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Record W7056627191

Essays in Public Economics

2023· other· en· W7056627191 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship (California Digital Library) · 2023
Typeother
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)PharmacyPublic policyPublic sectorHealth carePrivate sectorPublic healthDownstream (manufacturing)
DOInot available

Abstract

fetched live from OpenAlex

This dissertation explores empirically the role of government in addressing contemporary public health pressing issues. The first chapter studies the entrance of state-owned pharmacies to provide access to affordable pharmaceutical drugs. This is joint work with Juan Pablo Atal from University of Pennsylvania, José Ignacio Cuesta from Stanford University, and Felipe González from Queen Mary University of London. We find that public pharmacies sell the same drugs at a third of private pharmacy prices, because of stronger upstream bargaining and downstream market power in the private sector but are of lower quality. Leveraging the decentralized entry of public pharmacies to local markets in Chile, we show that public pharmacies induced market segmentation and price increases in the private sector, benefiting the switchers to the public option but harming the stayers. We conclude that the countrywide entry of public pharmacies would reduce yearly consumer drug expenditure and significantly outweigh the costs of the policy.In the second chapter, in joint work with Pablo Muñoz from Universidad de Chile, we ask how governments can improve healthcare provision in public hospitals. To this end, we study a reform in Chile that aimed to improve public service provision by dramatically changing the way government institutions recruit high-ranking civil servants. We focus on the impact of the policy on public hospital performance and examine the underlying mechanisms through which public managers affect public health outcomes. The paper shows that the policy reduced hospital mortality around 8%, an effect that persisted after three years. We also find that the policy changed the pool of CEOs by displacing older doctors with no management training in favor of younger CEOs with either undergraduate degrees in management or doctors with master’s degrees or diplomas in management. We find that the reform affected hospital mortality mostly when newly appointed managers had management studies, who introduced more efficient use of medical resources and better personnel practices.The third chapter studies an innovative nationwide policy that mandates the use of warning labels on products whose sugar or calorie concentration exceeds certain thresholds to address increasing obesity. The policy was first passed in Chile and has been widely replicated in several countries such as Argentina, Brazil, Canada, Mexico, Israel, among others. In a joint project with Nano Barahona and Sebastián Otero, both from UC Berkeley, we partnered with Walmart-Chile to study the effects of the policy Chile. We find that consumers substituted from labeled to unlabeled products, a pattern mostly driven by products that consumers mistakenly believe to be healthy. On the supply side, we document substantial reformulation of products and bunching at the thresholds. Next we develop and estimate an equilibrium model of demand for food and firms’ pricing and nutritional choices. The main finding is that that food labels increase consumer welfare, an effect that is enhanced by firms’ responses. We conclude that under optimal policy thresholds, food labels and sugar taxes generate similar gains in consumer welfare, but food labels benefit the poor relatively more.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.757
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.007

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 head0.016
GPT teacher head0.195
Teacher spread0.179 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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