The Economic Value of Environmental Capital Inputs Used to Produce the Gross Domestic Product in Ghana, 1993 to 2012
Bibliographic record
Abstract
Ghana has been one of the fastest growing countries in the world over the last decade driven by exports of oil from newly-discovered offshore oil fields, the export of its traditional commodities of cocoa, gold and other extractive minerals, construction, and the expansion of services related to banking, information and communication technologies, and tourism. Measured by the change in real gross domestic product (GDP), the economy grew at a pace of 7.5% over the period from 2004 to 2013 and 8.6% from 2009 to 2013, and was among the top 15 performers in the world. The Ghanaian economy was formally classified as lower-middle-income in 2010 with a per capita income of over 1,300 United States dollars. Our study focuses on measuring the values of labour and capital inputs used to produce the goods and services incorporated in the GDP. We acknowledge the existence of two types of capital inputs used to produce final goods and services. These are (1) human-made or manufactured capital such as machinery and equipment and (2) environmental capital items such as proven oil and gas reserves, mineral deposits, forest and water resources that are required to produce final goods and services in the economy. We estimated the size of environmental or natural capital stock used to produce the GDP over the twenty-year period, 1993 to 2012 assuming that the economy as a whole exhibited a constant returns to scale feature. The results indicate that over the period, 1993 to 2012, the average share attributed to labour in the production of GDP was about 45%. Human-made capital inputs contributed on average about 19% of GDP. The remaining share of 36% was the estimated value of environmental capital inputs used to produce GDP. We also established that the aggregate environmental depreciation was significantly related to GDP in a positive log-linear fashion while its relationship to real interest rate was negative but not statistically significant.
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 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".