| Summary: | I set forth a generalized stochastic time trend approach, based upon the Kalman filter, as an alternative to the general index approach to measure technological change. Technology is treated as a latent variable in a state-space model of the production function. In data sparse settings, where panel data are unavailable, the method provides results which encompass insights from the general index approach, but provides more detailed estimates. I revisit an analysis of technological change in the Lofoten fishery. The estimated technology time profiles agree to some extent between the methods, but my more detailed results demand a new historical interpretation.
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