Technical Change Components Research Articles

Profitability development of Czech dairy farms

The paper deals with the development and main determinants of the profitability of Czech dairy farms. The aim of the paper is to evaluate the differences in the dynamics of profitability for two types of milk producers - specialized dairy farms and mixed farms - within the context of the agricultural policy changes. This aim is achieved by decomposing profitability into output growth, output and input price changes, changes in decoupled subsidies, technical change, scale, mark-up, and technical efficiency change components based on input distance function estimation. Based on the panel data obtained from the FADN database in the time period 2004-2011, it was found that the change in profitability was positive in the analysed time period, and slightly higher for the specialized dairy farms than for the mixed ones. The changes in output price, mark-up component and technical change are the main determinants of the development of profitability. Agricultural policy measures had different effects on these components. The strongest correlation was between the operational subsidies and the technical change and technical efficiency change, and this correlation was negative.

Productivity change in a multisectoral economic system

ABSTRACTWe estimate productivity growth without recourse to data on factor input shares or prices. In the proposed model, the economy is represented by the Leontief input–output model, which is extended by the constraints of primary inputs. A Luenberger productivity indicator is proposed to estimate productivity change; this is then decomposed in a way that enables us to examine the contributions of individual production factors and individual commodities to productivity change. The results allow for the identification of inputs or outputs that are the drivers of the overall productivity change. Their contributions are then decomposed into efficiency change and technical change components. Using input–output tables of the US economy for the period 1977–2006, we show that technical progress has been the main source of productivity change. Technical progress was mostly driven by capital, whereas low-skilled labour contributed negatively.

Measuring green productivity growth of Chinese industrial sectors during 1998–2011

This study proposes an improved method for measuring green productivity growth in order to overcome the “discriminating power problem” and “technical regress” associated with the conventional data envelopment analysis (DEA) models. The rationale is to combine the concepts of super-efficiency and sequential DEA models to subsequently construct an improved production possibility set for the directional distance function (DDF). With this enhancement, the Malmquist–Luenberger productivity index (MLPI), which can be compared across sections and periods, is proposed. Therefore, the correct technical and efficiency change components can be obtained after decomposing the MLPI. This novel MLPI is employed to measure the green productivity growth of 36 Chinese industrial subsectors during the period 1998–2011, under the constraint of energy consumption and CO2 emissions. A comparison of the measures of the current study with the productivity growth indexes that have been previously used yielded the following results: (i) productivity growth rate is overestimated without considering CO2 emissions; (ii) the rates of technical and efficiency changes are under- and over-estimated respectively, and (iii) the rate of green productivity growth is also underestimated by the previous indexes. The main conclusions and its policy implications for China's green productivity growth through technology progress and structural adjustment are discussed in-depth.

Economic implications of climate change: evidence from agricultural productivity

The increased frequency and severity of drought episodes have characterised the natural environment of the Sahel region in Africa during the past four decades. With little to no mitigation option available to them, countries of the Sahel will face a further deterioration of their economic environment, as an ill-agricultural sector will most likely drag down their whole economies. This paper uses a six-month standardised precipitation index and average temperature during the growing season days to quantify the adverse impacts of climate change on agricultural productivity. I first estimate a Malmquist productivity index and its efficiency and technical change components. I further assess the statistical significance of the indices by estimating confidence intervals around the point estimates using a bootstrap method. In the second stage of the analysis, I model the adverse effects of drought and temperature on agricultural productivity using a probit specification. The findings of this paper point to a dismal agricultural productivity. These findings also highlight the significant cumulative negative impacts of higher temperatures and recurrent droughts on agricultural-based economies.

Productivity change in Lithuanian family farms with the sequential technology

The sequential Malmquist-Luenberger productivity index was employed to assess the sources of changes in the total factor productivity in Lithuanian family farms. The research sample encompasses 200 family farms reporting to the Farm Accountancy data Network. The sequential Malmquist-Luenberger index was decomposed by taking into account scale efficiency change and variable returns to scale technology. The obtained efficiency scores suggest that years 2006 and 2009 were those of the most inefficient farming activity. Analysis of the scale efficiency scores suggested that the mixed farming should expand its operation scale in order to maintain the economic viability and competitiveness. The sequential Malmquist-Luenberger productivity index suggested that the TFP had decreased by some 2.9% throughout 2004–2009. The technical change component stagnated in 2009, yet remained the most important factor of TFP growth accounting for increase of some 14% during 2004–2009. The decreasing pure technical efficiency, however, reduced the TFP by 16%. The scale efficiency change did not play an important role. Innovative decision making units – family farms – were identified in terms of distance function and productivity index values.

