Tag Archives: Statistics & Econometrics

If contributions made by statisticians to the understanding of causation are to be taken over with advantage in any specific field of inquiry, then what is crucial is that the right relationship should exist between statistical and subject-matter concerns … Where the ultimate aim of research is not prediction per se but rather causal explanation, an idea of causation that is expressed in terms of predictive power — as, for example, ‘Granger’ causation — is likely to be found...

Economic growth and the size of the ‘private sector’ Economic growth has since long interested economists. Not least, the question of which factors are behind high growth rates has been in focus. The factors usually pointed at are mainly economic, social and political variables. In an interesting study from the University of  Helsinki, Tatu Westling has expanded the potential causal variables to also include biological and sexual variables. In  the report...

Milton Friedman’s critique of econometrics Tinbergen’s results cannot be judged by ordinary tests of statistical significance. The reason is that the variables with which he winds up, the particular series measuring these variables, the leads and lags, and various other aspects of the equations besides the particular values of the parameters (which alone can be tested by the usual statistical technique) have been selected after an extensive process of trial...

Econometrics textbooks — vague and confused causal analysis Econometric textbooks fall on all sides of this debate. Some explicitly ascribe causal meaning to the structural equation while others insist that it is nothing more than a compact representation of the joint probability distribution. Many fall somewhere in the middle – attempting to provide the econometric model with sufficient power to answer economic problems but hesitant to anger traditional...

Proper use of regression analysis Level I regression analysis does not require any assumptions about how the data were generated. If one wants more from the data analysis, assumptions are required. For a Level II regression analysis, the added feature is statistical inference: estimation, hypothesis tests and confidence intervals. When the data are produced by probability sampling from a well-defined population, estimation, hypothesis tests and confidence...

There have been over four decades of econometric research on business cycles … The formalization has undeniably improved the scientific strength of business cycle measures … But the significance of the formalization becomes more difficult to identify when it is assessed from the applied perspective, especially when the success rate in ex-ante forecasts of recessions is used as a key criterion. The fact that the onset of the 2008 financial-crisis-triggered recession was...

Keynes’ critique of econometrics — the nodal point In my judgment, the practical usefulness of those modes of inference, here termed Universal and Statistical Induction, on the validity of which the boasted knowledge of modern science depends, can only exist—and I do not now pause to inquire again whether such an argument must be circular—if the universe of phenomena does in fact present those peculiar characteristics of atomism and limited variety which...

What inferential leverage do statistical models provide? Experimental (and non-experimental) data are often analyzed using a regression model of the form Yi =a+bZi +Wiβ+εi, where Wi is a vector of control variables for subject i, while a, b, and β are parameters (if Wi is 1×p, then β is p×1). The effect of treatment is measured by b. The disturbances εi would be assumed independent across subjects, with expectation 0 and constant variance. The Zi and Wi...

The trouble with econometrics In the process of translating a theory into implications about data, so many auxiliary assumptions are made that all contact with reality is lost. Any conflict can be resolved by adjusting the auxiliary assumptions. For example, suppose we want to learn if a production process satisfy diminishing, constant, or increasing returns to scale. The issue is of substantial significance from the point of view of theory. In carrying out...

How to save us from inferential mistakes when doing econometrics This is where statistical analysis enters. Validation comes in many different forms, of course, and much good theory testing is qualitative in character. Yet when applicable, statistical theory is our most powerful inductive tool, and in the end, successful theories have to survive quantitative evaluation if they are to be taken seriously. Moreover, statistical analysis is not confined to...