The Salary Structure and Factors of Salary Disparity of Imam in Bangladesh: A Cross-Sectional Study

The Salary Structure and Factors of Salary Disparity of Imam in Bangladesh: A Cross-Sectional Study

Rakibul Hasan^*, Muhammad Rabi Ullah, Umme Sumaiya Shampa, Faysal Ahmed Shaon

Department of Economics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University (BSMRSTU), Gopalganj – 8100.

^*Correspondence Author

DOI: https://doi.org/10.51244/IJRSI.2024.1108075

Received: 02 August 2024; Accepted: 10 August 2024; Published: 12 September 2024

ABSTRACT

Imams, as a profession, lagging far behind any other formal or informal profession in terms of work prospects, wage structure, and so on. This research aims to empirically investigate the factors influencing the socioeconomic level and salary disparities of imams in Bangladesh. In this case, we collected data applying questionnaires over a 6-month period. Questionnaires were distributed to 300 Imam who participated in the study voluntarily with oral consent. For quantitative data, we apply a multiple linear regression model, whereas qualitative data is analyzed using descriptive analysis and pivoted chart by using Microsoft excel and SPSS v25.In this research, most imams (61.7%) are between the ages of 21 to 40, 65% have large family. Average income of the respondent is about 10,045 BDT where 62.7% imam fall into lower income group (0-9990) although they all are educated in different level. 64.3 percent of imams have an oral job contract where 69% imam doing their job in full-time basis. In our study, 82% mosque is paka means build by bricks.

The investigation reveals the existence of statistically significant salary differentials in Imam. Prior to run the multiple linear regression model we test our assumption like linearity, multicollinearity, normality of u_i, homoscedasticity, outlier by box plot. In our regression model, the salary (dependent variable) is significantly depends on explanatory variables like education level, education type, job contract, location of the mosque and type of mosque that is statistically significant at 5% and 10% level. The R² value of this model is 0.269, indicating that approximately 27% of the variation in the dependent variable can be explained by the independent variables. The F-ratio in the ANOVA table indicates that the independent variables have a statistically significant predictive effect on the dependent variable, with F (3, 8) = 19.794, p (.000) < .05 (meaning that the regression model fits the data well).

Key words: Salary, Imam, Cross-section, Disparities, Socioeconomic Status, Bangladesh.

INTRODUCTION

According to population and housing census 2022, Bangladesh is evidently a Muslim majority country where 91.04 percent of 165.16 million people are Muslim. It is necessary for every Muslim society to pray at the mosque. In these circumstances according to Annual report 2020-21 of Islamic foundation, Bangladesh has around 3,13,395 mosques. Essentially each mosque has at least an Imam and he is counted as a paid full time or part time worker. Then there is minimum 3,13,395 people associated with Imam occupation which is significant amount of our work force as well as society.

BACKGROUND OF THE STUDY

According to the report of BANBEIS (Bangladesh Bureau of Educational Information and Statistics), Bangladesh is a South Asian developing nation. Bangladesh is widely considered a moderate Muslim democracy with 89.7% Muslims, 9.2% Hindus, 0.7 % Buddhists, and 0.3 % Christians. 0.1% of the population are animism and tribal religious adherents. Islam serves as the religio-cultural identity of the predominantly Muslim country. Among the country’s Muslims, the majorities of Bangladeshis are Sunni, and follow the Hanafi school of Fiqh.

An important hub for religious activity in Bangladesh is the mosque. Rashiduzzaman (1994), investigated that there are an estimated 133,197 mosques in the nation’s 65,000 communities, which serve as hubs for assemblies and daily and weekly prayers. According to the census of 2022, Bangladesh is a densely populated country with 165 million where about 91.04% of its total population identifies as Muslim and about 88% people are employed in informal sector. Simultaneously Muslims are directly relating to the mosque body and soul because they say their everyday prayer at mosque. The term “mosque” originates from the Arabic word “Masjid,” this refers to a sacred place for prayer. In other words, the Imam, who is the religious leader of the mosque, leads the prayer, and mosques function as the central hub of the Islamic religion. An imam’s primary duty is to promote a progressive, harmonious, and collaborative society by forecasting religious principles and ethics. However, imams in mosques significantly fall behind in all aspects of progress.

Imam, Arabic Imam (“leader,” “model”), in a general sense, one who leads Muslim worshippers in prayer. In a global sense, imam is used to refer to the head of the Muslim community (ummah). (Zeidan,1998)

Within the Muslim community, a religious leader is known as an ‘imam’ who primarily leads congregational prayers in the mosque setting. However, imams often take on additional roles within the Muslim community, including pastoral and advisory roles, conducting marriage ceremonies, teaching Islamic studies. Indeed, they are often regarded as spiritual role models. (Mustafa & et al, 2017).

Concepts of Imam, job nature& their responsibility

Generally, Imam is widely used to designate the official who leads prayers in mosques beside this their major duties are learning the Holy Quran and Namaz, providing religious guidance through Khutba, conducting Janaja (prayer for the dead body). Almost all imams work in the informal sector. This sector is described as ‘low wage’, ‘small and family-based’, ‘freedom of entry’, ‘lack of a secure employer-employee relationship’, and ‘being neglected by the authorities, while imam is not far from these features’. Shahjahan (2022), reported that most Imams are paid by the mosque management authority, not the national mosque’s government-funded Imam. Because they earn less than other workers, most Imams have lived below the poverty level since they started.

Imams’ monthly wages vary by country, according to the report of www.zippia.com. Imams in wealthy countries like the US and Saudi Arabia earn much more ($34,422 and $3047, respectively). Bangladesh’s $74 and $168 average salaries are much lower. This gap is largely due to economic progress, living standards, and religious leader government remuneration. Pakistan’s mean income is $278 and Dubai’s is $2506, both median. The data above shows church leaders’ different social, economic, and cultural backgrounds globally.

Rationale of the study

Bangladesh is primarily a Muslim nation. Consequently, imams are becoming more involved in the workforce as well as being important to Bangladesh’s perception as a Muslim-oriented nation. They continue to perform their jobs on time, but they do not receive a generous pay that would enable them to support themselves. The fact that so little research has been done on the pay scale and socioeconomic standing of imams raises serious concerns. In order to examine the social and economic circumstances of an imam, this topic was selected. It’s a chance to learn about them, hear what they have to say, and work together to address their social and economic problems.

Problem Statement

The first quarter of Labor Force Survey 2023 shows that, Bangladesh’s labor force has expanded to 73.69 million. Up to 80% of workers are unorganized. Gazi (2020) examined rural imam income qualitatively. Despite society’s reverence for Imams, he fell far behind economically. In addition, they have no wage scale like other professionals. Most imams have meager wages that cannot support their lifestyle and family. These positions have poor job security and perks. The research aims to discover dynamic elements that affect imams’ remuneration structure and socioeconomic status and provide solutions. Addressing their key concerns and providing solutions can help. By raising public awareness, government and non-governmental organizations can solve imams’ challenges.

Research Objective

In this paper, we attempt is made to answer the following questions about the Imam of Bangladesh. Is the wage difference due to education, experiences, age, and location of the job and so on. That is, is wage rate based on age of the worker. In our research paper, we have defined certain particular objectives to determine the answer to the research questions. The specific objectives of this study are:

1. to analyze the socioeconomic status of Imams in Bangladesh
2. to describe the different reasons of salary disparities of Imam in Bangladesh
3. to find out the major job facilities and challenges facing by the Imam
4. to suggested some policy recommendation for their betterment

LITERATURE REVIEW

In formal and informal sector, wage disparity and salary structure has been discussed nationally and internationally by a great number of authors in literature in many ways. Regarding the contribution of imams and their salary, there is a few number of research available where mainly discuss on Imams’ socio-economic status, role of mosque or Imam in the society and so on.

