Abstract
This article describes the construction of the Luenberger soil quality indicator (SQI) using data on crop yield, non-soil inputs, and soil profile from three irrigated agroecological zones of Punjab, Pakistan, namely, rice–wheat, maize–wheat–mix, and cotton–mix zones. Plot level data are used to construct a soil quality indicator by estimating directional distance functions within a data envelopment analysis (DEA) framework. We find that the SQI and crop yield relationships exhibit diminishing returns to improving soil quality levels. Using the constructed SQI values, we estimate linear regression models to generate weights that could be used directly to aggregate individual soil attributes into soil quality indicators without the necessity of fitting a frontier to the crop production data. For wheat and rice production, we find that SQI is most sensitive to changes in soil electrical conductivity (EC) and potassium (K). The SQI has direct relevance for site-specific decision-making problems where policymakers need to price land resources and conservation services to achieve agricultural and environmental goals.
| Original language | English |
|---|---|
| Pages (from-to) | 531-553 |
| Number of pages | 23 |
| Journal | Agricultural Economics (United Kingdom) |
| Volume | 55 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - May 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 15 Life on Land
Fingerprint
Dive into the research topics of 'Soil quality evaluation for irrigated agroecological zones of Punjab, Pakistan: The Luenberger indicator approach'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver