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Energy, being one of the significant drivers of growth, has gained much focus in the last four decades. A connection between energy and growth exists in the economy: on the one hand, energy is a vital factor of production while growth improves living standards, which increases energy consumption on the other hand. Previous studies on the energy‐growth nexus paid less attention to sectorial differentials in the consumption of energy and growth. Also, the literature could not relate that to sustainable development. Thus, this study explores the sectorial differentials in energy consumption and how they affect the energy‐growth nexus within the context of sustainable development. The research employed secondary data for 46 sub‐Saharan Africa (SSA) countries for the period 2007 to 2020. Using the General Methods of Moments estimation technique, we found that all the measures of energy consumption positively affect economic growth. Also, CO2 intensity is positively related to growth in the economy while CO2 emissions from solid fuels negatively affect economic growth. Again, Foreign Direct Investment (FDI) is positively impacting economic growth and Gross Domestic Product (SSA) per energy use. Policy implications are discussed in the paper. [ABSTRACT FROM AUTHOR]

This study examines the nexus between disaggregated energy consumption (EC), CO2 emissions, and economic growth in emerging South and East Asian countries over the period of 1994 to 2019. The long‐run equilibrium relationship is determined by using the "Autoregressive distributed lag (ARDL) model" and the "Generalized least square (GLS) technique." The panel causality test developed by "Dumitrescu and Hurlin, 2012" determines the direction of causation between variables. Disaggregated EC and CO2 emissions positively affect economic growth in the research. The PMG estimate also validates the GLS findings, which produce the same results as the PMG estimation. To check the robustness, we also use FMOLS and DOLS estimators. The results confirm the feedback hypothesis for South and East Asian nations regarding energy uses, CO2 emissions, and economic growth. In contrast, there is unidirectional causality between industrial development and economic growth. These findings will help governments in South and East Asia craft effective energy policy regulations for their financial institutions. [ABSTRACT FROM AUTHOR]

This study corroborates the importance of United Nations Sustainable Development Goal 7 (SDG‐7), intended to ensure access to affordable, reliable, sustainable energy for all, and SDG‐8, designed to promote decent work and sustainable economic growth. This article is motivated by the highlighted SDGs and empirically explores the long‐run and causality relationship between energy consumption, urbanization, trade openness, and economic growth for annual frequency data from 1965 to 2021 for the case of Mexico. To this end, we leverage the use of fully modified ordinary least squares, dynamic ordinary least squares, and canonical regression estimation methods, while for the direction of causality, the gradual shift and wavelet coherence methods are used. According to the Autoregressive distributed lag (ARDL), the bounds test traces a long‐run relationship between the outlined variables over the sampled period. Empirical evidence validates the energy‐induced growth hypothesis. This result resonates with the causality analysis, where energy consumption drives economic growth one way in Mexico. This suggests that Mexico cannot embark on energy‐conservative policies, as such actions will hurt economic progress. In addition, unidirectional causality is seen between urbanization, trade openness, and economic growth. These findings have far‐reaching implications for economic growth and macroeconomic indicators in Mexico. More insights are highlighted in the concluding section. [ABSTRACT FROM AUTHOR]

We report the results of position ties for short baselines at eight geodetic sites based on phase delays that are extracted from global geodetic very‐long‐baseline interferometry (VLBI) observations rather than dedicated short‐baseline experiments. An analysis of phase delay observables at X band from two antennas at the Geodetic Observatory Wettzell, Germany, extracted from 107 global 24‐hr VLBI sessions since 2019 yields weighted root‐mean‐square scatters about the mean baseline vector of 0.3, 0.3, and 0.8 mm in the east, north, and up directions, respectively. Position ties are also obtained for other short baselines between legacy antennas and nearby, newly built antennas. They are critical for maintaining a consistent continuation of the realization of the terrestrial reference frame, especially when including the new VGOS network. The phase delays of the baseline WETTZ13N–WETTZELL enable an investigation of sources of error at the sub‐millimeter level. We found that a systematic variation of larger than 1 mm can be introduced to the Up estimates of this baseline vector when atmospheric delays were estimated. Although the sub‐millimeter repeatability has been achieved for the baseline vector WETTZ13N–WETTZELL, we conclude that long term monitoring should be conducted for more short baselines to assess the instrumental effects, in particular the systematic differences between phase delays and group delays, and to find common solutions for reducing them. This will be an important step toward the goal of global geodesy at the 1 mm level. Plain Language Summary: We report the results of position ties for short baselines at eight geodetic sites based on phase delays that are extracted from global geodetic very‐long‐baseline interferometry (VLBI) observations rather than dedicated short‐baseline experiments. By using the inherently more precise observables—phase delays, a baseline vector repeatability of WETTZ13N–WETTZELL has been achieved at the sub‐millimeter level for the horizontal directions and at the 1 mm level for the vertical direction based on VLBI experiments of 107 days during 3.5 years. Position ties based on phase delays are also obtained for other short baselines between legacy antennas and nearby, newly built antennas, and they are critical to maintain a consistent continuation of the realization of terrestrial reference frame into the future of a network of these new antennas. We have evaluated the instrumental stability at the 1 mm level, which is an important step toward the goal of global geodesy at this level. Key Points: Baseline vectors between legacy antennas and co‐located VGOS antennas are obtained from phase delays with the highest possible precisionSources of error in short‐baseline observations are investigated at the 1 mm level in terms of their potential impacts [ABSTRACT FROM AUTHOR]

