Investment in Human Capital and Economic Growth in Nigeria Using a Causality Approach
Bibliographic record
Abstract
The paper examined the causal nexus between human capital Investment and economic growth in Nigeria for sustainable development in Africa at large between 1970 and 2009 using a Vector Error Correction (VEC) and Pairwise granger causality methodologies. The variables used in the study were tested for stationarity using the Augmented Dickey Fuller and Philip Perron test. The result showed that the variables are stationary at first differencing. Co-integration test was also performed and the result revealed the absence of co-integration between Investment in human capital and economic growth. The findings of the VAR model and pairwise estimate revealed no causality between human capital development and economic growth. The study recommends the need to increase budgetary allocation to the education and health sector and the establishment of sound and well-functioning vocational institute needed to bring about the needed growth in human capital that can stimulate economic growth. Also, the study identified that labour mismatch is an issue that government needs to reckon with in order to accelerate and sustain economic growth. In this regard, policy-makers in conjunction with employers and individuals needs to up date information on the real labour market value of different qualifications, in order to help them navigate through the increasingly complex education system and make the optimal kinds of educational investment decisions needed to propel economic growth. Key words: Human capital; Economic growth; Pairwise; Causality; VAR; Sustainable development; Budgetary allocation Resume: Le document examine le lien de causalite entre l'investissement en capital humain et croissance economique au Nigeria pour le developpement durable en Afrique en general entre 1970 et 2009 en utilisant un vecteur de correction d'erreur (VEC) et les methodologies de causalite de Granger par paire. Les variables utilisees dans l'etude ont ete testes pour stationnarite en utilisant les Dickey Fuller et Philippe Perron Test. Le resultat a montre que les variables sont stationnaires au differenciation premiere. Co-integration de test a egalement ete effectue et le resultat a revele l'absence de co-integration entre l'investissement en capital humain et croissance economique. Les resultats du modele VAR et estimer paires n'ont pas revele de lien de causalite entre le developpement du capital humain et croissance economique. L'etude recommande la necessite d'accroitre l'allocation budgetaire au secteur de l'education et la sante et la creation de sons et de bon fonctionnement institut professionnel necessaire pour provoquer la croissance necessaire dans le capital humain qui peut stimuler la croissance economique. En outre, l'etude a identifie que l'inadequation du travail est une question que le gouvernement doit compter avec dans le but d'accelerer et de soutenir la croissance economique. A cet egard, les decideurs politiques en collaboration avec les employeurs et les personnes ayant des besoins de mise a jour des informations sur la valeur reelle du marche du travail des qualifications differentes, afin de les aider a naviguer dans le systeme educatif de plus en plus complexes et faire le genre de decisions d'investissement optimales educatives necessaires a la propulser la croissance economique. Mots cles: Le capital humain; La croissance economique; Par paires; Causalite; VAR
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".