556
impact is possibly due to displacement of commercial inputs, input diversion, and
receipt of less than the required amount.
Using the computable general equilibrium (CGE) model calibrated to empirical
evidence from household-level evaluations, Arndt et al. (2015) reported the Malawi
FISP as pro-poor. The findings, however, contradicted Jayne and Rashid (2013)
who, using partial equilibrium assessments, reported FISP as low potential and
deeply grounded in political interests. Nonetheless, Arndt et al. (2015) observed that
FISP generates double dividends through higher and drought-resilient crop yields.
Using the integrated household survey data for 2010 and 2013, Sibande et al. (2017)
reported that access to FISP increases maize productivity, thereby leaving farmers
with a surplus for sale. However, the maize supply quantities are too small to affect
maize prices. Again, such quantities may not generate enough income to allow participating farmers self-finance input purchase in subsequent years, casting doubts
on the program’s long-term impact and sustainability.
Ricker-Gilbert and Jayne (2017) used four waves of panel data to estimate enduring effects of fertilizer subsidies on maize production and reported a modest positive
impact of fertilizer subsidies in a given year. One-kilogram increase in subsidized
fertilizer increases maize yield by 1.00–1.46 kg in year of access after accounting for
contemporaneous crowding out of commercial fertilizer, representing 100–150 kg at
standard FISP package. However, unlike their previous results of 2011, the 2017
findings by Ricker-Gilbert and Jayne did not find evidence of the impact of lagged
access to fertilizer subsidies on maize yield. This suggests that the Malawi fertilizer
subsidy program has limited long-term impacts on maize production.
Messina et al. (2017) used a novel approach to assess yield response to fertilizer
through remote sensing to identify the spatiotemporal performance of agricultural
fields and reported a national decline in the annual maize productivity trend. The
authors (ibid) suggest that the positive evidence reported by some authors could be
due to data error on maize production estimates and maize area cultivated. Farmlevel data often suffer from respondent measurement errors (Jayne and Rashid
2013). An evaluation of the 2016–2017 subsidy by the Centre for Development
Management (2017) also shows that production and productivity has stagnated in
recent years. While there was a substantial increase in maize productivity from
1.5 Mg/ha to 2.4 Mg/ha in the early years of the program, from 2013 to 2014 productivity has declined to 1.9 Mg/ha, suggesting low maize yield–fertilizer response
rate and subsequent reduction in the returns from FISP investments.
4.2 Marginal Maize Productivity Impact of Subsidized
Inorganic Fertilizer
Finding positive impact of FISP on beneficiaries vis-à-vis non-beneficiaries is not
enough as the success of the program depends on marginal return with respect to
what is agronomically expected (Pauw and Thurlow 2014). This is related to nitrogen use efficiency (NUE) (Vanlauwe et al. 2001a) defined in this chapter as amount
S. P. Katengeza
impact is possibly due to displacement of commercial inputs, input diversion, and
receipt of less than the required amount.
Using the computable general equilibrium (CGE) model calibrated to empirical
evidence from household-level evaluations, Arndt et al. (2015) reported the Malawi
FISP as pro-poor. The findings, however, contradicted Jayne and Rashid (2013)
who, using partial equilibrium assessments, reported FISP as low potential and
deeply grounded in political interests. Nonetheless, Arndt et al. (2015) observed that
FISP generates double dividends through higher and drought-resilient crop yields.
Using the integrated household survey data for 2010 and 2013, Sibande et al. (2017)
reported that access to FISP increases maize productivity, thereby leaving farmers
with a surplus for sale. However, the maize supply quantities are too small to affect
maize prices. Again, such quantities may not generate enough income to allow participating farmers self-finance input purchase in subsequent years, casting doubts
on the program’s long-term impact and sustainability.
Ricker-Gilbert and Jayne (2017) used four waves of panel data to estimate enduring effects of fertilizer subsidies on maize production and reported a modest positive
impact of fertilizer subsidies in a given year. One-kilogram increase in subsidized
fertilizer increases maize yield by 1.00–1.46 kg in year of access after accounting for
contemporaneous crowding out of commercial fertilizer, representing 100–150 kg at
standard FISP package. However, unlike their previous results of 2011, the 2017
findings by Ricker-Gilbert and Jayne did not find evidence of the impact of lagged
access to fertilizer subsidies on maize yield. This suggests that the Malawi fertilizer
subsidy program has limited long-term impacts on maize production.
Messina et al. (2017) used a novel approach to assess yield response to fertilizer
through remote sensing to identify the spatiotemporal performance of agricultural
fields and reported a national decline in the annual maize productivity trend. The
authors (ibid) suggest that the positive evidence reported by some authors could be
due to data error on maize production estimates and maize area cultivated. Farmlevel data often suffer from respondent measurement errors (Jayne and Rashid
2013). An evaluation of the 2016–2017 subsidy by the Centre for Development
Management (2017) also shows that production and productivity has stagnated in
recent years. While there was a substantial increase in maize productivity from
1.5 Mg/ha to 2.4 Mg/ha in the early years of the program, from 2013 to 2014 productivity has declined to 1.9 Mg/ha, suggesting low maize yield–fertilizer response
rate and subsequent reduction in the returns from FISP investments.
4.2 Marginal Maize Productivity Impact of Subsidized
Inorganic Fertilizer
Finding positive impact of FISP on beneficiaries vis-à-vis non-beneficiaries is not
enough as the success of the program depends on marginal return with respect to
what is agronomically expected (Pauw and Thurlow 2014). This is related to nitrogen use efficiency (NUE) (Vanlauwe et al. 2001a) defined in this chapter as amount
S. P. Katengeza