Paul Johnson, Steven Durlauf and Jonathan Temple 1165
Pritchett (2000a) has listed three questions for growth researchers to address:
- What are the conditions that initiate an acceleration of growth or the conditions
that set off sustained decline?
- What happens to growth when policies – trade, macroeconomic, investment –
or politics change dramatically in episodes of reform?
- Why have some countries absorbed and overcome shocks with little impact on
growth, while others seem to have been overwhelmed by adverse shocks?
Although this research agenda is almost ten years old, it retains considerable
relevance, not least because it focuses attention on substantive economic issues
rather than technicalities. The importance of the first of Pritchett’s questions is
evident from the many instances where countries have moved from stagnation to
growth and vice versa. Hausmann, Pritchett and Rodrik (2005) explicitly model
transitions to fast growth (“accelerations”) and make clear the scope for informa-
tive work of this kind. The second question we have discussed in section 24.5.3,
and research in this vein is increasingly prominent. Here, one of the major chal-
lenges will be to relax the (sometimes only implicit) assumption that policies are
randomly assigned, and to find ways of carrying out inference that are robust in
small samples. The third question has been addressed in an important paper by
Rodrik (1999).
In all three cases, it is clear that econometric work should be informed by detailed
studies of individual countries, such as those collected in Rodrik (2003). Too much
empirical growth research proceeds without enough attention to the historical and
institutional context. For example, a newcomer to this literature might be surprised
at the paucity of work that integrates growth regression findings with, say, the
known consequences of the 1980s debt crisis. Another reason for advocating case
studies is that much of the empirical growth literature essentially isolates only
reduced-form partial correlations. These can be useful, but it is clear that we often
need to move beyond this. A partial correlation is more persuasive if it can be
supported by theoretical arguments. The two combined are more persuasive if there
is evidence of the intermediating effects or mechanisms that are emphasized in the
relevant theory. There is plenty of scope for informative work that tries to isolate the
mechanisms by which variables such as financial depth, inequality, and political
institutions shape the growth process. Wacziarg (2002), in particular, highlights the
need for a “structural” growth econometrics, one that aims to recover channels of
causation.
A more extreme view is that growth econometrics should be supplanted by the
calibration of theoretical models. Klenow and Rodriguez-Clare (1997) emphasize
the potential of such an approach. The analysis of Mankiwet al.(1992) can be
seen partly as a comparison of estimated parameter values with those associated
with specific theoretical models, but relatively little of the empirical work that
has followed has achieved a similarly close connection between theory and evi-
dence. This has been a recurring criticism of the literature since at least Levine and
