Macroeconomic growth, sectoral quality of growth and poverty in developing countries: Measure and application to Burkina Faso. Working paper 04-07, Université de Sherbrooke
Bibliographic record
Abstract
Economic growth generally refers to GDP growth. The studies on the link between growth and poverty dynamic (Datt and Ravallion, 1992; Kakwani, 1997; Shorrocks, 1999) measure growth by mean household per capita expenditures. Furthermore, many countries experience at the same time economic growth and growing poverty. It is therefore important to establish a link between these two types of growth. This key link allows a formal shift from macroeconomic growth (GDP growth) to mean per capita household expenditure growth. The purpose of this paper is to discuss the link between macroeconomic growth and mean per capita household expenditure growth with the evidence drawn from Burkina Faso data. The paper also analyzes the impact of sectoral growth on poverty using Shapley value-based decomposition approach. National Accounts consumption- which is smaller- gives greater poverty incidences for 1994 and 1998 compared to the incidence from the surveys ’ consumption. An annual 3.99 % increase in real per capita consumption based on the survey gives a 13.37 % decrease in poverty incidence, while a 6.59 % annual growth in GDP yields only 6.59 % decrease in poverty incidence. Agricultural sector
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".