307
should be used for unbiased impact assessment (Lipper et al. 2018). It must also be
noted that little distinction is made between different types of loans (formal vs.
informal) and their terms and conditions (such as loan size, interest rate, collateral
requirements and duration). Loans can serve rather different purposes (e.g., a microcredit loan for a woman’s trading activity plays an entirely different role in the
household economy than a crop input loan) and will thus have different effects on
resource-management practices and CSA outcomes.
The overall evidence base supporting the idea that lack of available credit limits
CSA adoption is therefore rather weak. Sometimes access to credit can even lead to
land-use specialization and intensification at the expense of climate-friendly technologies. For resource-poor farmers, credit constraints can support the adoption of
more labour-intensive climate mitigation practices as an alternative to more expensive external input technologies (Rioux et al. 2016). As Arslan et al. (2016) demonstrated for Tanzania, improving access to credit is likely not only to increase the
adoption of modern inputs (such as high-yielding maize varieties and inorganic
fertilizer) but also to decrease maize-legume intercropping practices that have
longer- run benefits for soil health and adaptation. There are thus important tradeoffs to be considered among different intensification strategies that are supported
through access to finance.
26.3.2 Income and Expenditures Pathway
For investing in CSA, access to savings and financial services such as insurance,
transfers and remittances may be as important as access to credit. Poor farmers who
wish to avoid debt may prefer to invest using funding from their own non-farm or
off-farm income. An indirect pathway may work best: helping farmers to build a
larger household income derived from a variety of resources may allow them to
make investments in CSA practices.
Based on integrated farm-household models that combine production and expenditure decisions (Singh et al. 1986), smallholder farmers who have solid expectations for stable revenue streams (even at low levels) are more likely to invest in CSA
practices (Lopez-Ridaura et al. 2018; Ruben et al. 2007). Such models also enable
assessment of the likely impact of different policy incentives on the allocation of
resources within the farm household. Analytical simulation modelling suggests that
risk-sharing instruments (e.g., risk-bearing credit, input dealers’ risk sharing, voluntary cost sharing and hired-labour risk sharing)
1
can lead to higher CSA adoption
rates compared to subsidized loans. In fact, offering low-interest credit appears to
be a relatively ineffective strategy for encouraging the adoption of agricultural technologies (Feder and Umali 1993). Instead, activity diversification has repeatedly
been shown to encourage both savings and investing in strategies that help cope
1 Much of the risk modelling takes place within the framework of the AgMip programme (https://
www.agmip.org/).
26 Rural Finance to Support Climate Change Adaptation: Experiences, Lessons…
should be used for unbiased impact assessment (Lipper et al. 2018). It must also be
noted that little distinction is made between different types of loans (formal vs.
informal) and their terms and conditions (such as loan size, interest rate, collateral
requirements and duration). Loans can serve rather different purposes (e.g., a microcredit loan for a woman’s trading activity plays an entirely different role in the
household economy than a crop input loan) and will thus have different effects on
resource-management practices and CSA outcomes.
The overall evidence base supporting the idea that lack of available credit limits
CSA adoption is therefore rather weak. Sometimes access to credit can even lead to
land-use specialization and intensification at the expense of climate-friendly technologies. For resource-poor farmers, credit constraints can support the adoption of
more labour-intensive climate mitigation practices as an alternative to more expensive external input technologies (Rioux et al. 2016). As Arslan et al. (2016) demonstrated for Tanzania, improving access to credit is likely not only to increase the
adoption of modern inputs (such as high-yielding maize varieties and inorganic
fertilizer) but also to decrease maize-legume intercropping practices that have
longer- run benefits for soil health and adaptation. There are thus important tradeoffs to be considered among different intensification strategies that are supported
through access to finance.
26.3.2 Income and Expenditures Pathway
For investing in CSA, access to savings and financial services such as insurance,
transfers and remittances may be as important as access to credit. Poor farmers who
wish to avoid debt may prefer to invest using funding from their own non-farm or
off-farm income. An indirect pathway may work best: helping farmers to build a
larger household income derived from a variety of resources may allow them to
make investments in CSA practices.
Based on integrated farm-household models that combine production and expenditure decisions (Singh et al. 1986), smallholder farmers who have solid expectations for stable revenue streams (even at low levels) are more likely to invest in CSA
practices (Lopez-Ridaura et al. 2018; Ruben et al. 2007). Such models also enable
assessment of the likely impact of different policy incentives on the allocation of
resources within the farm household. Analytical simulation modelling suggests that
risk-sharing instruments (e.g., risk-bearing credit, input dealers’ risk sharing, voluntary cost sharing and hired-labour risk sharing)
1
can lead to higher CSA adoption
rates compared to subsidized loans. In fact, offering low-interest credit appears to
be a relatively ineffective strategy for encouraging the adoption of agricultural technologies (Feder and Umali 1993). Instead, activity diversification has repeatedly
been shown to encourage both savings and investing in strategies that help cope
1 Much of the risk modelling takes place within the framework of the AgMip programme (https://
www.agmip.org/).
26 Rural Finance to Support Climate Change Adaptation: Experiences, Lessons…