Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies

A number of studies have explored the semi- and nonparametric estimation of stochastic frontier models by using kernel regression or other nonparametric smoothing techniques. In contrast to popular deterministic nonparametric estimators, these approaches do not allow one to impose any shape constraints (or regularity conditions) on the frontier function. On the other hand, as many of the previous techniques are based on the nonparametric estimation of the frontier function, the convergence rate of frontier estimators can be sensitive to the number of inputs, which is generally known as “the curse of dimensionality” problem. This paper proposes a new semiparametric approach for stochastic frontier estimation that avoids the curse of dimensionality and allows one to impose shape constraints on the frontier function. Our approach is based on the singleindex model and applies both single-index estimation techniques and shape-constrained nonparametric least squares. In addition to production frontier and technical efficiency estimation, we show how the technique can be used to estimate pollution generating technologies. The new approach is illustrated by an empirical application to the environmental adjusted performance evaluation of U.S. coal-fired electric power plants.stochastic frontier analysis (SFA), nonparametric least squares, single-index model, sliced inverse regression, monotone rank correlation estimator, environmental efficiency

Effects of One-Sided Fiscal Decentralization on Environmental Efficiency of Chinese Provinces

China's actual fiscal decentralization is one-sided: while public expenditures are largely decentralized, fiscal revenues are recentralized after 1994. One critical consequence of the actual system is the creation of significant fiscal imbalances at sub-national level. This paper investigates empirically effects of fiscal imbalances on environmental performance of Chinese provinces. First, environmental efficiency scores of Chinese provinces are calculated with SFA for the period from 2005 to 2010. Then, these scores are regressed against two fiscal imbalance indicators in a second stage model. Finally, conditional EE scores are calculated. This paper finds that effects of fiscal imbalances on EE are nonlinear and conditional on economic development level. Fiscal imbalances are more detrimental to environment in less developed provinces. These results suggest that the one-sided fiscal decentralization in China may have regressive environmental effects and contribute to regional disparity in terms of sustainable development

Econometric analysis of economic and environmental efficiency of Dutch dairy farms

The Dutch government aims for competitive and sustainable farms, that use marketable inputs efficiently as well as apply environmentally detrimental variables efficiently in the production process. The objective of this research is to define, to estimate and to evaluate environmental efficiency. Environmental efficiency is a measure that allows for the combination of a firm's environmental pressure with its economic performance. If the environmental efficiency could be improved, the emission of nitrogen into the environment will decrease without loss of production or additional costs.Three econometric methods based on the neoclassical production theory (stochastic production frontier, output distance function and shadow cost system) are transformed to enable the definition and estimation of environmental efficiency. These methods are applied to a panel of Dutch dairy farms. Nitrogen surplus is the environmentally detrimental variable throughout this thesis. In the stochastic production frontier, nitrogen surplus is modelled as an environmentally detrimental input. In the distance function N surplus is applied as a bad output. Due to the materials balance definition of N surplus the shadow price of bad output is positive. A shadow cost system is used to compute the cost-efficient and the nitrogen-efficient production. The latter is based upon the input mix that minimises the nitrogen content of variable inputs. Finally the variation in efficiency is explained in a two-stage approach with characteristics that are hypothesised to influence environmental efficiency. The environmental efficiency measures are compared to alternative environmental indicators currently used.</p

Measuring and Decomposing of China’s Agricultural Productivity and Environmental Efficiency

