Introduction
In 2005, the United Nations estimated that, worldwide, there were 100 million homeless people, 1.6 billion people living in undignified housing conditions and about 15 million forcibly evicted each year (ESC-UN, 2019). On the one hand, in OECD countries, the number of homeless people amounts to 1.9 million (despite representing less than 1% of the population of these countries). On the other hand, the rate of people with housing instability varies between 2% and 25% of the population of these countries (ESC-UN, 2019). In this sense, developed countries face a series of risks associated with social and economic changes, both global and regional, with consequences that transform the environment at work, in the family and in daily life (Giddens, 2007). Homelessness is also a global problem, which affects people in different social and cultural contexts, both in developed and developing countries (Canberra Group, 2001). Regarding housing policies, although there is obviously no great agreement in the forms of action of European countries, we are witnessing a great diversity of ways of dealing with the same problem: a significant number of families cannot access the private housing market (Guerra, 2008) and considering that different housing policies reflect different political, social and economic situations (Santos, Teles and Serra, 2014). In view of the above, this investigation will study the citizen's «financial need situation», as one of the risks associated with the Local Housing Strategy (LHS), given that housing policies imply efforts by the legislator in order to recognize the right of access housing with decent conditions. This investigation presents the introduction in the first section, after which it will identify the methodology used. The third section develops the theoretical analysis by reviewing the literature underlying HLT. The fourth section presents the empirical analysis through an exploratory descriptive analysis focused on the citizen's «situation of financial need». The fifth presents a discussion on the issue of risk associated with HLT. In the sixth, the conclusions and limitations of this investigation are highlighted.
1. Literature revision
The LHS is an instrument that defines intervention in terms of housing policy, aiming to define the goals and objectives to be achieved during its period of validity, based on the participation of the community and its agents. Housing is one of the basic pillars in the life of every citizen and in the society in which they live. This theme is important for the quality of life of the same, in the fight against poverty, in the management of housing spaces and in the sustainability of the regions (Smeeding et al, 1993; Frick, Goebel Grabka, 2007).
In the analysis of international law, housing is considered one of the basic rights of the citizen, enshrined in Article 25(1) of the Universal Declaration of Human Rights: “every human being has the right to a standard of living capable of assuring him, and his family, health and well-being, including food, clothing, housing, medical care and necessary social services, and the right to security in the event of unemployment, illness, disability, widowhood, old age or other loss of livelihood in circumstances beyond their control” (UN, 2017).
The Charter of Fundamental Rights of the European Union reads: “in order to combat social exclusion and poverty, the European Union recognizes and respects the right to social and housing assistance, in order to guarantee a decent existence for all those who do not have sufficient resources, in accordance with the rules established by European Union law and national laws and practices” (EU, 2012).
Despite housing being a consecrated right, it is still not a reality for everyone, so the first debate of the European Parliament, in 2020, was on the problem of the 700,000 homeless people in Europe (PE, 2020). In recent years, the number of people in this situation in Europe has been increasing, with the exception of Finland, which recorded a 45% drop.
In the analysis of national law, housing is a fundamental right established in article 65 of the CRP: “Everyone has the right, for himself and his family, to adequate housing, in conditions of hygiene and comfort and that preserves the personal intimacy and family privacy” (AR, 1976). Yet there is a “growing inability of families and individuals to put a safe and affordable roof over their heads, which has a detrimental impact on our society and its ability to support equal opportunities for all citizens” (Gilliland, 2019).
From 2002 onwards, there was a strategic change in the housing policy with the promotion of rehabilitation and renting. In 2008, given the need for greater integration of central and local powers, the Local Housing Program was created (Xerez, Rodrigues, & Cardoso, 2018). In 2015, the National Housing Strategy (ENH) and the basic law on the right to housing were approved and the State's mandates were only approved in September 2019. The aforementioned Basic Housing Law, in paragraph 1 of article 2 of the Law n.º 83/2019 (AR, 2019)states that “everyone has the right to housing, for themselves and their family, regardless of ancestry or ethnic origin, sex, language, territory of origin, nationality, religion, belief, political or ideological convictions, education, economic status, gender, sexual orientation, age, disability or health condition”.
