Agroforestry Adoption: Keynes’ Animal Spirits are Alive and Well in the Yucatan James F. Casey Washington & Lee University Prepared for SAPPCREE Session Southern Economic Association Annual Meeting in New Orleans, LA November 21, 1999

CONTENTS OF THIS TALK Background / Motivation for the body of work Objective of this paper Keynes’ Theory of Investment Model for Agroforestry Adoption The Data Model Specification Results and Implications

BACKGROUND / MOTIVATION Agroforestry: emerging as a scientific discipline, emphasis on biophysical In general: lack of socioeconomic research –(Mercer and Miller 1998) Adoption rates are low

Low Rates of Adoption?? Natural Science is well understood Insufficient Economic data –models for behavior (Ghadim and Pannell 1999) –risk and uncertainty (Negatu and Parikh 1999) –non-market benefits –market failure ( Casey, Caviglia, Kahn and Rivas 1999)

OBJECTIVE Develop a model based on Keynes’ notion of profit expectation and “weight” in order to more accurately predict farmer interest in agroforestry

KEYNES’ THEORY OF INVESTMENT Profit expectations and confidence –(Anderson & Goldsmith 1997) Notions of “weight” Precarious nature of Investment

Keynes and Agroforestry Uncertainty Asking the farmer to invest Profit forecast and “Weight” Reducing Uncertainty Investment in Human Capital

Model for Agroforestry Adoption Max U (A(ta), C(tc), M(*, taB)) s.t. T - tc - ta = 0 –U(A(ta),C(tc),M(*, taB))> U(0,C(tc),M(*)) Comparative Statics for B dta/dB = (+) dtc/dB = (-) –Investment = f(profit forecast, weight) –Weight = f(Human Capital Investment) –HC Investment = f(Ed, Exp, Trees, Part) –Invest AF = f(Human Capital Investment)

Human Capital Investment Education Farming Experience Experience with Trees Comfort with Participation Previous Success

THE DATA Calakmul, Campeche, Mexico, the CBR 176 farmers interviewed 15 communities 142 expressed interest in Agroforestry

Farmer Characteristics

Model Specification Logit Y = a + bSi + bHi + bR + e S: Vector of socioeconomic variables H: Human Capital variables R: Rainfall strata

MODEL RESULTS –Table 4. LOGIT MODEL: participation (1) or not (0) VariablesCoefficientZ – stat TREES ** ED * SURV * EXP PART INC * STRAT FARM Constant Psuedo R2 = 0.156Chi2 (8) = 25.98N = 175  * significant at.1Correctly Classified 84.00%  ** significant at.05

HC variables Education (positive and significant) Farming Experience(positive) Experience with Trees (positive and significant) Comfort with Participation (positive) Previous Success (positive and significant)

Conclusion and Policy Implications Farmers with more human capital are more likely to participate. Weight is important. Investment is precarious. Education and Extension Listen to farmers.