Table 2.1: No. of factories and workers surveyed across 6 countries

Country No. of Factories No. of Workers

Bangladesh 21 271

Cambodia 24 294

India 55 433

Indonesia 28 390

Pakistan 50 605

Sri Lanka 11 192

Total 189 2185

Sampling Method

A two-stage random sampling method was used to ensure the representation of the overall garment worker population across surveyed countries:

• In the first stage, factories were identified and a representative sample was drawn for the identified factories.

• In the second stage, the number of workers to be sampled for each factory was drawn proportionate to the factory size.

The selection of factories, and further selection of workers was done in a phased manner. Both factories and workers were chosen based on definite inclusion criteria, to ensure the representativeness of the sample, as summarised below.

Selection Of Factories pandemic-induced recession in 2020, were selected by trade unions in the respective countries.

The inclusion criteria for selection of factories were as follows:

• Factory is registered under national legislation.

• Factory is operating in the supply chains of selected global apparel brands as a

Tier 1 supplier.

• Factories are present across major garment clusters in the respective countries, which are considered as the centres of garment manufacturing.

Selection Of Workers

The choice of factories satisfying the abovementioned criteria forms the sampling frame. Workers were selected from these factories based on their accessibility through trade unions. The selection of factories in all the countries followed a replacement sampling procedure, which allows the replacement of the selected factory if workers cannot be reached.

The inclusion criteria for selection of workers were as follows:

• They were employed in the garment factory for at least twelve months prior to the period of data collection. In other words, they were employed in the factory in the period prior to the pandemicinduced recession.

• Proportionate representation based on gender, employment contract type, different departments and job roles in the factory was ensured to the extent possible.

Details Of Sampling

The sample comprises workers employed in Tier 1 export factories operating in the supply chains of major global apparel brands, with

relatively better employment conditions as compared to informal, sub-contracted units, or home-based workers. Factories have been verified as supplying to major brands based on both the supplier lists of those brands (where publicly available) and reporting by workers and trade unions.

The sample, in most countries, is overrepresented by unionised and regular workers, who have relatively more secure employment, wages and benefits, as compared to non-unionised and contractual or casual workers.

As a result, the study under-estimates the wage theft experienced by garment workers and its human rights impact. By presenting the extent and severity of the crisis facing workers who fare relatively better, the study hints at the real magnitude of the crisis facing the majority of garment workers who are in more insecure forms of employment.

The specific limitations and details of the sampling in each country is summarised in the respective chapters.

Note: Data collection in Bangladesh was conducted within a short time period (May 2021) during a total, nationwide lockdown. As a result, the sample of workers from Bangladesh include workers who were easily accessible to trade unions during the lockdown – focusing on trade union members who were removed from their jobs, particularly in November-December 2020. The findings have been presented in a special chapter focusing on the unfair dismissals of garment workers and resultant wage theft in Bangladesh.

Collaboration With Trade Unions

The data collection for this study was conducted in collaboration with 23 trade unions and labour organizations across the 6 countries, who have a strong presence among workers employed in supplier factories of major global apparel brands. Trade union representatives identified factories and workers, and administered different data collection tools for the purpose of the study.

Trade unions faced immense challenges in documenting the conditions of workers during the pandemic, due to:

• Silencing and repression of workers, who were afraid of losing their employment if they reported violations in their factories.

• Increasing threats to trade unions and freedom of association in the context of the pandemic.

• Challenges in reaching out to workers who had left the industrial clusters and returned to their villages as they lost jobs and wages.

• Reduced accessibility to industrial zones as infection rates increased, and lockdown restrictions made transportation and access extremely difficult.

Classification Of Time Periods

The data was collected for different time periods across the year of 2020. The data has been classified into two broad periods in all countries:

• Pre-recession period: The months of January and February 2020 are considered the pre-recession period, as garment workers were not yet experiencing employment loss or wage theft related to the pandemic-induced recession.

• Pandemic-induced recession period:

There was a pandemic recession from

March to December 2020, where workers experienced employment loss and wage theft.

The data from the pre-recession period has been considered as the reference for calculating shifts in key variables during the pandemic-induced recession period.

In South Asian countries, where there were specific government-imposed lockdowns which impacted garment manufacturing, the pandemic-induced recession period has been further classified into different time periods based on relevant factors in each country, as detailed in the specific chapters. Several months in the pandemic-induced recession period have been grouped together for data collection, analysis and reporting as they had fairly similar situations in terms of employment loss and wage theft. In Southeast Asian countries, there were no specific periods of total lockdowns imposed by the government. As a result, the data has been collected, analysed and reported for each month during the pandemic-induced recession period.

For the purpose of keeping the language used to present the findings simple and accessible, the pre-recession period has been referred to as pre-Covid-19 period, and the pandemic-induced recession period has been referred to as the Covid-19 period throughout the chapters.

Sources Of Data

• The primary respondents of the study and the basic unit of analysis are garment workers employed in export-oriented factories supplying to major global apparel brands, and workers’ households.

• In addition to this, trade unions were interviewed to create profiles on the situation of total workforce and overall conditions in the selected factories, beyond the workers selected for the sample.

• Secondary sources, including aggregates of national level trade statistics and national level micro-data has been used for setting the context on how the Covid-19 pandemic impacted the industry.

Tools For Data Collection

1. Structured interview schedule was administered to workers from selected factories to collect data on:

• Demographic details of worker: Gender, age, migration status, religion, and other relevant social identity markers.

• Employment status, wages and benefits:

◦ Employment status: Layoffs or terminations experienced by workers across 2020.

◦ Loss in Work Days: Number of working days and layoffs per month.

◦ Wages and Benefits: Total monthly earnings, and other benefits such as bonus and social security payments.

◦ Overtime Work and Payment: Number of hours of overtime and overtime payment per hour.

• Consumption and indebtedness:

◦ Monthly Consumption Expenditure:

Monthly household consumption expenditure on selected items.

◦ Indebtedness: Cumulative monthly debt at the household level

• Household profile of the Worker: Details of other members of the household, employment status and wages.

2. Factory profile schedule was administered to trade unions with a strong presence in the selected factories to triangulate the data collected from workers selected for the sample, and collect additional data on the total workforce and overall conditions in each selected factory: