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Introduction: India has the 15th-largest domestic natural gas consumption (NGC), critical to sustainable economic growth. Promoting natural gas will have a crucial impact on production in all industries.

Purpose: This research gives an overview of NGC and gross domestic product (GDP) in India from 1990 to 2021 and investigates the association and nature of causality between NGC and GDP in India.

Methodology: For the years 1990 through 2021, we used annual statistics from the NGC and the GDP of India. Both research variables data have been taken from the World Bank Indicator.

Findings: There is no causality and correlation between natural gas and GDP in India.

Practical Implications: Based on the research, the Government of India can create different policies for substituting natural gas for other energy sources to have a healthier impact on a sustainable environment in the short and long term. In the future, researchers can work on environmental degradation and GDP.

The term “economic growth” refers to the increase of real gross national product or gross domestic product or per capita income. National income or else national product is usually expressed as a measure of total added value of a domestic economy known as gross domestic product (GDP). Generally, GDP measures the value of economic activity within a country during a specific time period. The current study aims to find the most suitable model that adjusts on a time-series data set using Box-Jenkins methodology and to examine the forecasting ability of this model. The analysis used quarterly data for Greece from the first quarter of 1995 until the third quarter of 2019. Nonlinear maximum likelihood estimation (maximum likelihood-ML) was applied to estimate the model using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm while covariance matrix was estimated using the negative of the matrix of log-likelihood second derivatives (Hessian-observed). Forecasting of the time series was achieved both with dynamic as well as static procedures using all forecasting criteria.

This chapter strives to evaluate the impact of tourist arrival on energy consumption, air pollution, gross domestic product (GDP), and foreign direct investment to suggest strategies for further tourism development. Relevant data from Taiwan are analyzed, entailing tourist arrivals, GDP, carbon dioxide emissions, energy consumption, and capital investment. It tests four hypotheses using the Augmented Dickey-Fuller single root test, the Autoregressive Distributed Lag model, and time series econometrics of Granger causality. This study finds that tourist arrival is positively related to energy consumption and GDP, whereas it negatively relates to carbon dioxide emission and capital investment. In consideration of a negative relationship between tourist arrival and direct investment, this study suggests devising timely research agendas on carrying capacity and service quality in the mind of international tourists to see if additional investment in tourism infrastructures is needed.

The world’s so-called developed countries of the West have long economic and political history compared to those of the East. The developed countries are far away from today’s developing countries in terms of aggregate income, aggregate capital formation, total number of human capital, etc. Though some countries from the East have outpaced some of the Western countries in terms of gross domestic product (GDP), aggregate bank credit and capital formation, in the twenty-first century, such as China and India, they are far behind in terms of per capita income, per capita financial facilities and per capita capital stock. On the other hand, the countries from the East, except a few one, are also well lagging behind their Western counterparts in the level of human development. With the theme of the book on the growth and developmental aspects of credit allocations, the present chapter makes an introduction to the subject area by means of credit histories in the selected 10 countries and their phase-wise levels of GDP, credit and Human Development Index (HDI). The figures for GDP, credit and HDI reflect the rising trends in GDP and credit for all in the entire phase but there are some downfalls in the GDP and credit during the phase of the global financial crisis. Besides, it observes rising trends of HDI in all the countries but the rates of rise are more in the case of the developing countries. There are thus the possibilities of getting correlations among the different pairs of the variables across the countries.

There have been increasing numbers of studies on the role of energy and environmental pollution upon income of the economies across the countries after the development of the endogenous growth literature. As standard practice, the factors which make explanations of why the developed countries are growing more compared to the common list of developing countries are the knowledge capital, role of institutions, etc. But, the roles of energy use and environmental resources upon economic growth have also been identified as additional source of endogenous growth. Sometimes, in certain economies, it is observed that both the factors maintain bidirectional causal relations with the level and growth of income. The present chapter aims to investigate whether energy use and environmental pollution make a cause to the level of income measured by gross domestic product, in both the long run and short run, for the world's highly developing group of economies in the nomenclature of BRICS. The period of study is taken to be 1990–2016 for which the data on all the indicators are available for the five member countries of the group. Using a VAR model, the study arrives at the conclusion that all the three are cointegrated for Brazil and Russia only. Further, there are short-run causal interplays among the three in different combinations across the member countries. While GDP and energy use are the common cause of CO2 emission for Brazil, India, and China; energy use and CO2 emissions are to GDP in India, South Africa, and China.

From Europe moving forward into Asia, the Silk Road has the Gulf Cooperation Countries (GCC) on the way. These countries alphabetically include: “Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates.” While these countries have long been dependent on oil for development, they are currently planning to reduce this dependence and consider innovation as an important mean for future development. This chapter explores the past progress of innovation in the GCC countries; and highlights future directions ahead. In this respect two end countries of the Silk Road, Italy and China, are also considered. The chapter views innovation from the wide angle of the Global Innovation Index, which has 7 main dimensions, consisting of 21 sub-dimensions, which are refined into 81 international indicators. An approach for looking into the current state, the past progress, and the future directions of innovation in the countries concerned is developed and followed using available data. Although the outcome is based on the currently available data, the approach can be re-used for newer data providing continuous benefits to directing future development.

Technological progress is a determining factor in the factors leading to economic and social well-being. Simultaneously, the development of a sustainable economy is based on the conservation of resources. In the energy sector, this fact can be corroborated with the reduction of energy consumption, thus increasing economic efficiency. On the one hand, improving energy efficiency contributes to increasing the quality of life, productivity, and, implicitly, the economy, but on the other hand, it leads to excess energy use – this behavioral change is known as rebound. The research estimates the rebound effect at the macroeconomic level for European countries in the period 2000–2019, referring the analysis to each country's gross domestic product (GDP) and energy consumption, as well as comparing the preaccession and postaccession periods of Romania in the EU space. The rebound effect is determined using multidimensional analysis methods, depending on the GDP of each country as well as the behavior of each in the use of energy resources in industry, agriculture, and services. Although the study results confirm the strong link between energy consumption and GDP at the level of each state, they did not show considerable changes between countries at the level of the two periods.