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Infinitely Stochastic Micro Forecasting

Matúš Maciak, Ostap Okhrin, Michal Pešta

arXiv 28 Aug 2019 · Econometrics

arXiv:1908.10636 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Forecasting costs is now a front burner in empirical economics. We propose an unconventional tool for stochastic prediction of future expenses based on the individual (micro) developments of recorded events. Consider a firm, enterprise, institution, or state, which possesses knowledge about particular historical events. For each event, there is a series of several related subevents: payments or losses spread over time, which all leads to an infinitely stochastic process at the end. Nevertheless, the issue is that some already occurred events do not have to be necessarily reported. The aim lies in forecasting future subevent flows coming from already reported, occurred but not reported, and yet not occurred events. Our methodology is illustrated on quantitative risk assessment, however, it can be applied to other areas such as startups, epidemics, war damages, advertising and commercials, digital payments, or drug prescription as manifested in the paper. As a theoretical contribution, inference for infinitely stochastic processes is developed. In particular, a non-homogeneous Poisson process with non-homogeneous Poisson processes as marks is used, which includes for instance the Cox process as a special case.

Citation extraction

78
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83
in-text mentions
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distinct cited
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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Hjort, N. L. and Pollard, D (2011) Asymptotics for minimisers of convex processes0.6444250%
2Schrodt, P (2014) Seven deadly sins of contemporary quantitative political analysis0.51121100%
3Aigner, D., Knox-Lovell, C., and Schmidt, P (1977) Formulation and estimation of stochastic frontier production function models0.40511100%
4Antonio, K. and Plat, R (2014) Micro-level stochastic loss reserving for general insurance0.40511100%
5Arjas, E (1989) The claims reserving problem in non-life insurance: Some structural ideas0.40511100%
6Arnold, C (2019) Death, statistics and a disaster zone: The struggle to count the dead after Hurricane Maria0.40511100%
7Azar, E. E (1980) The conflict and peace databank (COPDAB) project0.40511100%
8Benito, S. and López-Martín, C (2018) A review of the state of the art in quantifying operational risk0.40511100%
9Badescu, A. L., Lin, X. S., and Tang, D (2016) A marked Cox model for the number of IBNR claims: Theory0.40511100%
10Bosma, N., Van Praag, M., Thurik, R., and De Witt, G (2004) The value of human and social capital investments for the business performance of startups0.40511100%

Showing the top 10 of 78 scored citations.