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Estimate the effect of a job training program on real earnings of individuals

You can use Actable AI's no-code Data Science platform to estimate if an individual goes to certain training program how that training would impact that individuals future earnings. This kind of insights could help you better understand the impact of any training program and if its effectiveness justifies the effort and investment.

In this specific example, we use our causal inference to estimate the causal relationship between a job training program and the program attendees real life earning. As an example dataset, we are using a classical dataset from Lalonde 1986 widely used in academia. The video below shows the results of our casual inference analytics estimating whether attending a job training program (treat) has any impact on your real earnings (re78).

Example Dataset

The dataset consist of 445 observations on the 12 variables. More info about the dataset can be found here: Lalonde 1986 and Dehejia & Wahba 1999 scientific studies. Below are the 12 variables and their descriptions.

age: age in years

educ: years of schooling

black: indicator variable for blacks

hisp: indicator variable for hispanics

married: indicator variable for martial status

nodegr: indicator variable for high school diploma

re74: real earnings in 1974

re75: real earnings in 1975

re78: real earnings in 1978

u74: indicator variable for earnings in 1974 being zero

u75: indicator variable for earnings in 1975 being zero

treat: an indicator variable for treatment status

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