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Research Article

Exploring subjective well being in a developing country: Socio economic influence in Ecuador before and after the 2008 constitutional reform

[version 1; peer review: awaiting peer review]
W Alejandro Pacheco-Jaramillo
https://orcid.org/0000-0002-4208-5546
1, Riyana Miranti2, Robert Tanton3
W Alejandro Pacheco-Jaramillo
https://orcid.org/0000-0002-4208-5546
1, Riyana Miranti2, Robert Tanton3
PUBLISHED 16 Jan 2025
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Abstract

Background

This study investigates the impact of the 2008 constitutional change on Ecuadorians´ life satisfaction (developing country), based on the Sumak-Kawsay or “The good way of living” philosophy, with a particular focus on caring of people and mingas (community participation).

Methods

Through a repeated cross-sectional analysis of national survey data, this study compares the periods before (2007) and after (2014) the implementation of the 2008 constitution to examine how caring behaviors and mingas (community work) influence life satisfaction, using an ordinal logistic regression model to assess the role of this reform in shaping these effects.

Results

The findings reveal significant improvements in life satisfaction following the 2008’ reform, especially in the Eastern region, where community activities are prevalent, and poverty is most concentrated. These activities, including mingas, showed a positive association with an increase in life satisfaction, underscoring the role of public policies in improving public well-being.

Conclusion

This approach offers innovative empirical evidence on how social public policies that promote prosocial behaviors, such as solidarity and community participation, can create an environment encouraging to greater life satisfaction, particularly in less developed regions. It also underscores how social investment aimed at improving wealth distribution can positively influence collaborative behaviors.

Keywords

Life satisfaction, prosocial behaviour, subjective wellbeing, 2008 policy, mingas, Economics, Well-being, Poverty, Macroeconomic policy, Development

Corresponding author: W Alejandro Pacheco-Jaramillo
Competing interests: No competing interests were disclosed.
Grant information: The author(s) declared that no grants were involved in supporting this work.
Copyright:  © 2025 Pacheco-Jaramillo WA et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to cite: Pacheco-Jaramillo WA, Miranti R and Tanton R. Exploring subjective well being in a developing country: Socio economic influence in Ecuador before and after the 2008 constitutional reform [version 1; peer review: awaiting peer review]. F1000Research 2025, 14:95 (https://doi.org/10.12688/f1000research.159049.1) First published: 16 Jan 2025, 14:95 (https://doi.org/10.12688/f1000research.159049.1) Latest published: 16 Jan 2025, 14:95 (https://doi.org/10.12688/f1000research.159049.1)

1. Introduction

In this study, we undertake an exploration of the intricate relationship between prosocial activities and life satisfaction, examining the pivotal role played by policy, specifically focusing on the 2008 Ecuadorian Constitution. Our investigation commences with a thorough literature review, which underlines the consistent positive correlation between prosocial behaviours, such as mingas (participation in community work), and heightened life satisfaction. Additionally, policy changes have been shown to significantly influence individual and societal well-being, though the extent of their impact varies with the nature of the policies.

We use both ordinal logit regression and repetitive cross-section analysis, as well as the incorporation of regional fixed effects and a time dummy variable to enhance our understanding of temporal and regional dynamics. The study follows a structured model-building approach with a keen focus on investigating interactions between regional disparities and the post-2008 policy period regarding prosocial activities.

After this, we present our findings, discussing the impact of prosocial activities and the 2008 Ecuadorian Constitution on life satisfaction, providing valuable insights into their complex interactions. Acknowledging the importance of data limitations, we address the issue of income measurement consistency, which was not included in the analysis. Lastly, we conclude by summarizing our results and drawing policy implications, emphasizing the broader significance of understanding how policy changes and prosocial activities intersect to influence life satisfaction in Ecuador, while also suggesting directions for future research in the realm of policy, prosocial activities, and wellbeing.

The effects of prosocial behaviour on subjective wellbeing and the effects of government policy that may have an impact on people’s subjective wellbeing. This study is crucial in exploring the complex social behaviour underpinning collective visions in a Latin American context, drawing lessons from the Ecuadorian experience. Ecuador changed its constitution and applied social and equity policies based on the Sumak-Kawsay, “The good way of living”. The application of a new constitution had economic, social, and political impacts. These 2008 policies focused on reducing poverty and income inequality. National poverty reduced significantly, from 36.70% (2007) to 22.50% (2014), and extreme poverty fell from 16.5% (2007) to 7.7% (2014). Also, income inequality (as measured by the Gini coefficient index) fell from 0.54 (2007) to 0.45 (2014). It is important to see the changes in the socio-economic macro environment (extraordinary growth in GDP Gross Domestic Product in the two periods), however, the discussions about GDP are not part of this research.

Following the 2008 Constitution, there was an increase in public expenditure by the government on social protection, health and education to cover social services beyond the main cities (Ordóñez et al., 2015). Also, there was a reduction in the gaps related to other inequalities, such as gender, in terms of access to education and employment.

Policies that aim to improve institutional conditions improve life satisfaction. For instance, the different levels of individual happiness in the Centre and Eastern Europe are mainly determined by institutional factors such as public spending, corruption and decentralization (Rodríguez-Pose & Maslauskaite, 2011). People tend to be happiest when they are in good health, earn more, are better educated, married, and employed (Kahneman & Deaton, 2010). Therefore, as in the European case, in Ecuador, macroeconomic factors and adequate policies increase social investment and improve life satisfaction.

As part of the analysis, the study also takes into account regional differences in the patterns of wellbeing and prosocial activities. This was important because the Ecuadorian identity has been modelled by the geography and economic circumstances of the Coast, the Central and the Eastern regions, where the Eastern regions have been the last to be developed. This region has a higher concentration of poverty and indigenous people.

Ecuador was chosen as the focus of this research since its 2008 Constitution has been debated by many authors (Cubillo-Guevara & Hidalgo-Capitán, 2015; Fernández et al., 2014; Lalander, 2016; Martínez Godoy, 2015; Ordóñez et al., 2015; Peñafiel et al., 2017; Radcliffe, 2012) for its controversial statements, which differ from neoliberal thought (Friedman, 1988), and instead focus on a cooperative economy where the human being prevails over financial capital and which provides rights to nature.