By adopting Westerlund's panel cointegration test, and the panel Granger, non‐causality test, this study investigates the long‐run and causal relationship between energy consumption and economic growth and energy transition in Africa. The test took into account cross‐sectional dependency for five African areas from 1990 to 2018. The models additionally contain labour and capital stocks to investigate causality and cointegration in the areas. The cross‐sectional dependency test shows that the African region sample is cross‐sectionally correlated. The panel cointegration test shows evidence of a long‐run relationship between economic growth, energy consumption, labour and capital stock in all areas. The non‐causality result shows a uni‐directional causality from economic growth to energy use. [ABSTRACT FROM AUTHOR]

This study exposes the potential role of financial development to determine economic growth and utilisation of energy. Moreover, it also identifies how information communication technology (ICT) moderates this relationship. By sampling a large range of data from 138 economies for the year 1980–2020, the current study employs the panel least square model to test the regression. The result reveals that economic growth and information communication technology have a positive significant impact on energy utilisation. Financial advancement has a direct significant effect on energy utilisation and economic growth. Similarly, the moderating role of ICT was also observed in the current analysis. The current analysis guides policymakers on the relevant role of financial development in improving the economic status and consumption of energy. The policymakers in these various countries should balance the connection between the supply and demand of energy to accomplish the sustained development of the economies. Furthermore, the analysis speaks about the significance of ICT in boosting energy consumption and gives an important policy recommendation regarding the role of ICT both in economic growth and energy utilisation. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic has had a significantly negative impact on all transportation modules, especially air passengers. The authors aimed to forecast the air passenger load factor using time series modelling for the affecting variables. After providing general information about this pandemic, the forecasting results regarding getting back into the recovery period were presented by time series modelling. The last five years (2016–2020) and the first eight months of 2021 were examined with the following variables: available seat kilometre, revenue passenger kilometre, passenger load factor, gross domestic product, and domestic and international passenger numbers. The forecast results reveal that the recovery period started in June of 2021 and continues with a robust growth trend until September 2021 due to the vaccination process and the starting of the summer season. This trend changed between September to November 2021 slightly negative, from November 2021 to January 2022 slightly positive, and from January 2022 to March 2022 mildly negative. Correspondingly, passenger load factor (PLF) is affected by itself and domestic transportation in the short‐term period. This effect seems short‐term in domestic and international transport. This research reveals that minimising the economic damage by benefiting from the increasing trend of air passenger numbers increases the recovery period. [ABSTRACT FROM AUTHOR]

The growing apprehension of global warming, greenhouse gas emissions and increasing use of fossil fuel due to emergent economic activity signifies that for the sustainability of the environment cleaner energy use is important. In the same pursuit, this study aims to examine the energy, environment and economic growth nexus of Bangladesh, incorporating both renewable and non‐renewable energy consumption with forest depletion. We have employed the Two‐Stage Least Square approach to avoid likely simultaneity bias and possible endogeneity of the variables arising from the ordinary least squares. Result postulates non‐renewable energy consumption and forest depletion have a significant impact on CO2 emission, whereas renewable energy shows no significant consequence. The issue which arises in this regard is that renewable energy consumption has not yet reached a stage from where it could play a substantial role in emission reduction of the country. Therefore, countries should adopt policies that would provide a conducive environment for affordable energy use. [ABSTRACT FROM AUTHOR]

In causal relationship studies, the latent variables may summarize the phenotypes in theoretical traits according to their phenotypic correlations, improving the understanding of causal relationships between broilers phenotypes. In this study, we aimed to investigate potential causal relationships among latent variables in broilers using a structural equation model in the context of genetic analysis. The data used in this study comprised 14 traits in broilers with 2,017 records each, and 104,154 animals in pedigree. Four latent variables (WEIGHT, LOSSES, COLOUR, and VISCERA) were defined and validated using Bayesian Confirmatory Factor Analysis. Subsequently, a search for causal linkage structures was performed, obtaining a single causal link structure between the latent variables. Then, this information was used to fit the structural equation model (SEM). The results from the SEM indicated positive causal effects of the variables WEIGHT and LOSSES on the variables VISCERA and COLOUR, respectively, with structural coefficient estimates of 1.006 and 0.040, respectively. On the other hand, an antagonist causal effect of the variable WEIGHT on the variable LOSSES was verified, with a structural coefficient estimate of −4.333. These results highlight the causal relationship between performance and meat quality traits, which may be associated with the natural processes involved in the conversion of muscle into meat and the structural changes in muscle tissues due to intense selection for high growth rates in broilers. [ABSTRACT FROM AUTHOR]

This paper investigates the association among energy consumption, carbon‐dioxide emission, and India's economic growth along with supplemental variables including foreign direct investment, population density, inflation, and agricultural land. An autoregressive distributive lag model is applied over annual time‐series data from 1985 to 2019. Further, the robustness and novelty of the model are confirmed by applying fully modified ordinary‐least‐square, dynamic ordinary‐least‐square, canonical co‐integrating regression, variance decomposition, and impulse response function. The analysis results indicate that a cointegration association exists among variables. In the short run, the profound determinants of economic development are energy consumption, carbon‐dioxide emission, inflation, and agricultural land. In the long run, both inflation and agricultural land significantly negatively influence economic growth while carbon emission drives a positive impact. Interestingly, a one‐way Granger causality runs from economic growth towards energy consumption, carbon emission, and agricultural land. The new research presents a comprehensive understanding of economic growth indicators, aiding policymakers, and advancing existing literature. Consequently, as a recommendation, the policymakers should constitute explicit goals for renewable energy consumption to stimulate sustainable economic growth with carbon emission reduction. [ABSTRACT FROM AUTHOR]

