Template-Type: ReDIF-Article 1.0
Author-Name: Beatriz Benítez-Aurioles
Title:  DESCOMPOSICIÓN SECTORIAL DE LA CONVERGENCIA β EN LAS PRODUCTIVIDADES DE LAS PROVINCIAS ESPAÑOLAS
Abstract: Resumen:
Este trabajo cuantifica la contribución de cada sector a la convergencia entre las
productividades del trabajo a nivel provincial en España. La metodología se
basa en el análisis shift-share
distinguiendo dos periodos de análisis: 2000-2008 y 2008-2017. Los resultados
demuestran que, durante el primer periodo, la Agricultura y la Administración
pública y otros servicios lideraron la convergencia  incondicional. En
el segundo periodo se atenuó dicha convergencia y fueron Agricultura, Otras industrias
y Construcción los sectores que impulsaron
el proceso. La Industria manufacturera,
en cambio, tuvo un comportamiento que favoreció la divergencia, especialmente
durante el primer periodo. Por otro
lado, los flujos de empleo hacia sectores relativamente más productivos promovieron
la convergencia de las productividades provinciales en un grado relativamente menor,
en el primer periodo, y sin significación estadística en el segundo.
 Abstract:
There is enough
empirical evidence to suggest the absolute and conditional convergence of
income and productivity of Spanish provinces as a stylized fact. Nonetheless,
we have found no study referring to Spanish provinces that, after confirming
the β-convergence, attempts
to determine the sectorial contribution to said convergence and the role played
by structural changes in employment. In this sense, this work does not only
verify the existence of β-convergence in provincial productivities, but also tries to
answer two additional questions: which has been the contribution of each sector
to convergence or divergence? And, which role has been played by structural
changes in employment?
            The employed methodology has as a
reference the shift-share analysis,
which basically consists on decomposing the growth rate of a variable. In our
case, the increment in aggregate productivity is formed by the sum of three
effects: growth, which measures the
contribution of each sector to total productivity growth; change, which quantifies the contribution that job relocations
across sectors have on total productivity growth; and interaction, which shows the covariance of the two former effects.
This methodology allows the direct estimation of the contribution of each
sector to aggregate convergence, thereby overcoming the limitations of analysis
centered on convergence within sectors. Indeed, although a sector might not
exhibit a trend towards the convergence of productivity between different
territorial units, it could be contributing to aggregate convergence by
transferring resources (jobs) to more productive sectors. Thus, the proposed
methodology allows the evaluation of the contribution of each sector by telling
apart that which comes from productivity growth from that which can be
attributed to changes in employment across all productive sectors.
            The statistical information comes
from Spanish Regional Accounts published by the INE and, more concretely, from
the homogeneous series by provinces. On that basis, an analysis has been
performed differentiating the 2000-2008 period, where sustained GDP growth was
registered, from the 2008-2017 period, when the expansionary trend was halted.
Productivity has been calculated as the quotient of the added value and total
employment. The total sectorial division used corresponds to the following
aggregates: Agriculture; Manufacturing industry; Other industries; Construction; Commerce and tourism; Financial activities and professionals; Public administration and other services.
Firstly, it is
shown that aggregate productivity grew in all provinces in the two different
periods although, between 2008 and 2017, growth is lower in all cases—except in
Castellón. Furthermore, the data shows that the growth effect is that which
almost completely justifies the growth in productivity; while both the change effect and the interaction effect have, as a general
rule, much smaller values.
Regarding the change effect, it is interesting to note
that, while in the first period it is only negative in Teruel, forty of the
fifty provinces display this sign in the second. In other words, between 2000
and 2008, the sectors that initially had above-average productivity increased
their participation in provincial employment; and, conversely, the opposite
occurred between 2008 and 2017 since precisely the sectors with the highest
relative productivity were generally the ones that lost weight in total
provincial employment.
For its part, the interaction effect presents negative
values in most provinces in both periods, although much more clearly in the
second—which indicates that the sectors that increased their productivity more
than the average decreased their participation in employment. This is
compatible with the fact that productivity gains have been produced thanks to
job losses. In fact, there is an inverse relationship between productivity
growth and employment growth at the sectoral level, albeit with varying
intensity by period.
Once the
contribution of each sector to the growth effect by provinces has been
quantified, we can see that the manufacturing
industries explain, approximately, a fourth of the productivity growth.
This role is shared with the Public
Administration and other services between 2000 and 2008,
and with Commerce and Tourism since
2008. It is also worth mentioning that, in both periods, the Other industries sector decreased its
productivity in many provinces.
