martes, 15 de julio de 2008

Innovation and Development around the World 1960-2000

Innovation and Development around the World, 1960-2000
Daniel Lederman
Laura Saenz
Office of the Chief Economist
Latin America and the Caribbean
The World Bank
Abstract
This paper presents a database of indicators of innovative activity around the world since
the early 1960s. The data include measures of innovation outcomes as well as variables
related to innovation effort. The main indicator of innovation outputs is patents. The main
variables related to innovation inputs are investment in research and development (R&D)
and technical personnel (engineers, scientists) working in R&D activities. The sources of
these data are publicly available (OECD, UNESCO, etc.), yet there have been few
attempts at double checking the consistency of these data and digitizing observations
dating back to the 1960s. After discussing the sources and definitions of the data, the
paper examines trends and patterns of innovation outputs and inputs by looking at the
over-time behavior of the relevant series and comparing the performance of developing
and high-income countries. The authors also provide cross-regional comparisons and a
detailed examination of trends in selected countries. In turn, the authors provide estimates
of the impact of innovation on long-run development by following an emerging empirical
literature on the determinants of levels of GDP per capita. The econometric results
suggest that innovation might indeed have strong positive effects on long-run
development, which might be stronger than the direct effects of institutions. The analysis
pays close attention to issues related to the potential endogeneity of innovation (and
institutions) with respect to the level of development.
World Bank Policy Research Working Paper 3774, November 2005
The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of
ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are
less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings,
interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily
represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research
Working Papers are available online at http://econ.worldbank.org.
I am grateful to Laura Saenz for her dedicated research assistance. She patiently constructed the database
from original and computerized sources. I am also grateful to William F. Maloney for his guidance and
invaluable suggestions. José L. Guasch, Lauritz Holms-Nielsen, Guillermo Perry, Andrés Rodríguez-Clare,
and Luis Servén provided helpful discussions and comments at various stages.
WPS3774
Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized
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Innovation and Development around the World, 1960-2000
Daniel Lederman with Laura Saenz
LCRCE
World Bank
I. Introduction
The role of technological progress has intrigued economists for many decades if not centuries. In
Solow’s (1956) neo-classical treatment of the components of economic growth all countries face
a common rate of technological progress. Thus poor countries were thought to be able to
catchup to the levels of development in rich countries as a consequence of diminishing returns to
capital accumulation. Romer (1990) and many other proponents of modern growth theory
subsequently argued that the rate of technological progress is endogenous. Aghion and Howitt
(1998) is perhaps the most comprehensive review of endogenous growth theories that focus on
how growth and innovation interact, including how institutions and incentives affect the scope
and pace of technological innovation across countries.
Endogenous growth theories quickly led to a growing empirical literature aiming to
understand the factors that affect the rate of long-term economic growth across countries (Barro
1991; Caselli et al. 1996; many others). This literature argues that the neo-classical paradigm is
still valid. These authors arrived at this conclusion by pointing out that poor countries tend to
growth faster towards their steady-state level of income, which in turn is determined by a series
of policy-related factors such as financial development, education, and openness to international
trade.
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In the late 1990s, Klenow and Rodríguez-Clare (1997) pointed out that growth
accounting exercises that ignore the complementarity between technological progress and capital
accumulation tend to underestimate the role of technological progress in development. Likewise,
Acemoglu and Zilliboti (2001) highlighted the role of complementarities between human capital
and technological progress. It is now well understood that long-term development is driven
mostly by productivity growth, or the portion of growth that is unrelated to capital accumulation
(Easterly and Levine 2001). These theories and empirical evidence suggest that economic
convergence or catch-up by poor countries toward the levels of income per capita observed in
developed economies is not guaranteed. Growth seems to depend crucially on factors that
determine the rate of technological progress that might be country specific as opposed to
common to all countries. In spite of this, there are few studies of the impact of innovation on
long-run national development. Lederman and Maloney (2003) provide estimates of the social
rates of return to research and development (R&D) based on data presented in this paper.
The race to identify the main drivers of endogenous growth through cross-country growth
regressions has recently been the subject of much criticism (e.g., Solow 2001). In part, the
criticism of this literature has been driven by the fact that these studies tend to focus on a rather
long list of correlated explanatory variables. Moreover, the econometric techniques used for
these analyses have grown in sophistication but still seem to be unconvincing to readers who
believe that many of the explanatory variables are endogenous or not strictly related to policy
interventions (Rodrik 2003). This growing skepticism of cross-country growth regressions seems
to have led to an emerging empirical literature that attempts to explain the level of development
(GDP per capita), rather than its growth rates. Hall and Jones (1998), Frankel and Romer (1999),
Acemoglu et al. (2001) and a series of subsequent papers (Easterly and Levine 2003, Rodrik et
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al. 2002) are notable examples of analyses of the determinants of levels of development. These
analyses can be further justified by theories that propose mechanisms through which the stocks
of capital (human, equipment, and knowledge capital) affect only the steady-state level of
income, rather than the growth rate (Howitt and Mayer 2002; Klenow and Rodriguez-Clare
2004). The main empirical challenge of this emerging literature seems to be the identification of
the impact of the exogenous portion of various factors, including the quality of public institutions
(rule of law, corruption, etc.) and international trade (Acemoglu et al. 2001; Frankel and Romer
1999), on the level of GDP per capita. There is no existing study of the impact of innovation on
long-run development along the lines proposed by this literature.
This vacuum in the development literature is striking because indicators of innovation
output, such as patents, have been used as a measure of technological innovation output for quite
some time. For example, the review article by Grilliches (1990) highlighted some advantages
and disadvantages of the use of patent counts as indicators of innovation, and reviewed microeconometric
literature pointing to the role of R&D and patenting activity as correlates of
productivity growth across firms in the U.S. and other industrialized countries (see also Jaffe and
Trajtenberg 2002). The rest of this paper is organized as follows: Section II presents the
database. Section III provides a descriptive analysis of worldwide trends in innovative activity,
by looking at inter-regional and intra-regional trends. Section IV explains the findings of
empirical exercises to measure the impact of innovation on growth vis a vis other variables, such
as institutions. Section V presents some conclusions and suggestions for other uses of this
database.
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