Pratha Khandelwal, Philip Nadler, Rossella Arcucci, William Knottenbelt, Yi-Ke Guo
arXiv 27 Oct 2021 · Econometrics
arXiv:2110.14346 · PDF · DOI · OpenAlex · Extracted main text
The nature of available economic data has changed fundamentally in the last decade due to the economy's digitisation. With the prevalence of often black box data-driven machine learning methods, there is a necessity to develop interpretable machine learning methods that can conduct econometric inference, helping policymakers leverage the new nature of economic data. We therefore present a novel Variational Bayesian Inference approach to incorporate a time-varying parameter auto-regressive model which is scalable for big data. Our model is applied to a large blockchain dataset containing prices, transactions of individual actors, analyzing transactional flows and price movements on a very granular level. The model is extendable to any dataset which can be modelled as a dynamical system. We further improve the simple state-space modelling by introducing non-linearities in the forward model with the help of machine learning architectures.
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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 | Philip Nadler, Rossella Arcucci, and Yi-Ke Guo (2019) Data assimilation for parameter estimation in economic modelling self | 0.737 | 3 | 2 | 100% |
| 2 | Philip Nadler, Rossella Arcucci, and Yi-Ke Guo A Scalable Approach to Econometric Inference self | 0.644 | 2 | 2 | 100% |
| 3 | Guokun Lai, Wei-Cheng Chang, Yiming Yang, and Hanxiao Liu (2018) Modeling long-and short-term temporal patterns with deep neural networks | 0.585 | 3 | 1 | 100% |
| 4 | Rainer Bohme, Nicolas Christin, Benjamin Edelman, and Tyler Moore (2015) Bitcoin: Economics, technology, and governance | 0.405 | 1 | 1 | 100% |
| 5 | Mark Asch, Marc Bocquet, and Maëlle Nodet Data Assimilation: Methods, Algorithms, and Applications | 0.405 | 1 | 1 | 100% |
| 6 | Ross Bannister Variational data assimilation background and methods | 0.405 | 1 | 1 | 100% |
| 7 | Christian Hotz-Behofsits, Florian Huber, and Thomas Otto Zörner (2018) Predicting crypto-currencies using sparse non-gaussian state space models | 0.405 | 1 | 1 | 100% |
| 8 | Author Blockgeeks and Blockgeeks (2020) What is the 0x project? the most comprehensive guide ever written, Apr 2020 | 0.405 | 1 | 1 | 100% |
| 9 | Jake Frankenfield (2020) Bitcoin exchange definition, Aug 2020 | 0.405 | 1 | 1 | 100% |
| 10 | Andrew G Haldane (2018) Will big data keep its promise | 0.405 | 1 | 1 | 100% |
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