Macroeconometrics — the science of hubris When a macroeconometrician uses regression, he or she is implicitly saying, in effect, that the third quarter of 2007 is the same as the first quarter of 1988, once all factors that might be different between those two quarters are controlled for. The idea is that the economist is conducting an intertemporal quasi-experiment. But because there is only one economic history with which to work, there is a lack of...
Read More »Selection bias and the elite school illusion
Selection bias and the elite school illusion [embedded content] A great set of lectures — but I still warn my students that regression-based averages is something we have reasons to be cautious about. Suppose we want to estimate the average causal effect of a dummy variable (T) on an observed outcome variable (O). In a usual regression context one would apply an ordinary least squares estimator (OLS) in trying to get an unbiased and consistent estimate: O...
Read More »R A Fisher — the father of modern statistics (1/4)
R A Fisher — the father of modern statistics (1/4) [embedded content]
Read More »Causality — the back-door criterion
Causality — the back-door criterion [embedded content]
Read More »Working with DAGs (wonkish)
Working with DAGs (wonkish) [embedded content]
Read More »On causality and econometrics
On causality and econometrics The point is that a superficial analysis, which only looks at the numbers, without attempting to assess the underlying causal structures, cannot lead to a satisfactory data analysis … We must go out into the real world and look at the structural details of how events occur … The idea that the numbers by themselves can provide us with causal information is false. It is also false that a meaningful analysis of data can be done...
Read More »Experiments in social sciences
Experiments in social sciences How, then, can social scientists best make inferences about causal effects? One option is true experimentation … Random assignment ensures that any differences in outcomes between the groups are due either to chance error or to the causal effect … If the experiment were to be repeated over and over, the groups would not differ, on average, in the values of potential confounders. Thus, the average of the average difference of...
Read More »Dynamic and static interpretations of regression coefficients (wonkish)
Dynamic and static interpretations of regression coefficients (wonkish) When econometric and statistical textbooks present simple (and multiple) regression analysis for cross-sectional data, they often do it with regressions like “regress test score (y) on study hours (x)” and get the result y = constant + slope coefficient*x + error term. When speaking of increases or decreases in x in these interpretations, we have to remember that it is a question of...
Read More »Why all RCTs are biased
Why all RCTs are biased Randomised experiments require much more than just randomising an experiment to identify a treatment’s effectiveness. They involve many decisions and complex steps that bring their own assumptions and degree of bias before, during and after randomisation … Some researchers may respond, “are RCTs not still more credible than these other methods even if they may have biases?” For most questions we are interested in, RCTs cannot be more...
Read More »How to teach econometrics
How to teach econometrics Professor Swann (2019) seems implicitly to be endorsing the traditional theorem/proof style for teaching econometrics but with a few more theorems to be memorized. This style of teaching prepares students to join the monks in Asymptopia, a small pristine mountain village, where the monks read the tomes, worship the god of Consistency, and pray all day for the coming of the Revelation, when the estimates with an infinite sample will...
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