Negative Total Factor Productivity Growth Research Articles

Technical Efficiency and Total Factor Productivity Growth of Indonesian Manufacturing Industry: Does Openness Matter?

In this paper, we examine the contribution of openness variables such as import, export, absorptive capacity and foreign-shared capital to Indonesian firms’ technical efficiency and total factor productivity (TFP) growth. We use the most recent firm-level panel data of 23 subsectors in the manufacturing industry over the period from 2008 to 2015. We employ time-varying stochastic production frontier to examine factors affecting technical efficiency and to decompose the components of TFP growth. The results reveal that export and absorptive capacity alone contribute to the efficiency improvement of the firms under study. To speak specifically of foreign firms, they contribute to improving efficiency if they interact with absorptive capacity and imported raw material intensity. We identify that, on an average, the manufacturing industry in Indonesia experienced positive TFP growth. However, among 23 subsectors, there are only few subsectors that benefitted from the openness variables. In 2014, 15 out of 23 subsectors experienced negative TFP growth. This implies that, in 2014, there were some macroeconomic issues regarding the contracted policy, for example, the subsidy removal and the basic electricity tariff. JEL Classifications: C23, D24, F23, O14

Total factor productivity change in Indonesia’s provincial economies for 1990–2015: Malmquist productivity index approach

This study employs the Malmquist productivity index based on data envelopment analysis to measure and decompose total factor productivity (TFP) change into efficiency and technological change by province. Using annual observations of gross regional domestic product and factor inputs (labor, physical, and human capital) for 26 contiguous provinces, we find that over a quarter of them experienced negative TFP growth over 1990–2015 due to technological regress, which was barely offset by efficiency improvements. Three on-Java provinces—Jakarta, West Java, and East Java—contributed to national technological progress with full utilization and optimal allocation of resources at least once over the study period, except during 1995–2005, when Indonesia experienced a financial crisis and subsequent slow recoveries. Jakarta and West Java contributed in all other periods. Considering the high spatial density of urban economic activities in these three provinces, we conclude that urban agglomeration is influential for further regional technological growth in Indonesia.

Assessing Total Factor Productivity for Soybean Production in China Based on DEA-Malmquist Index: 2005-2017

The low and slowly increasing soybean yield restricts the development of soybean production. Accurate measures of total factor productivity (TFP) for soybean production can be helpful in identifying conditions, institutions or policies that promote soybean production development in China. In this paper, TFP growth for soybean production was estimated for a panel data of 10 major soybean producing provinces from 2005 to 2017. Results reveal that TFP grew at an average rate of 1.3% over the whole period, with technical progress contributing 2.3% and efficiency change providing the other -1.0%. The change of TFP for soybean production over that time, whether increase or decline, was mainly derived by technical change except in three years (2005-2007). Positive TFP growth in the provinces of Liaoning and Inner Mongolia, and negative TFP growth in Hebei and Anhui were mainly driven by efficiency change, specifically scale efficiency change except pure technical efficiency in Liaoning.

Productivity Analysis of Coal-fired Thermal Power Plants in India Using Malmquist Index Approach

The sustainable socio-economic growth of any country depends on the availability of adequate and reliable power at reasonable rates. This is even true in case of a rapidly developing country like India where coal-based power plants account for the majority of electricity generation. Making use of data envelopment analysis (DEA) and Malmquist productivity index (MPI), this study analyses the productivity change of coal-fired power plants during 2002–2012. Productivity change is further decomposed into technical efficiency change (EFFCH), technological change (TECHCH), scale efficiency change (SECH), pure technical change (PECH) and total factor productivity change (TFPCH). The study revealed that 0.70 per cent of average annual total factor productivity (TFP) growth was witnessed from 2002–2003 to 2011–2012 indicating overall progress. The contribution of TECHCH in TFP growth is positive, that is, 1.3 per cent per annum. It demonstrates that expansion of the efficient frontier. However, there was a decrease in technical EFFCH of −0.6 per cent per year, indicating the adverse sign of progress. Plants in the central sector achieved maximum growth of 4.6 per cent annually. A total of 54.05 per cent of plants have recorded negative TFP growth. Power plants between 500 and 999 MW achieved the highest operational performances in all indices except SECH.

