Growth and Productivity in Singapore Manufacturing Industries: 1975-1998

Koh, Soo-Wei; Rahman, Shafiqur; Tan, G. K. Randolph

doi:10.1111/1467-8381.t01-1-00151

Cited by 9 publications

(6 citation statements)

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“…This paper extends previous empirical studies (e.g. Kee, 2002;Koh et al, 2002;Mahadevan, 2000;Mahadevan and Kalirajan, 2000;MAS, 1998;Ramirez and Tan, 2003) that focus primarily on either the manufacturing or the services sector. I provide an estimate of how the markups have changed over the last 2 decades during which Singapore witnessed remarkable economic growth.…”

Section: Introductionsupporting

confidence: 80%

Markup Variation and Productivity Measurement in Singapore*

Lam

2006

Asian Economic Journal

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Conventional measures of total factor productivity using growth accounting may not be appropriate when there is variation in markups across industries. The existence of market power implies that total factor productivity contains an endogenous component related to the variation in markups. I examine the variation of markups at the industry level for the manufacturing and services sectors in Singapore from 1983 to 2003. Using two different measures, I find that the markups in Singapore are significant in most industries, at around 28 and 55 percent for the manufacturing and services sectors, respectively. Markups for the services sector declined during the period, while the markups for the key manufacturing industries increased after the Asian financial crisis in 1997. Accounting for variation in markups suggests that improvement in technological progress tends to be underestimated by 0.5-1.0 percent per year. The underestimation is more severe in industries with relatively high markups.

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Section: Introductionsupporting

confidence: 80%

Markup Variation and Productivity Measurement in Singapore*

Lam

2006

Asian Economic Journal

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“…The industry group classification used in this section follows from the set of industry group definitions employed in the Report on the Census of Industrial Production (CIP) 4 prevailing in 1998. Details of the data construction process are contained in Koh et al (2002). The following table displays summary statistics of the value shares and the logged values of the input and output variables as they enter into our chosen model (2).…”

Section: Data Constructionmentioning

confidence: 94%

“…The logarithmic values of real output and input quantities are given. Values computed from the data, details of which are provided byKoh et al (2002).…”

mentioning

confidence: 86%

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Stochastic Frontier Analysis of Singapore Manufacturing Industries

Koh

Rahman

Tan

2004

Singapore Econ. Rev.

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Previous papers on Singapore manufacturing productivity have focused almost exclusively on total factor productivity (TFP) growth rates and ignored the problem of measuring the extent of learningby-doing. In this paper, we examine an alternative measure: the rate of technical efficiency change. Using data from 1974-1998, a translog production frontier is estimated. Following a conceptual framework popularised by Bauer (1990), productivity growth is decomposed into components arising from technical progress, technical efficiency change, a scale economies effect and an allocative inefficiency effect.

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“…Studies on decomposition of Singapore's economic growth, such as Tsao (1982), Young (1992;, Rao and Lee (1995), Koh, Rahman and Tan (2002) and Hsieh (2002), have all pointed to the overwhelming importance of capital accumulation in propelling the growth of Singapore, and the smaller degree of contribution made by TFP growth. In addition, some of the earlier studies, such as those by Tsao (1982) and Young (1992;, concluded that Singapore's TFP growth rates were negligible.…”

Section: Capital Growth and Total Factor Productivity Growth Of Singamentioning

confidence: 99%

Economic growth and transition : econometric analysis of Lim's S-curve hypothesis

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Professor Lim Chong Yah's S-Curve hypothesis is a simple yet highly insightful theory. By augmenting the mathematical and econometrical sophistication of the hypothesis, this thesis extends the S-Curve hypothesis to provide further insights into economic growth and transition. The four core chapters in this thesis are closely related yet distinctly different, each dealing with a separate aspect of the S-Curve hypothesis. Chapter 2 constructs a stochastic growth model that provides the microeconomic foundation for the S-Curve hypothesis. The model is based on the technological diffusion model by Barro and Sala-I-Martin (1997) with two significant extensions: the (productivity) parameter in the model which represents social infrastructure is being endogenized and probability of adverse shocks is being incorporated into the productivity parameter. The stochastic technological diffusion model is able to explain the various transition points outlined in the S-Curve hypothesis. The model is also able to explain why some developing economies experience economic takeoff while others do not. This model highlights the importance of lowering the cost of technological absorption in enhancing growth rates of developing countries, and lowering the cost of innovation in achieving technological leadership. This model also highlights the importance of good governance in economic development and identifies negative shocks to governance as the main cause of slow growth of the poor developing countries.

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Growth and Productivity in Singapore Manufacturing Industries: 1975-1998

Cited by 9 publications

References 0 publications

Markup Variation and Productivity Measurement in Singapore*

Markup Variation and Productivity Measurement in Singapore*

Stochastic Frontier Analysis of Singapore Manufacturing Industries

Economic growth and transition : econometric analysis of Lim's S-curve hypothesis

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