2017年-世界发展银行全球_Toward_Labor_Market_Policy_20___The_Potential_for_Using_Online_Job-Portal_Big_Data_to_Inform_Labor_Market_Policies_in_India_36页_890kb

报告摘要

Toward Labor Market Policy 2.0: The Potential for Using Online Job-Portal Big Data to Inform Labor Market Policies in India

Core Content

This paper explores the potential of using big data from online job portals to inform and enhance labor market policies in India. It emphasizes the importance of data-driven decision-making in addressing skills mismatches, unemployment, and inequity in the labor market. The study focuses on Babajob, one of the leading online job portals in India, to demonstrate how such data can be used for policy-relevant research in labor economics and skills development.

Main Points

1. Big Data in Labor Market Research

Big data from online job portals provides real-time, granular, and multidimensional insights into labor market dynamics.
It complements traditional data sources such as sample surveys and government statistics, offering more timely and detailed information.
The data can be used for descriptive analysis, time-series analysis, text analysis, predictive modeling, and transactional data analysis.

2. Five Key Applications of Online Job-Portal Data

(i) Labor Market Monitoring and Analysis: Enables real-time tracking of employment trends, wage levels, and job seeker behavior.
(ii) Assessing Demand for Workforce Skills: Helps identify the types of skills in demand across different sectors and regions.
(iii) Observing Job-Search Behavior and Improving Skills Matching: Reveals patterns in job searching and helps align worker skills with employer needs.
(iv) Predictive Analysis of Skills Demand: Allows for forecasting future skill requirements based on historical data.
(v) Experimental Studies: Facilitates the design and evaluation of labor market interventions using large-scale data.

3. Challenges in Using Big Data

Representativeness: Online data may not fully represent the entire labor market, especially in regions with limited internet access.
Privacy and Confidentiality: Requires careful handling to ensure data is used responsibly and ethically.
Methodological Limitations: Data ownership, unstructured nature, and partial coverage pose challenges in interpretation and application.

Key Information

4. India’s Labor Market Context

India has a large and predominantly informal labor force.
The labor force participation rate is 54%, with 80% for men and 26% for women.
Only 16% of the labor force is engaged in wage employment, with the rest working in the informal sector.
The National Policy for Skill Development and Entrepreneurship (2015) and the 12th Five-Year Plan aim to train 400 million workers by 2022.

5. Babajob: A Unique Data Source

Babajob, established in 2007, is a leading Indian job portal.
It provides access to both formal and informal sectors and offers various platforms such as mobile sites, IVR, and text messaging.
Between 2007 and 2015, over 858,000 jobs were posted, and 240,000 employers and 4.5 million job seekers registered.

6. Gender Wage Gap Analysis

The analysis of Babajob data reveals significant gender wage gaps.
Female-specified job postings had 16.2% lower average wage offers compared to male-specified postings.
Clerical support jobs were the most common in 2015.
Professional-level jobs had higher wages (Rs. 14,900) compared to non-professional jobs (Rs. 12,739).
Cities like Ahmedabad, Ranchi, and Thane showed the widest gender wage gaps, while Gurgaon, Noida, and Indore had narrower gaps.

7. Skills Demand Insights

Text analysis of job descriptions helps quantify employer demand for specific skills.
Computer skills were highlighted in 25% of all job postings.
Non-cognitive skills such as communication and service skills were also in high demand.
Foreign language skills, particularly English, were highly requested in Poland (64%) and Czech Republic (28%).

Conclusion

The paper contributes to the academic literature on labor economics and provides policy insights for India.
It highlights the potential of big data to improve labor market policies and skills development strategies.
Real-time and granular data from online job portals can help address skills mismatches, improve job matching, and promote equitable wage structures.
The case of Babajob illustrates how big data analytics can be applied in developing countries to support demand-driven skills development and labor market efficiency.