Profile of the Economic ActorsProfile of the Economic Actors

Applied Inclusive Growth Analytics CourseJune 30, 2009Leonardo Garrido

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

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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

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Labor Force Employed mostly outside the Modern Sector in LDC

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y = -8.5203x + 101.63

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60

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6 7 8 9 10 11 12

Se

lf E

mp

loye

d, %

of

tota

l em

plo

yed

LN(GDPpc PPP $ of 2005)

Ratio of Self Employed to total Employment vs Per Capita Income. Cross Country Data, 2001.

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6 7 8 9 10 11 12Wag

e an

d S

alar

ied

wo

rker

s, %

of

tota

l em

plo

yed

LN(GDPpc PPP $ of 2005)

Ratio of Waged and Salaried Workers to total Employment vs Per Capita Income. Cross Country Data, 2001.

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.

Is the growth process accompanied by employment generation and poverty reduction?

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

Profile of economic actors: Helps identifying ways out of poverty

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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

Demographic Analysis

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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

Demographic Analysis

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Most growth models do not distinguish between output per capita (Ypc) and output per unit of worker (Ype).

peYpcYemployed

Y

pop

Y

pop

popageworking

popageworking

forcelabor

forcelabor

employed

employed

Y

pop

Y __

__

_

_

prawrappmepeYpcY

In a demographic transition this is not necessarily true: In a demographic transition this is not necessarily true: Changes in fertility, mortality and migration patterns yields different Changes in fertility, mortality and migration patterns yields different

dynamics in population and labor force growth rate (for given dynamics in population and labor force growth rate (for given participation rates)participation rates)

emp = employment rateemp = employment rate par = participation ratepar = participation rate wapr = Working age population ratio to wapr = Working age population ratio to

total populationtotal population

Demographic analysis: Fertility and Mortality Rates

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Countries have a window of opportunity to cash in a “demographic dividend” if they take advantage of improvements in the age dependency ratio (adr)

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waprpopwap

popwapadr

y = -0.7393x + 9.8851

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0 1 2 3 4 5 6 7 8

Ferti

lity

Rate

LN (Per capita GDP in US$ of 2000)

Cross Country Fertility Rate and Per Capita Income. 2005

y = -0.1633x + 9.2049

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Mor

talit

y Ra

te

LN (Per capita GDP in US$ of 2000)

Cross Country Mortality Rate and Per Capita Income. 2005

Profile of the economic actors

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Knowledge of the distribution of working age population and labor Knowledge of the distribution of working age population and labor force is essential to identify productive and non-included groupsforce is essential to identify productive and non-included groups

Profile of the economic actors: Country specific and data intensive

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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

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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

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-2%

-1%

0%

1%

2%

3%

4%

5%

6%

-50,000

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

1970 1975 1980 1985 1990 1995 2000 2005

Per

cen

t o

f p

op

ula

tio

n

# p

eop

le

Tajikistan: Net Emigration (Emigration minus Immigration). 1970-2005

Net migration Net Migration / Population

Case Study: Tajikistan. Migrants

Case Study: Tajikistan. Migrants

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Working in Tajikistan

27%

Unemployed67%

Student / pupil5%

Other1%

What Migrants were doing before migrating?

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Russia95%

Kazakhstan1%

Other Central Asia0%

Other CIS0% Other Non-CIS

4%

Tajik Migrants, Main Destination. 2007

Case Study: Tajikistan. Migrants

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Craft and related workers

58%

Service workers11%

Other5%

Professionals3%

Pland and machine

operators and assemblers

4%

Elementary occupations

19%

Tajik Migrants, by Occupation

Case Study: Tajikistan. Migrants

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Basic (Grades 1-8)16%

Secondary (Grades 1-9)

63%

Secondary special /

technical12%

Higher education9%

Education Attainment of Migrants

Case Study: Tajikistan. Migrants

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Case Study: Tajikistan. MigrantsMonthly Earnings of Returning Migrant per Month (US$).

All Illegal migrant Legal migrant All Illegal migrant Legal migrantMajor and Minor Groups -- -- -- 875 -- 875Professionals 707 200 787 827 250 951Technicians and Associate Professionals 543 500 555 238 238 --Clerks 356 356 -- 329 -- 329Service Workers 302 278 309 791 294 922Skilled Agricultural and Fisheries Work 196 203 193 2,062 1,332 2,321Craft and related workers 348 374 334 920 1,065 876Plant and Machine Operators and Assemblers 416 695 347 2,077 251 2,644Elementary Occupations 302 287 310 916 740 985All migrants 348 354 345 977 896 1,002

Returned Migrants Current Migrants Abroad

Mean Income by Employment Status and Urban / Rural. Somoni per monthEducational Attainment Rural Urban TotalPaid employment, regular basis 211 424 276Paid employment, piecework basis 387 563 421Self employed, owner without hiring 337 566 412Self employed, owner with hired workers 279 348 294Unpaid family worker 163 266 179Other Status 163 275 203All with status in employment info 264 446 309

Case Study: Tajikistan. Non cotton agriculture

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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

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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

titititititi VEXPSQEXPEDULY ,,,3,2,10,

Mincerian Returns to Education (I)

Tajikistan: Mincerian Returns to Education (II)

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Linear regression Number of obs 7,016Prob > F 0

Dependent: Income per capita, in logs R-squared 0.4729

Explanatory Variables Coefficient t statisticSecond. Tech. /Special Attainment, Dummy=1 0.092 2.67 ***Higher Education Attainment, Dummy=1 0.314 9.02 ***Experience, Years 0.028 6.72 ***Experience, squared 0.000 -4.02 ***Number of weeks worked per year -0.001 -0.55Dummy, Male==1 0.587 20.38 ***Secondary Sector, Dummy=1 0.667 15.36 ***Tertiary Sector, Dummy=1 0.476 10.97 ***Oblast, Sogd, Dummy=1 -0.109 -2.83 ***Oblast, Khatlon, Dummy=1 -0.314 -8.53 ***Oblast, RRP, Dummy=1 0.135 3.37 ***Oblast, GBAO, Dummy=1 -0.345 -7.41 ***Seasonal worker, Dummy=1 -0.104 -2.86 ***Temporary worker, Dummy=1 0.209 4.97 ***Occasional worker, Dummy=1 -0.090 -1.31Work in Small Firm, Dumy=1 0.007 0.16Work in Medium Firm, Dummy=1 0.052 1.09Work in Large Firm, Dummy=1 0.001 0.02Public Sector Worker, Dummy=1 -0.314 -5.98 ***Individual Worker, Dummy=1 0.185 3.38 ***Other Employer, Dummy=1 -0.031 -0.61No Employer, Dummy=1 0.146 1.98 **Self employed, individual, Dummy=1 0.167 2.51 ***Self emp., with hired labor, Dummy=1 -0.045 -0.86Unpaid worker, Dummy=1 0.127 1.64 *Self employed, other, Dummy=1 0.150 0.74Employed in piecework basis, Dummy=1 0.193 5.65 ***Waged worker, Dummy=1 1.597 23.27 ***Has migrated in last year, Dummy=1 -0.012 -0.21Constant term 2.503 20.00 ***

Default employer is Private Firm

Default status in employment is Paid

Regular

*** = Significant at 1% ; ** = Significant at 5%; * = Significant at 10%

Default Sector is Primary

Default Oblast is Dushanbe

Default type is Permanent

Default Size of Firm is Individual

Default Educ. is None, Prim. or Seco. General