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With the growth of income at the global level, the World Bank data show that there are rising levels of income disparity across countries, groups, regions and within the countries. This fact otherwise hints at the inter-country divergence in incomes, particularly between the developed and developing countries of the world. This chapter, therefore, attempts to examine the convergence or divergence in credit, GDP and HDI across the 10 selected countries for the period of 1990–2019 applying the neoclassical growth approach and the time series approach. The results of the exercise in line with the neoclassical theories on absolute convergence and sigma convergence show that the countries are unquestionably converging in GDP and HDI with mixed results in case of credit. The results of convergence in GDP and HDI in all the countries and their developed and developing counterparts provide a possible explanation as to why the cross countries’ income inequalities as well as world inequality in income and development are reducing over time. On the other hand, the results of the time series approach display that credit and HDI are converging in both absolute and conditional terms but the countries are converging in conditional terms only for GDP. Thus, the claims of the World Bank are not valid for the selected countries in the chapter, rather, they can be verified by taking other countries and groups into consideration.

In continuation to Chapter 3, the present chapter tries to quantify the impact of credit upon GDP and HDI as the first attempt and the linkages of NPA and security investments with credit, GDP and HDI of the countries as the second attempt. For these purposes, this chapter starts with the measurements of credit elasticity with respect to GDP and HDI to know the impact of credit on the private sectors upon the income and human development of the countries. Then, it focuses on the implications of common banking operating tools such as their investments in the governments’ securities in relation to credit to the private sectors, GDP and HDI of the selected countries in a panel data format. The results of the credit elasticity of GDP show that it has taken the positive sign in all of the countries and the negative changes are very little in number. Furthermore, the results on the linkages show that all the variables are mostly cointegrated and therefore maintain stable and equilibrium relationships in the long run among them. But the short-run results show that investment and credit make a cause to NPA, and investment and NPA make a cause to GDP. No variables make any interrelationships with the HDI in either the long-run or short-run systems. Thus, the countries in the list should put more emphasis on the working of the financial sectors as the key partner in the income-generating activities.

This study aims to determine how changes in macroeconomic indicators and the housing prices index (HPI) are related. These factors can cause short-term and long-term changes in the housing market in Spain.

The study used cointegrating regression, fully modified ordinary least squares and dynamic ordinary least squares methodologies. The models are trained using quarterly time series data for these parameters from 2010 to 2022. A comprehensive examination is conducted to explore the relationship between macroeconomic issues and fluctuations in the HPI.

The results indicate statistically significant short-run effects (p < 0.05) of economic growth, inflation, Spanish stock indices, foreign trade and the interest rate on HPI. The inflation variables, Spain’s stock indices, interest rate and monetary rate, have statistically significant long-run effects (p < 0.05) on HPI. The exchange rate, unemployment and money supply have no substantial impact on HPI in Spain.

The study’s findings significantly contribute to increased information concerning the level of investing activity in the Spanish housing sector. After conducting an in-depth study of both the long-run and short-run connections with HPI, the study proved to be highly effective in formulating appropriate policies.

The goal of this study is to look into the connection between Sri Lanka’s fiscal deficit and inflation. Sri Lanka is currently experiencing one of its worst inflation crises in its history, necessitating an investigation into how fiscal deficit affects inflation, as it has been experiencing an ever-increasing fiscal deficit for the last four decades. The quantitative methodology is employed in this study using annual data from 1977 to 2019 following the ARDL technique in the analysis. The findings showed that both in the long run and the near term, Sri Lanka’s fiscal deficit had a positive and significant link with inflation. The policymakers should increase the revenue through the taxes in order to bridge the fiscal deficit. As a developing country, it cannot afford to continue with the ever-increasing fiscal deficit which has become a burden to country. Also, it is the responsibility of each government to think carefully to reduce its massive expenditure which has become a common feature in the country for the last four decades. Cutting down government expenditure can improve the economic growth and well-being of the citizens too. The government should therefore concentrate on short-term investment programmes that will benefit the country while doing the same in the long run.

The purpose of this research is to systematically scrutinize the influence of macroeconomic determinants on trade openness, through the lens of various trade theories, with a particular focus on the economies of the GIPSI countries – Greece, Ireland, Portugal, Spain and Italy.

This study investigates the macroeconomic factors influencing trade openness in the GIPSI economies from 1995 to 2020. Methods include stepwise regression (SR) for model selection, Pedroni panel cointegration test and panel regression results. The analysis uses advanced panel regressions, including FMOLS, Panel OLS and FEM. The long-term dynamics were tested using Pedroni cointegration, while Granger causality testing was used to examine the causal direction between the trade openness ratio and trade determinant.

The results show both long-term and short-term relationships between trade openness and (1) foreign direct investment, (2) labor force participation rate, (3) trade reserves and (4) trade balance. The researchers also detected unidirectional and bidirectional causality relationships between trade openness and these four factors. The study also revealed that trade reserves (TR) emerge as the most influential determinant of trade openness, and per capita income does not exhibit economic significance concerning the trade openness of GIPSI economies.

This research is conducted within the context of the GIPSI nations (Greece, Ireland, Portugal, Spain and Italy). As such, the outcomes may not be universally applicable to other economic systems due to the distinct institutional settings and governance structures across different economic groups. Future investigations may explore the relationship between trade openness and its determinants by incorporating different variables.

To the best of the authors' knowledge, this is the first study investigating the theory that suggested trade drivers drive the trade openness of GIPSI countries context. By focusing on GIPSI countries, the study offers a unique perspective on the dynamics of trade openness in economies that have experienced financial crises and stringent austerity measures.

