Eco-efficiency Change Research Articles

Leading role of natural resources, eco-efficiency assessment, and energy transition in environmental sustainability: A depth of digital transformation

There has been a worldwide upsurge in environmental movements. The planet's ecosystem has degraded significantly over the years. The disturbing effects of environmental deterioration on Earth's physical geography cause concern among those concerned about the planet's future. While previous research has looked at various ecological elements, recent attention has turned to digital change and the need to make the most of it. Eco-efficiency is a critical component in reducing carbon output (CO2). Reaching carbon neutrality goals, getting carbon peaking, and achieving high-quality economic growth, digital transformation, and eco-efficiency are intense endeavors. A panel data set spanning G-15 economies from 1995 to 2022, this article examines the effects of digital transformation, eco-efficiency, and the food supply chain on carbon emissions. The unit root test established the stationarity of all indicators at the initial difference. In addition to Pedroni and Kao cointegration methods, the panel study uses ADF, DF-GLS, and PP unit root test, as well as dynamic ordinary least square (DOLS) and fully FMOLS stands for panel adjusted regular least square. Approaches for robustness: the present research additionally uses panel quantile regression to examine the effect of factors. In order to promote environmental sustainability and minimize CO₂ emissions, the findings highlighted the need for eco-efficiency, digital transformation, the food supply chain, and government policy. On the other hand, natural resource exploitation and energy transition worsen environmental quality and raise CO2 emissions in Great economies. We use the DH panel causality test to assess the factors' correlation further. Furthermore, carbon emissions (CO2) are affected in one way by changes in the energy sector and the food supply chain and in another by changes in eco-efficiency, digital transformation, and government policy. Environmental deterioration has many causes, and this study's results may help shed light on those reasons while suggesting solutions.

Eco-efficiency changes of the electricity and gas sectors across 28 European countries: A value-based data envelopment analysis productivity approach

This paper assesses the relative eco-efficiency changes in the electricity and gas sector (E&G)' production and consumption chains in 28 European countries. We propose a novel robustness assessment for the productivity index, specifically adjusted to value-based data envelopment analysis. Overall, results indicate that total factor productivity gains have been mainly driven by the catch-up effect across all chains of the E&G sector. When a more demanding perspective concerning negative environmental externalities is adopted, we find that the number of European countries that achieved productivity gains across all chains decreases. Besides, results depict the existence of lower productivity gains for the direct production chain when compared with the direct and indirect supply chains of the E&G sector. Germany, Luxembourg, and Belgium were consistently viewed as innovators across all chains, according to the environmental perspective. Several Eastern Europe countries usually viewed as policy laggards that resisted adopting the ambitious European decarbonization targets, showed total factor productivity gains in the supply chain of the E&G sector under a more environmental demanding perspective. Czechia was the only country with productivity losses across all chains, due to increasing coal-fired electricity generation in the time horizon assessed. The current partial return to coal as a source of electricity, due to the geopolitical tensions between Russia and Europe, brings additional challenges to the enhancement of the eco-efficiency of the European E&G sector.

Analysis of the Spatial Differentiation and Promotion Potential for Agricultural Eco-Efficiency-Evidence of Pollution's Strong Disposability.

Agricultural eco-efficiency is an important indicator used to measure agriculture's high-quality and sustainable development. Therefore, this paper uses the EBM-Super-ML method with strong disposability of undesired output to calculate Chinese agricultural eco-efficiency and uses a geographical detector to measure the driving force of the factor. The research conclusions are mainly reflected in three aspects. Firstly, from the perspective of eco-efficiency changes, the overall mean value of agricultural eco-efficiency increased by 3.5%, and the regional heterogeneity is significant, with the fastest growth in the eastern region. Secondly, the results of driving force analysis show that the main driving factors of agricultural eco-efficiency divergence are capital inputs, total carbon emissions, labor inputs, agricultural film residues, fertilizer use, and pesticide residues, with driving forces of 0.43, 0.37, 0.34, 0.31, 0.28, and 0.20, respectively. Finally, from the perspective of eco-efficiency improvement potential, the mean value of output improvement potential is 5%, and the input factor is 7%. Among the non-desired outputs, the reduction rate of agricultural films can reach 40%. Among the input factors, labor input has the highest potential for intensive use, while agricultural machinery has a negative effect. Therefore, strengthening the development of the agricultural service industry is of great significance to improve the utilization rate of mechanical equipment and reduce the undesired output of agriculture.