Existing research consistently demonstrates a robust connection between prosocial activities and life satisfaction. Acts of kindness, such as volunteering and charitable giving, are linked to higher levels of subjective wellbeing (Dunn et al., 2008; Dunn et al., 2014). In addition to the study by Dunn et al. (2008) on the relationship between charitable giving and happiness, other studies have established the positive effects of volunteering and community involvement on life satisfaction. For example, research by Helliwell and Putnam (2004); Helliwell et al. (2017a, b) demonstrated that social capital and community engagement significantly contribute to individual well-being. By expanding the literature review to include these studies, the argument that prosocial activities enhance life satisfaction will be better supported. While the precise impact of this policy change on life satisfaction remains underexplored in the literature, studies in diverse contexts have shown that progressive policies that bolster social welfare and equality can positively influence life satisfaction (Helliwell et al., 2017a).

Income is a well-documented determinant of life satisfaction, with higher incomes generally associated with greater well-being (Diener, 2012). Recognizing the role of these control variables is pivotal in deciphering the nuanced relationships among prosocial activities, policy changes, and life satisfaction.

This study employs an ordinal logit regression and repetitive cross-section analysis, in line with established practices in the study of subjective wellbeing. This methodology allows for the exploration of ordinal dependent variables and temporal shifts (Helliwell et al., 2017a). The use of a stepwise model-building approach, along with the examination of regional and policy effects, aligns with prevailing research methods in this domain.

Previous studies have demonstrated that policy changes can exert considerable impacts on life satisfaction. Thus, understanding the interaction between the 2008 Ecuadorian Constitution and prosocial activities in shaping subjective well-being is not only pertinent in the Ecuadorian context but contributes significantly to our broader understanding of how policies and prosocial behaviour collectively affect life satisfaction.

The 2008 Ecuadorian Constitution introduced a series of significant changes, such as the recognition of new social rights and the expansion of social spending, particularly in health, education, and social protection. These reforms were part of a broader framework of Sumak Kawsay, or “Good Living,” which emphasizes community wellbeing and social solidarity. These policy changes likely encouraged prosocial behaviors like community work and caring for others by fostering a culture of cooperation and collective responsibility. Prosocial behavior in this study, defined as community work (mingas) and caregiving activities, is acknowledged for its positive impact on community wellbeing. However, to ensure a more comprehensive understanding, the study incorporates an exploration of the potential challenges associated with unpaid care work, particularly for women. By examining both the positive and potentially negative effects of such responsibilities on life satisfaction, the analysis provides a more nuanced view that addresses the diverse experiences of those engaged in prosocial activities.

2. Data and methodology

2.1 Data source

This paper leverages Ecuadorian national data from the National Survey of Employment, Unemployment, and Underemployment (ENEMDU, 2007) conducted before the 2008 Constitution and the Ecuadorian National Survey of Life Conditions (ECV, 2014) conducted after the 2008 Constitution to employ a comparative analysis using data from 2007 and 2014 to examine the impact of the 2008 policy change. This comprehensive approach sheds light on how the 2008 Constitution and prosocial behaviour influence the well-being of Ecuadorians.

In this study, the role of the new 2008 Constitution in Ecuador, its interplay with prosocial values and its association with subjective wellbeing is investigated. Two datasets are combined into a pooled dataset. An ordinal logit regression analysis, and a repetitive cross-section study with the same set of variables for 2007 and 2014 are used.

The surveys used in this study were conducted by national statistical agencies, which adhered to ethical standards, including informed consent from participants. Although this study uses secondary data, it is crucial to acknowledge the ethical implications of using survey data and confirm that respondents were informed about the purpose of the surveys and their rights as participants. This ensures the study’s adherence to ethical research practices.

2.2 Structure of the data

The dependent variable is life satisfaction. Prosocial activities, and other controlled variables are included as independent variables. As this paper examines the role of the 2008 policy (the 2008 Ecuadorian Constitution) and how its interaction with prosocial values affects subjective wellbeing in Ecuador, the 2008 policy is included as an independent variable. The ‘After 2008 policy’ dummy variable was created and served as a variable that divides the period between before and after the implementation of the 2008 policy as the observation years refer to 2007 and 2014. As it is challenging to find a variable that represents the 2008 policy directly, this dummy variable indirectly includes the impact of the 2008 policy. This dummy has a value of 0 which refers to the period before the 2008 policy (for observations in 2007); the dummy variable “after the 2008 policy” takes a value of 1 which refers to the period after the implementation of the 2008 policy (for observations in 2014). 1 Therefore, the coefficient for this variable will indirectly show the potential impact of the period after the implementation of the 2008 Constitution. However, the limitation of having a year dummy is also noted as a proxy, as this does not only include a policy variable but also includes other omitted variables2.

The estimation also controls for regional differences (by including regional fixed effects) and includes a time dummy variable. The analysis is structured regionally, aligning with Ecuador’s historical and geographic intricacies that have significantly shaped its identity. The Coast, exemplified by Guayaquil, has been a longstanding agricultural hub and an agricultural exporter. In contrast, the Central region, home to the capital city, Quito, plays a pivotal role as a hub for public services and a major contributor to the nation’s tax revenue. Ecuador’s primary export, oil, has held economic prominence since the 1970s. Lastly, the Eastern region, encompassing the Amazon area, represents the nation’s latest development phase, characterized by a higher concentration of indigenous populations and elevated poverty levels (Traverso Yépez, 1998).

The estimation strategy follows a stepwise a full model with interactions between regions and after the 2008 policy against prosocial activities will be tested to identify the role of regional and 2008 policy effects on subjective wellbeing. Finally, the conclusion of this study will be presented.

The comparable available variables in 2007 and 2014 are tested in the regression model. After the treatment of data with statistical software (STATA3), both years are evaluated with the same set of variables, as indicated in Table 1.

Table 1. Variables included in the models.

