- #1

Haboudane farid

- 1

- 0

Which means what in impact evaluation

You are using an out of date browser. It may not display this or other websites correctly.

You should upgrade or use an alternative browser.

You should upgrade or use an alternative browser.

- MHB
- Thread starter Haboudane farid
- Start date

Thank you.In summary, a non-separable model in the error term is a statistical model used in impact evaluation where the errors in the data are correlated with the explanatory variables. This type of model can provide more accurate estimates of the impact of an intervention or program being studied.

- #1

Haboudane farid

- 1

- 0

Which means what in impact evaluation

Mathematics news on Phys.org

- #2

jvicens

- 1,422

- 2

Hello,

The term "non-separable model in the error term" refers to a type of statistical model used in impact evaluation. In this type of model, the errors or random variations in the data are not independent of the explanatory variables. This means that the errors are correlated with the variables being studied, which can affect the accuracy of the results.

In impact evaluation, a non-separable model in the error term may be used when analyzing the impact of a specific intervention or program on an outcome of interest. By taking into account the correlation between the errors and the explanatory variables, this type of model can provide more accurate estimates of the intervention's impact.

I hope this helps clarify the meaning of a non-separable model in the error term in the context of impact evaluation. Let me know if you have any further questions.

A non-separable model error term refers to the part of the model that cannot be explained by the independent variables. It represents the random variability in the outcome variable that is not accounted for by the explanatory variables.

The non-separable model error term can affect the results of an impact evaluation by introducing bias into the estimated effects of the independent variables. This can lead to incorrect conclusions about the effectiveness of a program or intervention.

No, non-separable model error terms cannot be eliminated completely. However, they can be minimized by carefully selecting and controlling for relevant variables and using appropriate statistical methods.

There are several potential sources of non-separable model error terms, including measurement error, omitted variables, and unobserved heterogeneity among individuals or groups being evaluated.

To address non-separable model error terms, researchers can use techniques such as instrumental variables, fixed effects, or difference-in-differences to control for potential sources of bias. It is also important to carefully consider and justify the choice of variables and statistical methods used in the evaluation.

- Replies
- 8

- Views
- 2K

- Replies
- 18

- Views
- 3K

- Replies
- 1

- Views
- 1K

- Replies
- 5

- Views
- 2K

- Replies
- 1

- Views
- 1K

- Replies
- 5

- Views
- 1K

- Replies
- 4

- Views
- 2K

- Replies
- 3

- Views
- 904

- Replies
- 2

- Views
- 1K

- Replies
- 1

- Views
- 2K

Share: