Migrant Worker Well-Being and Its Determinants: The Case of Qatar

Abstract

Despite significant media attention and criticism, we know very little about the living and working conditions of low-income migrants in the Arab Gulf states, how migrants themselves view these conditions, or what factors most shape migrant worker well-being. Utilizing data from a unique, nationally representative survey of migrant workers living in labor camps in Qatar, this paper uses subjective and objective indicators to provide a more complete picture of migrant worker well-being and its determinants. We create a composite score of well-being based on migrant worker satisfaction with their job, human rights, salary, company treatment, and medical care. We then utilize ordinary least square to examine the degree to which migrant well-being is shaped by demographic characteristics, contract honoring, salary and debt levels, working conditions, human rights, and living conditions. Results identify contract-related issues as the strongest determinant of well-being, including whether a contract was honored, whether a copy of the contract was provided, and whether the details of employment in the contract were clear. More broadly, our results point to workers having low levels of overall awareness of their legal rights under existing Gulf labor law. Migrant worker well-being can thus be improved by raising this awareness and enforcing existing laws.

Appendix: Factor Analysis for Worker Well-Being Index

To measure well-being, we asked workers five subjective questions about whether they are satisfied with their job, with the way their rights are respected in Qatar, with their salary, with how their company treats them at the workplace, and with their medical care. The answer choices for these questions are based on the 5-point Likert scales: Very satisfied, somewhat satisfied, neither satisfied nor dissatisfied, somewhat dissatisfied, very dissatisfied. To make sure that these questions can be collapsed into a single index, we conducted an explanatory factor analysis, commonly used method for index construction. The following show all 5 questions in the survey:

• 1. Overall, how satisfied are you with your job? Would you say that you are very satisfied, somewhat satisfied, somewhat dissatisfied, or very dissatisfied?

• 2. Overall, how satisfied are you with the way your rights are respected here in Qatar? Would you say that you are very satisfied, somewhat satisfied, somewhat dissatisfied, or very dissatisfied?

• 3. How satisfied are you with the following aspects of life in Qatar: Salary? Would you say that you are very satisfied, somewhat satisfied, somewhat dissatisfied, or very dissatisfied?

• 4. Overall, how satisfied are you with the way your company treats you at your workplace? Would you say that you are very satisfied, somewhat satisfied, somewhat dissatisfied, or very dissatisfied?

• 5. How satisfied are you with the following aspects of life in Qatar: Medical Care? Would you say that you are very satisfied, somewhat satisfied, somewhat dissatisfied, or very dissatisfied?

We used STATA to run the factor analysis (with the “factor” command) using all 5 questions. The scree plot is used to show the eigenvalues and the number of factors (see below). According to this plot, the model clearly have only one factor as the line connecting the dot is quite flat after 2 factors. To confirm this result, we also run the parallel analysis and the dotted line from this analysis is plotted on the Scree plot. Since the dotted line cut the Scree plot just before factor 2, we have further confidence that there is only 1 factor (or one single index) for this model (Fig. 1).

Fig. 1

Scree plot with parallel analysis

We also measure the internal consistency among these 5 questions with the Cronbach’s alpha and its value is as high as 0.76 which give us more confidence in the reliability of the well-being index.