As a result, in Portugal, in the New Generation of Housing Policies, the Support Program for Access to Housing called the 1st Right (PCM, 2018a) emerged, which aims to guarantee the conditions of access to adequate housing for people living in unworthy and unworthy conditions. who are in a «situation of financial need», not allowing access to an adequate housing solution (MA, 2018). Thus, it is precisely the citizen's «financial need situation» that will be investigated. To this extent, HLT stakeholders should propose intervention models in the area of active citizenship, with high levels of participation and involvement of all, especially those potentially affected by the decisions taken by politicians, whether at national, regional or local level (Santos, Seabra, Jorge, & Costa, 2014).
2. Methods
The research methodology is primarily divided into a theoretical analysis, focusing on legislation and regulations applicable in Portugal and in the European Union regarding housing and HLT. Also, in accordance with Standard NP EN 31010 (IPQ, 2016) and NP EN 31000 (IPQ, 2018), in a risk assessment process that is often expressed as the combination of the consequences of a given event (including changing circumstances) and the respective probability of occurrence. Thus, this evaluation implies a process composed of the identification, analysis, and evaluation of the same that culminated in an empirical analysis based on public statistics and made available by different national (INE) and international entities (ESC-UN, Eurofound, EU, Eurostat) through the exploratory descriptive analysis method.
2. 1 Sample
The data collected through consultation with different national (INE and IHRU) and international (ESC-UN, Eurofound, EU, Eurostat) entities, in the period from 2017 to 2020, was conditioned by the public availability of the data collected.
2.2. Data collection
Data collection allowed the comparative analysis of the population at an international, national, and regional level (Beiras and Serra da Estrela region) and was developed from indicators such as: gross income, indicators of poverty and social exclusion, material deprivation, inequality economy, housing deprivation and support granted by the 1st Law Program (Graham & Grisard, 2019). To analyze the gross income declared by tax aggregate, for the years 2017 and 2018, the source was the Income Statistics at the local level based on information produced by the Ministry of Finance (Autoridade Tributária e Aduaneira), of the National Institute of Statistics. To study the indicators of poverty and social exclusion, material deprivation and economic inequality, for the years 2018 and 2019, the source was the Survey on Living Conditions and Income from the National Statistics Institute. To examine the indicators of material deprivation, economic inequality and housing deprivation, the source was the Survey on Living Conditions and Income, from the National Institute of Statistics and, also, the European Union's statistical services, Eurostat. For data on support granted by the 1st Law Program, the source was the Presentation of the 1st Law Program of the Institute for Housing and Urban Rehabilitation (IHRU, 2020).
2.3 Statistical Analysis
After data collection, descriptive statistical analyzes were carried out, with an exploratory character (Riley et al., 2000; Field, 2017; Yin, 2018). Data were processed in the statistical software IBM® SPSS® Statistics (IBM, 2017), version 25, and measures of central tendency were simulated. At the same time, statistical inferences were developed, using non-parametric tests, with a significance level of 0.05, as well as the Chi-Square statistic for the analysis of the association of nominal and ordinal variables, and the correlation coefficient Pearson method for measuring the degree of association between two quantitative variables that present themselves (Greene, 2017; Hair et al., 2018).
3. Results
Decree-Law n.º 37/2018, 4th of June (PCM, 2018a) created the program of the 1st Law, defined in subparagraph e) of article 4 what is meant by “situation of financial need”, that is, “situation of the person or housing unit that holds movable assets with a value of less than 5% of the limit established under the terms of paragraphs 4 and 5 of article 2 of Decree-Law No. 70/2010, of 16 June (MTSS, 2010), in its current wording, and whose average monthly income is less than four times the social support index (IAS)”. The IAS set for 2021 is €438.81, as it has not been updated compared to the previous year, in 2018 it was set at €428.90, while in 2017 it was €421.32 (MFTSS, 2020), having increased by only 4.1%. As mentioned above, for a household to be classified as “in a situation of financial need”, then its Average Monthly Income (AMR) must be less than four IAS, which amounts to €1,715.60.
