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Record W2605589489 · doi:10.18452/18698

The Economics of German Unification after Twenty-five Years: Lessons for Korea

2017· preprint· en· W2605589489 on OpenAlexaboutno aff
Michael C. Burda, Mark Weder

Bibliographic record

VenueEconstor (Econstor) · 2017
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Policies and Impacts
Canadian institutionsnot available
FundersDeutscher Akademischer Austauschdienst
KeywordsGermanUnificationEconomicsQuarter (Canadian coin)Per capitaInvestment (military)Per capita incomeGerman reunificationDemographic economicsGerman economyProductivityDevelopment economicsEconomyGeographyEconomic growthPolitical scienceDemographySociologyPoliticsPopulation

Abstract

fetched live from OpenAlex

This paper reviews the performance of the East German economy in the turbulent quarter-century following reunification and draws some conclusions for the reunification of North and South Korea. In this period, the gap in output per capita between East and West Germany declined at a speed not far from empirical estimates of the neoclassical growth model, yet systematic total factor productivity di¤eren- tials persist despite identical institutional frameworks and significant investment in the eastern regions. At the same time, regional disparities in income, well-being, and health are little different from those found within West Germany, and net migration has ceased. On this human metric, German unification has been an unqualified success. For Korea, an e¤ort of this dimension will be costly. A back-of-the- envelope calculation suggests that Korean uni?cation will cost roughly twice as much as its German counterpart.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0040.004
Open science0.0000.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.040
GPT teacher head0.274
Teacher spread0.233 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2017
Admission routes1
Has abstractyes

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