Why do People Love their Country?
Loving one’s country is the expected result of being a citizen, nevertheless, this feeling may be conditioned to certain factors.
Emotional attachment to one’s country: an investigation of citizen’s feelings
This research further explores certain factors that can grant an explanation of why some people feel more emotionally attached to their country than others. To investigate this topic, the European Social Survey, (ESS8 2016/2017 version) has been used. This survey includes the participation of multiple European Countries, more specifically: Austria, Belgium, Czechia, Estonia, Finland, France, Germany, Hungary, Iceland, Ireland, Italy, Lithuania, Netherlands, Norway, Poland, Portugal, Russia, Slovenia, Spain, Sweden, Switzerland, United Kingdom. Consequently, the analysis and conclusion of this paper will have an emphasis on European society.
To explain what this research is trying to achieve, the Netherlands will be used as an example of the relationship we are looking for. The Netherlands is considered to be a very happy country, one of the happiest in the world ranking at number 5 according to studies (Hunter 2023). This fact is not hard to believe since studies undertaken by the OECD demonstrate that the Dutch population is overall satisfied with how the government manages public services (OECD 2015). Their fact sheet “Government at Glance 2015” indicates that satisfaction with health care is high at 86%, and education at 78% (OECD 2015). Coincidentally, the levels of attachment Dutch people have with their country are also high. The Statista Research Department’s investigation from 2015 indicates that 39% of the Dutch population feel “fairly attached” to the Netherlands, while 47% feel “very attached”, meaning that 86% of the Dutch population has a sense of attachment (Statista 2015). In order to deepen our knowledge of this possible relationship, the following question has been formulated: what is the relationship between individual satisfaction with their national government and their level of emotional attachment to their country?
The research question allows us to explore the relationship between the satisfaction of the national government and the level of attachment in hopes of understanding possible factors that can influence citizens’ feelings toward their country. The knowledge of understanding citizens’ feelings is what englobes the social relevance this research presents, which is explaining how 3 people can be influenced into developing feelings towards their nation. Ideally, if we discover that there is a relationship, highlight the idea that governments should work harder in attending to the needs of society so they can build a strong country with a sense of attachment, belonging, or pride which can lead to cooperation and appreciation of the nation. The academic relevance this research holds is to present literature that can provide future researchers with a variable to explore, which is the level of satisfaction with the government when investigating human behavior towards their country.
As regards to how this investigation is going to answer the research question, the following section will present the hypothesis. It will also explore other factors that can explain the relationship with the presence of a mediator and moderator. Next, a section dedicated to explaining the variables will detail how these were operationalized and used within the database as well as describe the research design. There will also be a display of the analysis that will showcase the findings, ending with a conclusion that will subsequently answer the question based on the interpretation of the analysis.
Theory and Hypothesis
Firstly, to understand the hypothesis that is going to be presented, it is important to understand the concepts that are going to be key elements of the investigation. For the purpose of this investigation, “satisfaction with the national government” will be conceptualized as the level of satisfaction a citizen feels with regard to the performance of the national government. This conceptualization entails that the national government englobes the policies the executive branch undertakes as well as their role in overseeing the ministries and their functions, such as healthcare in relation to the Ministry of Health, or how the level of education is the concern of the Ministry of Education. This conceptualization expands to countries with different systems from the presidential, such as countries with active royalties; we will use the Netherlands once again to clarify. The Dutch national government has an active royalty as it is a Constitutional Monarchy, which “means that the head of state is a King or Queen whose powers are laid down in the Constitution” (Government of the Netherlands 2023). A Prime Minister is responsible for what the government does, and the “government consists of ministers and state secretaries” (Government of the Netherlands 2023). So, countries with non-presidential systems that present ministries are 4 contemplated under the conceptualization because of the presence of a bureaucracy. On the other hand, the conceptualization of “emotional attachment to the country” concerns the emotional connection citizens feel toward their nation, this involves national identity and pride. Having clarified these concepts, the following hypothesis is formulated:
The national attachment to your country depends on how satisfied you are with the national government.
This hypothesis clearly claims that there is a relationship between emotional attachment and the national government. The theory behind why this is the case follows the next logical sequence. The national government is the representation of the country both domestically and internationally. Based on their policies and management of resources for the betterment of the country. The administration in charge can deliver results that can make the citizenry happy, as well as upset them. The results can involve policies that can interfere with the welfare of the nation, incompetence of ministries to, for example, worsen the educational system or healthcare, and even present cases of corruption. This can lead to people feeling ashamed of the representatives of their country and therefore reducing their pride or more specifically the level of attachment to their country since it does not contribute to a better lifestyle. This can also be the contrary, if a government delivers results such as better education, better classrooms, and projects for employment, among others, it produces a sense of pride and makes people connected to a country that contributed to their lives.
