Translog Production Research Articles

Sustainable practices in steel manufacturing: Substitution elasticities between waste, raw materials, and energy for greenhouse gas emission reduction

This study investigates the potential of waste utilization to mitigate greenhouse gas (GHG) emissions within the steel manufacturing industry. Utilizing a translog production function, we analyze the substitution elasticities among scrap steel, iron ore, and energy, exploring their roles in carbon reduction. Our approach incorporates the Resource Efficiency and Climate Change Mitigation model to simulate the impact of various waste utilization strategies on GHG emissions. The findings highlight that scrap steel and iron ore exhibit substitution dynamics. Iron ore and energy exhibit complementary relationship, and there is also a complementary relationship between scrap steel and energy but with lower elasticity, indicating that increasing scrap steel usage can significantly reduce emissions while decreasing iron ore demand. Specifically, enhancing the input efficiency of scrap steel in secondary steel production can reduce GHG emissions by over 8.3 tons for each additional ton produced—surpassing the impact of merely increasing the volume of reused material, which offers a reduction of more than 2.2 tons per ton. The strategies centered on reduction and recycling demonstrate even lower GHG reduction efficiency. The findings advocate for governmental intervention to promote and support waste reuse initiatives, highlighting the potential environmental benefits and efficiency gains from such policies.

Value and economic impact of fuel subsidies on the Mexican fishing industry

ABSTRACT Fuel is an important input in the fishing industry’s activities, and fuel subsidies are aimed at generating more competitiveness and encouraging development. Nevertheless, they can also create incentives for fishers to exert more effort, thereby resulting in overexploitation. This paper estimates the economic value of fuel used by the Mexican fishing industry based on the elasticity of production with respect to fuel (εC) and the value of the marginal product (ρC) through the Cobb-Douglas and Trans-Log production function. The εC and ρC were estimated to be 0.52 and USD 3.1, respectively, with the latter contributing to only 8.3% of the fuel subsidy. Furthermore, a direct relationship is evident when observing the trends and the differences in means of the average price of fishery landings and the number of subsidies between 2011 and 2019. That is, the higher the prices and/or subsidies, the higher the levels of extraction. These results have important implications for fuel management and its relationship with the extraction of fishery resources, especially in countries where a subsidy policy is applied in an attempt to support the sector, but which at the same time can have a negative impact on fishery resources.

Capital Inflow and Technical Efficiency: A Comparative Analysis Between India and China

This article empirically investigates the impact of foreign direct investment (FDI) on the technical efficiency of manufacturing firms in India and China. We apply the first-stage, stochastic frontier analysis (SFA), to the translog production frontier. The first-stage method estimates simultaneously consider exogenous technical efficiency determinants and translog production function factors. We take foreign ownership and foreign inputs as exogenous determinants of technical efficiency with control variables and foreign technology input in the production frontier. Empirical results find that foreign technology shifts the production frontier by enhancing productivity for Chinese firms, not for Indian firms. Furthermore, domestic firms which use foreign inputs and foreign firms are more efficient. JEL Classification: F14, O31, O32

Energy substitution possibilities and technological progress in Pakistan's industrial sector

Considered high-energy intensive, Pakistan's industrial sector has seen an upwelling in its energy use, reaching 19.74 million tons of oil equivalents in 2021, which is about 37% of Pakistan's total energy consumption. This has made the industry a major contributor to CO2 emissions and related contaminants. This research has tried to analyze the possibilities for factor substitution between energy and non-energy factors in the industrial sector by applying a trans-log production function. For the multicollinearity problem, ridge regression was used. The results show that (i) all the inputs are increasing return to scale; (ii) the measured substitution elasticity between gas-coal and oil-gas is about 0.901 and 0.953, while capital-oil, capital-gas, capital-coal, and labor-oil stands at 1.231, 1.088, 1.045, and 1.404. This is a strong sign that allocating more capital and labor to Pakistan's industrial sector instead of energy will be dynamic for sustainable development. (iii) oil-electricity consumption and electricity add to only a little share of energy by 0.378 because oil import has declined (about 15%) as a whole and imported electricity increased (5.53%), which gives the potential for primary interest, and (iv) technological progress is estimated between −0.051 and + 0.03 between energy inputs. The input of coal vs gas is a faster substitute with their relative difference in technological progress, while coal vs electricity also presents evidence of convergence. Our findings recommend robust policies, technological advancements, and industrial engagement for fostering energy efficiency towards a sustainable production system and contributing to an environmentally aware and efficient economy.