This empirical study examines the causal links among renewable energy consumption (REC) and non‐renewable energy consumption (NREC) and economic growth in Germany, the UK and France between 1980 and 2019. To this purpose, we use two different approaches: Toda and Yamamoto (Journal of Econometrics, 66, 1995, 225) time causality test and Lemmens et al. (International Journal of Forecasting, 24, 2008, 414) frequency causality test. For UK and France, the results show no significant causality between Gross Domestic Product (GDP) and REC, which supports the neutrality hypothesis. Regarding NREC, similar findings are obtained. However, for Germany, the time approach indicates bi‐directional causality between REC and GDP, while the frequency approach shows uni‐directional causality from REC to GDP in the long‐run. Therefore, there is a consensus on the growth hypothesis in Germany. Furthermore, the frequency analysis displays also one way causal nexus running from Germany's GDP to NREC in long horizons. The policymakers in UK and France should take into account that renewables and energy conservation policies are neutral in respect to economic growth. As for Germany, measures of reducing NREC would not significantly damage GDP, and renewable energies promotion plan would be beneficial for economic growth. [ABSTRACT FROM AUTHOR]

This paper investigates the nexus between energy consumption and economic growth in Bangladesh over the period 1971–2018 using the autoregressive distributed lag (ARDL) approach to cointegration. The main contribution of this study is the inclusion of exogenous dynamic (globalisation) and endogenous factor (political risk indicator measured by political terror scale (PTS)) to the energy consumption–economic growth nexus. The study explores an energy consumption–economic growth nexus where globalisation and PTS have both positive and negative influences on this relationship in the short run and long run. The Toda–Yamamoto Granger causality test confirms the feedback hypothesis, that is bidirectional causal relationship between energy consumption and economic growth, and the result is further verified by the impulse response function. Therefore, policymakers should enhance the availability of energy for people and industries to continue the existing momentum of economic growth. Besides, the government should cautiously deal with both the globalisation and political risk issues about energy consumption–economic growth nexus in Bangladesh. [ABSTRACT FROM AUTHOR]

There is a large literature examining the effects of agglomeration on income distribution but less is known about its effects in developing countries. In this study, we apply panel data from a microfirm‐level survey and from city‐level data to investigate whether there is a causal relationship between agglomeration and establishment wage dispersion in China. Given the potential endogeneity of city size, we employ an instrumental variable regression approach. We find strong evidence that agglomeration has significant effects on wage inequality in the short and long run. The link between agglomeration and wage inequality is heterogeneous across regions. The spatially varying results appear to be due to different stages of development. Our results are consistent with the sorting models in that it appears that the most productive and least productive firms are relatively thriving in coastal cities, but not inland. [ABSTRACT FROM AUTHOR]

Since the beginning of the 21st century, accompanied by the tremendous achievements of China's economic growth is an increasingly severe income gap between the rich and the poor. Based on panel data from 2000 to 2018, this study systematically examined the relationship among transport infrastructure, economic growth, carbon emissions, and income inequality in China, using the panel vector autoregressive model estimated by the generalized method of moments. We further divided China into three regions to investigate the regional heterogeneity of these relationships. The results show a long‐run equilibrium relationship between transport infrastructure, economic growth, carbon emissions, and income inequality. Income inequality in the previous year significantly affects that in the current year positively. Whether at the national or regional level, economic growth affects income inequality negatively. For the national sample, the highway reduces income inequality, while the railway increases income inequality. For both the subsamples and the national sample, carbon emissions significantly increase income inequality and are the Granger test cause for income inequality. Furthermore, we discuss some of the possible mechanisms of these results. Our findings generate policy implications for reducing income inequality in regard to economic growth, transport infrastructure, and carbon emissions. [ABSTRACT FROM AUTHOR]

Energy is the lifeblood of the global economy, a key input to almost all the goods and services of the modern world. The primary objective of this study is to examine the relationships between per capita energy consumption and per capita GDP in India from 1970–1971 to 2014–2015. The data analysis was conducted using the three‐stage Johnson cointegration, vector autoregression and Granger causality test. The results of the study documented that there was the presence of unidirectional causality running from per capita GDP to per capita energy consumption and the absence of a long‐term equilibrium relationship between per capita energy consumption and per capita GDP in India. More significantly, India has already demonstrated an impressive ability to develop, deploy, replicate and scale up innovative, market‐based approaches to energy efficiency. The country has an excellent basis for further energy efficiency policy innovation and market creation, including a strong community of non‐governmental organisations, research institutes and think tanks active in energy efficiency. [ABSTRACT FROM AUTHOR]

High income inequality has become a barrier to economic development for emerging economies. Education is commonly seen as a way to decrease income inequality; however, the empirical evidence is not convincing. By focusing on school performance, we take advantage of spatial econometrics to estimate a long‐run relationship showing that income inequality can be reduced by increases in school performance. In particular, our results show that increases in school performance at early stages of educational levels and using mathematics as the subject goal can decrease income inequality in the long run. We use the case of Chile, which presents high income inequality and low school performance compared to similar nations. [ABSTRACT FROM AUTHOR]

