TY - JOUR
T1 - Soil quality evaluation for irrigated agroecological zones of Punjab, Pakistan
T2 - The Luenberger indicator approach
AU - Sheikh, Asjad Tariq
AU - Hailu, Atakelty
AU - Mugera, Amin
AU - Pandit, Ram
AU - Davies, Stephen
N1 - Publisher Copyright:
© 2024 The Authors. Agricultural Economics published by Wiley Periodicals LLC on behalf of International Association of Agricultural Economists.
PY - 2024/5
Y1 - 2024/5
N2 - 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.
AB - 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.
KW - agroecological zones
KW - crop yield
KW - data envelopment analysis
KW - directional distance function
KW - soil attributes
KW - soil quality indicator
UR - http://www.scopus.com/inward/record.url?scp=85192222225&partnerID=8YFLogxK
U2 - 10.1111/agec.12831
DO - 10.1111/agec.12831
M3 - Article
AN - SCOPUS:85192222225
SN - 0169-5150
VL - 55
SP - 531
EP - 553
JO - Agricultural Economics (United Kingdom)
JF - Agricultural Economics (United Kingdom)
IS - 3
ER -