China’s agricultural productivity has achieved remarkable accomplishments in agricultural sector after China’s accession to World Trade Organization (WTO). According to National Bureau of Statistics of China (NBSC), the total meat production in 2018 is 43% more than in 2000, and the total cereal production in 2018 is 51% more than in 2000. However, the rapid development of agriculture is associated with environmental pollution. Since China’s rice output has quadrupled compared to the level in 1949, the rice production growth has serious repercussions on environment, which results in severe chemical fertilizer pollution. The amount of nitrogen fertilizer applied (209 kg ha-1) during rice production in China is 90% higher than global average level (Chen et al., 2014), and the N taken by rice is only 30-35% (Peng et al., 2009; Xu et al., 2012). In general, this research focuses on two empirical issues: one is the trade effects on China’s agricultural productivity, the other is measuring environmental efficiency and finding solutions for N pollution problem. First, we try to investigate the trade impacts on China’s agricultural productivity change and answer following questions. How productivity changes after China’s entry to WTO? Is there a substantial productivity growth behind yield growth? What’s the main factor behind TFP change? Second, we focus on evaluating environmental performance within the framework of productivity analysis and tackling N pollution issue. We try to measure China’s environmental efficiency and nitrogen use efficiency in particular to examine whether NUE is low, what factors lead to current NUE and what are the possible ways to abate N pollution. To measure China’s productivity change before and after China’s entry to WTO and analyze trade impacts on agriculture, the Stochastic Frontier Analysis (SFA) method is adopted. For the measurement of environmental efficiency, both Data Envelopment Analysis (DEA) and SFA are applied to estimate environmental productivity. Furthermore, based on empirical researches, both agricultural and environmental TFP are decomposed into explicit components to explore the decisive factors accounted for productivity change. In Chapter 2, we measure total factor productivity change in China’s agricultural sector before and after China’s entry to WTO, and obtain following conclusions. First, land, labor, intermediate input and capital could all lead to output growth. Second, China’s productivity increases during the whole research period, and TFP growth rate rises slightly after China’s entry to WTO. Third, the main contributors to TFP growth are not the same for the two sub-samples. Before China’s accession to WTO, productivity growth majorly owes to allocative effect of pork and other meat and the considerable technical progress, while allocative effect of crop and land and technical progress are contributing factors after China’s accession to WTO. Fourth, the development of technology achieves steady and substantial progress during the research period. Fifth, export has significant positive effect on technical efficiency before China’s entry to WTO, while import presents negative effect on technical efficiency after China’s entry to WTO. In Chapter 3, we measure and decompose China’s environmental productivity when production technology exhibits VRS. Based on the empirical research on rice production, we obtain following findings. First, the annual INE scores experience a mild fluctuation in 2004-2010, and the average INE indicates there is large potential to reduce current N input by 39%. Second, rice farmers in Hubei Province are already located at the most productive scale size. Third, RDTFP presents an annual decreasing rate owing to technical regress. Fourth, due to time lags and overestimation of inefficiency, the changing direction of TEC and TC are different. Fifth, rice farmers could decrease 19% of the nitrogen emissions based on the technical-efficient point on the CRS frontier. Sixth, NASEC is found to be more strongly correlated with NTFPC. Seventh, the changing direction of NTFP is consistent with RDTFP. In Chapter 4, we measure current TFP in rice production using SFA and analyze factors behind environmental productivity variation. After our empirical research on rice production, the main findings are as follows. First, increases in fertilizer N contents, land N contents, rice output, labor and intermediate input could all lead to N growth. Second, compared with fertilizer N contents, land N contents variation could lead to a larger rise in total N. Third, due to the complementary relationship between fertilizer and quasi-fixed input, increases in labor and intermediate input can also lead to total N growth indirectly through fertilizer increase. Fourth, technical efficiency in rice production remains stable during 2004-2010. Fifth, TFP is decreasing at an average annual rate of 2%, which is attributed to the negative impacts of the allocative effect of fertilizer nutrient, the effect of capital and technical regress. Sixth, the negative allocative effect of fertilizer N contents indicates that farmers use more fertilizer than they need. Seventh, due to the improvement of industrialization and low NUE, total N slightly increases at a rate of 1.6% every year. The empirical findings provide several policy implications. First, encouraging technological innovation and developing an efficient fertilizer application approach may be a prior choice for promoting agricultural development and soil conservation in the future. Second, to become crop production allocative-efficient, government could cut subsidies and national support concerning crop production. Third, enacting more proposals and regulations on perfecting the land circulation market and protecting arable land from using for commercial purpose could help reduce land allocative inefficiency. Fourth, government’s intervention and punishment on overuse of N fertilizer is necessary, due to the great potential of reducing N pollution by using less N. Fifth, after satisfying the current minimum amount of N input to become technical-efficient and scale-efficient, policy makers could guide farmers to reallocate their input combination to become environmental-efficient, since it is an effective way to prevent N pollution. Sixth, using less fertilizer, integrating small fragmented land and using land efficiently are beneficial to eliminating nutrient allocative inefficiency and improving TFP. Seventh, developing sustainable agriculture instead of high energy consumption, high waste and low efficiency agriculture could help to prevent N pollution growing over the years.2021-06-0

