1264 Spatial Analysis of Economic Convergence
technology diffusion. Indeed, take as a point of departure a static Cobb–Douglas
production function given by:
Q=A 0 exp(λt)KαEβ, (27.11)in whichA 0 is the level of technology at time 0,λis the growth of total factor
productivity or exogenous technical change,Q,KandEare the levels of output,
capital, and employment at timet;αandβare elasticities. Fingleton (2000) assumes
that the technical progress made by firms as a result of the growth of capital per
worker (p) is not fully internalized but spills over to benefit other firms and indi-
viduals. Two forms of technology spillovers are envisaged: one occurs as a result of
intraregional technical change and one occurs as a result of extraregional technical
change in neighboring regions:
λ=λ∗+φp+κWp. (27.12)λin one region is then proportional topin the same region and, through the
matrix productWp, is also a function of capital accumulation occurring within
the neighbors for each region, as specified byW. Taking equation (27.11) in logs,
differentiating with respect to time and assuming that capital stock growth and
output growth are approximately the same,^4 he shows that the reduced equation
can be written as:
p=ρWp+b 0 +b 1 q+Xb+ε, (27.13)whereXcontains other determinants of labor productivity growth, such as the
initial level of technology gap between each region and the leading technology
region, and measures of peripherality and urbanization. In subsequent papers,
Fingleton (2001a, 2001b) shows that the spatial lag version of Verdoorn’s law is,
in fact, also consistent with assumptions that underpin new economic geogra-
phy with, as a starting point, a Cobb–Douglas production function for the level
of output produced by manufacturers that depends on the input of manufactur-
ing labor efficiency units, on composite intermediate services and on the input of
land. Increasing returns are modeled via the product variety theory emphasized by
Dixit and Stiglitz (1977) and the rate of technical progress is assumed to be as in
equation (27.11).
27.3 Exploratory spatial data analysis of convergence
While a great deal of work has been done on confirmatory econometric analysis
of growth and convergence, a number of criticisms have been pointed at the rel-
atively restrictive nature of the underlying theoretical frameworks, their inability
to account for empirical regularities in growth datasets and the general problem of
using cross-section regressions to explain time-averaged growth rates with which
to make inferences about growth dynamics (Quah, 1993b). In response to some of
the criticisms, a number of researchers have adopted novel methods of exploratory