Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
27
datasets available to search
ShareScore release 0.9.0
Dataset results
27 results for “Economic growth”
C4 photosynthesis and the economic spectra of leaf and root traits independently influence growth rates in grasses
<p>Photosynthetic pathway is an important cause of growth rate variation between species, such that the enhanced carbon uptake of C<sub>4</sub> species leads to faster growth than their C<sub>3</sub> counterparts. Leaf traits that promote rapid resource acquisition may further enhance the growth capacity of C<sub>4</sub> species. However, how root economic traits interact with leaf traits, and the different growth strategies adopted by plants with C<sub>3</sub> and C<sub>4</sub> photosynthetic pathways is unclear. Plant economic traits could interact with, or act independently of, photosynthetic pathway in influencing growth rate, or C<sub>3</sub> and C<sub>4</sub> species could segregate out along a common growth rate-trait relationship.</p> <p>We measured leaf and root traits on 100+ grass species grown from seeds in a controlled, common environment to compare with relative growth rates (RGR) during the initial phase of rapid growth, controlling for phylogeny and allometric effects.</p> <p>Photosynthetic pathway acts independently to leaf and root functional traits in causing fast growth. Using C<sub>4</sub> photosynthesis, plants can achieve faster growth than their C<sub>3</sub> counterparts (by an average 0.04 g g<sup>-1</sup> day<sup>-1</sup>) for a given suite of functional trait values, with lower investments of leaf and root nitrogen. Leaf and root traits had an additive effect on RGR, with plants achieving fast growth by possessing resource-acquisitive leaf traits (high specific leaf area and low leaf dry matter content) or root traits (high specific root length and area, and low root diameter), but having both leads to an even faster growth rate (by up to 0.06 g g-1 day-1). C<sub>4</sub> photosynthesis can provide a greater relative increase in RGR for plants with a 'slow' ecological strategy than in those with fast growth. However, aboveground and belowground strategies are not coordinated, so that species can have any combination of 'slow' or 'fast' leaf and root traits.</p> <p>Synthesis: C<sub>4</sub> photosynthesis increases growth rate for a given combination of economic traits, and significantly alters plant nitrogen economy in the leaves and roots. However, leaf and root economic traits act independently to further enhance growth. The fast growth of C<sub>4</sub> grasses promotes a competitive advantage under hot, sunny conditions.</p>
Impact of Clean Energy on CO2 Emissions and Economic Growth within the Phases of Renewables Diffusion in Selected European Countries
<p>This study explores the impact of clean energy and non-renewable energy consumption on CO<sub>2</sub> emissions and economic growth within two phases (formative and expansion) of renewable energy diffusion for three selected countries (France, Spain, and Sweden). The vector autoregression (VAR) model is estimated on the basis of annual data disaggregated into quarterly data. The Granger causality results reveal distinctive differences in the causality patterns across countries and two phases of renewables diffusion. Clean energy consumption contributes to a decline of emissions more clearly in the expansion phase in France and Spain. However, this effect seems to be counteracted by the increases in emissions due to economic growth and non-renewable energy consumption. Therefore, clean energy consumption has not yet led to a decoupling of economic growth from emissions in France and Spain; in contrast, the findings for Sweden evidence such a decoupling due to the neutrality between economic growth and emissions. Generally, the findings show that despite the enormous growth of renewables and active mitigation policies, CO<sub>2</sub> emissions have not substantially decreased in selected countries or globally. Focused and coordinated policy action, not only at the EU level but also globally, is urgently needed to overhaul existing fossil-fuel economies into low-carbon economies and ultimately meet the relevant climate targets.</p>
