Showing papers on "Tobit model published in 2022"
TL;DR: In this article , the authors investigate the effect of ICT on sustainable development and the mechanisms through which the effect is modulated, and the results show that ICT has a positive and significant effect on sustainability development.
52 citations
TL;DR: Zhang et al. as discussed by the authors used the Super-efficiency DEA mothod to calculate the regional ecological efficiency, and selected a Tobit model to verify the impact of green finance and natural resource abundance on Chinese regional eco efficiency.
34 citations
TL;DR: In this paper , the urban land use efficiency (ULUE) of 57 cities in the Yellow River Basin (YRB) from 2005 to 2017 with the super epsilon based measure (Super-EBM) model, analyzed its difference characteristics and evolution trend by using the Theil index and kernel density function, revealed its spatial correlation by Moran index and LISA clustering, and explored its influencing factors by the Tobit model.
32 citations
TL;DR: Based on the panel data of China's 31 energy-mineral cities in 2007-2018, the energy eco-efficiency is evaluated, Tobit regression and threshold regression models are constructed to test the effects of heterogeneous environmental regulations on energy ecoefficiency as discussed by the authors .
31 citations
TL;DR: In this article , the Tobit model was used to analyze the impact of green finance on energy efficiency, and the results showed that green finance has not significantly forced the improvement in energy efficiency.
30 citations
TL;DR: In this article , the authors examined the role of inherent differences in development cycle and resource endowment and highlighted the need for a targeted revitalization policy in resource-based cities in China. But, they did not consider the impact of road networks and science and technology on urban land use efficiency.
26 citations
TL;DR: Wang et al. as discussed by the authors used the DEA-Malmquist index to measure regional green innovation efficiency, and constructed a Tobit regression model to explore the impact of green finance and environmental regulations on the green innovation efficient in these three regions.
Abstract: Innovation is the first driving force for development, and green innovation efficiency (GIE) plays a very important role in regional sustainable development. Data from 31 provinces and cities in China from 2011 to 2020 were used to select the proportion of energy saving and environmental protection costs in GDP as the green financial value, and the proportion of industrial pollution control input in GDP as the environmental regulation index. Green innovation efficiency is measured from two aspects of input and output by DEA method, and carried out for 31 provinces and cities in three regions. Using the DEA-Malmquist index to measure regional green innovation efficiency, the results show that the green innovation efficiency in three regions basically presents an upward trend, but the upward trend of green innovation efficiency is different between the three regions. A Tobit regression model is constructed to explore the impact of green finance and environmental regulations on the green innovation efficiency in these three regions. Research indicates that environmental regulations, the proportion of output value of tertiary industry in GDP, industrial structure, and foreign direct investment have significant impacts on the green innovation efficiency in all regions. Green finance, industrial structure, and power consumption have a significant impact on the green innovation efficiency in eastern China. Industrial structure has a significant impact on green innovation efficiency in central China, while power consumption and industrial structure have a significant impact on green innovation efficiency in western China. Therefore, each region needs to improve the standard of environmental regulation innovation, and introduce and use foreign investment in a scientific and reasonable way so as to promote the improvement of industrial infrastructure.
26 citations
TL;DR: In this article , the authors calculated the carbon emission efficiency of the Yellow River basin from 2005 to 2019 based on the slack-based measured directional distance function (SBM-DDF) model and combined with the Malmquist-Luenberger (ML) index.
