MétaCan
Menu
Back to cohort
Record W7132951949

Essays in Spatial and International Economics

2024· dissertation· W7132951949 on OpenAlexaffabout
Guangbin Hong

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEarningsSortingWelfareInequalityProfit (economics)General equilibrium theorySpatial mismatch
DOInot available

Abstract

fetched live from OpenAlex

This thesis studies a range of issues in spatial and international economics. The first two chapters focus on spatial earnings inequality across cities; the last chapter studies international profit shifting. In the first chapter, I examine how the two-sided sorting of workers and firms affects spatial earnings inequality, efficiency of the allocation of workers and firms across cities, and the welfare consequences of place-based policies. I build a general equilibrium model in which heterogeneous workers and firms sort across cities and match within cities. I structurally estimate the model using Canadian matched employer-employee data and decompose the urban earnings premium, finding that worker and firm sorting account for 67% and 27% of this premium, respectively. The decentralized equilibrium is inefficient as low-productivity firms overvalue locating in high-skilled cities. The optimal spatial policy would incentivize high-skilled workers and high-productivity firms to co-locate to a greater extent while redistributing income towards low-earning cities, leading to a 6% increase in social welfare. Model counterfactuals underscore the importance of two-sided sorting when evaluating distributional and aggregate outcomes of place-based policies. It has been documented that larger cities foster faster earnings growth, which is an important driver for cross-sectional spatial earnings inequality. In the second chapter, I empirically investigate the sources of the urban earnings growth premium. I find that the between-firm and within-firm growth components each explain 66% and 34% of the greater returns to big city experience, respectively. Workers do not move between jobs more frequently but enjoy a bigger earnings increase on average per movement in larger cities. Faster within-firm learning in larger cities is mostly explained by better learning environments at the firm level. The empirical results of this chapter highlight the important role of firm heterogeneity across cities in explaining the dynamic gains from working in bigger cities. In the jointly authored third chapter, we study the macroeconomic consequences of tax policies designed to reduce international profit shifting by multinational enterprises (MNEs) using a model that emphasizes the transfer pricing of intangible capital. We prove analytically that such policies would reduce MNEs’ intangible investment, reducing outputboth at home and abroad. We then quantify the effects of the OECD’s proposed reforms: reallocating the rights to tax MNEs’ profits to the countries where they sell their products; and a minimum global corporate income tax. These policies would reduce profit shifting by more than two-thirds but would also reduce output in all regions of the global economy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.272
Teacher spread0.246 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueTSpaceSame topicRegional Economics and Spatial AnalysisFrench-language works237,207