The building collapse in Savar has led to more than 1,000 deaths and left many more injured, adding to the increasing number of casualties from accidents at ready-made garment (RMG) factories over the last decade. The proposed across-the-board compensation of Tk.20 lakhs ($$25,628) for injured workers and Tk.1 crore ($128,090) for deceased workers is undoubtedly generous, but it appears arbitrary, and the methodology used behind such estimates remains largely unclear. While it is nearly impossible to estimate the monetary worth of a human life or the long-term suffering of families of the affected, it is still necessary to determine a reasonable compensation amount for the affected workers and their families, based on a systematic analysis in the current domestic and global economic context.
We have performed the following analysis using data retrieved from government reports, garment industry releases and various online sources. The analytical framework has been created based on the wage structure of RMG workers, the age of the worker at the time of accident and the average age of retirement for workers in Bangladesh.
We have calculated an approximate compensation amount by considering the income that the worker would have brought in if alive till the age of retirement (assumed 50 years), further adjusted to the current market wage, inflation, interest rates and possible wage increments through job promotions. Due to limitations in data, we have had to make conservative assumptions, such as considering only gross wage, which does not include festival bonuses and overtime, for calculating compensatory amounts.
However, bonuses and overtime, which constitute a large portion of workers’ income, are partially accounted for in our analysis with the assumption that the wage increases annually according to the inflation rate averaged over the last 25 years (6.28%, source: WB). Since we believe the compensation should be paid on a one-time basis, we have calculated the present discounted value of the future annual wage applying the real discount rate averaged over the last 25 years (2.72%, source: WB).
The Bangladesh Garments Owners and Manufacturers Association (BGMEA) categorises the industry staff in two broad groups — workers, personnel who are directly involved with processing apparel products, and employees, who are not. The wage structure for employees is divided into grades — 1 to 4 — with grade 1 being the highest and grade 4 the lowest, whereas workers’ wage rate is divided into grades — 1-7. For example, the monthly wage for grade 7 workers, such as assistant sewing machine operators and assistant knitting machine operators, is Tk.3,000 ($38). On the other hand, the monthly wage for grade 1 workers, such as pattern masters and chief cutting masters, is Tk.9,300 ($119). Unskilled new workers, taken in as apprentices, usually get promoted to grade 7 within 3-4 months of employment. Promotions for workers and employees in job grade leading to increments in salary and benefits was assumed to take place every 5 years.
Details of our calculations based on the facts and assumptions mentioned above are available online (savartragedy.wordpress.com).
According to our estimates:
- Workers of age 20 years and below, should receive a minimum compensatory amount of Tk.29,35,000 ($37,594) (grade 7 at the time of the accident) and a maximum of Tk.54,74,000 ($70,116) (grade 3 during the accident), for 30 years equivalent of wages lost;
- 21-25 years age group (25 years wage loss): minimum (grade 7) Tk.18,13,000 ($23,222) and maximum (grade 3) Tk.45,88,000 ($58,767);
- 26-30 years age group (20 years wage loss): minimum (grade 7) Tk.12,58,000 ($16,114) and maximum (grade 1) Tk.33,65,000 ($43,102);
- 31-35 years age group (15 years wage loss): minimum (grade 5) Tk.9,78,000 ($12,527) and maximum (grade 1) Tk.23,34,000 ($29,896);
- 35 years and above (10 years wage loss): minimum (grade 3) Tk.8,99,000 ($11,515) and maximum (grade 1) Tk.14,64,000 ($18,752).
Compensations for employees have been calculated similarly based on age groups and working grades. It is important to note that these estimates are only applicable to deceased workers and employees. Workers who have lost their full productivity due to severe physical injury should receive a higher compensation compared to that of a deceased worker to account for recurring costs of medical treatment and rehabilitation. Injured workers with a short recovery period should receive at least 3-4 months’ worth of wage and be given other employment opportunities as seen fit. For simplicity’s sake, we have excluded the medical treatment and rehabilitation costs of injured workers, but that can be fitted into the indemnity through some methodological adjustments based on various degrees of limb amputations and physical injury.
Such disasters also inflict various degrees of mental trauma and social harm on workers and their families. Theoretically, these impacts should be considered while assessing indemnity, but in reality, it is almost impossible to do so given the nature of these afflictions.
Thus, the compensation awarded becomes quite insignificant in the long run, especially for the families who have lost their only earning member, when compared to the long-term effects such a disaster would have on them.
The aim of our current work is to build a preliminary structure required for calculating the indemnity and we would like to reinforce that our estimates are primarily meant to point the government and policy-makers in the right direction. We earnestly hope that the government will establish a proper compensation procedure based on fair assessments, and will compel the RMG owners to be more conscious about ensuring safety for their employees to prevent further loss of human and social capital.
The writers are,
Ayesha Sania, Doctor of Science (Epidemiology), Harvard University.
Syed Galib Sultan, PhD student/researcher (Economics), University of Washington, Seattle.
Fahim Hassan, M.A (Economics),University of Alberta
Nisha Noor, M.A. (Political Science), Saint Louis University, Missouri.
RumanaJesmin Khan, PhD (Epidemiology), University of California, Davis.
NafisHasan, BS (Biology), Lafayette College.