Estimation of technical efficiency of maize farmers in Wa East District in Ghana: translog stochastic frontier approach

ABSTRACT Efficiency analysis among maize farmers is crucial, especially when maize output continues to decline, even under improved technology. The aim of this study was to estimate the level of technical efficiency among maize farmers in Wa East District in Ghana and to assess the determinants of their technical efficiency. Data were collected from 273 household heads using the multistage sampling method. The study applied the stochastic translog production function to do the estimation and assessment. The results revealed a variation of 60.2%–89.5% efficiency levels among maize farmers. In addition, maize farmers achieved about 71.5% of the required technical competences. Factors contributing significantly were labour, land, age, farming experience, household size, hired labour and seed quality. The results showed an increasing returns-to-scale parameter being significantly different from unit. Recommendations are improvement in the capacity of farmers by agriculture extension service and accessibility of farmers to affordable production inputs in real time.

Fuel substitution possibilities, factor productivity, and technological progress in the industrial sector of India

India is often referred to as the next development superpower, and generally, becoming a large-scale industrialization center is seen as an achievable goal for the country. This article investigates the output elasticity, substitution elasticity, and technological advancement between the various factors (i.e., labor, capital, and energy use) in the industrial sector of India. To investigate the factor's productivity, a trans-log production function was applied; however, ridge regression was used to analyze the various parameters to check the multicollinearity issue. The results show that (1) the analyzed inputs are optimistic and return-to-scale averages of 1.18, 1.41, and 1.24 between labor, capital, and energy, respectively, are increasing; (2) the pairs substitution between labor–industrial energy utilization and capital–industrial energy consumption is found to be 0.96 and 0.98, respectively, on average, indicating that capital, labor, and energy are good substitutes that need more attention in the production process; and (3) the technological progress between factors ranges from −0.4 to 0.02, in which labor–energy and capital–energy utilizations provide quicker outcomes than a capital–labor utilization. Finally, the industrial sector can attain maximum productivity if capital and skilled labor are improved under the sustainable development goals, as energy and capital are optimized for maximum efficiency. Finally, energy substitution and low-carbon technological efforts can be better suited for attaining dual-carbon goals in the industrial sector.

The Euro Area 12: A Comparative Assessment of Its Member States in the Period 1998–2022

The primary objectives of this research are to compare the economic performance of the Member States (MS) in the Euro Area 12 (EA-12) of the European Union (EU) that served as net contributors and net recipients of its budget during the period 1998–2022. The comparison focuses on aspects related to economic growth and the business cycle, exploring the presence of hysteresis. To achieve these objectives, a novel approach is employed, which integrates the analysis of both growth and cycles. This approach involves using the Seemingly Unrelated Regression Equations (SURE) model to estimate a translog production frontier and assess the impact of lagging output gaps on the potential output or capacity for each of the MS considered. The data used to estimate each frontier and analyze growth decomposition consist of quarterly data filtered using the Kalman filter. The results reveal that lagging output gaps, occurring one or two quarters prior, significantly affect the potential output or capacity of the EA-12 MS, thereby supporting the existence of hysteresis. However, the impacts appear to be minimal. Furthermore, the research concludes that changes in total factor productivity (TFP), mainly due to technical change, play a more crucial role in the growth of MS that are net contributors to the EU budget. Conversely, total factor accumulation (TFA), mainly physical capital accumulation, has a more pronounced impact on the growth of MS net recipients from the EU budget. Interestingly, the heterogeneity observed among the EA-12 MS extends beyond the simple division between net contributors and net recipients of the EU budget. This heterogeneity raises questions about the European Central Bank’s (ECB) ability to stabilize the economies of these various MS solely through conventional monetary policy.

