Payments for Ecosystem Services, Poverty and Sustainability: The Case of Agricultural Soil Carbon Sequestration

Abstract

This chapter explores the potential impacts of payments for ecosystem services on poverty and sustainability of farm households, using the example of agricultural soil carbon sequestration. Economic analysis shows that there is a variety of technical and economic factors affecting adoption of practices that increase soil carbon and their impacts on poverty, hence, the net effect of these factors is an empirical question. The evidence suggests that carbon payments could have a positive impact on the sustainability of production systems while also raising incomes and reducing poverty. However, carbon contracts are found to have only modest impacts on poverty, even at relatively high carbon prices. Moreover, the participation of poor farmers in carbon contracts is likely to be constrained by the same economic and institutional factors that have inhibited their use of more productive, more sustainable practices in the first place. Thus, payments for ecosystem services are most likely to have a positive impact on poverty and sustainability when they are implemented in an enabling economic and institutional environment.

Appendix

In this appendix we provide a more formal discussion of how farmer participation in carbon contracts is modeled in the case studies. Following Antle and Diagana (2003), the analysis is formalized by assuming that to increase the stock of SOC on a land unit, a farmer must make a change from production system i (conventional) that had been followed over some previous period (the historical land-use baseline) to some alternative (conservation) system s. We assume that utilization of management practice i up to time 0 results in a SOC level of C(i), and adoption of practice s at time 0 causes the level to increase to an equilibrium C(s) at time T. At time T, the soil reaches a new level at which the level of soil C stabilizes until further changes in management occur. In defining ex ante carbon contracts, we emphasize that the expected change in carbon accumulation is the relevant variable; the actual rate of carbon accumulation will typically only be verified for the land units aggregated into a contract, as discussed by Antle et al. (2003a). This expected change in carbon is assumed to be estimated by agro-ecozone and past land-use practices, with all farmers in the contract in that zone receiving credit for the same rate, as explained further below.

With a per-ton carbon contract, the farmer receives a payment of $P _t per ton of C sequestered each time period, so if the farmer changes from practice i to practice s and soil C is expected to increase by Δc _t(i,s) tons/ha per period, the farmer receives a payment of P _t Δc _t(i,s) per hectare per period. The net present value (NPV) of changing from system i to system s for T periods is given by:

$$ NPV(i,s){\rm{ = }}\sum\limits_{t{\rm{ = 1}}}^T {D_t {\rm{[}}NR{\rm{(}}p_t {\rm{, }}w_{\rm{t}} {\rm{, }}z_t {\rm{, }}s{\rm{) + g}}_{\rm{t}} {\rm{(}}i,s{\rm{) -- }}M_{\rm{t}} {\rm{(}}i,s{\rm{)] -- }}I(i, s{\rm{)}}} $$

((7.A1))

where D _t = (1/(1 + r))^t and r is the interest rate per time period, NR(p _t , w _t, z _t , s) is expected net returns per hectare for system s in period t, given product price p _t , input prices w _t and capital services z _t ; g _t (i,s) = g _t if a per-hectare contract, or g_t(i,s) = P _t Δc _t(i,s) if a per-ton contract; M _t (i,s) is the variable cost per period for changing from system i to s; and I(i,s) is the fixed cost for changing from system i to system s (both variable and fixed costs of adoption may include transaction costs). If the farmer does not participate in the contract and continues producing with system i, then g _t (i,s) = M _t (i,s) = I(i,s) = 0 and the farmer earns NPV(i). The farmer enters the contract if and only if NPV(i,s) > NPV(i), and does not enter the contract otherwise.

To simplify this discussion, it is useful to consider the special case where NR(p, w, z, s), P, Δc(i,s), and M(i,s) are constant over time. If we also let the fixed investment be converted into an equivalent annuity of fc(i,s) dollars per period, then the expression NPV(i,s) > NPV(i) can be simplified to

$$ NR(p,w,z,s) + g(i,s) - M(i,s) - fc(i,s) > NR(p,w,z,i){\rm{.}} $$

((7.A2))

Note that under these assumptions, if it is profitable to enter the contract in one period, it is profitable in all periods regardless of the discount rate. More generally, the discount rate will play an important role, as in the analysis of terracing in Peru. This expression has several implications for analysis of adoption of soil carbon sequestration practices.

In the initial equilibrium in which there are no payments available for carbon sequestration, g = 0, and the farmer adopts the conservation practice s only if it provides higher net returns than the conventional practice i. When a carbon contract is offered for adoption of practices that sequester carbon, g > 0 and we can rewrite Eq. (7.A2) as:

$$ g(i,s) > NR(p,w,z,i) - NR(p,w,z,s) + M(i,s) + fc(i,s). $$

((7A3))

The expression on the right-hand side is the opportunity cost for switching to system s from system i. The farmer will switch practices when the opportunity cost is less than the payment per period. In the case of a per-ton contract, g(i,s) = PΔc(i,s) and the condition for participation in the contract can be expressed as:

$$ P > \{ NR(p,w,z,i) - NR(p,w,z,s) + M(i,s) + fc(i,s)\} /\Delta c(i,s) $$

((7.A4))

showing that the farmer will be willing to enter a carbon contract when the price per ton of carbon is greater than the opportunity cost per ton.

A critical feature of Eq. (7.A4) is the spatial variation in the opportunity cost. Net returns to the conventional and alternative practices are site-specific. Some components of the variable and fixed costs of changing practices may be site-specific (e.g., the cost of constructing a terrace), whereas transaction costs may be spatially invariant. The denominator of Eq. (7.A4), the expected rate of carbon accumulation, is specific to the agro-ecozone where the land unit is located, as noted above. Thus, the participation by farmers in carbon contracts depends on the spatial distribution of the opportunity cost of changing practices. Those land units with opportunity cost less than P will participate in the contract, and those land units with a higher opportunity cost will not participate. Summing the quantities of carbon across participating land units at each price gives the carbon supply curve for the region.

In the discussion thus far, we have assumed that the practices i and s involve a binary choice, such as the use of terracing on a field. In the case of incorporation of organic matter and use of fertilizer, however, while it is true that many farmers use no fertilizer, many farmers may use positive amounts but less than the quantities required by the carbon contract. In that case, the carbon rate used to calculate the payment is adjusted to reflect the fact that a smaller amount of carbon will be added to the soil before the new equilibrium stock of carbon is attained. The simulation studies discussed below assume that for a required input rate x _c specified in the contract, farmers who have been using a baseline rate x _b less than x _c receive credit for a carbon rate in proportion to the difference between the base rate and the contract rate, and receive zero credit otherwise:

$$ \Delta c(i,s,x_c ,x_b ) = \Delta c(i,s)(x_c - x_b )/x_c ,x_c - x_b > 0 $$

((7.A5))

$$ = 0\;otherwise $$

The baseline rate of input use is defined as the average rate used by the farmer on a field, over a specified period of time, before the field was entered into a carbon contract.