1. Introduction
ubjective Well-Being (SWB) is a broad category of phenomena that includes people’s emotional responses, domain satisfactions, and global judgments of life satisfaction [1, 2]. SWB refers to how people experience and evaluate their lives. In other words, SWB is a person’s cognitive and emotional evaluations of his life [3, 4]. SWB has long been the subject matter of works in the fields of psychology and sociology studies, then it expanded to studies on human geography, urban and regional studies, and economics. Easterlin (1974) grounded the issue of the relationship between economics indices and well-being on the empirical analysis of self-reported data on SWB or happiness [5]. The literature uses different labels for happiness: well-being, SWB, happiness, or life satisfaction. Well-being is a general concept encompassing happiness and life satisfaction; SWB is self-reported [6]. Happiness (equally SWB) is one of the variables, which has a major impact on the mental health status of people in recent years [1, 7, 8]. Literature uses interchangeably “subjective well-being”, “life satisfaction”, and “happiness” [6, 9, 10], and we have also the same conception in this article.
A subjective view of utility acknowledges that people have their ideas about their mental health status and welfare. For decades, neoclassic economists have explained that the choices, which are made by individuals are determined by the utility that depends on consuming goods and services [11]. Recently, economists have increasingly believed that economic choices and decision utility approaches are not good indicators for well-being, and self-reported SWB is a robust indicator, which shows the whole evaluation of personal life [3]. Happiness economics has the potential to fundamentally change the economy in the future; happiness is usually considered the final goal of life; usually, everyone wants to be happy. The “pursuit of happiness” is a “basic right” similar to the right to life and liberty. In addition to natural desire, there are some main reasons for economists to pay attention to happiness. The first is economic policy and the usage of happiness data for making proper policies for society. The second reason, due to which economists are interested in happiness is the effect of institutional conditions, such as quality of governance and the amount of social capital on individual well-being [12]. 
SWB information is valuable data regarding its considerable potential to monitor the economic, social, and health conditions of populations and in potentially informing policy decisions across these domains [13]. Exploring all determinants, affecting nations’ happiness is a fundamental key for policymakers [8]. To measure how policies affect social welfare and mental health, economists have traditionally connected policy to welfare through some theoretical models, like SWB studies 
According to the main aim of each SWB study, it may focus on determinants, like health status [9, 10], religion [2, 9], different components of the living environment [14, 15], residence space [16], tenure status - residency or not- [10 , 14] and some socio-economic variables, like income, age, marital status, education, and employment status [3, 9, 17], which are common in all SWB studies. Considering the effects of geographic locations on SWB is a new set of determinants, which most regional and environmental studies on SWB have shown its importance. Some of these determinants are the place where people live and its quality, and satisfaction with the living area [9, 14, 16, 18]. Some studies have been conducted to evaluate urban-rural differences in happiness levels. On the other hand, there has been much immigration from rural areas and towns to metropolitan cities. This migration happens due to more job opportunities and higher income levels [6]. Consequently, due to higher housing expenses in metropolises, informal housing and shack settlements have been raised [19]. Also, more urbanization is associated with more industrialization [20]. 
To our knowledge, there are a few studies on this topic in Iran, and this study tried to evaluate SWB and its determinants in Iran. Given the importance of happiness, investigating the probable difference of outskirt-urban dwellers in happiness level is crucial. Besides, an increasing amount of living people in outskirts of metropolises become a serious problem for the government and cause several social and economic problems and it seems that there is no comprehensive study on outskirt dwellers̓ level of happiness compared with metropolitans’ dweller and defining related determinants of the SWB in Iran. In this article, we focused on people living in Rasht city, a metropolis in the northern part of Iran. Using Gallup’s Global Emotions questionnaire, we designed a proper localized and culturized questionnaire, and data were collected by conducting a structured interview with 219 interviewees selected by two-stage cluster sampling method. Using related econometrics and statistical tests, and ordered logit regression was used to evaluate the determinants. Also, some robustness checks were carried out on the results.
