Sub-Saharan Africa at a crossroads: a quantitative analysis of regional development

This repository item contains a single issue of The Pardee Papers, a series papers that began publishing in 2008 by the Boston University Frederick S. Pardee Center for the Study of the Longer-Range Future. The Pardee Papers series features working papers by Pardee Center Fellows and other invited authors. Papers in this series explore current and future challenges by anticipating the pathways to human progress, human development, and human well-being. This series includes papers on a wide range of topics, with a special emphasis on interdisciplinary perspectives and a development orientation.Sub-Saharan Africa is at a crossroads of development. Despite a quarter of a century of economic reforms propagated by national policies and international financial agencies and institutions, sub-Saharan Africa is still lagging in development. In this paper, the authors adopt two techniques using both qualitative (e.g. governance) and quantitative factors (e.g., GDP) to examine regional patterns of development in sub-Saharan Africa. More specifically, they examine and analyze similarities and differences among the countries in this region using a multivariate statistical technique, Principal Component Analysis (PCA), and a unsupervised neural network called Kohonen’s Self-Organizing Map (SOM) to cluster levels of development. PCA serves as a tool for determining regional patterns while SOM is more useful for determining continental patterns in development. Both PCA and SOM results show a “developed” cluster in Southern Africa (South Africa, Namibia, Botswana, and Gabon). SOM exhibits a cluster of least developed countries in southern Western Africa and western Central Africa. The results demonstrate that the applied techniques are highly effective to compress multidimensional qualitative and quantitative data sets to extract relevant information about development from a policy perspective. Our analysis indicates the significance of governance variables in some clusters while a combination of variables explains other regional clusters. Zachary Tyler works for a consulting firm in Massachusetts that conducts program evaluations for energy efficiency programs, and he continues to work on statistical and geospatial analyses of human development issues. In 2010, he will receive a master’s degree in energy and environmental analysis from Boston University. Sucharita Gopal is Professor and Director of Graduate Studies in the Department of Geography and Environment and a member of the Cognitive & Neural Systems (CNS) Technology Lab at Boston University. She teaches and conducts research in geographical information systems (GIS), spatial analysis and modeling, and remote sensing for environmental and public health applications. Her recent research includes the development of a marin integrated decision analysis system (MIDAS) for Belize, Panama, and Massachusetts, and a post-disaster geospatial risk model for Haiti. This paper is part of the Africa 2060 Project, a Pardee Center program of research, publications, and symposia exploring African futures in various aspects related to development on continental and regional scales. For more information, visit www-staging.bu.edu/pardee/research/

What really matters is the economic performance: Positioning tourist destinations by means of perceptual maps

The present study aims to cluster the world's main tourist destinations according to the growth of the economic performance of the tourist activity and of the tourist and economic development experienced during the last decade. With this objective, we combine the information from a set of tourist and economic indicators for the main 45 tourist destinations over the period between 2000 and 2010. Destinations are ranked with respect to their average growth rate over the sample period. By assigning a numerical value to each country corresponding to its position, all the information is summarised into two components (“economic performance of tourist activity” and “tourist and economic development”) via multivariate techniques for dimensionality reduction: multidimensional scaling (MDS) and categorical principal components analysis (CATPCA). By means of perceptual maps, we find that destinations can be clustered into four different groups. The first one, dominated by Western and Northern Europe markets, contains some of the top destinations (France, Spain and the United States). A second one, with a predominance of Mediterranean destinations (Cyprus, Greece, Italy and Israel), obtains high scores in both dimensions. In the third one, we find Cambodia and China, alongside Egypt and Turkey. Finally, a fourth group dominated by Eastern Europe destinations (Bulgaria, Croatia and Latvia) with low scores in both dimensions

Positioning and clustering of the world's top tourist destinations by means of dimensionality reduction techniques for categorical data

This study aims to cluster the world's top tourist destinations based on the growth of the main tourism indicators over the period between 2000 and 2010. It ranks the destinations with respect to the average growth rate over the sample period. The results find that both China and Turkey are at the top of the rankings of all variables. By assigning a numerical value to each country corresponding to its position, a Spearman's coefficient is calculated and a negative correlation found between a destination's dependency on tourism and the profitability of the tourism activity. Finally, several multivariate techniques for dimensionality reduction are used to cluster all destinations according to their positioning. Three groups are obtained: China, Turkey, and the rest of the destinations. These results show that the persistent growth of the tourism industry poses different challenges in different markets regarding destination marketing and management

Decision Model for Predicting Social Vulnerability Using Artificial Intelligence

The APC was funded by their authors.Social vulnerability, from a socio-environmental point of view, focuses on the identification of disadvantaged or vulnerable groups and the conditions and dynamics of the environments in which they live. To understand this issue, it is important to identify the factors that explain the difficulty of facing situations with a social disadvantage. Due to its complexity and multidimensionality, it is not always easy to point out the social groups and urban areas affected. This research aimed to assess the connection between certain dimensions of social vulnerability and its urban and dwelling context as a fundamental framework in which it occurs using a decision model useful for the planning of social and urban actions. For this purpose, a holistic approximation was carried out on the census and demographic data commonly used in this type of study, proposing the construction of (i) a knowledge model based on Artificial Neural Networks (Self-Organizing Map), with which a demographic profile is identified and characterized whose indicators point to a presence of social vulnerability, and (ii) a predictive model of such a profile based on rules from dwelling variables constructed by conditional inference trees. These models, in combination with Geographic Information Systems, make a decision model feasible for the prediction of social vulnerability based on housing information.This research was funded by the University of Granada, grant number PP2016-PIP0

