The Methodology of Empirical Macroeconomics by Kevin D. Hoover
By Kevin D. Hoover
Financial method mostly makes a speciality of microeconomic thought. The technique of Empirical Macroeconomics breaks new flooring via focusing in its place at the real difficulties that come up for macroeconomists attempting to relate thought to facts. It demonstrates that with cautious awareness to genuine macroeconomic perform, financial method and the philosophy of technology support to unravel difficulties confronted via operating macroeconomists. a few matters addressed are: the connection among theoretical versions and empirical observations; microfoundations for macroeconomics; the scope and nature of financial legislation, the position of idealizations, methodological individualism, and the matter of causality.
"I think that this booklet accomplishes its major mission--relating the philosophy of technological know-how to useful macroeconomic issues." -
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The fitted curves have different slopes, although they are qualitatively similar. 51 The Methodology of Empirical Macroeconomics advertisements conditional on forecasts of the unemployment rate. 20 Observations invite explanation. Even if a fact, such as the relationship of unemployment to vacancies, were to vanish, its having been so now stands in need of explanation. The robustness of econometric facts is an argument for the existence of nomological machines, but the tools for discovering those facts do not presuppose (fully articulated) knowledge of the construction of those machines.
On this, I am of two minds. Pissarides does not really present his model in that light. But among new classical business-cycle modelers, real-business-cycle modelers present models that are no less unrealistic as adequate explanations of macroeconomic fluctuations. 13 Our task as I see it . . somewhat more bluntly and operationally . . 14 Kydland and Prescott and the other real-business-cycle modelers have taken Lucas’s program to heart, but in full realization that their models are idealized, or in their more usual turn of phrase, stylized.
The practical reason for using idealized models is that we do not know all of the secondary factors that influence a phenomenon. There is an analogue in experimental sciences. Often an experiment has to be shielded from outside influences: protected from radiation, light, magnetism, motion, and so forth. Yet, no matter how an experiment is shielded – that is, no matter how many secondary factors are set aside – there may always be another outside influence against which inadequate precaution was taken.