Type of variableVariables Name of the variable in the regression
Dependent variableLife satisfactionLifeSatisf
Independent variablesProsocial activitiesMingas (hours/week)MingaCAT
Caring for people (hours/week)CaringCAT
Demographic variables4AgeAgeCAT
Tertiary educationEdu_Dumm
GenderFemale
EthnicityIndigenous
PovertyPoor_Dumm
Marital StatusMarried_Lawunion
RegionsRegionsCAT
Urban/rural areasRural_Dumm
Policy variableAfter the 2008 ConstitutionAfter Constitution
InteractionsRegions in mingasRegions#MingasCAT
Regions in caring for peopleRegions#CaringCAT
Policy in mingasConstitution#MingasCAT
Policy in caring for peopleConstitution#CaringCAT

For the classification used in the repetitive cross-section analysis in this study (2007–2014), the prosocial activities use the 2014 classifications as the base. To classify the categories, the mean hours per week for each prosocial activity was used as a reference. Thus, the ranges of mingas in three ordered categories: 0 hours per week, 1–6 hours per week, and 7 or more hours per week are used. Also, the categories of caring for people are expressed in 0 hours per week, 1–7 hours per week, and 8 or more hours per week.

We also examine whether the pattern in the relationship between age and life satisfaction would differ from the findings noted in the literature review, with previous research finding that, in Ecuador, older ages are associated with less life satisfaction (Stukas et al., 2015).

The age has been classified into four classifications: 13–31, 32–48, 49–64 and 65 and older5. These intervals were determined by the mean of age (48.61) and based on two standard deviations below and one standard deviation above the mean (see Table 2). Nevertheless, as the minimum age is 13, the 13–31 category is used as the base for the age analysis in the econometric models.

Table 2. Intervals and ranges for age.

Age group
Std Dev16.391
1 Std Dev +65.00265+
Mean48.61149-64
1 Std Dev -32.21932-48
2 Std Dev -15.82813-31

In terms of tertiary education, a dummy variable has been created to classify the of households who have undertaken university post-school studies and those who do not. In the same way, dummy variables were created for gender (male is the base), ethnicity (non-indigenous is the base) and poverty (non-poor is the base).6 Marital status has been classified into three categories: married or de facto union (base); divorced, separated, or widowed; and single. At the regional level, the three regions in the models use the Eastern region as the base. For the area dummy variable, the rural area is the base.

The study’s sample, while focused on heads of households, provides valuable insights but may reflect a demographic skew due to the overrepresentation of older individuals and the underrepresentation of married women. To mitigate the potential biases introduced by this sample composition, the analysis can be supplemented with weighted adjustments or sensitivity checks that better account for the broader population’s age and gender distribution.

2.3 Descriptive statistics

Within the three categories of life satisfaction, most of the population (65.3%) are in the category “satisfied” when practising mingas between 1 and 6 hours per week, and 34.7% are in the “satisfied” category undertaking mingas for 7 hours or more per week (see Table 4).

Mingas and caring for people do not represent a value greater than 38% of the total sample, and mingas represents only 8%. Table 3 shows that the Eastern region practices more mingas of at least one hour a week than the other regions (13.6% of the population, compared with 10.2% for the Central region and only 2.7% for the Coast region), and compared to the entire sample (see Table 5). This finding is linked to the higher percentage of indigenous people (11.6% of the population) who are concentrated in the Eastern region and practice mingas. There is a higher concentration of poverty in the Eastern region: 49.9% of the population in the Eastern region, 37% in the Central region and 44.9% in the Coast region considered themselves to be poor (see Tables 3 and 4). Poverty is higher in the Eastern region.

Table 3. Characteristics of the pooled sample.

Data 2007, 2014
Characteristics of the sample%MeanMedianRange
VariableN(SD)
Total data 47,894
Life satisfaction
  Unsatisfied11,42923.9
  Satisfied25,26252.9
  Very satisfied11,10923.2
Prosocial activities (hours per week)
 Total mingas
  0 h/w39,82092.1
  1–6 h/w2,2395.2
  7+ h/w1,1952.8
 Total caring for people
  0 h/w26,93770.1
  1–7 h/w8,10521.1
  8+ h/w3,3918.8
Demographic variables
 Age48.6 (16.4)1399
  Age group 13–31 Y (base)7,66716.0
  Age group 32–48 Y18,00937.6
  Age group 49–64 Y13,12327.4
  Age group 65 Y+9,10419.0
 Education level (years)5.9 (2.4)111
  Non-tertiary education (base)33,44569.8
  Tertiary education (university & superior institute)14,45830.2
 Gender
  Male (base)736,66376.5
  Female11,24023.5
 Ethnic group
  Indigenous5,53711.6
  Non-indigenous (base)42,36688.4
 Poverty perception8
  Poor19,62341.3
 Non-poor (base)27,84858.7
 Marital status
  Married or de facto union (base)33,21169.3
  Divorced, separated or widowed10,60922.2
  Single4,0838.5
 Regions
  Coast + GP18,15137.9
  Central24,44551.0
  Eastern (base)5,30711.1
 Area
  Urban25,82853.9
  Rural (base)22,07546.1
 After the 2008 policy
  Before constitution (base)18,93339.5
  After constitution28,97060.5

Table 4. Life satisfaction and mingas combined.

Life satisfaction categories
MingasUnsatisfiedSatisfiedVery satisfied Total
1–6 hours per week6231,1284852,236
%62.6165.2869.0965.28
7 or more hours per week3726002171,189
%37.3934.7230.9134.72
Total9951,7287023,425

Around 69.3% of Ecuadorians are married or in a de facto union; these percentages differ slightly by region, with 74.1% in the Eastern region, 69.5% in the Central region and 67.7% in the Coast region married or in a de facto union (see Tables 3 and 4). In Ecuador, 30.7% of the population has tertiary education of at least one year or more. Examining this 30.7% by region, the Eastern region has less participation in tertiary education (13.9%), followed by the Coast (37.2%) and the Central region (48.9%) (see Table 5). Finally, 53.6% of the population in the sample is less than 48 years old (see Table 3).

Table 5. Mingas, poverty, marital status and education at a regional level.

