1. Profile of the Economic Actors
Applied Inclusive Growth Analytics Course
June 30, 2009
Leonardo Garrido
Round table presentation

2. Presentation plan
Discuss the rationale for a profile of the economic actors
Present elements of a profile of economic actors exercise
Introduce elements of a demographic analysis
Case study: Tajikistan

3. Why do we need a Profile of the Economic Actors?
Growth Diagnostics addresses the issue of low returns to investments and entrepreneurship
But being mainly directed to the analysis of businesses, it mostly overlooks a fundamental issue:
Are all economic actors properly endowed to benefit from and participate in the economic activity?
Non-Included groups may represent a significant share of population
Inclusive Growth: Concerned about the pace and pattern of economic growth
Rapid and sustained poverty reduction requires inclusive growth, which allows previously non-included sectors to contribute and benefit from growth.
Growth should be broad based across sectors and inclusive of a large part of the country’s labor force

4. Labor Force Employed mostly outside the Modern Sector in LDC
Higher self-employment, non wage employment in LDC.
Substantial share of Agricultural, informal self employment in total employment in LDC.
Low employment rates in LDC masks issues of underemployment or employment at subsistence levels.
Substantial fraction of employed population receive earnings close to or below the poverty line.

5. Is the growth process accompanied by employment generation and poverty reduction?
Answering this question requires knowledge of:
Which are the growing sectors?
Are the poor are benefitting from employment and productivity increases?
Which sectors growth have a bigger effect on poverty reduction?
What is the employment and labor income profile of the population?
Which are the sectors in which the poor are working?
Which are the non included sectors?
What are the characteristics of the Labor Force? Education, Health Status,

6. Profile of economic actors: Helps identifying ways out of poverty
It begs for an analysis of selected labor groups:
Employed vs unemployed (and underemployed)
Agricultural, Informal, Self employed vs Modern Employees
Rural vs Urban + Poor vs non poor (i.e. Poor Rural vs Poor Urban)
By Selected Economic Activities
It attempts to identify non-included groups and the ways out of poverty
In many cases a full employability analysis must be conducted when early stages of the diagnostic exercise appear to show significant human capital deficiencies
Jesus Cuaresma presentation on Human Capital
In addition, a demographic analysis must be necessary as demographic dynamic may have significant impacts on the structure of population and labor force

7. Demographic Analysis
Relevant for Inclusive Growth analysis if at least one of the following is expected to occur during the relevant period:
A demographic transition
Changes in fertility and / or mortality rates
Changes in migration patterns
Internal and / or across the border
Changes in participation rates
Mainly linked to changes in schooling and / or increased participation of female in the labor market
Demographic shock
Fragile or post-conflict states.
Natural disasters
HIV / AIDS or any other epidemics affecting population stock and / or leading to changes in morbidity rates

8. Demographic Analysis
Most growth models do not distinguish between output per capita (Ypc) and output per unit of worker (Ype).
In a demographic transition this is not necessarily true:
Changes in fertility, mortality and migration patterns yields different dynamics in population and labor force growth rate (for given participation rates)
emp = employment rate
par = participation rate
wapr = Working age population ratio to total population

9. Demographic analysis: Fertility and Mortality Rates
Countries have a window of opportunity to cash in a “demographic dividend” if they take advantage of improvements in the age dependency ratio (adr)

10. Profile of the economic actors
Knowledge of the distribution of working age population and labor force is essential to identify productive and non-included groups
Working age population
Labor force
Employment abroad
Permanent
Returning
Employed
Modern Sector Employee /
Wage employee
Self Employment,
Agricultural Subsistence,
Informal Sector
Underemployed
Unemployed
Inactive population

11. Profile of the economic actors: Country specific and data intensive
Every Inclusive Growth analysis reveals particular issues of interest regarding the Labor Force:
Tajikistan: Migration, cotton workers
Zambia: Poor agricultural farmers
Mongolia: Skills mismatch and poor agricultural farmers
Benin: Informal economy
Kenya: informal economy and youth employment
Macro data alone is insufficient to generate a profile of economic actors
LSMS data
Labor Force Surveys
DHS data

12. Profile of Economic Actors. Case Study: Tajikistan
A profile of the economic actors point out of 3 groups / channels for poverty reduction, inclusive growth:
Migrants
Non cotton agricultural workers
Higher educated

13. Case Study: Tajikistan. Migrants

14. Case Study: Tajikistan. Migrants

15. Case Study: Tajikistan. Migrants

16. Case Study: Tajikistan. Migrants

17. Case Study: Tajikistan. Migrants

18. Case Study: Tajikistan. Migrants

19. Case Study: Tajikistan. Non cotton agriculture
Poverty rates have fallen the most in Tajikistan’s principal non-cotton farming areas
This sector has shown significant productivity improvements as a result of agricultural sector reforms
Non-cotton has been a much less regulated than cotton farming

20. Mincerian Returns to Education (I)
Dependent variable: Earnings, in logs (LY)
Interpretation of coefficient: Depend upon the specification of the education variable
If data on number of years of education is available: Coefficient represents marginal returns from additional year of education
Consider non linear specification to test for decreasing / increasing returns
If data on attainment is available (primary, secondary, higher education…) : Create dummy variables for each group. Coefficient represents additional return to education compared with base group
Both education (EDU) and experience (EXP) to be included in specification
Also consider the possibility of no linear impact of experience on earnings (EXPSQ)
Include as many individual, family, community and regional controls as possible (Vector V) to reduce omitted bias problems

21. Tajikistan: Mincerian Returns to Education (II)