Another remarkable
fact is that, between 2000 and 2008, all the provinces' production structures
approached the national average. However, between 2008 and 2017 there were no
significant changes in provincial employment structures compared to that
average.
On the other hand,
the analysis performed confirms that, between 2000 and 2008, there has been a β-convergence between the provincial
productivities—that is, that provinces starting from lower levels have grown
relatively more than those with higher values ​​at the beginning of the period.
On the other hand, between 2008 and 2017 the results are not so evident. This
reality supports the thesis that expansionary periods, unlike recessive
periods, promote convergence. This finding, although not trivial, simply
reinforces the results of previous research referring to other periods.
However, the identification of the sectors that have contributed to this
convergence is novel. Specifically, during the first period, the sectors that
contributed the most to convergence were Agriculture
and Public Administration and other
services, although with different dynamics. While in Agriculture there is a loss of employment in most provinces—and
consequently, also at an aggregate level— there was a general increase in
employment in the Public Administration
and other services. The transformations in Agriculture can be framed within a more general process of
structural change in the context of the European Union. In this sense, evidence
is found that emigration, motivated to a certain extent by mechanization,
together with the greater capabilities of workers remaining in the sector,
explain the labor productivity growth in Agriculture
over time and its convergence among European regions. Public administration and other services present a peculiar dynamic
as most of their production is not destined for the market. In these
circumstances, economic logic loses relevance with respect to political
decisions oriented to public service provision.
In the second
period, besides Agriculture, Other industries and Construction were the sectors that
contributed statistically significantly to aggregate convergence, although on a
much smaller scale.
Conversely, the
behavior of the manufacturing industry—which
had the greatest loss of employment among all the sectors considered—favored
the divergence of productivities at the provincial level, especially during the
expansionary period. This evidence questions the theory on the spatial
homogenization of productive processes supposedly induced by the mobility of
factors or by technological imitation. In this context, the contribution of the
manufacturing industry sector to the
divergence between provincial productivities is a sign of the role that the
agglomerations of companies that make up local production systems may be
playing. In particular, the conformation of industrial districts and
clusters—on which academic interest has been renewed in recent years—can
generate different dynamics depending on the context in which they evolve.
Thus, the geographical concentration of companies and industrial activities
would be justified by the presence of agglomeration economies—that is, positive
intra-industrial (localization economies) and inter-industrial (urbanization
economies) externalities that offer a set of different development possibilities.
Therefore, the existence of specific factors associated with concrete spatial
environments that persist over time should be acknowledged. Consequently,
divergent productive trajectories could arise at the territorial level in
certain industries; and, particularly, as the results of our analysis suggest,
in the manufacturing industry in
Spain. Therefore, the relevance of alternative hypotheses that incorporate,
among other variables, market rigidities, the presence of agglomeration
economies, the different endowments of public / private capital, or the various
training levels of the labor force. On this basis, opportunities appear for the
design of economic policy measures that foster the spatial convergence of
productivities and, more generally, of income.
Furthermore, it is
shown that employment flows towards relatively more productive sectors
contributed to the convergence of provincial productivities between 2000 and
2008, but not between 2008 and 2017.
Finally, we
acknowledge the limitations of this work and the sensitivity of its results to
both the time references and sectoral aggregation used—which, on the other
hand, are restrictions that we have assumed in the absence of more specific
data. In any case, despite the significant volume of contributions on
convergence, our work has progressed along a road unexplored until now, in
identifying the sectors that are contributing to aggregate productivity
convergence at the provincial level.
Apart from what is
stated in this article, it is convenient to make cleara more general
argument of special importance. The analytical tools that we have used are
based on a sectoral and provincial breakdown of the productivities, and do not
allow to know the implications of the economic evolution on people's well-being.
Although labor productivity is directly related to wages from a conventional
perspective, it is not possible to determine the ultimate consequences on
personal income from the sectoral breakdown of its growth. However, the
knowledge of the contribution of each sector to the spatial convergence of
productivities provides hints that help determine the consequences that
economic policies (oriented, for example, to the maintenance or promotion of
industrial companies in specific territories) have on income growth or
distribution.
Classification-JEL: R1
Keywords: Β Convergencia, Índice de Productividad de Malmquist., Análisis shift-share, Provincias Españolas, Β Convergence, Apparent Productivity of Employment, Shit-Share, Spanish Provinces
Pages: 197-233
Volume: 1
Year: 2022
File-URL: http://www.revistaestudiosregionales.com/documentos/articulos/pdf-articulo-2629.pdf
File-Format: Application/pdf
Handle: RePEc:rer:articu:v:1:y:2022:p:197-233