Abstract: The Yellow River basin (YRB) is China’s most critical energy consumption and coal production area. The improvement of carbon emission reduction efficiency in this area is the key for the Chinese government to achieve the 2030 carbon peak and 2060 carbon neutral (“30.60”). Given this, this study first calculates the carbon emission efficiency of YRB from 2005 to 2019 based on the slack-based measured directional distance function (SBM-DDF) model and combined with Malmquist–Luenberger (ML) index and decomposes the carbon emission efficiency of each province. Then, a panel Tobit model with random effect is constructed to measure the influencing factors and their influence degree of carbon emission efficiency of YRB. Finally, the main influencing factors are selected, and policy suggestions on how to improve the carbon emission efficiency of each province are put forward with the help of the coupling coordination degree (CCD) model. The results show that first, the carbon emission efficiency of each province is significantly different, but it shows a fluctuating upward trend on the whole. Second, the reasons for the rise or decline of the ML index in different provinces are different. Therefore, the development strategies of different provinces should be formulated from the perspective of accelerating technological progress and improving technical efficiency. Finally, the calculation results of influencing factors and coupling coordination degrees show that provinces with high coupling coordination degrees should focus on developing per capita power consumption and controlling per capita power consumption to consolidate the actual urbanization process and industrial structure adjustment. Provinces with low coupling coordination degrees should focus on maintaining the urbanization process and increasing the development of the tertiary industry. Therefore, to fundamentally reduce carbon emissions in YRB areas, we need to consider implementing differentiated emission reduction schemes based on national strategic objectives and in combination with the development characteristics of various provinces.
21 citations
20 citations
TL;DR: In this paper , the feasibility of using videoconferencing (VC) administered interviews and to derive an EQ-5D-5L value set for Italy was evaluated.
Abstract: To test the feasibility of using videoconferencing (VC) administered interviews and to derive an EQ-5D-5L value set for Italy.Preferences were collected using the EuroQol standardized valuation protocol (EQ-VT) administered via VC. Two valuation methods were employed, composite time trade-off (cTTO) and discrete choice experiment (DCE). Technical, organizational and protocol feasibility were tested in a pilot of 198 interviews. Upon positive assessment, data collection continued with a target sample of 1000-1200 participants including the pilot. Quality control (QC) procedures were employed to monitor interviewers' performance during the pilot and the data collection. Data were modelled using GLS, Tobit, Logit and Hybrid models with different error specifications. Monotonicity of coefficients, statistical significance, and theoretical considerations informed the model choice.Dropouts and technical problems occurred in less than 5% of the 198 pilot interviews. Protocol compliance was demonstrated with significant improvements in QC parameters and limited interviewers' effects, for all interviewers. Overall, interviewers were satisfied with this mode of administration, highlighting it allows flexibility and efficient scheduling. Based on these results, VC was deemed as a feasible mode of administration. The study collected preferences for 1182 responders, including the pilot interviews. The demographic characteristics of the sample were representative of the Italian general population for age, gender and geographical macro-areas. The hybrid Tobit heteroscedastic model without constant estimated on the full sample (including pilot) was selected for the derivation of the value set. Values ranged from -0.571 for the worst health state (55555) to 1 for the best health state (11111). Pain/discomfort registered the largest decrement, followed by mobility, anxiety/depression, self-care, and usual activities. 523 health states were worse than dead.VC is viable for the conduct of valuation interviews. The Italian value set for the EQ-5D-5L can be used for value determinations of health technologies.
19 citations
TL;DR: In this article , the authors employed a hybrid methodology that combines spherical fuzzy sets based analytical hierarchical process (SFS-AHP) and data envelopment analysis (DEA), which provided a solid basis for efficiency analysis.
TL;DR: In this article , the authors used a dataset collected by the authors themselves of more than 2000 households in 2016, which was a random, nationally representative sample of 100 rural villages among five provinces in China.
TL;DR: Based on the panel data of 11 provinces and cities in the Yangtze River Economic Belt from 2005 to 2018, Wang et al. as discussed by the authors used the SBM-DEA efficiency model with undesired output to measure the green innovation efficiency.
Abstract: Based on the panel data of 11 provinces and cities in the Yangtze River Economic Belt from 2005 to 2018, this paper uses the SBM-DEA efficiency model with undesired output to measure the green innovation efficiency of the Yangtze River Economic Belt. The panel Tobit empirical analysis model was used to quantitatively analyze the impact of three different forms of government environmental regulations on the efficiency of green innovation. The research results show that the government’s mandatory environmental regulations and government financial subsidies for green innovation technology are two regulatory methods that positively promote the efficiency of regional green innovation, but government investment in environmental governance has a negative impact on the efficiency of regional green innovation. Then the study found that this negative impact has a significant inflection point effect: when it exceeds a certain threshold, the negative impact turns into a positive effect. At the same time, the impact of environmental regulations on the efficiency of green innovation has significant regional heterogeneity, and the three environmental regulations have a greater impact on downstream provinces and cities.
