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By using Data Envelopment Analysis approach, we treat the health production system in a certain province as a Decision Making Unit (DMU), identify its inputs and outputs, evaluate its technical efficiency in 1982, 1990 and 2000 respectively, and further analyze the relationship between efficiency scores and social-environmental variables. This paper has found several interesting findings. Firstly, provinces on frontier in different year are different, but provinces far from the frontier keep unchanged. The average efficiency of health production has made a significant progress from 1982 to 2000. Secondly, all provinces in China can be divided into six categories in terms of health production outcome and efficiency, and each category has specific approach of improving health production efficiency. Thirdly, significant differences in health production efficiencies have been found among the eastern, middle and western regions in China, and among the eastern and middle regions. At last, there is significant positive relationship between population density and health production efficiency but negative relationship (not very significant) between the proportions of public health expenditure in total expense and efficiency. Maybe it is the result of inappropriate tendency of public expenditure. The relationship between abilities to pay for health care services and efficiency in urban areas is opposite to that in rural areas. One possible reason is the totally different income and public services treatments between rural and urban residents. Therefore, it is necessary to adjust health policies and service provisions which are specifically designed to different population groups.

This paper is dedicated to probing into the dynamic performances of industrial productivity across regions of transitional China, using the panel data of provincial level. Based on the approach by Kumbhakar (2000), TFP (total factor productivity) growth is decomposed into four components. The main results are as follows. First, since 1988, the industrial TFP growth has been commonly accelerated across regions, with a rising technical change rate as the principal impetus. Second, meanwhile, technical efficiency and factors’ allocative efficiency are deteriorated with scale efficiency switching from being retrogressive to being progressive. Third, although the SOE (state-owned enterprise) reform in the late 1990s has constituted a common shock to the industrial productivity, the eastern area with relatively few SOEs suffers the least from this policy enforcement. Fourth, by exploring the sources of productivity differences, we further confirm that the institutional shock launched by SOE reform in the late 1990s is crucial for the enhancement of scale effects as well as the temporarily rapid decline of factors’ allocative efficiency; in addition, the educational level of the labor-force and the share of non-SOEs in the industrial output contribute positively to the acceleration of technical change and the improvement of allocative efficiency. The economic transition, accompanied by gradual institutional reforms, is reshaping the map of regional industrialization through various channels.

This study estimates and analyzes provincial productivity growth in China for the period 1979–2001. The Malmquist Index approach allows us to decompose productivity growth into two components, technological progress and efficiency change. Considerable productivity growth was found for most of the data period, but it was accomplished mainly through technological progress rather than efficiency improvement. Although China's capital stock has accumulated at record speed in recent years, our findings show that TFP growth slowed down significantly during 1995–2001. The study thus raises serious questions about whether China's recent growth pattern is consistent with its comparative advantages, and whether its reliance on capital accumulation can be sustained in the long run.

The paper investigates the relationships between technological regimes and firm-level productivity performance, and it explores how such a relationship differs in different Schumpeterian patterns of innovation. The analysis makes use of a rich dataset containing data on innovation and other economic characteristics of a large representative sample of Norwegian firms in manufacturing and service industries for the period 1998-2004. First, we decompose TFP growth into technical progress and efficiency changes by means of data envelopment analysis. We then estimate an empirical model that relates these two productivity components to the characteristics of technological regimes and a set of other firm-specific factors. The results indicate that: (1) TFP growth has mainly been achieved through technical progress, while technical efficiency has on average decreased; (2) the characteristics of technological regimes are important determinants of firm-level productivity growth, but their impacts on technical progress are different from the effects on efficiency change; (3) the estimated model works differently in the two Schumpeterian regimes. Technical progress has been more dynamic in Schumpeter Mark II industries, while efficiency change has been more important in Schumpeter Mark I markets.

China’s unorthodox approach to economic transition has resulted in sustained high growth. However, in recent years Chinese economists have increasingly referred to the growth pattern as “extensive”, generated mainly through the expansion of inputs. Our investigation of the Chinese economy during the reform period finds that reform measures often resulted in one-time level effects on TFP. China now needs to adjust its reform program towards sustained increases in productivity. Market and ownership reforms, and open door policies have improved the situation under which Chinese firms operate, but further institutional reforms are required to consolidate China’s move to a modern market economy.

This study estimates and analyzes provincial productivity growth in China for the period of 1979-2001. The Malmquist Index approach used in the study allows us to decompose productivity growth into two mutually exclusive and exhaustive components, technical progress and efficiency change. Considerable productivity growth was found for most of the data period, but it was accomplished mainly through technical progress rather than through efficiency improvement. In comparison with the period of 1979-1995, although China’s capital stock has been accumulated at the speed of a historical record in recent years, our findings show that TFP growth has slowed significantly during 1995-2001. The study thus raises a number of serious questions on whether China’s recent growth pattern is consistent with its comparative advantages, and whether its reliance on capital accumulation can be sustained in the long run.

In spite of rapid economic growth and swift structural change during the last two decades, China's industrial reform is far from complete, especially with regard to state enterprises (SOEs). Although troubled with huge financial losses, heavy debt, and substantial over-staffing, SOEs will continue to play a crucial part in the government policy to maintain social stability and economic growth in China. This study, based on samples of about 700 state enterprises during 1980-94, investigates productivity performance of the SOEs using Data Envelopment Analysis and Malmquist Index. Our empirical results show that average technical efficiency had been low among the sample SOEs. Considerable productivity growth was found, but it was mainly accomplished through technical progress rather than efficiency improvement. Regression analyses indicate that wage incentives and education had positive impacts on productivity growth, while large scale was an important determinant of whether an SOE was applying best practice technology. It is also shown that large SOEs were more likely to generate technical progress. These findings are consistent with the industrial structural adjustment program initiated by the government in 1994, which has focused on improving productive efficiency via redundancies and technology upgrading, and on building its best SOEs into conglomerates

Differences in cross-country economic performance have been attributed to differences in the quantity and quality of capital and labour stocks over time and space and cross- country differences in the productivity of these factors. Furthermore, institutional infrastructures have been considered deep determinants of the allocation and productivity of the factors of production. Despite the persistently low economic performance of middle- and low-income economies, there is a paucity of research into the dynamics of the relationship between institutions, productivity and economic performance in middle- and low-income economies. There is much research on these relationships among advanced and OECD economies, but no clear perspective of the dynamics of these relationships in middle- and low-income economies. This thesis extends the discussion of the relationship between institutions as deep determinants, productivity and the factors of production and their influence on long-run economic performance in middle- and low-income economies.\ud \ud This thesis takes a positivist-deductivist approach. A representative sample of 17 developing economies for which relevant data is publicly available is used to test for the fixed and random effect of institutions and productivity on long-run economic performance. Using growth-accounting, this thesis decomposes aggregate output to calculate national levels of productivity, measured as TFP . Then using factor analysis, publicly available data is used to calculate an aggregate institutional index and four institutional factors. Using fixed and random effects models, this thesis tests for the influence of the aggregate institutional index and four institutional factors on levels of TFP capital and labour stock.\ud \ud There is evidence that in the long run, levels of TFP drive how efficiently and intensely the factors of input are converted in the production process in the sample of 17 developing economies. The results suggest that cross-country differences in economic performance amongst these developing economies may be due to differences in TFP. Further that in the long run, institutions indirectly affect economic performance in these 17 developing economies through their direct influence on levels of TFP. Levels of TFP are directly influenced by the quality of national institutions, thereby impacting the efficiency and intensity of converting labour and capital stocks in the production process.