9781330285886 - statistical aggregation analysis: characterizing macro functions, with cross section data (classic reprint) di stoker, thomas m. (3 risultati)
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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EUR 24,92
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 24,73
EUR 3,83 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 15 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Altre immagini- Brossura
- Print on Demand
Da: Forgotten Books, London, Regno UnitoForgotten Books
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Paperback. Condizione: New. Print on Demand. This book studies the use of cross-section data to describe macro functions, which are typically derived from microeconomic theories but estimated with time-series data. It introduces a new property called asymptotic sufficiency, which characterizes when cross-section data can be used… to estimate the first derivatives of macro functions. The author explores the relationship between asymptotic sufficiency and aggregation assumptions and shows that it embodies both kinds of aggregation assumptions known: linear aggregation and sufficient statistics. The book presents a methodology for estimating higher-order derivatives of macro functions from cross-section data when the distribution is a member of the exponential family, which extends to higher-order derivatives. Finally, it describes a general test of linear aggregation schemes that relies only on the existence of certain population moments. This book is a valuable resource for researchers and practitioners interested in using cross-section data to characterize macro functions. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item.
