Main Source Of Productivity Growth Research Articles

Technical Efficiency and Productivity Change in the European Union with Undesirable Output Considered

Global competition and climate change are changing the nature of economic activity and impose the urgent need to have environmentally sensitive productivity growth. The paper addresses both desirable and undesirable output to assess technical efficiency and productivity changes, as well as evaluate the importance of an energy input in the production function and productivity change differentials in the European Union (EU) over the period 2000–2018. To that end, it uses output-oriented data envelopment analysis and Malmquist productivity analysis. The results reveal that the EU is facing significant challenges due to a decreasing trend in technical efficiency and slow productivity growth. The absence of major improvements in human resource performance has reduced the benefits of technological innovations which are the main source of productivity growth. Additionally, the results show that energy use did not critically influence efficiency and productivity.

Total Factor Environmental Productivity in the Mediterranean Countries: A Malmquist–Luenberger Index Approach

This paper examines the environmental productivity in the Mediterranean countries over the period 2009-2014.We use the Malmquist-Luenberger productivity index (MLPI) that can handle undesirable outputs within Data Envelopment Analysis (DEA) approach. We decompose the MLPI index into technical efficiency, technological change and scale efficiency change in order to determine the source of productivity changes. Empirical findings indicate that the total factor environmental productivity in the Mediterranean countries have a negative developmental trend. Furthermore, we find that technological progress is the main source of productivity growth. Finally, Mediterranean countries need a considerable effort on R&D to optimize the potential for technical development and enhance the environmental efficiency levels.

English

In Ethiopia, agricultural production and productivity are very low, and hence increase in production and productivity are vital to meet increasing food demand. This study identifies and quantifies the main sources of productivity growth in Ethiopian agriculture using the translog (TL) stochastic input distance function and the Ethiopian Rural Household Survey (ERHS) panel dataset. The true fixed effects (TFE) panel data estimator is used to separate inefficiency effects from observed and unobserved heterogeneity. The parametric Malmquist productivity index (MPI) is used to decompose total agricultural growth into three major sources. The average technical efficiency score was 0.875; this finding indi¬cates that on average a farmer produces 87.5% of the value of the output that is produced by the most efficient farmer using the same technology and inputs. This implies that they can reduce the inputs required to produce the average output by 12.5% if their farming operation becomes technically efficient. MPI shows that the average annual productivity growth was 17.9% between 1994 and 2009. Further decomposition of the index shows that scale efficiency change is the most important source of this growth, and accounts for about 14.5%. Technological improvement accounts for approximately 4.8% while the contribution of technical efficiency change is negative, leading to an annual productivity decline of 1.3%. This finding suggests that increasing productivity is possible via improving these components by improving training to the farmers, extension services, research and development, and agronomic practices. Keywords: Productivity growth, translog stochastic input distance function, Malmquist productivity index, Ethiopia.

Productivity growth and structural change in China (1995–2009): A subsystems analysis

This paper provides an analysis of productivity growth and structural change of the Chinese economy for the period 1995–2009 based on the Subsystems approach. The approach allows a disaggregated analysis without losing sight of sectoral inter-dependences. We observe, in a clearer way, the transition in China from the development phase based on agriculture and ‘light’ industry to the phase based on ‘heavy’ industry and technology-intensive industry and services. We find that best performing subsystems where targeted by industrial policy for promotion. Although there is not a clear pattern, the main source of productivity growth across subsystems was direct labor savings.

