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The purpose of this paper is to reveal some basic characteristics in social and economic process, and lay the analytic foundation for advance‐retreat course (ARC).

The paper presents the analytic model of stochastic ARC (SARC), which is based on the partial distribution and partial process (belonging to the probability theory and stochastic process), and describes some important characteristics of social and economic process in a quantitative method.

The successful socio‐economic process, including many biological process, are usually divided into three basic stages: the weak growth, the quick development and the swift decline. In general, rapid growth brings with it the weak persistence, and slow growth brings with it the strong persistence. The socio‐economic fluctuations are mainly caused by the excessive environmental pressures. The duration of the socio‐economic growth is inverse with the environmental pressure.

All the basic variables and parameters in an ARC model should be no less than zero.

Based on US GDP (chained) price index data (1940‐2005), American economic process in recent 70 years is analyzed, and the analysis indicates, American economic motivity is clearly insufficient after 2008, and the present economic recovery will be very arduous and prolonged.

The environmental pressures will become the main problem for future global socio‐economic development.

SARC model in this paper presents a special way to analyze the social development and economic growth, and is helpful to related academic research and socio‐economic decision making.

This study contributes to the debate about the sustainability of Chinese loans in Africa. The literature suggests that economic growth is among other crucial debt dynamic indicators for assessing debt sustainability in the economy. However, this hypothesis has hardly been tested in the current case due to data ambiguities on Chinese loans to Africa. Following China Africa Research Initiative (CARI)'s initiative to ameliorate these data challenge, this study utilises CARI's dataset in a GMM panel VAR framework for the period (2000–2018) to explore the dynamic relations between Africa's growth and Chinese loans. The methodology is theoretically underpinned by the exogenous growth models that consider physical capital accumulation in the form of savings as a prime growth stimulus in the economy's production function. Thus, Chinese loans are typically viewed as physical capital input that directly adds to Africa's physical capital accumulation. It was found that Africa's growth responds positively to Chinese loans but only in the short run. In the long run, the effects of shocks to Chinese loans on Africa's growth phase out despite the inclusion of merchandise trade as a productivity factor in the model. The findings suggest that Chinese loans can boost Africa's growth through physical capital accumulation. Nonetheless, for growth to continue in the long run, these loans ought to be effectively invested in productive economic sectors that can generate productivity-enhancing economic incentives and enough savings for repayment. This initiative should be complemented by reforming institutions involved in acquiring, investing and servicing Chinese loans.

This chapter is a radical critique of the neoclassical growth theory, justifying ways out of mainstream economics. It has three parts. The first one analyzes growth theories from the Classical representation to the endogenous growth models. The second part demonstrates that the “new growth theory” is not a break with Solow's formalization. To prove it, we build an original Solowian endogenous growth model. Then, this neoclassical macrodynamic framework is technically, deeply critized in a third part. We show that both exogenous and endogenous neoclassical models prove to be incapable to explain growth in the long period. We concentrate on the ambiguities surrounding the hypothesis of single agent, as well as on the role of the state, in particular when it is considered as a “planner” by the neoclassicals. Endogenous growth models do not correspond to macrodynamization of the Walrasian general equilibrium, nor have solid microeconomic bases. We advocate in favor of rehabilitating state's intervention in social areas and of reactivating Marxist theoretical reflections regarding social planning and class analysis in the current time of structural crisis of the capitalist world system.

This paper seeks to explain how inefficient learning rules may lead to a perception of economic and ecological realities that may be systematically distorted in the long run.

The paper evaluates long‐term growth in standard growth‐pollution models. Expectations about future levels of pollution are formed under adaptive learning.

Socio‐economic players (private agents, governments, non‐profit organizations and/or groups of states) may fail in understanding, with full accuracy, long‐term environmental conditions. The perception about environment threats acquires a cyclical nature, even when ecological problems evolve steadily.

Relevant policy implications emerge if the agent is unable to compute the true levels of environmental pollution that will persist in the steady state. Authorities of several kinds are likely to underestimate or overestimate ecological problems.

The learning approach to the perception of the environment can be applied to other economic, social and biological issues, besides material growth. For instance, it can contribute to explain some cases of over‐exploitation of resources: even in the presence of a social planner capable of avoiding typical “tragedy of the commons” situations, this entity may fail in perceiving the reality and, thus, in applying the policies that prevent the exhaustion of resources.

The paper contributes to the literature on growth and environmental issues, but takes a step forward: it approaches not only the observed relation between economy and ecology, but also the impact over the observed relation of a systematically incorrect interpretation of such a connection.

