1146 The Methods of Growth Econometrics
but weaker evidence for causality in the more conventional direction from invest-
ment to growth. In a similar vein, Campos and Nugent (2002) find that, once
Granger causality tests are applied, the evidence that political instability affects
growth may be weaker than usually believed.
A familiar objection to the more ambitious interpretations of Granger causal-
ity is that much economic behavior is forward-looking (see, for example, Bils
and Klenow, 2000, on the forward-looking nature of educational investments).
The movements of stock markets are another obvious instance where temporal
sequences can be misleading about causality. Nevertheless, it could be argued
that evidence on timing has been under-utilized in the growth literature to date,
especially in panel data studies.
An underlying assumption of most studies is that timing patterns and effects will
be similar across units such as countries or regions. Potential heterogeneity has
only sometimes been acknowledged, as in the observation of Campos and Nugent
(2002) that their results are heavily influenced by the African countries in the
sample. The potential importance of these factors is also established in Binder and
Brock (2004) who, by using panel methods to allow for heterogeneity in country-
specific dynamics, find feedbacks from investment to growth beyond those that
appear in Blomstromet al.(1996).
Since testing for Granger causality using panel data requires a dynamic model,
the use of a standard fixed effects estimator is likely to be inappropriate when
individual effects are present. We discuss this further in section 24.5.2. In the
context of investment and growth, a comprehensive examination of the associated
econometric issues has been carried out by Bond, Leblebicioglu and Schiantarelli
(2004). Their work shows that these issues are more than technicalities: unlike
Blomstromet al.(1996), they find strong evidence that investment has a causal
effect on growth.
24.5.2 Panel data
As we emphasized above, the prospects for reliable generalizations in empirical
growth research are often constrained by the limited number of countries avail-
able. This constraint makes parameter estimates imprecise, and limits the extent
to which researchers can apply more sophisticated methods, such as semiparamet-
ric estimators. A natural response to this constraint is to use the within-country
variation to multiply the number of observations. Using different episodes within
the same country is ultimately the only practical substitute for somehow increasing
the number of countries. To the extent that important variables change over time,
this appears the most promising way to sidestep many of the problems that face
growth researchers. Moreover, as the years pass and more data become available,
the prospects for informative work of this kind can only improve.
We first discuss the implementation and advantages of panel data estimators
in more detail, and then some of the technical issues that arise in the context
of growth. We will useTto denote the number of time series observations in
a panel ofNcountries or regions. At first sight,Tshould be relatively high in
this context, because of the availability of annual data. But the concerns about