The declared gross income and the RMM per aggregate, in Euro, in the year 2017 and in the year 2018. From the observation of Table 1 in 2017, the RMM, in Portugal, is lower (€1,474.17) to the value of the household classified in «situation of financial need» (€1,685.20). Likewise, in 2018, the RMM per aggregate was €1,522.08, below the reference value of four times the IAS, which corresponds to €1,715.60. The RMM in 2019 at the national level was €1,582.33, continuing to be below the four IAS line (€1,743.04).
It can also be seen that all municipalities in the Beiras and Serra da Estrela Region have values below those of Portugal, with the municipality with the lowest RMM per household being, in 2017, Mêda (€1,071.58) and in 2018 and 2019, Figueira de Castelo Rodrigo and the highest RMM is Guarda, with €1,518.58; €1,584.83 and €1,652.42, in 2017, 2018 and 2019 respectively.
Regions | Declared gross income per household | Average monthly income per household | Declared gross income per household | Average monthly income per household | Declared gross income per household | Average monthly income per household |
---|---|---|---|---|---|---|
(€) | 2017 | 2018 | 2019 | |||
Portugal | 17690 | 1477.17 | 18265 | 1522.08 | 18988 | 1582.33 |
Continental | 17726 | 1477.17 | 18304 | 1525.33 | 19026 | 1585.50 |
Center | 16562 | 1380.17 | 17130 | 1427.5 | 17866 | 1488.83 |
Beiras and Serra da Estrela | 14982 | 1248.5 | 15546 | 1295.5 | 16343 | 1361.92 |
Almeida | 14570 | 1214.17 | 15061 | 1255.08 | 15408 | 1284.00 |
Belmonte | 13522 | 1126.83 | 14052 | 1171 | 15137 | 1261.42 |
Celorico da Beira | 13564 | 1130.33 | 14032 | 1169.33 | 14723 | 1226.92 |
Covilhã | 15493 | 1291.08 | 16092 | 1341 | 17001 | 1416.75 |
Figueira do Castelo Rodrigo | 1985 | 1082.08 | 13322 | 1110.17 | 14025 | 1168.75 |
Fornos de Algodres | 13157 | 1096.42 | 13672 | 1139.33 | 14390 | 1199.17 |
Fundão | 14158 | 1179.83 | 14724 | 1227 | 15532 | 1294.33 |
Gouveia | 13596 | 1133 | 14122 | 1176.83 | 14850 | 1237.50 |
Guarda | 18223 | 1518.58 | 19018 | 1584.83 | 19829 | 1652.42 |
Manteigas | 13300 | 1108.33 | 13715 | 1142.92 | 14256 | 1188.00 |
Mêda | 12859 | 1071.58 | 13504 | 1125.33 | 14256 | 1188.00 |
Pinhel | 13173 | 1097.75 | 13447 | 1120.58 | 14150 | 1179.17 |
Sabugal | 13497 | 1124.75 | 13849 | 1154.08 | 14439 | 1203.25 |
Seia | 14211 | 1184.25 | 14613 | 1217.75 | 15329 | 1277.42 |
Trancoso | 13303 | 1108.58 | 13843 | 1153.58 | 14727 | 1227.25 |
The material deprivation rate and the severe material deprivation rate indicate the percentage of the population of Portugal with forced deprivation due to economic hardship in at least four, and at least three, of the following items, respectively: a) ability to ensure payment immediately of an unexpected expense and close to the monthly value of the poverty line (without resorting to a loan); b) ability to pay for one week of vacation, per year, away from home, bearing the expense of accommodation and travel for all members of the household; c) ability to timely pay rent, credit installments or out-of-pocket expenses of the principal residence, or other expenses unrelated to the principal residence; d) ability to have a meat or fish meal (or vegetarian equivalent) at least every 2 days; e) ability to keep the house adequately warm; f) ability to have a washing machine; g) ability to have color television; h) ability to have a landline or mobile phone; i) ability to own a car (passenger car or mixed) (INE, 2021a).