Micer. J. (1970) carried out an empirical investigation into the labor market and human capital that was directly related to the salary distribution. This study examined the human capital earnings function, a single-equation model used in empirical economics to explain wage income as a function of various independent variables. In another paper published in 1974 determines that earnings variation is significantly interpreted by years of experience rather than age. Schaffer and Luke (2000) conducted a study and applied an empirical method for investigating wage determination criteria in Russia. This empirical investigation had addressed a practical problem faced by many researchers during conducting econometric analyses using data. This problem is known as outlier. The researcher had employed a wide range of econometric methods of outlier detection and robust estimation to deal with the outlier problem.

DS Saini (2010), research has been made to comprehend the socioeconomic status of imams and the challenges that they encounter in both the organized and unorganized sectors. The author has researched the conditions of imams employed in the unorganized sector, the challenges they encounter with social security, and how they establish themselves there. M Abuelezz (2011), investigated the principal duties, qualifications, and challenges of imams in America.

A Salie (2012), revealed that job satisfaction in terms of how imams feel about their jobs and different aspects of their jobs in Netherlands. He argued that the job satisfaction and dissatisfaction not only depends on the nature of the job, it also depends on the expectation what kind of facility he gets and what amount of salary and bonus he receives. This can be positive and negative depending on the achievement of the expectations and desires. If the expectations and desires many achieved then an imam will feel job satisfaction.

It has been explored in prior studies by Abdul Karim Gazi (2020) and M.A. Ali (2013) shows that socioeconomic status of imam and identified that the Imams get the honor from the society but economically he remains far behind.

Nazrul Islam (2020), suggested that job facilities like housing, water and sanitation conditions, wages, social status, adaptation of cultural values and norms are significantly related to the socio-economic status imams of Bangladesh. S A Noor (2022), studied about the Covid 19 effect on the informal sector job like imams in a mosque. This condition has reduced the mosque’s financial income and experience financial depletion.

METHODOLOGY

Every study is a series of activities which are logically and operationally link together. Preparation of working procedure or scheduling comes after developing goals and objectives. It refers the process that how the study will be conducted.

Data Collection and Sample Size

The cross-sectional study was conducted in different areas of Bangladesh because the respondent, who is an Imam, is related to the mosques that are scattered. In rural areas, mosques are usually built per village where in urban areas mosque is built based on population density. A survey has tried to cover both rural and urban areas in Bangladesh. The survey data were collected from primary and secondary sources. The primary data were cross-sectional in nature and consisted of the use of a structured questionnaire. A survey of respondents was conducted to collect data primarily on salary structure, socio-economic characteristics and job nature, job facilities as well as challenges. Secondary sources of data collection were from different journal articles, newspaper, Islamic Foundation of Bangladesh.

The sample is the segment of the population that helps us make conclusions about the population. We therefore need an appropriate sample size in order to make population inferences based on this sample. There is no general rule for specifying the sample size. In the determination of the minimum required sample size the number of explanatory variables is important. Maxwell (2000), suggests that sample sizes of 100 in behavioral research may leave the door open for publication when all variables correlate with one another at a medium level. He also states that ‘‘sample size will almost certainly have to be much larger for obtaining a useful prediction equation than for testing the statistical significance of the multiple correlation coefficient’’ Miller and Kunce (1973) suggest that a ratio of 10 to 1 is sufficient. As Harris (1985) and Wampold and Freund (1987) have pointed out, historically the most common rule seems to have been that the ratio of TV to p should be at least 10:1. Different applications of multiple regressions usually require different minimum sample sizes (Brooks &Barcikowski, 1995, 1996; Casciok et al., 1978; Darlington, 1990; Gross, 1973; Pedhazur, 1997; Tabachnik & Fidell, 2001). In general, in regression analysis, many researchers usually used at least ten observations per variable.

The data was collected in a 6-month period from September, 2021 to February, 2022. The data was collected through a close-ended questionnaire. Ten 4^th year university students were recruited to collect the data in the selected areas. The students were trained on techniques of data collection and interviewing. A pre-test of the questionnaire was done after some adjustment data was collected for 300 Imam as a respondent in the sample.

