If you can’t devise an experiment that answers your question in a world where anything goes, then the odds of generating useful results with a modest budget and nonexperimental survey data seem pretty slim. The description of an ideal experiment also helps you formulate causal questions precisely. The mechanics of an ideal experiment highlight the […]
Statistics & Econometrics
It is widely recognized but often tacitly neglected that all statistical approaches have intrinsic limitations that affect the degree to which they are applicable to particular contexts … John Maynard Keynes was perhaps the first to provide a concise and comprehensive summation of the key issues in his critique of Jan Tinbergen’s book Statistical Testing […]
Ed Leamer’s Tantalus on the Road to Asymptopia is one of my favourite critiques of econometrics, and for the benefit of those who are not versed in the econometric jargon, this handy summary gives the gist of it in plain English: Most work in econometrics is — still — made on the assumption that the researcher […]
The Potential Outcome framework starts by defining the potential outcomes with reference to a manipulation. In doing so it makes a distinction between attributes or pre-treatment variables which are fixed for the units in the population, and causes, which are potentially manipulable. This is related to the connection between causal statements and randomized experiments. The […]
Econometricians would like to project the image of agricultural experimenters who divide a farm into a set of smaller plots of land and who select randomly the level of fertilizer to be used on each plot. If some plots are assigned a certain amount of fertilizer while others are assigned none, then the difference between […]
The problem with a table presenting multiple estimated effect measures from the same model (“Table 2”) is that it encourages the reader to interpret all these estimates in the same way, typically as total-effect estimates. As illustrated above, the interpretation of a confounder effect estimate may be different than for the exposure effect estimate. Of […]
Breaking news! Using advanced multiple nonlinear regression models similar to those in recent news stories on alcohol and dairy and more than 3.6M observations from 1997 through 2012, I have found that drinking more causes people to turn into men! Across people drinking 0-7 drinks per day, each drink per day causes the drinker’s probability […]
. The central problem with the present ‘Machine Learning’ and ‘Big Data’ hype is that so many — falsely — think that they can get away with analyzing real-world phenomena without any (commitment to) theory. But — data never speaks for itself. Data by themselves are useless. Without a prior statistical set-up, there actually are […]
Yours truly, of course, feels truly honored to find himself on the list of the world’s 25 best econometrics blogs. 1. Bruno Rodrigues 7. Eran Raviv Blog Statistics and Econometrics 9. How the (Econometric) Sausage is Made 14. Lars P Syll Pålsson Syll received a Ph.D. in economic history in 1991 and a Ph.D. in economics in 1997, […]
Debating econometrics and its shortcomings yours truly often gets the response from econometricians that “ok, maybe econometrics isn’t perfect, but you have to admit that it is a great technique for empirical testing of economic hypotheses.” But is econometrics — really — such a great testing instrument? Econometrics is supposed to be able to test […]