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Disaggregation in Econometric Modelling (Routledge Revivals) [Paperback]

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  • Category: Books (Social Science)
  • ISBN-10:  0415616638
  • ISBN-10:  0415616638
  • ISBN-13:  9780415616638
  • ISBN-13:  9780415616638
  • Publisher:  Routledge
  • Publisher:  Routledge
  • Pages:  366
  • Pages:  366
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Dec-2012
  • Pub Date:  01-Dec-2012
  • SKU:  0415616638-11-MPOD
  • SKU:  0415616638-11-MPOD
  • Item ID: 100759942
  • Seller: ShopSpell
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  • Delivery by: Jul 01 to Jul 03
  • Notes: Brand New Book. Order Now.
In this book, first published in 1990, leading theorists and applied economists address themselves to the key questions of aggregation. The issues are covered both theoretically and in wide-ranging applications. Of particular intrest is the optimal aggregation of trade data, the need for micro-modelling when imoprtant non-linearities are present (for example, tax exhaustion in modelling company behaviour) and the use of a micro-model to stimulate labour supply behaviour in a macro-model of the Netherlands.1. Disaggregation in econometric modelling: an introduction  Part I  2. Aggregation of time-series variables: a survey  3. On the dynamic specification of aggregated models  4. Aggregation versusdisaggregation in forecasting construction activity  5. Aggregation problems in a model of wage formation and employment demand  6. Aggregation bias in labour demand equations for the UK economy  7. Optimal aggregation of linear net export systems  8. The choice of aggregate production functions in Mexican industries  9. Disaggregation of hte demand for hospital care  10. Aggregation in discrete choice models: an illustration of non-linear aggregation  Part II  11. Macroeconomic and micoreconomic modelling: some issues  12. MICROFKA: integrating a micro labour-supply model and a macro model of the Dutch economy  13. Macro to micro linkage: some experiments with the UK commodity flow accounts  14. What determines the bank borrowing and liquid lending of UK companies? Explanations based on aggregated and disaggregated data
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