While subjective measures of life are internal, for evaluating SWB, we tried to modify the local expression of SWB, due to Iranian culture. The relative status and comparison with a reference group are more important than the absolute statue of people [6, 21, 22]. In Iran, people are more concerned about their relative status (income, consumption, etc.) than their absolute status [23]. The Duesenberry relative income theory explains consumer behavior in the Iranian economy accurately [24]. The rate of relative consumption and estimated coefficient of relative importance coefficients show that relative status or rivalry is high among Iranian households’, indicating high relative importance in Iranian households’ consumption patterns [25]. Defining this indicator is regarded as a contribution of this paper. The second trait of this study is that, culturally, when Iranian people are formally asked about their expenses and income, they understate their real income and it is a common problem in a typical empirical study in Iran. To overcome these problems, in addition to questions about wage and other sources of income, as the second contribution of this study, we asked about relative financial satisfaction and used it as a factor for showing financial status.
In the next section, there is a full explanation of the methodology used in this study. In the results section, the most important estimation and related tables are presented. Based on different tests and models, only important ones are reported and included in the final results. In the discussion section, the main findings are mentioned and discussed. The last section of the paper provides the highlighted conclusions of the study. 
2. Methods
This study was conducted using a structured interview using a validated structured questionnaire with people living in Rasht city and its outskirts in 2018. This study is a part of a larger cross-sectional study, with the aim of evaluating SWB and its determinants in Iranian metropolitans and comparing happiness levels between outskirt dwellers and urban dwellers. The sample was selected using a stratified, two-stage cluster method. At this stage, direct interviews with people by research partners who had the necessary training, background, and knowledge of the research method with a history of collaboration with the Statistics Centre were done. All interviewees were residents of the area, in which they were interviewed and asked to answer on a voluntary and honest basis. The sample size was calculated based on two formulas. The first was a sample-proportion formula in order to be ensured of having a representative sample and the second was comparing the mean of two populations [26]. Given the budgetary constraint, 112 people who lived in the outskirt and 107 people in the city were interviewed. The age limit for an interviewee was 16 years or older. Gallup’s Global Emotions questionnaire was used in this study regarding the positive and negative experiences. The validity of the questionnaire was assessed using a panel of experts. Its reliability was measured using Raykov’s Reliability Coefficient (RRC) [27].
Studies on the determinant of SWB adopt a general Formula 1:



SWB is a dependent variable and independent variables are categorized into Socio-Economic (SEs), Socio-Demographic (SDs), and Health Variables (Hs) in addition to variables related to residence, district of living (RDs), and people religious beliefs (R). The main hypothesis is that the district of living area and other factors related to the people’s residency, affect SWB.
Despite the widespread application of the SWB measure, no unique measure is available for it [10]. As relative status (income and consumption) are more important than absolute status in Iran, for choosing the dependent variable, a localized index was defined. The theoretical idea stating relative status matters for happiness; this is referred to as the social comparison effects [28]. According to the aspiration level theory, the gap between aspiration and achievement determines happiness [12]. Then, instead of a typical question, like “how satisfied are you with your life in general?”, - which was in the questionnaire for robustness and double-check - it is asked “how satisfied are you with your whole life relative to your family, friends, and neighbors, in general ?”, which is a contribution of this study in Iran. The responses are ordinal, not cardinal, scored on a 7-point Likert scale ranging from 1 (completely dissatisfied) to 7 (completely satisfied). The scales that have been used in different surveys have different ranges. For instance, the world value survey used an 11-point scale while a 3-point scale was used by the US General Social Survey, and the British Household Panel used a 7-point scale.
Almost in all happiness studies, socioeconomic independent variables, like age, sex, living with a partner, educational level, and having a career are the independent variables. Financial satisfaction is defined as a factor for income and financial status of people as all data about income is understated by interviewees in Iran. Some other variables are used in the model to indicate the health status of people. Variables that are related to the housing environment (like residential satisfaction, tenure status, and residence space) and religious beliefs [29] of people are also considered as explanatory variables for the model.
A series of statistical techniques (Correlation Process, Ordered Probit Regression, and ordinary least squares regression) were used to examine the relationships between SWB and related determinants. For non-binary variables, the Shapiro-Wilk test, and for testing the normality of data, the Skewness/Kurtosis test was used. The mean and the standard deviation for all variables were calculated, and also the mean score of male and female interviewees, and two kinds of dwellers were calculated separately. All data analyses were performed using STATA 14.2.