Summary: Inspired by constructing large‐size cointegrated portfolios, this paper considers a vector error correction model and develops the adaptive Lasso estimator of the cointegrating vectors. The asymptotic properties of the estimators and the oracle property of the adaptive Lasso are derived. An optimisation algorithm for estimating the model parameters is proposed. The simulation study shows the effectiveness of the parameter estimation procedures and the forecasting performance of our model. In the empirical study, we apply the proposed method to construct the sparse cointegrated portfolios with or without market‐neutral property. The trading performances of different types of cointegrated portfolios are evaluated using the Dow Jones Industrial Average composite stocks. The empirical findings reveal that the sparse cointegrated market‐neutral portfolios of a number of securities are capable to benefit the investors who wish to construct statistical arbitrage portfolios which are market‐neutral. [ABSTRACT FROM AUTHOR]

Summary: We examine the relationships between electoral socio‐demographic characteristics and two‐party preferences in the six Australian federal elections held between 2001 and 2016. Socio‐demographic information is derived from the Australian Census which occurs every 5 years. Since a census is not directly available for each election, an imputation method is employed to estimate census data for the electorates at the time of each election. This accounts for both spatial and temporal changes in electoral characteristics between censuses. To capture any spatial heterogeneity, a spatial error model is estimated for each election, which incorporates a spatially structured random effect vector. Over time, the impact of most socio‐demographic characteristics that affect electoral two‐party preference do not vary, with age distribution, industry of work, incomes, household mobility and relationships having strong effects in each of the six elections. Education and unemployment are among those that have varying effects. All data featured in this study have been contributed to the eechidnaR package (available on CRAN). This paper models all Australian federal elections from 2001‐2016 to examine the socio‐demographic drivers of electorates' two‐party preferred vote. [ABSTRACT FROM AUTHOR]

The study examined the responsiveness of the environment of Ghana to changes in key economic indicators such as the international trade, energy consumption, urbanization, economic growth, and financial development. Our study utilized the ecological footprint as the indicator for environmental degradation as it encompasses the entire ecosystem that supports humankind consumption and activities. Consequently, the use of ecological footprint gives a clear and a bigger picture of environmental degradation than any individual pollutant(s). This study takes into cognizance the influence of structural break in the time series variables. The findings from the dynamic ordinary least square (DOLS) established the existence of an inverted N‐shaped environmental degradation‐economic growth relationship for Ghana under the cubic EKC framework. The ARDL bound testing approach confirmed the presence of long‐run cointegration among the variables. Furthermore, the bootstrap causality revealed a unidirectional causality running from energy consumption to export and urbanization to export. Our study, therefore, advocates for the production and consumption of enhanced energy‐efficient products and commodities among the populace of Ghana. [ABSTRACT FROM AUTHOR]

This study proposes an efficient local energy management system (LEMS) based on the generalised power prediction model for the uncertain operation of renewable distributed generations (DGs)-based microgrid. Photovoltaic with battery energy storage, and wind power generation are considered as primary DGs to compensate intermittency. Conventional direct power prediction models are limited to specific DG applications, where the plant data acquisition system is a necessity. Solar irradiance and wind speed are considered here as prediction targets to cope with such additional expenditure for a microgrid. To ensure a robust reduction in prediction error (ep), a short-term prediction model is developed by virtue of the proposed robust regularised random vector functional link network. A maximum-likelihood estimator using Huber's cost function is employed to attain the robustness of this model. Further, a direct renewable energy source-power calculation is opted to address model accuracy under local uncertainties. The LEMS operation is completed by compensating ep with distributed adaptive droop-based primary controllers for multi-DG based microgrid. To ensure the performance of the prediction model, solar irradiance, wind speed and power at different atmospheric conditions (seasonal volatility) and time span (i.e. 5, 10 and 60 min) have been implemented in MATLAB and real time. [ABSTRACT FROM AUTHOR]

Unlike the retail‐like (for selected variables) statistical post‐processing methods, a wholesale‐like (for all variables) dynamical approach is proposed to correct forecast bias during model integration. Subtracting a bias tendency from the model total tendency is intended to de‐bias all variables at once to better (i.e. more dynamically consistent) couple with downstream applications. Three experiments were tested using an ensemble prediction system since the method is intended for an ensemble model. The verification was carried out over China for a period of 31 days (1–31 July 2015). The verification of 500 hPa temperature indicates that all three experiments have significantly improved the raw ensemble forecasts with reduced bias error, a more accurate ensemble mean, a better spread‐skill relationship, and more reliable and sharper probabilities. The performance is better than or comparable to the current operational statistical method. When the verification was expanded to include more variables, a summary scorecard shows that the three experiments also had a general positive or neutral impact on both upper‐air and surface variables, especially the height and temperature fields. Precipitation forecasts remained relatively unchanged. There were only a few categories that were degraded. The comparison between the three experiments yielded a mixed result: the most sophisticated approach often performed the best for 500 hPa temperature, while the simplest approach worked the best when verifying a mixture of variables. The degradation of the wind forecasts by the third experiment was discussed. These are the two challenges: how to accurately describe the bias tendency and how to add internally coherent bias tendencies to multiple variables. Given its advantages, this approach could be a promising approach for correcting biases in a numerical model. [ABSTRACT FROM AUTHOR]

