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Autor(en): 
  • Thomas J. Sargent
  • Lars Peter Hansen
  • Recursive Models of Dynamic Linear Economies 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Dezember 2013  
    Genre:  Wirtschaft / Recht 
     
    BUSINESS & ECONOMICS
    ISBN:  9780691042770 
    EAN-Code: 
    9780691042770 
    Verlag:  Princeton University Press 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  The Gorman Lectures in Economics  
    Dimensionen:  H 260 mm / B 183 mm / D 27 mm 
    Gewicht:  981 gr 
    Seiten:  420 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    A guide to the economic modeling of household preferences, from two leaders in the field A common set of mathematical tools underlies dynamic optimization, dynamic estimation, and filtering. In Recursive Models of Dynamic Linear Economies, Lars Peter Hansen and Thomas Sargent use these tools to create a class of econometrically tractable models of prices and quantities. They present examples from microeconomics, macroeconomics, and asset pricing. The models are cast in terms of a representative consumer. While Hansen and Sargent demonstrate the analytical benefits acquired when an analysis with a representative consumer is possible, they also characterize the restrictiveness of assumptions under which a representative household justifies a purely aggregative analysis. Hansen and Sargent unite economic theory with a workable econometrics while going beyond and beneath demand and supply curves for dynamic economies. They construct and apply competitive equilibria for a class of linear-quadratic-Gaussian dynamic economies with complete markets. Their book, based on the 2012 Gorman lectures, stresses heterogeneity, aggregation, and how a common structure unites what superficially appear to be diverse applications. An appendix describes MATLAB programs that apply to the book's calculations.

      



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