3. Results
Table 1 represents descriptive data of the whole sample, including people aged 16 years old or older living in Rasht city and its outskirts in 2018, according to gender and living district for dependent and all independent variables. 



SWB is a factor for assessing happiness and it’s mean for outskirt dwellers was 4.9 (out of 7), which is less than city dwellers (5.23). The same trend was found in gender; (the average number of males: 4.95 and females: 5.16).
In order to have a better understanding of the relationship between variables, Table 2 represents the correlation between all variables. 



Table 3 represents the Ordered Probit Regression results. 



The marginal effects (the effect of a unit change in each variable on the probability of being very satisfied) are shown, along with the significance of the coefficients, e.g., a unit rise in financial satisfaction, raises the probability of being satisfied and lowers that of being unsatisfied. The estimations were done for the whole data and for each group of dwellers, separately. Equation 1 is a basic equation and in other equations, for showing the robustness of the results, some variables were added to the model separately. Equation 6 includes all the independent variables of the model. In equations 7 to 12, all estimations were carried out just for outskirt dwellers, and equations 13 to 18 are related to the city dwellers. All data shows almost similar effects of independent variables on the probability of each result for dependent variable except for a few exceptions. 
In Table 4, equation 1, regional and housing parameters were removed and religious variables were added. 



The estimation was repeated to evaluate the effect of religion on happiness. The religious variable had a positive marginal effect on SWB. Equations 2 and 3 represent the same estimation for the outskirt and city dwellers, respectively. To double-check the negative effects of having a job on SWB, we replaced the employed variable (1 for who has a job) with the active variable (1 for active population) in Equations 4 and 5, which are the same as equations 1 and 6 of Table 3. Almost all results were the same and this new variable had a negative coefficient, as well. This table also presents that all results are robust. As a third test for robustness, all equations were estimated using an OLS method. The pattern of results was very similar to that of Table 3. To save space, these results are not reported. Generally, the results were robust in the form of the dependent variable. 
4. Discussion
The current study may be the first study to link the topic of outskirt/urban living statues and the literature on SWB. It has posed the question “Is there any difference between the happiness level of city dwellers and outskirt dwellers aged 16 years old or older in Rasht city in 2018?”. One difficulty is providing a quantitative measurement for SWB, while subjective measures of life are internal [10]. We tried to modify the local expression of SWB. After controlling the important variables, there was an urban-outskirt difference in SWB. Results showed that city dwellers were statistically happier than the second group. This difference needs to be considered by decision-makers and researchers to find possible reasons.
In recent decades, there has been a huge amount of immigration from a rural area or small towns to urban areas and some have lived in the outskirt of metropolises due to higher expense of living, especially housing expense in metropolises. They choose to live in cities due to seeking for more income and better job opportunities, which are key to migration decisions [10]. Respect the choice of whether to migrate or not, all those who find more attractive income and leisure combinations in another land will leave [31]. Secondly, in the standard economics view, individuals are considered to have no self-control problems; they can make decisions that are following their long-term preferences. Limited willpower to the process of decision making, lack of self-control, and self-regulation can reduce SWB and fall the happy feeling of people [32, 33]. These arguments can be a clue for the researchers to find more reasons for the lower level of happiness among the outskirt dwellers.
Apart from the district of living, financial satisfaction is the most influential factor in happiness. Our outcome is that taking relative earnings thoughtfully is an important step towards greater behavioral realism in economics, such that our models and empirical analysis move closer to how real people feel and behave [31, 34]. Also, in developing countries, measuring income is difficult because most respondents work in informal sectors; thus, they cannot report a fixed salary [12]. To overcome these problems, in addition to questions about wage and another source of incomes, as the second contribution of this study, we asked about relative financial satisfaction and used it as a factor for showing financial status; outskirt dwellers had less financial satisfaction (mean=2.96) compared with city dwellers (mean= 3.41 out of 7). This difference could be explained by the result of some studies that concerned relative income, comparison effect, and aspirations [12, 21, 22, 28, 31, 34, 35], which emphasize the negative effect of relative status on SWB.