Elasticity of substitution between clean energy and non-clean energy: Evidence from the Chinese electricity industry

At present, China is in a stage of high-quality economic development. Rising demand for electricity has created a lot of CO2 emissions, which has put great pressure on the low-carbon development of China's power industry. Therefore, China attaches great importance to the potential of various clean power generation to replace thermal power generation. Given this, the study examines the potential for substitution of non-clean energy generation (thermal power generation) and clean energy generation (hydropower, nuclear power generation, and other energy generation) from 1993 to 2022 by using the translog production function and provides a scenario analysis of energy substitution for power generation. Firstly, the k-fold cross-validation method is used for ridge regression estimation in this paper, which avoids the subjective bias caused by the ridge trace diagram method used in most of the previous literatures. Secondly, compared with the previous research on the substitution elasticity of the power sector, this paper subdivides the types of clean power energy when estimating the substitution elasticity, which can better analyze the substitution relationship between thermal power and various clean power. Finally, the estimated substitution elasticity of thermal power and various clean energy sources is greater than 1, which indicates that clean energy generation can effectively replace non-clean energy generation. This provides an effective substitution elasticity parameter for the power sector to study low-carbon development. The scenario analysis show China's power sector can increase the proportion of clean power generation to reduce the carbon emission intensity while ensure power supply, which can help the Chinese government adjust the implementation of policies to promote the early peak of carbon emissions and keep carbon emission at a low level in the power sector.

Machinery structure, machinery subsidies, and agricultural productivity: Evidence from China

AbstractAlthough agricultural machinery is indispensable for modern agriculture, the effect of machinery structure on food production is rarely scrutinized. Machinery structure, referring to the proportion of high‐capacity machines which are represented by tractors with relatively high horsepower, is used to measure the scale of agricultural machinery. In response, this article investigates how agricultural machinery structurally impacts grain production theoretically and empirically, with particular emphasis on the effects of capacity structure and subsidy policy. The article estimates a Translog production function with a panel dataset covering 126 counties across Xinjiang and Hubei provinces in China from 2002 to 2012. Though we find the general elasticity of output with respect to machinery inputs is .03, the capacity structure of agricultural machines could impact agricultural production by inducing the reallocation of other input factors. Along with the upsizing of farming machines, we observe the complementarity between machinery horsepower and land inputs in production increases, while the joint effect of machinery and fertilizer decreases. The positive land channel is found in areas with fewer high‐capacity machines, while the negative fertilizer channel occurs when there are more large machines.

Assessment of technical efficiency and its determinants among smallholder pepper farmers in Tolon district of Ghana

The main purpose of the study was to assess technical efficiency (TE) and its determinants among smallholder pepper farmers in a less developed country, Ghana. The study used a stochastic frontier approach and the translog production function to analyze TE of the selected pepper farmers. The mean technical efficiency was estimated at 81.4% implying high efficiency of production among the producers. Pepper output increased with the cost of ploughing as well as the quantity of seed used in production. Furthermore, respondent’s age, years of formal education, household size, weeding frequency, livestock ownership and access to credit were identified as significant factors affecting TE. The study recommends provision of credit to farmers, training on effective weed control and soil fertility management alongside integration of livestock rearing as measures necessary to boost TE of pepper farmers.