A bootstrapped Malmquist index applied to Swedish district courts

This study measures the total factor productivity (TFP) of the Swedish district courts by applying data envelopment analysis to calculate the Malmquist productivity index (MPI) of 48 Swedish district courts from 2012 to 2015. In contrast to the limited international literature on court productivity, this study uses a fully decomposed MPI. A bootstrapping approach is further applied to compute confidence intervals for each decomposed factor of TFP. The findings show a 1.7% average decline of TFP, annually. However, a substantial variation between years can be observed in the number of statistically significant courts below and above unity. The averages of the components show that the negative impact is mainly driven by negative technical change. Large variations are also observed over time where the small courts have the largest volatility. Two recommendations are: (1) that district courts with negative TFP growth could learn from those with positive TFP growth; and (2) that the back-up labour force could be developed to enhance flexibility.

Causes and Consequences of Deindustrialization in the Euro Area

The post-industrial stage of development reached in developed countries is characterized by an increase in services' share and the progressive decline of the manufacturing share in their economies. The intensification of deindustrialization process heated up the discussion pertaining to its impact on the weakening of investment, technological progress, innovation, and a decline in labour productivity and GDP growth. The aim of the paper is to present the scale and consequences of deindustrialization in the euro area based on analysis of manufacturing and other sectors shares in the gross value added and employment in the euro area. The indicators used for the assessment of deindustrialization consequences are: labour productivity and total factor productivity (TFP) growth rates. As the outcome of conducted analysis, the author has drawn two main conclusions: 1) the decreasing importance of manufacturing limits the possibility of carrying out research projects and creating technological progress, 2) the negative TFP growth rate, declining of labour productivity growth rate in 2008-2015 and the decrease of GDP testifies to the threat of secular stagnation in the euro area.

A Comparative Analysis of Productivity among Organic and Non-Organic farms in the West Mamprusi District of Ghana

The study was conducted in organic and conventional crop farms in the West Mamprusi District of the Northern Region of Ghana. The key issue the study sought to determine was whether there are productivity differences among organic and conventional crop farms and what factors account for these differences. The results indeed revealed that there are productivity differences among organic and conventional crop farms. However, both had negative total factor productivity growth, largely accounted for by a negative technical change over the period considered. The technical efficiency change, however, was positive for both but much higher for organic farms than conventional farms. More importantly, the study revealed that the type of agriculture practiced by farmers is not the most critical problem confronting farmers as indicated by the negative total productivity growth for both. Major constraints confronting farmers that need to be addressed include better organization on the farmers’ front, improved access to extension and improved access to farm inputs. These challenges notwithstanding, the study revealed that organic agriculture has the potential, in the long run, to achieve much more progress in total factor productivity, compared to conventional agriculture, if the right conditions exist for its uptake and optimal application.

Economic Reforms and Sources of Productivity Growth in Selected Organised Manufacturing Labour Intensive and Capital Intensive Industries in India - A Comparative Study

This study uses the non parametric data envelopment technique to investigate the impact of economic reforms on Total Factor Productivity Growth in Selected 20 Indian Organised Manufacturing Industries by classifying them into Labour Intensive and Capital Intensive industries; by using non parametric DEA technique to four-digit panel data for the period 1990 to 2011. The study reveals that the Labour Intensive Industries have negative Total Factor Productivity Growth as -6.1% deteriorated mainly due to Technological Change which is -4%. Meanwhile, the Capital Intensive Industries have positive Total Factor Productivity Growth of 6.7%, mainly contributed by Efficiency Change of 1.6% and Technological Change of 5.0%. Eight out of ten Organised Manufacturing Capital Intensive Industries have shown positive Total Factor Productivity Growth during the economic reform period, whereas seven out of ten Organised Manufacturing Labour Intensive Industries showed negative Total Factor Productivity Growth due to lack of technological change.