Efficiency and productivity analysis of Indian banking industry using Hicks-Moorsteen approach

Purpose – The purpose of this paper is to attempt to measure the performance of the Indian banking sector in terms of efficiency and productivity levels and their determinants during the post-reform period. Design/methodology/approach – The present study is a novel attempt as it has used pooled data for a duration of 15 years (i.e. 1997/1998-2010/2011) from 59 selected banks for estimating the Hicks-Moorsteen (HM) total factor productivity (TFP) index. Findings – Poor technical efficiency has experienced with scale efficiency change exerting dominant factors; whereas relatively better productivity growth has been experienced by the banks with major contributions from technical change components. The study found relatively underestimated efficiency and productivity levels by traditional data envelopment analysis-based Malmquist index. Additionally, the study brings into account the results for external and environmental determining factors contributing to the TFP growth. Originality/value – Using HMTFP indices has helped to eliminate certain drawbacks of data envelopment and provided the more elaborative decomposition of productivity growth along with their components so as to have lucid and multidimensional insights about the performance of the Indian banking industry after the initiation of financial reforms.

Productivity accounting for separable technologies

This paper develops a method for decomposing total factor productivity growth in separable production technologies and uses it to examine the role of pest-damage prevention on agricultural productivity. The rate of technical change is decomposed into output-enhancing and damage-preventing components. Growth accounting cannot provide separate estimates of these two components of technical change, and instead a parametric model is developed based on the dual cost function. The proposed model captures both components of technical change, properly accounts for environmental effects, and also accommodates the presence of capacity utilization and scale biases. The empirical application of the model is to a sample of Cretan olive-oil producers, and the results show that output-enhancing technical change is more important than damage-preventing technical change in explaining observed total factor productivity (TFP) changes. The second largest source of TFP growth is due to the scale effect.

Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools

In this paper we develop a Malmquist productivity index for public sector production characterized by the influence of environmental variables. We extend Johnson and Ruggiero (2011) to the more general case of variable returns to scale to further decompose the Malmquist productivity index into technical, efficiency, scale and environmental change. We apply our model to analyze productivity of Dutch schools using 2002–2007 data. The results indicate that the environment influences the productivity index as well as the technical, efficiency, scale and environmental change components. We see that schools with a moderate classification of environment have the highest productivity numbers. In line with expectations, schools with the worst environment also perform worse and would perform better with an improved environment.

Productivity trends of Chinese regions: A perspective from energy saving and environmental regulations

Energy saving and emissions reduction has recalibrated China’s economic development mode to a more sustainable way. In this paper, we construct a novel total factor productivity (TFP) index using a sub-vector enhanced hyperbolic distance function, which simultaneously credits for an expansion in economic output along with contractions in energy input and undesirable output. Subsequently, this index is employed to evaluate the TFP change for 30 provincial regions in China during 2006–2015. The results indicate that China’s productivity considering energy saving and emissions reduction experiences a gradual improvement shifting from decline to increase throughout this decade, and the amelioration can mainly be attributed to the efficiency improvements from the east regions, while the contributions from technical change component will not emerge until 2013 due to insufficient energy and environmental R&D investments. Finally, some policy recommendations are also put forward on how to enhance China’s productivity.

On the inconsistency of the Malmquist–Luenberger index

Apart from the well-known weaknesses of the standard Malmquist productivity index related to infeasibility and not accounting for slacks, already addressed in the literature, we identify a new and significant drawback of the Malmquist–Luenberger index decomposition that questions its validity as an empirical tool for environmental productivity measurement associated with the production of bad outputs. In particular, we show that the usual interpretation of the technical change component in terms of production frontier shifts can be inconsistent with its numerical value, thereby resulting in an erroneous interpretation of this component that passes on to the index itself. We illustrate this issue with a simple numerical example. Finally, we propose a solution for this inconsistency issue based on incorporating a new postulate for the technology related to the production of bad outputs.

