Subjects -> STATISTICS (Total: 130 journals)
 Showing 1 - 151 of 151 Journals sorted alphabetically Advances in Complex Systems       (Followers: 11) Advances in Data Analysis and Classification       (Followers: 62) Annals of Applied Statistics       (Followers: 39) Applied Categorical Structures       (Followers: 4) Argumentation et analyse du discours       (Followers: 11) Asian Journal of Mathematics & Statistics       (Followers: 8) AStA Advances in Statistical Analysis       (Followers: 4) Australian & New Zealand Journal of Statistics       (Followers: 13) Bernoulli       (Followers: 9) Biometrical Journal       (Followers: 11) Biometrics       (Followers: 52) British Journal of Mathematical and Statistical Psychology       (Followers: 18) Building Simulation       (Followers: 2) Bulletin of Statistics       (Followers: 4) CHANCE       (Followers: 5) Communications in Statistics - Simulation and Computation       (Followers: 9) Communications in Statistics - Theory and Methods       (Followers: 11) Computational Statistics       (Followers: 14) Computational Statistics & Data Analysis       (Followers: 37) Current Research in Biostatistics       (Followers: 8) Decisions in Economics and Finance       (Followers: 11) Demographic Research       (Followers: 15) Electronic Journal of Statistics       (Followers: 8) Engineering With Computers       (Followers: 5) Environmental and Ecological Statistics       (Followers: 7) ESAIM: Probability and Statistics       (Followers: 5) Extremes       (Followers: 2) Fuzzy Optimization and Decision Making       (Followers: 9) Geneva Papers on Risk and Insurance - Issues and Practice       (Followers: 13) Handbook of Numerical Analysis       (Followers: 5) Handbook of Statistics       (Followers: 7) IEA World Energy Statistics and Balances -       (Followers: 2) International Journal of Computational Economics and Econometrics       (Followers: 6) International Journal of Quality, Statistics, and Reliability       (Followers: 17) International Journal of Stochastic Analysis       (Followers: 3) International Statistical Review       (Followers: 13) International Trade by Commodity Statistics - Statistiques du commerce international par produit Journal of Algebraic Combinatorics       (Followers: 4) Journal of Applied Statistics       (Followers: 21) Journal of Biopharmaceutical Statistics       (Followers: 21) Journal of Business & Economic Statistics       (Followers: 39, SJR: 3.664, CiteScore: 2) Journal of Combinatorial Optimization       (Followers: 7) Journal of Computational & Graphical Statistics       (Followers: 20) Journal of Econometrics       (Followers: 84) Journal of Educational and Behavioral Statistics       (Followers: 6) Journal of Forecasting       (Followers: 17) Journal of Global Optimization       (Followers: 7) Journal of Interactive Marketing       (Followers: 10) Journal of Mathematics and Statistics       (Followers: 8) Journal of Nonparametric Statistics       (Followers: 6) Journal of Probability and Statistics       (Followers: 10) Journal of Risk and Uncertainty       (Followers: 33) Journal of Statistical and Econometric Methods       (Followers: 5) Journal of Statistical Physics       (Followers: 13) Journal of Statistical Planning and Inference       (Followers: 8) Journal of Statistical Software       (Followers: 21, SJR: 13.802, CiteScore: 16) Journal of the American Statistical Association       (Followers: 72, SJR: 3.746, CiteScore: 2) Journal of the Korean Statistical Society       (Followers: 1) Journal of the Royal Statistical Society Series C (Applied Statistics)       (Followers: 33) Journal of the Royal Statistical Society, Series A (Statistics in Society)       (Followers: 27) Journal of the Royal Statistical Society, Series B (Statistical Methodology)       (Followers: 43) Journal of Theoretical Probability       (Followers: 3) Journal of Time Series Analysis       (Followers: 16) Journal of Urbanism: International Research on Placemaking and Urban Sustainability       (Followers: 30) Law, Probability and Risk       (Followers: 8) Lifetime Data Analysis       (Followers: 7) Mathematical Methods of Statistics       (Followers: 4) Measurement Interdisciplinary Research and Perspectives       (Followers: 1) Metrika       (Followers: 4) Modelling of Mechanical Systems       (Followers: 1) Monte Carlo Methods and Applications       (Followers: 6) Monthly Statistics of International Trade - Statistiques mensuelles du commerce international       (Followers: 2) Multivariate Behavioral Research       (Followers: 5) Optimization Letters       (Followers: 2) Optimization