The Tourism Eco-Efficiency Measurement and Its Influencing Factors in the Yellow River Basin

Tourism eco-efficiency is an essential indicator to measure the level of green and sustainable development of tourism. Based on the data of nine provinces in the Yellow River Basin, from 2011 to 2020, this article estimates the changes in tourism eco-efficiency in the Yellow River Basin and explores its internal drivers by establishing multiple input-output index systems using the Global Malmquist-Luenberger (GML) index method. Finally, a panel stochastic Tobit model was applied to identify the key external drivers of its eco-efficiency improvement. The analysis shows that with the continuous promotion of the Yellow River Basin’s high-quality development strategy and ecological civilization construction, the tourism eco-efficiency of the Yellow River Basin provinces has been improved in the past decade. Due to the obvious ecological advantages in the upper reaches of the Yellow River Basin and the high level of tourism promotion and economic development in the lower reaches, tourism ecological efficiency in the upstream and downstream areas is commonly higher than in the midstream areas. The improvement of efficiency is the internal core driver of regional tourism eco-efficiency, but the essence of eco-efficiency improvement lies in technological progress. In the analysis of the impact of external drivers on tourism eco-efficiency, tourism economy scale, tourism industry structure, technological innovation, and economic development are the crucial external factors to eco-efficiency enhancement. This work can serve as a guide for the high-level growth of regional tourism industry.

Analysis of Eco-efficiency Change according to Waste Treatment Scenarios

Analysis of Eco-efficiency Change according to Waste Treatment Scenarios

Spatiotemporal Evolution of Tourism Eco-Efficiency in Major Tourist Cities in China

Tourism development consumes ecological resources to varying extents while bringing economic benefits; tourism eco-efficiency (TEE) assessment has thus become an area of major focus in destination sustainability research. This paper intends to examine the spatiotemporal characteristics and driving factors of eco-efficiency changes in 36 tourist cities on the Chinese mainland from 2010 to 2019, using a super-slacks-based measure (SBM) model, the data envelopment analysis (DEA)–Malmquist index, spatial correlation, and regression analysis. In contrast to the previous work, this work explores TEE among major tourist cities in China by considering the undesirable outputs of carbon emissions and sewage. The results show that (1) the TEE of most cities during the study period was low but increasing; there were significant spatial differences among different cities, and the eco-efficiency of the same city fluctuated over time. (2) The TEE was globally uncorrelated, but low-eco-efficiency areas were adjacent to each other and formed agglomerates, enhancing the negative spillover effect. (3) Despite fluctuations, the Malmquist indices exhibited positive trends, which resulted from the technical progress index rather than the technical efficiency index. (4) Socioeconomic development significantly promoted TEE. This research reveals the evolutionary law of TEE on the urban scale and explores the impact of social and economic development on TEE, which can provide a reference for policymaking and enrich research on destination sustainability.

Detection and attribution of changes in agricultural eco-efficiency within rapid urbanized areas: A case study in the Urban agglomeration in the middle Reaches of Yangtze River, China

The rapid urbanization and industrialization have caused excessive utilization of natural resources, which seriously threatened food security and ecological security in the world. Improving agricultural eco-efficiency (AEE) to obtain greater agricultural output at a lower environmental consume, is an significant part of agricultural sustainable development. However, the existing studies ignore agricultural carbon absorption when measuring the AEE, which leads to evaluating results distortive to some extent. Additionally, few research focuses on this topic within the rapid urbanized areas where the population, land and agricultural industry have undergone great changes. Thus, this study attempts to take the Urban Agglomeration in the Middle Reaches of Yangtze River (UAMRYR) in China as a case study and customize a new measurement system of AEE. The super slack-based measure (Super-SBM) model and Tobit model were applied to evaluate AEE and analyze the attribution of its spatiotemporal changes at the county level during 2000–2018. The results show that the average AEE value of the UAMRYR decreased from 0.534 in 2000 to 0.490 in 2005, and then showed an increasing trend to 0.677 in 2018. The spatiotemporal pattern revealed that the number of counties with high and medium–high AEE was increasing, while the number of counties with medium–low and low AEE continued to decrease from 2000 to 2018. Furthermore, there was a positive spatial correlation of AEE during the study period. The magnitude and direction of attribution in changes of AEE indicates that socioeconomic development, undesirable inputs reducing, the tolerance of crops to harsh environment improving, and investment in agricultural science and technology increasing could effectively improve the AEE. These findings have important implications for promoting agriculture highly-efficient utilization and sustainable development in China as well as other regions or countries with rapid urbanization in the world.

