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PLFS: Year, Region, and Gender wise Share of Salaried Employees without Written Contracts, Paid Leave, and Social Security Eligibility

Dataset Overview

This dataset provides the percentage of regular wage/salaried employees in usual status (ps+ss) engaged in the non-agriculture sector who had no written job contract, were not eligible for paid leave, and were not eligible for specified social security benefits. For years before 2017-18, the data was obtained in different quinquennial rounds of NSSO conducted from 2004-05 (NSS 61st) to 2011-12 (NS...

Number of Rows

324

Number of Columns

7

Time Period

2004-05, 2009-10, 2011-12, 2017-18 to 2023-24, 2022 to 2025

Sectors

Labour and Employment

Organisation

Ministry of Statistics and Programme Implementation

Sources

Periodic Labour Force Survey: Annual Reports

Update FrequencyUpdate Frequency At Source

Yearly

Last UpdatedLast Updated at Dataful

May, 2026

Granularity

Yearly

Time Saved

5.5 hours

Units

share_of_employees in percentage

Related Datasets

PLFS: Year, Industry, Region, and Gender wise Distribution of Workers

Organisation

Ministry of Statistics and Programme Implementation

Time Period

1977-78, 1983, 1987-88, 1993-94, 1999-2000, 2004-05, 2009-10, 2011-12, 2017-18 to 2023-24, 2022 to 2025

PLFS: Year, Region, and Gender wise Distribution of Workers by Status of Employment

Organisation

Ministry of Statistics and Programme Implementation

Time Period

2017-18 to 2023-24, 2022 to 2025

Year, Region, Gender, and State wise Share of Regular Wage/Salaried Employees without Social Security Benefits

Organisation

Ministry of Statistics and Programme Implementation

Time Period

2017-18 to 2023-24

Data Preview

fiscal_yearcategory_of_employeesregiongendershare_of_employeesunitnote
2025regular wage/salaried employees who had no written job contractruralmale62.6share_of_employees in percentage
2025regular wage/salaried employees who had no written job contractruralfemale55share_of_employees in percentage
2025regular wage/salaried employees who had no written job contractruralperson60.7share_of_employees in percentage
2025regular wage/salaried employees who had no written job contracturbanmale55.4share_of_employees in percentage
2025regular wage/salaried employees who had no written job contracturbanfemale58.6share_of_employees in percentage
2025regular wage/salaried employees who had no written job contracturbanperson56.3share_of_employees in percentage
2025regular wage/salaried employees who had no written job contractrural+urbanmale58.5share_of_employees in percentage
2025regular wage/salaried employees who had no written job contractrural+urbanfemale57.2share_of_employees in percentage
2025regular wage/salaried employees who had no written job contractrural+urbanperson58.2share_of_employees in percentage
2025regular wage/salaried employees not eligible for paid leaveruralmale53.8share_of_employees in percentage

Metadata

NameNumber of Distinct ValuesNumber of Unique ValuesTypeCount
fiscal_year1414String324
category_of_employees33String324
region33String324
gender33String324
share_of_employees188188Float64324
unit11String324
note11String0

Related Datasets

PLFS: Year, Industry, Region, and Gender wise Distribution of Workers

Organisation

Ministry of Statistics and Programme Implementation

Time Period

1977-78, 1983, 1987-88, 1993-94, 1999-2000, 2004-05, 2009-10, 2011-12, 2017-18 to 2023-24, 2022 to 2025

PLFS: Year, Region, and Gender wise Distribution of Workers by Status of Employment

Organisation

Ministry of Statistics and Programme Implementation

Time Period

2017-18 to 2023-24, 2022 to 2025

Year, Region, Gender, and State wise Share of Regular Wage/Salaried Employees without Social Security Benefits

Organisation

Ministry of Statistics and Programme Implementation

Time Period

2017-18 to 2023-24

Tags

Wage Employees
Job Contract
Paid Leave
+2

Citation

Ministry of Statistics and Programme Implementation. PLFS: Year, Region, and Gender wise Share of Salaried Employees without Written Contracts, Paid Leave, and Social Security Eligibility [Data set]. Dataful. https://dataful.in/datasets/20479