COWLES FOUNDATION FOR RESEARCH IN
ECONOMICS Box 208281
COWLES FOUNDATION DISCUSSION PAPER NO. 1685 The Perils of the Learning Model For Modeling Endogenous Technological Change William D. Nordhaus January 2009 Learning or experience curves are widely used to estimate cost functions in
manufacturing modeling. They have recently been introduced in policy models of energy and
global warming economics to make the process of technological change endogenous. It is not
widely appreciated that this is a dangerous modeling strategy. The present note has three
points. First, it shows that there is a fundamental statistical identification problem in
trying to separate learning from exogenous technological change and that the estimated
learning coefficient will generally be biased upwards. Second, we present two empirical
tests that illustrate the potential bias in practice and show that learning parameters are
not robust to alternative specifications. Finally, we show that an overestimate of the
learning coefficient will provide incorrect estimates of the total marginal cost of output
and will therefore bias optimization models to tilt toward technologies that are
incorrectly specified as having high learning coefficients. |
