Measuring regional competitiveness through agricultural indices of productivity. The Peruvian case
| Pages | 78-95 |
| DOI | https://doi.org/10.1108/WJEMSD-06-2016-0031 |
| Date | 08 May 2017 |
| Published date | 08 May 2017 |
| Author | Francisco Coronado,Vincent Charles,Rocky J. Dwyer |
| Subject Matter | Strategy,Business ethics,Sustainability |
Measuring regional
competitiveness through
agricultural indices
of productivity
The Peruvian case
Francisco Coronado, Vincent Charles and Rocky J. Dwyer
CENTRUM Católica Graduate Business School, PUCP, Lima, Peru
Abstract
Purpose –The purpose of this paper is to incorporate factors that characterize the agricultural activity
as productivity indices to compute the agricultural competitiveness of regions in order to rank the regions,
and compare the results with those obtained by applying other commonly used social and economic
indicators.
Design/methodology/approach –The authors identify regional factors related to the use of water, soil,
production, revenues, and rural population, which conform a total of six productivity indices, that the authors
then employ to calculate the regional agricultural competitiveness index.
Findings –The agricultural-related indices are informative in supporting the regional ranking related to
resources and technology utilization. The results reveal that the coastal regions are the most competitive
when compared to the regions located in the highlands and the jungle. Nevertheless, in contrast with other
existing competitiveness rankings, the present study identifies the regions with the greatest potential for
agriculture.
Research limitations/implications –The authors identify the regions which have a higher potential
of development considering the natural resources and agricultural production. The authors hope that this
paper can assist regional and national policymakers in their endeavor to improve regional and national
competitiveness.
Practical implications –The authors identify the regions with a higher potential of development
considering natural resources and agricultural production and the possibili ties to improve their
competitiveness.
Social implications –The study also bears social implications, given that the rural activities in Peru are
carried out by approx. 7 million inhabitants, whose contribution to the gross domestic product (GDP) is as
much as 7 percent, making use of about 94 percent of the available water.
Originality/value –The originality of the present paper resides in the attempt to compute a regional
competitiveness index by taking agricultural resources as determinant factors. The authors rank the regions
based on their agricultural competitiveness.
Keywords Productivity, Competitiveness index, Economic growth, Regional competitiveness
Paper type Research paper
Introduction
With today’s increased globalization of the world economy, coupled with the rising income
inequality, the social and political turmoil, low trade, and low growth, among others,
competitiveness has become ubiquitous. But what exactly is competitiveness and in what sense
can one talk about regional competitiveness? Although the term competitiveness is rather clear
when applied to firms –being a measure of the degree in which firms can compete with other
firms –it is more difficult to define and measure when applied to regions and countries.
Despite this, the concept of competitiveness of regions within a country bears similarities
World Journal of
Entrepreneurship, Management
and Sustainable Development
Vol. 13 No. 2, 2017
pp. 78-95
© Emerald PublishingLimited
2042-5961
DOI 10.1108/WJEMSD-06-2016-0031
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2042-5961.htm
The authors wish to express their gratitude to the Editor-in-Chief and the three anonymous
reviewers, whose comments and suggestions have helped us to substantially improve the
paper.
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WJEMSD
13,2
with the concept of competitiveness of countries. In this sense, the existing literature on
competitiveness of countries may be applicable to the competitiveness of regions within a
country, as well (Budd and Hirmis, 2004; Camagni, 2002; Gardiner et al., 2004; Malecki, 2002).
Briefly stated, the concept of regional competitiveness, although widely studied, has no
single accepted framework or definitions, nor strong agreement on its measurement,
being an often-debated issue (Békés, 2015). A more accepted view is that regional
competitiveness has to do with the degree (and success) with which regions compete with
one another over shares of national and global export markets (Gardiner et al., 2004),
being viewed as a derivation of the macroeconomic competitiveness, defined at national
level (Békés, 2015).
Enhancing competitiveness, both at the national and regional levels, is a popular target
in economic policy-making, given its connectedness with economic growth and societal
progress. The competitiveness of regions can be computed based on the application of
indices of technology, economic environment, business development, innovative capacity,
physical infrastructure, facilities, capital markets, competition, trade and monetary policies,
the pool of skilled labor, and education and health, among others. Other aspects, also, such
as the level of education, production services, and communication channels, are considered
in the current measurements of competitiveness.
Nevertheless, despite its relevance to the different facets of the economic analysis, the
empirical measurement of competitiveness faces certain constraints which arise from the
very lack of a unique definition of the concept and the insufficiency of disaggregated
indicators that adequately capture the wide range of factors relevant to competitiveness
(Crespo Rodriguez et al., 2011). As such, the existing enhancers of the economic efficiency do
not show the factors which are directly related to the agricultural activity and, therefore,
they miss to consider the activities which may exist in vast areas of the country. In this
sense, for example, few indicators are available to assess, monitor, and evaluate changes in
the quality of land resources (Pieri et al., 1995).
We address this gap by proposing productivity indices that reflect the rural activities
and apply them to the case of Peru. As such, the purpose of the present paper is to
incorporate factors that characterize the agricultural activity as productivity indices to
compute the agricultural competitiveness of regions in order to rank the regions of Peru, and
compare the results with those obtained by applying other commonly used social and
economic indices.
Such endeavors would bear substantial implications for practice, given that the rural
activities in Peru are carried out by approx. 7 million inhabitants, whose contribution to the
gross domestic product (GDP) is as much as 7 percent, making use of about 94 percent of the
available water, a resource that is a matter of concern due to the recent climatic changes.
In this sense, we also aim to identify the potential for improvement in the agricultural
activity, which should be of interest in guiding management decisions for investments at the
regional and country level, which will further lead to the improvement of competitiveness in
each region and, ultimately, in the entire country. We hope to be able to advance the
knowledge on the topic.
The remainder of the paper is organized as follows: the next section develops the topic of
regional competitiveness, highlighting the most important aspects of its definition and
measurement. This is then followed by the methodology section, wherein we introduce
the indices of agricultural productivity. Further, we briefly describe the situation of the
natural resources and the agriculture sector in Peru, data based on which we proceed to
calculate the proposed indices, followed by the computation of the regional agricultural
competitiveness index (ACI). The following sections describe the findings of the study and
compare the results (ranking) with those reported by other existing studies. The last section
concludes the paper, with additional insights regarding policy implications.
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Agricultural
indices of
productivity
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