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This study uses machine machine learning techniques to assess industrial development in Africa.

This study uses nightlight time data and machine learning techniques to assess industrial development in Africa.

This study provides evidence on how machine learning techniques and nightlight data can be used to assess economic development in places where subnational data are missing or not precise. Taken together, the research confirms four groups of important determinants of industrial growth: natural resources, agriculture growth, institutions and manufacturing imports. Our findings indicate that Africa should follow a more multisector approach for development, putting natural resources and agriculture productivity growth at the forefront.

Studies on the use of machine learning (with insights from nightlight satellite images) to assess industrial development in Africa are sparse.

The purpose of the study is to evaluate whether nighttime luminosity sourced from the Defense Meteorological Satellite Program-Operational Linescan System satellite sensors is a suitable proxy for measuring poverty in Africa.

Our study performs wavelet coherence analysis to investigate the time-frequency synchronization between the nightlight data and “income-to-wealth” ratio for 39 African countries between 1992 and 2012.

All-in-all, the authors find that approximately a third of African countries produce positive synchronizations between nighttime data and “income-to-wealth” ratio and hence conclude that most African countries are not at liberty to use nighttime data to proxy conventional poverty statistics.

In differing from previous studies, the authors examine the suitability of nightlight intensity as a proxy of poverty for individual African countries using much more rigorous analysis.

The Inflation Expectations Survey of Households, conducted by the Reserve Bank of India (RBI), indicates that there is considerable disparity in inflation expectations across cities in India. The purpose of this paper is to investigate why different cities exhibit heterogeneous inflation expectations despite coming under a central monetary policy umbrella.

First, the correspondence between city-level inflation expectations and city-specific economic characteristics is mapped. Second, how the disagreement in inflation expectations across cities, measured by dispersion, behaves over the business cycle is investigated. Finally, using seemingly unrelated regression technique, the economic factors that play a role in explaining inflation expectations heterogeneity across cities are estimated.

Cities with higher economic activity and cost of living have higher inflation expectations. Disagreement across cities regarding inflation expectations rise with an increase in output gap and inflation. Information friction plays an important role in explaining the disparity in inflation expectations across cities, and the effects of macro-level factors vary across cities, thereby accentuating expectations dispersion.

Monetary policy-related communication by the RBI (toward the general public) should increase in order to address information friction, which, in turn, would temper down the extent of inflation expectations heterogeneity across cities in India.

This is a novel application of the data from the monetary policy perspective. Heterogeneity in inflation expectations across cities or regions is an unexplored area. The use of nightlights as a proxy for city-level economic activity in India (in absence of data on city-level income) is another original contribution.

This paper aims to look at the economic concepts of consumption preferences and merit goods and the well constructed examples: The Lazy Rotten Kids, The Nightlight Controversial, and The Prodigal Son, in the light of a recent systemic model, named yoyo model.

With the systemic yoyo model and its methodology used as the road‐map, the traditional calculus‐based methods are employed.

From the angle of whole systemic evolution, an astonishing theorem is established, named the Theorem of Never‐Perfect Value Systems. It states that, no matter how a value system is introduced and reinforced, the system will never be perfect. Also, it is shown that, when a tender loving parent exists, his selfish child would take advantage of the parent by putting as little effort into his work as possible.

With recent development of systems research as the foundation, two brand new insights into household economics were discovered.

Modern dementia care is increasingly turning to technology to address a wide range of issues. Such developments are argued to improve quality of life, as, for example, technological interventions that reduce risks and increase safety can enable people with dementia to stay in their own homes for longer. However, all interventions in dementia care must strike a balance between doing what is perceived to be for the best and preserving the personhood of people with dementia. Technological interventions run a particularly high risk of crossing the line into doing things to people with dementia, rather than with them. Doing things for people with dementia is also problematic if it takes away their ability to do things for themselves. These issues are examined with reference to electronic tagging, assistive or ‘smart’ technology and interventions to address the psychosocial needs of people with dementia.

Carbon storage in protected land is a practical climate stabilization strategy. It is increasingly being recognized as an essential means of safeguarding biomass carbon and improving local ecological conditions. Yet, increasing soil carbon sequestration by setting aside nature reserves does not depend only on the scale of the reserve but more so on the implementation and enforcement of the reserve protection policy. This paper aims to discuss the aforementioned issues.

The authors show how nature reserves established and managed by different administrative levels affect carbon sequestration. Empirically, the authors estimate a time-varying difference-in-difference model that exploits China's distinct four-layered hierarchical nature reserve management system at the county level.

The findings show that higher administrative level (i.e. national and provincial) nature reserves have no effects on the carbon dynamic. However, reserves managed by lower administrative levels (i.e. prefecture- and county-level) are associated with reduced carbon sequestration. The results imply local governments fail to fulfil their responsibilities for nature reserves protection, leading to increased extractive activities and declined ecological biomass.

