Tag Archives: Statistics & Econometrics

‘Modern’ economics — blah blah blah A key part of the solution to the identification problem that Lucas and Sargent (1979) seemed to offer was that mathematical deduction could pin down some parameters in a simultaneous system. But solving the identification problem means feeding facts with truth values that can be assessed, yet math cannot establish the truth value of a fact. Never has. Never will. In practice, what math does is let macro-economists locate...

The most beautiful identity in mathematics  [embedded content] div{float:left;margin-right:10px;} div.wpmrec2x div.u > div:nth-child(3n){margin-right:0px;} ]]> Advertisements

On the fundamental difference between ergodic and non-ergodic processes in economics Yours truly has tried to explain the fundamental difference between time averages and ensemble averages repeatedly on this blog. Still people obviously seem to have problems grasping it. Maybe this video will help … [embedded content] div{float:left;margin-right:10px;} div.wpmrec2x div.u > div:nth-child(3n){margin-right:0px;} ]]> Advertisements...

In a blog post the other day, Noah Smith returned again to the discussion about the ’empirical revolution’ in economics and how to — if it really does exist — evaluate it. Counter those who think quasi-experiments and RCTs are the true solutions to finding causal parameters, Noah argues that without structural models empirical results are only locally valid. And you don’t really know how local “local” is. If you find that raising the minimum wage from $10 to $12 doesn’t reduce...

The statistical crisis in social science  [embedded content] Advertisements

Trig trick (student stuff)  [embedded content] Advertisements

Don’t trust summary statistics alone When teaching statistics and econometrics yours truly always stress the importance of data visualization. The thirteen datasets shown above is a great illustration of why one should always plot data. They all have the same summary statistics — mean, standard deviation, correlation coefficient — but some are dinosaurs and others are stars … Conclusion: never trust summary statistics alone! Advertisements...

The spectacular failure of DSGE models In most aspects of their lives humans must plan forwards. They take decisions today that affect their future in complex interactions with the decisions of others. When taking such decisions, the available information is only ever a subset of the universe of past and present information, as no individual or group of individuals can be aware of all the relevant information. Hence, views or expectations about the future,...

Cholesky decomposition (student stuff)  [embedded content] Advertisements

The problem with unjustified assumptions An ongoing concern is that excessive focus on formal modeling and statistics can lead to neglect of practical issues and to overconfidence in formal results … Analysis interpretation depends on contextual judgments about how reality is to be mapped onto the model, and how the formal analysis results are to be mapped back into reality. But overconfidence in formal outputs is only to be expected when much labor has...