Data analysis and Model Specification

In this study a simple multiple regression model is used. In determining wage or salary of any profession, it is important to know to which extent other characteristics do. To find out the salary disparity of our Imam which is one of the major objectives of our project, we will use the econometric model. The origin of the wage function developed by Jacob Mincer and which is one of the most widely used human capital earnings function which is a single-equation model that explains wage income as a function of different independent variable in empirical economics. General theoretical form of econometric multiple regression model is:

Salary= (education level, education type, job contract, location of the mosque, types of mosque)

The functional form of the dependent variable determines basic statistical properties of the wage equation and both qualitative (categorical) and quantitative independent variable which guides interpretation of the results. Economists widely agree on logarithmizing the wage variable because of comfortable interpretation of coefficients. But we use the normal form of salary and for categorical independent variable we use dummy.

Yi = β_{0 +} β₁ X_1i + β₂X_2i + β₃ X_3i + β₄ X_4i + β₅X_5i+ ui

Salary (Y) = β_{0 +} β₁ (X₁) + β₂ (X₂) + β₃ (X₃) + β₄ (X₄) + β₅ (X₅) + u_i

Variable Nature	Coded
Dependent Variable
Salary	Monthly salary (in BDT) given by the mosque authority
Independent Variable
X1 (education level)	Five level of formal education.
X2 (Qawmi education)	Education Type, Qawmi for 1, Aliya for 0
X3 (Oral Contract)	Job contract, Oral for 1, Written for 0
X4 (Mosque location Rural)	Location of the mosque, Rural for 1, Urban for 0
X5 (Mosque Type_Kacha)	Mosque Building type, Kacha for 1, Paka for 0

Here the X₅ = The types of mosque used as the proxy variable of society’s income percapita which influences the salary of Imam. Kacha mosque type determines the low socioeconomic status and paka mosque structure indicates relatively high income per capita of the society.

Ethical Consideration

The Research Center of Bangabandhu Sheikh Mujibur Rahman Science and Technology University in Gopalganj, granted ethical approval for this investigation. All individuals gave their informed consent (voluntary participation) prior to the start of data collection. Every piece of identifiable information was removed from the data in order to protect participant privacy. Information was safely reserved to the writer.

RESULTS AND DISCUSSION

Socio-economic and demographic Status of Imam

This chapter of the study will discuss the basic characteristics of Imam and related features and also present a descriptive analysis of some statistics gathered through the survey. The primary objective of our research is to identify different demographic status of Imam. Before determining salary structure of this profession, we should to know their socioeconomic profiles, job nature, types of mosques, and location of their job and so on.

In terms of individual characteristics, the average age of reporting respondents is 39 years old, while about 62 and 34 percent Imam lies on 21-40 and 41-60 age group respectively. Among them 88 percent were married and rest of them which is 12 percent were unmarried. Majority of the respondents (68.7%) were belonged into large family contain 5 to 12 members. About 54.7 percent Imam earn alone in their family. The average monthly salary given by the society or mosque authority is only 10,045 BDT where 188 out of 300 respondents fall under the lowest group of income level (0-9999) which is 62.7 percent. Negligible number of imams gets the monthly salary above the 30,000 BDT which is only 2 percent.

All Imams engage with mosque and their job nature and salary structure is different from other profession especially working hours, number of attendants, type of mosque, location of their job or mosque and so on. Table also shows that numerous numbers of Imam 64.3 percent appointed in their job orally which means no written document where as only 35.7 percent have written document. The main and daily job responsibility is leading daily prayer where they can doing their job as a part-time or full-time in nature because there is no obligation to stay in the mosque except during prayer. In this study most of the imams 207 out of 300 which is 69 percent were working full time and only 31 percent were working as a part-time. The mosque is the place of work of the imams which is located in rural or urban areas. In this study, 52.7 percent mosques were located in rural areas and 47.3 were in urban areas. Muslims have a strong religious attachment to mosques, thus they invest more money in their construction in the hopes of reaping greater benefits from Allah. In this perspective, the number of bricked mosques (paka) is more than that of raw or semi-bricked mosques (Kacha& Semi-paka). This study demonstrates that 246 out of 300 mosques, or 82 percent, were brick-built and only 54 of the 300 mosques, or 18%, were not entirely constructed of brick.

