Average Total Factor Productivity Growth Research Articles

How R&D Expenditures Influence Total Factor Productivity and Technical Efficiency?

In this paper we estimate the impact of R&D expenditures on the total factor productivity (TFP) and technical efficiency of two panels of countries in the period 1990-2011. We obtain TFP decomposition estimates using one- and two-step Stochastic Frontier Analysis (SFA) and a modified (O’Donnell, 2008) Data Envelopment Analysis (DEA) framework. Our estimates of TFP growth rates correlate highly with those of OECD, The Conference Board and PWT. The efficiency-based rankings of the countries are similar to those from the results of other studies. The estimates of R&D’s impact on TFP and technical efficiency were obtained controlling for various factors, including the structure of the economy, institutional and infrastructural development and R&D expenditures over a total of five hundred possible model specifications. We found that the increase in total R&D expenditures by 1% of GDP in five years raises the average TFP growth rate by 5.0 to 7.7 percentage points, depending on the sample. Also, raising total R&D expenditures by $1,000 per researcher raises TFP growth five years later by 0.013 to 0.025 percentage points, depending on the sample. Also we have identified a significant impact of lagged R&D expenditures (up to ten years) on the dynamics of the global technology frontier component in the presence of a number of control variables.

The determinants of productivity in Chinese large and medium-sized industrial firms, 1998–2007

Using a large firm-level dataset, this paper examines total factor productivity (TFP) and its determinants in China. Our preferred GMM estimation results indicate increasing returns to scale in most industries and a usually large positive trend representing technical change. Various firm characteristics such as age, ownership, political affiliation, export behavior, liquidity, and geographic location are included in the production function. Our results show that in the context of China’s institutional background, including such factors is important when estimating TFP. The average TFP growth in Chinese industries is 9.6 % per annum during the period 1998–2007, and is mainly driven by firm entry. The sub-sector decomposition exercises show that the inter-firm resource reallocations are more prominent across industries than across provinces.

Estimating and decomposing productivity growth of the electricity generation industry in Malaysia: A stochastic frontier analysis

This study examines the total factor productivity (TFP) growth of the Malaysian electricity generation industry over the 1998 to 2005 period. The stochastic frontier analysis (SFA) approach is used to measure TFP change and decompose TFP growth into efficiency change and technical progress. We find that it achieved average annual TFP growth of 2.34%, with technical change contributing the most to the TFP growth over the eight year period. We hence hypothesise that the new power plants with their newer capital-embodied technologies commencing during the sample period are likely to be the main reason for this strong technical change. In addition, it is also noted that this estimate for the Malaysian electricity generation industry is larger than the estimate obtained for the electricity sector as a whole, where we obtain 1.34% per year for a comparable period.

Does Freer Trade Really Lead to Productivity Growth? Evidence from Africa

Theory predicts that trade liberalization should raise average total factor productivity (TFP) among manufacturing firms. However, this is a generic prediction and depends on maintained assumptions about industries, factor markets, and trade patterns that may not fit well for developing countries. Using firm-level data from Ghana, Kenya, and Tanzania during the 1990s, a period of fairly rapid trade policy liberalization, we estimate productivity effects of trade. Our analysis confirms the well-known association between export intensity and higher productivity of the firm; however, the evidence for “learning by exporting,” or an increase in productivity associated with greater exports, is mixed, with several instances of negative average TFP growth among exporters. Our analysis indicates that such declines are likely attributable to the effects of lower external tariffs, because the firm-level productivity margin below which exporting is unprofitable moves down as the external tariff rate is reduced. We also find that sales to the rest of the world and sales to other African economies have differential effects on productivity growth rates, and that for country-specific reasons, these effects are not uniform. Controlling for initial productivity and the destination of exports (within or outside Africa) helps us understand why in some cases, export participation is associated with negative rates of TFP growth.