TL;DR: Zhang et al. as mentioned in this paper investigated the impact of increasingly active land transfer on farmers' willingness to pay for straw return, and found that only 37.69% of farmers were willing to pay.
TL;DR: Based on the panel data of Changjiang Economic Corridor (CEC), this paper included agricultural carbon emissions as an unwanted output into the evaluation index system for agricultural carbon emission performance (ACEP), and measured the ACEP of the 11 provinces in the CEC of 2005-2018, using the minimum distance to weak efficient frontier (MinDW) model.
Abstract: Based on the panel data of Changjiang Economic Corridor (CEC), this paper includes agricultural carbon emissions as an unwanted output into the evaluation index system for agricultural carbon emissions performance (ACEP), and measured the ACEP of the 11 provinces in the CEC of 2005–2018, using the minimum distance to weak efficient frontier (MinDW) model. In addition, a Tobit model was constructed for empirical analysis on the impactors of CEC ACEP. The results show that: In general, the CEC achieved an excellent ACEP, with certain differences between the provinces; the ACEP trends varied between the upper, middle, and lower reaches of the CEC, and the lower reaches had a much higher ACEP than the upper and middle reaches; the results of Tobit model demonstrate that industrial upgrading and rural power consumption have significant positive correlations with CEC ACEP, while human capital, planting structure, and agricultural disaster have significantly negative correlations with CEC ACEP.
TL;DR: In this article , the authors focused on the sustainability of the intermediate function of banks, especially in recent years when interest rates on deposits have been at a minimum level, and they applied the output-oriented DEA model using deposits, labor costs, and capital as input variables; on the other side, they used loans and investments as output variables.
Abstract: Since the beginning of the application of the Data Envelopment Analysis (DEA) model in various areas of the economy, it has found its wide application in the field of finance, more specifically banks, in the last few years. The focus of this research was to determine the sustainability of the intermediate function of banks, especially in recent years when interest rates on deposits have been at a minimum level. The research was divided into two parts, wherein the first part determined the efficiency of the intermediate function of banks in the countries of the Western Balkans in the period from 2015 to 2019. The second part approached the regression analysis in which we determined the influence of the bank size, type of bank, and mergers and acquisitions (M&A) activity on the defined efficiency. In the first stage we applied the output-oriented DEA model using deposits, labor costs, and capital as input variables; on the other side, we used loans and investments as output variables. We used data from the revised financial statements of the banks operating in Serbia, Bosnia and Herzegovina, Montenegro, North Macedonia, and Albania. The results of our study showed that there is a difference in efficiency levels between countries and within countries in the considered time period. Furthermore, Tobit regression analysis showed a significant and negative influence of the bank type and M&A on relative technical efficiency of banks, and a positive and significant relationship between bank size and relative efficiency. These findings suggest that large commercial banks can sustain on the West Balkan market. It is to be expected that less efficient small banks will be taken over by large and more efficient banks.
TL;DR: Wang et al. as discussed by the authors used logistic regression and Tobit regression model to analyze the impact of farmland tenure fragmentation on farmland abandonment and showed that the farmland abandonment rate decreased when the average plot area increased by 1 mu (1 mu = 666.67 m2).
TL;DR: In this article , a novel outlier-resistant filtering problem is concerned for a class of networked systems with dead-zone-like censoring under the weighted try-once-discard protocol (WTODP).
Abstract: In this paper, a novel outlier-resistant filtering problem is concerned for a class of networked systems with dead-zone-like censoring under the weighted try-once-discard protocol (WTODP). To describe the phenomenon of dead-zone-like censoring, the sensor output is characterized by the Tobit model in which the censored region is restrained by specified left- and right-censoring thresholds. The WTODP is employed to decide the transmission sequence of sensors so as to alleviate undesirable data collisions. In the case of the measurement outliers, a saturation function is employed in the Tobit Kalman filter structure to constrain the innovations contaminated by the measurement outliers, thereby maintaining satisfactory filtering performance. By resorting to the approach of the matrix inequality, an upper bound is first obtained on the filtering error covariance where the gain matrix of the Tobit Kalman filter is carefully designed to minimize the obtained upper bound. Moreover, the exponential boundedness of the filtering error is analyzed in the mean square sense. Finally, the effectiveness of the proposed outlier-resistant filtering algorithm is verified by three practical examples.
