the country but also serve as an example
for other countries to implement actions on adequate housing, mainly in Latin American
countries where thousands of people live in poverty.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.