Table 2 presents the indicators of poverty or social exclusion and material deprivation for the years 2018, 2019 and 2020, in particular, the Resident population at risk of poverty or social exclusion, the Material deprivation rate, and the deprivation rate severe material
Regions | 1 | two | 3 | 1 | two | 3 | 1 | two | 3 |
---|---|---|---|---|---|---|---|---|---|
(%) | 2018 | 2019 | 2020 | ||||||
Portugal | 21.6 | 16.6 | 6.0 | 21.6 | 15.1 | 5.6 | 19.8 | 13.5 | 4.6 |
North | 22.8 | 17.7 | 6.4 | 23.2 | 16.1 | 6.7 | 22.0 | 14.4 | 4.6 |
Center | 23.0 | 15.0 | 4.9 | 20.4 | 13.7 | 4.1 | 19.4 | 11.6 | 3.4 |
AM Lisbon | 16.7 | 15.3 | 5.8 | 17.8 | 13.2 | 4.6 | 14.6 | 11.2 | 4.1 |
Alentejo | 21.1 | 13.3 | 4.5 | 22.0 | 12.9 | 4.6 | 20.2 | 12.5 | 4.8 |
Algarve | 22.9 | 18.1 | 6.6 | 23.2 | 17.6 | 8.1 | 22.3 | 19.5 | 6.5 |
AR Azores | 36.4 | 28.3 | 12.0 | 36.7 | 28.0 | 13.1 | 32.4 | 23.4 | 9.6 |
RA Madeira | 31.9 | 25.5 | 9.4 | 32.2 | 23.3 | 7.3 | 32.9 | 27.7 | 11.0 |
Caption: 1-Resident population at risk of poverty or social exclusion; 2- Material deprivation rate; 3- Severe material deprivation rate. Source : INE (2019a, 2020a, 2021b)
As for the proportion of the population whose equivalent disposable income is below the poverty line, in 2018, in Portugal, it was 21.6%, with only the Lisbon Metropolitan Area (AMLisboa) below the national average (16.7% ) and Alentejo (21.1%) (INE, 2019a). In 2019 it was 17.2%, with only AMLisboa (16.7%) registering a lower percentage (INE, 2020a). In 2020, the at-risk-of-poverty rate in Portugal was 19.8%, with the Centro region (19.4%) and AMLisboa (14.6%) registering a lower percentage than the national one. The Autonomous Regions of the Azores and Madeira have a high rate of resident population at risk of poverty or social exclusion compared to the national rate in the three years under analysis.
Thus, it is clear that the LHS's municipal and geographical differentiation presents great national disparities, and the Autonomous Regions of the Azores and Madeira need the support of the responsible entities to guarantee the minimum for each citizen. And it is in the Lisbon Region that it presents better national results, and the effort that must be directed to the HLT is still worrying. Table 3 shows the statistics of central tendency and dispersion of indicators of poverty or social exclusion and material deprivation, in the period from 2018 to 2020.
