Sunday , November 24 2024
Home / Lars P. Syll (page 99)
Lars Pålsson Syll
Professor at Malmö University. Primary research interest - the philosophy, history and methodology of economics.

Lars P. Syll

Hur kan vi återskapa förtroendet för nationalekonomi som vetenskap?

Hur kan vi återskapa förtroendet för nationalekonomi som vetenskap? Nationalekonomin som vetenskap har världen över förlorat otroligt mycket i prestige och status under senare år. Inte minst på grund av dess oförmåga att analysera och förklara ekonomiska och finansiella kriser och på grund av dess avsaknad av konstruktiva och hållbara förslag på att ta oss ur dessa kriser. Hur återskapar vi förtroendet för nationalekonomin? Fem förändringar är helt...

Read More »

The dangers of randomization idolatry

The dangers of randomization idolatry How, then, can social scientists best make inferences about causal effects? One option is true experimentation … Random assignment ensures that any differences in outcomes between the groups are due either to chance error or to the causal effect … If the experiment were to be repeated over and over, the groups would not differ, on average, in the values of potential confounders. Thus, the average of the average...

Read More »

Economics as ideology

Although I never believed it when I was young and held scholars in great respect, it does seem to be the case that ideology plays a large role in economics. How else to explain Chicago’s acceptance of not only general equilibrium but a particularly simplified version of it as ‘true’ or as a good enough approximation to the truth? Or how to explain the belief that the only correct models are linear and that the von Neuman prices are those to which actual prices converge pretty...

Read More »

The shocking truth about econometric ‘precision’ and ‘rigour’

Leverage is a measure of the degree to which a single observation on the right-hand-side variable takes on extreme values and is influential in estimating the slope of the regression line. A concentration of leverage in even a few observations can make coefficients and standard errors extremely volatile and even bias robust standard errors towards zero, leading to higher rejection rates. To illustrate this problem, Young (2019) went through a simple exercise. He collected...

Read More »