Eastern%Central%Coast%Total %
Mingas
 Mingas 0 h/w4,40386.519,91589.915,50296.939,82092.1
 Mingas 1–6 h/w50710.01,2995.94332.72,2395.2
 7+ h/w1813.69484.3660.41,1952.8
Poverty
 Non-Poor 2,68550.815,23563.09,92855.127,84858.7
 Poor2,60249.28,93237.08,08944.919,62341.3
Marital status
 Married or de facto union (base)3,93474.116,98469.512,29367.733,21169.3
 Divorce, Separated or widowed91617.35,16921.24,52424.910,60922.2
 Single4578.62,2929.41,3347.44,0838.5
Education
 Non-tertiary education3,3029.917,36951.912,77438.233,44569.8
 Tertiary education2,00513.97,07648.95,37714.514,45830.2

3. Methods

This study utilized a repeated cross-sectional design to analyze national survey data from Ecuador, focusing on the years 2007 and 2014. The dependent variable, life satisfaction, was assessed using a three-category ordinal scale (unsatisfied, satisfied, and very satisfied). As noted above, a dummy variable was also created after the 2008 policy. Prosocial activities, such as mingas (community work) and caregiving, were classified into distinct categories based on weekly hours. Data analysis employed ordinal logistic regression to evaluate the effects of these activities and the 2008 constitutional reform on life satisfaction. The models incorporated control variables (age, gender, ethnicity, education, marital status, poverty status, and regional differences) and interaction terms to explore the nuances of these relationships. Robustness checks included assessments for multicollinearity and heteroskedasticity using variance inflation factors and clustering standard errors (Yamano, 2009). All analyses were conducted using STATA software, ensuring rigorous adherence to econometric standards. Additionally, the categorization of prosocial activities was refined to enhance the granularity of the findings, addressing potential variability in engagement levels.

The economic model is expressed in this way:

Equation 1, economic model repeated cross-section analysis 2007–2014

Life Satisfaction=f(Prosocial;Economic;Demographic;Othervariables;After New Policy;Interactions)

The model determines how well the answers to the research questions are predicted with the prosocial and controlled variables and with the inclusion of the 2008 policy dummy. Independent variables include control variables such as age, gender (of the head of households), ethnicity, poverty, education, and marital status. Comparable available variables in both surveys are used.

3.1 Repeated cross-section

The method we use is a repeated cross-section design. As Rafferty et al. (2015, p. 4) note, where “data in which the same (or similar) information is asked to a different sample of individuals each time … the samples can then be compared over time”. This method is applied in this analysis to identify changes in the coefficients of the explanatory variables and life satisfaction in two periods, 2007 and 2014 (before and after the 2008 Constitution). The life satisfaction questions in both surveys have different respondents (so that panel data estimation cannot be used). The repeated cross-section9 design uses “pseudo-panels”. The assumption of having the same respondents over time is not essential (Allison, 2021; Lebo & Weber, 2015).

Using this methodology, conclusions can be drawn about how levels of life satisfaction for the heads of households changed after the 2008 Constitution. However, we cannot deduce how life satisfaction for a given head of household has changed over time, because different people are in the two different samples in the two years. Even though this is a data limitation, the sample in both periods is of the heads of the households.

The effect of the 2008 policy on prosocial variables and life satisfaction is the priority of the research.

3.2 Full model: Life satisfaction, prosocial activities, and controlled variables at the regional level with the 2008 policy

The full model associates life satisfaction, prosocial activities, control variables, regions/areas and the policy variable (see Equation 4).

Equation 4, full model repeated cross-section analysis 2007–2014

LifeSatisf=β0+β1MingaCAT+β2CaringCAT+β3AgeCAT+β4Female+β5Edu_Dumm+β6Indigenous+β7Poor_Dumm+β8Married_Lawunion+β9RegionsCAT+β10RuralDumm+β11AfterPolicy+u

The full model incorporates all the prosocial, the policy variable, regional level and controlled variables. Correction for heteroskedasticity is made in a similar way to the previous models. Also, as shown in Table 6, all variables have a weak correlation, again suggesting multicollinearity will not be a problem in the full model (Gujarati et al., 2004). This was confirmed with a variance inflation factor of less than 3.05 (VIF mean = 1.66). After checking for heteroskedasticity and multicollinearity, the coefficients and statistics are presented in Table 7.

Table 6. Correlation coefficients: Full model.

Life SatisfactionMingasCaring for peopleAge CategoryFemaleTertiary EducationIndigenousPovertyMarital StatusRegionsRural After Policy
Life Satisfaction 1
Mingas -0.04141
Caring for people -0.00630.00431
Age Category -0.0975-0.0109-0.23221
Female -0.0732-0.04220.08930.11281
Tertiary Education 0.2227-0.07720.0518-0.2235-0.03311
Indigenous -0.05310.2543-0.0021-0.0146-0.0314-0.09521
Poverty -0.11330.07280.01240.04290.0491-0.23050.13431
Marrital status -0.0698-0.0512-0.01260.10060.584-0.0262-0.05040.02781
Regions 0.0043-0.11050.00320.02870.0154-0.0296-0.30280.0150.01971
Rural -0.08260.1886-0.03310.0631-0.0857-0.29940.28110.2712-0.0711-0.1831
After Policy 0.3325-0.0386-0.0352-0.05840.01210.27590.08890.08860.0043-0.1240.05151

Table 7. Determinants of life satisfaction, prosocial activities and controlled variables with after the 2008 policy.

Lower to higher category of life satisfaction
Unsatisfied, satisfied and very satisfied
VariablesOdds ratio P-Value
Mingas (hours/week)
 1–6 h/w1.0690.154
 7+ h/w1.0100.876
Caring for people (hours/week)
 1–7 h/w0.9560.089
 8+ h/w0.9590.261
Age (years old)
 32–480.9520.104
 49–640.8850.000***
 65+0.7480.000***
Other
 Gender0.8660.000***
 Tertiary education1.4280.000***
 Ethnicity0.7310.000***
 Poverty0.6360.000***
Marital status
 Divorce, separated or widowed0.7750.000***
 Single0.8000.000***
Regional level
 Central0.9670.298
 Coast1.1620.000***
Rural0.8720.000***
 After the 2008 policy4.3540.000***
Pseudo R2 McFadden0.084
Prob > chi20.000

*** Statistically significant at the 1% level.

** Statistically significant at the 5% level.

In the full model, the pseudo-R2 (0.084). The impacts of age ranges from 49 years and above relative to the youngest group (13–31) are significant. Gender, tertiary education, ethnicity, poverty and marital status (divorced, separated, widowed and single) are also statistically significant. Finally, the 2008 policy, living in the Coast region and living in rural areas are also significant.

