Human Capital and Development in Kenya: Health, Education and Labor - - PowerPoint PPT Presentation

Human Capital and Development in Kenya: Health, Education and Labor Income Profiles, 1994 and 2005

Moses Muriithi Reuben Mutegi Germano Mwabu

University of Nairobi, Kenya Presented at NTA Conference, Peking University, Beijing, China 10th ‐15th November 2014

Introduction

• Long Term National Plan for Kenya, KENYA

_VISION_2030, recognizes the role of human capital in development

• Health and education are identified as vital

ends in themselves and as means of national development

But Plan lacks information on...

• Expenditure on health and education services

by age and gender

• Productivity of human capital or its return, by

age and gender

• Human capital created within households or in

household enterprises, especially by women

This information is needed

To design policies that would promote:

• Human capital formation (health and

education) by age

• Social protection by gender
• Development of tools to count human capital

produced at home and in family enterprises

Current education policies

• Free primary education
• Subsidised secondary education
• Parallel (unsubsidized) degree programs at

all universities

• Higher Education Loan Board

Education

• The Higher Education Loans Board (HELB)
• ffers loans to students in both public and

private universities

• Licensing of private schools created unintended

expansion in private primary schools due to (a) low quality education offered in free public schools and (b) desire to get subsidies granted by National Treasury

• University Charters have encouraged rapid

expansion of universities

Education: Major policy gaps

• There are no data to show how policies

influence schooling and spending at different ages or by gender

• Policies ignore time used at home or in

household enterprises, especially by women, to support or complement formal schooling [Same for the health sector]

– Household budget and time‐use surveys needed

Health policies

• Free maternity care
• Free treatment of children
• free anti‐retrovirus therapy
• Subsidized bed‐nets
• Free vaccinations

Improving social policies: NTA & NTTA evidence needed

• NTA and NTTA profiles can reveal variations

in health and education expenditures by age, gender, region and year of survey data

• They can suggest (or be used to consider)

ways to improve social policies

• Use 1994 and 2005/06 household surveys

to approximate policy effects

1994

• 200.00

400.00 600.00 800.00 1,000.00 1,200.00 1,400.00 1,600.00 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35

Kenya Shillings Age

PRIMARY SECONDARY HIGHER TOTAL

2005

500 1,000 1,500 2,000 2,500 3,000 3,500 5 10 15 20 25 30 k s h Age Primary Secondary total public education Higher

Public education consumption

Education, health and labor income profiles for Kenya, 1994 and 2005

Private education consumption

1994

50 100 150 200 250 300 350 10 20 30 40 50 60 70 80 90+ ksh Age

2005

2000 4000 6000 8000 10000 12000 10 20 30 40 50 60 70 80 90 K S H age

Total public and private education consumption

1994

‐ 500.00 1,000.00 1,500.00 2,000.00 2,500.00 3,000.00 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90+ Ksh Age Total public Total private

2005

‐ 2,000.00 4,000.00 6,000.00 8,000.00 10,000.00 12,000.00 0 5 101520253035404550556065707580859095 Ksh Age Total public education consumption Total private education consumption

Health profiles, 1994

Health profiles, 2005

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 percapita health 2005 per capita health 1994

Per capita health consumption, 1994 and 2005

Labor Income Profile, 1994 and 2005

0.05 0.1 0.15 0.2 0.25 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 laborY1994 laborY 2005

NTTA profiles

Can help design better social policies around work, equity and human rights

Unpaid family workers

20 40 60 80 100 120 140 160 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 number of people age male female

Time use in household enterprises, by gender

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 5 8 13 18 23 28 33 38 43 48 53 58 63 68 73 78 Hours per day Age

Home enterprise management, unpaid work

Enterprise, male Enterprise, male (smoothed) Enterprise, female Enterprise, female (smoothed)

Thank you

Notes

• Time use analysis is performed for both

market and non‐market economies

• For the market economy NTA frame work is

used

• The CWW methodology disaggregates NTA

by gender and counts goods and services excluded from NTA

• For non‐market services, unpaid household

services are included in the NTA framework

• NTTA combines data from time use and

wage surveys to measure time men and women spend in unpaid production

• NTTA is linked to gender because women’s

work, especially, is not captured in NTA

Notes

Steps in doing NTTA:

• Identify available time use survey by age
• Identify time spent on household work
• Find appropriate wages to impute value

Construct NTTA for men and women

Notes

Examples of NTTA graphs: Garden and animal care (unpaid)

0.5 1 1.5 2 2.5 3 3.5 4 5 8 13 18 23 28 33 38 43 48 53 58 63 68 73 78 h

• u

r s age male femal

Total unpaid work

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5 8 13 18 23 28 33 38 43 48 53 58 63 68 73 78 Hours per day Age Farmtotal, male Farmtotal, male (smoothed) Farmtotal, female Farmtotal, female (smoothed)

• Vision identifies human capital development as a

key foundation for national socio‐economic transformation

• Since 1994, several policy interventions have

aimed at promoting human capital development, especially in the areas of education and health