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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.

Sudoku quilts and job matches: An experiment on networks and job referrals

David McKenzie's picture

One of the frustrations facing job seekers worldwide, but especially in many developing countries, is how much finding a job depends on who you know rather than what you know. For example, in work I’ve done with small enterprises in Sri Lanka, less than 2 percent of employers openly advertised the position they last hired – with the most common ways of finding a worker being to ask friends, neighbors or family members for suggestions. Clearly networks matter for finding jobs.

What are "Mechanism Experiments" and should we be doing more of them?

David McKenzie's picture

In an interesting new paper, Jens Ludwig, Jeffrey Kling and Sendhil Mullainathan argue that economists should be doing more experiments to identify behavioral mechanisms, and that these can be central to policy, even if the experiments themselves are far from what a policymaker would implement. So what are these mechanism experiments, and what can we learn from them?