Jere R. BehrmanUniversidad de Chile

13 Diciembre 2011

International Team: Hollis Chenery, Richard Eckaus, Paul Rosenstein-Rodan, Carlos Diaz-Alejandro, Edmar Bacha, Peter Clark, LanceTaylor

National Team: Alejandro Foxley, Ana Maria Jul, Ricardo Lira, Cristian Osa

Other National Economists: Ricardo Ffrench-Davis, Joseph Ramos, Vitorio Corbo, Marcelo Selowsky

"Sectoral Elasticities of Substitution Between Capital and Labor in a Developing Economy: Time Series Analysis in the Case of Postwar Chile," Econometrica 40:2 (March 1972), 311-328 (Spanish translation in Cuadernos de Economia 9:26, April 1972, 70-88).

"The Determinants of the Annual Rates of Change of Sectoral Money Wages in a Developing Economy," International Economic Review 12:3 (October 1971), 431-447 (Spanish translation in Cuadernos de Economia 9:27, August 1972, 102-119).

"Short-Run Flexibility in a Developing Economy," Journal of Political Economy 80:2 (March/April 1972), 292-313.

"Sectoral Investment Determination in a Developing Economy,"

American Economic Review 62:5 (December 1972), 825-841.

Macroeconomic Policy in a Developing Country: The Chilean Experience, Amsterdam: North-Holland Publishing Company, 1977 (Contributions to Economic Analysis, No. 106).

Foreign Trade Regimes and Economic Development: Chile, New York: Columbia University Press for NBER, 1976 (Special Conference Series on Foreign Trade Regimes and Economic Development, edited by Jagdish Bhagwati and Anne O. Krueger,Vol. 8).

Substantial flexibility and responsiveness to incentives both for capacity utilization and capacity expansion.

Therefore substantial policy distortions through high and high variance barriers to international sector likely to have been costly

Encuesta Protección Social National Team: Alberto Arenas, David Bravo, Javiera

Vasquez, Sandra Quijada (and the Survey Unit) International Team: Olivia Mitchell, Petra Todd and

Kenneth Wolpin at University of Pennsylvania Analysis of pension system, schooling U.S. National Institutes of Aging and Spencer

Foundation grants for collaborative research Exploration of parallel surveys in other LAC countries

led by Alberto Arenas and David Bravo, with support from IDB.

“The Chilean Pension Reform Turns 25: Lessons from the Social Protection Survey” (with Alberto Arenas de Mesa, David Bravo, Olivia S. Mitchell, Petra E. Todd and with the assistance of Andres Otero, Jeremy Skog, Javiera Vasquez, Viviana Velez-Grajales), in Stephen J. Kay and Tapen Sinha, eds. Lessons from Pension Reform in the Americas. Oxford University Press, 2008, 23-58.

“First-Round Impacts of the 2008 Chilean Pension System Reform” (with Maria Cecilia Calderon, Olivia S. Mitchell, David Bravo, and Javiera Vasquez), Journal of Pension Economics and Finance (revised and resubmitted).

“Teacher Labor Markets in Chile” (with David Bravo, Michela Tincani, Petra Todd, Kenneth Wolpin), in progress.

“How Much Might Human Capital Policies Affect Earnings Inequalities and Poverty?” Estudios de Economía 38:1 (June 2011), 9-42.

“Financial Literacy, Schooling and Wealth” (with Olivia S. Mitchell, Cindy K. Soo and David Bravo) American Economic Review. Forthcoming 2012.

Pension Wealth

Housing Wealth

Other Wealth

Total Net Wealth

Pension Density

Calculated Retirement

Money

Schooling 5.55 1.98 2.66 10.18 3.23 1.12

Fin Lit 3.23 1.14 1.83 6.2 1.88 0.62

Fin Lit 3.4 1.06 4.46 8.93 1.94 0.31Schooling -0.34 0.14 -5.05 -5.25 -0.12 0.58

Fin Lit -2.28 -1.51 0.28 -3.51 2.15 2.19

Schooling 2.44 1.4 -3.01 0.82 -0.23 -0.34Fin Lit*Schooling 0.44 0.2 0.33 0.97 -0.02 -0.15

Fin Lit*Schooling 0.34 0.12 0.2 0.66 0.19 0.06

Table I. Instrumental Variable Estimates of Schooling & Financial Literacy on Wealth Outcomes, Pension Contributions, and Retirement Planning

Bold means statistically significant.