Analysis of Growth Factors of the Four Asian Dragons Following the Asian Financial Crisis

Purpose - This study aims to identify implications from a factor decomposition analysis of the growth structure of four Asian dragons, Korea, Singapore, Hong Kong, and Taiwan, which have re-emerged as key regions in the fourth industrial revolution and the global value chain.
 Design/Methodology/Approach - With the Translog Production Function employed as the analysis model, the Stochastic Frontier Analysis model was used to derive total factor productivity (TFP), which was decomposed into four factors including returns to scale, technological changes, technical efficiency, and others.
 Findings - The results of the analysis conducted over different periods indicate that during periods of high growth, the economy’s scale effect largely contributed to total factor productivity. However, it became evident that the effect of technological changes had become increasingly important after going through the foreign exchange and financial crises.
 Research Implications - The new growth momentum in these four regions suggests a need to invest in human capital, research and development, and other areas to cope with the low-growth era. Although past high-growth was attributed to the returns to scale effect, the economic structures shifted in the direction of enhancing efficiency, and the effect of technological changes became a driving force while going through the crises. These results show a need to focus on technological advancement through active research and development investment to increase total factor productivity.

Can factor substitution reduce the shadow price of air pollution embodied in international trade? A worldwide perspective.

The calculation of trade-embodied air pollution (TEAP) and its economic losses can be reasonably used to assess the impact of transboundary air pollution. However, these air pollutants, which are associated with international trade, can be easily ignored due to their concealment. Based on this, the global multiregional input‒output model (MRIO) is used to quantify the volume of five air pollutants that are embodied in the trade of 20 countries from 2000 to 2016. Then, the shadow price of trade-embodied air pollution (SPTEAP) and the elasticity of factor substitution (EFS) are both calculated by applying the translog production function. Finally, impulse response analysis is used to study the dynamic impact of EFS on the SPTEAP. The main conclusions are as follows: (1) All countries experienced a mass transfer of TEAP, among which China and the USA are the developing and developed countries with the largest amount of TEAP transfers, respectively. (2) The SPTEAP and EFS vary greatly among countries, and these values are generally higher in developed countries than in developing countries. The relationship between the three EFSs can be expressed as [Formula: see text] in all countries, thus indicating that improving the technological level of a country is the best solution for reducing the TEAP in that country while incurring the lowest cost and the least difficulty. (3) Over the long run, the increase in [Formula: see text] and [Formula: see text] reduces the SPTEAP. Conversely, an increase in [Formula: see text] increases the SPTEAP. Therefore, policymakers should weigh these three factors according to the fluctuation of the SPTEAP and constantly adjust the allocation structure and ratio of these factors to maximize the benefits of transboundary air pollution governance.

Accuracy of Deterministic Nonparametric Frontier Models with Undesirable Outputs

The accuracy of deterministic nonparametric frontier models with desirable outputs has been extensively investigated. However, research on the models’ accuracy in the presence of undesirable outputs is almost nonexistent, though applications in this regard are abundant. This paper evaluates the accuracy of seven representative deterministic nonparametric frontier models in dealing with undesirable outputs. The experimental design employs Monte Carlo simulation and translog production functions across a wide range of settings. We find that the integration of undesirable outputs lowers model accuracy. All seven models display robust performance under different returns-to-scale assumptions. Outputs correlation has a positive effect on model performance. Using a large sample can improve the models’ accuracy except for the range-adjusted measure model. The models’ accuracy is most sensitive to noise at low noise levels. Endogeneity has a negative effect on the models’ accuracy, but depreciation of accuracy is minor at low to medium endogeneity levels. Heteroskedasticity leads to improved performance. Overall, the experimental results support the usage of the by-production approach and strongly disfavor the range-adjusted measure approach and the hyperbolic approach. The directional distance function method has an edge for large samples, if the objective is to identify top and bottom units. Another approach, treating undesirable outputs as inputs, is dominated by other methods. The ranking of the methods is generally robust to the variations of returns-to-scale, sample size, noise, outputs correlation, endogeneity, and heteroskedasticity. We also show that the slacks-based measure under the by-production framework has better performance than the Färe–Grosskopf–Lovell index proposed in literature.

Estimating production functions to determine the marginal economic value and price elasticity of water in the Chilean industrial sector

This study determines the marginal economic value of water and the price elasticity of demand for this resource using data from the 2018 Annual National Industrial Survey. Specifically, a translog production function is estimated with the ordinary least squares (OLS), constrained least squares (CLS), and instrumental variables (IV) methods, CLS being the method with the best results. Based on the estimates of the production function at the national level, it is determined that, on average, the marginal value of water is 14.6 USD/m3. Finally, the price elasticity of water demand varies between −0.8 and −1.2 depending on the industrial subsector.