Swiss Cantonal Banks: A DEA Efficiency and Productivity Analysis

This paper applies a data envelopment analysis (DEA) to study the efficiency and productivity changes in the Swiss cantonal bank sector in the period 2006-2014. The efficiency analysis is conducted by applying the production input-oriented DEA variable returns to scale model in a three-stage procedure. The productivity is studied by estimating a DEA-based Malmquist Productivity Index (MPI) that provides evidence of increasing productivity growth on average for the sector in the studied period. The main source of productivity growth as per the components of the Banker, Charnes and Cooper (BCC) MPI model is related to a frontier-shift (technological innovation) rather than to improvements in the technical efficiency. The decreasing average DEA scores in the post-global financial crisis period of 2008-2014 further support this finding. In the second stage of the efficiency analysis, the environmental factors influencing the productivity growth are analysed by conducting a general method of moments (GMM) regression. The results provide evidence of a positive and statistically significant relationship between the stock of residential buildings per canton and technical efficiency. In the third stage, the environmental variables from the second-stage regression are included within the constraints of the first-stage DEA model as proposed by Ray [1]. The third-stage DEA scores support the evidence of slightly decreasing average post-global crisis technical efficiency. The overall average technical efficiency in the Swiss cantonal banking sector, however, remains at a relatively high level in the studied period.

The estimation and decomposition of tourism productivity

This paper estimates a total factor productivity index that allows for a rich decomposition of productivity in the tourism industry. We account for two important characteristics: First, the heterogeneity between multiple tourism destinations, and second, the potential endogeneity in inputs. Importantly we develop our index at the macro level, focusing on cross-country comparisons. Using the Bayesian approach, we test the performance of the model across various priors. We rank tourism destinations based on their tourism productivity and discuss the main sources of productivity growth. We also provide long-run productivity measures and discuss the importance of distinguishing between short-run and long-run productivity measures for future performance improvement strategies.

PRODUCTIVITY GROWTH, HUMAN CAPITAL AND DISTANCE TO FRONTIER IN SUB-SAHARAN AFRICA

Using the Malmquist productivity index and panel data methods, we study the role of total human capital and its composition in the technological “catch –up” process and productivity growth via the channels of innovation and adoption of technology in a panel of 19 sub -Saharan African countries between 1960 and 2003. Our findings indicate different roles played by the composition of human capital and a follow-on consistent and significant contribution of total human capital to productivity growth. Primary and secondary school attainment (unskilled labour) contribute significantly to the adoption of technology(the main source of productivity growth in sub-Saharan Africa) whilst tertiary school attainment (skilled labour) plays a significant role in local innovation. Total human capital on the other hand, contribute more significantly to the adoption of technology and innovation. Technological “catch-up” remains a significant element in productivity growth in sub-Saharan Africa and economies with higher tertiary school attainment(skilled labour) and higher total human capital tend to contribute significantly to productivity growth through the channel of technological “catch-up”. Our results rather point towards a circuitous depiction of the symbiotic characteristics of the composition of human capital in enhancing productivity growth in sub -Saharan Africa and hence efforts in scaling- up investments in human capital by governments, development partners etc should not be too concentrated on one composition of human capital.

Nanometrology in Emerging Economies: The Case of Mexico

Nanotechnology is a global phenomenon already impacting, in some way, the scientific, technological, economic and social development, and the culture, of emerging economies, like Mexico’s. As any new technology, on one hand it has the potential to be one of the main sources of productivity growth for these economies, but on the other it can also be the origin of drawbacks if no appropriate actions are taken about. The effects of such impact depend on how the country prepares itself concerning the aforementioned aspects of development. Metrology constitutes a discipline which is transversal to all of these aspects. It has to move forward in order to face the challenges derived from nanotechnology, in proportion to the particular status of the country. Metrology has to be seen as an essential part of nanotechnologies. Any activity within science and technology must be accompanied by reliable measurements. The current paper describes issues and challenges in metrology to be faced in Mexico concerning this technology.

Exploring the Sources of Productivity Changes for the US Forest Products Industry

This research investigates sources leading to productivity changes for the US forest products industry during the time period from 1997 to 2009 using the contemporaneous and global Malmquist productivity index (MPI) approaches. Under the assumption of variable returns to scale, the global MPI breaks down into new measures of decomposition, such as efficiency change, best practice change, and scale efficiency change. Overall, the productivity change for this industry shows progression in both approaches. The technical and scale efficiency changes are main sources of productivity growth. However, compared with the contemporaneous MPI, the global MPI can reflect the real-world situation in terms of productivity change. Within the US forest products industry, the annual growth rates in housing starts and in real export value significantly affect the productivity growth in the wood product sector. In contrast, the real export value's growth rate is the only notable effect on the pulp and paper sector's productivity growth.

