Evolution of structural indicators: China and its regions 1981-2010
| Published date | 30 September 2013 |
| Pages | 100-118 |
| DOI | https://doi.org/10.1108/JCEFTS-04-2013-0010 |
| Date | 30 September 2013 |
| Author | J.M. Albala-Bertrand |
| Subject Matter | Economics,International economics |
Evolution of structural indicators:
China and its regions 1981-2010
J.M. Albala-Bertrand
Queen Mary, University of London, London, UK
Abstract
Purpose – This paper deals with some structural indicators and their evolution, in China and its
regions, over the period 1981-2010.
Design/methodology/approach – The paper uses a quantitative approach. Linear programming
and structural growth decompositions were used. The authors first produce estimates of the optimal
productivities of incremental capital and the optimal incremental income elasticity of capital by means
of a linear programming exercise. They then produce an accounting growth decomposition to assess
the changes in the contribution of capital productivity, capital intensity and labour participation to the
growth rate of output per capita. Finally, they combine an accounting growth decomposition with a
standard production function, growth accounting, decomposition to assess the contribution of both
capital productivity and capital intensity to total factor productivity (TFP). They also show in the
Appendix the difference in the TFP growth contribution when marginal elasticities are assumed
variable over time and when scale returns are assumed to be increasing rather than constant.
Findings – The main conclusion of the paper is that capital intensity, rather than capital productivity
or labour participation, has been the main growth contributor. Capital productivity has fallen, while
capital intensity has increased significantly, but that does not mean that quantity in itself, rather than
quality, is behind such growth, as total factor productivity, which is significantly more than
engineering technical change, has been relatively important over the period.
Originality/value – Both the use of linear programming to assess the evolution of incremental
capital productivity and the decomposition of TFP.
Keywords Incremental capital productivity,Structural change, TFP/growthdecomposition
Paper type Research paper
1. Introduction
There has been a good deal of macroeconomic studies about China’s productivity and
related issues. These are normally framed in standard production functions, especially
the Cobb-Douglas, under the assumption of constant returns to scale (CRS) and
often, implicitly or otherwise, assuming perfect competition with their theoretically
convenient marginal conditions. CRS is often imposed in econometrics studies or
directly used to calculate the elasticities via the actual capital and labour shares in GDP
from official statistics (Jefferson et al., 2008; W ang and Yao, 2003; Young, 2000; Chow,
1993b; Hu and Khan, 1997). In turn, the income elasticities of capital and labour are
assumed constant over all the target period, which may be unlikely, as shown by Holz
(2006). This means that the results necessarily carry a baggage of assumpti ons that may
not tally with the reality of especially a latecomer and fast growing country undergoing
significant structural change (Thirwall, 2011; DeLong, 2008; Zheng et al., 2008; H olz,
2006).
Associated with it, a good number of papers deal with the generation of capital stock
series for China, normally via a PIM from an initial benchmark capital stock, which is
estimated in various, more or less elaborated, ways (Albala-Bertrand and Hao, 2007;
Chow, 1993a, b; Wang and Yao, 2003; Li and Tang, 2003), but also from more detailed
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1754-4408.htm
Received 3 April 2013
Revised 31 May 2013
Accepted 6 June 2013
Journal of Chinese Economic and
Foreign Trade Studies
Vol. 6 No. 3, 2013
pp. 100-118
qEmerald Group Publishing Limited
1754-4408
DOI 10.1108/JCEFTS-04-2013-0010
JCEFTS
6,3
100
estimations based upon the characteristics of the country and the meaning of variables
(Holz, 2006). The former has however become standard among practitioners and
institutions because of its simplicity and comparability over time and across countries
(OECD, 2001; Hofman, 2000b). Again, these series incorporate additional assumptions
about capital idleness, depreciation, quality, and the like. There is however little ways to
improve such series, as idleness is extremely difficult to assess, so is normally either
assumed away or some convenient overall rate is used to discount it. In turn, the rate of
capital depreciation is normally a conventional rate that you can live with (Woo, 1998;
Wang and Fan, 2000; Young, 2000). And lastly the productive quality of capital is too
heterogeneous and variable to be assessed directly, so it is implicitly estimated via
aggregate national and/or regional output results.
The present paper attempts an aggregate contribution that is more founded on
empirical patterns than theoretical assumptions and may complement alternative
approaches. This is a quantitative paper that deals with structural indicators tha t are
mostly based on definitional accounting, rather than functional, relationships. The point
is to produce useful decompositions of growth rates by means of discrete first differences
and from there observe compositional contributions to the national and regional actual
growth rates as well as to total factor productivity (TFP). The paper structure is as
follows. We first produce estimates of the optimal productivities of incremental capital
for the post-economic reform, encapsulated in the 30-year period 1981-2010, for the
country and key regions, by means of a linear programming (LP) exercise. This
approach may reduce the difficulty of assessing idleness, as capital formation is related
to optimal output directly (Albala-Bertrand, 2010)[1]. In addition, a value for the optimal
incremental income elasticity of capital can be derived from it, which can give an idea
about the level and variability of the marginal elasticity used in standard production
functions under CRS. We next produce a definitional accounting growth decompositions
via first differences to assess the changes in the contributions of capital productivity,
capital intensity and labour participation to the growth rate of output per capita over the
said period. We then combine a definitional accounting decomposition with a standard
growth accounting decomposition of a production function to assess both the
contribution of both capital productivity and capital intensity to TFP growth (G
TFP
).
Finally, in the Appendix, we show how different the TFP contribution can be when
using variable elasticities over time and when using increasing rather than CRS.
As a general conclusion, we show that the growth contribution of capital
productivity has been becoming significantly negative, and that of labour participation
meagre or negative, while capital intensity has taken the bulk of supporting both GDP
growth and TFP. This does not necessarily mean that GDP growth has relied on the
quantity rather than the quality of resources and production, as capital intensity itself
has also been the main contributor to TFP, behind which are changes in human capital,
organization, adaptations, technical efficiency and the like. So it has not just been the
hardware of physical capital, but the important changes in economic and social
software required to use it and absorb it, that are behind the high growth rates.
2. Estimation procedures
We use two estimation methods for our presentation below. One for the optimal
incremental productivity of capital and one for the capital stock benchmark and derived
series.
Evolution
of structural
indicators
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