Strengthening Labor Data Collection for Inclusive Policy Formulation

Household and enterprise surveys provide important data on work and employment. While these labor force surveys (LFS) remain one of the most reliable sources of information, no single data source can fully meet the diverse and increasing requirements for labor statistics.

Data integration combines the labor force survey with other sources for enhanced insights. It leverages the strengths of each type of data source and mitigates the weaknesses associated with using each type alone. One such data source is administrative data, obtained from records maintained by government agencies and private institutions for administrative purposes, such as program implementation. Over the years, administrative data sources have been widely accepted as effective supplements to census and survey data and have the potential to strengthen labor data systems.

While administrative data sources cannot replace the LFS as the main source of labor statistics, they can enrich analysis when used in conjunction with the LFS.

Compiling data on the informal economy is challenging due to its diverse and complex nature. This sector comprises small-scale units producing goods or services to generate income and employment, operating without formal contracts, entitlements, accounting systems, or legal safeguards. It is prevalent in developing countries, disproportionately affecting women, young people, low-skilled workers, and rural residents who face greater barriers to accessing the formal economy.

Quantitative data on the scale and extent of the informal economy, as well as the needs and challenges of its workers, are scarce. This scarcity primarily stems from the informal economy being insufficiently covered by the regular data collection systems of national statistics offices.

Informal economic activities have market value and would contribute to GDP if properly recorded. Establishing a robust framework for measuring the contributions of the informal economy would allow governments to account for activities within this complex sector. 

In the past, ADB utilized a mixed survey approach to estimate the prevalence of informal employment and measure the economic contribution of this sector. In this survey approach, two phases are involved. Initially, the sampling frame of informal sector units (second phase) is constructed from a household survey (first phase). Specific questions aimed at identifying informal sector production units are incorporated into the household survey questionnaire. Subsequently, the second phase comprises a survey conducted among the informal sector production units to gather data on working conditions and economic performance. While individuals are sampled in the first phase, the second phase targets informal sector production units, resulting in what is termed a "mixed" survey. This methodology facilitates correlating informal sector activities and business owner characteristics with household characteristics.

Strengthening the capacity of national statistical systems to adopt new standards for compiling statistics on informality can provide deeper insights into sectors that employ 60% of the global workforce.

The COVID-19 pandemic has not only accelerated the adoption of digital transformation across various industries but has also heightened the demand for new skills necessary for success in the modern workforce. As emerging industries and job opportunities continue to evolve, it becomes imperative to examine how technology, globalization, and structural changes can drive job creation. However, there remains a dearth of data on the task content of jobs across diverse occupation groups and economic sectors, including cognitive, analytical, and interpersonal skills.

Despite significant economic reforms, economies in the region still grapple with development challenges, such as high unemployment and underemployment. Studies suggest that these trends reflect a skill gap in the labor market, particularly concerning low- and mid-level technical and soft skills. 

Jobs and skills surveys that gather key labor market statistics contribute to identifying gaps and mismatches that hinder individuals' employability. For instance, ADB’s Jobs and Skills Survey (JSS) initiative, to be conducted in collaboration with select national statistics offices, aims to address the lack of reliable and up-to-date data, serving as a foundation for formulating effective policies, programs, and interventions tailored to enhance the efficiency and productivity of the labor market. By aligning workplace skills with the evolving needs of the labor market, this initiative seeks to generate employment opportunities, stimulate economic growth, and promote greater social mobility.

• Policy makers can utilize reliable and timely statistics on work and employment to address the diverse and evolving needs of the global labor force. These statistics offer crucial insights for evaluating the alignment between the supply of skills and labor market demands, identifying areas of mismatch that require immediate intervention.
• Resource challenges in statistical activities necessitate a more sustainable approach.
• Labor data can shape effective and inclusive policies by highlighting the realities faced by economically challenged groups and elucidating the complexities of the informal economy. Understanding the dynamics of the informal economy can help advance the Decent Work Agenda and achieve the goals of the 2030 Agenda for Sustainable Development.
• Collaborative efforts, including maintaining strong relationships with policy makers and coordinating with other development partners to leverage diverse expertise, can help refine existing methods of data collection and analysis, particularly in response to technological advancements and shifts in the economic landscape in the post-pandemic era.

Asian Development Bank (ADB). 2023. Using Administrative Data to Strengthen Development Statistics in Asia and the Pacific. Manila.

ADB. 2011. A Handbook on Using the Mixed Survey for Measuring Informal Employment and the Informal Sector. Manila.

ADB. 2018. Measuring Asset Ownership and Entrepreneurship from a Gender Perspective: Methodology and Results of Pilot Surveys in Georgia, Mongolia, and the Philippines. Manila.

ADB. 2018. Data for Development (Phase 2) Project Data Sheet. Manila.

ADB. 2023. Gender Gaps in Ownership of Nonagricultural Enterprises in Georgia, Mongolia, and the Philippines. Manila.

International Labour Organization (ILO). 2015. National Employment Policies: A Guide for Workers’ Organisations.

ILO. 2023. 21st International Conference of Labour Statisticians. Geneva.

ILO. 2023. Administrative Data Sources in Labour Statistics. Geneva.