Efficiency and productivity in the Thai non-life insurance industry

This paper estimates a stochastic cost frontier for a sample of the non-life insurance industry in Thailand from 2000 to 2007. Our model explicitly considers the heteroscedasticity in the variances of the noise and inefficiency components that could affect the position of the cost frontier as well as the measurement of efficiency. Tests for double heteroscedasticity and appropriate specification for the cost frontier are performed. The chosen model is used to examine whether economies of scale and a change in technology exist. In addition, this paper calculates total factor productivity (TFP) change and decomposes it into scale effect, cost efficiency effect, technology effect, output effect, price effect, and environmental effect. Our results reveal that, on average, Thai non-life insurance firms are between 74 and 79 % efficient, that economies of scale exist, and that regress in technology shifts the cost frontier upward by 2.2 %. The regress in technology is the dominant contributor to a negative TFP growth of 1.15 %. The restructuring of the industry following the 1997 Asian financial crisis finally paid off when the industry experienced technology progress in 2005 and beyond. Between 2005 and 2007, technology progress and productivity growth occurred at a little over 2 % a year. In-depth analysis of the most and the least efficient firms reveals that most efficient firms tend to strategically select types of insurance services and underwrite average and small size sum insured per policy to diversify their risks. In addition, they tend to be savvy investors. The opposite holds for the least efficient firms which concentrate in providing labor-intensive, small sum automobile insurance policies or underwrite large coverage policies for fewer policyholders. Balancing the mix of insurance types, spreading risk across insurance types or across number of policyholders, investing in high yield assets, or developing a market niche may prove beneficial for improving cost efficiency.

The Analysis of Productivity Growth of Tuber Crops in Nigeria (1995-2006)

This study analyzed the productivity of Tuber crops in Nigeria from twenty states between the periods of 1995 -2006 using Data Envelopment Analysis (DEA) to estimate the total factor productivity (TFP) which was further decomposed to reveal the source of productivity growth over the reference period. Negative TFP growth was observed for all the tuber crops considered in the study on the average but an evidence of convergence in productivity level was observed when considering the starting TFP, majority of the states had low TFP (<0.6) but grew over the years by about 0.2 with Kaduna and Adamawa having the highest TFP for cocoyam and cassava respectively.

ON THE EVOLUTION OF TOTAL FACTOR PRODUCTIVITY IN LATIN AMERICA

Because of several policy distortions, including import‐substitution industrialization, widespread government intervention, and both domestic and international competitive barriers, there has been a general presumption that Latin America has been much less productive than the leading economies in the last decades. In this paper we show, however, that until the late 1970s Latin American countries had high productivity levels relative to the United States. It is only after the late 1970s that we observe a fast decrease of relative total factor productivity (TFP) in Latin America. We also show that the inclusion of human capital in the production function makes a crucial difference in the TFP calculations for Latin America. (JEL O11, O47, O54)

The Rise and Fall of German Productivity Software Investment as the Decisive Driver

Investments in Information and Communication Technology (ICT) are the source of the global growth resurgence that commenced in the mid-1990s. Most studies focus on broad ICT measures, or on computer hardware; here we examine the contributions of software-intensive industries to productivity growth. The price of prepackaged software has been falling exponentially since the 1960s, which has led to substitutions towards software investments, and to reductions in the total cost of ICT hardware investments. We use novel German ICT investment data to show that software-intensive industries have been the crucial determinant of German productivity growth since 1995. Not only did these industries contribute strongly to productivity growth, but they offset declining investments and productivities in other industries. Post 1995, other industries’ investments in new equipment per worker collapsed, while software-intensive industries’ capital investments rose steadily to generate over half of Germany's productivity growth by 2000–04. We document sharply diverging productivity paths for software-intensive and other (non-software-intensive) industries. Post 1991, total factor productivity (TFP) declined secularly in other industries to generate a −0.39 percent drag on German labor productivity by 2000–04, while TFP in software-intensive industries rose steadily to contribute 35 percent to German labor productivity growth by the same period. Overall, the results combine to paint a stark picture of rising capital per worker and TFP growth in software-intensive sectors, contrasting with falling capital per worker and increasingly negative TFP growth in other sectors. About two-thirds of the impact from software-intensive industries is generated by investments in prepackaged and purchased custom software. (JEL codes: O03, O04)

Sources of the German Productivity Demise: Tracing the Effects of Industry-Level Information and Communication Technology Investment

AbstractWhile the United States experienced two successive labor productivity surges in 1995 and 2000, Germany’s productivity declined dramatically during the same period. We examine the sources of Germany’s productivity demise using the ifo industry growth accounting database that provides detailed industry-level investment information. While much attention has focused on the reduction in German labor hours, our data show that information and communication technology (ICT) investment in Germany was deeply lacking in the mid-1990s as compared with the United States. The transition to the new economy mitigated the German productivity slowdown, but did not reverse it. After 2000, we find that a recovery in Non-ICT investment was offset by a widespread collapse in German total factor productivity. Over half of the German industries (accounting for almost 50 per cent of German output) experienced negative total factor productivity growth. This second major difference between the United States and German industry performance explains Germany’s secular departure from the technological frontier.