Is it the same to invest in health care or social care? A health production function study

Abstract Background This study aims to explore the relationship between health expenditure and social expenditure in their role in affecting health outcomes, such as death rates and disability-adjusted life years. Both types of spending may behave as complementary or supplementary goods, besides, they may interact with each other over time. Methods We used a translog production function using both health and social expenditures as inputs, for a panel of 27 years and EU countries, in order to estimate their respective output elasticities and the elasticity of substitution between them. Instrumental variables and ridge regressions were used to estimate unbiased elasticities. Results Our results point out that the elasticity of substitution between social and health expenditures is positive and less than one, which means that these spending variables may be classified as weak substitutes. Still, the substitutability pattern is heterogeneous according to each country, year and health outcome, being most sensitive to mortality rates in comparison with disability-adjusted life years. Conclusions Our Results support the hypothesis of a weak substitution relation between health and social expenditure. This implies that investments in the health sector should not be independent of social sector investments. Thus, policymakers need to consider the joint effect of these two spending categories when considering investment decisions aiming at achieving specific health gains. This presentation was supported by National Funds through FCT - Fundação para a Ciência e a Tecnologia,I.P., within CINTESIS, R&D Unit (reference UIDB/4255/2020) Key messages • As health and social expenditures behave as weak substitutes, they have a complex relationship that depends on time, technology and the type of health benefit. • Both types of spending may affect health outcomes, still, their effect is heterogenous and may be cummulative with time.

Estimation of a demand system to obtain the price elasticities of water and elasticities of substitution in the Chilean industrial sector

A system of demand for inputs and productive factors is estimated to calculate the elasticities of substitution and the own-price elasticity of industrial water demand in Chile. A previous study used the Annual National Industrial Survey (ENIA) panel (1995–2014) to estimate the value of water and own-price elasticity through a translog production function. However, that database does not report the industrial firms' location to protect the informants’ statistical secrecy. In contrast, in this study, the survey ENIA 2018 is chosen since it includes the region where each firm is located, which allows for evaluating the endogeneity of the water price variable and using three instrumental variables related to the water supply. In addition, the performance of non-linear regression methods with constraints is evaluated to ensure that the estimated coefficients meet the conditions imposed by economic theory. The results show that the elasticity of industrial water demand is unitary but not statistically significant in most subsectors. The water demand in the wood and paper industry subsector is elastic (−2.2) and statistically significant. On the other hand, the elasticities of substitution obtained adopt values very low, indicating that water is an essential resource that is difficult to replace by other inputs or productive factors.

Efficiency Analysis of the Food and Beverage Industry in Tanzania: A Comparative Analysis

Purpose: This study examined the performance of food and beverage industries in Tanzania in terms of productive and technical efficiency. The specific objectives of the study were to evaluate the productive efficiency performance of food and beverage industries in Tanzania, to determine the level and trend of efficiency of food and beverage of food and beverage industry in Tanzania, and to assess the levels of productive efficiency performance in the food and beverage subsectors in Tanzania
 Methodology: The study used secondary data to achieve its objectives. The study employed a Panel data analysis technique using 40 companies in the manufacturing sector over a period of three years, 2018-2020. A stochastic frontier production model was applied using a linearized Translog production function to determine the performance elasticity coefficients of inputs and technical efficiency. The study used production theory advanced by Koutsoyiannis (1979) to explain the relatonship between input and output factors.
 Findings: One of the key findings was that the level and trend of efficiency in food and beverage industry demonstrated an upward trend for the period between 2018 and 2020 as evidenced by the changes in average in both food and beverage sub-sector which grew from 0.776 in 2018 to 0.7557 in 2019 and finally to 0.7746 in 2020. Another finding of the study was that, the individual productive efficiency distribution between food and beverage sub-sector revealed that beverage sub-sector performs much better than food sub-sectors, with an average technical efficiency of 77.85% and 81.36% for both food and beverage sub-sectors, respectively.
 Unique Contribution to Theory, Practice and Policy: The study’s unique contributions to theory include its assessment of efficiency levels, analysis of efficiency trends, and exploration of sector-specific variations. Its practical contributions encompass policy recommendations, guidance on modernization and technology adoption, and the importance of skills development and export promotion. These insights have direct implications for policymakers, industry stakeholders, and practitioners in Tanzania's food and beverage sector, aiding in the formulation of effective strategies to enhance efficiency and competitiveness.
 The study recommends that the government and other stakeholders comes up with policy reforms to address the underlying factors contributing to the underutilization of each firm’s production capacity. This includes reforming the input market in the manufacturing sector in order to increase the level of efficiency to 100%. There should be establishment of an efficient marketing mechanism that reduces the involvement of many parties in the supply chain and hence high transaction costs.

