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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Aggregravity: Estimating Gravity Models from Aggregate Data

Badinger, Harald, Crespo Cuaresma, Jesus 09 1900 (has links) (PDF)
This paper considers alternative methods to estimate econometric models based on bilateral data when only aggregate information on the dependent variable is available. Such methods can be used to obtain an indication of the sign and magnitude of bilateral model parameters and, more importantly, to decompose aggregate into bilateral data, which can then be used as proxy variables in further empirical analysis. We perform a Monte Carlo study and carry out a simple real world application using intra-EU trade and capital flows, showing that the methods considered work reasonably well and are worthwhile being considered in the absence of bilateral data. (authors' abstract) / Series: Department of Economics Working Paper Series
2

Aggregravity: estimating gravity models from aggregate data

Badinger, Harald, Crespo Cuaresma, Jesus 20 January 2015 (has links) (PDF)
This paper considers alternative methods to estimate econometric models based on bilateral data when only aggregate information on the dependent variable is available. Such methods can be used to obtain an indication of the sign and magnitude of bilateral model parameters and, more importantly, to decompose aggregate into bilateral data, which can then be used as proxy variables in further empirical analysis. We perform a Monte Carlo study and carry out a simple real world application using intra-EU trade and capital flows, showing that the methods considered work reasonably well and are worthwhile being considered in the absence of bilateral data. (authors' abstract)

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