Methodological Evaluation of Process-Control Systems in Nigeria Using Difference-in-Differences for Yield Improvement Assessment
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| Format: | Recurso digital |
| Sprache: | Englisch |
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2011
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| _version_ | 1866901595526004736 |
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| author | Nwosu, Iheanacho Chikwendiu, Nkwerere Okechi, Osaze Ezigbo, Uzoma |
| author_facet | Nwosu, Iheanacho Chikwendiu, Nkwerere Okechi, Osaze Ezigbo, Uzoma |
| contents | <p>Process-control systems play a critical role in enhancing yield efficiency across various industries, including manufacturing and agriculture. In Nigeria, these systems are underutilized or poorly implemented, leading to significant losses in productivity and revenue. A mixed-methods approach is employed, integrating both qualitative interviews with stakeholders and quantitative DiD model analyses to evaluate the impact of process-control systems on yields in Nigerian settings. Data from a select sample of agricultural and manufacturing sectors will be analysed using regression models to estimate yield changes over time. The preliminary analysis suggests that implementing robust process-control systems can lead to an average 15% increase in yield, with notable improvements observed in crop yields for small-scale farmers in the northern region of Nigeria. The DiD model estimates a significant return on investment (ROI) of at least 20% within two years. This study demonstrates the potential of process-control systems to significantly boost agricultural and industrial productivity in Nigeria, offering a practical framework for policymakers and practitioners aiming to enhance yield efficiency. Policymakers are encouraged to invest in capacity-building programmes for farmers and manufacturers, providing training on effective use of process-control systems. Additionally, government support through subsidies or grants can facilitate wider adoption of these technologies. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18928994 |
| institution | Zenodo |
| language | eng |
| publishDate | 2011 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Methodological Evaluation of Process-Control Systems in Nigeria Using Difference-in-Differences for Yield Improvement Assessment Nwosu, Iheanacho Chikwendiu, Nkwerere Okechi, Osaze Ezigbo, Uzoma Nigerian geospatial econometrics process-control yield-gap intervention-analysis difference-in-differences <p>Process-control systems play a critical role in enhancing yield efficiency across various industries, including manufacturing and agriculture. In Nigeria, these systems are underutilized or poorly implemented, leading to significant losses in productivity and revenue. A mixed-methods approach is employed, integrating both qualitative interviews with stakeholders and quantitative DiD model analyses to evaluate the impact of process-control systems on yields in Nigerian settings. Data from a select sample of agricultural and manufacturing sectors will be analysed using regression models to estimate yield changes over time. The preliminary analysis suggests that implementing robust process-control systems can lead to an average 15% increase in yield, with notable improvements observed in crop yields for small-scale farmers in the northern region of Nigeria. The DiD model estimates a significant return on investment (ROI) of at least 20% within two years. This study demonstrates the potential of process-control systems to significantly boost agricultural and industrial productivity in Nigeria, offering a practical framework for policymakers and practitioners aiming to enhance yield efficiency. Policymakers are encouraged to invest in capacity-building programmes for farmers and manufacturers, providing training on effective use of process-control systems. Additionally, government support through subsidies or grants can facilitate wider adoption of these technologies. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.</p> |
| title | Methodological Evaluation of Process-Control Systems in Nigeria Using Difference-in-Differences for Yield Improvement Assessment |
| topic | Nigerian geospatial econometrics process-control yield-gap intervention-analysis difference-in-differences |
| url | https://doi.org/10.5281/zenodo.18928994 |