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PhD dissertation: Transformer Network for Macroeconometric Analysis. Pass with distinction.
Non-technical summary: I develop a new methodology and apply it to two real-world problems.
Defence on YouTube . Lectio summarizing the dissertation in the first 15 minutes.
Job Market Paper
Oliver Snellman (2024): Non-Linear Dynamic Factor Analysis With a Transformer Network. [arXiv], [SSRN].
Abstract: The paper develops a Transformer architecture for estimating dynamic factors from multivariate time series data under flexible identification assumptions. Performance on small datasets is improved substantially by using a conventional factor model as prior information via a regularization term in the training objective. The results are interpreted with Attention matrices that quantify the relative importance of variables and their lags for the factor estimate. Time variation in Attention patterns can help detect regime switches and evaluate narratives. Monte Carlo experiments suggest that the Transformer is more accurate than the linear factor model, when the data deviate from linear-Gaussian assumptions. An empirical application uses the Transformer to construct a coincident index of U.S. real economic activity.
Working papers
Oliver Snellman (2024): Using a Transformer Network to Measure Fragility in the Financial System. Available at SSRN.
Abstract: The paper proposes a new method for measuring fragility in the financial system. The measure is constructed from macro-financial panel data, with a custom Decoder-only Transformer. The historic time periods preceding systemic banking crises are considered as training examples of excess fragility. The fragility measure helps with timing macroprudential counter-cyclical policies. JEL Classification: C63, E58, E61, G28.
Oliver Snellman (2023): Analyzing Epidemic Contact Tracing with Queuing Theory. Available at SSRN.
Abstract: To prevent epidemic escalation early on, contact tracing uses costly resources to identify and quarantine the unknown contagious people. Both the prevailing epidemic situation and the effectiveness of tracing are uncertain. I derive a resource allocation rule, where this uncertainty is quantified using Erlang's C queuing model, which is incorporated into a macro-epidemiological model featuring cautious heterogeneous agents. Using this rule to operate contact tracing results in containing the epidemic in most cases, reducing labor costs, and supporting a livelier economy, compared to the alternative where uncertainty is not accounted for in resource allocation. Keywords: Contact tracing, Queuing theory, Erlang C, Resource allocation. JEL Classification: C18, H12, I18, Q54.
Oliver Snellman (2019): Evaluation of DSGE model KOOMA with a sign restricted Structural VAR model, Publications of the Ministry of Finance 2019:62.
Abstract: The aim of this study is to evaluate the calibration of DSGE model KOOMA of the Ministry of Finance with a SVAR model, which is identified with sign restrictions. I compare impulse response functions from the SVAR model, which are found statistically significant and robust to changes in model specifications, to the equivalent impulse response functions from KOOMA. The findings suggest that KOOMA generally produce impulse responses with same signs as the SVAR model, but there are some differences in the magnitudes and persistence of the responses.
Policy work
Oliver Snellman (2020): Confidence shock. An analysis about the impact of declining consumer confidence on the economic downturn, in the emergence of the COVID-19. Ministry of Finance memorandum. Cited in the Economic survey 2020:56, page 41.
Economic Survey, Winter (2019): Section 1.2, foreign trade. Publications of the Ministry of Finance 2019:70.
Media (in Finnish)
Haastattelu Yrjö Jahnssonin säätiön vuosikertomuksessa. YJS-säätiö on rahoittanut yhteensä neljä vuotta jatko-opintojani.
Tulevaisuuden toivot: 7 nuorta kykyä, joista kuulemme vielä. Kotiliesi julkaisi 100-vuotis juhlanumerossaan artikkelin, jossa eri aloilla jo meritoituneet suosittelevat lupaavia tulokkaita. Minua suositteli akatemian/yhteiskuntatieteen tulokkaaksi aivotutkija Katri Saarikivi.
Ilta-Sanomien artikkeli Suomen vaaleista USA:ssa asuvien näkökulmasta. Tunnelmia presidentinvaalien toisen kierroksen ennakkoäänestyksessä New Yorkissa.
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