Open AccessECONOMIC EVALUATION OF BIOTECHNOLOGICAL PROGRESS: THE EFFECT OF CHANGING MANAGEMENT BEHAVIOR
Author(s) -
GONG PEICHEN,
LÖFGREN KARLGUSTAF,
ROSVALL OLA
Publication year - 2013
Publication title -
natural resource modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.28
H-Index - 32
eISSN - 1939-7445
pISSN - 0890-8575
DOI - 10.1111/j.1939-7445.2012.00118.x
Subject(s) - counterfactual thinking , economics , economic surplus , partial equilibrium , welfare , value (mathematics) , production (economics) , function (biology) , econometrics , microeconomics , natural resource economics , mathematics , statistics , general equilibrium theory , biology , philosophy , epistemology , evolutionary biology , market economy
The paper assesses the welfare effects of biotechnological progress, as exemplified by tree improvements, using a partial equilibrium model. Timber demand is assumed to be stochastic and the distributions of its coefficients known. The coefficients of a log‐linear supply function are determined by maximizing the expected present value of the total surplus of timber production, both in the presence and in the absence of genetically improved regeneration materials. The supply functions are then used to estimate the expected present values of the total surplus in different cases through simulation. These estimates enable us to assess the direct effect and the effect of changing harvest behavior on the expected present value of the total surplus. The main results of the study are (i) the presence of genetically improved regeneration materials has significant impacts on the aggregate timber supply function; (ii) the application of genetically improved regeneration materials leads to a significant increase in the expected present value of the total surplus; and (iii) a considerable proportion of the welfare gain results from the change in harvest behavior. A conclusion we draw from this study is that ignoring the influences of technological and policy changes on behavior can lead to significantly biased welfare estimates. We view the model as a potential approach to conducting counterfactual policy comparisons in economics without forward‐looking data.