Identifying sensitive periods in which the returns to investments into skills are especially high is challenging, but crucial for an effective and efficient timing of parental or public investments aimed at fostering children's skills. We can detect sensitive periods with a novel design by...

We investigate how strongly the local environment beyond the family can contribute to understanding the formation of children's economic preferences. Building on precise geolocation data for around 6000 children, we use fixed effects, spatial autoregressive models and Kriging to capture the...

Identifying sensitive periods in which the returns to investments into skills are especially high is challenging, but crucial for an effective and efficient timing of parental or public investments aimed at fostering children's skills. We can detect sensitive periods with a novel design by...

Identifying sensitive periods in which the returns to investments into skills are especially high is challenging, but crucial for an effective and efficient timing of parental or public investments aimed at fostering children's skills. We can detect sensitive periods with a novel design by...

We investigate how strongly the local environment beyond the family can contribute to understanding the formation of children's economic preferences. Building on precise geolocation data for around 6.000 children, we use fixed effects, spatial autoregressive models and Kriging to capture the...

We investigate how strongly the local environment beyond the family can contribute to understanding the formation of children's economic preferences. Building on precise geolocation data for around 6.000 children, we use fixed effects, spatial autoregressive models and Kriging to capture the...

Identifying sensitive periods in which the returns to investments into skills are especially high is challenging, but crucial for an effective and efficient timing of parental or public investments aimed at fostering children’s skills. We can detect sensitive periods with a novel design by...

We investigate how strongly the local environment beyond the family can contribute to understanding the formation of children's economic preferences. Building on precise geolocation data for around 6000 children, we use fixed effects, spatial autoregressive models and Kriging to capture the...

We investigate how strongly the local environment beyond the family can contribute to understanding the formation of children's economic preferences. Building on precise geolocation data for around 6.000 children, we use fixed effects, spatial autoregressive models and Kriging to capture the...

We investigate how strongly the local environment beyond the family can contribute to understanding the formation of children's economic preferences. Building on precise geolocation data for around 6.000 children, we use fixed effects, spatial autoregressive models and Kriging to capture the...