Estimating the Technology of Cognitive and Noncognitive Skill Formation



Panel B of Table 4 presents estimates of the technology of noncognitive skills. Note that,
contrary to the estimates reported for the technology for cognitive skills, the elasticity of
substitution increases slightly from the first stage to the second stage. For the early stage,
σ1,N = 0.62 while for the late stage, σ2,N = 0.65. The elasticity is about 50% higher for
investments in noncognitive skills for the late stage in comparison to the elasticity for invest-
ments in cognitive skills. The estimates of
σ1,N and σ2,N are not statistically significantly
different from each other, however.
39 The impact of parental investments is about the same
at early and late stages (
γ1,N,3 = 0.06 vs. γ2,N,3 = 0.05). Parental noncognitive skills affect
the accumulation of a child’s noncognitive skills both in early and late periods, but parental
cognitive skills have no effect on noncognitive skills at either stage. The estimates in Ta-
ble 4 show a strong effect of parental cognitive skills at both stages of the production of
noncognitive skills.

4.2.5 A More General Approach to Solving the Problem of the Endogeneity of
Inputs

This section relaxes the invariant heterogeneity assumption and reports empirical results
from a more general model of time-varying heterogeneity. Our approach to estimation is
motivated by the general analysis of Section 3.6.2, but, in the interest of computational
tractability, we make parametric and distributional assumptions.

We augment the measurement system (3.1)-(3.3) by investment equation (3.11), which
is motivated by economic theory. Our investment equation is

It = kC θC,t + kN θN,t + kC,P θC,P + kN,P θN,P + kyyt + πt.40               (4.2)

We substitute (4.2) into equations (3.2) and (3.10). We specify the income process as

lnyt = ρy ln yt-1 + νy,t,                                     (4.3)

and the equation of motion for πt as

πt = ρππt-1 + νπ,t.                                      (4.4)

We assume that νy,t ⊥⊥ (θt0 , νy,t0 ) for all t0 6= t and νy,t ⊥⊥ (yt0 , νk,t, θP ), t > t0, k {C, N},
where
“_LL” means independence. We further assume that νπ,t _LL (θtopk,to) and that
39See Table 10-5 in Web Appendix 10.

40 The intercept of the equation is absorbed into the intercept of the measurement equation.

29



More intriguing information

1. Surveying the welfare state: challenges, policy development and causes of resilience
2. The name is absent
3. Improving behaviour classification consistency: a technique from biological taxonomy
4. The name is absent
5. On Dictatorship, Economic Development and Stability
6. The name is absent
7. Disturbing the fiscal theory of the price level: Can it fit the eu-15?
8. RETAIL SALES: DO THEY MEAN REDUCED EXPENDITURES? GERMAN GROCERY EVIDENCE
9. The name is absent
10. Review of “The Hesitant Hand: Taming Self-Interest in the History of Economic Ideas”
11. Input-Output Analysis, Linear Programming and Modified Multipliers
12. Motivations, Values and Emotions: Three Sides of the same Coin
13. The name is absent
14. AGRIBUSINESS EXECUTIVE EDUCATION AND KNOWLEDGE EXCHANGE: NEW MECHANISMS OF KNOWLEDGE MANAGEMENT INVOLVING THE UNIVERSITY, PRIVATE FIRM STAKEHOLDERS AND PUBLIC SECTOR
15. Inflation and Inflation Uncertainty in the Euro Area
16. AN ECONOMIC EVALUATION OF THE COLORADO RIVER BASIN SALINITY CONTROL PROGRAM
17. Wirkt eine Preisregulierung nur auf den Preis?: Anmerkungen zu den Wirkungen einer Preisregulierung auf das Werbevolumen
18. Novelty and Reinforcement Learning in the Value System of Developmental Robots
19. Une Gestion des ressources humaines à l'interface des organisations : vers une GRH territoriale ?
20. Antidote Stocking at Hospitals in North Palestine