Markups, Returns to Scale, and Productivity: A Case Study of Singapore's Manufacturing Sector
The results of this paper challenge the conventional wisdom in the literature that productivity plays no role in the economic development of Singapore. Properly accounting for market power and returns to scale technology, the estimated average prod...
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| Language: | English en_US |
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World Bank, Washington, D.C.
2013
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| Online Access: | http://documents.worldbank.org/curated/en/2002/06/1943367/markups-returns-scale-productivity-case-study-singapores-manufacturing-sector http://hdl.handle.net/10986/14284 |
| Summary: | The results of this paper challenge the
conventional wisdom in the literature that productivity
plays no role in the economic development of Singapore.
Properly accounting for market power and returns to scale
technology, the estimated average productivity growth is
twice as large as the conventional total factor productivity
(TFP) measures. Using a standard growth accounting
(production function) technique, Young (1992, 1995) found no
sign of TFP growth in the aggregate economy and the
manufacturing sector of Singapore. Based on Young's
results, Krugman (1994) claimed that there was no East Asia
miracle as all the economic growth in Singapore could be
attributed to its capital accumulation in the past three
decades. Citing evidence on nondiminishing market rates of
return to capital investment in Singapore during the period
of fast growth as an indication of high productivity growth,
Hsieh (1999) challenged Young's findings using the dual
approach. But all of these papers maintained the assumptions
of perfect competition and constant returns to scale and
used only aggregate macro-level data. Kee uses industry
level data and focuses on Singapore's manufacturing
sector. She develops an empirical methodology to estimate
industry productivity growth in the presence of market power
and nonconstant returns to scale. The estimation of industry
markups and returns to scale in this paper combines both the
production function (primal) and the cost function (dual)
approaches while controlling for input endogeneity and
selection bias. The results of a fixed effect panel
regression show that all industries in the manufacturing
sector violate at least one of the two assumptions. Relaxing
the assumptions leads to an estimated productivity growth
that is on average twice as large as the conventional TFP
calculation. Kee concludes that productivity growth plays a
nontrivial role in the manufacturing sector. |
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