Analysis on DEA-Malmquist efficiency index of medical facilities in Zhejiang province

Objective To measure the changes of total factor productivity (TFP)of Zhejiang medical facilities for decision makers to promote their service efficiency.Methods Collecting the panel data of 2005-2010(four input indexes and five output indexes)from medical facilities in Zhejiang province and measuring with Malmquist index of DEA programs of DEAP2.1.Results The average annual TFP growth rate in the period is 2.0％.A further decomposition found that the average annual growth rate of technology progress is 1.8 ％,while that of technical efficiency and pure technical efficiency is only 0.2％respectively.In the meantime,no scale efficiency growth was found.Conclusion The average annual growth of total factor productivity of Zhejiang medical institutions is substantially low in the period,with technology recession found as well.To maximize productivity of the medical sector,the allocation and internal management should be strengthened to stimulate technical efficiency and scale efficiency while encouraging technology innovation. Key words: Total factor productivity; Malmquist index; Data envelopment analysis; Medical facility

ON THE DETERMINANTS OF TOTAL FACTOR PRODUCTIVITY GROWTH: EVIDENCE FROM SPANISH MANUFACTURING FIRMS

This paper explores the main determinants of productivity growth. The analysis is performed using Spanish firm-level data. We define a framework where the relative magnitudes of alternative, but not exclusive, sources of technical change are simultaneously estimated. Our main finding is that the average total factor productivity (TFP) growth is fully explained by embodied technical progress (i.e., either new capital goods or human capital). Our results contradict the existence of a positive contribution of economywide neutral technological progress in determining average TFP growth. They also leave little room for large, unpriced effects external to the firm, both at the aggregate and at the industry level. We find evidence of firm-specific learning by doing, short-lived and due to adoption of new processes.

Distinction between Informal and Unorganized Sector: A Study of Total Factor Productivity Growth for Manufacturing Sector in India

Since its very onset, the concept and definition of the informal sector has been a subject of debate both at the national and international levels. Existing literature uses the terms ‘informal sector’ and ‘unorganized sector’ interchangeably. However, in India, the characteristics of enterprises in the informal and non-informal unorganized manufacturing sectors are different and, thus, it is not justifiable to consider the informal and unorganized sector interchangeably for the manufacturing sector. Thus, the objective of this paper is to test the hypothesis on whether or not the total factor productivity growth (TFPG) of the informal manufacturing sector is different from the non-informal unorganized manufacturing sector. TFPG is decomposed into technical efficiency change and technological change. Later, technical efficiency change is further decomposed by pure efficiency change and scale efficiency change. Results show that the average TFPG of the non-informal sector is higher than the informal sector. The informal sector heavily concentrates in own account small enterprises, whereas the non-informal unorganized sector concentrates only in directory manufacturing enterprises (DME). Due to large in size, DME avails the advantages of economies of scale, which, in turn, helps the units for more growth in terms of total factor productivity growth. The main reason for productivity decrease of the enterprises, besides technology regress and the lack of adequate investments, is the limitation of activities and scale along with the optimal allocation of resources. This study provides a basis on how policies can be designed for enhancing the total factor productivity growth of the informal sector.

Productivity Growth in German Dairy Farming using a Flexible Modelling Approach

AbstractA random‐coefficients specification of an output distance function is used to measure and decompose productivity growth in German dairy farming. This specification can accommodate heterogeneity with respect to the technology employed by dairy farms, allowing for specialised and non‐specialised farms to be included in the analysis. The proposed modelling approach is favoured by the data when compared with the conventional translog specification of distance functions. The average total factor productivity growth rate for German dairy farms is estimated at 1.1%, with the technical progress component contributing most of this growth.

Efficiency evolution of coal‐fired electricity generation in China, 1999‐2007

PurposeThe paper seeks to evaluate the changes in efficiency and productivity of coal‐fired electricity generation of 30 Chinese administrative regions from 1999 to 2007.Design/methodology/approachThe paper incorporates data envelopment analysis with the Malmquist index to study the progress made in this sector. The model considers both economic and environmental factors by including the variables fuel consumption, labor, capital, sulfur dioxide emissions and electricity generated. A second model is constructed without the variable sulfur dioxide emissions to evaluate economic performances without taking environmental measures into consideration.FindingsBy comparing the two models, the paper identified provinces that favored economic performance over environmental performance, or vice versa. Also, it showed that the more efficient provinces tend to manage both economic and environmental efficiencies equally well, while the reverse is true for the least efficient provinces. The average total factor productivity growth in coal‐fired electricity generation of all provinces was 3.96 per cent for 1999‐2007, and this growth is mainly attributed to technological change. In addition, it found that the Eastern provinces are the most efficient and productive of the group.Research limitations/implicationsIn the absence of provincial coal quality data, a key efficiency factor is missing from the analysis.Practical implicationsEfficiency improvement efforts in the Chinese generation sector should target the least efficient provinces identified in this paper. Practices in the most efficient provinces should be further investigated to be replicated when possible.Originality/valueThe paper provides a contemporary overview of Chinese provincial efficiency and productivity measures for policy makers and investors to improve China's coal‐fired electricity generation sector.