Panel II. Fin Lit Index Alone

Panel I. Schooling Alone

Panel III. Both Fin Lit and Schooling

Panel IV. Linear and Interaction Effects

Panel V. Interaction Effect Alone

Const R sq

Prim Sec Ter Level Square F

0.04 0.102 0.235 0.04 -0.00048 12.412 0.201

5.31 22.9 36.69 28.79 -22.5 286 1009

xMale 0.036 0.015 -0.038 0.169

4.16 2.84 -4.2 4.05

0.039 0.104 0.227 0.022 -0.0003 5.481 0.339

9.06 49.16 77.89 21.37 -16.44 220.08 2810

xMale 0.041

30.42

Weighted Semi-Log Earnings and Wage Functions for 51,244 Adults Age 21+ in 2004 Chilean SPS *

Spline in Schooling Pot Experience

*t-statistics in italics beneath coefficient estimates; potential experience is age - schooling attainment - 6; the row with "xMale" includes all significant coefficients for the interaction between "male" and the right-side variable in that column

ln Wage

ln Earnings

Level SE Level SE Level SE

Schooling 0.23 0.001 0.18 0.002 0.30 0.002

Earnings 0.53 0.003 0.20 0.002 0.36 0.002

1 3 grades sch <=6 Schooling 0.18 0.001 0.06 0.001 0.18 0.002

Earnings 0.52 0.003 0.18 0.002 0.33 0.002

2 3 grades sch <=9 Schooling 0.16 0.001 0.06 0.001 0.15 0.002

Earnings 0.51 0.003 0.17 0.002 0.31 0.002

3 to 6 grades sch < 6 Schooling 0.19 0.000 0.00 0.000 0.30 0.002

Earnings 0.52 0.003 0.19 0.002 0.34 0.002

4 to 9 grades sch < 9 Schooling 0.12 0.001 0.00 0.000 0.00 0.000

Earnings 0.50 0.003 0.16 0.002 0.30 0.002

Base

Simulations of Impacts of Changed Schooling Distribution on Inequality and Poverty Based on 2004 Chilean Social Protection Survey*

Simulation Gini Poverty Headcount

Schooling Change

Target Pop

Coefficient "Low" Cutoff "Higher" Cutoff

Encuesta Longitudinal de la Primera Infancia (ELPI)

“Tools of the Mind” preschool experiment National Team: David Bravo, Marthita Kluttig,

Daniela Marshall, Pamela Soto, Sergio Urzúa International Team: Elena Bordova, Angela

Duckworth, Patrice Engle, Deborah Leong, Thomas McDade, Whitney Schott

United States National Institute of Child Health and Development grant for analysis

“Economic Perspectives on Some Important Dimensions of Early Childhood Development in Developing Countries” (with Sergio Urzúa) in Pia Rebello Britton, Patrice L. Engle and Charles M. Super, eds, Handbook of Early Childhood Development: Translating Research to Global Policy Oxford, UK: Oxford University Press, 2012.

“Cognitive and Non-Cognitive Patterns in Chilean Early Childhood Development: Associations with Income and Other Factors” (with David Bravo, Marthita Kluttig, Daniela Marshall, Whitney Schott, Pamela Soto), 2011.

“Wealth gradients in early childhood cognitive development in five Latin American countries” (with Norbert Schady, Maria Caridad Araujo, Rodrigo Azuero, Raquel Bernal, David Bravo, Florencia Lopez-Boo, Karen Macours, Daniela Marshall, Christina Paxson, and Renos Vakis), Washington, DC: Inter-American Development Bank, 2011.