Methods and Software       (Followers: 8) Oxford Bulletin of Economics and Statistics       (Followers: 34) Pharmaceutical Statistics       (Followers: 17) Probability Surveys       (Followers: 4) Queueing Systems       (Followers: 7) Research Synthesis Methods       (Followers: 8) Review of Economics and Statistics       (Followers: 128) Review of Socionetwork Strategies Risk Management       (Followers: 15) Sankhya A       (Followers: 2) Scandinavian Journal of Statistics       (Followers: 9) Sequential Analysis: Design Methods and Applications Significance       (Followers: 7) Sociological Methods & Research       (Followers: 38) SourceOCDE Comptes nationaux et Statistiques retrospectives SourceOCDE Statistiques : Sources et methodes SourceOECD Bank Profitability Statistics - SourceOCDE Rentabilite des banques       (Followers: 1) SourceOECD Insurance Statistics - SourceOCDE Statistiques d'assurance       (Followers: 2) SourceOECD Main Economic Indicators - SourceOCDE Principaux indicateurs economiques       (Followers: 1) SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques SourceOECD Monthly Statistics of International Trade       (Followers: 1) SourceOECD National Accounts & Historical Statistics SourceOECD OECD Economic Outlook Database - SourceOCDE Statistiques des Perspectives economiques de l'OCDE       (Followers: 2) SourceOECD Science and Technology Statistics - SourceOCDE Base de donnees des sciences et de la technologie SourceOECD Statistics Sources & Methods       (Followers: 1) SourceOECD Taxing Wages Statistics - SourceOCDE Statistiques des impots sur les salaires Stata Journal       (Followers: 9) Statistica Neerlandica       (Followers: 1) Statistical Applications in Genetics and Molecular Biology       (Followers: 5) Statistical Communications in Infectious Diseases Statistical Inference for Stochastic Processes       (Followers: 3) Statistical Methodology       (Followers: 7) Statistical Methods and Applications       (Followers: 6) Statistical Methods in Medical Research       (Followers: 27) Statistical Modelling       (Followers: 19) Statistical Papers       (Followers: 4) Statistical Science       (Followers: 13) Statistics & Probability Letters       (Followers: 13) Statistics & Risk Modeling       (Followers: 3) Statistics and Computing       (Followers: 13) Statistics and Economics       (Followers: 1) Statistics in Medicine       (Followers: 195) Statistics, Politics and Policy       (Followers: 6) Statistics: A Journal of Theoretical and Applied Statistics       (Followers: 14) Stochastic Models       (Followers: 3) Stochastics An International Journal of Probability and Stochastic Processes: formerly Stochastics and Stochastics Reports       (Followers: 2) Structural and Multidisciplinary Optimization       (Followers: 12) Teaching Statistics       (Followers: 7) Technology Innovations in Statistics Education (TISE)       (Followers: 2) TEST       (Followers: 3) The American Statistician       (Followers: 23) The Annals of Applied Probability       (Followers: 8) The Annals of Probability       (Followers: 10) The Annals of Statistics       (Followers: 34) The Canadian Journal of Statistics / La Revue Canadienne de Statistique       (Followers: 11) Wiley Interdisciplinary Reviews - Computational Statistics       (Followers: 1)
Similar Journals
 Environmental and Ecological StatisticsJournal Prestige (SJR): 0.594 Citation Impact (citeScore): 1Number of Followers: 7      Hybrid journal (It can contain Open Access articles) ISSN (Print) 1573-3009 - ISSN (Online) 1352-8505 Published by Springer-Verlag  [2655 journals]
• Forecasting the Yellow River runoff based on functional data analysis
methods
• Abstract: This study examines the runoff prediction of each hydrometric station and each month in the mainstream of the Yellow River in China. From the perspective of functional data, the monthly runoff of each hydrometric station can be regarded as a function of both time and space. A sequence of such functions is formed by collecting the data over the years. We propose a new approach by combining the two-dimensional functional principal component analysis (FPCA) and time series analysis methods to predict the runoff. In the simulation, we compared the proposed method with two others: one based on one-dimensional FPCA and the seasonal auto-regressive integrated moving average (SARIMA) method. The method combining standard two-dimensional FPCA and time series analysis outperforms others in most cases, and is used to predict the runoff of each hydrometric station and each month in the Yellow River in 2018.
PubDate: 2021-03-01