Nevertheless, it is important to take into consideration the possibility of a mediator that can further explain the relationship this investigation studies so that the results can be more accurate and decrease the chances of providing false claims. The mediator will be the ‘satisfaction one has with the state of the economy in the country’. The reason why this was chosen as a mediator is that IMF reports depict that economic development is considered a factor that can increase the overall happiness of a nation (Bala et al.: 2021). This claim is also not hard to believe since economic growth allows the government to present a bigger fiscal budget that can be invested in social projects. Additionally, economic growth provides people with the satisfaction of meeting their needs (food, rent, etc.), as well as enhancing the population’s economic freedom. Taking note of the fact that a scenario of a bad economic state such as inflation or recession leads to people suffering from unemployment, lack of access to services, and an overall impact on their everyday 5 lifestyle, it is intuitive to argue that a bad economic state will provoke the feelings of hate, shame, or disgrace over one’s country; consequently, a good economic state would generate positive feelings.
Moreover, to provide a deeper analysis of the investigation, this paper wants to identify if certain variables vary under different conditions. For this reason, a moderator has been selected to identify if the relationship changes under the presence of an interaction. In this circumstance, the moderator is going to be the presence of democracy. The reasoning behind this choice goes along with the claim that the lack of democracy is usually associated with a corrupt system that wishes to stay in power such as a dictatorship or autocracy, where its survival depends on censorship and control of mass media (Guriev and Treisman 2015). Under censorship and with a non-democratic party in power, citizens are pressured to approve and support the only party in government, therefore, their high levels of national government satisfaction would be forced and their emotional attachment to the country an artificial feeling.
Research Design
The dependent variable is ‘emotional attachment to the country’. The ESS asks respondents how emotionally attached they are to their country. The Independent variable concerns respondents to rank their level of ‘satisfaction regarding their national government’. The mediator is ‘satisfaction with the national economy’. The respondents answered: “How satisfied you are with the present economy in the country”? The measurement of all three variables are operationalized as intervals from 0 (0 = “extremely dissatisfied”) to 10 (10 = “extremely satisfied”), which are considered continuous variables. The moderator is ‘satisfaction with democracy’, also ranked their answer on the same 0 to 10 scale as the previous variables. This variable has been recoded into a dummy variable to differentiate outputs between subgroups. In the new (recoded) variable, the measurements indicate that the interval from 0 to 4 (new value: 0) refers to low democracy, while the interval from 5 to 10 (new value: 1) refers to high democracy. This research utilizes three control variables. The first one concerns religion, where respondents answer: “How religious are you?” on a scale from 0 (0 = “not at all religious”) to 10 (10 = “very religious”). This control variable has been chosen since the level of religiousness in society can impact the way they feel about their country, for example, a Catholic feels connected to Italy due to its history with 6 Catholicism. The second control variable the ESS gathers information on the ‘household’s main source of income’. It classifies them into different categories such as wages, investments, or grants, which protect the relationship from individual cases where the sample instead of criticizing the overall economy, they are troubled with (for example) the wages their employers put on them. The third control variable measured the respondents’ ‘placement on the left-right scale, this scale is measured from 0 (0 = “left”) to 10 (10 = “right”), for the possible influence of bias.
Evidently, this investigation uses a cross-sectional research design, which involves “analyzing a sample, or cross-section, of a population at a single point in time” (Halperin and Heath 2020: 165). This research design is characterized by its strong reliability, this applies to this research since the use of the ESS8 database can be easily accessible to other researchers who can perform the same calculations in the same SPSS program and would be very likely to achieve the same outputs as the ones the next section is going to illustrate. Besides, by having surveyed such a big geographical area, the large sample that was drawn increases the chances of a random sample. The large sample size also contributes to a high external validity. The ESS sample size involves diverse samples from different countries, this also increases the chances of a representative sample of the population that is being studied and reduces the risk of selection bias. Nonetheless, it is important to consider the possible challenges a cross-sectional research design may present. It is usually associated with having a low internal validity. Alternatively, there are methods by which the uncertainty of the outputs of the variables’ relationship can be reduced. The control variables protect the outputs from possible variables that may influence the significance of the relationship or alter the scenario to other interpretations of the causality. To further explore other possible explanations, the mediator is used and can offer a deeper understanding of how the dependent variable is affected, or the steps the independent variable requires to reach the dependent variable.
Analysis and Interpretation
Having discussed the operationalization of the variables and research design, this section will portray the outputs of the relationship between the variables through the construction of multivariate linear regression models. A table will display the outputs of three models that were constructed, the first model will explain the relationship between the dependent and independent variables alongside the control variables. The second model introduces the mediator, and the third 7 model displays the moderator as well as a scatter dot graph that visualizes the interaction. For matters of transparency, Appendix A contains the steps taken in SPSS to achieve the outputs. The first model that this section is going to explore is Model 1. This model seeks to find the answer to whether there is an existing relationship between the dependent or independent variables. Therefore, a regression model has been constructed where a significance between the independent and dependent variables will determine a relationship; not forgetting the presence of control variables.
Table 1: Effects of satisfaction with the national government on emotional attachment to country
Model 1 of Table 1 shows that there is a significant relationship between the independent and independent variables. More specifically, their relationship would be considered ‘very significant’ having <0.001 as statistical significance. The model also reveals that there is a positive relationship, meaning that the higher your satisfaction with the national government, the higher is going to be your emotional attachment to your country, more explicitly, it increases by 0,235. It is also worth noticing that the control variable of religion is also very significant. Even though the other two control variables are not significant, the religion variable by being significant means that independently of the model, it has some influence over the dependent variable. By having it as a control variable, its influence got separated from the outcome, hence it increased the internal validity of the research.
