期刊名称：CREDIT Research Paper / University of Nottingham
出版年度：2011
卷号：1
出版社：Nottingham
摘要：The cross-country growth literature commonly uses aggregate economy datasets such
as the Penn World Table (PWT) to estimate homogeneous production function or
convergence regression models. Against the background of a dual economy
framework this paper investigates the potential bias arising when aggregate economy
data instead of sectoral data is adopted in macro production function regressions.
Using a unique World Bank dataset we estimate production functions in agriculture
and manufacturing for a panel of 41 developing and developed countries (1963-
1992). We employ novel empirical methods which can accommodate technology
heterogeneity, variable nonstationarity and the breakdown of the standard crosssection
independence assumption. We focus on technology heterogeneity across
sectors and countries and the potential for biased estimates due to aggregation and
empirical misspecification, relying on both theory and empirical evidence. Using data
for a stylised aggregate economy made up of agricultural and manufacturing sectors
we confirm substantial bias in the technology coefficients and thus any total factor
productivity measures computed. Our empirical findings imply that sectoral structure
is of crucial importance in the analysis of growth and development, thus
strengthening the recent revival of research on structural change in development
economics.