Renewable energy is at the forefront of countries’ concerns due to its global economic and environmental impacts. Previous studies have thoroughly examined the impact of renewable energy on overall national income, and this paper aims to shed light on an indicator that has received insufficient attention in research regarding its impact on economic growth, using data from 2000 to 2018.

This study examines the causal relationship between trade balance, renewable energy consumption and CO₂ emissions per capita in Organization for Economic Cooperation and Development (OECD) countries using an auto regression distributed lag model (ARDL) and Johansen Cointegration Test.

The findings reveal that there is evidence of a long-run and short-run cointegrating relationship and that renewable energy consumption in the long run impacts the trade balance positively and in the short run negatively.

Therefore, bioenergy trade between countries and local investment should be prioritized to increase the trade balance surplus, since many of OECD countries suffer from deficit problems.

The authors analyze a model for N different measurements of a persistent latent time series when measurement errors are mean-reverting, which implies a common trend among measurements. The authors study the consequences of overdifferencing, finding potentially large biases in maximum likelihood estimators (MLE) of the dynamics parameters and reductions in the precision of smoothed estimates of the latent variable, especially for multiperiod objects such as quinquennial growth rates. The authors also develop an R² measure of common trend observability that determines the severity of misspecification. Finally, the authors apply their framework to US quarterly data on GDE and GDI, obtaining an improved aggregate output measure.

This study aims to empirically examine the relationship between energy consumption, agricultural economic growth and globalization in Turkey by using data from 1980 to 2018.

The Lee-Strazicich LM breakpoint test was used to test the stationarity of the variables. The presence of the long-run relationship between the variables was examined by using the Maki cointegration test. The dynamic ordinary least squares method was used to estimate the long-run coefficients of the model. The direction of causalities was determined using the Toda–Yamamoto causality test.

Research results showed that consuming energy on average of 14,460 GJ/hectare has returned $1,612 agricultural gross domestic products (GDP)/hectare per year. Turkey’s energy consumption (EC), GDP and globalization index (GI) from 1980 to 2018 increased by 2-fold, 3-fold and 1.5-fold, respectively. Research results also showed that Turkey’s EC was affected by GI and GDP.

The study suggests using environmentally friendly energy inputs and conscious consumption to reach growth targets and to reduce the pressure of intensive energy use on natural resources. Further research is needed for exploring the causality and relationship between EC and GI and along with other variables in the agricultural sector.

The study contributes two contributions to the existing literature. The first contribution is to examine the neglected relationship between GI and EC and GDP in Turkey. The second is that the EC data for Turkish agriculture used in the study were calculated by the authors.

This study aims to examine the short- and long-term equilibrium relationship between All share price index (ASPI), macroeconomic variables and the economic crisis in Sri Lanka.

Monthly time series data for inflation (CPI), industrial production (IP), an exchange rate (EX), an interest rate (TB), short-term interest rate (CD) and economic crisis were used from 2010 to 2021. The ADF test, the bound testing approach, the CUSUM test and the CUSUMQ test were used in this study.

The findings show a long-run stable relationship between stock price, macroeconomic variables and political crisis (i.e., CPI, IP, ER, TB, CD and economic crisis). The results of the Johansen cointegration test suggest that there is at least one cointegrating equation, indicating that there is a long-run equilibrium relationship between macroeconomic variables and stock prices in Sri Lanka.

The vector error correction estimates show that the coefficient of the error correction term is significant with a negative sign, indicating that a long-run dynamic relationship exists between macroeconomic variables and stock prices. In the short term, economic crisis has had a big effect on stock prices suggesting that Sri Lanka’s domestic financial markets are linked to the stability of the country.

This research establishes the links between stock returns, macroeconomic variables and economic crisis. So far, research has been unable to establish the empirical nature of such links. The authors believe that this paper fills that gap.

The purpose of this paper is to determine the effect of the industrial sector, renewable energy consumption and nonrenewable energy consumption in Indonesia on the ecological footprint from 1990 to 2020 in the short and long term.

This paper uses vector error correction model (VECM) analysis to examine the relationship in the short and long term. In addition, the impulse response function is used to enable future forecasts up to 2060 of the ecological footprint as a measure of environmental degradation caused by changes or shocks in industrial value-added, renewable energy consumption and nonrenewable energy consumption. Furthermore, forecast error decomposition of variance (FEVD) analysis is carried out to predict the percentage contribution of each variable’s variance to changes in a specific variable. Granger causality testing is used to enhance the analysis outcomes within the framework of VECM.

Using VECM analysis, the speed of adjustment for environmental damage is quite high in the short term, at 246%. This finding suggests that when there is a short-term imbalance in industrial value-added, renewable energy consumption and nonrenewable energy consumption, the ecological footprint experiences a very rapid adjustment, at 246%, to move towards long-term balance. Then, in the long term, the ecological footprint in Indonesia is most influenced by nonrenewable energy consumption. This is also confirmed by the Granger causality test and the results of FEVD, which show that the contribution of nonrenewable energy consumption will be 10.207% in 2060 and will be the main contributor to the ecological footprint in the coming years to achieve net-zero emissions in 2060. In the long run, renewable energy consumption has a negative effect on the ecological footprint, whereas industrial value-added and nonrenewable energy consumption have a positive effect.

For the first time, value added from the industrial sector is being used alongside renewable and nonrenewable energy consumption to measure Indonesia’s ecological footprint. The primary cause of Indonesia’s alarming environmental degradation is the industrial sector, which acts as the driving force behind this issue. Consequently, this contribution is expected to inform the policy implications required to achieve zero carbon emissions by 2060, aligned with the G20 countries’ Bali agreement of 2022.