• Bayesian predictive model selection in circular random effects models with
applications in ecological and environmental studies
• Abstract: In this paper we present a detailed comparison of the prediction error based model selection criteria in circular random effects models. The study is primarily motivated by the need for an understanding of their performance in real life ecological and environmental applications. Prediction errors are based on posterior predictive distributions and the model selection methods are adjusted for the circular manifold. Plug-in estimators of the circular distance parameters are also considered. A Monte Carlo experiment scheme taking the account of various realistic ecological and biological scenarios is designed. We introduced a coefficient that is based on conditional expectations to examine how the deviation from von Mises (vM) distribution, the standard choice in applications, effects the performances. Our results show that the performances of widely used circular predictive model selection criteria mostly depend on the sample size as well as within-sample-correlation. The approaches and selection strategies are then applied to investigate orientational behaviour of Talitrus saltator under the risk of dehydration and direction of wind with respect to associated atmoshperic variables.
PubDate: 2021-03-01

• Halton iterative partitioning master frames
• Abstract: A spatial sampling design determines where sample locations are placed in a study area. To achieve reliable estimates of population characteristics, the spatial pattern of the sample should be similar to the underlying spatial pattern of the population. A reasonable assumption for natural resources is that nearby locations tend to have more similar response values than distant locations. Hence, sample efficiency can be increased by spreading sample locations evenly over a natural resource. A sample that is well-spread over the resource is called spatially balanced and many spatially balanced sampling designs have been proposed in the statistical literature. Robertson et al. (Environ Ecol Stat 25:305–323, 2018) proposed a sampling design that draws spatially balanced samples using a nested partition. This article modifies their partitioning strategy to spatially order a point resource into a highly structured master frame. Samples of consecutive points from the master frame are spatially balanced and these individual samples can be easily incorporated into a broader spatially balanced design for integrated monitoring. Numerical results show that the master frame’s ordering is effective and that a range of samples drawn from it are spatially balanced.
PubDate: 2021-02-17

• Modified information criterion for regular change point models based on
confidence distribution
• Abstract: In this article, we propose procedures based on the modified information criterion and the confidence distribution for detecting and estimating changes in a three-parameter Weibull distribution. Corresponding asymptotic results of the test statistic associated the detection procedure are established. Moreover, instead of only providing point estimates of change locations, the proposed estimation procedure provides the confidence sets for change locations at a given significance level through the confidence distribution. In general, the proposed procedures are valid for a large class of parametric distributions under Wald conditions and the certain regularity conditions being satisfied. Simulations are conducted to investigate the performance of the proposed method in terms of powers, coverage probabilities and average lengths of confidence sets with respect to a three-parameter Weibull distribution. Corresponding comparisons are also made with other existing methods to indicate the advantages of the proposed method. Rainfall data is used to illustrate the application of the proposed method.
PubDate: 2021-02-12