PRODUCTIVITY GROWTH IN LATIN AMERICA OVER THE LONG RUN

The low pace of Latin American productivity growth in recent decades, despite extensive economic reforms, has yet to be understood in a longer‐run context where factors such as demographic changes, structural shifts, and investment levels can be taken fully into account. The OxLAD database provides comparable sectoral output and workforce series over 1900–2000 for the six leading economies in the region for the first time. Our analysis of this new dataset shows that: intersectoral resource reallocation reduced aggregate productivity growth in all three periods; total factor productivity growth was low throughout the century, and even negative in the closing three decades; and thus factor accumulation—investment in fixed capital and skilled labor—was the main source of productivity growth in Latin America during the twentieth century.

Sources Of Efficiency And Productivity Growth In The Philippine State Universities And Colleges: A Non-Parametric Approach

This paper evaluates the efficiency and productivity growth of State Universities and Colleges (SUCs) in the Philippines. The SUCs performance is determined on the changes in total factor productivity (TFP), technological, and technical efficiency. We use two Data envelopment analysis (DEA) models for the first time in estimating the relative performance of SUCs. Firstly, the output-orientated DEA-Malmquist index is calculated from panel data of 59 SUCS over the period 1999-2003 or a total of 295 observations, and secondly, the DEA multi-stage model (input reduction) is estimated. The two DEA models are calculated using three educational outputs and three inputs. Using Malmquist Index model, findings reveal that 49 SUCs or 83 percent are efficient. The technological index shows that six (6) SUCs or 10.16 percent only shows a technological progress. In terms of total factor productivity, SUCs obtained an index score of 1.002, which implies a productivity growth. This means that 27 SUCs or 45.76 percent shows a remarkable productivity growth. The main source of productivity growth is due to technical efficiency than innovation. In general, SUCs shows a 5.2 percent technological regression over the study period. Lack of innovation in the Philippine higher institutions has a policy implication: the Philippine government should exert more efforts to provide modern teaching and learning facilities in every state school to improve its deteriorating technological performance. Furthermore, using multi-stage method, technical efficiency has an average of 95.4 percent (Constant-returns-to scale DEA) compared with 96.6 percent (Variable-returns-to scale DEA). Finally, the scale efficiency has a 98.7 percent rating. This implies that, in general, SUCs obtained a below frontier efficiency score. The new findings in this paper may give impetus to Commission on Higher Education, lawmakers or legislators, and the university administrators to adopt measures that would be beneficial to the improvement of State Universities and Colleges in terms of inefficiency and unproductive growth.

TECHNOLOGICAL SOURCES OF PRODUCTIVITY GROWTH IN GERMANY, JAPAN, AND THE UNITED STATES

In this paper we use a dynamic general equilibrium growth model to quantify the contribution to productivity growth from different technological sources in the three leading economies of the world: Germany, Japan, and the United States. The sources of technology are classified into neutral progress and investment-specific progress. The latter can be split into two different types of equipment: information and communication technologies (ICT) and non-ICT equipment. We find that in the long run, neutral technological change is the main source of productivity growth in Germany and Japan. For the United States, the main source of productivity growth arises from investment-specific technological change, mainly associated with ICT. We also find that a non-negligible part of productivity growth in the three countries has been due to the technology specific to non-ICT equipment.

Productivity growth, capacity utilization, and technological progress in the natural gas industry

The main objective of this paper is to estimate the total factor productivity in the natural gas industry based on international comparison. Countries to be considered in the empirical analysis include the US, Canada, France, Italy, Japan and Korea. We also examine the determinants of total factor productivity performance focusing on the scale and capacity utilization effect. Methodologically, we will adopt the short-run equilibrium model based on the translog cost function incorporating the capacity utilization as an endogenous factor. From the results of our study, we found that the sources of productivity growth over time and productivity difference among countries in the natural gas industry differ from country to country. Especially, technological change turned out to be the main source of productivity growth in those countries with mature industry, while the effect from scale economies was the main contributor to productivity growth in Korea with a premature industry. Based on the empirical findings, we consider policy implications for the Korean natural gas industry.