ISBN:
9789400963344
Language:
English
Pages:
Online-Ressource (340p)
,
digital
Edition:
Springer eBook Collection. Humanities, Social Sciences and Law
Series Statement:
Theory and Decision Library, An International Series in the Philosophy and Methodology of the Social and Behavioral Sciences 41
Series Statement:
Theory and Decision Library 41
Parallel Title:
Erscheint auch als
Parallel Title:
Erscheint auch als
Parallel Title:
Erscheint auch als
Keywords:
Social sciences
;
Social sciences Methodology
;
Sociology—Methodology.
Abstract:
I. Introduction -- I. Introduction -- II. On Theory -- 1. Aggregation without side conditions -- 2. Aggregation of production functions under optimum conditions -- 3. Aggregation and individual preferences -- 4. Aggregation and the distribution of individual characteristics -- 5. Linear aggregation and estimation -- 6. Aggregation over arguments of a function -- III. Some Applications -- 7. Aggregation and consumer behaviour -- 8. Collective choice and macro-economic policy -- IV. Epilogue: Optimal aggregation -- IV. Epilogue: Optimal aggregation -- References -- Author Index.
Abstract:
Our interest in problems of aggregation originates from about seven years ago when we became involved in research in the field of applied microeconomics. To our astonishment a vast majority of researchers in this area took it for granted that their, mostly thoroughly derived, micro models could meaningfully be confronted with per capita data. Nany of them did not even realize - at least they gave no utterance to it - that applying macro data in micro models raises considerable problems. Those who did mention the difficulty, almost always belittled its importance. Fortunately, there are noteworthy exceptions. Thinking about aggregation raises at least two questions: "Why or why not aggregate?" and "How to aggregate and, in particular, to what degree?" General answers to these questions can only be given in uninformative wording (as many assertions in economics): one aggregates for the sake of tractability, because of the lack of (individual) data, to avoid or to reduce multicollineartiy, to save degrees of freedom; one abstains from aggregation to avoid loss of information, to avoid aggregation biases and one aggregates such and to such degree as to bypass or reduce the drawbacks mentioned above.
DOI:
10.1007/978-94-009-6334-4
URL:
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