|
|
|
|
LEADER |
02685nmm a2200541 u 4500 |
001 |
EB001309407 |
003 |
EBX01000000000000000894019 |
005 |
00000000000000.0 |
007 |
cr||||||||||||||||||||| |
008 |
161223 ||| eng |
020 |
|
|
|a 9781498358934
|
100 |
1 |
|
|a Anand, Rahul
|
245 |
0 |
0 |
|a South Africa
|b Labor Market Dynamics and Inequality
|c Rahul Anand, Siddharth Kothari, Naresh Kumar
|
260 |
|
|
|a Washington, D.C.
|b International Monetary Fund
|c 2016
|
300 |
|
|
|a 37 pages
|
651 |
|
4 |
|a South Africa
|
653 |
|
|
|a Labor Turnover
|
653 |
|
|
|a Labour
|
653 |
|
|
|a Unemployment: Models, Duration, Incidence, and Job Search
|
653 |
|
|
|a Trade unions
|
653 |
|
|
|a Labor-Management Relations, Trade Unions, and Collective Bargaining: General
|
653 |
|
|
|a Unemployment
|
653 |
|
|
|a Labor markets
|
653 |
|
|
|a Aggregate Labor Productivity
|
653 |
|
|
|a Demand and Supply of Labor: General
|
653 |
|
|
|a Aggregate Human Capital
|
653 |
|
|
|a Personal Income, Wealth, and Their Distributions
|
653 |
|
|
|a Labor
|
653 |
|
|
|a Labor Force and Employment, Size, and Structure
|
653 |
|
|
|a Vacancies
|
653 |
|
|
|a Layoffs
|
653 |
|
|
|a Labor market
|
653 |
|
|
|a Wages
|
653 |
|
|
|a Labor unions
|
653 |
|
|
|a Unemployment rate
|
653 |
|
|
|a Economic theory
|
653 |
|
|
|a Intergenerational Income Distribution
|
653 |
|
|
|a Income economics
|
653 |
|
|
|a Employment
|
700 |
1 |
|
|a Kothari, Siddharth
|
700 |
1 |
|
|a Kumar, Naresh
|
041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
989 |
|
|
|b IMF
|a International Monetary Fund
|
490 |
0 |
|
|a IMF Working Papers
|
028 |
5 |
0 |
|a 10.5089/9781498358934.001
|
856 |
4 |
0 |
|u https://elibrary.imf.org/view/journals/001/2016/137/001.2016.issue-137-en.xml?cid=44078-com-dsp-marc
|x Verlag
|3 Volltext
|
082 |
0 |
|
|a 330
|
520 |
|
|
|a This paper analyzes the determinants of high unemployment in South Africa by studying labor market dynamics using individual level panel data from the Quarterly Labor Force Survey. While prior work experience and gender are found to be important determinants of the job-finding rate, education attainment and race are important determinants of the job-exit rate. Using stock-flow equations, counterfactual exercises are conducted to quantify the role of these different transition rates on unemployment. The paper also explores the contribution of unemployment towards inequality. Reducing unemployment is found to be important for reducing inequality – estimates suggest that a 10 percentage point reduction in unemployment lowers the Gini coefficient by 3 percent. Achieving a similar reduction solely through transfers would require a 40 percent increase in government transfers
|