Energy consumption is closely related to industrial structure, economic prosperity, and population. Because of the Granger causal relationship between GDP and energy consumption, many researchers consider the regression method to predict energy consumption using economic variables. However, some other researchers regard the time series method (forecast) to estimate for energy consumption. To address the advantages and disadvantages of two methods in energy consumption prediction, we performed the deep learning (DL) based on the case of China. The experiment results show that the accuracy of time series forecast is much higher than regression methods. In addition, we also explored the relationship between industry, economy, population, and energy consumption. We found that GDP, population, secondary sector, and tertiary sector were significant to energy consumption. A tertiary sector can help to reduce energy consumption to some extent. This could give suggestions about changing industry structure. More and more attention has been paid to energy intensity. The strategic approach to sustainable development requires reducing energy intensity while developing the economy. Since China is committed to achieving carbon emission peak by 2030, this paper predicts the energy intensity of China in the next decade based on a DL algorithm. The prediction results show that energy intensity would slightly decrease in the next decade. Different types of energy represent the industrial structure behind economic growth. Therefore, this paper was conducted using ridge regression (RR) to explore the relationship between different types of energy and energy intensity. In addition, the effect (positive or negative) of different energy sources in reducing energy intensity has also been explored. We found that the best way of developing the economy and reducing energy consumption is to use natural gas and hydroelectric instead of coal. This can guide policy development about changing energy source structure. [ABSTRACT FROM AUTHOR]

Agriculture is one of the primary contributors to Pakistan's economy. However, over the last few decades, the atmospheric carbon dioxide emission has been amplified to a great extent in Pakistan. This amplification may cause climate change, global warming, and environmental mitigation in Pakistan. This paper empirically investigates the impact of CO2 emissions on the agricultural export trade of Pakistan over the period 1975–2017. Evidence suggests that climate change could be a primary cause for the decline in Pakistan's agriculture export trade; no studies have been carried out for this specific issue, particularly over time. In this paper, the empirical analysis suggests the negative coefficient of agriculture export trade with CO2 emissions subsequently decreases agriculture export trade, which leads to direct impact on Pakistan's economy. Both theoretical and empirical outcomes suggest that the adaptation of clean and green energies and technologies are the key to reduce pollution in Pakistan. Overall, the effects of carbon dioxide emissions on agriculture export trade are stronger in the long‐run dynamics, thus making the finding heterogeneous. Possible initiatives should be taken by the government of Pakistan to improve the agriculture sector and it should also introduce new policies to reduce the emissions of carbon dioxide. [ABSTRACT FROM AUTHOR]

Foreign direct investment is an engine of economic growth. However, it may affect environmental quality (improve or deteriorate it), depending on the context. Under a multivariate framework, this paper aims to investigate the relationship between foreign direct investment and deforestation for Sub‐Sahara African countries with economic growth, trade openness and urbanization as additional determinants of deforestation. The analyses reveal that all variables are non‐stationary and cointegrated based on recent panel data techniques. On applying dynamic ordinary least squares, the long‐run results suggest the validity of the pollution haven hypothesis for some countries, and that of the pollution halo hypothesis for other countries. The findings are also mixed across Sub‐Sahara African countries for trade openness and urbanization. The results from this study suggest that Sub‐Sahara African countries should continue attracting foreign direct investment, while a certain number of them should put more emphasis on controlling deforestation associated with foreign direct investment inflows to limit greenhouse gas concentrations in the atmosphere. [ABSTRACT FROM AUTHOR]

This study aims to investigate the validity of the pollution haven hypothesis for the global panel consisting of 29 countries (Bahrain, Israel, Jordan, Saudi Arabia, Turkey, United Arab Emirates, Oman, Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, Uzbekistan, China, Japan, Mongolia, Hong Kong, Korea rep, Bangladesh, India, Pakistan, Sri Lanka, Nepal, IR Iran, Indonesia, Malaysia, Philippines, Singapore, Thailand and Vietnam are taken as the sample of this study) with energy consumption, economic growth and trade openness as additional determinants of environmental degradation over the period 1994–2014. To make the panel data analysis more homogenous, we also investigate the validity of the PHH for a number of sub‐panels. These sub‐panels are constructed based on the sub‐regions of Asia. In this way, we end up with six Asian panels; namely, Global panel, West Asia, Central Asia, East Asia, South Asia and Southeast Asian panels. Based on the IPS and ADF chi‐square unit root test and Pedroni cointegration test results, all variables were found to be first difference stationary and cointegrated. On applying FMOLS, the long‐run results suggest the presence of the pollution haven hypothesis only in East Asian panel. In turn, foreign direct investment reduces environmental degradation, thus rejecting the validity of the pollution haven hypothesis (PHH) in the Southeast Asian panel which is found to be negatively linked to CO2 emissions. Moreover, energy consumption seems to be the main determinant of carbon emissions and GDP growth has a positive impact on it in all panels except West Asia. Lastly, East Asian countries have followed the Kyoto protocol in order to reduce their emissions level. [ABSTRACT FROM AUTHOR]

The aims of the present study are to represent the concept of restricted breeding values algebraically and to propose a criterion for evaluating the genetic responses achieved by using a restricted selection procedure. An additive genetic mixed model characterized by multiple traits with constraints was assumed. If the random errors approach zero and the fixed effects can be completely estimated correctly in the model, the restricted best linear unbiased predictor of breeding values (uR) is equal to [Iq−G0C0(C0′G0C0)−1C0′]⊗Iu, where G0, C0, and u are the additive genetic variance‐covariance matrix for the q traits, the matrix for restriction, and the vector of breeding values, respectively. Therefore, if we want to evaluate the response to restricted selection, such as by a stochastic computer simulation study with known breeding values, we can use uR as only one criterion. [ABSTRACT FROM AUTHOR]

