HOME » wiiw Seminar in International Economics » Estimating bilateral relationships from ...
Harald Badinger, WU, WIFO
with Jesus Crespo Cuaresma, WU, IIASA, WIC, WIFO
In many econometric applications, inference about bilateral relationships across economic units is desired, but only aggregated data exist for the variable of interest. In particular, often bilateral explanatory variables are available but the dependent variable is collected at an aggregated level. Such settings are common in econometric applications related to international trade (where certain variables may be observed at the country level but inference on bilateral country relationships is of interest) and regional economics (where variables of interest may be observed at a lower level of geographical disaggregation). This paper proposes a method to overcome this shortcoming by directly estimating the parameters corresponding to the disaggregated model using aggregated data for the dependent variable. Our contribution is directly related to the literature on nonlinearly aggregated models, which have been mostly applied in econometrics to obtain inference in time series models for data at higher frequencies than that at which observations are available. We provide empirical examples based on international trade and spatial econometric models.
wiiw Seminar in International Economics
 |
Estimating bilateral relationships from aggregated data (by Harald Badinger and Jesus Crespo-Cuaresma) wiiw Seminar in International Economics 01 December 2011, 4 p.m., Venue: wiiw, 1060 Vienna, Rahlgasse 3 FREE DOWNLOAD |
Harald Badinger, WU, WIFO
with Jesus Crespo Cuaresma, WU, IIASA, WIC, WIFO
In many econometric applications, inference about bilateral relationships across economic units is desired, but only aggregated data exist for the variable of interest. In particular, often bilateral explanatory variables are available but the dependent variable is collected at an aggregated level. Such settings are common in econometric applications related to international trade (where certain variables may be observed at the country level but inference on bilateral country relationships is of interest) and regional economics (where variables of interest may be observed at a lower level of geographical disaggregation). This paper proposes a method to overcome this shortcoming by directly estimating the parameters corresponding to the disaggregated model using aggregated data for the dependent variable. Our contribution is directly related to the literature on nonlinearly aggregated models, which have been mostly applied in econometrics to obtain inference in time series models for data at higher frequencies than that at which observations are available. We provide empirical examples based on international trade and spatial econometric models.
Visitors who downloaded this publication/presentation also downloaded:
|
Reforming innovation systems in BY, KAZ and UA: Lost in Transition/Translation?” (by Hannes Leo) wiiw Seminar, 15 October 2012, 5 p.m., Venue: wiiw, Rahlgasse 3, 1060 Vienna DETAILS |
|
What went wrong in Slovenia and how to get out of the mess? (by Joze P. Damijan) wiiw Seminar Series 'EU in Crisis' 08 October 2012, 5 p.m., Venue: wiiw, 1060 Vienna, Rahlgasse 3 DETAILS |
|
The European Rim Countries - Challenges and Opportunities for EU Competitiveness (by Vasily Astrov, Peter Havlik, Mario Holzner, Gabor Hunya, Isilda Mara, Sandor Richter, Roman Stöllinger and Hermine Vidovic) wiiw Policy Note and Report No. 9, October 2012 49 pages including 3 Tables and 12 Figures DETAILS |