Cognitive skills are but one component of early childhood development and recent literature suggests possible high payoffs to others as well, such as executive function

Here we look at (1) patterns by income quintile and (2) simple regressions for cognitive and language skills, anthropometrics and motor skills, behavioral and social-emotional skills

Measures of child development not highly correlated

Encuesta Longitudinal de la Primera Infancia

First round of data, 2010 Representative sample of 13,895 children,

ages 9-55 months for this presentation (ELPI also includes children 0-8 months)

Includes measures of cognitive, psychosocial, and physical development, as well as parental schooling, income, and household environment

Ages Measure Description Components/examples

8-24 months

Battelle Developmental Inventory (Battelle)

A battery of tests to evaluate fundamental components of development

Communication:Example: Smiles in response to interaction with adult

24-53 months

Test of Psychomotor Development(TEPSI)

Evaluates psychomotor development

LanguageExamples: recognizes big and small, names shapes, describes scenes

30-53 months

Peabody Picture Vocabulary Test (TVIP)

Evaluates cognitive skill level

Children are asked to identify what is shown in picturesBoat, cow, cooperation, surprised, crawl

Ages Measure

9-53 months Z-score length for ageZ-score weight for lengthZ-score for BMIZ-score for head circumference

(Z scores give standard deviations from medians)

Ages Measure Description Component/Examples

8-24 months

Battelle Developmental Inventory (Battelle)

A battery of tests to evaluate fundamental components of development

MotorExamples: Sits without support, walks holding an object, climbs stairs, turns pages of a book, copies a circle, folds a piece of paper in half

24-53 months

Test of Psychomotor Development (TEPSI)

Evaluates psychomotor development

CoordinationExamples: Can make a tower with 8 blocks, can copy a circle, can button and unbuttonMotor skillsExamples: can jump with both feet, throws a ball with one hand, jumps on one foot three times

Ages Measure

Description Examples

18-53 months

from Child Behavior Checklist

Composite of inattention, restlessness/impatience, noncompliance, distractibility, lack of emotional regulation

Examples: Can’t concentrate, can’t sit still, disobedient, easily frustrated

Ages Measure Description Components

9-18 months

Ages and Stages (ASQ)

Screening for possible social/emotional developmental delays

Self-regulation, affect, interaction with people, autonomyExample: Does your child enjoy being held? Does your baby smile?

8-24 months

Battelle Develop-mental Inventory

A battery of tests to evaluate fundamental components of development

Personal/social: interaction with adults, expression of emotions, interaction with peersExample: Smiles in response to interaction with adultAdaptability: ability for self-help/independenceExample: Puts on his/her own shoes

18-53 from Child Behavior Checklist (CBCL)

Composite of emotional and social skills

Examples: Avoids eye contact, does not get along with peers, fights a lot, cries a lot, shows little affection towards people

(negative)

(negative)

(negative)

Even at very young ages (9 to 24 months), level differences in cognitive skills are apparent by income quintile, and education and WAIS score of the mother

Divergence in cognitive skills appears to take place after age 3 (between 36 and 40 months)

This divergence is characterized by the lowest quintile not improving, while the highest quintile does improve, as evidenced by TVIP scores

Patterns by income are less clear for the anthropometric measures

There are differences by income in coordination, and possibly in motor skills

Pronounced level differences in behavioral and socio-emotional indices at young ages

Possible divergence in behavioral development between the highest and lowest quintiles around 40 months

1. Regressed each measure on income quintiles and age in month dummies only

2. Regressed each measure on household environment and parental characteristics, plus age in month dummies

When other variables included, income differences less pronounced:

Ages 30-53 months

Ages 9-53 months

Ages 9-53 months

Ages 24-53 months

Ages 9-53 months

When income associations are important, controlling for other factors reveals that mother’s cognitive skills play a key role in “explaining” much of these difference

This is true for both cognitive and non-cognitive measures: coordination, behavior, and socio-emotional skills

For behavioral and socio-emotional skills, having an older and wiser mother is associated with better outcomes

Birth weight has persistent and large associations not only with anthropometric measures, but also with coordination, language ability, motor skills, and cognitive performance

Day care enrollment is negatively associated with cognitive performance at young ages, but positively associated with language after 24 months; it is negatively associated with behavioral outcomes for all ages

Females have higher TVIP scores, language ability, better coordination and motor skills, and fewer behavioral social/emotional problems

Overall, a wide array of home environmental and parental characteristics are associated with child development when these multiple components of child development are considered.

Important to move beyond associations to estimate causal effects with both 2010 and 2012 ELPI as guide for understanding and policy.