The local-neighborhood effect of green credit on green economy: a spatial econometric investigation.
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ABSTRACT:
SUBMITTER: Lei X
PROVIDER: S-EPMC8316542 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundIn 2013, an unusually high incidence of biliary tract cancer among current or former workers of the offset color proof printing department of a printing company in Osaka, Japan, was reported. The purpose of this study was to examine whether distance from the printing factory was associated with incidence of biliary tract cancer and whether incident biliary tract cancer cases clustered around the printing factory in Osaka using population-based cancer registry data.MethodsWe estimated the age-standardized incidence ratio of biliary tract cancer according to distance from this printing factory. We also searched for clusters of biliary tract cancer incidence using spatial scan statistics.ResultsWe did not observe statistically significantly high or low standardized incidence ratios for residents in each area categorized by distance from the printing factory for the entire sample or for either sex. The scan statistics did not show any statistically significant clustering of biliary tract cancer incidence anywhere in Osaka prefecture in 2004-2007.ConclusionsThere was no statistically significant clustering of biliary tract cancer incidence around the printing factory or in any other areas in Osaka, Japan, between 2004 and 2007. To date, even if some substances have diffused outside this source factory, they do not appear to have influenced the incidence of biliary tract cancer in neighboring residents.
| S-EPMC5008965 | biostudies-literature
Project description:Rapidly developing countries contain both the bulk of intact natural areas and biodiversity, and the greatest untapped natural resource stocks, placing them at the forefront of "green" economic development opportunities. However, most lack scientific tools to create development plans that account for biodiversity and ecosystem services, diminishing the real potential to be sustainable. Existing methods focus on biodiversity and carbon priority areas across large geographies (e.g., countries, states/provinces), leaving out essential services associated with water supplies, among others. These hydrologic ecosystem services (HES) are especially absent from methods applied at large geographies and in data-limited contexts. Here, we present a novel, spatially explicit, and relatively simple methodology to identify countrywide HES priority areas. We applied our methodology to the Gabonese Republic, a country undergoing a major economic transformation under a governmental commitment to balance conservation and development goals. We present the first national-scale maps of HES priority areas across Gabon for erosion control, nutrient retention, and groundwater recharge. Priority sub-watersheds covered 44% of the country's extent. Only 3% of the country was identified as a priority area for all HES simultaneously, highlighting the need to conserve different areas for each different hydrologic service. While spatial tradeoffs occur amongst HES, we identified synergies with two other conservation values, given that 66% of HES priority areas intersect regions of above average area-weighted (by sub-watersheds) total forest carbon stocks and 38% intersect with terrestrial national parks. Considering implications for development, we identified HES priority areas overlapping current or proposed major roads, forestry concessions, and active mining concessions, highlighting the need for proactive planning for avoidance areas and compensatory offsets to mitigate potential conflicts. Collectively, our results provide insight into strategies to protect HES as part of Gabon's development strategy, while providing a replicable methodology for application to new scales, geographies, and policy contexts.
| S-EPMC5464629 | biostudies-literature
Project description:BackgroundThe progress of green credit in China is accelerating, but its development is uneven and insufficient in different regions. And whether the issuance of green credit can effectively promote the improvement of the environment and economy is not well understood.ObjectivePrevious research has found that green credit promotes economic growth through improvement of the industrial structure and green technological innovation. However, these studies have not considered the positive externality of environmental improvement even though environmental improvement and economic growth are requirements of the sustainable development concept.MethodsWe use the chain-mediated model to estimate the impact of green credit issuance on the economic growth of different provinces since the large-scale implementation of green credit in China with data from 2008 to 2016.Results and conclusionThis paper shows that the issuance of green credit can improve labor supply rather than labor productivity through the improvement of air quality to achieve regional economic growth. Such a chain-mediated path is different from the economic growth caused by industrial structural adjustment and green technology innovation. At the national level, every 1% increase in green credit issuance relative to industrial loans will increase the per capita gross domestic product (GDP) by approximately 4.6 yuan, or 0.012%, through air quality and labor supply, accounting for 2.875% of the total effect. Heterogeneity analysis indicates that due to regional industrial structure differences and diminishing marginal effects, the impact of green credit is stronger in the western region than in the eastern and central regions. For every 1% increase in the proportion of green credit issuance relative to industrial loans, the per capita GDP growth achieved through the chain-mediated path is approximately 30.17 yuan in the western region, approximately 6.6 times greater than that at the national level. Within a 95% confidence interval of 5000 bootstrap samples, this path is found to be true, and the chain-mediated effect accounts for approximately 12.96% of the total indirect effect.LimitationsThe limitation of this paper is the measurement of green credit. Although green credit has a large volume, it remains underdeveloped, and there is a lack of perfect indicators. Most existing studies have adopted only alternative or reverse indicators to measure the issuance of green credit. For example, this paper takes the interest expenditure of six high-energy-consuming enterprises as the reverse indicator, which may to a certain extent lead to the overestimation of the issuance of green credit and its impact on the environment and economy. Future research can accurately explore the performance of green credit on the basis of its mature development.
