Search, Matching and Training

Abstract

We estimate a partial and general equilibrium search model in which firms and workers choose how much time to invest in both general and match-specific human capital. To help identify the model parameters, we use NLSY data on worker training and we match moments that relate the incidence and timing of observed training episodes to outcomes such as wage growth and job-to-job transitions. We use our model to offer a novel interpretation of standard Mincer wage regressions in terms of search frictions and returns to training. Finally, we show how a minimum wage can reduce training opportunities and decrease the amount of human capital in the economy.

Wages, Experience and Training of Women over the Lifecycle

“…This is a central question, all the more so if we are to understand why college graduates have such high levels of job training but little or no observed return. In a follow up paper we are investigating this issue based on a model inspired by Acemoglu and Pischke (1999) (see also Flinn et al (2017), Lentz and Roys (2015)). end with 56,093 individual-year observations after the cleaning trajectories after they cross self-employment or full-time education.…”

Macroeconomic Long-Run Effects of the German Minimum Wage when Labor Markets are Frictional

“…However, from a theoretical, experimental, and empirical perspective, positive spillovers are likely, even on sectors not directly affected by the policy (lighthouse effects). Methodologically, extensions of the model should integrate and analyze the role of fairness (Green/Harrison 2010;Falk et al 2006;Dittrich et al 2011) and explore other mechanisms for the employment decision (Brown et al 2014(Brown et al , 2015 and for wage setting (Burdett/Mortensen 1998;Flinn et al 2017). A further extension could involve the inclusion of a participation margin, similarly to Flinn (2006), which may significantly mitigate the disemployment effects found here.…”

Actors in the Child Development Process

“…26 Using the point estimates of the model parameters, we focus on the growth in child quality between ages 15 and 16 in the baseline and under the unrestricted transfer policy, while varying the level of the transfers. 27 Let g t denote the average growth rate in child latent human capital between age t and t + 1, which is given by…”

“…This comparison is with a restricted transfer policy that offers an in-kind transfer of φ U of childinvestment goods and with a conditional cash transfer policy that pays φ U when the household satisfies the requirements for receiving the transfer 27. Recall that we are assuming that all households receive the same amount of the transfer, φ U .…”