The Conundrum of Economic Miracle: Manufacturing Growth without TFP Growth

The findings of low or even negative total factor productivity (TFP) growth in Singapore's manufacturing industries by Young (1995) and many others has been a controversial issue in view of its crucial role in the future sustainability of Singaporean manufacturing. This paper applies the varying coefficients frontier model to re-examine productivity growth in Singapore's manufacturing at the 3-digit industry level over the period 1970–1997. The results indicate that Singapore's manufacturing has on average experienced a –0.8 percent TFP growth per annum although the extent of TFP growth improved slightly in the 1990s. The decomposition of TFP growth into technical efficiency change and technological progress, found technological regress is responsible for the negative TFP growth. Factor accumulation remains the principal contributor to the economic miracle of Singapore's manufacturing industries.

HOW IMPORTANT ARE CAPITAL AND TOTAL FACTOR PRODUCTIVITY FOR ECONOMIC GROWTH?

We examine the relative importance of the growth of physical and human capital and the growth of total factor productivity (TFP) using newly organized data on 145 countries that spans more than 100 years for 23 of these countries. For all countries, only 14% of average output growth per worker is associated with TFP growth. We use priors from theories to construct estimates of the relative importance of the variances of aggregate input growth and TFP growth across countries. Much of the importance of the variance of TFP growth across countries is associated with negative TFP growth. (JEL O47, O50, O57, O30, N10)

Production Structure, Factor Substitution, and Total Factor Productivity in the South African Agricultural Sector

The production structure of the South African agricultural sector is analyzed using duality theory in production and cost. An unrestricted translog cost function is estimated, and a number of model restrictions (homothetic, homogenous, unitary elasticity of substitution, Hick’s neutral technical change, and no technical change) are tested for, but none of them was found to be statistically significant. The Allen Elasticity of Substitution (AES) and the Morishima Elasticity of Substitution (MES) are calculated to analyze factor substitution, and found that the AES may give erroneous results in the case of number of factors exceeding two. The substitution of land is found to be easiest while that of fuel to be hardest. Furthermore, technical change is found to have a negative impact on agriculture, but there are increasing returns to scale in South African agriculture. However, technical change dominates over scale effect, and results in negative total factor productivity growth. When these results are combined with the finding that, it is easier to substitute machinery by labor than vice-versa, it appears that labor-intensive technologies may be useful for agriculture growth.

How Important Are Capital and Total Factor Productivity for Economic Growth?

We examine the relative importance of the growth of physical and human capital and the growth of total factor productivity (TFP) using newly organized data on 145 countries that spans more than 100 years for 23 of these countries. For all countries, only 14% of average output growth per worker is associated with TFP growth. We use priors from theories to construct estimates of the relative importance of the variances of aggregate input growth and TFP growth across countries. Much of the importance of the variance of TFP growth across countries is associated with negative TFP growth.

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.

Technical Efficiency, Technological Change and Total Factor Productivity Growth in Chinese State‐Owned Enterprises in the Early 1990s

Based on a framework proposed by Battese and Coelli (1995), we estimated the stochastic frontier production function for four Chinese industries: building materials, chemicals, machinery and textiles during 1990–1994. The type of technological change is tested and total factor productivity (TFP) growth is calculated for each industry. We found no evidence of technological change in the building materials, chemicals and textiles industries and a neutral technological progress in the machinery industry. There was significant reduction of technical efficiency in the chemicals, machinery and textiles industries. As the result, chemicals and textiles experienced a negative TFP growth, whereas building materials and machinery display negligible TFP change. Our result cast doubt on the industrial reform measures in China.