• The measurement of green finance index and the development forecast of
green finance in China
• Abstract: This paper proposes a green finance index that may help policymakers and investors take more favorable actions based on the development of green finance. After analysis and organization of the development process of green finance and related green finance and index concepts, this paper uses the improved fuzzy comprehensive evaluation method to construct a measurement model suitable for measuring the development level of green finance based on the principle of fuzzy mathematics. The index weight adopts the entropy method and improved Analytic Hierarchy Process (AHP) joint determination. At the same time, using the relevant statistical indicators of China's green credit from 2011 to 2019, and using the constructed model, the level of China's green finance development during this period was evaluated. Finally, the obtained data and classical gray model methods were used to predict China's green development level from 2020 to 2024. The research results show that: This model is a good measure of the level of development of green finance, and China's green finance index has generally shown a rapid growth trend over the past nine years, with the fastest growth rate between 2013 and 2014. From the perspective of the weight of each index affecting the green financial index, the weight of new energy, green transportation projects and new energy vehicles ranked in the top three, and the impact of these three indexes on China's green financial index is significant. In the future, China's green financial development level will continue to improve.
PubDate: 2021-02-09

• The role of odds ratios in joint species distribution modeling
• Abstract: Joint species distribution modeling is attracting increasing attention these days, acknowledging the fact that individual level modeling fails to take into account expected dependence/interaction between species. These joint models capture species dependence through an associated correlation matrix arising from a set of latent multivariate normal variables. However, these associations offer limited insight into realized dependence behavior between species at sites. We focus on presence/absence data using joint species modeling, which, in addition, incorporates spatial dependence between sites. For pairs of species selected from a collection, we emphasize the induced odds ratios (along with the joint occurrence probabilities); they provide a better appreciation of the practical dependence between species that is implicit in these joint species distribution modeling specifications. For any pair of species, the spatial structure enables a spatial odds ratio surface to illuminate how dependence varies over the region of interest. We illustrate with a dataset from the Cape Floristic Region of South Africa consisting of more than 600 species at more than 600 sites. We present the spatial distribution of odds ratios for pairs of species that are positively correlated and pairs that are negatively correlated under the joint species distribution model.
PubDate: 2021-02-09

• Determinants of CO 2 emissions: empirical evidence from Egypt
• Abstract: This paper aims to explore the main determinants of environmental quality in Egypt by utilizing the data covering the years from 1971 to 2014. These dynamics were explored by utilizing the ARDL, wavelet coherence and Gradual shift causality approaches. The ARDL bounds test revealed cointegration among series. Findings based on the ARDL revealed; (i) positive and significant interaction between energy usage and CO2 emissions; (ii) no evidence of significant link was found between urbanization and CO2 emissions; (iii) no significant link was found between gross capital formation and CO2 emissions; and (iv) GDP growth impact CO2 emissions positively in Egypt. Furthermore, findings from the wavelet coherence technique provide supportive evidence for the ARDL estimate. The Gradual shift causality test revealed one-way causality from CO2 emissions to energy consumption and economic growth, while there is evidence of feedback causality between CO2 and gross capital formation. Based on these findings, policymakers in Egypt need to formulate environmental policies to promote sustainable urbanization and clean energy without undermining economic growth.
PubDate: 2021-02-05

• The relationships between ecological urbanization, green areas, and air
pollution in Erzurum/Turkey
• Abstract: The aim of this research is to determine the design criteria of habitable spaces with microclimate data for ecological urbanization. Different types of housing in the city of Erzurum, which is in the northeast region of Turkey, were used in this study. The hourly microclimate and air pollution data from 2018 for the city center were used to analyze the relationships between different residential textures, air pollution, green area, and thermal comfort. The data of Ata Botanical Garden, where trees are dense, and the vicinity of the city center, where air pollution is most intense, are discussed. The physiological equivalent temperature (PET) and sky view factor (SVF) data were analyzed with a RayMan Pro 2.1 computer model. Spatial settlement area analyses were conducted by evaluating the SVF values in ArcGIS 10.3. The relationships between air pollution, residential textures, and SVF data were determined. A comparative analysis of existing green areas was undertaken with the pollution forecast maps. The statistical results indicated that there is a difference in the relationship between the thermal comfort and air pollution of the residential textures and the SVF value of the study area according to the seasons. A strong relationship was found in the present study between pollutants and SVF, while it is weaker for green areas. Air pollution was observed to have the lowest density in the areas where detached house types are located among the different residential textures. In addition, in the same area, street geometry is closer to its ideal form, and therefore thermal comfort is also at a higher level. As a result of this study, residential textures were found to have effects on air pollution and thermal comfort.
PubDate: 2021-01-31
DOI: 10.1007/s10651-021-00484-6