Assessing eco-productivity change in Chilean municipal solid waste services

The management of municipal solid waste (MSW) is a public service that affects the environment and public health. This study sought to assess the eco-productivity change (i.e., temporal dynamics of eco-efficiency) of a sample of municipalities in the provision of MSW management services. The Malmquist-Luenberger Productivity Indicator (MLPI) and its drivers, namely eco-efficiency and technical changes, were employed to estimate the eco-productivity change of each municipality. The empirical application was examined in 313 Chilean municipalities from to 2015–2019. Based on the results, on average, Chilean municipalities improved their eco-productivity, with eco-efficiency change being the main driver of this improvement.

Eco-efficiency estimation with quantile stochastic frontiers: Evidence from the United States

This paper based on quantile stochastic frontier framework constructs quantile eco-efficiency measures. Using the estimates from the quantile stochastic frontier, the eco-performance of the U.S. states for nitrogen oxides (NOX), carbon dioxide (CO2), and sulfur dioxide (SO2) emissions is evaluated. A decoupling analysis involving the evaluation of the nonsynchronous change among states' economic output and environmental degradation levels is also performed. The findings suggest that U.S. states have followed a decoupling process among their GDP and emission levels over the period 1990–2017. In addition, a quantile eco-productivity change estimator is presented alongside with its main components (i.e. quantile eco-technical change and quantile eco-efficiency change). Our findings suggest that over the examined period states’ eco-productivity levels have been improved driven both from their eco-technical and eco-efficiency change levels.

Eco-Efficiency for the G18: Trends and Future Outlook

Eco-efficiency is an important ecological indicator for tracking the progress of how countries’ environmental-adjusted economic activity changes over time. The objective of this research is to calculate country-level eco-efficiency for a group of 18 major countries (G18) that are part of the G20. First, the data envelope analysis (DEA) method is used to calculate eco-efficiency scores. Second, the Malmquist productivity index (MPI) is used to examine how eco-efficiency changes over time. Eco-efficiency is forecast to the year 2040 using automated forecasting methods under a business-as-usual (BAU) scenario. Over the period 1997 to 2040, eco-efficiency varies widely between these countries with some countries reporting positive growth in eco-efficiency and other countries reporting negative growth. Eco-efficiency leaders over the period 1997 to 2019 and 2019 to 2040 include Australia, Brazil, France, Germany, Great Britain, Italy, Japan, Russia, and the United States. Laggards include Canada, China, India, and Indonesia. These laggard countries recorded negative growth rates in eco-efficiency over the period 1997 to 2019 and 2019 to 2040. Negative eco-efficiency growth points to a worsening of environmental sustainability. Large variations in eco-efficiency between countries make it more difficult to negotiate international agreements on energy efficiency and climate change. For the G18 countries, the average annual change in MPI over the period 1997 to 2019 was 0.5%, while the forecasted average annual change over the period 2019 to 2040 was a 0.1% decrease. For the G18 countries, there has been little change in eco-efficiency. The G18 are an important group of developed and developing countries that need to show leadership when it comes to increasing eco-efficiency.

Regional eco-efficiency of the agricultural sector in V4 regions, its dynamics in time and decomposition on the technological and pure technical eco-efficiency change