This paper derives the Ramsey optimal fiscal policy for taxing asset income in a model where government expenditure is a function of net output or the inputs that produce it. Extending work by Kenneth L. Judd, I demonstrate that the canonical result that the optimal tax on capital income is zero in the medium to long term is a special case of a more general model. Employing a vector error correction model to estimate the relationship between government consumption and net output or the factor inputs that generate it for the United States between 1948Q1 and 2015Q4, I demonstrate that this special case is empirically implausible, and show how a cointegrating vector can be used to determine the optimal tax schedule. I simulate a version of the model using the empirical estimates to measure the welfare implications of changing the tax rate on asset income, and contrast these results with those generated in a version of the model where government consumption is purely exogenous. The shifting pattern of welfare measurements confirms the theoretical results. I calculate that the prevailing effective tax rate on net asset income in the United States between 1970 and 2014 averaged 0.449. Hence abolishing the tax completely does generate welfare improvements, though only by the equivalent of between 1.103% and 1.616% permanent increase in consumption-well under half the implied welfare benefit when the endogeneity of the government consumption is ignored. The maximum welfare improvement from shifting part of the burden of tax from capital to labor is the equivalent of a permanent increase in consumption of between only 1.491% and 1.858%, and is attained when the tax rate on asset income is lowered to between 0.148 and 0.186. Allowing the tax rate to vary over time raises the maximum welfare benefit to 1.865%. All the results are very robust to a wide range of elasticities of labor supply. ( JEL E62, H21, H50) [ABSTRACT FROM AUTHOR]

This research examines the causality between energy consumption and economic growth in the Philippines, and determines their long‐run relationship by including labour force and gross fixed capital formation. Results show that the variables were found to be stationary at first difference and that cointegration existed among the variables, suggesting causality in at least one direction. They also show that GDP is dependent on energy consumption, indicating that the growth hypothesis applies in the Philippines. Moving from non‐renewable to renewable energy without securing the supply of energy can possibly limit economic growth. This inference is crucial in policy development, particularly when it comes to energy conservation and switching to renewable energy sources. Considering that the Philippines remains a developing country and needs to produce energy at least cost, policy‐makers must ensure the supply of energy before deciding to switch to renewable energy and must also consider the high cost of generating renewable energy. [ABSTRACT FROM AUTHOR]

The aim of this study is to explore the dynamic linkage between energy efficiency and total factor productivity ( TFP) using carbon emission and trade openness as control variables for the period of 1971-2013. For this purpose, vector error correction mechanism ( VECM) is employed to determine the direction of causality. A popular and simple measure of energy efficiency, GDP per unit of energy use and trade as a percentage of GDP are used for the proxy of trade openness. The result shows negative impact of energy efficiency on TFP, in other way energy intensity has a positive impact on the growth of TFP. Hence, the negative sign indicates a trade-off between energy efficiency and TFP. There is a unidirectional causality running from energy efficiency to TFP. Whenever energy intensity increases, the TFP level increases as well. So, in the long run, a higher TFP implies higher energy consumption. Further, TFP and carbon emission Granger cause trade openness, and there is unidirectional causality from TFP to CO2 emission. [ABSTRACT FROM AUTHOR]

The paper statistically examines whether the fluctuations in crude oil prices over the last 10 years are due to speculative activities or changes in market fundamentals. Following a brief review of the oil market developments and speculative activities in recent years, the paper employs two multivariate time series models-the vector autoregressive model (VAR) and the vector error correction model (VECM)-to evaluate observed fluctuations in crude oil prices. The VAR and its granger test allow for the detection of factors responsible for fluctuations in crude oil prices, while the VECM tests the co-integration of the variables. The VAR includes both fundamental and non-fundamental variables as covariates. The VECM results show that in both the short- and long-term the significant variables of the VAR model are co-integrated. The empirical results confirm that in the long-term the fundamentals are the main drivers of crude oil prices. However, in the short term, both fundamentals and speculative positions in the oil futures market differentially cause fluctuations in crude oil prices. The effect of the fundamentals is more than double in the long term, when compared to the short-term. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic causal relationship between energy consumption, human capital investment and economic growth in South Africa for the period 1960-2015 within the vector error correction model ( VECM) framework. It was revealed that there is cointegration among the variables. The causality test result reveals that there exists a long-run bi-directional relationship between economic growth and energy consumption. While on the other hand, a long-run unidirectional causal relationship was discovered running from economic growth and energy consumption to social and economic infrastructure investment. This justifies the government's massive investment in the energy sector which is aimed at meeting the increasing energy demand. However, the lack of feedback from social infrastructural investment may imply that the focus social infrastructure investment is not adequate to granger cause growth or due to high inequality and unemployment in the country which will require more investment attention for it to significantly affect growth. The government, therefore, should give priority to the provision of both social and economic infrastructure investment and implementation of policies that are aimed at human capital development through public empowerment so that they can support the economy instead of depending on the government. [ABSTRACT FROM AUTHOR]

This study investigates the estimation of continuous-time Box–Jenkins model parameters from irregularly sampled data. The Box–Jenkins structure has been successful in describing systems subject to coloured noise, since it contains two submodels that feature the characteristics of both plant and noise systems. Based on plant-noise model decomposition, a two-step iterative procedure is proposed to solve the estimation problem, which consists of an instrumental variable method for the plant model and a prediction error method for the noise model. The proposed method is of low complexity and shows good estimation robustness and accuracy. Implementation issues are discussed to improve the computational efficiency. Numerical examples are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This study investigates the influence of biofuel energy consumption on Brazil's economic growth during the period 1980-2012 by employing the Autoregressive Distributed Lag ( ARDL) approach and the vector error correction model ( VECM) Granger causality. The results revealed two structural breaks during the early 1980s due to the Latin American debt crisis as well as the early 2000s due to the worries related to the increasing global spreads. Moreover, it was found that economic growth, biofuel energy consumption, capital, urbanization, and globalization are co-integrated. Additionally, it was found that biofuel energy consumption, capital, urbanization, and globalization increase Brazil's economic growth in the short run and in the long run. However, the two structural breaks have a significant negative influence on economic growth. The vector error correction model Granger causality revealed a feedback causal relationship between all the variables (with the exception of capital). However, a unidirectional causality was concluded from capital to economic growth, biofuel energy consumption, urbanization, and globalization. From the results of this study, a number of policy implications were provided. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd [ABSTRACT FROM AUTHOR]

