Human Capital: Education and Health in Development Economics

University of New England Week 6

University of New England Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.7 LO.8 LO.9 LO.10 Human Capital: Education and Health Week 6 Prescribed Reading: de Janvry and Sadoulet, ch. 17 ECON390/590 Economics of Developmentune

Learning Objectives Week 6

University of New England Learning Objectives Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10

1. Why are education and health important for development?
2. Indicators and status of education
3. Education and growth
4. What determines the levels of schooling?
5. Estimating the return to education
6. Policy issue: Conditional cash transfers
7. Indicators and status of health
8. What determines health achievements?
9. Impact of health on development outcomes
10. Issues in health policies: The debate around subsidiesthe

Importance of Education and Health for Development

University of New England Why Are Education and Health Important for Development? Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10 Education and health are simultaneously "ends" and "means." Better education and health raise labour productivity and encourage entrepreneurship. Strong positive social externalities associated with individual education and health achievements. However, private under-investment and insufficient public provision in human capital due to parents' low appreciation, liquidity constraints, and free-rider problem. With positive externalities, everyone under-invests in human capital, requiring government intervention to correct market failures via subsidies or free provision. Education and health are public goods, which are non-rival and non-excludable in their uses. Social safety nets are needed to minimise irreversibilities.the

Positive Externalities of Human Capital on Energy Consumption

University of New England Positive Externalities of Human Capital on Energy Consumption Week 6 ELSEVIER Contents lists available at ScienceDirect Energy Economics journal homepage: www.elsevier.com/locate/eneeco Does human capital matter for energy consumption in China? CrossMark Ruhul Salim ª,*, Yao Yao b, George S. Chen ℃ a School of Economics & Finance, Curtin Business School, Curtin University, Perth, WA 6845, Australia b School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong " UNE Business School, University of New England, Armidale, NSW 2351, Australia ARTICLE INFO Article history: Received 12 December 2016 Received in revised form 19 May 2017 Accepted 24 May 2017 Available online 1 June 2017 JEL classification: C33 Q43 J24 050 ABSTRACT This article investigates the dynamic relationship between human capital and energy consumption using Chinese provincial data over the period 1990-2010. Considering for cross-sectional dependence and parameter heteroge- neity across space and over time, we identify a significant and negative human capital-energy consumption relationship in China. Specifically, we find that a 1% increase in human capital reduces energy consumption by a range between 0.18% and 0.45%. Furthermore, this negative relationship can be attributed to stronger accumulation of post-school human capital in eastern China. This finding suggests that energy conservation in China could be achieved by improving post-school human-capital components such as on-the-job training, experience and learning-by-doing. @ 2017 Elsevier B.V. All rights reserved. Energy Economics LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10une

Indicators and Status of Education

University of New England Indicators and Status of Education Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10 Gross enrolment rate (GER): The ratio of the number of children enrolled in a given school category to the number of children in the age group that officially corresponds to that level of schooling. A GER greater than 100% or too low is not a good sign. At the secondary and tertiary levels, GER rises sharply with GDPpc. While GERs have increased across the world, large gaps remain across regions and countries, and between rich and poor, rural and urban areas, and males and females. Net enrolment rate (NER): The percentage of children of a given age group that are enrolled in a given school category. NER is always less than 100% and can be represented in a school enrolment pyramid by age and proportion of the population in each schooling level. 1 0une

Children Out of School and Grade Completion

University of New England Indicators and Status of Education Children out of school: The number of children of primary school age not in school. The largest number is in sub-Saharan Africa. Grade completion rate: The number of children who actually complete a certain grade level, regardless of age, relative to the population at the entrance age for that particular grade. It characterises an education system's coverage and the students' educational attainment. Grade retention rate: The percentage of children that do not pass into the next grade at the end of the school year. Conditional cash transfers (CTTs) that pay mothers to keep their children at school was effective in reducing the dropout rate by half in some instances. Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10une

Educational Attainment and Achievement

University of New England Indicators and Status of Education Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10 Educational attainment: Completed years of schooling per adult in the population of age 25 years or older. It is measured by the percentage distribution of the population across four categories of educational attainments. Educational achievement: The quality of schooling using standardised test procedures. The OECD's Program for International Student Assessment (PISA) in math, sciences, and reading.the