Dataset of 'Unequal Impacts of Urban Industrial Land Expansion on Economic Growth and Carbon Dioxide Emissions'
<p>This dataset is an integral component of the research presented in 'Unequal Impacts of Urban Industrial Land Expansion on Economic Growth and Carbon Dioxide Emissions' by Yoo et al., 2024. It encompasses:</p> <p><strong>1. Links to two publicly accessible datasets:</strong></p> <ul> <li>Industrial land mapping data derived from Google Earth Engine.</li> <li>Data employed in a longitudinal analysis to evaluate the effects of urban industrial land expansion on CO2 emissions and economic growth.</li> </ul> <p><strong>2. Comprehensive input data </strong>utilized in Mixed Effects Random Forest (MERF) longitudinal modeling to assess the separate impacts on CO2 emissions and economic growth in developing and developed regions.</p> <p><strong>3. Python scripts provided for:</strong></p> <ul> <li>Executing MERF longitudinal modeling.</li> <li>Computing SHAP (SHapley Additive exPlanations) values to interpret the contributions of each predictor variable.</li> <li>Generating figures that visually summarize the findings for both developing and developed regions.</li> </ul> <p> </p> <p><strong>The manuscript is available</strong> at: <a href="https://doi.org/10.1038/s43247-024-01375-x"><span>https://doi.org/10.1038/s43247-024-01375-x</span></a></p> <div> <div> </div> </div>
Analysis tools and data for study "Better insurance could effectively mitigate the increase in economic growth losses from US hurricanes under global warming"
<p>This scripts are used for post-analysis and for creating the main figures for our study "Better insurance could effectively mitigate the increase in economic growth losses from US hurricanes under global warming". Our raw results are calculated by InGroClIm (DOI:10.5281/zenodo.5017904).</p>
C4 photosynthesis and the economic spectra of leaf and root traits independently influence growth rates in grasses
Open the record for dataset details and reuse information.
The world economic growth 1980 2019
<p>A simple display of IFM' data that spams the real GDP evolution from 1980 to 2019 of 194 countries. </p>
Data from: The inverted U-shaped effect of urban hotspots spatial compactness on urban economic growth
The compact city, as a sustainable concept, is intended to augment the efficiency of urban function. However, previous studies have concentrated more on morphology than on structure. The present study focuses on urban structural elements, i.e., urban hotspots consisting of high-density and high-intensity socioeconomic zones, and explores the economic performance associated with their spatial structure. We use nighttime luminosity (NTL) data and the Loubar method to identify and extract the hotspot and ultimately draw two conclusions. First, with population increasing, the hotspot number scales sublinearly with an exponent of approximately 0.50~0.55, regardless of the location in China, the EU or the US, while the intersect values are totally different, which is mainly due to different economic developmental level. Secondly, we demonstrate that the compactness of hotspots imposes an inverted U-shaped influence on economic growth, which implies that an optimal compactness coefficient does exist. These findings are helpful for urban planning.
Dataset "How Does Education Quality Affect Economic Growth?"
<p>Dataset and do files used in "How Does Education Quality Affect Economic Growth?" paper.</p>
Data for: Palma, N. and Reis, J. (2019). From convergence to divergence: Portuguese economic growth, 1527-1850. Journal of Economic History 79 (2): 477-506
<p>Data for: Palma, N. and Reis, J. (2019). From convergence to divergence: Portuguese economic growth, 1527-1850. Journal of Economic History 79 (2): 477-506 </p>
Demystifying Economic Growth Implications of Population Ageing
<p>This is part of a study attempting to estimate the impact of population ageing on economic growth in a panel of nations.</p>
Data from: The inverted U-shaped effect of urban hotspots spatial compactness on urban economic growth
Open the record for dataset details and reuse information.
Plant growth forms determine root resource acquisition strategy along ‘fast-slow’ economics spectrum in a temperate forest community
Open the record for dataset details and reuse information.