Education Level

The present system of Islamic education is mainly two types one is Aliya madrasa which run according to the curriculum and syllabus framed by an education commission constituted by the government another is Qawmi madrasa which are free from government assistance or influence and are follow Dars-i-Nizamicurriculum. There are five stages in both in Aliya madrasah and Qawmi madrasah, which isIbtedayi (primary), Dakhil (secondary), Alim (higher secondary), Fazil (undergraduate) and Kamil (post-graduate, 2 years) in Aliya and Ibtedayi, Mutawassitah, Sanariaammah, Fazilat, Takmil in Qawmi. Imam must have the Islamic knowledge and follow the education level. In our study, highest number of respondent 54.3 percent completed their master’s equivalent degree and few respondent 4.3 percent completed Ibtedayi level. Among them 27 percent completed their lower and higher secondary level of education and 14 percent completed their Fazil or Fazilat which is equivalent to undergraduate level of education.

Relationship between Education level and job type and job contract

The findings also show that Imams are working as a part-time and full-time in every education level. Among them about 73 percent of full-time imams and 26 percent of part-time imam have a higher degree (Fazil and Kamil). On the other hand, Imam who have lower degree like primary and secondary were mostly engage in part-time rather than full-time.

Figure: Relationship of Education level with job type

The study also found that there are some relationships between education level and job contract. The majority of imams 64 percent were worked under oral contract only 36 percent imams had written employment contracts. Importantly, research demonstrates that they had no dominance as a written contact at any level of education although the number of written contracts increases with education level and number of oral contracts decline with lower to higher level of education.

Figure: Relationship of Education level with Job Contract

Job facilities of Imam

Job facilities are sometimes called employee benefits or factors of motivation for doing job. In formal job the main job facilities are paid leave, housing, medical, insurance, travel benefits, training, pension etc…  In informal in Bangladesh many of them are absent especially insurance, medical benefits, pension and training.   Nature of job facility of Imam is different from any other job. That includes 5 types of direct job facility and 4 types of indirect job facility which is salary sufficiency, leave, housing facility, sanitation facility, job security, freedom of speech, decision making and social honor. We use the Likert Scale that makes data collection flexible for respondents and simple to understand. We are going to focus on the result from the surveys. We use 5 points Likert scale to measures opinion about the facilities of job for the Imam.

The following table shows that percentage of respondent in different job facilities which is divided by tow parts like indirect and direct job facilities.

Table shows the percentages of different job facilities of Imam.

Category	Mean value	Decision
Salary Sufficiency	2.6	Low
Leave Facility	2.7	Average
Job Security	3.5	Enough
Housing Facility	2.3	Low
Sanitation Facility	2.7	Average
Food Facility	2.5	Low
Freedom of Speech	3.2	Average
Decision Making	2.9	Average
Social Honor	4.0	Enough

Figure: Average value of job facilities

In terms of salary sufficiency, the housing and food facilities have low Likert scores (2.6, 2.3, and 2.5, respectively), indicating that the basic or direct employment facilities are not well-facilitated at all. Whereas leave, sanitation, freedom of speech- and decision-making power have average scale. In there job social honor and job security have enough or Likert scale 4 but none other facility reach highest level of Likert scale which is mostly enough. The data clearly demonstrates that social honor receives the highest value (4.0) when it comes to housing facilities, which have relatively low scores(2.3).

Figure: Radar diagram (Likert scale point) about job facility

Model Description

To run the linear regression model, we test the assumption of normality which residual is normally distributed, multicollinearity through VIF value and heteroscedasticity through scatter plot.  To getting model fit we deducted outlier observation.  Among 300 respondents by using box diagram method, we deleted 25 the outliers from our data set. Finally, we run the multiple linear regression wage model.