Interpretation of the estimates of the full model 2007–2014

When controlled variables are added into the model, the odds ratio of 0.885 for the 49–64 age group means that this age group is associated with 11.5 per cent lower odds of life satisfaction. The odds ratios of 0.748 for the 65+ age group means that this age group is associated with 25.2 per cent lower odds of being in a higher rather than a lower category of life satisfaction. Younger people between 13 and 31 years old are the basis for the age range analysis.

The odds ratio of 1.428 for tertiary education shows that having tertiary education (more than 12 years of formal education) is associated with 42.8 per cent greater odds of being in a higher rather than a lower category of life satisfaction relative to those without tertiary education. Interestingly, none of the prosocial activity variables is statistically significant.

On the other hand, the odds ratio of 0.866 for gender shows that being a female is associated with 13.4 per cent lower odds of being in a higher rather than a lower category of life satisfaction relative to males. For ethnicity, the odds ratio of 0.731 shows that being indigenous is associated with 26.9 per cent lower odds of being in a higher rather than a lower category of life satisfaction. For poverty, the odds ratio of 0.636 shows that being poor is associated with 36.4 per cent lower odds of being in a higher rather than a lower category of life satisfaction.

The odds ratio of 0.775 for marital status means that being divorced or separated is associated with 22.5 per cent lower odds of being in a higher rather than a lower category of life satisfaction, and the odds ratio of 0.800 for being single is associated with 20 per cent lower odds of being in a higher rather than a lower category of life satisfaction, both relative to being married or in a de facto union.

Finally, the odds ratio of 4.354 for after the 2008 policy means that after the 2008 policy heads of households had nearly three-and-a-half times greater odds of being in a higher rather than a lower category of life satisfaction relative to the time before the 2008 policy. When regions are added into the model, we can observe an odds ratios of 1.162 for the Coast region, which means that people who live in that region have 16.2 per cent greater odds of being in a higher rather than a lower category of life satisfaction relative to the Eastern region. For rural areas, the odds ratio of 0.872 means that people who live in rural areas have 12.8 per cent lower odds of being in a higher rather than a lower category of life satisfaction relative to those living in urban areas.

3.3 Interactions between prosocial activities and regions with the 2008 policy (full model)

In this section, the interaction between the regional dummies and prosocial activities is added to the model (see Equation 5).

Equation 5, full model repeated cross-section analysis 2007–2014 with interactions (prosocial activities and regions)

LifeSatisf=β0+β1MingaCAT+β2CaringCAT+β3AgeCAT+β4Female+β5Edu_Dumm+β6Indigenous+β7Poor_Dumm+β8Married_Lawunion+β9RegionsCAT+β10Rural_Dumm+β11RegionsCATXMingasCAT+β12RegionsCATXCaringCAT+β13After Policy+u

When we run the model with the interactions between mingas, caring for people, and regions with the new policy dummy variable, coefficients of the mingas variables are statistically significant. Some of the effects of regions interacted with mingas are statistically significant. Some interactions variables between region and caring for people are statistically significant. The control variables have similar coefficients and significance than without interactions.

3.4 Interpretation of the estimates with interactions, full model 2007–2014

In this model, heads of households have nearly three-and-a-half times greater odds of being in a higher rather than a lower category of life satisfaction relative to the time before the constitution. The results shows that the main effects of mingas in the 1–6 h/w category, the odds ratio of 1.254 shows that the effect of spending time in mingas is associated with 25.4 per cent greater odds of being in a higher rather than a lower category of life satisfaction relative to the Eastern region and no time spent in mingas. The odds ratios of 1.929 for the 7+ hours category of mingas shows that the effect of spending time on mingas is associated with 92.9 per cent greater odds of being in a higher rather than a lower category of life satisfaction relative to the Eastern region and spending no time in mingas.

There is some evidence of interactions in two categories of “regions*mingas”. The odds ratios of 0.474 for those living in the Central region and spending 7+ hours/week in mingas means that the effect of the Central area combined with the value of mingas is associated with 52.6 per cent lower odds of being in a higher rather than a lower category of life satisfaction relative to the Eastern region and no time spent in mingas. The odds ratios of 0.409 for those living in the Coast region and spending 7+ hours a week in mingas means that the effect of the Coast region combined with the value of mingas is associated with 59.1 per cent lower odds of being in a higher rather than a lower category of life satisfaction relative to the Eastern region and no time spent in mingas. Historically, the Eastern region is taken into account as the reference because it is the one with the greatest problems of poverty, rurality and inequality (Navarro-Jiménez, 1975). However, changing the reference to another region will result in similar interpretations regardless of which region is taken as the reference category.

Also, there are interactions in one category of “regions*caring”. The odds ratios of 0.752 for those living in the Central region and spending 8+ hours/week caring for people means that the effect of the Central region combined with the value of caring for people is associated with 24.8 per cent lower odds of being in a higher rather than a lower category of life satisfaction relative to the Eastern region and no time in spent caring.

Thus, mingas seems to have a positive impact, increasing life satisfaction for the Eastern region as the base category of region in both categories of mingas.

3.5 Interactions between prosocial activities and after the 2008 policy (full model)

In this section, prosocial activities and the new constitution are interacted to recognise the role of a new constitution and its interactions with caring for people and mingas on life satisfaction. In this model, only interactions between mingas and the new constitution are statistically significant (see Table 8). Coefficients and significance for the control variables are similar in the models with and without the region interactions. No coefficients were found as statistically significant in the interactions between the new constitution and caring for people. By refining the methodological framework, the study ensures that the association between prosocial activities and life satisfaction is captured with greater precision, offering a more nuanced interpretation of the data (Lebo & Weber, 2015).

