Statistics & Econometrics
Causal effects are comparisons of what did happen with what would have happened if people had received different treatments. Randomized treatment assignment has reduced this problem to the minor technical problem of drawing an inference about a finite population of people on the basis of a probability sample from that population. Expressed differently, if we […]
Yours truly, of course, feels truly honoured to find himself on the list of the world’s 25 Best Econometrics Blogs and Websites. 2. Bruno Rodrigues 8. Eran Raviv Blog Statistics and Econometrics 13. 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. […]
Purchasing power parity doctrine is examined by sophisticated statistical and econometric techniques. The time series of aggregated price levels and the nominal exchange rates are treated as a random sample. Most papers of this type deal with the technical properties of the slightly different data sets. To take some examples (at random): “Two potential problems […]
Yours truly’s latest book has made it onto Amazon’s lists of best sellers in economics and econometrics. I am — of course — truly awed, honoured and delighted.
To understand the relationship between economic data and economic phenomena, it is helpful first to be clear about what we mean by each of these terms. Following Jim Woodward (1989), we can characterize “phenomena” as features of our experience that we take to be “relatively stable” and “which are potential objects of explanation and prediction […]
Suppose there is a series of Bernoulli trials, that each trial has the same probability p of success, and that the trials are independent—like the standard model of coin tossing, treating ‘heads’ as ‘success.’ Then the Law of Large Numbers guarantees that the rate of successes converges (in probability) to the probability of success. If […]
Fitting a model that has a parameter called ‘probability’ to data does not mean that the estimated value of that parameter estimates the probability of anything in the real world. Just as the map is not the territory, the model is not the phenomenon, and calling something ‘probability’ does not make it a probability, any […]
In some fields—physics, geophysics, climate science, sensitivity analysis, and uncertainty quantification in particular—there is a popular impression that probabilities can be estimated in a ‘neutral’ or ‘automatic’ way by doing Monte Carlo simulations: just let the computer reveal the distribution … Setting aside other issues in numerical modeling, Monte Carlo simulation is a way to […]