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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 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]

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]

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 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 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]

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]

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]