Table 8. Determinants of life satisfaction, the new constitution and prosocial activities and their interactions.

Lower to higher category of life satisfaction
VariablesOdds ratio P-Value
Mingas (hours/week)
 1–6 h/w0.9570.534
 7+ h/w1.0210.846
Caring for people (hours/week)
 1–7 h/w1.0190.713
 8+ h/w1.0390.522
Age (years old)
 32–480.9490.084
 49–640.8820.000***
 65+0.7460.000***
Other
 Gender0.8670.000***
 Tertiary education1.4320.000***
 Ethnicity0.7280.000***
 Poverty0.6350.000***
Marital status
 Divorced or separated0.7750.000***
 Single0.7990.000***
Regional level
 Central0.9690.333
 Coast1.1640.000***
Rural0.8730.000***
Effects of after the constitution interacted with n mingas
 Constitution with mingas 1–6 h/w1.2320.023**
 Constitution with mingas 7+ h/w0.9810.883
Effects of after the constitution interacted with caring
 Constitution with caring 1–7 h/w0.9100.096
 Constitution with caring 8+ h/w0.8710.063
After the 2008 policy4.4410.000***
Pseudo R2 McFadden0.000
Prob > chi20.084

*** Statistically significant at the 1% level.

** Statistically significant at the 5% level.

These models are not only statistically robust but also effectively disentangle the effects of various socio-economic variables on life satisfaction (Wooldridge, 2010). The inclusion of interaction terms between year dummies and the post-2008 Constitution variable allows the analysis to isolate the impact of the constitutional reforms more accurately, thereby addressing potential multicollinearity issues. Furthermore, the study meticulously examines the unexpected negative coefficients associated with prosocial behaviors, proposing that these results may stem from the burden or stress linked to unpaid care work, particularly among certain demographic groups. By clustering standard errors by year or region/year, the study accounts for heteroskedasticity and autocorrelation, enhancing the reliability of the regression estimates (Cameron & Trivedi, 2005). This thorough approach not only clarifies the role of prosocial activities in shaping life satisfaction but also contributes to the broader discourse on the complex interplay between social engagement and wellbeing.

Interpretation of the estimates with the effect of after the new constitution and prosocial activities (interactions), full model 2007–2014

The odds ratio of 4.44 for the new constitution shows that the effect of the constitution is associated with approximately three-and-a-half times greater odds of being in a higher rather than a lower category of life satisfaction relative to 2007 national survey (before the 2008 Constitution) for all controlled variables.

The odds ratios of 1.232 for those who spend 1–6 hours/week in mingas means that the effect of the constitution is associated with 23.2 per cent greater odds of being in a higher rather than a lower category of LS relative to the non-policy period. The 2008 policy has a positive effect, increasing life satisfaction for those who spend 1–6 hours per week in mingas.

4. Discussion of results

In the full model with interactions for regions and mingas, after the 2008 policy and participation in mingas has a high odds ratio. Controlled variables, such as age, gender, tertiary education, ethnicity, poverty and marital status affect life satisfaction in the ways anticipated as in the literature review.

In relation to participation in mingas, the hypothesis is accepted. The findings shows that people who live in the Eastern region experience an increase in life satisfaction when they spend time participating in mingas. The regression analysis also accepts the hypothesis which was that the 2008 policy had increased life satisfaction in 2014 for people who practice mingas between 1-6 hours per week. In contrast, there are limited significant findings with prosocial activities of caring and their interactions. There is, effectively, a decrease in mingas between 2007 and 2014 according to Minga surveys, however, this may be due to increased government spending on public investment, education or health. Indigenous communities did not feel the need to work collectively since they have more economic subsidies. However, mingas are associated to subjective well-being in 2014.

It was noted that cooperative behaviour provides benefits for everyone (Post, 2005; Van Dijk, 2015). Also, studies by Schroeder and Graziano (2015); Wilkinson and Klaes (2012) also corroborated that the desire to be kind to others increases life satisfaction. In Ecuador, possibly regions that have practised mingas for a long time (the Amazon region and regions with a higher concentration of indigenous people) perceive benefits from this interaction with the community. Individuals become more prosocial when they perceive the benefits of this behaviour (Nolan & Schultz, 2015). Thus, the cooperative model (mingas) seems to have worked in these communities and increased life satisfaction.

The Eastern region, where there is a higher concentration of poverty, indigenous people and income inequality (in particular, in rural areas) (Chiasson-LeBel, 2019), has lower levels of life satisfaction than the Coast region when mingas is not considered. However, the 2008 policy, which promoted prosocial activities11, has increased life satisfaction in the region that practises mingas. According to the results, in particular, the interactions between prosocial behaviour and after the 2008 constitution, the coefficients are significant in 2014 compared to 2007.

Ecuador has a large gap between males’ and females’ wellbeing. If life satisfaction of women and men is related to how they feel about the activities they are doing, men are more satisfied than women. There has been an historically disadvantaged group of females, indigenous people and people who live in rural areas (Nicola et al., 2018, p. 15). This situation of disadvantage has not changed after the policy. The findings of this study show that gender is not a significant determinant of the relationship between prosocial behaviour and life satisfaction.

Even though there was a significant reduction in poverty and inequality in Ecuador from 2007 to 2014, there are still problems with the lack of an efficient health system, and this may be one of the main factors affecting older people’s life satisfaction. Poverty and inequality in Ecuador are linked to race, ethnicity, rurality and gender (Pérez, 2004, p. 184), as mentioned in the literature review.

Results seem consistent with previous studies. There was an increase in life satisfaction in 2014 in comparison to 2007. The results show higher life satisfaction after the new policy was established, taking into account several control variables. Moreover, the results from the control variables are plausible: the relationships are all in the same direction as those highlighted in the literature review.

4.1 Data limitations

This study combines national data which includes both life satisfaction and prosocial data using data from ENEMDU and ECV national surveys. In these surveys, there is specific and limited information about life satisfaction and prosocial activities that can be analysed at the regional level and for urban/rural areas.