Another element to look for is the R2 which is the explanatory power. In this model, that element has a value of 0,083. This means that 8.3% of the observed variation in the dependent variable is explained by the independent variable. There is still a current debate on how important the need for a high R2 in different sciences is, it is also important to acknowledge that the one this model produced is considered low, and therefore the relationship between the variables remains uncertain. This element does not take away the fact that the coefficients do present a high significance. To formalize this result, the output is going to be constructed in the following formula:
When we add the values, it takes this shape: Level of attachment to country = 5,302 + 0,235 x satisfaction with government + 0,092 x religiousness + 0,032 x left-right placement + 0,028 x main household income + e
On the other hand, Model 2 has the presence of the mediator. The main element to be on the search for is if the mediator actually ‘mediates’ the relationship, which occurs when the coefficient of the independent variables is modified by its presence in the regression. As previously theorized, the mediator has a level of influence in explaining the relationship, and it is proven by observing the change of the independent variable’s coefficient drop from 0,235 to 0,211 (remains a positive relationship).
However, the mediation coefficient is not significant as it is displayed in Table 1, and the coefficient of the independent variable of Model 2 is still very significant. As a result, we cannot establish that ‘satisfaction with the present state of the economy’ is a full mediator. Instead, the interpretation that is drawn from this result is that the ‘economy’ variable is a partial mediator. This means that it does not explain the entire relationship between the independent and dependent variables, and there may be other factors between these two variables that explain the relationship. Simultaneously, the R2 of this model has been modified, the explanatory power is now of 8.6%, an increase of 0.3% from Model 1. This R2 is still considered low, but it does not interfere with the result of discovering a partial mediation and the current significance between variables.
To formalize the results, the mediator variable will be included in the formula: Level of attachment to country = 5,302 + 0,235 x satisfaction with government + 0,092 x religiousness + 0,032 x left-right placement + 0,028 x main household income + 0,059 x economic satisfaction + e
Moreover, Model 3 represents a regression that includes the moderator (without the mediator). This is with the purpose of identifying if there is a difference between subgroups once we add an interaction variable. As previously stated, the variable was recoded and is visible in Table 1 as ‘democracy dummy’, which presents two categories: low democracy and high democracy. Once it was multiplied by the independent variable, the moderation was added to the regression. The outputs show that the moderation has no significance. This means that the variable of democracy does not moderate. Therefore, there is not really a difference between people who perceive the country’s democracy at a low or high level in regard to the relationship between the variables. Nonetheless, this paper will still interpret a graph that visualizes the outputs of the moderation variable that was achieved through a plot interaction as if it were significant.
Graph 1: The interaction of the ‘democracy’ variable
This graph depicts that both groups 0 (low democracy) and 1 (high democracy) have a positive trend line which means that the more satisfied they are with the national government the more emotionally attached they are going to be to their country regardless of a low or high satisfaction of democracy. They engage in what would be considered a somewhat medium-low interaction (not strong but also not non-existent). However, the difference is that individuals who are more satisfied with democracy tend to be more emotionally attached when their satisfaction with the government increases than those who are not satisfied with democracy. Although, it is important to remark that the moderation is not significant, so the interpretation of the graph is not important for the interpretation of the outputs.
Before transitioning to the final section of this paper, it is also important to mention that all the models passed a collinearity test. Hence, criticism regarding variables being closely related is shielded by the variables scoring higher than 0,20 in the SPSS tolerance diagnosis.
Conclusion
In essence, the answer to the question: what is the relationship between individual satisfaction with their national government and their level of emotional attachment to their country? The findings of this research demonstrate that there is a positive relationship between the independent and dependent variables, the more a person is satisfied with their national government, the more emotionally attached they are to their country. This is concluded because the independent variable’s coefficient is significant in Model 1. Likewise, Model 2 presents the ‘economical’ variable, the findings indicate that this variable is a partial mediator, which contributes to the depth of the research by further investigating other pathways that explain the hypothesized relationship. Moreover, Model 3 attempted to identify an interaction effect with the ‘democracy’ variable, this one was found not significant and therefore it does not influence the relationship of variables.
The positive takes of this investigation are the reliability and external validity. By using a respectable and easily accessible database to build the models, its replicability becomes feasible and would very likely lead to the same results. Additionally, the large sample size contributes to the diversity of the survey, which translates to a representative sample that increases the chances of this study being generalized among European society successfully. In contrast, some limitations were encountered such as a challenged internal validity. Even though a cross-sectional design by default has issues with internal validity, this research utilized control variables to limit the influence of other variables over the dependent and independent variables. Additionally, neither of the models presented a high explanatory power. The low R2 questions the causality by keeping the relationship between the variables uncertain. Nonetheless, the importance of acknowledging the challenges leads to transparent research.
Bibliography
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