Unemployment and Endogenous Growth

In this paper we develop a two-sector endogenous growth model with a dual labour market, based on efficiency wages. Growth is driven by intentional R&D performed in the high-tech and high-wage sector. How a change in rivalry among firms affects simultaneously growth and unemployment is examined. On the one hand, an increase of the elasticity of substitution between the product varieties of different high-tech firms reduces market power and leads to higher growth but reduces job prospects. On the other hand, if barriers to entry exist, an increase of the number of rivals in the market (due to removal of entry barriers) leads to lower growth, whereas the effect on aggregate employment is ambiguous.     

Within-family linkages between parental monitoring and adolescents externalizing problems with autonomy support as a moderator

Parents' monitoring efforts are thought to be effective in reducing children's future externalizing problems. Empirical evidence for this claim, however, is limited, as only few studies have unraveled the temporal ordering of these constructs. The present six-wave longitudinal study contributed to the existing literature by examining within-family linkages between monitoring efforts (behavioral control and solicitation) and adolescents' externalizing behaviors while controlling for between-family differences. In addition, it was assessed whether these associations differed when using child versus parent reports, differed for less versus more autonomy-supportive parents, and differed for fathers' versus mothers' monitoring efforts. Longitudinal data (six annual waves) of 497 adolescents (56.9% boys, M_age at T₁ = 13.03, SD = 0.46), their mothers (N = 495, M_age at T₁ = 44.41, SD = 4.45), and their fathers (N = 446, M_age at T₁ = 46.74, SD = 5.10) of the Dutch study Research on Adolescent Development and Relationships (RADAR) were used. Results showed no evidence for the claim that parents' monitoring efforts predict future externalizing problems. In contrast, we found some evidence for the idea that parents' monitoring efforts change in reaction to changes in externalizing problems; when adolescents reported higher levels of externalizing problems than usual in 1 year, this predicted less behavioral control from mothers in the next year. Linkages between monitoring efforts and externalizing problems did not differ between less or more autonomy-supportive parents. Overall, our findings suggest that monitoring efforts are not effective, but also not damaging, in relation to adolescents' externalizing problems.     

Using machine learning to identify early predictors of adolescent emotion regulation development

As 20% of adolescents develop emotion regulation difficulties, it is important to identify important early predictors thereof. Using the machine learning algorithm SEM-forests, we ranked the importance of (87) candidate variables assessed at age 13 in predicting quadratic latent trajectory models of emotion regulation development from age 14 to 18. Participants were 497 Dutch families. Results indicated that the most important predictors were individual differences (e.g., in personality), aspects of relationship quality and conflict behaviors with parents and peers, and internalizing and externalizing problems. Relatively less important were demographics, bullying, delinquency, substance use, and specific parenting practices—although negative parenting practices ranked higher than positive ones. We discuss implications for theory and interventions, and present an open source risk assessment tool, ERRATA.