This paper aims to test three hypotheses in city growth literature documenting the poverty reduction observed in Brazil and exploring a rich spatial dataset for 5,564 Brazilian cities observed between 1991 and 2010. The large sample and the author's improved econometric methods allows one to better understand and measure how important income growth is for poverty reduction, the patterns of agglomeration and population growth in all Brazilian cities.

The author identifies literature gaps and use a sizeable spatial dataset for 5,564 Brazilian cities observed in 1991, 2000 and 2010 applying instrumental variables methods. The bias-corrected accelerated bootstrap percentile interval supports the author's point estimates.

This manuscript finds that Brazilian data for cities does not support Gibrat's law, raising the scope for urban planning and associated policies. Second, economic growth on a sustainable basis is still a vital source of poverty reduction (The author estimates the poverty elasticity at four percentage points). Lastly, agglomeration effects positively affect the city's productivity, while negative externalities underlie the city's development patterns.

Data for cities in Brazil possess unique characteristics such as spatial autocorrelation and endogeneity. Applying proper methods to find more reliable answers to the above three questions is a desirable procedure that must be encouraged. As the author points out in the manuscript, dealing with endogenous regressors in regional economics is still a developing matter that regional scientists could more generally apply to many regional issues.

This paper reviews one of the crucial issues in the recent growth literature concerning the hypothesis of cross country convergence of levels and growth rates of income per capita implied by the neo‐classical growth model, both in the Solow‐Swan and Rampsey‐Cass‐Koopmans versions. The alternative endogenous growth models, consistent with permanent income inequality, are considered. Convergence to a common income level versus divergence is discussed from a theoretical point of view. Then, empirical tests of the convergence property are presented. What emerges is that Barro type regressions and their findings about “conditional” convergence are questionable and cannot be used to give a definitive response on this issue.

The purpose of this study is to empirically investigate how external debt vulnerability has affected the economy of emerging countries over time, with particular reference to Sub-Saharan African countries. It also deals with the policy issues associated with the economic effects.

The techniques of dynamic ordinary least squares and fully modified ordinary least squares are used in this investigation, covering the period 1990–2022. A panel of 43 Sub-Saharan African countries is used in the study.

The estimation results reveal that external debt vulnerability impacted negatively on economic growth, thus validating the concerns raised about the debt problem in Sub-Saharan Africa. Furthermore, the results revealed that domestic credit and openness of economy played a passive role and were therefore unable to cushion the adverse effect of debt vulnerability. Capital stock, however, stands out as the only variable that played a significant positive role in facilitating economic growth. The results are considered to be highly reliable for short-term forecast of economic growth and formulation of relevant policies.

Over the years, economic analysts and stakeholders have expressed concern about the inadequate ratio of foreign reserves to external debt in developing countries. The effect of this external debt vulnerability on the economy of these countries has yet to be given sufficient attention by researchers. In view of this perceived void, this current study is carried out to determine the economic and policy consequences of the problem.

Since the original Harrod‐Domar capital‐output models, and the highly influential work of Ragnar Nurkse, nearly all writers have found the effective constraints on growth to be on the side of supply. Thus stress has been placed on the “exchange gap” (shortage of imports) or the “savings gap” (shortage of capital formation) or on shortages in skills or natural resources. Others focus on constraints imposed by institutional or cultural factors, though often these are assumed to be fixed. An implicit assumption of all such models is that no problem will be posed by lack of effective demand, which may therefore be safely neglected. The apparent basis for this view is the presence of inflation, which suggests excessive demand. However, many writers do express great anxiety about the possibility of an inadequate demand for labour. They claim that excessive concern for the goal of maximum output gives rise to a shortage of capital and a “maluse” of capital in capital intensive processes, thus reducing the demand for labour and causing growing unemployment. The inconsistency of an insufficient demand for labour and an excessive demand for goods is not recognized nor is explained in terms of maldistribution of income or excessive use of capital intensive methods of production.

The purpose of this paper is to evaluate the role of human capital technology spillovers across countries in converging their growth rates.

This paper develops a closed form mathematical endogenous growth model and applies it to a small open economy using simulation and calibration techniques.

The paper finds that human capital technology spillovers play an important role in convergence in growth rates across countries regardless of tax policy and that there will be non‐convergence in levels if saving rates are differentially distorted across countries because of taxes. In addition, the exploration of the optimal tax reveals that such a structure is a consumption tax.

This paper implies that higher levels of human capital are important in attaining higher levels of per capita income.

This paper shows that some implications for the endogenous growth model are equivalent to those from the Solow model. This implies that some empirical tests commonly used will not resolve which model is more appropriate.