eprintid: 33839 rev_number: 22 eprint_status: archive userid: 1482 importid: 105 dir: disk0/00/03/38/39 datestamp: 2021-03-22 09:02:48 lastmod: 2021-09-10 11:32:17 status_changed: 2021-07-26 15:22:07 type: article metadata_visibility: show creators_name: Florens, Jean-Pierre creators_name: Simoni, Anna creators_idrefppn: 02883755X creators_affiliation: Toulouse School of Economics creators_halaffid: 1002422 title: Gaussian Processes and Bayesian Moment Estimation ispublished: pub subjects: subjects_ECO abstract: Given a set of moment restrictions (MRs) that overidentify a parameter θ, we investigate a semiparametric Bayesian approach for inference on θ that does not restrict the data distribution F apart from the MRs. As main contribution, we construct a degenerate Gaussian process prior that, conditionally on θ, restricts the F generated by this prior to satisfy the MRs with probability one. Our prior works even in the more involved case where the number of MRs is larger than the dimension of θ. We demonstrate that the corresponding posterior for θ is computationally convenient. Moreover, we show that there exists a link between our procedure, the generalized empirical likelihood with quadratic criterion and the limited information likelihood-based procedures. We provide a frequentist validation of our procedure by showing consistency and asymptotic normality of the posterior distribution of θ. The finite sample properties of our method are illustrated through Monte Carlo experiments and we provide an application to demand estimation in the airline market. date: 2021 date_type: published publisher: American Statistical Association id_number: 10.1080/07350015.2019.1668799 official_url: http://tse-fr.eu/pub/123945 faculty: tse divisions: tse language: en has_fulltext: TRUE doi: 10.1080/07350015.2019.1668799 view_date_year: 2021 full_text_status: public publication: Journal of Business and Economic Statistics volume: vol. 39 number: n° 2 pagerange: 482-492 refereed: TRUE issn: 0735-0015 oai_identifier: oai:tse-fr.eu:123945 harvester_local_overwrite: publish_to_hal harvester_local_overwrite: pending harvester_local_overwrite: creators_affiliation harvester_local_overwrite: faculty harvester_local_overwrite: id_number harvester_local_overwrite: note harvester_local_overwrite: creators_idrefppn harvester_local_overwrite: creators_halaffid harvester_local_overwrite: number harvester_local_overwrite: volume harvester_local_overwrite: issn harvester_local_overwrite: ispublished harvester_local_overwrite: abstract harvester_local_overwrite: pagerange harvester_local_overwrite: publisher oai_lastmod: 2021-07-30T07:07:32Z oai_set: tse site: ut1 publish_to_hal: FALSE citation: Florens, Jean-Pierre and Simoni, Anna (2021) Gaussian Processes and Bayesian Moment Estimation. Journal of Business and Economic Statistics, vol. 39 (n° 2). pp. 482-492. document_url: https://publications.ut-capitole.fr/id/eprint/33839/1/07350015.2019.1668799