TL;DR: In this paper , the authors adopted the two-stage Data Envelopment Analysis (DEA) methodology to measure energy efficiency among nine selected West African states and their influencing factors.
TL;DR: Li et al. as discussed by the authors explored the effects of environmental constraint target on green innovation efficiency by super efficiency slacks-based measure (SBM), panel Tobit and instrumental variables-two stage least square (IV-2SLS) models.
TL;DR: Wang et al. as discussed by the authors evaluated the influencing factors of coal consumption inefficiency in the energy intensive industries of China and suggested diverse policy recommendations to improve coal consumption efficiency and carbon emission reductions at the aggregate and disaggregate industrial level.
TL;DR: In this article , the impact of urban development on green development efficiency (GDE) was studied, and the Super-SBM model was introduced to measure the GDE of 41 cities in the Yangtze River Delta during 2009-2018.
Abstract: Green development is a significant concept that cannot be ignored in contemporary society. However, in the context of China’s transition from high-speed growth to high-quality development, the complex impact of urban development has brought great challenges to the urban green environment. In this paper, the impact of urban development on green development efficiency (GDE) was studied. First and foremost, a Super-SBM model was introduced to measure the GDE of 41 cities in the Yangtze River Delta during 2009–2018. Moreover, a Tobit model was used to analyze the correlation between four urban development factors, including economic development and GDE. According to the results, the mean GDE of the Yangtze River Delta is 0.824, and the GDE in most cities there has shown a fluctuating growth trend in this decade. By comparison, the GDEs of coastal cities and cities in the southeast of the Yangtze River Delta were generally higher than those of cities in the north, indicating that the green development is geographically unbalanced, and there is spatial heterogeneity in the area studied. The study’s results also suggest that the urban economic development, innovation level, and government planning play a significant role in stimulating urban green development, and that the expansion of urban construction area hinders the improvement of GDE.
01 Jan 2022
TL;DR: Based on the panel data of Changjiang Economic Corridor (CEC), this article included agricultural carbon emissions as an unwanted output into the evaluation index system for agricultural carbon emission performance (ACEP), and measured the ACEP of the 11 provinces in the CEC of 2005-2018, using the minimum distance to weak efficient frontier (MinDW) model.
Abstract: Based on the panel data of Changjiang Economic Corridor (CEC), this paper includes agricultural carbon emissions as an unwanted output into the evaluation index system for agricultural carbon emissions performance (ACEP), and measured the ACEP of the 11 provinces in the CEC of 2005–2018, using the minimum distance to weak efficient frontier (MinDW) model. In addition, a Tobit model was constructed for empirical analysis on the impactors of CEC ACEP. The results show that: In general, the CEC achieved an excellent ACEP, with certain differences between the provinces; the ACEP trends varied between the upper, middle, and lower reaches of the CEC, and the lower reaches had a much higher ACEP than the upper and middle reaches; the results of Tobit model demonstrate that industrial upgrading and rural power consumption have significant positive correlations with CEC ACEP, while human capital, planting structure, and agricultural disaster have significantly negative correlations with CEC ACEP.
TL;DR: In this article , the authors used descriptive statistics and Tobit model analysis techniques to estimate the magnitude of post-harvest losses of all crops and identify its determinants, including households with larger adult family size, higher levels of education attendance, and wealth status, large landholding size and damage of stored crops by insect pests infestation and/or rodent feeding.