One of the data limitations of both surveys is that the data relates only to the heads of households. Even though both national surveys will have different heads of households in 2007 and 2014, deductions can still be made about how life satisfaction for the heads of the households has changed over time. Unfortunately, there is no longitudinal data available. Thus, individual experience could not be tracked over time. However, repeated cross-sections allowed us to identify the determinants of satisfaction with life after the 2008 policy for heads of households and their relationships with controlled and socio-demographic variables in a group over time.

To address the potential limitations of the original categorization, the study has re-evaluated and refined the thresholds for mingas and caregiving based on the data distribution. By choosing more representative categories (e.g., 0, 1-6, and 7+ hours for mingas; 0, 1-7, and 8+ hours for caregiving), the analysis more effectively captured the diversity in how individuals engage in these prosocial activities. This adjustment allowed for a clearer understanding of how different levels of participation impact life satisfaction, providing a more precise and meaningful analysis. The paper discuss the rationale behind these revised thresholds to clarify their significance and ensure transparency.

Additionally, the potential influence of male-dominated household heads in the database may bias the findings on the association between life satisfaction, prosocial activities, and gender. Thus,performing a dedicated analysis that focuses on female-headed households would provide valuable information for future research.

Although the variables we used to model subjective wellbeing and prosocial behaviour were limited, due to the lack of information in the data, we believe that the data are sufficient and the best fit to understand that in the seven years covered by the analysis, after the application of the new constitution, Ecuadorians increased their subjective wellbeing. Also, the poorer regions that practice mingas increased their wellbeing. Both in the descriptive analysis and the modelling, the findings show similar results.

As discussed, treating the policy variable as a dummy (the value 1 indicated the presence of the Constitution effect) may not be ideal. However, the results of the “repeated cross-section” econometric model in this study agrees with the literature review. It is worthy to add the limitation of the 2008 dummy variable, as it may encompass not only a variable related to politics, but also other omitted variables that could affect life satisfaction.

5. Conclusions and Policy Implications

The study’s findings suggest that several factors are linked to increased life satisfaction in Ecuador, including the impact of social-oriented policies outlined in the 2008 Constitution. These policies, along with living in the Coast region or urban areas, higher education, increased income, greater job satisfaction, and active community participation, are all correlated with elevated well-being (Marsh, 2010). Notably, those who practiced concepts of solidarity and the common good experienced higher life satisfaction following the implementation of these social policies, underlining the positive psychological effects of cooperation12.

Furthermore, the study delves into the effects of the 2008 Constitution, examining how it influenced life satisfaction alongside control variables and prosocial activities like community work (mingas) in Ecuador (Nicola et al., 2018). While income, education, and age are traditionally associated with life satisfaction changes, this study reveals that prosocial activities through mingas, particularly prevalent in the Eastern region, also contribute to increased life satisfaction. Caring for family members may be tied to a moral obligation effect, and the Sumak-Kawsay philosophy’s promotion of community-oriented practices like mingas plays a crucial role in stimulating prosocial behavior and enhancing life satisfaction (Dunn et al., 2014). Government services aimed at reducing family burdens can have implications for life satisfaction, with a potential to decrease the perceived burden of caregiving.

Community-centric initiatives, especially where mingas is prevalent, prove to be beneficial, with cooperation and the principles of reciprocity and solidarity holding significance in the Eastern region’s cultural values (Wilson, 2000)13. Additionally, the study identifies the role of gender, educational attainment, marital status, and poverty status in shaping well-being, reinforcing expected relationships with these factors. These collective findings underscore the multifaceted dynamics of subjective well-being in the context of Ecuador and the influence of a combination of socio-economic policies, community practices, and individual characteristics (Nolan & Schultz, 2015; Wright, 2009).

The 2008 Constitution was associated with increased life satisfaction in Ecuador. This type of wellbeing increase has not only been observed in this country. Bolivia also changed its constitution in 2009, and this has created significant progress until the present day (Grugel & Riggirozzi, 2018). Social policies from left-wing governments focused on increasing social spending have had some implications in Latin America that go against the neoliberal model implemented in the 1980s. For example, Ecuador, Bolivia, and Brazil made a large investment in education, health, and public infrastructure between 2006 and 2018 (De la Torre et al., 2020). This investment was also supported by the high prices of raw materials that are the main source of income in most Latin American countries, as argued by several authors, including those who mention an Ecuadorian golden decade (2005–2014) where high commodity prices were the cause of its strong development in a short time.

It needs to be understood that an excessive increase in social spending can also lead to other problems, such as an increase in unproductive public institutions and corruption (Yunan and Pacheco-Jaramillo, 2024). Therefore, social spending policies must be efficient and must be focused on the sectors that need them, such as health and education, and to stimulate the production of the private sector. Also, social policies have promoted positive values in Ecuador by encouraging prosocial activities and guiding cultural identity. Public policies and macroeconomic factors that aim to improve institutional conditions can change human behaviours and improve life satisfaction (Head, 2007).

People tend to be happier when they are in good health, earn more, are better educated, and perceive an environment of fairness and justice. Community involvement can be more useful in societies in which government assistance does not support social-economic programs by the number of people who need help. However, when there is no support from governments, self-management arises as a reaction of the poor to their situation, often in alliance with NGOs (Choguill, 1996). These social policies can be useful for other developing countries which have diverse kinds of communal practices, cultures, and other aspects of diversity to create a development model aligned with the society and its social reality. It could be that a better distribution of income and resources as an engine or stimulus to reduce poverty and income inequality (although these are beyond the scope of the study) has helped Ecuador to improve life satisfaction from 2007 to 2014. Similarly, finally, it is important to note that apart from distributive social policies, economic growth also helped increase the wellbeing of Ecuadorians after 2007. For example, from 2007 to 2017, Ecuador’s GDP more than doubled, from 51 to 104 billion dollars. What we could conclude is that economic growth combined with distributive policies (growth with equity) has increased wellbeing in Ecuador (Worldbank-INEC, 2016).

