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Record W2597839512

Three Essays Assessing Global Value Chain Fragmentation on International Trade Using the World Input-Output Database

2016· article· en· W2597839512 on OpenAlexaboutno aff
Johanna Retana Attoh

Bibliographic record

VenueScholarWorks - WMU (Western Michigan University) · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsDatabaseFragmentation (computing)Value (mathematics)International tradeComputer scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

The growing fragmentation of supply chains across countries have changed the way nations engage in international trade. Conventionally, studies have used data on exports to measure trade flows; however, the use of this type of data imposes many assumptions that might misrepresent the real world. For instance, the assumption that the supply chain of a product is confined in only the domestic country does not take into consideration the increasing number of foreign inputs needed to produce a final good. In this dissertation, I use the World Input-Output Database (WIOD), since this dataset allows one to track and decompose the so-called global value chain (GVC) of a product.\nThe first essay uses the WIOD to analyze the degree of competitiveness and integration of the manufacturing sector of Canada, Mexico, and the U.S. (North American countries –NAC) from 1995 to 2007. Competitiveness is the capacity of a country to increase its share of GVC income and GVC jobs. Greater integration with a region is defined as experiencing a growing rate of GVC income and GVC jobs from that specific region to meet domestic final demand of manufactured goods. I answer three main questions: (1) did the NAC lose global competitiveness in the manufacturing sector? This is ambiguous, since the manufacturing sector of NAC experienced a decrease in the share of GVC jobs, from 7.11% in 1995 to 5.79% in 2007. However, the share of labor income associated with those jobs increased. (2) Were the NAC successful at integrating with the ROW? Yes, the share of GVC jobs that the ROW contributed to the NAC manufacturing sector increased from 18.14% in 1995 to 29.66% in 2007; while the share of GVC labor income increased from 7.84% in 1995 to 9.60% in 2007. (3) Were the NAC successful at integrating with the region itself? No, the NAC have become less integrated with the NAC region itself.\nThe second essay uses the WIOD to derive the exchange rate pass-through (ERPT) of the manufacturing sector of NAC for the years 1995 to 2009. ERPT is defined as the percentage change in export prices that is associated with a percentage change in the exchange rate. I am able to derive a measure that improves the estimates of the ERPT. In addition, I derive improved measures of marginal cost, product differentiation, and import share. Using a variance-weighted least-squares regression, I find that product differentiation and marginal cost have a positive and significant impact on ERPT, while the import share has a negative effect on the degree of ERPT.\nThe third essay uses the WIOD to derive a measure of vertical specialization (VS). VS measures the foreign value-added share in the output value of final manufacturing goods in a country. I use a dynamic ordinary least square (DOLS) model to examine the effect of vertical specialization, exchange rate, and exchange rate volatility on bilateral trade flows between the United States and Canada and Mexico for the years 1995 to 2007. DOLS controls for the endogeneity between the dependent variable and vertical specialization. I find that the vertical specialization has a positive effect on trade flows when non-linearities are taken into consideration.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.978

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 communication0.0000.002
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 head0.074
GPT teacher head0.256
Teacher spread0.182 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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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