Research background: Agriculture plays a vital role in producing food to ensure food security, but it is one of the biggest contributors to environmental pollution. One of the main goals of the new CAP is to set higher ambitions for environmental actions, which brings into the front the concept of agricultural eco-efficiency. The notion of eco-efficiency includes the economic and also ecological dimensions of sustainable agriculture.
 Purpose of the article: The main goal of this paper is to evaluate the eco-efficiency of agricultural production and its dynamics during the years 2013, 2015, and 2017 of NUTS 2 regions within the Visegrad 4 (V4), i. e. The Czech Republic, Slovakia, Hungary, and Poland. The part of the main goal is to verify the research hypothesis that all the biggest agriculture producers are eco-efficient.
 Methods: V4 regional eco-efficiency of the agricultural sector is expressed by the Malmquist productivity index and is estimated using the output-oriented Data envelopment analysis (DEA) model, under the assumption of constant return to scale (CRS). The Malmquist index is decomposed to technical eco-efficiency change (EC) and technological change (TC). Based on the eco-efficiency, technological and pure technical eco-efficiency change, V4 regions are classified into three groups: the most progressive regions, the progressive regions, and the regressive regions.
 Findings & value added: CZ02: Central Bohemia, CZ04: Northwest, HU33: Dél-Alföld, HU31: Észak-Magyarország, HU32: Észak-Alföld, PL21: Malopolskie, PL41: Wielkopolskie, SK01: Bratislava region, and SK02: Western Slovakia have an eco-effective agricultural sector, the remaining V4 regions have eco-ineffective agricultural sector. The research hypothesis that all the biggest agricultural producers are eco-effective is not confirmed. During the analyzed years, 19 V4 regions improve their agricultural eco-efficiency. The main contributor to eco-efficiency improvement is technological progress, which indicates that producers implement innovations that lead to more eco-efficiency agricultural production.

Coordinated Development of Urban Land Use and Ecological Economics in China

To analyze the coordination between land use and the ecological economy in China, ecoefficiency and land use intensity were measured using the nonradial, nonoriented slacks-based measure (SBM) and the vertical and horizontal scatter degree method. The TOPSIS method was then used to comprehensively evaluate regional differences in coordination. Our research indicates that the level of coordinated development between intensive urban land use and the ecological economy in China showed an overall upward trend from 2006 to 2017. The level of coordination was high in Beijing, Shanghai, and Tianjin and was low in Gansu, Ningxia, and Xinjiang. Changes in ecoefficiency were not consistent with the degree of coordination, and intensive urban land use was positively correlated with the level of coordination, which showed a mutually reinforcing relationship. Improving ecoefficiency is necessary for intensive urban land use, and for ecological improvement, coordinated development between ecoefficiency and urban land use intensity is essential. The establishment of environmentally friendly land use patterns could promote urban land use.

Assessment of eco-efficiency change considering energy and environment: A study of China’s non-ferrous metals industry

In this paper, we comprehensively consider the environment and economic performance by employing non-radial distance function to study the regional eco-efficiency of China’s Non-ferrous Metals Industry (NMI) during 2000–2016, from the perspective of total-factor through Data Envelopment Analysis (DEA)-Malmquist analysis framework. The change of regional technology gap ratio and the source of regional eco-inefficiency is also explored. Moreover, this paper analyzes the evolution of regional eco-efficiency and the main factors that contribute to changes in eco-efficiency. The results indicate that: First, the eco-efficiency of China’s NMI has improved and has shown a certain degree of regional heterogeneity. Second, the main source of eco-inefficiency is management inefficiency in eastern China. The central, western and northeastern China all showed an increasing trend of technology gap inefficiency and a declining trend of management inefficiency during the sample period. Third, eastern China is regarded as a technology leader. The improvement of eco-efficiency in the central and northeastern China is mainly due to the promotion of technological progress, while the western region relies on the improvement of technical efficiency. The study suggests that strengthening scientific and technological research, promoting inter-regional technical exchanges are particularly important for eco-efficiency improvement and regional coordinated development in China’s NMI.

Measuring eco-efficiency and its convergence: empirical analysis from China

At present, the contradiction between economic development and resource and environmental sustainability has become increasingly acute in China. Improving the quality of the ecological environment has become an important strategic goal for China’s national economic and social development. In this paper, we used the panel data of 30 provinces in China from 1986 to 2016 to measure the eco-efficiency and its decomposition indexes based on a non-radial metafrontier Malmquist-Luenberger data envelopment analysis model. The results showed that the eco-efficiency grows at an annual rate of 0.7% on the whole, with the technical efficiency decreasing at an annual rate of 0.6%, the innovation effect increasing at an annual rate of 2.3%, and the technical leadership effect decreasing at an annual rate of 1%. In the sample study period, the cumulative growth rates of eco-efficiency change index, technical efficiency change index, innovation effect, and technical leadership effect were 20.4%, − 19.4%, 70.5%, and − 30.7%, respectively. It was also found that regional eco-efficiency decreased from east to west. Furthermore, convergence test results showed that there were four convergence clubs and three divergent individuals in terms of eco-efficiency. Areas with high eco-efficiency tended to converge with areas with high eco-efficiency and vice versa.