Descriptive Statistics
Variables	Mean	Std. Deviation	N
Monthly Salary Income	8728.00	3752.408	275
X1 (education level)	3.99	1.254	275
X2 (Qawmi education)	.3673	.48294	275
X3 (Oral Contract)	.6582	.47518	275
X4 (Mosque location Rural)	.5600	.49729	275
X5 (Mosque Type Kacha)	.1927	.39516	275

This table provides the R, R², adjusted R², and the standard error of the estimate, which can be used to determine how well a regression model fits the data: R can be considered to be one measure of the quality of the prediction of the dependent variable; in this case, salary of imam. A value of .519 in this report indicates a good level of prediction. The R Square” column presents the R² value (also called the coefficient of determination), which is the proportion of variance in the dependent variable that can be explained by the independent variables. In this model our value of .269 that our independent variables explain 26.9 % of the variability of our dependent variable, salary. However, it doesn’t tell us the entire story.

Model Summaryb
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.519a	.269	.255	3238.017
a. Predictors: (Constant), X5 (Mosque Type Kacha), X2 (Qawmi education), X1 (education level), X3 (Oral Contract), X4 (Mosque location Rural)
b. Dependent Variable: Monthly Salary Income

To get the full picture, one must consider R² value in combination with residual plots, other statistics, and in-depth knowledge of the subject area.  According to Frost (2017) caveats about R² is: small R-squared values are not always a problem, and high R-squared values are not necessarily good.  To accurately report the data interpretation of “Adjusted R Square” (adj. R²) is another important factor. A value of .255 (coefficients table) in this example indicates true 25.5% of variation in the outcome variable is explained by the predictors which are to keep in the model. Whereas, adjusted R² tells how well the data points fit a regression line showing the percentage of variation explained only by the independent variables that actually affect the dependent variable.

ANOVAa
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	1037675405.141	5	207535081.028	19.794	.000b
	Residual	2820398994.859	269	10484754.628
	Total	3858074400.000	274
a. Dependent Variable: Monthly Salary Income
b. Predictors: (Constant), X5 (Mosque Type_Kacha), X2 (Qawmi education), X1 (education level), X3 (Oral Contract), X4 (Mosque location Rural)

The F-ratio in the ANOVA tests whether the overall regression model is a good fit for the data. The table shows that the independent variables statistically significantly predict the dependent variable, F (5, 269) = 19.794, p (.000) < .05 (i.e., the regression model is a good fit of the data).

Coefficientsa
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.	Collinearity Statistics
		B	Std. Error	Beta			Tolerance	VIF
1	(Constant)	10094.118	806.484		12.516	.000
	X1 (Education level)	319.909	161.046	.107	1.986	.048	.938	1.066
	X2 (Type of Education)	819.274	412.977	.105	1.984	.048	.962	1.040
	X3 (Job Contract)	-2237.726	437.725	-.283	-5.112	.000	.884	1.131
	X4 (Location of Mosque)	-2327.323	419.153	-.308	-5.552	.000	.881	1.135
	X5 (Type of Mosque)	-866.662	523.265	-.091	-1.656	.099	.895	1.117
a. Dependent Variable: Monthly Salary Income, X2. X3, X4 and X5 are dummy variables

Statistical significance of each of the independent variables tests whether the unstandardized (or standardized) coefficients are equal to 0 (zero) in the population (i.e. for each of the coefficients, H0: β = 0 versus Ha: β ≠ 0 is conducted). If p < .05, the coefficients are statistically significantly different to 0 (zero). The usefulness of these tests of significance are to investigate if each explanatory variable needs to be in the model, given that the others are already there.

