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“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

The purpose of this paper is to empirically test a more comprehensive model of economic growth using a sample of 28 lower middle-income developing countries.

The authors modify the conventional neoclassical growth model to account for the impact of the increase in the number of people working relative to the total population and that of the increase in the value added per worker over time. The authors then extend this model by incorporating the role of trade, government consumption, and human capital in output growth.

Regression results show that over three quarters of cross-lower middle-income country variations in per capita GDP growth rate can be explained by per capita growth in the share of public expenditures on education in the GDP, per capita growth in the share of government consumption in the GDP, per capita growth in the share of imports in the GDP, per capita growth in the share of manufactured exports in the GDP (not of that of total exports in the GDP), and the growth of the working population relative to the total population.

Statistical results of such empirical examination will assist governments in these countries identify policy fundamentals that are essential for economic growth.

To address the simultaneity bias, the authors develop a simultaneous equations model and are able to show that such model is more robust and helps explains cross-country variations in per capita GDP growth over the 2000-2014 period.

This study provides the critical masses (thresholds) at which the positive incidence of finance and economic growth will be dampened by the negative effects of income inequality and poverty on energy consumption in Sub-Saharan Africa for policy direction.

The study employed the two steps systems GMM estimator for 41 countries in Africa from 2005–2020.

The study found that for finance to maintain a positive effect on energy consumption per capita, the critical thresholds for the income inequality indicators (Atkinson coefficient, Gini index and the Palma ratio) should not exceed 0.681, 0.582 and 5.991, respectively. Similarly, for economic growth (GDP per capita growth) to maintain a positive effect on energy consumption per capita, the critical thresholds for the income inequality indicators (Atkinson coefficient, Gini index and the Palma ratio) should not exceed 0.669, 0.568 and 6.110, respectively. On the poverty level in Sub-Saharan Africa, the study reports that the poverty headcount ratios (hc$144ppp2011, hc$186ppp2011 and hc$250ppp2005) should not exceed 7.342, 28.278 and 129.332, respectively for financial development to maintain a positive effect on energy consumption per capita. The study also confirms the positive nexus between access to finance (financial development) and energy consumption per capita, with the attending adverse effect on CO₂ emissions inescapable. The findings of this study make it evidently clear, for policy recommendation that finance is at the micro-foundation of economic growth, income inequality and poverty alleviation. However, a maximum threshold of income inequality and poverty headcount ratios as indicated in this study must be maintained to attain the full positive ramifications of financial development and economic growth on energy consumption in Sub-Saharan Africa.

The originality of this study is found in the computation of the threshold and net effects of poverty and income inequality in economic growth through the conditional and unconditional effects of finance.

The per capita GDP of the countries of Southeast Asia (SEA) varies from less than $5,000 to over $97,000. This paper aims to analyze the political factors behind such variation, such as wars, extreme politics, political instability, and kleptocratic governments and leaders, and how they affect the development experience within the region.

This paper uses the comparative political economy analysis approach to make a comparison among SEA countries using knowledge from well-known political–economic history and development data from World Development Indicators provided by World Bank.

A long period of political stability creates a favorable environment for investment that, in return, stimulates sustained economic growth in SEA. The countries have all grown rapidly, but their experience of development varies. The four countries that avoided political extremes (Singapore, Malaysia, Thailand and Brunei) have the highest per capita incomes today. Those that have had long periods of war and political instability, but which have also had substantial periods of stability (Indonesia, Vietnam and the Philippines), come next. Cambodia and Laos have suffered long periods of war and are the least developed. Myanmar’s military rulers, through civil wars and kleptocratic mismanagement of the economy, have prevented growth much of the time.

Most studies of Southeast Asian growth have analyzed the experience of single countries and missed the central role played by extreme politics, including wars, to explain why some countries have much higher per capita incomes than others. This paper is expected to fill this gap.

This study aims to examine the impact of financial inclusion on per capita gross domestic product (GDP) at varying degrees of financial inclusion for a sample of 76 developing countries between 2011 and 2017. To evaluate the heterogeneous impact, this paper constructs the multi-dimension index of financial inclusion to classify sample countries into two sub-samples in terms of the value of FIID, taking account of three dimensions of financial inclusion: access, usage and availability.

This study attempts to identify the presence of reverse causality and long-run relationship between financial inclusion and economic growth by using the Granger causality test (Wald test) and three alternative panel cointegration tests (Kao Test, Pedroni Test, Westerlund Test) respectively. Because of the existence of the bi-directional causality between financial inclusion and per capita GDP, this study uses a fixed effect instrumental variable model with lagged dependent variable to get unbiased estimators from the panel regressions for sample countries.

This paper finds a strong positive impact of financial inclusion on per capita GDP growth in sample developing countries, controlling for labor market structure, financial institutions’ efficacy, infrastructural and governance issues. This study suggests that economic growth will be high in developing economies with a higher level of financial inclusion; however, the positive impact for two sub-samples countries (low and medium level of inclusion and high level of inclusion) are heterogeneous. The estimated result explains that a 1% increase in the financial inclusion index leads to a 0.0153% point increase in the per capita GDP for the countries with a low and medium level of financial inclusion, while this positive impact is significantly higher, 0.0794% point for countries with the high level of financial inclusion. This study also suggests that the higher concentration in the financial market by few agents and the lower level of governance may have an adverse impact on economic growth for the economies with a low and medium level of financial inclusion.

This study is an original study that contributes to the research gap by explaining the heterogeneous impact of financial inclusion on economic growth at varying degrees of inclusion in the two sub-sample countries. Moreover, this study posits greater appeal as it explores the issue using the sample of only developing economies.

The purpose of this paper is to determine how population ageing is related to economic growth as measured by real GDP per capita in Japan. This study is to address the following questions: first, how is population composition by age group related to economic change? Second, how is the dependency ratio related to economic change? And finally, what are the predictions for economic growth in the future? This study answers these questions in relation to Japan.

Regression methods were applied to single-country data for the period 1975-2011.

This study finds that an increase in the 70-74 population age group is associated with a decrease in economic growth, while an increase in the 75 and over population age group is associated with an increase in economic growth in Japan.

The relationships that were found in this study do not imply causation from demographic change to economic change.

One potential way of promoting sustainable economic growth under conditions of population ageing is to devise a comprehensive policy that focuses on demographic factors.

This study analyses population ageing and economic growth in Japan using single-country data by applying regression methods.

The purpose of this paper is to provide a model to measure the effect of broadband availability on economic growth in developed OECD countries.

The effect of the broadband availability‐related variables on economic growth is analyzed by using cross‐country panel data for 34 OECD countries over the years 1998‐2009. The robustness of the results by the six econometric estimation approaches is compared. The preferable dynamic panel model with the system of Generalized Method of Moments is selected.

The access channels per inhabitant and total broadband per inhabitant have improved over time, but vary across the analysed OECD countries. The improved access channels per inhabitant and gross capital growth (investment) play a positive and significant role in the per‐capita gross domestic product (GDP) growth. Labour productivity growth has encouraged economic growth positively. These results are robust independently of the estimation procedure.

The authors do not find a positive and significant role of the total broadband per inhabitant on the per‐capita GDP growth. These findings and the results for control variables pertaining to trade openness and inward foreign direct investment (FDI) in the growth equation are biased to the estimation procedure.

The conceptual‐empirical value to the research of new connections made using the key elements of economic growth theory with focus on the effect of the broadband availability, main macroeconomic and economic openness variables on economic growth. This is one of the first studies that, in the growth equation, uses different broadband availability‐related variables, which in addition to gross capital growth, government consumption, and inflation in the adjusted augmented growth model are controlled for labour productivity growth, trade openness, and inward FDI.

The purpose of this paper is to investigate the economic impacts of intra- and inter-regional water reallocation on sectoral transformation and economic growth.

A multi-sector, Ramsey-type growth model is fit to Chinese data and used to perform policy experiments.

An intra-regional water reallocation increases per capita gross domestic product (GDP) by about 1.5 percent per year over the period 2000-2060. The aggregate potential welfare gain due to this reallocation is 1002.51 billion RMB. Transferring water from southern to northern China via the South-North Water Transfer Project, on average, has a negligible impact on per capita GDP over the period 2000-2060, but aggregate welfare increases by 557.23 billion RMB. Combining intra-regional and inter-regional water reallocations, on average, increases per capita GDP by 0.38 percent per year over the period and the aggregate welfare gain from this combination is 1148.06 billion RMB. Each policy scenario has implications for long-run regional production patterns: In an intra-regional reallocation scenario, Southern China produces almost 70 percent of aggregate GDP, in the inter-regional transfer it produces 58 percent of aggregate GDP, while in a combined intra/inter-regional reallocation it produces 55 percent of aggregate GDP.

This analysis can serve as a template for developing a useful planning tool that one can fit to national or regional data and use to examine a variety of policy relevant questions.

The purpose of this study is to investigate the impacts of urbanization on per capita energy consumption and emissions in India.

The present study analyses the effects of urbanization on energy consumption patterns by using the Stochastic Impacts by Regression on Population, Affluence and Technology in India. Time series data from the period of 1960 to 2015 has been considered for the analysis. Variables including Population, GDP per capita, Energy intensity, share of industry in GDP, share of Services in GDP, total energy use and urbanization from World Bank data sources have been used for investigating the relationship between urbanization, affluence and energy use.

Energy demand is positively related to affluence (economic growth). Further the results of the analysis also suggest that, as urbanization, GDP and population are bound to increase in the future, consequently resulting in increased carbon dioxide emissions caused by increased energy demand and consumption. Thus, reducing the energy intensity is key to energy security and lower carbon dioxide emissions for India.

The study will have important policy implications for India’s energy sector transition toward non- conventional, clean energy sources in the wake of growing share of its population residing in urban spaces.

There are limited number of studies considering the impacts of population density on per capita energy use. So this study also contributes methodologically by establishing per capita energy use as a function of population density and technology (i.e. growth rates of industrial and service sector).

The purpose of this paper is discussing on cross-city empirical economic growth, by estimating an unbalanced dynamic panel for the most vulnerable region of Brazil.

The authors propose including additional and specific sources of cross-city variation, enabling them to capture the essence and reality of this region. The sample selection is given by the solution of a trade-off on the number of cities and the available explanatory variables. Considering the final choice, the analysis is based on 6,452 observations extracted from a sample of 925 cities between 2009 and 2015. Reconciling the regional growth literature and this availability of observable data, the authors decide to explain cross-city real gross domestic product per capita in log, controlling for its lagged value besides 15 explanatory variables on human capital, financial system, business environment and social infrastructure.

This study uses growth drivers on human capital, financial system, business environment and social infrastructure. Considering 6,452 observations for the period from 2009 to 2015, this study finds a significant role played by the levels of education of formal workers, rural financing, real estate financing and FIRJAN indices (health and employment).

A more comprehensive and complete understanding of cross-city variation, whether in the Northeast, in the North of the country or in other regions, involves the expansion of growth drivers in the model. Certainly, the impact of the industrial sector (not captured by the FIRJAN employment/income index), or programs and initiatives geared to technology, must be significant and positive. Despite the low market share, the insertion of microcredit data for informal, small business owners and more underserved families, can bring insights not measured in this article.

On financial system and development: The results on the significant and positive coefficient of rural and real estate financing are fundamental in conducting public policies aimed at granting credit. On human capital: The expected and intuitive relevant role of education suggests that good policies that are implementable need to be looked for and replicated to other northeastern cities. The state of Ceará seems to be that benchmark to be followed by the other states.

Another public policy that needs to be strengthened so that the most vulnerable cities can grow is related to the partnership with the private sector in the expansion and maintenance of basic sanitation. In this context, the new Legal Framework for Basic Sanitation is an important step. Its main objective is to universalize and qualify the provision of services in the sector. Theoretically, it seems to be an important advance and this also unlocks the first big wave of investments.

The analysis aims to contribute to the recent studies on regional growth applied to Brazil. To the best of the authors’ knowledge, this is an innovative contribution, and the main differences between this paper and the others are the sample of cities, the period, the growth model and the estimation technique. For instance, Da Mata et al. (2005, 2007) explore population growth and its implications for economic dynamics and income generation among 123 urban agglomerations between 1970 and 2000. Alves (2021) studied slum growth in contemporary urbanization of households in 272 Brazilian cities from 1991 to 2010.