Regions | Resident population at risk of poverty or social exclusion | material deprivation rate | Severe material deprivation rate | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
(%) | M | PD | Max | Min | THE | Ç | Me | PD | Max | Min | THE | Ç | Me | PD | Max | Min | THE | Ç |
Portugal | 21.0 | 1.0 | 21.6 | 19.8 | -1.7 | 3.8 | 15.9 | 1.1 | 16.6 | 15.1 | -0.1 | 3.4 | 5.4 | 0.7 | 6.0 | 4.6 | -1.2 | 2.6 |
North | 22.7 | 0.6 | 23.2 | 22.0 | -0.9 | 4.0 | 16.9 | 1.1 | 17.7 | 16.1 | -0.1 | 3.4 | 5.9 | 1.1 | 6.7 | 4.6 | -1.6 | 1.2 |
Center | 20.9 | 1.9 | 23.0 | 19.4 | 1.2 | 3.6 | 14.4 | 0.9 | 15.0 | 13.7 | -0.7 | 3.0 | 4.1 | 0.8 | 4.9 | 3.4 | 0.2 | 1.7 |
AM Lisbon | 16.4 | 1.6 | 17.8 | 14.6 | -0.9 | 3.4 | 14.3 | 1.5 | 15.3 | 13.2 | 0.1 | 2.7 | 4.8 | 0.9 | 5.8 | 4.1 | 1.1 | 2.2 |
Alentejo | 21.1 | 0.9 | 22.0 | 20.2 | 0.0 | 3.9 | 13.1 | 0.3 | 13.3 | 11.2 | 0.0 | 3.9 | 4.6 | 0.2 | 4.8 | 4.5 | 0.9 | 3.9 |
Algarve | 22.8 | 0.5 | 23.2 | 22.3 | -0.9 | 4.0 | 17.9 | 0.4 | 18.1 | 17.6 | 1.2 | 3.8 | 7.1 | 0.9 | 8.1 | 6.5 | 1.7 | 3.1 |
AR Azores | 35.2 | 2.4 | 36.7 | 32.4 | -1.7 | 3.7 | 28.2 | 0.2 | 28.3 | 28.0 | -1.7 | 3.3 | 11.6 | 1.8 | 13.1 | 9.6 | -1.0 | 2.5 |
RA Madeira | 32.3 | 0.5 | 32.9 | 31.9 | 1.1 | 4.0 | 24.4 | 1.6 | 25.5 | 23.3 | 0.0 | 3.6 | 9.2 | 1.9 | 11.0 | 7.3 | -0.4 | 1.7 |
Legend: M= average; SD= standard deviation; Max= maximum, Min= minimum; A= asymmetry; C = kurtosis. Source : Own elaboration.
Table 3 presents the descriptive statistics, of central tendency and dispersion, of the indicator “Resident population at risk of poverty or social exclusion”. From the sample, it is observed that the maximum (36.7%) is reached in the Autonomous Region of the Azores, in 2019, having improved the situation, and the minimum (14.6%) is achieved in the Lisbon Metropolitan Region, in year 2020, being the best indicator of the period under analysis. Undoubtedly, there is a very high national average of 21.0%, which is why the dispersion that goes from 2.4% in the Autonomous Region of the Azores to 0.5% in the Autonomous Region of the Algarve and Madeira, in proportions opposite.
In the indicator “Rate of material deprivation”, the sample shows a maximum (28.3%) is reached in the Autonomous Region of the Azores, in 2018, having improved the situation, and the minimum (11.2%) is achieved in the Region Metropolitana de Lisboa, in 2020, being the best indicator of the period under analysis. The national average is high at 15.9%, which is why the dispersion ranges from 1.6% in the Autonomous Region of Madeira to 0.3% in the Alentejo Region, in opposite proportions.
Finally, in the indicator “Rate of severe material deprivation” it is observed that the sample presents a maximum (13.1%) is reached in the Autonomous Region of the Azores, in the year 2018, having improved the situation, and the minimum (3, 4%) is achieved in the Central Region, in 2020, being the best indicator of the period under analysis. The national average is high (5.4%) and by this is understood the dispersion ranging from 1.9% in the Autonomous Region of Madeira to 0.2% in the Alentejo Region, in opposite proportions.
In article 5 of Decree-Law no. adequate housing, residing permanently, namely, in situations of: a) Precariousness; b) Unhealthy and insecurity; c) Overcrowding, when, based on the relationship between the composition of the household and the number of rooms in the dwelling, this constitutes an insufficient dwelling space, due to the lack of two or more rooms, in terms of the concept of overcrowded dwelling space used by the Instituto Nacional de Statistics, IP (INE, IP); d) Inadequacy” (PCM, 2018a).