Measuring Regional Eco-Efficiency in China (2003-2016): A "Full World" Perspective and Network Data Envelopment Analysis.

Eco-efficiency enhancement is an inherent requirement of green development and an important indicator of high-quality development in general. It aims to achieve the coordinated development of nature, the economy, and society. Therefore, eco-efficiency measurements should focus on not only total factor input, but also process analysis. Based on the “full world” model in ecological economic theory, this study constructed a theoretical framework for a composite economic-environmental-social system that reflects human welfare and sustainability. To this end, using network data envelopment analysis (DEA), this study established a staged eco-efficiency evaluation model that uses economic, environmental, and social factors to measure the overall and staged eco-efficiency of China’s provinces from 2003 to 2016 and analyze its spatiotemporal characteristics. A geographically weighted regression (GWR) model was also used to analyze the influencing factors of eco-efficiency changes and the spatial differentiation in their effect intensity. The findings were as follows: (1) China’s overall eco-efficiency is still at a low level. It varies significantly from region to region, and only three regions are at the frontier of production. The eastern region has the highest eco-efficiency, followed by the central region, and the gap between the central and western regions has gradually narrowed. In terms of staged efficiency, the level of eco-efficiency in the production stage is less than in the environmental governance stage, which is less than that in the social input stage. (2) In terms of the efficiency of each stage, the efficiency level of the production stage showed a downward trend throughout the entire process, and the decline in the central and western regions was more obvious. The social input stage and the environmental governance stage both showed upward trends. The social input stage showed a higher level, and the increase was relatively flat during the period of study. Efficiency continued to rise during the environmental governance stage from 2003 to 2010 and rose overall, but with some fluctuations from 2011 to 2016. (3) Geographically weighted regression showed that the effects of the influencing factors on eco-efficiency had obvious spatial heterogeneity. The factors affecting overall, production stage, and social input eco-efficiency were, in order of effect intensity from high to low, economic growth level, marketization level, and social input level. In terms of environmental governance, social input level had the greatest impact, followed by economic growth; marketization level did not show a significant impact.

Tracking urban sustainability transition: An eco-efficiency analysis on eco-industrial development in Ulsan, Korea

The ecologically efficient transformation of natural resources into economic output is a critical pathway to achieve urban and industrial sustainability. Eco-efficiency approach offers an effective tool to uncover both the status and trends of such a transformation. This paper applied a modified eco-efficiency approach in combination with data envelopment analysis, to analyze the sustainability transition of Ulsan metropolis, Korea, under a fifteen years’ promotion (2000–2015) of eco-industrial development (EID). In the design for analysis, eco-efficiency change – both at industrial park level and the regional level – was investigated to analyze whether eco-efficiency improvements at the park level coincide with those at the regional level. Our main findings were highlighted as: At the regional level, from 2000 to 2015, eco-efficiency of industrial waste generation and energy use has improved by 35.0% and 21.4%, respectively, driven by a significant reduction in waste and energy intensities attributable to technological improvements (EID promotion and urban-industrial symbiosis). At the industrial park/complex level, two national eco-industrial parks (EIPs) in Ulsan showed highest eco-efficiency (pure technical efficiency was 1.0) in analytical years, compared with nine regional industrial complexes. At both levels of analysis, EIPs stood out as eco-efficient and their contribution to urban sustainability transition was overwhelming. Moreover, EIP implementation and urban-industrial symbiosis in Ulsan were identified as the major drivers of regional EID policy. Based on our critical findings, EID was highlighted as a preventative and regenerative approach to improve eco-efficiency at the regional and industrial park level, enlightening other regional and local initiatives towards urban sustainability.

