How is unemployment data collected through surveys like PLFS?
How is unemployment data collected through surveys like PLFS?
Unemployment data in India is primarily collected through surveys like the Periodic Labour Force Survey (PLFS), conducted by the National Statistical Office (NSO). The PLFS is designed to gather comprehensive information on the labor market and measure key indicators such as employment, unemployment, and labor force participation. Here’s a detailed look at how unemployment data is collected through surveys like PLFS:
1. Survey Design and Sampling:
Stratified Multi-Stage Sampling: The PLFS uses a stratified multi-stage sampling design to ensure that the data is representative of the entire population, covering both urban and rural areas across all states and union territories in India.
Household Survey: Data is collected from a representative sample of households across different regions and socio-economic backgrounds. The sample size is large enough to ensure that the estimates of unemployment and other labor market indicators are reliable.
2. Types of Employment Indicators Collected:
The PLFS collects data to measure three key employment-related indicators:
Labour Force Participation Rate (LFPR): The proportion of the population aged 15 and above that is either employed or actively seeking employment.
Worker Population Ratio (WPR): The proportion of the population aged 15 and above that is employed.
Unemployment Rate (UR): The proportion of the labor force that is unemployed but actively seeking work.
3. Three Types of Reference Periods for Unemployment Data:
The PLFS collects unemployment data based on different reference periods to capture both short-term and long-term employment conditions:
Usual Status (Principal Status and Subsidiary Status):
Principal Status: This method defines unemployment based on a long-term perspective, where individuals are considered employed or unemployed based on their principal activity over the last 365 days. If a person has been unemployed for a significant portion of the year but has been involved in some economic activity for a short period, they may still be considered unemployed.
Subsidiary Status: This captures individuals who may not have been primarily employed but engaged in some form of work as a secondary activity during the year.
Current Weekly Status (CWS): This method measures the current unemployment status based on the last 7 days. A person is considered unemployed if they did not work even for one hour during the reference week but were available for work and seeking employment.
Current Daily Status (CDS): This method provides a more granular view of unemployment by capturing daily variations in employment. It measures the employment status on each day of the week and accounts for those who may have worked intermittently or were employed part-time during the week.
4. Questionnaire Design and Data Collection:
The PLFS uses structured questionnaires to collect detailed information from households. The questionnaire includes the following components:
Demographic Information: Data on age, gender, education level, and location (urban or rural).
Employment Status: Questions to determine whether the respondent is employed, unemployed, or not in the labor force.
Nature of Employment:
For those who are employed, questions capture the type of employment (self-employed, salaried, casual labor, etc.).
For those unemployed, the survey asks if they are actively seeking work and available for work.
Wage Information: Data on earnings for those employed and reasons for not working for those unemployed.
Industry and Occupation: Questions to determine the sector and industry in which the individual is employed or looking for work.
Reason for Unemployment: The survey collects information on the reasons for being unemployed, such as lack of work, seasonal employment, or seeking better opportunities.
5. Capturing Different Categories of Unemployment:
The PLFS collects data that allows policymakers and researchers to analyze various types of unemployment:
Open Unemployment: People who are actively looking for jobs but are unable to find work.
Disguised Unemployment: Particularly relevant in the agricultural sector, where more people are employed than necessary, leading to low productivity.
Underemployment: People who are employed part-time or in jobs that do not fully utilize their skills and are seeking full-time employment.
Seasonal Unemployment: This is common in sectors like agriculture, where employment opportunities are only available during certain seasons, and workers may be unemployed for the rest of the year.
6. Training and Deployment of Enumerators:
Field Enumerators: Trained field enumerators visit households to conduct interviews using face-to-face methods. They use a combination of paper questionnaires and Computer-Assisted Personal Interviewing (CAPI) tools for data collection.
Enumerator Training: Enumerators receive extensive training to ensure they accurately interpret the survey questions, explain them to respondents, and minimize response bias. This training is critical for ensuring consistency and reliability in the data collection process.
7. Ensuring Response Accuracy and Reducing Non-response Error:
Repeated Visits: Enumerators make repeated visits to households if needed to ensure that they collect complete and accurate data from all selected households.
Handling Non-response: In cases where respondents are not available or unwilling to participate, enumerators use follow-up procedures and may revisit the household at a later time to minimize non-response errors.
Cross-verification: Supervisors conduct spot checks and re-interviews to verify the accuracy of data collected by enumerators.
8. Processing and Analysis of Collected Data:
After the fieldwork is completed, the data undergoes extensive cleaning and validation processes to remove errors or inconsistencies. Data is then processed for statistical analysis.
Weighting and Adjustments: To ensure the results are representative of the entire population, data is weighted according to the sample design. This accounts for differences in population size across regions, states, and demographic groups.
9. Reporting of Unemployment Data:
The results of the PLFS are compiled and published in regular reports by the National Statistical Office (NSO). These reports include detailed tables on employment and unemployment indicators at the national, state, and sectoral levels (rural/urban).
Data Dissemination: The findings are made available to policymakers, researchers, and the public through annual reports and quarterly bulletins. This data is critical for designing employment policies and programs like job creation initiatives, skill development schemes, and unemployment benefits.
10. Challenges in Collecting Unemployment Data:
Capturing Informal Employment: A large portion of India’s workforce is employed in the informal sector, making it difficult to capture their employment status accurately, especially when there is no formal record of their work.
Seasonal and Disguised Unemployment: In rural areas, particularly in the agricultural sector, disguised unemployment is prevalent, where workers are underemployed but appear to be engaged in productive activity.
Respondent Understanding: In some cases, respondents may not fully understand the concept of "actively seeking work," leading to underreporting or misclassification of their employment status.
Conclusion:
The Periodic Labour Force Survey (PLFS) plays a vital role in collecting and analyzing unemployment data in India. Through a carefully designed sampling process, comprehensive questionnaires, and multiple reference periods, the PLFS provides detailed insights into the employment status of individuals across the country. This data is essential for monitoring the labor market, guiding government policies, and designing programs aimed at reducing unemployment, improving labor force participation, and promoting sustainable job creation in both rural and urban areas.
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