Contents
What are identification assumptions?
Identifying assumption: assumptions made about the DGP that allows you to draw causal inference. In other words, the ‘identification assumption’ you make for estimate the causal effect of smoking on cancer rates, i.e. that smokers & non-smokers only differ in terms of their smoking behavior, is likely not to hold here.
What is excluded instrument?
The (L+M) variables in zi are called instruments. The L additional variables in zi which are not included in xi are called excluded instruments. Sometimes only those L variables are called instruments.
How are assumptions stated?
Assumptions can be either explicit (directly stated) or implicit (not directly stated but implied). When you identify someone’s assumptions, look for both kinds. An explicit premise in the sample article is the statement that “the stranded were poor, black, disproportionately elderly” (paragraph 5).
What is the monotonicity assumption?
The monotonicity assumption implies there are no “defiers”, i.e., no patients who would be prescribed Treatment A when seen by a physician who usually prefers B and would be prescribed Treatment B when seen by a physician who usually prefers A (a rigorous and more general definition is provided below).
When do you need to make identification assumptions?
If one tries to construct a statistical model by adding unobserved disturbances to an economic model, identification needs to be addressed. In order to make the resulting structural econometric model identified, usually one needs to make certain assumptions, either of economic or technical nature. These are called identification assumptions.
When to use IVs in instrumental variable estimation?
Instrumental variables estimation. Intuitively, IVs are used when an explanatory variable of interest is correlated with the error term, in which case ordinary least squares and ANOVA give biased results. A valid instrument induces changes in the explanatory variable but has no independent effect on the dependent variable,…
Which is an identification assumption for diff-in-diff?
For diff-in-diff, the parallel-trends condition is an identification assumption. For regression discontinuity design, the identification assumptions are that, first, there are no other discontinuities except the forcing variable, and second, agents cannot manipulate the forcing variable.
Which is better, an OLs or an IV estimate?
The precision of IV estimates is lower than that of OLS estimates (least squares is just that). In the presence of weak instruments (excluded instruments only weakly correlated with included endogenous regressors) the loss of precision will be severe, and IV estimates may be no improvement over OLS.