Estimation of total factor productivity in the Indian garment industry

PurposeThe Indian garment industry has witnessed a significant change since the inception of the New Textile Policy 2000 that suggests removing the industry from the list of small‐scale industries with a view to improving its competitiveness in the global market. As productivity is the driving factor in enhancing the competitiveness of any decision‐making entity (firm), a study of total factor productivity (TFP) and its sources can provide vital inputs to a firm for improving its competitiveness. Keeping this as a backdrop, the paper attempts to measure the TFP in the Indian garment‐manufacturing firms; identify sources of the TFP; and suggest measures for the firms to enhance their productivity.Design/methodology/approachThe study is based on the firm‐level panel data collected from the Centre for Monitoring Indian Economy for the years 2002‐2007. One output variable, namely, gross sale and four input variables, namely, net fixed assets, wages & salaries, raw material, and energy & fuel, have been selected. The DEA‐based Malmquist Productivity Index (MPI) approach has been applied to measure the TFP.FindingsThe Indian garment industry has achieved a moderate average TFP growth rate of 1.7 per cent per annum during the study period. The small‐scale firms are found to be more productive than the medium‐ and large‐scale firms. The decomposition of TFP growth into technical efficiency change (catch‐up effect) and technological change (frontier shift) reveals that the productivity growth is contributed largely by technical efficiency change rather than by technological change.Originality/valueEarlier studies on the Indian garment industry have applied the partial factor productivity approach, which has several limitations. This paper measures the TFP and identifies its sources through applying a non‐parametric DEA‐based MPI approach. Through this approach, the productivity growth is decomposed into technical efficiency change and technological change. Further, an attempt has also been made to study the variation in the productivity growth rates across location, scale‐size and type of garments.

Global Trends of Productivity Growth: Evidence from the Malmquist Index

This paper examines the trend of productivity growth in OECD countries by applying the Malmquist index. Our findings indicate that total factor productivity (TFP) growth in OECD countries was much more sluggish in the 1990s than in the 1980s. The nature of productivity growth also differed between the two decades. During the 1980s, a wave of innovation in production technology is found to have improved productivity in most countries considerably, but at the same time widened the efficiency gap between a small group of technically efficient economies and other nations. However, we find that most countries managed to narrow their gap with technically efficient economies over the following decade although they experienced technological regress during that time. The trend of slow productivity growth continued well into the post¡ⓒ2000 period with the average TFP growth for our sample countries actually being negative over 2001¡ⓒ2006. We note that this deterioration in productivity was largely driven by technological regress while the trend of efficiency convergence prevalent in the 1990s all but disappeared during the period.

Technical Change and Total Factor Productivity Growth for Chinese Provinces: A Panel Data Analysis

We present in this paper the panel econometrics estimation approach of measuring the technical change and total factor productivity (TFP) growth of 30 Chinese provinces during the period of 1993 to 2003. The random effects model with heteroscedastic variances has been used for the estimation of the translog production functions. Two alternative formulations of technical change measured by the single time trend and the general index approach are used. Based on the measures of technical change, estimates of TFP growth could be obtained and its determinants were examined using regression analysis. The parametric TFP growth measure is compared with the non-parametric Solow residual. TFP has recorded positive growth for all provinces during the sample period. Regional breakdown shows that the eastern and central regions have higher average TFP growth when compared with the western region. Foreign direct investment (FDI) and information and communication technology (ICT) investment are found to be significant factors contributing to the TFP difference. While these two factors are found to have significant influence on TFP, their influence on production is relatively small compared to traditional inputs of production.

