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Record W2338364650

The Bayesian estimation of private investment in Finland

2009· book· en· W2338364650 on OpenAlex
Samuli Pietiläinen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJyväskylä University Digital Archive (University of Jyväskylä) · 2009
Typebook
Languageen
FieldEconomics, Econometrics and Finance
TopicInnovation Policy and R&D
Canadian institutionsnot available
FundersJyväskylän YliopistoUniversity of Toronto
KeywordsEstimationBayesian probabilityInvestment (military)EconometricsEconomicsStatisticsBusinessMathematicsPolitical scienceManagement
DOInot available

Abstract

fetched live from OpenAlex

Abstract This paper estimates an investment equation for private investment using Bayesian estimation techniques. In the paper we derive the optimal capital accumulation behavior in the model economy from the households’ optimization problem of utility. The equation is derived as in Smets and Wouters (2003). The model contains costly adjustment of investment and random shocks to adjustment cost function. The driving variable of investment is Tobin Q variable. The empirical proxy for Tobin Q in this paper is the ratio of OMX Helsinki Cap Index to the price index of the physical capital. The investment series is the seasonally adjusted private investment in quarterly national accounts. The AR(1) modelled investment shocks are found to be less persistent in Finland than in the euro area. The estimated median of persistence parameter for Finland is 0.485. Also the shocks to investment adjustment cost function are found to vary less in Finland as in the euro area. The estimated standard deviation of the shocks is 0.065. The adjustment cost parameter is roughly the same for both data sets. The results are robust to loosening the strict prior of discount factor, beta=0.99. The paper also provides discussion about adjustment cost parameter and we investigate the behaviour of the posterior chain of B with different prior distributions for the parameter. Tiivistelmä Tässä pro gradussa estimoidaan yhtälö yksityisille investoinneille bayesilaisella menetelmällä. Tässä työssä optimaalinen pääoman akkumulointi mallikansantaloudessa johdetaan kotitalouksien hyödyn optimointi-ongelmasta. Investointiyhtälö johdetaan kuten Smets’n ja Wouterin (2003) artikkelissa. Malli sisältää investointien sopeutuskustannukset ja satunnaisia shokkeja sopeutuskustannus-funktioon. Investointien selittävä muuttuja on Tobin Q -muuttuja. Empiirinen vastine teoreettiselle Tobin Q muuttujalle on OMX Helsinki Cap indexin arvo suhteutettuna fyysisen pääoman hintaindeksillä. Työssä käytetty investointisarja on kausitasoitettu yksityisten investointien sarja kansantalouden neljännestilinpidossa. Investointishokit ovat AR(1)-prosessi. Shokit osoittautuvat vähemmän pysyviksi Suomessa kuin euroalueella. Estimoitu AR(1)-kerroin investointishokeille on 0.485. Investointishokit myös vaihtelevat vähemmän Suomessa kuin euroalueella, sillä estimoitu shokkien keskihajonta on 0.065. Investointien sopeutuskustannus on likipitäen samankokoinen Suomessa ja euroalueella. Tulokset ovat robusteja kiinnitetyn diskonttausparametrin beta=0.99 löysäämiselle antamalla betalle eri priorijakaumia. Tässä työssä myös keskustellaan sopeutuskustannusparametrista ja tutkitaan sen posterioiriketjujen käyttäytymistä kun sille annetaan eri priorijakaumia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.496
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.164
Teacher spread0.152 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it