Final answer:
A model employing dummy variables D and T, along with variable Y representing benefits, can be used to evaluate the differential impact of a job training program on immigrants versus non-immigrants. The interaction term in the model indicates the additional effect the training program has on immigrants. The significance of this term determines if there is a differential impact.
Step-by-step explanation:
When evaluating the differential impact of a job training program on immigrants compared to non-immigrants, a statistical model can be employed that incorporates dummy variables to capture the distinct effects. In this case, you would introduce two dummy variables: D, which represents immigration status (1 if the individual is an immigrant, 0 if not), and T, which indicates participation in the training program (1 if the individual has participated, 0 if not). The dependent variable Y would represent the "benefits" received from the program, which could include various metrics such as an increase in wages, employment probabilities, or skill levels.
The model could be specified as follows:
- Y = α + βD + γT + δ(D*T) + ε
α is the constant term, β captures the difference in benefits for immigrants, γ represents the average impact of the training program, δ is the interaction term between being an immigrant and participating in the training program, and ε is the error term. The interaction term δ is crucial as it shows the additional effect, if any, that the training program has on immigrants over and above the effect it has on non-immigrants.
To assess the differential impact, you would estimate the model and specifically look at the estimate for δ. A significantly positive δ would suggest that immigrants benefit more from the training program, while a significantly negative δ would indicate they benefit less. If δ is not significantly different from zero, this suggests there is no differential impact of the training program between immigrants and non-immigrants.