Abstract: Abstract Background Reduction of post-harvest loses of crops are crucial tasks in ensuring food and nutrition security. However, a lack of knowledge on the extent of post-harvest losses and its associated impeding factors are posing major challenges to effectiveness of grain post-harvest loss management strategy and to scale up for all other crop types in Ethiopia. The study estimates the magnitude of post-harvest losses of all crops and identifies its determinants. Methodology A national-level agriculture survey data were obtained from the Central Statistical Agency of Ethiopia. Data were analyzed using descriptive statistics and Tobit model analysis techniques. Results The analysis shows 25.81% perceived annual average post-harvest losses of crops were obtained with considerable variation across the crop types. The main factors impeding post-harvest losses of crops were households with larger adult family size, higher levels of education attendance, and wealth status, large landholding size and damage of stored crops by insect pests infestation and/or rodent feeding due to utilization of traditional storage equipments, access to extension support services, cooperative marketing membership, and being far away from both all weathered roads and near local market centers due to a higher transaction costs associated with a lack of market information, contamination, and mechanical injuries. Conclusion Minimization of post-harvest losses of crops could be achieved through a holistic approach by providing short and long-term training on post-harvest management practices, promoting the use of post-harvest technologies, paying special attention to the institutional support systems (agriculture extension and rural credit services), strengthening the support for post-harvest handling technologies, reinforcing the existing farmer cooperative marketing, and improvements of the local market and road networking infrastructures of rural areas should be undertaken by the government in collaboration with non-government organizations.
TL;DR: Zhang et al. as discussed by the authors explored the impact of economic growth targets on green total factor productivity (GTFP) based on a panel Tobit model and two manual datasets of 30 Chinese provinces from 2002 to 2019.
Abstract: This study explores the impact of economic growth targets on green total factor productivity (GTFP) based on a panel Tobit model and two manual datasets of 30 Chinese provinces from 2002 to 2019. We find that economic growth targets significantly inhibit GTFP, which is more pronounced in provinces that have high incentives when setting targets, use hard constraints when announcing targets, and fulfill their targets. In addition, we find that economic growth targets inhibit GTFP by undermining economic efficiency and aggravating environmental pollution. Moreover, the command-controlled environmental regulations weaken the inhibitory effect on GTFP, while market-motivated environmental regulations aggravate this inhibitory effect. Our findings confirm that the promotion assessment system based on economic performance leads to the irrationality of local governments in establishing economic growth targets, and the local governments pursue economic growth at the cost of development quality and sustainability.
TL;DR: Zhang et al. as discussed by the authors measured the ecological welfare performance and the green economic efficiency of 11 cities in Zhejiang Province, China, from 2000 to 2019 by using the undesirable slack-based measure (SBM) model.
Abstract: China’s high-speed economic growth and severe environmental problems have resulted in a poor Environmental Performance Index and have affected China’s sustainable development and ecological welfare improvement. Therefore, exploring whether there is a certain relationship between the two and their influencing factors is an important way and a breakthrough to solve the problems regarding green economic progress and ecological welfare enhancement. To this end, by using the undesirable slack-based measure (SBM) model, this paper measures the ecological welfare performance and the green economic efficiency of 11 cities in Zhejiang Province, China, from 2000 to 2019. Through the methods of spatiotemporal evolution, coefficient of variation, coupling coordination degree, and the Tobit model, we found that: (1) The development trend of urban green economic efficiency and ecological welfare performance were both in a “U” shape that first fell and then rose; (2) The coupling coordination degree between green economic efficiency and ecological welfare performance showed a wave-like upward trend as a whole and most cities have entered a more advanced coupling coordination stage during the study period. The coefficient of variation revealed a downward trend; (3) The urbanization level, industrial structure, and government investment can promote the regional coordinated development, while the industrialization degree and the opening level had a negative impact on it; (4) The “Two Mountains” theory was beneficial to the improvement of regional urban green economic efficiency and ecological welfare performance and their coordinated development both in theory and practice. Finally, according to the findings, we offer relevant suggestions on making good use of the country’s preferential policies and informatization means from the perspective of the regional coordinated development.
TL;DR: Zhang et al. as discussed by the authors proposed a theoretical framework to address the impact of labor migration on crop diversification under the background of climate change; then, with the data collected from 499 households in the Hehuang Valley (HV), Tibetan Plateau, they explored the factors influencing the adoption of diversification by employing Tobit model.
TL;DR: In this paper , the use of various agrochemicals in watermelon farming in the southern region of Bangladesh and evaluated farmers' willingness to adopt organic inputs was evaluated. But no training was provided to the farmers to use agrochemical inputs and they used overdoses of different fertilizers and crop protective chemicals.