The effect of renewable and nuclear energy consumption on decoupling economic growth from CO2 emissions in Spain
<p>This study examines the relationship between renewable and nuclear energy consumption, carbon dioxide emissions and economic growth by using the Granger causality and non-linear impulse response function in a business cycle in Spain. We estimate the threshold vector autoregression (TVAR) model on the basis of annual data from the period 1970‒2018, which are disaggregated into quarterly data. Our analysis reveals that economic growth and CO<sub>2</sub> emissions are positively correlated during expansions but not during recessions. Moreover, we find that rising nuclear energy consumption leads to decreased CO<sub>2</sub> emissions during expansions, while the impact of increasing renewable energy consumption on emissions is negative but insignificant. In addition, there is a positive feedback between nuclear energy consumption and economic growth, but unidirectional positive causality running from renewable energy consumption to economic growth in upturns. Our findings do indicate that both nuclear and renewable energy consumption contribute to a reduction in emissions; however, the rise in economic activity, leading to a greater increase in emissions, offsets this positive impact of green energy. Therefore, a decoupling of economic growth from CO<sub>2</sub> emissions is not observed. These results demand some crucial changes in legislation targeted at reducing emissions, as green energy alone is insufficient to reach this goal.</p>
Considering institutional type: a varieties of capitalism approach to the economic growth resource curse
<p>Defined by North (1994) as the "rules of the game", over the last few decades, many scholars have sought to understand whether quality institutions can alleviate the Resource Curse (the idea that natural resource abundance hinders rather than promotes economic growth). However, with this focus on quality, few papers have addressed the question of institutional type, and its Curse mitigating properties. This paper, via utilising the associated data, contributes towards filling this gap. Using the Varieties of Capitalism framework, we test whether certain institutional typologies possess the ability to mitigate the Resource Curse and perhaps even turn it into a blessing. Specifically, Rougier and Combarnous' cluster analysis, "The Diversity of Emerging Capitalisms in Developing Countries" (2017), whereby nations are assigned various institutional typologies is used to create our primary (dummy) independent variables of interest in this study. The remaining control variables essential for economic growth analysis are collected via the World Bank and Polity datasets.</p>
THE IMPACT OF THE EXPORT POTENTIAL OF THE FRUIT AND VEGETABLE INDUSTRY ON THE ECONOMIC GROWTH OF THE REPUBLIC OF UZBEKISTAN.
Open the record for dataset details and reuse information.
Supplementary material 1 from: Strokov AS, Potashnikov VY (2022) Environmental tradeoffs of agricultural growth in Russian regions and possible sustainable pathways for 2030. Russian Journal of Economics 8(1): 60-80. https://doi.org/10.32609/j.ruje.8.78331
Maps of main environmental indicators of Russian regional agricultural development
Supplementary material 2 from: Strokov AS, Potashnikov VY (2022) Environmental tradeoffs of agricultural growth in Russian regions and possible sustainable pathways for 2030. Russian Journal of Economics 8(1): 60-80. https://doi.org/10.32609/j.ruje.8.78331
The dataset on agricultural waste, nitrogen concentration, and GHG emissions in Russian regions
An empirical analysis of AfCFTA economic growth prospects in the SADC region Evidence using ARDL-PMG estimation techniques: Dataset
Open the record for dataset details and reuse information.
Compounding uncertainties in economic and population growth increase tail risks for relevant outcomes across sectors
<p>Understanding the long-term effects of population and GDP changes requires a multisectoral and regional understanding of the coupled human-Earth system, as the long-term evolution of this coupled system is influenced by human decisions and the Earth system. This study investigates the impact of compounding economic and population growth uncertainties on long-term multisectoral outcomes. We use the Global Change Analysis Model (GCAM) to explore the influence of compounding and feedback between future GDP and population growth on four key sectors: final energy consumption, water withdrawal, staple food prices, and CO2 emissions. The results show that uncertainties in GDP and population compound, resulting in a magnification of tail risks for outcomes across sectors and regions. Compounding uncertainties significantly impact metrics such as CO2 emissions and final energy consumption, particularly at the upper tail at both global and regional levels. However, the impact of staple food prices and water withdrawal depends on regional factors. Additionally, an alternative low-carbon transition scenario could compound uncertainties and increase tail risk, particularly in staple food prices, highlighting the influence of emergent constraints on land availability and food-energy competition for land use. The findings underscore the importance of considering and adequately accounting for compounding uncertainties in key drivers of multisectoral systems to enhance our comprehensive understanding of the complex nature of multisectoral systems. The paper provides valuable insights into the potential implications of compounding uncertainties.</p>
Considering institutional type: a varieties of capitalism approach to the economic growth resource curse
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.