Future research should prioritize the collection of longitudinal data to strengthen the understanding of the determinants of SWB and prosocial behaviour in Ecuador. Currently available data concerning SWB and prosocial activities in the country are limited, with a notable absence of SWB measurements since 2017. Consequently, primary data collection becomes imperative to fortify the robustness of SWB models. Moreover, additional research endeavours should delve into the factors that influence life satisfaction within Ecuador’s diverse regions. A thorough regression analysis could offer valuable insights into these regional dynamics. Furthermore, the impact of communal practices on individual behaviour, particularly in the context of SWB, is a subject ripe for exploration in future studies.

In forthcoming research, a broader spectrum of prosocial activities should be investigated, encompassing both developed and developing countries. These activities include donations and assistance, shedding light on their impact on changes in subjective wellbeing. The motivation behind prosocial behaviour should be examined in depth, delving into not just intrinsic motivations but also the influence of reputation and other aspects on individuals’ engagement in altruistic actions. Experimental economics stands out as a promising tool to study cooperative behaviour, termed “prosocial economics,” and its effects on increasing subjective well-being. While the current research acknowledges the two-way relationship between life satisfaction and prosocial activities, future studies should focus on whether happiness drives prosocial behaviour. Additionally, the sustainability and resilience of social policies, particularly in the face of economic cycles, need to be scrutinized. Longitudinal data on SWB and the effectiveness of social policies over time can provide invaluable insights. Finally, extending the analysis to examine the relationship between GDP and life satisfaction in other countries can yield illuminating comparative findings, allowing us to understand the impact of GDP changes on life satisfaction more comprehensively.

Ethics and consent

Ethical approval and consent were not required for this study, as it relied exclusively on publicly available and anonymized data from national surveys conducted by the National Institute of Statistics and Census (INEC) of Ecuador. These datasets, freely accessible through the INEC website; https://www.ecuadorencifras.gob.ec/estadisticas/, adhere to ethical standards, including obtaining informed consent from participants during their collection, ensuring compliance with research guidelines and safeguarding participant confidentiality.

Data availabilty statement

Underlying data

The data supporting the findings of this study are derived from the National Survey of Employment, Unemployment, and Underemployment (ENEMDU) 2007 and the Ecuadorian National Survey of Living Conditions (ECV) 2014, both conducted by the National Institute of Statistics and Census (INEC) of Ecuador. These datasets are publicly accessible through the INEC website: https://www.ecuadorencifras.gob.ec/estadisticas/. The data is available in STATA format and can be accessed without restrictions.

Extended data

This project contains the following extended data:

Repository name: Zenodo

Title of project: Understanding Subjective Wellbeing, Prosocial Activities and the Sumak-Kawsay “The Good Way of Living”: An Ecuadorian Case Study Pacheco-Jaramillo, W. A. (2008–2015)

DOI: 10.5281/zenodo.14009925, Repeated Cross_section 28mar23.dta: Dataset consolidated from INEC – Ecuador DATA base used in the study, containing repeated cross-sectional data related to subjective well-being and socio-economic factors in Ecuador. Self-perception of the heads of the households and the use of time surveys 2007 (original survey and translated). Also, Self-perception of the heads of the households and use of time survey 2014 (original survey and translated).

Software availability statement

The statistical analyses for this study were performed using STATA 16 (StataCorp, 2019). Detailed information about STATA can be found on its official website. Since STATA is a proprietary software, we recommend R as a free and open-access alternative for replicating the analyses. R provides comparable functionalities and is available for download at its official website. To ensure transparency and reproducibility, a Software Availability Statement has been included at the end of the article, detailing the tools and their availability.

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Footnotes

1 The sample after the constitution (2014) is larger than 2007. In the 2014 national survey, approximately 53% more heads of households were interviewed than in 2007.

2 The 2008 dummy variable limitation may not only include a policy variable but also other omitted variables.

3 Creation of dummies, the generation of names for the new variables with interactions, and the unification of the two databases for the repeated cross-section model are part of the treatment applied to the prosocial and controlled variables.

4 Other variables, such as job satisfaction and environmental concern, are not available in both years. Thus, these variables are not considered in the repeated cross-section analysis.

5 In the sample, 54% of the population is between 13 and 48 years old ( Table 3). The fact that the survey sample focuses on heads of households also needs to be considered, as heads of households are more likely to be older than younger.

6 There is a question in both the 2007 and 2014 surveys that captures self-reported poverty: “How do you consider your household? Poor or non-poor?”

7 As the survey uses heads of households, males have stronger representation in the national data.

8 In the national survey there is the question: How do you consider your household? very poor, poor, more or less poor and not poor. A dummy was created for the poor and very poor categories.

9 “Repeated cross-section data are created where a survey is administered to a new sample of interviewees at successive time points. For an annual survey, this means that respondents in one year will be different people to those in a prior year. Such data can either be analysed cross-section, by looking at one survey year, or combined for analysis over time” Rafferty, A., Walthery, P., & King-Hele, S. (2015). Analysing Change over Time: Repeated Cross Sectional and Longitudinal Survey Data.

10 There is a collinearity problem between the new constitution and mingas of 8+ hours per week.

11 “The system shall be coordinated with the National Development Plan and with the national decentralized system of participatory planning; it shall be guided by the principles of universality, equality, equity, progressivity, interculturalism, solidarity and non-discrimination…” article 340, Constitution, E. (2008). Magna Carta (Ecuadorian Constitution). Montecristi: Asamblea Nacional del Ecuador Retrieved from http://www.asambleanacional.gov.ec/documentos/constitucion_de_bolsillo.pdf

12 Mestizos also have continued practising mingas activities based on indigenous experiences until now (that is, not only indigenous people practise mingas).

13 Sociodemographic characteristics, as well as perceptions of the environment, are strong predictors of participation in the community Rodrigo, R., Yan, Y., Parra, D. C., & Brownson, R. C. (2014). Assessing Participation in Community-Based Physical Activity Programs in Brazil.(Report). Medicine and Science in Sports and Exercise, 46(1), 92-98.

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Pacheco-Jaramillo WA, Miranti R and Tanton R. Exploring subjective well being in a developing country: Socio economic influence in Ecuador before and after the 2008 constitutional reform [version 1; peer review: awaiting peer review]. F1000Research 2025, 14:95 (https://doi.org/10.12688/f1000research.159049.1)
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