Total Factor Productivity Growth in the Philippines: 1960−2000

Average total factor productivity growth (TFPG) for the Philippine economy is negative, indicating that it has not been the source of growth in the Philippines. However, TFPG estimates showed an increasing trend in the 1990s when major economic reforms were implemented. The educational level of the labor force has improved consistently since the 1960s. However, based on the decomposition analysis the paper finds that its contribution to TFPG has declined.

Market Imperfection and Productivity Growth—Alternative Estimates for Taiwan

This study first explores why the shares of factor inputs have not been measured correctly and concludes that the earlier findings are biased due to the miscalculation of factor shares which have produced low estimated total factor productivity (TFP) growth in the East Asian countries. Second, three approaches are proposed to empirically illustrate the impact of capital and labor shares on the estimates of TFP growth. It is suggested that TFP growth in the East Asian economies will be understated if net indirect taxes and imperfect competition profit are ignored. Finally, by taking the net indirect taxes and imperfect competition profits into account, the result of this paper indicates that Taiwan's economy has enjoyed an average annual TFP growth rate of 3.6% over the period 1980–1999.

The Effect of Incentive Reforms Upon Productivity: Evidence from the Vietnamese Rice Industry

In this study we use region-level panel data on rice production in Vietnam to investigate total factor productivity (TFP) growth in the period since reunification in 1975. Two significant reforms were introduced during this period, one in 1981 allowing farmers to keep part of their produce, and another in 1987 providing improved land tenure. We measure TFP growth using two modified forms of the standard Malmquist data envelopment analysis (DEA) method, which we have named the Three-year-window (TYW) and the Full Cumulative (FC) methods. We have developed these methods to deal with degrees of freedom limitations. Our empirical results indicate strong average TFP growth of between 3.3 and 3.5 per cent per annum, with the fastest growth observed in the period following the first reform. Our results support the assertion that incentive related issues have played a large role in the decline and subsequent resurgence of Vietnamese agriculture.

APEC and the Asian Economic Crisis: Early Signals from Productivity Trends

This paper provides empirical estimates of total factor productivity (TFP) trends in a sample of 17 APEC countries over the period 1975 to 1996. TFP growth is an important measure of an economy's performance and if measured correctly it can provide valuable guidance on issues related to the assessment of sustainable growth trends. We use the Malmquist index to measure TFP growth and decompose it into an efficiency change and a technical change component. This decomposition provides extra insight on assessing sustainable growth trends. The measurement technique itself is regarded as a significant improvement over previous conventional measures of TFP growth. The results are very interesting. Japan, Thailand and primarily Indonesia and Malaysia are identified as countries exhibiting on average negative TFP growth rates in the 1975‐1990 period. In all these countries as well as in South Korea and Taiwan the main cause of low TFP growth is a poor (negative) efficiency record. The average TFP growth rate for Japan and Malaysia is positive in the 1975‐1996 period but the efficiency change component remains negative. In all these countries the main contributor to labour productivity growth is capital accumulation. Unlike previous studies we find no evidence of a poor TFP growth performance for Singapore. Furthermore, we estimate that most of Singapore's labour productivity growth is driven by efficiency change. Estimates of rates of convergence towards the frontier economy that is estimated (not assumed as in other studies) to be the US, are also reported.

An Application of the Extended Glass and McKillop Procedure for Computing TFP Growth to the Malaysian Rice Sector

The objective of the present study is three-fold: to employ an aggregated data to investigate the total factor productivity (TFP) growth of the Malaysian rice sector; to investigate the sources of the TFP growth; and, to examine and extend the Glass and McKillop procedure for computing TFP growth. To this end, we establish several procedures which make it possible for us to: (i) link the TFP analysis with the theory of production; (ii) disentangle the sources of TFP growth into scale and technological change effects; and (iii) apply, compute, examine and extend the Glass and McKillop procedure for computing TFP growth.The finding of the study is as follows. (i) Using the standard procedure forcomputing TFP growth it was found that the average TFP growth for Malaysian rice farming was 1.37%, of which the scale effect contributed 0.29% and the remaining 1.08% was due to the technological change effect. (ii) Using the extended Glass and McKillop procedure, however, it was found that the average TFP growth, the technological change effect and the scale effect were 3.48%, 3.19% and 0.29%, respectively. (iii) Comparing these two results, derived from two different procedures, we concluded that the difference in magnitude of the TFP growth was due to the two distinct procedures for computing the technological change effect per se.