Education and Growth Correlation

University of New England Education and Growth Meta analyses reveal a strong positive correlation between the average level of schooling (Sit ) and GDPpc (Yit). In Yit = a + BSit + Eit where B measures the percentage increase in In Yit associated with a one-year increase in Sit. Estimation issues: Simultaneity between education and growth and between health and growth. Omitted variable bias, e.g. economic institution stability. The quality-quantity debate on education, with quality having a larger impact on growth, e.g. teachers' effort. What explains the large disparities in educational outcomes by country, income level, gender, and residence? Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10une

Determinants of Schooling Levels

University of New England What Determines the Levels of Schooling? To understand the determinants of the schooling levels, suppose an individual lives for two periods: Period 1: School or work Period 2: Work The wage structure: If went to school in period 1 => Earn wi in period 2. If didn't go to school and worked in both periods => Earn w0 in both periods. The economic value of schooling: w1 > Wo. The discount factor is & = + ≤ 1, where r is the discount rate => The pv of period 2's wage is ow. Let i be the intrinsic value of schooling, but it requires a cash expenditure c to attend school. An individual will prefer school in period 1 if, and only if, i- c + 8w1 > wo + Swo =>i+ &(w1 - WO) > c + WO Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10une

School Quality and Family Characteristics

University of New England What Determines the Levels of Schooling? Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10 To account different school qualities, we add three relationships: 1 Schooling produces education (E), which is function of school quality (qs) and family characteristics (x): E = E(qs, x). 2 The wage wi is function of received education (E) and the economic context: w1 = w1(E, Context). 3 The intrinsic value attached to school (i) is function of school quality and family characteristics: i = i(qs, x). The decision that parents make in sending their children to school has both supply- and demand-side determinants.une

Supply and Demand Side Determinants

University of New England What Determines the Levels of Schooling? Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10 Supply side (qs) Quantity indicators: Distance to school and hours of instruction. Quality indicators: Teachers' attendance, level of training, and motivation, and school resources. Demand side . Intrinsic value of schooling (i) Expected economic return from schooling (w1 - wo) Direct cost of schooling (c) Opportunity cost of schooling (w0) Discount factor (8)une

Social Externalities and Under-investment in Education

University of New England Social Externalities and Under-investment Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10 / Expected private returns 1 Returns and costs Tertiary Secondary Private costs Primary 0 Years of schooling completed (a) Private returns and costs Social costs 1 I - Social returns Returns and costs Secondary 1 Primary 1 Tertiary 0 B Years of schooling completed (b) Social returns and costsune

Estimating the Return to Education

University of New England Estimating the Return to Education The Mincer wage equation for an individual: In wi = a + Bschooling; + yexperience; + €i where B measures the percentage increase in wage associated with one more year of schooling. Instrumental variables (IVs) are required to control for endogeneity during estimations. Endogeneity: The regressors are correlated with the error term (ci). Solution: IVs must be related to the regressors but unrelated to the dependent variable. Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10the

Schooling Returns for Migrant Workers in China

University of New England Schooling Returns for Migrant Workers in China Week 6 LO.1 LO.2 LO.3 LO.4 LO.5 LO.6 LO.Z LO.8 LO.9 LO.10 Contents lists available at ScienceDirect China Economic Review ELSEVIER journal homepage: www.elsevier.com/locate/chieco CHINA Economic Review - Schooling returns for migrant workers in China: Estimations from the perspective of the institutional environment in a rural setting Check for updates Yao Yaoº, George S. Chenª,*, Ruhul Salimb, Xiaojun Yud a UNE Business School, University of New England, Armidale, NSW 2351, Australia b School of Economics & Finance, Curtin University, Bentley, WA 6102, Australia School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong SAR d Faculty of Business and Economics, Macquarie University, North Ryde, NSW 2109, Australia ARTICLE INFO JEL classifications: J21 J31 J61 Keywords: Schooling returns Instrumental variables Migrant workers Gender gap rural institutional environment ABSTRACT We examine schooling returns for migrant workers in China based on the 2009 Rural-Urban Migration in China (RUMiC) survey. Using a novel instrumental variable (IV) set based on the institutional environment unique to rural China, we find the point estimates of returns to lie within the range of 7.8%-10.7% for each additional year of schooling. Whilst our estimates are slightly higher than those reported for this cohort of workers in the literature, they are sig- nificantly lower than those enjoyed urban dwellers. Furthermore, we identify a wider gap in schooling returns between male (14.7%) and female (8.5%) migrant workers than the compar- able gap for urban dwellers. Our results provide another line of evidence supporting a segmented labor market in urban China and remain robust to different estimators and under various IV restrictions. We suggest that improving the education system in the rural areas and eliminating the gender gap among migrant workers represent the necessary steps for enhancing social har- mony in the Chinese society.