MétaCan
Menu
Back to cohort
Record W2466931159

Essays On Russian Economic Geography: Measuring Spatial Inefficiency

2004· article· en· W2466931159 on OpenAlexaboutno aff
Tatiana Mikhailova

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsnot available
Fundersnot available
KeywordsInefficiencyPopulationContext (archaeology)GeographyCounterfactual thinkingEconomicsEconomyMarket economy
DOInot available

Abstract

fetched live from OpenAlex

Compared with other transition countries Russia faces the burden of extreme cold. This is not, however, strictly a function of geography. Soviet location policy directly affected the average (population weighted) temperature of the Russian economy. Soviet policy moved industry and population from the western part of the country to the east, effectively making Russia even colder than it was in the pre-Soviet era. Movements to the east have the significant impact on aggregate temperature because the isotherms on the Eurasian continent resemble lines of longitude, not latitude. Thus, the Russian economy entering transition faces not only the usual burden of an inhospitable Russian climate, but also suffers from the extra disadvantage due to the legacy of Soviet location policy. In this thesis I estimate the cost to Russian economy of the inefficient spatial allocation of its productive resources. Spatial inefficiency can result not only in added production and distribution costs — when regional comparative advantages are not exploited and unnecessary transportation and communication expenditures are incurred — but also the wrong allocation of labor brings inefficiency in consumption: there are extra costs associated with people living in unsuitable places. In the Russian context, “unsuitable” usually means “too far” and “too cold.” I focus on the “cost of cold,” or precisely, the cost of production being wrongly located in places with a climate too cold. The first essay is a counterfactual exercise. To obtain a benchmark of spatial efficiency, I construct an allocation of industry and population that would result in Russia in the absence of Soviet location policy. To design such an allocation, I impose Canadian behavior on Russian initial conditions. I estimate a spatial dynamic model on Canadian regional panel data in a multinomial logit framework. I then project the estimated relationship onto Russia. The result is a hypothetical allocation of population and industry, specific to Russia’s endowment and initial conditions, but free of any disadvantages stemming from Russian historical circumstances. This procedure, however, ignores the effect of WWII — a major exogenous shock to Russian economy with no precedent in Canada. We should expect that war would have an impact on industry allocation irrespective of economic or political system. To account for the possible effects of WWII I conduct a separate simulation exercise, taking into account the fact that the war was fought primarily in the west. The results of this exercise show that the eastern part of Russia is still significantly overdeveloped — in other words, WWII explains only a small part of the misallocation.

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 categoriesInsufficient 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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.004

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 head0.193
Teacher spread0.167 · 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

Citations17
Published2004
Admission routes1
Has abstractyes

Explore more

Same topicEconomic Growth and ProductivityFrench-language works237,207