Given that, the t-value and corresponding p-value are in the “t” and “Sig.” columns in this, respectively, in our model, the tests tell us that education level, types of education, job contract and mosque location value is respectively p(.048), p(.048) , p(.000) and p(.000)  is less than (<) 0.05 which is statistically significant to describe the dependent variable. And only X5 variable like mosque type is significant level at 10%. Salary (Y) = 10094.118 + 319.909 (X₁) + 819.274 (X₂) -2237.726 (X₃) -2327.323 (X₄) -866.662 (X₅)

This table also shows the multicollinearity of this variable by VIF value. If VIF is less than 1 and more than 5 then we called model has multicollinearity problems in this model our VIF value is in between 1 and 5 so no multicollinearity exists. A common rule of thumb: for any predictor VIF > 10 should be examined for possible multicollinearity problem (Dhakal, 2016). In our multiple linear regression model. VIF should be < 10 (or Tolerance > 0.1) for all variables, which they are.

CONCLUSION AND POLICY RECOMMENDATION

Monitoring and address salary disparities: Addressing the salary disparities of Imams indicates the presence of other factors contributing to wage disparities. It is important for policymakers to continually monitor wage disparities, identify underlying causes, and implement measures to address any unfair wage differentials based on gender, ethnicity, or other factors.

Promoting secure job contracts and age-related employment challenges: Promoting secure job contracts suggest that individuals with a job contract have higher salaries compared to those oral contracts. Furthermore the study found that there are no pension facilities for the Imams after retirement. Encouraging the provision of secure job contracts and initiating pension scheme, supporting lifelong learning opportunities, and eliminating age discrimination and fair compensation for them can contribute to improving overall salary levels and economic stability.

FUNDING

This study received financial support from Bangabandhu Sheikh Mujibur Rahaman Science and Technology University.

Competing Interests

The Authors declared that they have no competing interests.

Authors Contribution

All authors contributed equally to the conception and design of the study.

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APPENDIX

Assumption Test:

Graph: The residual is normally distributed.

Graph: No heteroscedasticity

Residuals Statisticsa
	Minimum	Maximum	Mean	Std. Deviation	N
Predicted Value	4982.32	12512.94	8728.00	1946.057	275
Residual	-9512.937	10697.775	.000	3208.337	275
Std. Predicted Value	-1.925	1.945	.000	1.000	275
Std. Residual	-2.938	3.304	.000	.991	275

Table: Test of linearity

ANOVA Table
			Sum of Squares	df	Mean Square	F	Sig.
Monthly Salary Income * X1 (education level)	Between Groups	(Combined)	181599738.972	4	45399934.743	3.334	.011
		Linearity	158530820.736	1	158530820.736	11.642	.001
		Deviation from Linearity	23068918.236	3	7689639.412	.565	.639
	Within Groups		3676474661.028	270	13616572.819
	Total		3858074400.000	274

Figure: No outlier in box plot

Table: Check Multicollinearity Problem

Correlations
			X1	X2	X3	X4	X5
		Monthly Salary Income	education level	Qawmi (education)	Oral (Contract)	Mosque location (Rural)	Mosque Type Kacha
Pearson Correlation	Monthly Salary Income	1.000	.203	.034	-.359	-.391	-.232
	X1 (education level)	.203	1.000	.001	-.227	-.066	-.121
	X2 (Qawmi education)	.034	.001	1.000	.183	.067	-.009
	X3 (Oral Contract)	-.359	-.227	.183	1.000	.195	.119
	X4 (Mosque location Rural)	-.391	-.066	.067	.195	1.000	.303
	X5 (Mosque Type_Kacha)	-.232	-.121	-.009	.119	.303	1.000
Sig. (1-tailed)	Monthly Salary Income	.	.000	.290	.000	.000	.000
	X1 (education level)	.000	.	.496	.000	.137	.023
	X2 (Qawmi education)	.290	.496	.	.001	.132	.442
	X3 (Oral Contract)	.000	.000	.001	.	.001	.024
	X4 (Mosque location_Rural)	.000	.137	.132	.001	.	.000
	X5 (Mosque Type_Kacha)	.000	.023	.442	.024	.000	.