The meteoric decline in oil price in late 2014, a manifestation of crude oil price volatility, pressured the fiscal positions of many oil-exporting countries (OECs). This study examined the relationship between oil price volatility and OECs' fiscal policy [proxied by primary fiscal balance (PFB)] responses. It estimated a small open-economy aggregate demand model in which oil price is externally determined. Using various measures of oil price volatility in a vector error correction (VEC) model, this study established that fiscal policies in OEC were not procyclical but driven by oil price volatility. Oil price volatility reduced PFB in the short run. In the long run however, PFB rose in response to price volatility, suggesting that OECs' governments eventually consolidate their fiscal positions to reduce short-run fiscal deficit induced by oil price volatility. Though their fiscal policies were pressured in the short run, OECs were able to stabilise their fiscal dynamics in the long run. [ABSTRACT FROM AUTHOR]

The fast increase in oil prices in the past 15 years and the spectacular fall in 2008 and in 2014 has led to the rethinking of supply and demand as the only determinant price. It has been observed in the last decade that large financial institutions, hedge funds, index funds and other investment funds invest billions of dollars in the futures market benefiting from the changes in oil prices. We considered the net long position of each trader category in the New York Mercantile Exchange to estimate, through the Vector Error Correction Model (VECM), the impact of each category on oil price and on volatility. Similarly, we also consider quarterly world oil demand, supply, inventories and industrial production from 1993 and 2015. The results show that fundamental variables have a strong and longlasting relationship with oil price. Unlike the fundamental variables, the non-fundamental variables very quickly became stable and react in a different way when the prices of oil rise and fall. The results show that the main factor for the increase of the price in 2008 was the higher than expected demand. For the 2014 decline the VECM shows that supply is the main force behind it. The non-fundamental variables together can explain almost 11 per cent of the variations of the price in 2008-2009. However, for the 2014-2015 period, the non-fundamental combined explained only 5 per cent. The non-fundamental have low share in the changes in oil price despite having a strong effect on volatility. [ABSTRACT FROM AUTHOR]

On the basis of the kinematic model of a unicycle mobile robot in polar coordinates, an adaptive visual servoing strategy is proposed to regulate the mobile robot to its desired pose. By regarding the unknown depth as model uncertainty, the system error vector can be chosen as measurable signals that are reconstructed by a motion estimation technique. Then, an adaptive controller is carefully designed along with a parameter updating mechanism to compensate for the unknown depth information online. On the basis of Lyapunov techniques and LaSalle's invariance principle, rigorous stability analysis is conducted. Because the control law is elegantly designed on the basis of the polar-coordinate-based representation of error dynamics, the consequent maneuver behavior is natural, and the resulting path is short. Experimental results are provided to verify the performance of the proposed approach. [ABSTRACT FROM AUTHOR]

The study explores Africa's regional integration models with a view to determining their suitability or otherwise for rapid economic growth. Using annual data spanning 1980-2012, the study employs the Johansen () and the Johansen and Juselius () method of cointegration and Vector Error Correction Mechanism (VECM) to test for the presence of long-run equilibrium relationships among the variables and estimate their static and dynamic coefficients. The study found a significant positive role for infrastructure financing, and human and physical capital accumulation both of which significantly influenced Africa's economic growth. Intra-African trade, though positive and significant, was found to be less effective in inspiring growth compared to the above growth fundamentals. Trade openness and government spending were the only variables discovered to significantly influence Africa's economic growth in both the short and long run. The study concludes that the traditional approach to regional integration may not provide the best alternative for Africa's economic growth. It, thus, recommends the adoption of a mixed policy approach to regional economic integration to foster Africa's economic growth in the 21st century. The contribution of the study lies in its ability to subject Africa's models of regional integration to practical examination using modern approaches. [ABSTRACT FROM AUTHOR]

The response by regional and national economies to exogenous impulses has a well-established literature in both spatial econometrics and in mainstream econometrics and is of considerable importance given the post-2007 economic crisis, which is characterized by a period of severe global instability resulting from unprecedented economic shocks. This paper focuses on dynamic counterfactual predictions and impulse-response functions derived from appropriate econometric models. These provide insight regarding the question of whether responses to economic shocks are transitory or whether they have a permanent effect. Analysis shows that output shocks have had permanent effects on productivity so that economies have tended not to return to the pre-shock path but rather adjust to new levels. This suggests that the current recession will be embodied permanently within the memory of some of Europe's leading economies as a hysteretic effect. [ABSTRACT FROM AUTHOR]

The study investigated whether the depreciation of exchange rate has a favourable impact on trade balance in Nigeria, based on the Marshall-Lerner (ML) condition. The Johansen method of cointegration and vector error correction methodology (VECM) was employed to investigate the existence of a long-run relationship between trade balance and the specified set of independent variables. The results confirm the satisfaction of the Marshall-Lerner condition in Nigeria, implying that depreciation of the exchange rate has a positive effect on trade balance in the long run. The study also established that a one per cent depreciation in the exchange rate would improve trade balance by 1.16 per cent. In the light of these findings, the study recommends a gradual depreciation of the exchange rate, which should be accompanied with export policy that encourages domestic production of non-oil products for exports. [ABSTRACT FROM AUTHOR]