Embodied Greenhouse Gas Emissions in Diets

Changing food consumption patterns and associated greenhouse gas (GHG) emissions have been a matter of scientific debate for decades. The agricultural sector is one of the major GHG emitters and thus holds a large potential for climate change mitigation through optimal management and dietary changes. We assess this potential, project emissions, and investigate dietary patterns and their changes globally on a per country basis between 1961 and 2007. Sixteen representative and spatially differentiated patterns with a per capita calorie intake ranging from 1,870 to <3,400 kcal/day were derived. Detailed analyses show that low calorie diets are decreasing worldwide, while in parallel diet composition is changing as well: a discernable shift towards more balanced diets in developing countries can be observed and steps towards more meat rich diets as a typical characteristics in developed countries. Low calorie diets which are mainly observable in developing countries show a similar emission burden than moderate and high calorie diets. This can be explained by a less efficient calorie production per unit of GHG emissions in developing countries. Very high calorie diets are common in the developed world and exhibit high total per capita emissions of 3.7-6.1 kg CO2eq./day due to high carbon intensity and high intake of animal products. In case of an unbridled demographic growth and changing dietary patterns the projected emissions from agriculture will approach 20 Gt CO2eq./yr by 2050

Embodied Greenhouse Gas Emissions in Diets

Changing food consumption patterns and associated greenhouse gas (GHG) emissions have been a matter of scientific debate for decades. The agricultural sector is one of the major GHG emitters and thus holds a large potential for climate change mitigation through optimal management and dietary changes. We assess this potential, project emissions, and investigate dietary patterns and their changes globally on a per country basis between 1961 and 2007. Sixteen representative and spatially differentiated patterns with a per capita calorie intake ranging from 1,870 to <3,400 kcal/day were derived. Detailed analyses show that low calorie diets are decreasing worldwide, while in parallel diet composition is changing as well: a discernable shift towards more balanced diets in developing countries can be observed and steps towards more meat rich diets as a typical characteristics in developed countries. Low calorie diets which are mainly observable in developing countries show a similar emission burden than moderate and high calorie diets. This can be explained by a less efficient calorie production per unit of GHG emissions in developing countries. Very high calorie diets are common in the developed world and exhibit high total per capita emissions of 3.7-6.1 kg CO2eq./day due to high carbon intensity and high intake of animal products. In case of an unbridled demographic growth and changing dietary patterns the projected emissions from agriculture will approach 20 Gt CO2eq./yr by 2050

Long-term impacts of tropical storms and earthquakes on human population growth in Haiti and the Dominican Republic

Since the 18th century, Haiti and the Dominican Republic have experienced similar natural forces, including earthquakes and tropical storms. These countries are two of the most prone of all Latin American and Caribbean countries to natural hazards events, while Haiti seems to be more vulnerable to natural forces. This article discusses to what extent geohazards have shaped both nation&#x27;s demographic developments. The data show that neither atmospheric nor seismic forces that directly hit the territory of Haiti have significantly affected the country&#x27;s population growth rates and spatial population densities. Conversely, since the 1950s more people were exposed to atmospheric hazards, in particular, in regions which historically experienced higher storm frequencies

Geography and Development in Bolivia: Migration, Urban and Industrial Concentration, Welfare, and Convergence: 1950-1992

This paper argues that considering the impact of geographical variables within Bolivia makes feasible a considerably richer analysis. The picture that emergesis occasionally not entirely consistent with the international evidence, but nonethelesspoints toward a systematic and significant impact of geography on development.

Does Country Equate with Culture? Beyond Geography in the Search for Cultural Boundaries

Traditionally, cultures have been treated as though they reside exclusively within, or perfectly overlap with countries. Indeed, the terms ‘‘country’’ and ‘‘culture’’ are often used interchangeably. As evidence mounts for substantial within-country cultural variation, and often between-country similarities, the problem with equating country and culture becomes more apparent. To help resolve the country-culture conundrum, we evaluate the extent to which political boundaries are suitable for clustering cultures based on a meta-analysis of 558 studies that used Hofstede’s (Culture’s consequences: international differences in work-related values. Sage Publications, Beverly Hills, 1980) cultural values framework. The results reveal that approximately 80 % of variation in cultural values resides within countries, confirming that country is often a poor proxy for culture. We also evaluate the relative suitability of other demographic and environmental characteristics, such as occupation, socio-economic status, wealth, freedom, globalization, and instability. Our results suggest that it may be more appropriate to talk about cultures of professions, socio-economic classes, and free versus oppressed societies, than about cultures of countries

SYSTEMIC ANALYSIS OF ILLEGAL MASS MIGRATION IN THE CENTRAL MEDITERRANEAN REGION

This thesis explores the systemic behavior of illegal mass migration in the Central Mediterranean region and proposes strategic approaches to address the problem. We hypothesize that the illegal migration is a complex systemic problem, where parts of the system are interdependent and behavioral change of any element effects the behavior of the whole. This research applies a series of quantitative and qualitative analyses where each reveals different aspects and properties of the migration system as a whole. The systemic analysis highlights the interconnectedness of different parts and their impact of the system’s output. Also, it reveals the cognitive background as a unique aspect of this region: namely, the decision to migrate is based on biased perception and bounded rationality rather than rational choice. In conclusion, we claim that the system’s output (i.e. level of illegal migration) is characterized by the interrelated behavior of parts of the migration system; therefore, strategic planning requires the notion of the dominant feedback loops, self-organization, time delays, limitations, and non-linear relations. Also, we conclude that a skewed perception based on social influence and cognitive biases influences a large number of people in that region to migrate.Captain, Hungarian Defence ForceApproved for public release. Distribution is unlimited