Tag Archives: scientific method

There is a big difference between predicting and forecasting. Scientific theory is about causal explanation and prediction through formulating testable hypothesis that challenge the theory rigorously based on experimental evidence. Forecasting is making educated guesses based on limited and variable information information. The former applies chiefly to ergodic systems and the latter to non-ergodic, or if the system is actually ergodic, not enough it known about it to construct a rigorous...

This is important but may be too wonkish for those who are not intimately familiar with econometrics. So let me try to simplify it and universalize it. The basic idea in logical reasoning is that an argument is sound if and only if the premises are true and the logical form is valid.  Then the conclusion follows as necessarily true. This is the basis of scientific reasoning. In modeling, a set of assumptions, both substantive and procedural, is stipulated, that is, assumed to be...

This is a big deal even though it won't be noticed by most people. However, precise measurement essential to science and measurement involves application of metrics defined by criteria. The units and their criteria are arbitrary. There was no such thing as a kilogram prior to the development and introduction of the metric system. Same with other measurement systems. The "trick" is to establish a constant criterion in a relative universe. That is as close to an absolute as human can...

Modern Monetary Theory (MMT) offers an understanding of sovereign (and non-sovereign) currencies that is applicable to a wide range of economic systems, including capitalist and socialist ones. Irrespective of the personal political preferences of its proponents, the theoretical framework in itself is neutral on the appropriate balance between public sector and private sector activity, or the relative merits of capitalism and socialism. In contrast to neoclassical theory, which starts from...

In a previous article, I argued that having unknown fixed parameters within many economic models does not create much in the way of uncertainty: just extend the range of historical data available, and we can pin down the parameter values. This article covers a related case: what if we allow parameters to vary with time? This possibility will make it impossible to make reliable forecasts with the model. However, such models have another defect: they can be fitted to practically any data set,...

On the basis of scientific method.Lars P. Syll’s BlogScientific realism and inference​ to the best explanationThe poverty of deductivismLars P. Syll | Professor, Malmo UniversitySee alsoStumbling and MumblingThe illusion of knowledge Chris Dillow | Investors Chronicle

The knives are out for the p-value. This statistical quantity is the Holy Grail for empirical researchers across the world -- if your study finds the right p-value, you can get published in a credible journal, and possibly get a good university tenure-track job and research funding. Now a growing chorus of voices wants to de-emphasize or even ban this magic number. But the crusade against p-values is likely to be a distraction from the real problems afflicting scientific inquiry.... The...

Summary: The end-in-view is doing good science and avoiding junk science, which is proliferating. Adjusting standards, etc. are only means to an end. There are no silver bullets or magic wands. Doing good science depends on good design, accurate measurement, and replication. Statistical Modeling, Causal Inference, and Social ScienceWhen considering proposals for redefining or abandoning statistical significance, remember that their effects on science will only be indirect! Andrew Gelman |...

If you are keeping up with this. Some finer points.From the epistemological point of view, criticism of statistical significance here is based on questioning a criterion that is stipulated, i.e., defined arbitrarily.Doing so gives formalization and modeling a greater importance than advancing understanding. That is unscientific.A pragmatic approach is more appropriate than a strictly formal one, especially as an institutional norm.Formal rigor is a necessary condition but not a sufficient...

As shown over and over again when significance tests are applied, people have a tendency to read ‘not disconfirmed’ as ‘probably confirmed.’ Standard scientific methodology tells us that when there is only say a 10 % probability that pure sampling error could account for the observed difference between the data and the null hypothesis, it would be more ‘reasonable’ to conclude that we have a case of disconfirmation. Especially if we perform many independent tests of our hypothesis and they...