ISIDCE

Identification and Structural Inference of Dynamic Causal Effects: Theory and Applications

 Coordinatore THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD 

 Organization address address: University Offices, Wellington Square
city: OXFORD
postcode: OX1 2JD

contact info
Titolo: Dr.
Nome: Stephen
Cognome: Conway
Email: send email
Telefono: +44 1865 289800
Fax: +44 1865 289801

 Nazionalità Coordinatore United Kingdom [UK]
 Totale costo 100˙000 €
 EC contributo 100˙000 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-2011-CIG
 Funding Scheme MC-CIG
 Anno di inizio 2012
 Periodo (anno-mese-giorno) 2012-01-01   -   2015-12-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD

 Organization address address: University Offices, Wellington Square
city: OXFORD
postcode: OX1 2JD

contact info
Titolo: Dr.
Nome: Stephen
Cognome: Conway
Email: send email
Telefono: +44 1865 289800
Fax: +44 1865 289801

UK (OXFORD) coordinator 100˙000.00

Mappa


 Word cloud

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variation    econometric    weak    identification    policy    inference    causal    problem    data    instruments   

 Obiettivo del progetto (Objective)

'Identification of causal effects from non-experimental data is a difficult task because of the scarcity of plausible exogenous variation in the data. Typically, variation in the ‘treatment’ variable, such as a policy intervention, is not independent from relevant but unobserved characteristics of the underlying causal relationship. Causal inference often relies on the availability of valid instruments. A serious threat to the internal and external validity of econometric inference arises when the instruments are weak. This problem is well documented and is pervasive across most areas of economics. The proposed research will make a number of methodological and applied contributions to the current state of the art. First, it will provide improved methods of inference that are robust to the problem of weak instruments. Second, it will propose new approaches to the identification of dynamic causal effects that is particularly relevant for the analysis of macroeconomic policy. Third, it will apply state of the art econometric methods to the study of unemployment and business cycle fluctuations, with particular emphasis on European data.'

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