?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Estimation+under+Ambiguity&rft.creator=Giacomini%2C+R&rft.creator=Kitagawa%2C+T&rft.creator=Uhlig%2C+H&rft.description=To+perform+Bayesian+analysis+of+a+partially+identified+structural+model%2C+two+distinct+approaches+exist%3A+standard+Bayesian+inference%2C+which+assumes+a+single+prior+for+the+structural+parameters%2C+including+the+non-identified+ones%3B+and+multiple-prior+Bayesian+inference%2C+which+assumes+full+ambiguity+for+the+non-identified+parameters.+The+prior+inputs+considered+by+these+two+extreme+approaches+can+often+be+a+poor+representation+of+the+researcher%E2%80%99s+prior+knowledge+in+practice.+This+paper+fills+the+large+gap+between+the+two+approaches+by+proposing+a+multiple-prior+Bayesian+analysis+that+can+simultaneously+incorporate+a+probabilistic+belief+for+the+non-identified+parameters+and+a+concern+about+misspecification+of+this+belief.+Our+proposal+introduces+a+benchmark+prior+representing+the+researcher%E2%80%99s+partially+credible+probabilistic+belief+for+non-identified+parameters%2C+and+a+set+of+priors+formed+in+its+Kullback-Leibler+(KL)+neighborhood%2C+whose+radius+controls+the+%E2%80%9Cdegree+of+ambiguity.%E2%80%9D+We+obtain+point+estimators+and+optimal+decisions+involving+non-identified+parameters+by+solving+a+conditional+gamma-minimax+problem%2C+which+we+show+is+analytically+tractable+and+easy+to+solve+numerically.+We+derive+the+remarkably+simple+analytical+properties+of+the+proposed+procedure+in+the+limiting+situations+where+the+radius+of+the+KL+neighborhood+and%2For+the+sample+size+are+large.+Our+procedure+can+also+be+used+to+perform+global+sensitivity+analysis.&rft.publisher=Institute+for+Fiscal+Studies&rft.date=2019-05-28&rft.type=Working+%2F+discussion+paper&rft.language=eng&rft.source=++++(Cemmap+Working+Paper++24%2F19).+Institute+for+Fiscal+Studies%3A+London%2C+UK.+(2019)+++++&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10087226%2F