Antecedents of Religious Tolerance in Southeast Asia

Abstract

Southeast Asia is home to a religiously diverse population. Malaysia and Brunei have a Muslim majority, Philippines has a large Christian population while Myanmar, Thailand, Cambodia and Laos have a large Buddhist population. In recent years, the region has seen an increase in faith-based tension with communal violence in Myanmar and insurgencies in southern Thailand and the Philippines, which conspicuously exemplifies the rising religious intolerance in the region. The social dynamics at play in these instances highlight the importance of trust and tolerance within the community for a harmonious existence. The current study is a comparative analysis to gauge the factors influencing religious tolerance in Southeast Asia. The study employed the tolerance conceptual framework with the identity economics and the social comparison as the overarching theoretical framework. The findings reveal that countries in Southeast Asia experiencing religious conflict were reporting higher level of religious tolerance. Interestingly, Malaysia a country without any faith-based conflicts, was recording higher religious intolerance. This indicates that a façade of tolerance might guise the actual reality on the ground. And incidents of faith-based conflicts might be wrongly perceived as an indication of rising religious intolerance within a society.

Appendix 1

The utility estimation from the decision making process was expressed in the function below

$$ \begin{aligned} U^{i} & : \propto_{1} g_{i}^{2} - \propto_{2} g_{i} + \beta_{1} s_{i}^{2} - \beta_{2} s_{i} \\ & \quad + \chi_{1} g_{i}^{2} s_{i}^{2} - \chi_{2} g_{i} s_{i} + \delta_{1} \psi_{i}^{2} - \delta_{2} \psi_{1} \\ \end{aligned} $$

(3)

The self-positioning in an income group is denoted by $g_{i}$, while $s_{i}$ is an evaluation of the quality of the social environment, the interaction term $g_{i} s_{i}$ expresses the synergy between comparison in income and the perceived quality of the social relationship while $\psi_{1}$ is a vector of other potential determinants of utility. The perceived quality of the social environment was expressed as:

$$ s_{i} = w_{1} tol^{i} - w_{2} c^{i} $$

(4)

The perceived quality of social environment is expressed as influenced by degree of tolerance ($tol^{i} )$ and the predisposition towards tolerance or confrontation ($c^{i}$). Dima and Dima (2016) elaborates that Equation (4) captures the attitude of balance between tolerance and confrontation. Stating that an individual might be tolerant to one religious group but intolerant towards another or express preferences for certain behavior in public but intolerant in private life. Equation (4) was substituted in utility function (Equation 3). After having derived the new utility function, they proceeded to differentiate tolerance against utility to obtain the optimal level of tolerance that maximizes individual utility. Therefore, the optimal tolerance level was given as:

$$ tol^{opt} = \frac{{\beta_{2} w_{1} + \chi_{2} g_{i} w_{1} - 2w_{1} w_{2} \left( {\beta_{1} c^{i} + \chi_{1} g_{i}^{2} } \right)}}{{2w_{1}^{2} \beta_{1} \left( {1 + w_{1} w_{2} c^{i} + \chi_{1} g_{i}^{2} } \right)}} $$

(5)

In order to enhance the explanatory power of this framework, Dima and Dima (2016) suggested incorporating subjective factors $\left( \vartheta \right)$ into the framework. The present study incorporates two subjective factors; individual religiosity and social religiosity. The influence of these two subjective variables on predisposition towards tolerance and confrontation is expressed as follows:

$$ c^{i} = c^{i} \left( {\vartheta^{i} } \right) $$

(6)

Taking into consideration the impact of these two variables, the optimal level of tolerance for the present study is re-written as:

$$ tol^{opt} = \frac{{\beta_{2} w_{1} + \chi_{2} g_{i} w_{1} - 2w_{1} w_{2} \left( {\beta_{1} c^{i} \left( {\vartheta^{i} } \right) + \chi_{1} g_{i}^{2} } \right)}}{{2w_{1}^{2} \beta_{1} \left( {1 + w_{1} w_{2} c^{i} + \chi_{1} g_{i}^{2} } \right)}} $$

(7)

Equation (7) shows the optimal level of tolerance which maximizes individual utility after the inclusion of the two subjective variables.