The Role of Legal System and Socioeconomic Aspects in the Environmental Quality Drive of the Global South

The increasing environmental challenges associated with the Global South is potentially associated with the socioeconomic changes amid potential institutional deficiencies such as the weak or inefficient environmental regulation. Thus, this twenty-first century challenge has increasingly necessitated more climate action from the Global South as championed by the developed economies. On this note, examines the environmental aspects of law and order (LO) vis-à-vis legal system and socioeconomic (SE) indexes of the Political Risk Services for a panel of 80 selected Global South countries over the period 1984–2014. Additionally, by employing the economic growth vis-à-vis the Gross Domestic Product per capita (GDPC) as additional explanatory variable, the study employs the more recent experimental techniques of Mean Group Estimator (MG), the Augmented Mean Group Estimator (AMG) and the Common Correlated Effects Mean Group (CCEMG). Importantly, with the more efficient CCEMG, the study found that the strength of the legal system in the Global South (although not statistically significant) is a crucial factor to mitigated carbon emission in the panel countries. However, the study found that an improved socioeconomic condition and economic expansion is detrimental to the Global South’s environmental quality. Furthermore, the Granger causality result implied that each of LO, SE and GDPC exhibits a feedback relationship with carbon emissions. Hence, the study suggests the need for a stronger implementation of environmental regulations through a revitalized legal system and some concerted socioeconomic policies that address poverty and unemployment among other factors.

     

The impact of electronic land administration on urban housing development: The case study of the Federal Capital Territory of Nigeria

This paper evaluates the impact of electronic land administration as an e-government policy initiative in Nigeria. It analyses conceptually the differences between the expected and actual value of Abuja Geographic Information Systems (AGIS)—an e-land administration project—on urbanisation in Abuja, the Federal Capital Territory (FCT) of Nigeria. The AGIS case study reveals that differences between the expected and actual value of strengthening the state’s financial capacity are low. The differences are medium for enhancing access to and security of credit, and improvement of land use planning and environmental management and high for the promotion of popular participation. The elicited differences are traceable to hindrances inscribed in Land Use and National Housing Acts, to inequitable access to land, inconsistent resettlement policy, poor community participation and financial misconduct. The findings suggest the need to pay attention to provisions through which e-government can support the reduction of country specific problems, improve the quality of institutions and to promote urbanisation, thereby increasing social welfare as well as participation by the people in promoting suitable and adequate shelter for all citizens.     

Recoverable robust timetabling for single delay: Complexity and polynomial algorithms for special cases

In this paper, we study the problem of planning a timetable for passenger trains considering that possible delays might occur due to unpredictable circumstances. If a delay occurs, a timetable could not be able to manage it unless some extra time has been scheduled in advance. Delays might be managed in several ways and the usual objective function considered for such purpose is the minimization of the overall waiting time caused to passengers. We analyze the timetable planning problem in terms of the recoverable robustness model, where a timetable is said to be recoverable robust if it is able to absorb small delays by possibly applying given limited recovery capabilities. The quality of a robust timetable is measured by the price of robustness that is the ratio between the cost of the recoverable robust timetable and that of a non-robust optimal one.     

Perspectives on the battered child syndrome in Nigeria

The battered child syndrome remains an understudied phenomenon in Nigeria. This is partly due to the romanticized and the noble savage image which holds that child abuse cannot occur in Africa. Even when it is occasionally discovered, it tends to be blamed on urbanization. Evidence now shows that some cultural practices in Nigeria could be defined as child battering. Many types of child battering which occur include: physical abuse, some forms of female circumcision, nonaccidental injury, corporal punishment, infanticide, and abandonment. Other types are sexual abuse, emotional abuse, and malnutrition. A current focus on the battered child syndrome may avert problems for future generations of Nigerians.     

Modified ridge-type for the Poisson regression model: simulation and application

The Poisson regression model (PRM) is employed in modelling the relationship between a count variable (y) and one or more explanatory variables. The parameters of PRM are popularly estimated using the Poisson maximum likelihood estimator (PMLE). There is a tendency that the explanatory variables grow together, which results in the problem of multicollinearity. The variance of the PMLE becomes inflated in the presence of multicollinearity. The Poisson ridge regression (PRRE) and Liu estimator (PLE) have been suggested as an alternative to the PMLE. However, in this study, we propose a new estimator to estimate the regression coefficients for the PRM when multicollinearity is a challenge. We perform a simulation study under different specifications to assess the performance of the new estimator and the existing ones. The performance was evaluated using the scalar mean square error criterion and the mean squared error prediction error. The aircraft damage data was adopted for the application study and the estimators’ performance judged by the SMSE and the mean squared prediction error. The theoretical comparison shows that the proposed estimator outperforms other estimators. This is further supported by the simulation study and the application result.KEYWORDS: Poisson regression model, Poisson maximum likelihood estimator, multicollinearity, Poisson ridge regression, Liu estimator, simulation     

Robust designs for misspecified logistic models

We develop criteria that generate robust designs and use such criteria for the construction of designs that insure against possible misspecifications in logistic regression models. The design criteria we propose are different from the classical in that we do not focus on sampling error alone. Instead we use design criteria that account as well for error due to bias engendered by the model misspecification. Our robust designs optimize the average of a function of the sampling error and bias error over a specified misspecification neighbourhood. Examples of robust designs for logistic models are presented, including a case study implementing the methodologies using beetle mortality data.