Table 4 presents the housing overcrowding rate which corresponds to the proportion of the population living in housing where the number of habitable rooms (≥4 m 2 ) is insufficient for the number and demographic profile of household members. Thus, it is still considered that an individual lives in conditions of overcrowding in the dwelling if it does not have a minimum number of rooms, which allows the household: one room for the household; one division for each couple; one division for each individual aged 18 and over; a split for two individuals of the same sex between the ages of 12 and 17; a division for each individual of different sex between 12 and 17 years old; a split for two individuals under the age of 12.
Regions | 1 | two | 3 | 1 | two | 3 | 1 | two | 3 |
---|---|---|---|---|---|---|---|---|---|
(%) | 2018 | 2019 | 2020 | ||||||
Portugal | 9.6 | 4.1 | 5.7 | 9.5 | 4.1 | 5.7 | 9.0 | 3.9 | 4.1 |
North | 9.2 | 3.6 | 5.1 | 8.3 | 3 | 4.6 | 8.9 | 3.5 | 4.0 |
Center | 4.8 | 1.7 | 5.4 | 5.4 | 2.3 | 4.4 | 4.8 | 2.5 | 3.6 |
AM Lisbon | 12.9 | 5.8 | 6.2 | 12.9 | 6.4 | 7.7 | 11.6 | 5.1 | 4.5 |
Alentejo | 7.6 | 3.3 | 5.5 | 7.8 | 2.3 | 5.4 | 6.8 | 2.2 | 3.1 |
Algarve | 16.5 | 8.1 | 9.2 | 17.8 | 7.2 | 8.2 | 16.2 | 6.4 | 5.2 |
AR Azores | 17.5 | 9.2 | 6.4 | 15.7 | 8.7 | 7.3 | 14.0 | 7.4 | 4.2 |
RA Madeira | 9.0 | 5.7 | 5.9 | 8.3 | 4.5 | 6.5 | 8.2 | 5.2 | 4.4 |
Caption: 1- Housing overcrowding rate; 2- Severe deprivation rate of housing conditions; 3- Overhead rate of housing expenses. Source: (INE, 2019b, 2020b)
Table 4 shows that the housing overcrowding rate in Portugal, in 2020, was 9%, with values higher than the national value corresponding to the Algarve (16.2%) and the Autonomous Region of the Azores (14, 0%). The Center Region had a rate of 4.8% in 2018 and recorded an increase in the following year (+0.6 pp), returning to the rate of 4.8% in 2020, as well as the Alentejo and Algarve regions that registered a small increase in 2019, but in 2020 the rate decreased.
Table 4 includes the severe deprivation of housing conditions related to the combination of an overcrowded housing and the existence of at least one of four problems: lack of installation of a bath (or shower) or complete toilet inside the housing, transfers of water or rotting windows/floors or insufficient natural lighting on a sunny day. The scenario is repeated with the Autonomous Region of the Azores and the Algarve being the most worrying regions in this indicator.
the housing expenditure burden rate which reflects the proportion of the population living in households whose housing expenditures (after related social transfers) represent 40.0% or more of disposable income. The proportion of the population in overload of housing expenditure in Portugal from 2018 to 2019 remained at 5.7%, in 2020 it decreased (-0.6 pp), with a decrease in the rate recorded from 2018 to 2020.
4. Discussion
The first discussion focuses on the risk associated with the assessment of poor housing conditions, which is one of the main factors preventing Europeans from enjoying an acceptable standard of living (EU, 2018). At the same time, the condition of access to decent housing can present other risks, such as: lack of employment or precarious employment, low income earned by the citizen, unforeseen circumstances, aging, domestic violence, poverty, and social exclusion.
The second discussion focuses on the risk associated with the articulation between the New Generation of Housing Policies and the instruments that aim to respond to the needs of the most vulnerable groups, despite the mission being: “to guarantee everyone's access to adequate housing, understood in the broad sense of habitat and people-oriented.” (PCM, 2018b). However, there are requirements for scrutiny of the use of public money, so there are very strict rules to validate the support to be granted to the most vulnerable groups.