• Revisiting the impacts of economic growth on environmental degradation:
new evidence from 115 countries
• Abstract: This paper examines the causal relationship between economic growth and environmental degradation for 115 countries over the period 1990–2016. The empirical results show a long-run equilibrium relationship between the CO2, CH4 and PM2.5 emissions and their macroeconomic determinants economic growth, energy consumption, trade openness, urbanization, and transportation. The author found mixed support of the Environmental Kuznets Curve (EKC) hypothesis, confirming the U-shaped EKC for all the income countries in CO2 and an inverted U-shaped EKC both in CH4 and PM2.5 emissions for the low, lower-middle and high-income countries. In the subsequent Granger causality test, the author revealed that energy consumption and economic growth raise the level of CO2, the most significant pollutant because of their positive causal effect. Moreover, the impulse response function forecasts an inverted U-shaped EKC mostly for selected pollutants in all countries. Results suggest that promoting energy efficiency and reducing the use of fossil fuels are effective measures for reversing environmental degradation in the country.
PubDate: 2021-01-30
DOI: 10.1007/s10651-020-00479-9

• Concurrent functional regression to reconstruct river stage data during
flood events
• Abstract: On October 4, 2015, the Cedar Creek gage at Congaree National Park stopped reporting stages, and the readings did not resume until approximately 2 weeks later because of record-breaking rainfall that led to some of the worst floodings in South Carolina history. Our goal is to reconstruct the Cedar Creek stage during this missing 2-week window. Our analysis uses a sample of ten historical flood events from the last 25 years. The Congaree River gage in Congaree National Park remained functioning throughout the October 2015 flood, when the stage reached its maximum recorded crest. The stages from the two gages are directly related during floods. We introduce a new method to objectively determine the start and end points of each flood event in the sample and then use these events to predict the missing Cedar Creek stage. We treat the stage as functional data and use a concurrent model to establish the relationship between the two locations during each timepoint of prior flood events. Once this relationship is found, the known Congaree stage is used to predict the missing Cedar Creek stage during the 2015 flood. The results show that there is a strong functional relationship between the two locations, and that the crest of Cedar Creek is a historic high, reaching stages above 17 feet, with a previous high of just over 16 feet.
PubDate: 2021-01-28
DOI: 10.1007/s10651-021-00487-3

• Prediction framework in a distributed lag model with a target function: an
application to global warming data
• Abstract: Due to the nature of the distributed lag model, researchers are likely to encounter the problem of multicollinearity in this model. Biased estimation techniques, one of which is Almon ridge estimation, are alternatively considered instead of Almon estimation with the aim of recovering the multicollinearity. Although estimation performance is often taken into consideration, predictive performance is rarely handled in the distributed lag model. The principal purpose of this paper is to investigate the predictive performance of the distributed lag model through target function. In this context, we employ Almon ridge estimation to define a new predictor that is more resistant to multicollinearity. For an extensive analysis of the prediction problem in the distributed lag model, we concentrate on the theoretical results and comparisons. Then, the issue of determining optimal parameters is considered by means of minimizing the prediction mean square error. Numerical analysis depending on global warming data is examined to validate our theoretical outcomes. Moreover, a Monte Carlo experiment is carried out to evaluate the predictive ability of the estimators.
PubDate: 2021-01-21
DOI: 10.1007/s10651-020-00477-x

