Econometrics: Controls and Difference-in-Differences

In summary, the poster is working on an econometrics project using a difference-in-differences approach to estimate the effects of the 1996 TANF welfare reform in the US on ln(total household income). They ask when it is appropriate to add controls in this framework and for ideas on instrumental variables in the Current Population Survey. It is appropriate to add controls when there are other factors that could affect the outcome variable and are not related to the treatment. Some potential IVs in the Current Population Survey could be parental education or occupation. It is important to thoroughly test the validity of the chosen instrument before using it.
  • #1
aridneptune
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Sorry for the double post with the SS section -- I thought this was probably a better place to ask this question.

Hello all,
I'm working on an econometrics project in which I'm using difference-in-differences approach to estimate the effects of the 1996 TANF welfare reform in the US. My main dependent variable is ln(total household income). My treated group is single women with children and my control group is single women without children.

My question is, when is it appropriate to add controls in a difference-in-differences regression framework? Is it only when one believes that the value of the control variables differs systematically (i.e. with time) between the treatment and control groups and also affects the dep. var.?

A related question: I want to control for education and want to use an instrumental variable for education. Any good ideas of IVs in the Current Population Survey (must use this dataset)?

Thanks very much!
 
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  • #2


Dear poster,

Thank you for your question. In a difference-in-differences approach, it is appropriate to add controls when there are other factors that could potentially affect the outcome variable (in this case, ln(total household income)) and are not related to the treatment (1996 TANF welfare reform). This could include individual characteristics, such as education or employment status, or external factors, such as changes in the economy or policies unrelated to the TANF reform. Adding controls can help to isolate the effect of the treatment on the outcome variable and provide more accurate estimates.

As for your question about using an instrumental variable for education, it is important to carefully select an instrument that is strongly correlated with education but not directly related to the outcome variable. This can be challenging, but some potential IVs in the Current Population Survey could include parental education or parental occupation. It is important to thoroughly test the validity of your chosen instrument before using it in your regression analysis.

I hope this helps. Good luck with your project!
 

FAQ: Econometrics: Controls and Difference-in-Differences

1. What is the difference between econometrics and regular statistics?

Econometrics is a branch of economics that uses statistical methods to analyze economic data, while regular statistics is a broader field that can be applied to any type of data. Econometrics focuses specifically on economic data and the relationships between variables in a given economic system.

2. What are controls in econometrics?

Controls are variables that are included in an econometric model to account for potential confounding factors. They help to isolate the effect of a particular variable of interest, allowing for a more accurate understanding of causality.

3. Can you explain the difference-in-differences (DID) method?

The DID method is a statistical technique used in econometrics to compare the effect of a treatment or intervention on a group of individuals to a control group. It involves comparing the changes in outcomes for both groups before and after the treatment, and then taking the difference between the two. This helps to control for any other factors that may be affecting the outcome, allowing for a more accurate estimation of the treatment effect.

4. What are some common challenges in using the DID method?

One challenge in using the DID method is ensuring that the treatment and control groups are similar in all other aspects except for the treatment. This can be difficult to achieve in practice. Another challenge is the potential for selection bias, as individuals may self-select into the treatment group, leading to biased results.

5. How is the DID method used in real-world applications?

The DID method is commonly used in policy evaluations, particularly in the field of economics. It has been used to evaluate the impact of various policies such as minimum wage laws, tax reforms, and education programs. It is also used in other fields, such as healthcare and education, to evaluate the effectiveness of interventions.

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