The third discussion focuses on the risk associated with housing itself, because the construction sector is one of the most relevant economic activities for the Portuguese economy and for the State Budget. Undoubtedly, these housing policies aim to regulate the real estate market, the rehabilitation market and promote social housing policies, as a pillar for the well-being of citizens. This policy justifies that housing is one of the twelve priorities of the Urban Agenda of the European Union, as stated in the 2016 Amsterdam Pact (EC, 2016), whose objectives are the basis of affordable, good quality and comfortable social housing. thermal (Housing Europe, 2015).
The fourth discussion focuses on the risk associated with the paradigm shift in housing policies in Portugal, which advocate a reorientation of housing policy from the “house” objective to the “ access to housing ” objective, which aims to create conditions that facilitate the access of families to housing, as ease of access in terms of price, location, quality, comfort, safety, accessibility, typology, form of occupation, mobility and the surrounding environment. Although for many decades, these policies consisted of allowing families to buy a house with access to credit facilities, nowadays they intend to adjust the legal framework to the new economic, social, and demographic realities, through the promotion of urban rehabilitation, housing lease and accommodation qualification (PCM, 2015).
Conclusion
The risk management associated with the LHS evidence the best practices developed at the municipal level in Portugal, often applied in strict accordance with the law, regulations, and standards, but, of course, they demonstrate that the interested parties promote true strategies of social responsibility, indisputably recognized as crucial to promoting economic success, social innovation, well-being and quality of life for citizens.
However, Portugal has a long way to go when it comes to housing, since it is an essential pillar for society and for the improvement of well-being and health (Eurofound, 2016). Thus, this research confirms that risks inherent to HLT, which the citizen faces to enjoy decent housing, are especially justified in the indicators of the “resident population at risk of poverty or social exclusion”, in the “rate of material deprivation” and the “rate of severe material deprivation”. The difference between the regions is still confirmed, namely in the indicators that present a very similar trend between them, demonstrating that Portugal fights against strong regional asymmetries (between the Metropolitan Region of Lisbon and the Autonomous Region of the Azores, as opposites), which lead to the citizen living within the limits of the severe material deprivation rate, so the defense of housing with decent conditions defended by the Constitution of the Portuguese Republic proves to be fundamental for a life that is sustainable for Portuguese society as a whole.
Undoubtedly, risk is defined as a combination of the probability of an event and its consequences, recognizing that it has two aspects, not only the negative, but also the positive. Thus, risk management is not just a topic for companies or public organizations, but also for any short or long-term activity or strategy, considering its context and its various stakeholders. However, housing policies must be thought of from a risk management perspective and, more specifically, the LHS must be developed taking into account the inherent risks, such as inequalities in access, market volatility, the aging of the housing stock, among others.
Fundamentally, the research promoted the need to involve citizens, companies, entities, and politicians immersed in more sophisticated and comprehensive collaboration and cooperation strategies. Although, not forgetting the central question of this research, the management of risks associated with the local housing strategy, which must implement true strategies of social responsibility, undoubtedly recognized as crucial to promote the quality of life of citizens, in order to allow their access to housing with decent conditions.
The limitation of this investigation is justified in the access to household income data, which is conditioned to the information system of the Tax Authority, which at the time of this investigation, only released the year 2017, which is the latest available. However, the objective of disclosing the risks that make it possible to mitigate the application of the Local Housing Strategy through citizens' access to housing with decent conditions overcomes all the difficulties felt in the process of collecting and processing data.
Given the profound changes that society is facing, in the present and in the future, it is expected that the local housing strategy will gain much relevance for citizens who need housing with decent conditions. Thus, in this sense, future research will be consolidated in this area with greater data robustness, as well as a comparative analysis of case studies in each of the 308 municipalities (Yin, 2018).