Abstract: Extensive and improper use of agrochemicals by the farmers is disrupting environmental conditions and endangering human health. The use of organic inputs is the most reasonable solution for ecological sustainability. This study assessed the use of various agrochemicals in watermelon farming in the southern region of Bangladesh and evaluated farmers' willingness to adopt organic inputs. Primary data were collected from 120 watermelon farmers of Khulna district. Adoption Quotient Index was employed to assess farmers' usage of agrochemicals, and a Tobit model was used to determine the factors influencing their usage. In addition, determinants of farmers' willingness to adopt organic inputs were identified through logistic regression. Results revealed that no farmers received any training on the use of agrochemicals. They used overdoses of different fertilizers and crop protective chemicals. The farmers' educational level, farming experience, and extension positively affected the use of agrochemicals, whereas farm size had a negative effect. About 65.8% of the watermelon farmers were willing to adopt organic inputs, and anticipated loss of production is the primary cause for unwillingness in adoption. Farmers' educational level, watermelon farming experience, and training positively influenced their willingness, while annual income had a negative impact. This study suggests conducting proper economic evaluation of watermelon production considering environmental and social costs, educating and providing training to the farmers on appropriate agrochemicals usage and organic inputs for sustainable watermelon production.
TL;DR: Wang et al. as discussed by the authors integrated carbon emissions into the urban land use efficiency evaluation index system, measured low-carbon urban land usage efficiency using a non-radial directional distance function and analyzed its spatial and temporal evolution and its influencing factors using a combination of a kernel density estimation method and a Tobit model.
Abstract: The development and use of urban land is a major source of carbon emissions. How to reduce carbon emissions in the process of urban land use without harming the economy has become an extremely important issue. This paper integrating carbon emissions into the urban land use efficiency evaluation index system, measures low-carbon urban land use efficiency using a non-radial directional distance function and analyses its spatial and temporal evolution and its influencing factors using a combination of a kernel density estimation method and a Tobit model. The study found that: (1) China’s low-carbon urban land use efficiency shows a fluctuating development and tends to converge; (2) there is much room for reducing land input and carbon emissions in China, and in 2016 alone, land input and carbon emissions in the sample could be reduced by 10.38% and 5.31%, respectively; (3) at the national level, land finance, economic level and population density have a positive impact on low-carbon urban land use efficiency, while the traffic level has negative effects, and these effects show regional heterogeneity. Accordingly, the paper proposes corresponding policy recommendations.
TL;DR: Wang et al. as discussed by the authors used a super-SBM model, kernel density estimation and Tobit regression model to analyze regional differences and influencing factors of EALU for 31 provinces in China from 2000 to 2019.
Abstract: Eco-efficiency of arable land utilization (EALU) emphasizes efficient coordination between land use systems and ecosystems. It is therefore of great significance for agricultural sustainability based on the systematic assessment of EALU. This study took carbon emissions and non-point source pollution resulting from arable land utilization into the measurement system of EALU, and a super-SBM model, kernel density estimation and Tobit regression model were used to analyze regional differences and influencing factors of EALU for 31 provinces in China from 2000 to 2019. The results showed that there was an upward trend in EALU in China from 0.4393 in 2000 to 0.8929 in 2019, with an average annual growth rate of 4.01%. At the regional level, the EALU of three categories of grain functional areas generally maintains an increasing trend, with the highest average value of EALU in main grain marketing areas (MGMAs), followed by grain producing and marketing balance areas (GPMBAs) and main grain producing areas (MGPAs). There are obvious differences in EALU among provinces, and the number of provinces with high eco-efficiency has increased significantly, showing a spatial distribution pattern of “block” clustering. In terms of dynamic evolution, kernel density curves reflect the evolution of EALU in China and grain functional areas with different degrees of polarization characteristics. The results of Tobit regression show that natural conditions, financial support for agriculture, science and technology inputs, level of industrialization, agricultural mechanization, and the living standards of farmers are significant factors resulting in regional disparities of EALU. Therefore, this study proposes the implementation of differentiated arable land use/agricultural management strategies to improve the sustainable utilization of arable land.