Analysis of Environmental and Economic Efficiency: Application of the Overseer model and simulated data

New Zealand’s success in raising agricultural productivity has been accompanied by higher input use, leading to adverse effects on the environment. Until recently, analysis of farm performance has tended to ignore such negative externalities. The current emphasis on environmental issues has led dairy farmers to target improvements in both environmental performance and productivity. Therefore measuring the environmental performance of farms and integrating this information into farm productivity calculations should assist informed policy decisions which promote sustainable development. However this is a challenging process since conventional environmental efficiency measures are usually based on simple input and output flows but nitrogen discharge is a complex process which depends on climate variability, pasture and cow physiology and geophysical variability. Furthermore the outdoor, pastoral nature of New Zealand farming means that it is difficult to control input and output flows, particularly of nitrogen. Therefore this paper proposes a novel approach to measure environmental and economic efficiency of farms using the Overseer nutrient budget model and a spatially micro-simulated virtual population data. Empirical analysis is based on dairy farms in the Karapiro catchment, where nitrogen discharge from dairy farming is major source of nonpoint pollution.Data Envelopment Analysis, Economic, Efficiency, Environment, Agricultural and Food Policy, Crop Production/Industries, Environmental Economics and Policy, Farm Management, Land Economics/Use, Livestock Production/Industries, Research Methods/ Statistical Methods,

Environmental Efficiency Analysis of Basmati Rice Production in Punjab, Pakistan: Implications for Sustainable Agricultural Development

The intensive use of chemicals worked as a catalyst to shift the production frontier but the most critical factor of maintaining a clean environment was totally ignored. The present study attempts to estimate the environmental efficiency of rice production by employing the translog stochastic production frontier approach. The data are collected from five major Basmati rice growing districts (Gujranwala, Sheikupura, Sialkot, Hafizabad, and Jhang) of Punjab in 2006. Chemical weedicides and nitrogen are treated as environmentally detrimental inputs. The mean technical efficiency index is sufficiently high (89 percent) but the environmental efficiency index of chemical weedicides alone is 14 percent while the joint environmental efficiency index of chemical weedicides and nitrogen is 24 percent implying that joint environmental efficiency is higher than chemical weedicide alone. It indicates that substantial reduction (86 percent) in chemical weedicide use is possible with higher level of productivity. Moreover, it is likely to contribute a considerable decrease in environmental pollution which is expected to enhance the performance of agriculture labour. The reduction in chemical weedicides will save Rs 297 per acre and Rs 1307.3 million over all from the rice crop in Punjab, improving the profitability of rice growing farmers by the same proportion. Empirical analysis indicates that reduction in environmental pollution together with higher level of profitability in rice production is achievable.Rice Production, Environmental Efficiency, Weedicide, Fertiliser (NPK), Stochastic Translog Frontier

Environmental efficiency analysis of Swiss acute care hospitals

Supported by the Swiss National Science Foundation (SNSF) within the framework of the National Research Program “Sustainable Economy: resource-friendly, future-oriented, innovative” (NRP 73) Grant-N◦ 407340_ 172453.Using a novel set of Global Warming Potential (GWP) data for hospitals in Switzerland, we estimate the environmental efficiency by stochastic frontier analysis and data envelopment analysis for the hospitals overall and 14 specific hospital areas. We find median efficiency of hospitals of at most 53.4 percent. The improvement potential for the Swiss acute care hospitals is estimated to be 136’669 t CO2-eq based on a GWP weighted mean environmental efficiency of 69.3 over all hospitals. The areas with the highest potential are heating and electricity: a one percent increase in efficiency would reduce overall GWP by 0.60 and 0.58 percent, respectively

Regional environmental efficiency and economic growth: NUTS2 evidence from Germany, France and the UK

This paper by applying nonparametric techniques measures spatial environmental heterogeneities of 98 regions from Germany, France and the UK. Specifically environmental performance indexes are constructed for the 98 regions (NUTS 2 level) identifying their ability to produce higher growth rates and reduce pollution (in the form of municipal waste) generated from regional economic activity. By applying conditional stochastic kernels and local constant estimators it investigates the regional economic activity – environmental quality relationship. The results indicate several spatial environmental heterogeneities among the examined regions. It appears that regions with higher GDP per capita levels tend to have higher environmental performance.Regional environmental efficiency; directional distance function; conditional stochastic kernel; nonparametric regression