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Record W7056476984

Essays on Multinationals and International Spillovers.

2016· dissertation· en· W7056476984 on OpenAlexaboutno aff

Bibliographic record

VenueDeep Blue (University of Michigan) · 2016
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)NettingTubulopathyLimitingCircumstantial evidence
DOInot available

Abstract

fetched live from OpenAlex

The essays in this dissertation examine the causes and consequences of international spillovers and globalization, with a focus on the role of multinational firms. Chapter 1, joint with Christoph E. Boehm and Aaron Flaaen, highlights the important role played by U.S. owned multinationals in the decline of U.S. manufacturing, using a new microdata panel from 1993-2011 augmented with multinational identifiers and transactions level trade. These multinationals are responsible for both 41% of the manufacturing employment decline and the majority of input imports over this period. A structural framework establishes that the supply-chain fragmentation associated with the imports of intermediates has been substituting for domestic employment. Our estimates imply that approximately half the observed employment decline can be attributed to the foreign sourcing of inputs by multinationals. Chapter 2, also with Christoph E. Boehm and Aaron Flaaen, changes focus to a cause of international spillovers -- the inflexible supply chains of multinationals. Using novel firm-level microdata and leveraging a natural experiment – the 2011 Tohoku Earthquake --, this paper demonstrates that the substantial intermediate input linkages displayed by foreign multinational affiliates in the U.S. with their source country are a source of the international transmission of shocks. The scope for these linkages to generate cross-country spillovers depends on the elasticity of substitution with respect to other inputs. Structural estimates of this elasticity are close to zero, suggesting that global supply chains are sufficiently rigid to play an important role in the cross-country transmission of shocks. Chapter 3, joint with Andrei A. Levchenko, examines the role of non-technology shocks in the international transmission of business cycles. We propose a novel identification scheme for a non-technology business cycle shock, that we label “sentiment.” This is a shock orthogonal to conventionally identified surprise and news TFP shocks. We estimate the international transmission of three identified shocks -- surprise TFP, news of future TFP, and “sentiment” -- from the US to Canada, and find that the sentiment shock is more important than either of the technology shocks in generating business cycle comovement in the short run.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0980.000

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 head0.007
GPT teacher head0.230
Teacher spread0.223 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

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

Citations0
Published2016
Admission routes1
Has abstractyes

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