Quantitative Economics
Journal Of The Econometric Society
Edited by: Stéphane Bonhomme • Print ISSN: 1759-7323 • Online ISSN: 1759-7331
Edited by: Stéphane Bonhomme • Print ISSN: 1759-7323 • Online ISSN: 1759-7331
In this supplemental section we prove that, for an autoregressive process, the gradient of the quasi-log-likelihood does not equal zero when evaluated at the popluation parameter values.
This supplement contains the Lemmas and their proofs that are used in the proofs of Theorems 3.1 and 3.2 of the paper in Sections S1 and S2; the proof of Corollary 3.1 in Section S2; a missing data example and Monte Carlo simulations in Section S3; the verification of Assumptions A.6 and A.7 in two leading examples in Section S4; a discussion of the intuition behind Theorem 3.2 in Section S5; and details of the computations carried out in Table 1 in Section S6.
This file contains proofs omitted from the paper.
This file contains the proof of Theorem 4 which is omitted in the main text.
This zip file contains the replication files for the manuscript.
This zip file contains the replication files for the manuscript.
This PDF file contains the proofs of Lemmas found within the manuscript.
This online appendix contains the proofs of all the lemmas that do not appear in the printed appendix to the paper. It also contains the statements of all these lemmas and details of the intervening arguments in the proofs of the propositions. It also contains a proof of existence for a more general model that implies Proposition 3 (ii).
The purpose of this supplement is to establish the strong connection between the continuous-time model of Daley and Green (2011) and a discrete-time analog.
This zip file contains the replication files for the manuscript.
This appendix provides a more detailed analysis of a parameterized version of the consumer model presented in Section 4.1. It also illustrates some of the theoretical properties of the model and shows that the model can incorporate features observed in the data. Third, it shows the calibrated parameters of the model to match several key moments in data and further explores the features of the model. Finally, it reports how well this model can be approximated by the linearized version in Section 4.3 of the paper.
This appendix describes the details associated with the estimation of the model described Sections 4 and 5 of the paper.
This zip file contains codes used to generate the numerical results.
This appendix contains analytical and numerical results on various models. It also presents a method to numerically compute information bounds and check the non-surjectivity condition. Lastly, it outlines a specification test of parametric random-effects models.