Syndicate content

Blogs

Better Nutrition Through Information

Markus Goldstein's picture

In honor of Labor Day here in the US, I want to talk about a recent nutrition paper by Emla Fitzsimons, Bansi Malde, Alice Mesnard and Marcos Vera-Hernandez.   This paper, “Household Responses to Information on Child Nutrition,” is one with a twist – they look not only at nutrition outcomes, but they also try and figure out where these might be coming from – and hence also look at labor supply.  

Power of the Pill or Power of Abortion?

Berk Ozler's picture

I am a dual citizen of two countries, both of which legalized safe abortions when I was little or young, meaning that I grew up taking a woman’s right to a safe abortion as granted. Usually, when I hear family planning policy, I think of men and women planning the number, the timing, and the spacing of their children with the aid of modern contraceptives.

Paper or Plastic? Part II: Approaching the survey revolution with caution

Markus Goldstein's picture

Coauthored with Raka Banerjee and Talip Kilic

So if you missed it, Part I of this two-part blog post outlines all of the main reasons that you should consider incorporating Computer Assisted Personal Interviewing (CAPI) into your survey efforts. We’ll now try to even things out, by going over the many pitfalls to watch out for when switching to CAPI.

Guest Post by Howard White: Can we do small n impact evaluations?

3ie was set up to fill ‘the evaluation gap’, the lack of evidence about ‘what works in development’. Our founding document stated that 3ie will be issues-led, not methods led, seeking the best available method to answer the evaluation question at hand. We have remained true to this vision in that we have already funded close to 100 studies in over 30 countries around the world.

Guest Post by Winston Lin: Regression adjustment in randomized experiments: Is the cure really worse than the disease? (Part II)

1. Putting the bias issue in perspective

 

Yesterday’s post addressed two of the three problems David Freedman raised about regression adjustment. Let’s turn to problem #3, the small-sample bias of adjustment. (More technical details and references can be found in my paper.)

 

Guest Post by Winston Lin - Regression adjustment in randomized experiments: Is the cure really worse than the disease? (Part I)

Random assignment is intended to create comparable treatment and control groups, reducing the need for dubious statistical models. Nevertheless, researchers often use linear regression models to "adjust" for random treatment-control differences in baseline characteristics.

Pages