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Indonesia is the fourth most populous country in the world, which has a strong effect on primary energy use and depletion of natural resources. This paper considers energy intensity (EI) defined as a measure of the amount of energy it takes to produce a dollar's worth of economic output. The purpose of the paper is to explore how different factors contributed to the decline in Indonesia's EI.

The cointegration regression methodology is applied to explore the long-term nexus between EI and its factors in Indonesia during 1990–2016.

Results show that domestic credit to the private sector, as well as the share of alternative energy, has a significant impact on the decline of EI in Indonesia.

We do not try to rule out other possible determinants of EI. We consider the determinants of EI using time series data, while an ideal analysis would be based on panel-level data. Another limitation is that the study covers only the small-time period from 1990 to 2016.

Our findings serve to aid the government and policymakers in prioritizing improvements in the sphere of energy policy. An important policy implication, regarding Indonesia, that arises from our study is that, for the country to be able to decrease its EI, it must be able to develop its financial market and zero-carbon energy sources, mainly geothermal energy with its huge potential.

We show that energy prices, financial development and the share of alternative energy sources contribute to EI decrease. Policy recommendations include geothermal and solar energy development as one of the most prospective sources of alternative energy in Indonesia.

This paper investigates the impact of trade liberalization measured by trade openness (OPN) and tariffs on women empowerment measured by the gender gap index and gender development index, for two groups of Arab countries divided based on their income levels using annual data for the period 1995–2020. The study also considers other factors that may influence the gender gap, such as GDP growth and the female unemployment rate. The purpose of this paper is to address these issues and explorers whether the effects of trade liberalization differ based on the countries' income levels.

This study employs the fully modified ordinary least squares (FM-OLS) regression model for heterogeneous cointegrated panels to examine the impact of trade liberalization on women empowerment. The study constructs an empirical two regression model of women empowerment measured by the gender gap model and gender development model for the two groups of higher-income countries and lower and middle-income countries.

The authors’ findings reveal that the impact of OPN on the gender gap varies between the two groups of Arab countries where more OPN within the higher-income group may increase the gender disparity, while it may reduce disparity within the lower and middle-income countries. In addition, GDP growth may reduce the gender disparity, while female unemployment raises the gender disparity between the two groups of countries in the long run. Findings also reveal that more OPN, tariffs and female unemployment may reduce gender development within the two groups, but more GDP growth may support the gender development in the long run.

This paper not only assesses the impact of trade liberalization on women empowerment generally, but also assess the women empowerment via two indices that are the gender gap and gender development in Arab countries which is – to the knowledge of the researchers – not yet investigated; further it explores if the effects of trade liberalization differs based on the countries' income levels.

Bank consolidations in many Middle East and North Africa (MENA) countries have been proceeding at a rapid pace, leading to a decline in the number of banks and an increase in market concentration. This may raise concerns regarding the impact of such increase in concentration on the behaviour of banks and consequently on the financial development. Therefore, this study aims to examine the impact of concentration on the financial development of MENA region.

The study adopts fully modified ordinary least squares model on a heterogeneous, non-stationary, cointegrated panel data set. The exploited panel is formed of 15 MENA countries and covers the period 1996–2014.

The empirical results show that concentration per se is not harmful for financial development. Nevertheless, concentration combined with bank market power may deteriorate the development of MENA financial systems.

In addition to considering an understudied region, the research presents very important findings, which suggest that if banks obtain market power, an increase in concentration following a wave of bank mergers, could weaken the financial development.

The effect of foreign direct investment (FDI) on economic growth is widely believed to be contingent on the development of the financial sector. Nevertheless, as the possibility that the effect of financial development on growth being contingent on FDI has been neglected in existing literature, the authors have investigated it in this paper. In general, the purpose of this paper is to examine the effect of financial development and FDI on economic growth in Sudan using annual data from 1970 to 2014.

Since most of the macroeconomic variables are subject to unit root problem, the time series data are assessed using unit root and cointegration tests with/without structural break. Moreover, the study uses the fully modified ordinary least squares and the dynamic ordinary least squares techniques to estimate the long-run model.

The results of the cointegration tests provide evidence that a long-run relationship exists among variables even after accounting for the structural break. The results show that financial development and FDI are positive and significant in explaining economic growth in Sudan. Financial development is found to be more beneficial to economic growth than FDI. Moreover, the findings reveal that FDI leads to better economic performance through financial development. Interestingly, the findings of the study show that the effect of financial development on economic growth is further enhanced by the inflows of FDI.

The government should focus on promoting FDI in more productive sectors. In addition, further cooperation with multinational enterprises is needed to increase FDI in the country.

This is the first paper that empirically examines both the interlinked impact of FDI on growth through financial development and the impact of financial development on economic growth through FDI in Sudan using appropriate econometric methods.

This paper investigates the impact of microfinance on poverty gap which is the shortfall in income or consumption expenditures below $1.90, $3.20 and $5.50 per day. The paper’s primary goal is to investigate how microloans have impacted the severity of poverty and influenced the cost of poverty eradication in Latin America, empirically evaluate these effects and offer appropriate policy recommendations.

This paper used panel data for 13 Latin American countries from world bank spanning the period 2001–2019 and Fully Modified Ordinary Least Squares model for heterogeneous cointegrated panels. This study used Gross Loan Portfolio per active borrowers, gross domestic product per capita, Gini index, Inflation and Unemployment rate as independent variables and poverty gaps as dependent variables.

Poverty gaps narrow as the loan per borrower increases, and the degree of effect differs with the poverty line, with the magnitude increasing as the poverty line falls, underscoring microloans as an effective tool in closing poverty gaps and lowering the cost of poverty eradication. Growth of GDP per capita is helpful reducing the poverty gap, especially for the less poor of the poor. Inflation and unemployment have no to little impact on the severe poverty gaps, but they start to matter when the poverty line is $5.5 per day. Finally, income distribution inequality widens the poverty gap regardless of the poverty line used.

This study suggests several implications. For example, Latin American nations need to embrace tangible policies that encourage economic growth while reducing inequalities in income distribution to effectively eradicate poverty. More supportive environment is necessary to increase the effectiveness of microfinance operations, particularly for the poorest populations. Microfinance institutions need to set less stringent conditions for loan accessibility and repayment schedules that are commensurate with different levels of poverty. Finally, strengthening microfinance as a strategic policy to gradually close poverty gaps and reduce the cost of poverty eradication.

Purpose: Following the theoretical literature on growth model with externalities, the chapter aims at finding empirical evidence of the main sources of economic interdependencies in Europe.

Methodology/approach: A two-step econometric procedure is adopted. In the first step, in order to evaluate growth spillovers in Europe, cointegration relationships between indexes of industrial production per capita are estimated for 15 European countries. The estimated coefficients, interpreted as long-run elasticities between European countries, appear to be different between countries and unstable over time. In the second step, these coefficients are explained by trade, specialization, research and development (R&D), and macroeconomic variables.

Findings: Panel estimations show strong evidence in favor of a positive relationship between openness, country size, knowledge accumulation, and the long-run sensitivity to European income. European income spillovers are not explained by the specialization of trade and production. We conclude that countries that benefit the most from economic integration are the largest and those that invest the most in R&D.

Originality/value of chapter: The two-step approach adopted in this chapter is original and allows for measuring the impact of various determinants of externalities at the same time.

Applies new tests for parameter instability in cointegrated models to evaluate the traditional export demand function. The determinants of exports considered are world real income, export price and competitors’ export price. The data for Singapore (a newly industrializing economy), from 1973‐1997, are used as a case study. Results suggest that Singapore does not satisfy the conditions of a small, price‐taking country in world trade. Irrespective of whether one normalizes export demand function by price or quantity, the state of external demand appears to be a key ingredient in Singapore’s export growth. This finding differs markedly from Riedel’s evidence. It is found that the estimation of Singapore’s export demand model requires the inclusion of some dummy variables in order to achieve not only cointegration but also long‐run parameter stability. However, once the structural breaks are accounted for, a stable relation is found, which resists a series of specification tests.

In this paper, the authors investigate the inbound tourism demand elasticities of the Middle East and North African (MENA) countries. The authors emphasize the role of external and internal conflicts, world gross domestic product and relative prices over the period 1995–2017.

This study applies the heterogeneous panel data estimators based on the fully modified-OLS (FM-OLS), dynamic-OLS (DOLS) and the recently developed method of moments quantile regression (MMQR).

The empirical results indicate that the effect of external and internal conflicts on inbound tourism demand is negative and inelastic with external conflict having a stronger effect. The effect of both classifications of conflicts diminishes as the market share of the tourist destination increases. In addition, the role of the world GDP on tourism demand is positive and elastic, suggesting that tourism is a luxury good while an increase in relative prices diminishes inbound tourism demand.

The paper, therefore, concludes that if policy measures are not put in place to curtail incidences of conflicts, economic growth in these countries may suffer setbacks. This by implications could affect the attainment of the sustainable development goals (SDGs) targets.

The main aim of this paper is to examine labour productivity trends in Italy over the period 1981‐2004.

To this end, relying on recent developments in the analysis of non‐stationary dependent panels, the paper develops a new method for estimating total factor productivity (TFP) trends.

The conclusions confirm the view that the recent decline in Italian labour productivity growth is mostly due to a widespread fall in TFP growth.

The main assumption underlying the proposed TFP estimation method is that technology growth is driven by a single trend common to all units included in the panel (industries, regions or countries).

The paper provides two distinct contributions: empirically, it provides robust evidence that TFP slow‐down is the main cause of recent negative trends in labour productivity in Italy. Methodologically, the paper proposes an approach to estimating TFP that enjoys several advantages: only basic data for input and output flows are needed, the non‐stationary nature of the data is explicitly taken into account, and confidence intervals for TFP growth can be computed. This method can thus be easily applied to many routinely available datasets, to either corroborate existing growth accounting estimates or to obtain previously unavailable estimates.

The aim of this paper is to advocate and implement cointegration methods for the estimation of interconnectedness of service quality and customer loyalty as intangible strategic assets within management decision.

Using longitudinal time series quarterly data on loyalty and service quality, the paper uses cointegration methods to empirically estimate the weight of interconnectedness of customer loyalty and service quality as intangible strategic assets.

The research evidence suggests that customer loyalty and service quality are interconnected intangible strategic assets that managers can develop, accumulate, estimate and deploy for superior competitive advantage.

To the extent that the global economies are increasingly service‐driven, managerial capability to estimate intangible strategic assets as drivers of superior competitive advantage will remain strategically important. Assumedly, this paper is the first to illustrate how cointegration methods can be used by managers to estimate interconnectedness of intangible strategic assets. In this sense, to the extent that this method is new to managers, it represents another toolkit of intangible strategic asset management for managers.