Ecoefficiency, environmental regulation opportunity costs, and interregional industrial transfers: Evidence from the Yangtze River Economic Belt in China

The construction of the Yangtze River Economic Belt is a major strategic measure for coordinating China's regional development. In promoting regional integration, the belt has shown a trend in industrial gradient transfers, especially polluting industries. Measuring the impact of environmental regulations on the economic output and marginal changes in the output caused by pollution reduction is particularly practical and important. This paper analyzes the ecoefficiency, environmental regulation opportunity costs, and interregional industrial transfer strategies for the provinces in the belt under a scenario paradigm. The nonparametric method is used to construct an ecoefficiency measure model. The ecoefficiency changes and differences under various regulations are measured from the temporal (historical) and spatial (provincial) perspectives, respectively. The ecoefficient provinces in the eastern region can be considered benchmarks for the central and western regions to achieve ecoefficiency. A comparative analysis is conducted to assess the opportunity costs of regulations on different pollutants. The results show that a certain degree of difference in regulations must be maintained across the belt to coordinate economic and environmental development. Based on the potential differences in regulations, an appropriate gradient transfer direction for polluting industries is proposed for the provinces, and related policy recommendations are provided.

NonLinear Effects of Environmental Regulation on Eco-Efficiency under the Constraint of Land Use Carbon Emissions: Evidence Based on a Bootstrapping Approach and Panel Threshold Model.

Eco-efficiency has been receiving attention worldwide, and the effective implementation of environmental regulations (ERs) has become crucial to regional eco-efficiency. This paper uses a method combining mixed directional distance function and bootstrapping approach to investigate the spatial and temporal distribution characteristics of eco-efficiency under the constraint of land use carbon emission in China from 2004 to 2016. The nonlinear relationship between ER and eco-efficiency is observed with a panel threshold model. Results from empirical tests reveal that eco-efficiency in China during the study period has an upward trend, and the spatial and temporal distribution of eco-efficiency is unbalanced and concentrated. Technical innovation and land marketization (LM) shows double threshold, whereas industrial structure (IS) has a single threshold effect. LM has a promotional effect on eco-efficiency, which differs in the promotion before and after promotion across the threshold value. Reasonable ER can reduce cost by stimulating the innovation of green production technology and achieves a win-win situation between environment and output. This finding further verifies that the ER for eco-efficiency under the constraint of land use carbon emission conforms to the Porter hypothesis. The effect of ER on eco-efficiency changes from negative to positive with the increase of IS level. Adjusting the ownership structure and increasing the proportion of green achievements in the promotion and assessment of officials are important measures in the upgrading of eco-efficiency.

Use of interval data envelopment analysis, goal programming and dynamic eco-efficiency assessment for sustainable supplier management

Two big challenges for sustainable supplier management consist of (1) properly integrating the multiple factors necessary to measure the sustainability performance of suppliers and (2) modeling the dynamic nature of those factors. In this study, we demonstrate the aggregation of environmental and economic supplier performance criteria into a single (eco-efficiency) index using Data Envelopment Analysis (DEA) for interval data. Suppliers are pre-qualified according to this index and are allocated orders using multiple criteria models for single and multiple sourcing. In multiple sourcing, preemptive, non-preemptive and fuzzy goal programming models are used with purchase price and eco-efficiency as conflicting objectives. Finally, eco-efficiency change is assessed using an approach based on the Malmquist productivity index, which monitors suppliers over time. Thus, our methodology can be used for supplier evaluation, selection and monitoring. Data obtained from an auto parts manufacturer is used to illustrate the proposed method.

Assessing eco-efficiency through the DEA analysis and decoupling index in the Latin America countries

This study was developed according to a two-step approach. In the first step, we provide an investigation of the changes in eco-efficiency under constant and variable return to scale, while on a second step the evaluation of the decoupling elasticity will be given. The impacts of energy, economic and environmental determinants (inputs) on the performance indicators of eco-efficiency were calculated as the inverse of the carbon intensity (ratio of the GDP over the CO2 emissions, both from the World Development Indicators database), the changes in eco-efficiency and the decoupling elasticity between CO2 emissions, and economic growth changes. Data was used for 16 Latin America countries, according to five-year periods, from 1994 to 2013. For all the five-time span considered, it is worth noting, that the degree of technical efficiency for the Latin America countries is lower than the degree of technological efficiency, thus indicating that a portion of the overall inefficiency is due to the fact that these countries are producing below the production frontier rather than to an inefficient use of technology. On average, the results have confirmed that the technological scale change in energy production is the dominant factor influencing the optimal production frontier in the sample of countries under analysis. Complementarily, according to the mixed results from the decoupling analysis, we may conclude that the increase/decrease of the CO2 per capita emissions was due to other economic and environmental factors rather than to a negative/positive effect of the GDP growth rate.