Most of the literature shows that the upper level of education can improve SWB, but there are a few studies, which show that educated people are less happy than the others [9, 10, 15, 22, 36]. One of the controversial results of this study is that people who have academic educations are less happy. It may happen because of the unemployment rate of educated people. Data analysis regarding the unemployment rate in Economic Research Deputy, Iranian Centre for Statistics Collection shows that there has been an upward trend in recent decades. Furthermore, according to the last formal Iranian census report, the unemployment rate of educated people in Gilan province (Rasht as the center of the province), is equal to 22.3%; 12 out of 31 provinces had the highest unemployment rate for educated people (maximum and minimum percentage are 34.9 and 12.5, respectively). Consequently, the people who have spent some years in universities hoping for better welfare circumstances and income, have not been successful in finding a proper job or job, which is related to their education. Then, they are not satisfied with all the years spent to increase their human capital and they are less happy than the others.
Another surprising result is related to employed people. The marginal effect of the employed variable is almost statistically negative. It means that the people who have a job are less happy than the second group. Examining this result, we replaced the active variable to separate the effect of active unemployment people from cases who did not seek for a job and are in the passive population (being responsible for housework, student, retired and unemployed who quit of seeking for a job) and repeated estimations with this revision in variables. All estimations remained almost equal to previous ones. The marginal effect for active people was negative, like employed people. All these results show that those who have a job are less happy than the others. This result is almost on the contrary to previous studies [9, 10, 21, 22,]. This result can be caused by job security and working situation, including stress and dissatisfaction, especially with income. In the survey, we asked people about their job security. Their average score for this index was 3.15 out of 6, which means that employed people feel job insecurity. It may be an explanation for their lower level of happiness.
We used multidimensional positive and negative life intangibles’ feelings and emotion indices according to the Gallup Global Emotion Annually Report definition. Having more positive feelings can raise the SWB of people. This result is in accordance with what we expected and the inverse relationship was found for negative emotional index [37].
In most literature, there is a gender difference between the level of SWB [9, 10]. Our results showed that the average level of SWB of women who live in the city is higher than similar men. It is the same for the SWB of women living outskirt. Also, women in both the city and outskirt areas are more satisfied with their house location and their financial status compared with the men. They also feel that they are healthier and more religious.
Religious belief had a positive impact on the SWB level in some studies, and negative in other studies. Our results showed positive effects. People who had higher religious beliefs tend to have an upper level of SWB, due to better adaption with life circumstances [38] and this adaptation leads to the upper level of happiness [7]. Some types of religious beliefs, behavior, and cognition foster self-regulation and, more specifically, self-control, and consequently increase the SWB level. Religiousness was positively associated with SWB and measures of positive psychological outcomes, such as satisfaction with life and happiness, and negatively associated with measures of negative outcomes, such as anxiety and depression [39].
Implications for making policy must be taken cautiously. This study has some limitations to claim cross-sectional study to the total population. Our findings highlight the necessity of improving people’s financial status to increases people’s level of happiness. But, this study cannot investigate the path to increase people’s financial satisfaction. Furthermore, the timing of income changes and external shock in Iran according to the current high inflation rate and US sanctions is another source of skepticism toward our results and the current situation will become even worse. The empirical prediction from the loss aversion hypothesis of Tversky and Kahneman is that the absolute effect of losses is more powerful compared with equivalent gains [40].
5. Conclusion 
sht are less happy than city dwellers. Women who have better health, financial status, satisfaction with their living area, and also those living with a partner in a more spacious residence, which belongs to them are happier. Educated people with a job or seeking a job had a lower level of happiness. More religious people tended to be happier. Two exclusive contributions of this study are defining two indices for SWB and financial circumstances according to Iranian culture. Importantly, data were collected in early 2018, while currently, Iran faces an economic crisis due to the US sanctions. This has a considerable effect on not only Iranian’s financial satisfaction, as an important determinant of happiness, but also on the marginal effect regarding ‘external shocks’ on people’s perception about their own well-being. In the future study, it would be advisable to implement this questionnaire to evaluate a new level of satisfaction and SWB of people.
Ethical Considerations
Compliance with ethical guidelines
This study was approved by the Ethics Committee of Tarbiat Modares University (Code: IR.MODARES.REC.1398.219).
Funding
This article is extracted from the PhD. dissertation of first author at the Tarbiat Modares University (Approval Code: 72D/1447 dated October 27, 2017).
Authors' contributions
All authors equally contributed to preparing this article.
Conflict of interest
The authors declared no conflict of interests.


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