| S-EPMC8454949 | biostudies-literature
Project description:Despite lower rates and intensity of smoking, Black men experience a higher incidence of lung cancer compared to White men. The racial disparity in lung cancer is particularly pronounced in Chicago, a highly segregated urban city. Neighborhood conditions, particularly social stress, may play a role in lung tumorigenesis. Preliminary studies indicate that Black men residing in neighborhoods with higher rates of violent crime have significantly higher levels of hair cortisol, an indicator of stress response. To examine the relationship between social stress exposure and gene expression in lung tumors, we investigated glucocorticoid receptor (GR) binding in lung tumor samples in relation to GR target gene expression levels and zip code level residential neighborhood violence. Spatial transcriptomics and a version of ChIP-sequencing known as CUT & RUN were used. GR recruitment to chromatin was correlated with neighborhood violent crime rate and overall GR binding increased with increasing neighborhood violent crime rates. Among patients residing in high-violence neighborhoods, tumor samples, compared to normal neighboring lung tissue, had fewer GR binding sites. The opposite was seen in patients residing in low-violence neighborhoods, with tumor samples having more GR binding sites when compared to normal lung tissue. Tumor samples from patients living in high-violence neighborhoods exhibited increased GR recruitment to genes associated with greater tumor aggressiveness. Our findings suggest that exposure to neighborhood violence may influence tumor biology via reprogramming GR recruitment. Prioritizing lung cancer screening in neighborhoods with increased social stress, such as high violence, may reduce racial disparities in lung cancer.
2024-07-10 | GSE268049 | GEO
Project description:The development of information technology has created conducive conditions for the digital economy. The digital economy is regarded as a critical pathway for transforming traditional economic models. Green total factor productivity serves as an indicator for assessing the quality of economic development. During pivotal periods of economic transition, the digital economy and green total factor productivity have emerged as two prominent themes for achieving sustainable economic development. But the impact of digital economy on green total factor productivity is less discussed. Innovation environment refers to a confluence of conditions shaped by factors such as talent, funding, cultural atmosphere and government policies, all of which collectively support innovative activities within a region. The institutional environment encompasses the aggregate of economic, political, social, and legal rules. Currently, there is little discussion on bringing innovation environment and institutional environment into the impact of digital economy on green total factor productivity. To fill the research gap, this paper adopts the Slack based measure-Directional distance function model and Malmquist-Luenberger productivity index to measure green total factor productivity in each region based on the panel data collected from 30 provinces in China from 2004 to 2019. Generalized Method of Moments method is constructed to carry out an empirical study on the impact of digital economy on green total factor productivity. This paper constructs a panel threshold model with innovation environment and institutional environment as threshold variables. In further analysis, this paper employs panel quantile regression for the empirical analysis of the impact of the digital economy on green total factor productivity. Further analysis elucidates the evident disparities in the influence of the digital economy on green total factor productivity at various levels. The research results can provide a guide for discussing the green value of the digital economy and its role in fostering the development of a green economy.
| S-EPMC10906909 | biostudies-literature
Project description:IntroductionGreenspace exposure has been associated with physical activity, but few studies have investigated its association with physical activity in the residential neighborhood. This study investigates whether greater amounts of neighborhood open space and forest are associated with neighborhood-based walking in older adults.MethodsIn 2020, cross-sectional analyses were conducted on those aged ≥65 years from the 2017 National Household Travel Survey. Minutes of neighborhood walking per day were derived from travel diaries. Green land cover measures from the 2011 National Land Cover Dataset were linked to respondent data by the U.S. census tract. Adjusted linear regression models, using weights accounting for survey sampling, tested the associations between the percentage of green land cover in the neighborhood (open space, forest) and minutes of neighborhood walking per day. Adjusted models were stratified to examine whether the associations varied by an individual- and neighborhood-level SES, sex, and race/ethnicity.ResultsRespondents (N=72,753) were aged 74 (SD=7) years on average. Greater percentage of open space was associated with more neighborhood walking in African Americans (estimate=0.069, 95% CI=0.005, 0.133). Greater percentage of forest was associated with more neighborhood walking in the overall sample (estimate=0.028, 95% CI=0.006, 0.050), women (estimate=0.025, 95% CI=0.005, 0.045), and Whites (estimate=0.034, 95% CI=0.004, 0.064).ConclusionsType of neighborhood green land cover (open space versus forest) may be differentially associated with neighborhood walking depending on race/ethnicity. This study suggests a possible association between greater neighborhood open space and greater walking among African Americans that must be confirmed in future studies.