• A constrained-memory stress release model (CM-SRM) for the earthquake
occurrence in the Corinth Gulf (Greece)
• Abstract: The complexity of seismogenesis requires the development of stochastic models, the application of which aims to improve our understanding on the seismic process and the associated underlying mechanisms. Seismogenesis in the Corinth Gulf (Greece) is modeled through a Constrained-Memory Stress Release Model (CM-SRM), which combines the gradual increase of the strain energy due to continuous slow tectonic strain loading and its sudden release during an earthquake occurrence. The data are treated as a point process, which is uniquely defined by the associated conditional intensity function. In the original form of the Simple Stress Release Model (SSRM), the conditional intensity function depends on the entire history of the process. In an attempt to identify the most appropriate parameterization that better fits the data and describes the earthquake generation process, we introduce a constrained “ $$m$$ -memory” point process, implying that only the $$m$$ most recent arrival times are taken into account in the conditional intensity function, for some suitable $$m \in N$$ . Modeling of this process is performed for moderate earthquakes (M ≥ 5.2) occurring in the Corinth Gulf since 1911, by considering in each investigation different number of steps backward in time. The derived model versions are compared with the SSRM in its original form and evaluated in terms of information criteria and residual analysis.
PubDate: 2021-01-10
DOI: 10.1007/s10651-020-00478-w

• Measuring the impact of higher education on environmental pollution: new
evidence from thirty provinces in China
• Abstract: The study reported in this article investigated the relationship between higher education and environmental sustainability with control variables including foreign direct investment, electricity consumption, population, and gross domestic product from 30 provinces in China during the 2000–2018 period. The data were analyzed with cross-sectional dependency tests, panel unit-root tests, Kao cointegration tests, fully modified ordinary least squares, and dynamic ordinary least squares. Some of the main results are presented as follows. First, the results showed that higher education and foreign direct investment play a vital role in mitigating CO2 emissions, thereby confirming both the education-CO2 led hypothesis and the pollution halo hypothesis, respectively. Second, the estimates suggested that an increase in electricity consumption, population, and gross domestic product significantly contributed to enhancements in CO2 emissions. Based on the current estimated results, this research proposes important policies to help policymakers and governments in mitigating CO2 emissions.
PubDate: 2021-01-10
DOI: 10.1007/s10651-020-00480-2

• Neyman–Scott process with alpha-skew-normal clusters
• Abstract: The Neyman–Scott processes introduced so far assume a symmetric distribution for the positions of the offspring points and this makes them inappropriate for modelling the skewed and bimodal clustered patterns and is a hindrance in fitting them to data that exhibit skewness or bimodality. In this paper, we apply the bivariate alpha-skew-normal distribution to the locations of the offspring points and introduce a Neyman–Scott process that regulates skewness and bimodality shapes in clustered point patterns. For this process, we obtain closed forms of the pair correlation function and the third-order intensity reweighted product density function and by use of the composite likelihood method, we fit the model to data. To examine the goodness-of-fit of the presented model, we use a statistical test based on the combined global scaled MAD envelopes. The use of the introduced process to model a clustered point pattern is illustrated by application to the locations of a species of trees in a rainforest dataset.
PubDate: 2021-01-08
DOI: 10.1007/s10651-020-00476-y

• Analysing the relationship between district heating demand and weather
conditions through conditional mixture copula
• Abstract: Efficient energy production and distribution systems are urgently needed to reduce world climate change. Since modern district heating systems are sustainable energy distribution services that exploit renewable sources and avoid energy waste, in-depth knowledge of thermal energy demand, which is mainly affected by weather conditions, is essential to enhance heat production schedules. We hence propose a mixture copula-based approach to investigate the complex relationship between meteorological variables, such as outdoor temperature and solar radiation, and thermal energy demand in the district heating system of the Italian city Bozen-Bolzano. We analyse data collected from 2014 to 2017, and estimate copulas after removing serial dependence in each time series using autoregressive integrated moving average models. Due to complex relationships, a mixture of an unstructured Student-t and a flipped Clayton copula is deemed the best model, as it allows differentiating the magnitude of dependence in each tail and exhibiting both heavy-tailed and asymmetric dependence. We derive the conditional copula-based probability function of thermal energy demand given meteorological variables, and provide useful insight on the production management phase of local energy utilities.
PubDate: 2021-01-06
DOI: 10.1007/s10651-020-00475-z