BUSINESS CYCLES WITH CYCLICAL RETURNS TO SCALE

AbstractWe study business cycles with cyclical returns to scale. Contrary to tightly parameterized conventional production functions, we empirically identify strong input complementarity that leads to procyclical returns to scale. We, therefore, propose a flexible translog production function that allows complementarity‐induced procyclical returns to scale. We integrate this function into a standard medium‐scale dynamic stochastic general equilibrium model. Our estimated model with input complementarity (i) features procyclical returns to scale and acyclical price markups, (ii) better matches the cyclicality of factor shares, and (iii) significantly decreases the contribution of markup shocks to output fluctuations relative to those of the standard model.

A Copula-Based Meta-Stochastic Frontier Analysis for Comparing Traditional and HDPE Geomembranes Technology in Sea Salt Farming among Farmers in Phetchaburi, Thailand

This study analyzed sea salt production and compared the technical efficiency level and the technology gap between traditional technology and High-Density Polyethylene Geomembranes (HDPE GMB) technology in the Phetchaburi province using a copula-based meta-stochastic frontier technique. A total sample size of 250 was chosen, comprising 195 traditional farmers and 55 HDPE GMBs farmers. Several copula families were used to analyze the dependence structure of the two error components and the best-fit copula-based meta-frontier model used Gaussian copulas. Land, labor, and fuel energy are the most significant input variables in the Gaussian copula-based meta-frontier model with a translog production function. Compared to meta-frontier production, the average technological gap between traditional technology production and HDPE GMB technology production was 0.69 and 0.77, respectively, meaning HDPE GMB technology is more technically efficient than traditional technology. The study identified that land, market price, sex, and experience were the contributing technical inefficiency factors for traditional technology production. For HDPE GMB technology production, land, sex, and experience were found to be contributing factors. The performance of HDPE GMB technology in salt farming in the Phetchaburi province suggests that public and private sector agencies should promote greater access to this technology for salt farmers.

Sustainable Environmental Economics in Farmers’ Production Factors via Irrigation Resources Utilization Using Technical Efficiency and Allocative Efficiency

This study reports the results of farmers’ production via irrigation resources utilization and efficiency parameters of technical efficiency and allocative efficiency by way of sustainable environmental economics. The hypothesis is that factors of farmers’ production affect technical efficiency and allocative efficiency in the irrigation scheme as sustainable environmental economics. Data from cross section and panel data were used and then the productivity parameters measurement of the production function are outlined in two scenarios: first, the data report that the parameters such as output elasticity determine factors of inefficiency and technical efficiency. Second, it presents the scores for the allocative efficiency to explain whether production factors (resources) are optimally, under- or over-allocated by farmers in the irrigation systems under environmental sustainability. This paper presents the productivity and efficiency parameters estimated using stochastic frontier analysis for the translog production function, which was estimated by the MLE method, and the allocative efficiency for the factor inputs allocation in the irrigation systems estimated by ordinary least square for the Cobb-Douglas production function. This study concludes that collective farmers lead into technical inefficiency and over use of factors of production.