| S-EPMC8217158 | biostudies-literature
Project description:Forestry plays an essential role in reducing CO2 emissions and promoting green and sustainable development. This paper estimates the CO2 emissions of 30 provinces in China from 2008 to 2017, and uses Global DEA-Malmquist to measure the total factor productivity of the forestry industry and its decomposition index. On this basis, by constructing a spatial econometric model, this paper aims to empirically study the impact of forestry industry's total factor productivity and its decomposition index on CO2 emissions, and further analyze its direct, indirect and total effects. The study finds that the impact of forestry industry's total factor productivity on CO2 emissions shows an "inverted U-shaped" curve and the inflection point is 0.9395. The spatial spillover effect of CO2 emissions is significantly negative. The increase of CO2 emissions in adjacent areas will provide a "negative case" for the region, so that the region can better address its own energy conservation and emission reduction goals. TFP of forestry industry also has positive spatial spillover effect. However, considering the particularity of forestry industry, this effect is not very significant. For other factors, such as foreign direct investment, urbanization level, industrial structure and technology market turnover will also significantly affect regional CO2 emissions.
| S-EPMC8270944 | biostudies-literature
Project description:Abstract This paper investigates the consequences of the COVID-19 crisis on firms’ performance and financial vulnerability. Exploiting longitudinal firm-level data from the World Bank’s “Enterprise Surveys follow-up on COVID-19” for 20 European countries, we assess whether green management quality and pre-pandemic credit access difficulties affect firms’ ability to withstand the negative impact of the pandemic. Our results indicate that green firms are more resilient to the pandemic shock. In particular, the likelihood of pandemic-induced drops in sales and liquidity significantly decreases as the quality of green management improves. Conversely, prior financing constraints strongly exacerbate the pandemic’s impact on firms’ performance and amplify liquidity stress and financing problems. Credit-constrained enterprises are not only more likely to experience liquidity shortages and repayment problems, but they also face higher difficulties in accessing bank financing. The COVID-19 crisis has also hampered the beneficial role that green management exerted on access to credit in the pre-pandemic period. During the pandemic, firms with sound environmental management practices do not benefit from improved access to finance and have a lower demand for credit, possibly suggesting a slowdown in their green investment activities. Supplementary information The online version contains supplementary material available at 10.1007/s11187-023-00759-1. Green firms are more resilient to the COVID-19 shock, while prior credit access difficulties strongly exacerbate the pandemic’s impact on businesses. Using data on firms from 20 European countries, we find that enterprises with sound environmental management practices have a lower probability of pandemic-induced reductions in sales and liquidity. Pre-pandemic financing constraints significantly impair firms’ economic and financial performance and increase difficulties in accessing bank credit during the COVID-19 crisis. Our results suggest that public policies, aimed at encouraging firms’ environmentally sustainable behaviours and at supporting their access to credit, may contribute to strengthen the resilience of the economic system to unexpected shocks and favour the transition to a sustainable economy. Furthermore, the awareness of the competitive advantages offered by eco-sustainable practices may represent an incentive form firms to improve their environmental management quality and increase investment in green technologies. Supplementary information The online version contains supplementary material available at 10.1007/s11187-023-00759-1.
| S-EPMC10113997 | biostudies-literature
Project description:Dopamine in the nucleus accumbens helps motivate behavior based on expectations of future reward ("values"). These values need to be updated by experience: after receiving reward, the choices that led to reward should be assigned greater value. There are multiple theoretical proposals for how this credit assignment could be achieved, but the specific algorithms that generate updated dopamine signals remain uncertain. We monitored accumbens dopamine as freely behaving rats foraged for rewards in a complex, changing environment. We observed brief pulses of dopamine both when rats received reward (scaling with prediction error), and when they encountered novel path opportunities. Furthermore, dopamine ramped up as rats ran towards reward ports, in proportion to the value at each location. By examining the evolution of these dopamine place-value signals, we found evidence for two distinct update processes: progressive propagation along taken paths, as in temporal-difference learning, and inference of value throughout the maze, using internal models. Our results demonstrate that within rich, naturalistic environments dopamine conveys place values that are updated via multiple, complementary learning algorithms.
| S-EPMC10054934 | biostudies-literature
Project description:Cell competition is a quality-control mechanism through which tissues eliminate unfit cells. Cell competition can result from short-range biochemical inductions or long-range mechanical cues. However, little is known about how cell-scale interactions give rise to population shifts in tissues, due to the lack of experimental and computational tools to efficiently characterize interactions at the single-cell level. Here, we address these challenges by combining long-term automated microscopy with deep-learning image analysis to decipher how single-cell behavior determines tissue makeup during competition. Using our high-throughput analysis pipeline, we show that competitive interactions between MDCK wild-type cells and cells depleted of the polarity protein scribble are governed by differential sensitivity to local density and the cell type of each cell's neighbors. We find that local density has a dramatic effect on the rate of division and apoptosis under competitive conditions. Strikingly, our analysis reveals that proliferation of the winner cells is up-regulated in neighborhoods mostly populated by loser cells. These data suggest that tissue-scale population shifts are strongly affected by cellular-scale tissue organization. We present a quantitative mathematical model that demonstrates the effect of neighbor cell-type dependence of apoptosis and division in determining the fitness of competing cell lines.
| S-EPMC5687024 | biostudies-literature