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Estimating Duality Models with Biased Technical Change: A Time Series Approach
Author(s) -
Clark J. Stephen,
Youngblood Curtis E.
Publication year - 1992
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1242489
Subject(s) - econometrics , technical change , variable (mathematics) , series (stratigraphy) , measure (data warehouse) , representation (politics) , contrast (vision) , economics , omitted variable bias , function (biology) , term (time) , econometric model , mathematics , computer science , macroeconomics , productivity , mathematical analysis , paleontology , physics , quantum mechanics , database , artificial intelligence , evolutionary biology , biology , politics , political science , law
Technical change is an omitted variable in econometric models which estimate technical change biases with no direct measure of this variable. Modeling technical change as a deterministic time trend is a restrictive representation that may be inconsistent with the type of nonstationarity of the other model variables. We used a time‐series approach to estimate a cost function for central Canada and found that factor shares, prices, and output are cointegrated, implying that technical change is neutral. In contrast, estimating the system with a time trend as a technical change measure leads one to conclude inappropriately that technical change biases exist.

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