• Assessing competition among species through simultaneously modeling
marginal counts and respective proportions
• Abstract: Evolution processes of multiple competitive and non-competitive species have traditionally been handled using different methods. In particular, evolution processes of multiple competitive species have usually been evaluated by the continuous and discrete proportions analysis; however, such evolution processes cannot be solely characterized by their relative proportions in practice. In this paper, we introduce a community based Poisson model with multivariate random effects to explicitly characterize marginal counts and respective proportions simultaneously. Furthermore, our method provides a unified approach to handle evolution processes of competitive and non-competitive species. In fact, the existence and strength of the competition among species can be assessed through our approach. Unlike those marginal modelling methods, our approach explicitly predicts random effects. Our model inference does not rely on distributional assumption of observed multivariate random effects, and thus is more robust than traditional approaches assuming parametric random effects.
PubDate: 2021-01-02
DOI: 10.1007/s10651-020-00472-2

• Special Issue: Statistical mathematics for ecological and environmental
data
• PubDate: 2020-11-17
DOI: 10.1007/s10651-020-00474-0

• Financial development, globalization and ecological footprint in G7:
further evidence from threshold cointegration and fractional frequency
causality tests
• Abstract: This paper empirically explores the dynamic relationships between financial development, globalization, energy consumption, economic growth, and ecological footprint in G7 countries over the period 1980–2015. Using a recently introduced threshold cointegration test with an endogenous structural break, the paper aims primarily to determine the effects of financial development and globalization on environmental degradation. The results confirm the presence of cointegration in Canada, Italy, and Japan. The long-run estimates indicate that globalization significantly reduces ecological footprint in Canada and Italy, while financial development reduces pollution in Japan. The findings also demonstrate that energy consumption stimulates environmental degradation in these three countries. Furthermore, the causality test that considers smooth structural breaks via a fractional frequency flexible Fourier function indicates that globalization causes ecological footprint in all the G7 countries except France, while financial development causes ecological footprint in France, Japan, and the United Kingdom. Finally, the overall results suggest that globalization is a more effective tool than financial development in regulating ecological footprint for G7 countries. Therefore, we recommend that policymakers should make use of the opportunities that globalization offers to solve environmental problems.
PubDate: 2020-10-26
DOI: 10.1007/s10651-020-00467-z

• A puzzle over ecological footprint, energy consumption and economic
growth: the case of Turkey
• Abstract: The paper investigates the non-linear causality from energy consumption and economic growth to ecological footprint for the case of Turkey by employing ARDL Models and ECM-Based Granger Causality over the period from 1961 to 2016. The major contribution of the article to the literature is that (i) the data period of the empirical analysis of the study is much longer than the one of the other studies for the case of Turkey; (ii) ecological footprint, which has been rarely used in the studies for the same case is taken as a sophisticated proxy of environmental degradation; (iii) it is found that the sophisticated key term ‘awareness’ needs much more multidisciplinary attention and wider mind maps as the causality from energy consumption to ecological footprint has U-shape; (iv) the non-linear causality is investigated and the complicated puzzle is discussed in the framework of a wide and coherent mind map.
PubDate: 2020-10-09
DOI: 10.1007/s10651-020-00465-1

• A far-near sparse covariance model with application in climatology
• Abstract: Teleconnection, the strong dependence between two distant locations, provides interesting information for discovering the structures in spatial data. While teleconnections are often sparse and estimated through sample correlations, there are also abundant correlations among nearby locations. We propose a far-near covariance model that simultaneously models the abundant short-distance dependencies and the sparse long-distance dependence. This approach provides a new framework for utilizing the short-distance dependence structure to improve the exploration and estimation of the sparse remote dependence signals. The statistical properties of proposed estimators are provided. The detection of teleconnection in high-dimensional data is a multiple testing problem. We relate this detection problem to $$\tau$$ -coherence statistical testing and generalize the $$\tau$$ -coherence for the covariance matrix of two-dimensional grid locations. The applications are illustrated through numerical studies on both synthetic data and real climate data.
PubDate: 2020-09-18
DOI: 10.1007/s10651-020-00462-4

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