دانلود مقاله ISI انگلیسی شماره 8604
عنوان فارسی مقاله

اندازه گیری در سیستم های اقتصادی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
8604 2005 10 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Measurement in economic systems
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Measurement, Volume 38, Issue 4, December 2005, Pages 275–284

کلمات کلیدی
اقتصاد - مدل اقتصادی - تغییرناپذیری - اقتصاد کلان - مشاهده منفعل - سیستم نرم افزاری
پیش نمایش مقاله
پیش نمایش مقاله اندازه گیری در سیستم های اقتصادی

چکیده انگلیسی

The metrology literature neglects a strong empirical measurement tradition in economics, which is different from the traditions as accounted for by the formalist representational theory of measurement. This empirical tradition comes closest to Mari’s characterization of measurement in which he describes measurement results as informationally adequate to given goals. In economics, one has to deal with soft systems, which induces problems of invariance and of self-awareness. It will be shown that in the empirical economic measurement tradition both problems have been on the agenda for a long while, and that the proposed solutions to these problems provide clues for the directions in which one could develop a measurement theory that takes account of soft systems.

مقدمه انگلیسی

In economics, there exist two different and separate traditions of measurement. Ignoring one of these traditions would mean understanding only half of how economics proceeds as a science. To emphasize the distinction between these two traditions, I would like to label them as the formalist and the empirical approach. The first tradition is the one most often referred to in the metrology literature when discussing economics and will therefore only briefly discussed. The second, in metrology more neglected, tradition deserves more attention because it shows how measurement formulae maintain empirical significance. The representation theory of measurement with its landmark publication [1] and its most recent publication [2] only provides a partial understanding of measurement practices in economics. Because most of its major contributors have been mathematicians and psychologists, it has undoubtedly been influential in the field where economics and psychology overlap, namely in the field where decision, choice and game theories flourish, and which is more or less adequately covered by the more general label microeconomics. Beside these often-referred applications, e.g. [3], I would also like to mention the axiomatic index theory, particularly as developed by Eichhorn [4], which is based on Pfanzagl [5]. However, the representational theory as a formalist theory of measurement does not provide an adequate understanding of a lot of other measurement practices to be found mainly in macroeconomics, econometrics, and its combination macroeconometrics. Measurements of important macroeconomic indicators like inflation, business cycle, unemployment and GDP are not adequately described by the representational theory of measurement. It will appear that we need to revise this theory by taking into account the more practical oriented GUM approach [6]. The account of measurement in economics presented here is closely related to Mari’s [7] final answer he gave to the problem of what characterizes measurement with respect to generic evaluation. Mari discusses three different characterizations of measurement: ontological (measurement is an evaluation able to determine those numbers that are essential properties of things), formal (measurement is an evaluation producing symbols that can be formally dealt with in a well definite way), and informational (measurement is an evaluation whose results are informationally adequate to given goals).

نتیجه گیری انگلیسی

Economists have developed all kinds of strategies to deal with problems typical for soft systems: the inability to control environmental conditions and to secure invariance. Instead of making demands on the measuring systems, they require the representation of these systems to fulfill certain empirical criteria. To achieve accuracy, they require models to account for the noisy environment. And to capture invariance, instead of trying to find invariant relationships they model from stable facts.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.