This study explores the causal relationship among electricity consumption, economic growth and CO2 emissions for a group of 14 sub-Sahara African (SSA) countries from 1980 to 2009 using panel cointegration and panel vector error correction modelling methods. The findings demonstrate that in the long run electricity consumption has a statistically significant positive impact on CO2 emissions. The results also reveal that the inverted U-shaped Environmental Kuznets Curve (EKC) hypothesis exists in the SSA countries' case. The panel causality tests indicate that there is short-run unidirectional causality running from economic growth to CO2 emissions and electricity consumption respectively. Simultaneously, there is long-run bidirectional causality between electricity consumption and economic growth, electricity consumption and CO2 emissions, economic growth and CO2 emissions. Depending on the results, relevant policies can be initiated without negatively affecting economic growth. [ABSTRACT FROM AUTHOR]

Vector autoregressive (VAR) models with error-correction structures (VECMs) that account for cointegrated variables have been studied extensively and used for further analyses such as forecasting, but only with single-frequency data. Both unstructured and structured VAR models have been estimated and used with mixed-frequency data. However, VECMs have not been studied or used with mixed-frequency data. The article aims partly to fill this gap by estimating a VECM using the expectation-maximization (EM) algorithm and US data on four monthly coincident indicators and quarterly real GDP and, then, using the estimated model to compute in-sample monthly smoothed estimates and out-of-sample monthly forecasts of GDP. Because the model is treated as operating at the highest monthly frequency and the monthly-quarterly data are used as given (neither interpolated to all-monthly data, nor aggregated to all-quarterly data), the application is expected to be unbiased and efficient. A Monte Carlo analysis compares the accuracy of VECMs estimated with the given mixed-frequency data vs. with their single-frequency temporal aggregate. [ABSTRACT FROM AUTHOR]

This paper examines the determinants of current accounts balance in Nigeria with emphasis on oil-related variables using the Johansen-Julius vector error correction estimation approach, the impulse response function and the variance decomposition analysis. The results showed that oil price, oil balance and oil revenue are positively related with the current account, with only oil wealth having a significant negative impact in the long run. We find that the impact of oil price on the current balance is only significant in the short run. The variance decomposition analysis indicated that the variance in the current account is better explained by shocks to itself followed by shocks to oil price, oil balance and fiscal balance. [ABSTRACT FROM AUTHOR]

Longitudinal data analysis focused on internal characteristics of a single time series has attracted increasing interest among psychologists. The systemic psychological perspective suggests, however, that many long-term phenomena are mutually interconnected, forming a dynamic system. Hence, only multivariate methods can handle such human dynamics appropriately. Unlike the majority of time series methodologies, the cointegration approach allows interdependencies of integrated (i.e., extremely unstable) processes to be modelled. This advantage results from the fact that cointegrated series are connected by stationary long-run equilibrium relationships. Vector error-correction models are frequently used representations of cointegrated systems. They capture both this equilibrium and compensation mechanisms in the case of short-term deviations due to developmental changes. Thus, the past disequilibrium serves as explanatory variable in the dynamic behaviour of current variables. Employing empirical data from cognitive psychology, psychosomatics, and marital interaction research, this paper describes how to apply cointegration methods to dynamic process systems and how to interpret the parameters under investigation from a psychological perspective. [ABSTRACT FROM AUTHOR]

In this paper we contribute to the empirical literature on the size of network effects of public infrastructures. A novel approach is introduced to this purpose. Moving from estimates of the common dynamics shared by the regional public capital stock series, identification of co-ordinated policy shocks is obtained within a properly specified structural vector error correction model. Our empirical findings confirm previous evidence that transport infrastructures exert positive effects in the long run. At the same time, we find evidence that this influence is mostly attributable to the impact of co-ordinated public policy shocks, as predicted by the literature on network externalities. Resumen En este artículo contribuimos a la literatura empírica sobre el tamaño de los efectos de red de infraestructuras públicas. Para este propósito se presenta un enfoque novedoso. A partir de estimaciones de las dinámicas comunes compartidas por series de reservas de capital público regional, la identificación de perturbaciones políticas se realiza dentro de un modelo de corrección del error vectorial estructural debidamente especificado. Nuestros descubrimientos empíricos confirman indicios anteriores de que las infraestructuras de transporte ejercen efectos positivos a largo plazo. A la vez, hallamos pruebas de que esta influencia es atribuible principalmente al impacto de perturbaciones en las políticas públicas coordinadas, tal y como predice la literatura sobre externalidades de red. [ABSTRACT FROM AUTHOR]

Presented is a digital-RF transmitter using multi-bit ▵ Σ modulators with noise-shaped segmentation and butterfly shufflers for shaping mismatches between digital-to-RF converter (DRFC) cells. The segmented butterfly shufflers prevent mismatch errors of DRFCs from aggravating the linearity and the LO leakage of the transmitter. A prototype based on a digitally-intensive top-down design is fabricated in 90 nm CMOS process. Measurement results for wideband-code division multiple access demonstrate an adjacent channel leakage ratio (ACLR) (5 MHz/10 MHz) of -49.6 dBc/-53.9 dBc and an Error Vector Magnitude of 1.89% with a main channel output power of -0.1 dBm centred at 1.95 GHz. [ABSTRACT FROM AUTHOR]