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

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

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

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.

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,

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

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

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

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)

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

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

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

Case Study: Tajikistan. Migrants

Case Study: Tajikistan. Migrants

Case Study: Tajikistan. Migrants

Case Study: Tajikistan. Migrants

Case Study: Tajikistan. Migrants

Case Study: Tajikistan. Migrants

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

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

Tajikistan: Mincerian Returns to Education (II)