1164 The Methods of Growth Econometrics
One approach is pursued by Conley and Ligon (2002). In their analysis, they
attempt to construct estimates of the spatial covariation of the residualsεiin a cross-
section. In order to do this, they construct different measures of socioeconomic
distance between countries. They separately consider geographic distance (mea-
sured between capital cities) and measures of the costs of transportation between
these cities. Once a distance metric is constructed, these are used to construct a
residual covariance matrix. Estimation methods for this procedure are developed
in Conley (1999). Conley and Ligon (2002) find that allowing for cross-section
dependence in this way is relatively unimportant in terms of appropriate calcu-
lation of standard errors for growth model parameters. Their methods could be
extended to allow for comparisons of different variables as the source for cross-
section correlation, as in Conley and Topa (2002) in the context of residential
neighborhoods. A valuable generalization of this work would be the modeling
of cross-section dependence as a function of multiple variables. Such an analysis
would allow further progress on the measurement of distances in socioeconomic
space, which may arise through multiple channels.
An alternative approach is to build spillover effects directly into the structure of
an empirical model. Easterly and Levine (1997) is an example of a study which
incorporates a direct effect of the growth of neighboring countries, but such
examples remain rare. Some of the relevant issues have been highlighted in the
theoretical literature on social interactions, inspired by empirical problems such
as the measurement of peer effects in schools. While a structural approach has
advantages, the presence of spillovers has consequences for identification that
are not easily resolved, for the reasons explained in Manski (1993) and subse-
quently discussed in Brock and Durlauf (2001b). These consequences have yet to
be fully explored in the context of empirical growth studies. Binder and Pesaran
(2001) and Brock and Durlauf (2001b) analyze identification and estimation prob-
lems for intertemporal environments that are particularly relevant to the growth
context.
24.8 Conclusions: the future of growth econometrics
In this section, we offer some closing thoughts on the most promising directions
for empirical growth research. We explicitly draw on previous contributions along
these lines, many of which deserve wider currency. It is especially interesting to
compare the current state of the field against the verdicts offered in the early survey
by Levine and Renelt (1991).
A dominant theme will be that the empirical study of growth requires an eclectic
approach, and that the field has been harmed by a tendency for research areas to
evolve independently, without enough interaction.^27 This is not simply a question
of using a variety of statistical techniques. It also suggests the need for a closer
connection between theory and evidence, a willingness to draw on ideas from
areas such as trade theory, and more attention to particular features of the countries
under study, including the historical context.