Productivity of Nations: A Stochastic Frontier Approach to TFP Decomposition

This Paper Tackles the Problem of Aggregate TFP Measurement Using Stochastic Frontier Analysis (SFA). Data From Penn World Table 6.1 are Used to Estimate a World Production Frontier For a Sample of 75 Countries Over a Long Period (1950-2000) Taking Advantage of the Model Offered By Battese and Coelli (1992). We Also Apply the Decomposition of TFP Suggested By Bauer (1990) and Kumbhakar (2000) to a Smaller Sample of 36 Countries Over the Period 1970-2000 in Order to Evaluate the Effects of Changes in Efficiency (Technical and Allocative), Scale Effects and Technical Change. This Allows Us to Analyze the Role of Productivity and Its Components in Economic Growth of Developed and Developing Nations in Addition to the Importance of Factor Accumulation. Although not Much Explored in the Study of Economic Growth, Frontier Techniques Seem to Be of Particular Interest For That Purpose Since the Separation of Efficiency Effects and Technical Change Has a Direct Interpretation in Terms of the Catch-Up Debate. The Estimated Technical Efficiency Scores Reveal the Efficiency of Nations in the Production of Non Tradable Goods Since the GDP Series Used is Ppp-Adjusted. We Also Provide a Second Set of Efficiency Scores Corrected in Order to Reveal Efficiency in the Production of Tradable Goods and Rank Them. When Compared to the Rankings of Productivity Indexes Offered By Non-Frontier Studies of Hall and Jones (1996) and Islam (1995) Our Ranking Shows a Somewhat More Intuitive Order of Countries. Rankings of the Technical Change and Scale Effects Components of Tfp Change are Also Very Intuitive. We Also Show That Productivity is Responsible For Virtually All the Differences of Performance Between Developed and Developing Countries in Terms of Rates of Growth of Income Per Worker. More Important, We Find That Changes in Allocative Efficiency Play a Crucial Role in Explaining Differences in the Productivity of Developed and Developing Nations, Even Larger Than the One Played By the Technology Gap

Efficiency Change over Time in a Multisectoral Economic System

Neoclassical growth accounting is a methodology used to measure the contribution of different production factors to economic growth and to indirectly compute the rate of technological progress. This model assumes constant returns to scale and perfectly competitive factor markets, which implies that factor prices are equal to marginal products – something that is only satisfied if factor markets are cleared, and external effects and distortions are absent. However, these conditions are usually not satisfied in real economies. Moreover, growth accounting assumes efficiency on factor and commodity markets, and consequently does not distinguish between efficiency change and technical change. In this paper, we estimate total factor productivity growth without recourse to data on factor input shares or prices. In the proposed model, the economy is represented by the Leontief input-output model, which is extended by the constraints of primary inputs. A Luenberger productivity indicator is proposed to estimate productivity change over time; this is then decomposed in a way that enables us to examine the contributions of individual production factors and individual outputs to productivity change. The results allow the inference of which inputs or outputs of an economy are the drivers of the overall productivity change– this is then decomposed into efficiency change and technical change components. Using input-output tables of the US economy for the period 1977 to 2006, we show that technical progress is the main source of productivity change. Technical progress, in turn, is mostly driven by capital whereas low-skilled labor contributes negatively.

Technical Progress and Regress in Norwegian Salmon Farming: A Malmquist Index Approach

Abstract In this study we measure change in total factor productivity for production of Atlantic salmon in Norway from 2001 to 2008. The Malmquist Productivity Index (MPI) is used. Our results demonstrate that total factor productivity change measured by MPI increased from 2001 to 2005, but thereafter regressed. This is due to a regress in the technical change component of the MPI. The efficiency change component is as strong as before. We interpret this result as an indication that the industry has reached a level of technological sophistication from where it is difficult to make substantial progress. For an individual producer it may still be possible to improve efficiency by catching up relative to the best practice frontier. When this possibility is exhausted, the total factor productivity change for the industry may come to a halt. JEL Classification Codes: Q22, O33, D24, C43.

Productivity change and the effects of policy reform in China's agriculture since 1979

During China's rural reforms, policies were frequently adjusted. Most policies favoured the continuation and deepening of reform; but some were contradictory or even led to regression in the reform process. How have the rural reforms affected China's agricultural production over the past three decades; and what lessons can be learned to aid the future course of reform? To answer these questions, this study estimates productivity change in China's agriculture and evaluates the effects of policy on agricultural output during the reform period. Aggregated provincial-level data for the 1979–2008 period are used in a translog production frontier model to estimate indices of total factor productivity (TFP) change and its three components—technical change, technical efficiency change, and a scale effect—with a focus on explaining the variation in technical efficiency. The estimation results show that the impressive improvement of TFP change is dominated by the technical change component. However, technical efficiency change and scale effects have worked against the improvement in TFP change in most periods. To improve technical efficiency, social welfare policies designed to eliminate the rural–urban divide, and reform polices focusing on factor market reforms, such as reform of the household registration system (hukou) and reform of land rights, seem to hold some potential.

