Roads, Electricity, and Jobs: Evidence of Infrastructure Complementarity in Sub-Saharan Africa
Bibliographic record
Abstract
Evidence for road expansion and \n electrification as drivers of job creation is limited and \n mixed, with most studies having considered either one or the \n other, and only in isolation. This paper estimates the \n average and heterogeneous impacts of road and electricity \n investments and the interaction of the two on job creation \n over the past two decades in 27 countries of sub-Saharan \n Africa. Exploiting the exogenous location of ancestral \n ethnic homelands, a new instrumental variable is created for \n road accessibility, inspired by post-independence \n leaders' agenda of building roads to extend authority \n over the entire expanse of their country, and to promote \n nation building. Topography and lightning strikes—a key \n source of damage to electric lines and disruption of \n service—are used to instrument electricity supply. The paper \n finds positive and significant effects on employment from \n enhancing proximity to roads and to electric grids. \n Moreover, the interaction of the two enhances the effects, \n making them complementary investments. The impacts of both \n individual and bundled investments are positive, but with \n differences between men and women, workers of various ages, \n and countries at different stages of development. In urban \n areas, better access to roads and electricity promotes all \n types of employment. In rural areas, greater access induces \n a transition from low- to high-skilled occupations. These \n differential effects suggest that the structural \n transformation brought about by road and electricity \n expansion is primarily a rural phenomenon.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".