Abhishek K. Umrawal, Joshua C. C. Chan
arXiv 23 Oct 2021 · Econometrics
arXiv:2110.12149 · PDF · DOI · OpenAlex · Extracted main text
We propose a new quadratic programming-based method of approximating a nonstandard density using a multivariate Gaussian density. Such nonstandard densities usually arise while developing posterior samplers for unobserved components models involving inequality constraints on the parameters. For instance, Chan et al. (2016) provided a new model of trend inflation with linear inequality constraints on the stochastic trend. We implemented the proposed quadratic programming-based method for this model and compared it to the existing approximation. We observed that the proposed method works as well as the existing approximation in terms of the final trend estimates while achieving gains in terms of sample efficiency.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Chan, J. C., Koop, G., and Potter, S. M (2016) A bounded model of time variation in trend inflation, nairu and the phillips curve self | 0.969 | 11 | 5 | 91% |
| 2 | Chan, J. C. and Strachan, R. W (2012) Estimation in non-linear non-gaussian state space models with precision-based methods self | 0.644 | 2 | 2 | 100% |
| 3 | Chan, J. C. and Jeliazkov, I (2009) Efficient simulation and integrated likelihood estimation in state space models self | 0.405 | 1 | 1 | 100% |
| 4 | Kozlov, M. K., Tarasov, S. P., and Khachiyan, L. G (1980) The polynomial solvability of convex quadratic programming | 0.405 | 1 | 1 | 100% |
| 5 | Sahni, S (1974) Computationally related problems | 0.405 | 1 | 1 | 100% |
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