Productivity growth patterns in US dairy products manufacturing plants

We analyse the productivity growth patterns in the US dairy products industry using the Census Bureau's plant-level data set. We decompose Total Factor Productivity (TFP) growth into the scale and technical change components and analyse variability of plants’ productivity by constructing transition matrices. We observe a cross-sectional dispersion in plant-level productivity growth in the industry. Even though the industry aggregate shows a small TFP growth rate −0.3%, quartile rank analysis shows that while the lowest productivity quartile plants average 1.9% loss in productivity, the highest productivity quartile plants average 1.1% growth annually. Our results show considerable movements of plants in their productivity rank categories overall and across age groups, and we find that the scale effect contribution to TFP growth accounts for about 90% of TFP growth on average in the industry. These plants extract scale efficiencies over technological progress to fuel TFP growth. The youngest plants start with the lowest productivity growth at the initial time period, but they catch up older plants productivity, which present the highest average growth rate through years. This may indicate a ‘learning-by-doing’ process for the industry.

Productivity growth in food crop production in Imo State, Nigeria

Agriculture plays pivotal roles in Nigeria including food security, employment, foreign exchange earnings and poverty reduction. This study examined the growth in food crop productivity in Imo State in Nigeria withemphasis on the decomposition of total factor productivity (TFP) into technical progress, changes in technical and allocative efficiency and scale effects. A panel data set comprising 210 observations drawn over 2001 – 2007 periods was used. Using the translog stochastic frontier production function, the decomposition components were computed. The results showed that TFP decreased through time, while technical change was negative, implying downward shift of the production frontier. As a major component, technical change was the main constraint to the achievement of high levels of TFP during the study period. The scale effect, which is generally bigger than technical change component shows that the sampled farms had not taken advantage of scale economies. Furthermore, the allocative efficiency had an average magnitude closer to the scale effect and points towards decreases in the efficiency with which production factors are allocated. This is an indication of a decline in technical efficiency. We suggest reforms in the Agricultural Development Programmes (ADPs) geared towards enhancing their capacity in extending novel technologies and innovations to farmers.

Total Factor Productivity Growth and its Determinants for West Bengal Agriculture

The present study is concerned with the measurement of total factor productivity growth (TFPG) using the non-parametric approach for seven major crops--aus, aman, boro, jute, wheat, rapeseed-mustard, and potato--in West Bengal, from 1980 to 2003. TFPG is decomposed into the components of technical change, efficiency change, and scale change. A second stage regression analysis highlights the favorable role of factors (i.e., public expenditure, credit, irrigation, regulated markets, and inequality reduction in the distribution of operational land holdings) in fostering TFPG.

The Luenberger indicator and productivity growth: a note on the European savings banks sector

We employ the Luenberger productivity indicator to estimate productivity growth and its decomposition into technical change and efficiency change components for savings banks sectors in 10 EU countries between 1996 and 2003. The Luenberger indicator requires less restrictive assumptions than standard nonparametric productivity indexes, and it allows the assumption of profit maximization to be made for sample firms. We estimate average productivity growth in the savings banks sector to be 2.78% per annum and driven almost entirely by technical change. Whilst the general results confirm earlier findings, this study is one of the earliest to identify cross-border differences in productivity growth in the savings banks sector.

ENVIRONMENTAL REGULATION AND PRODUCTIVITY: THE EFFECT OF ENVIRONMENTAL POLICIES ON JAPANESE MANUFACTURING INDUSTRIES

This paper describes the authors. attempt to measure effects of environmental regulations imposed on industrial solid waste generation. Productivity was measured using the Luenberger Productivity Index based on Data Envelopment Analysis. The sources of productivity change were examined by decomposing the observed index into efficiency change and technical change components. Results show that Japanese manufacturing industries have entered a stagnant phase and actually showed no high productivity growth during 1990-2006. Furthermore, positive changes in surviving industries mainly result from technological innovation, not from improved efficiency.

How R&D investments influence TFP growth: Evidence from China’s large and medium-sized industrial enterprises

This paper investigates the potential channels through which R&D may influence TFP growth using industry-level panel data of China’s large and medium-sized industrial enterprises over the period of 2000–2007. Comparing with existing literature, we provide a closer look of the relationship between R&D and TFP growth by decomposing TFP growth into efficiency change and technical change components using Malmquist productivity index and distinguishing between upstream R&D spillovers and downstream R&D spillovers. We find TFP grow slightly during 2000–2007, and R&D investment indeed serves as an engine of productivity growth just as endogenous growth theories argued, which is largely because R&D accelerates technical progress even it also results in enlarging technical inefficiency. However, we find a robust negative effect of downstream R&D spillovers on TFP growth, the effects of upstream is positive but not statistically significant. In addition, we do not find the positive effects of human capital on TFP as endogenous growth theories indicated, but find human capital severs as “assimilation device” for R&D spillovers both in promoting TFP growth and increasing technical efficiency even the effects on technical progress is adverse.