Responsibility and accountability mechanisms for the violation of the nature reserves requirements need to be stipulated accordingly. Greater emphasis should be placed on nature reserves at the base level. The central government should continue efforts toward the establishment of ad hoc and independent management agencies at the ground-management level that are free of influence from base-level governments.

The heterogeneity in the performance of nature reserves across administrative levels confirms that ecosystem service quality is highly dependent on establishment, management and supervision. This provides a better understanding of the socio-ecological interdependence of protected areas.

The purpose of this paper is to estimate the impact of the COVID-19 pandemic on the patterns of convergence/divergence among the districts in India. Specifically, this paper investigates if the impact is heterogeneous among different cohorts of districts (based on income distribution). The differential impact may lead to heterogeneous long-run growth paths, resulting in unbalanced development across regions within the country. A study of convergence can ascertain the possible trajectory of such development across regions. Investigation of this phenomenon is the primary aim of this study.

This paper uses the panel regression method for estimation. This paper uses high-frequency nighttime light intensity data as a proxy for aggregate output.

The authors observe a significant reduction in the convergence rate as a result of the pandemic. Across the cluster of districts, the drop in ß-convergence rate, compared to the pre-pandemic period, varied from approximately 33% for the poorer districts to close to zero for the richest group of districts. These findings suggest that the pandemic may lead to a wider disparity among different regions within the country.

This paper contributes to the literature in the following ways. First, to the best of the authors’ knowledge, this is the first paper to investigate the impact of COVID-19 on the convergence rate. A detailed look into the possible disparity in convergence among various regions is critical because a larger drop in convergence, especially among the poorer regions, may call for policy attention to attain long-term equitable development. The authors perform this exercise by dividing the districts into four quantile groups based on the distribution of night-light intensity. Second, while previous studies on convergence using nighttime light data have used a cross-sectional approach, this study is possibly the first attempt to use the panel regression method on this data. The application of this method can be useful in tackling district-level omitted variables bias. Finally, the heterogeneity analysis using different quantiles of the distribution of night-light intensity may help in designing targeted policies to mitigate the disparity across districts due to the shock.

In the light of a recent systemic model, the yoyo model, this paper aims to look at how to show Bergstrom's Rotten Kid theorem as a simple corollary of earlier results along this line of work, explaining why transferable utility implies Becker's Rotten Kid theorem. It also aims to look at the relevant problem with child labor.

The systemic yoyo model published earlier is the road‐map and foundation for the discussion. Since “as long as the benevolent head continues to contribute his income to all, other members are also motivated to maximize the family income,” as claimed by Becker's Rotten Kid theorem, the issue of child labor naturally comes into play. To this end, an example is constructed to show that the works of Baland and Robinson and Bommier and Dubois need to be fine‐tuned.

The paper provides a short and clean proof for Bergstrom's Rotten Kid theorem and, by linking to Buchanan's Samaritan's dilemma, the clouds surrounding the difficult situation can be penetrated with more clarity. More specifically, child labor and children's human capital accumulation should not be mutually exclusive, as Baland and Robinson and Bommier and Dubois had assumed.

The paper shows rigorously how Baland and Robinson and Bommier and Dubois need to be fine‐tuned in order to capture more of the published empirical findings.

The purpose of this paper is to make evidence-based recommendations for improving the responses of criminal justice agencies to juvenile burglary offenders.

The paper first analyzes what is known about factors relevant to young offenders’ initiation into burglary and subsequent persistence in that offense. It then evaluates research regarding juvenile justice interventions that can mitigate those factors in order to prevent youth from becoming involved in burglary or to encourage desistance in juvenile burglars.

Effective early intervention with juvenile burglars is vital, as burglars often begin committing this crime in their early teens and quickly develop expertise in the offense. Evidence supports the importance of positive mentoring, substance abuse programs, some forms of restorative justice and multi-modal interventions with education and employment components, while waiving these youth to adult court appears to offer little benefit over less punitive approaches.

This work delivers an original contribution by providing an analysis of existing burglary and juvenile justice research that may be useful to policymakers, law enforcement and other justice practitioners.

The current study examines the prevalence, perceived effectiveness, and potential antecedents (e.g. departmental culture) of law enforcement agencies in collaborating with probation and parole agencies. Specifically, the study reveals how the leaders (i.e. police chief, sheriff) in law enforcement view police-community corrections partnerships.

Data were collected from a state-wide survey of all sheriffs’ offices and a random sample of municipal police departments in Texas.

Findings indicated information sharing and specialized enforcement partnerships were the most common partnership types, partnerships were more common with adult and juvenile probation than with adult parole, and partnerships remain predominantly informal. Finally, police chiefs/sheriffs in the departments with a culture supportive of offender reentry were more likely to support and engage in partnerships with adult/juvenile probation and adult parole agencies.

Even without formal programs, it seems that police-probation/parole partnerships are, in one form or another, practically inevitable. The positive evaluation of law enforcement personnel leaves room for hope for expansions of such partnerships in the future.