Using panel survey and remote sensing data to explain yield gaps for maize in sub-Saharan Africa. Issue 3 (4th May 2018)

• Record Type: Journal Article
• Authors: Djurfeldt, Göran; Hall, Ola; Jirström, Magnus; Archila Bustos, Maria; Holmquist, Björn; Nasrin, Sultana
• Is Part Of: Journal of land use science. Volume 13:Issue 3(2018)
• Page Start: 344
• Page End: 357
• Publication Date: 2018-05-04
• Subjects: Smallholders -- sub-Saharan Africa -- yield gaps -- panel data -- transdisciplinary explanation; Land use -- Periodicals; 333.7313
• DOI: 10.1080/1747423X.2018.1511763
• Languages: English
• ISSNs: 1747-423X

Abstract

ABSTRACT: The aim of this paper is to combine remote sensing data with geo-coded household survey data in order to measure the impact of different socio-economic and biophysical factors on maize yields. We use multilevel linear regression to model village mean maize yield per year as a function of NDVI, commercialization, pluriactivity and distance to market. We draw on seven years of panel data on African smallholders, drawn from three rounds of data collection over a twelve-year period and 56 villages in six countries combined with a time-series analysis of NDVI data from the MODIS sensor. We show that, although there is much noise in yield forecasts as made with our methodology, socio-economic drivers substantially impact on yields, more, it seems, than do biophysical drivers. To reach more powerful explanations researchers need to incorporate socio-economic parameters in their models.