Multi-Dimensional Analysis of Poverty in Ghana Using Fuzzy Sets Theory

The paper studies the multidimensional aspects of poverty and living conditions in Ghana. The aim is to fill the vacuum that has been left by traditional uni-dimensional measures of deprivation based on poverty lines, exclusively estimated on the basis of monetary variables such as income or consumption expenditure. It combines monetary and non-monetary, and qualitative and quantitative indicators, including housing conditions, the possession of durable goods, equivalent disposable income, and equivalent expenditure, with a number of composite human welfare measures. The study employs the fuzzy-set theoretic framework to compare levels of deprivation in Ghana over time usig micro data from the last two rounds of the Ghana Living Standard Surveys (1991/1992 and 1998/1999). The estimation results of the membership functions, depicting the levels of deprivation for the various categories of deprivation indicators, show a composite deprivation degree of 0.2137 for the whole country in 1998/99 as compared to 0.2123 in 1991/92. This deprivation trend reveals that poverty levels hard scarcely changed in Ghana. In fact, it even rose slightly during the nineties, contrary to the uni-dimensional analytical GLSS 4 report of an overall broadly favourable trend in poverty in Ghana during the 1990s.Ghana, fuzzy set, multi-dimensional poverty, composite deprivation or poverty index

Working Paper 83 - Are African Countries Richer Than They Are Developed? A Multidimensional Analysis of Well-Being

Sen’s capability approach inspired a new conception of development and succeeded in the Human Development Index (HDI). On the basis of HDI critics, we propose to enlarge the number of variables and we use 9 indicators of Standard of Living and 9 indicators of Quality of Life that allows measuring two components of well-being and that can be divided into various fields (health, education, environment, etc.) to provide a finest measurement of poverty. The empirical results for 170 countries in 2000 are based on two different multidimensional analysis of poverty, the Totally Fuzzy Analysis and the Factorial Analysis of Correspondences. The conclusions depend on the considered method but are generally similar. The paper focuses on the African continent and shows that some countries are “richer” than “developed” or inversely. The correlation matrix between different indicators reveals that education is a key variable for defining poverty. Comparisons extended with HDI classification and GDP per capita classification prove that monetary poverty is related with all other dimensions of poverty and that the HDI takes into account its essential dimension even if it can’t be used to reduce some specific aspects as our original index.

Methodological Developments in Human Development Literature

The present paper is a review of methodological advancements in human development literature starting from 1990 till date. While highlighting the contribution of UNDP to the concept of human development and construction of HDI it mentions that the introduced concept and method of measurement is a huge qualitative improvement over the earlier concept of growth and per capita GDP measurement. Although the human development report started with a poor methodology, thanks to the galaxy of scholars for their untiring efforts and invaluable contributions in the successive years that enabled UNDP in refining its methodology to a large extent. There is no denying fact that there is no end to refinements, the purpose for which Mahbub ul Haq struggled in his entire life has been served

A capability approach to the analysis of rural households' wellbeing in Nigeria

Rural households in Nigeria have been characterized as poor, and with little opportunity for development. Many studies have equated poverty with well being, however empirical literature on well being is less researched. This paper attempts bridge the knowledge gap in the empirical literature of well being studies and specifically the use of the capability approach in its application in the Nigerian well being context which is not as well researched as poverty studies. The study made use of the Nigerian Core welfare indices survey questionnaires of 2006 to provide data relevant to capability well being dimensions. The dimensions include housing, health, nutrition, education, asset ownership/economic, information flow and security. The first part of the study involve developing indices of well being using the fuzzy set in order to generate a composite well being index by the elementary indicators of the well being dimensions. The second part of the study used a logistic regression to explore the variability in achieving the composite well being index value by a set of Conversion factors. The fuzzy set result revealed that the capability to attain a desired state of well being is highest with respect to asset ownership and lowest with respect to security. The logistic analysis shows that the predicted probability of attaining the mean capability well being level increases for male headed rural households, increasing educational level and age of the head, increasing household size, employment in the public sector and residence in any other geopolitical zone except the Northwestern zone.Well being, Capability, Rural Households, Nigeria

A New Approach to Modeling Early Warning Systems for Currency Crises : can a machine-learning fuzzy expert system predict the currency crises effectively?

This paper presents a hybrid model for predicting the occurrence of currency crises by using the neuro fuzzy modeling approach. The model integrates the learning ability of neural network with the inference mechanism of fuzzy logic. The empirical results show that the proposed neuro fuzzy model leads to a better prediction of crisis. Significantly, the model can also construct a reliable causal relationship among the variables through the obtained knowledge base. Compared to the traditionally used techniques such as logit, the proposed model can thus lead to a somewhat more prescriptive modeling approach towards finding ways to prevent currency crises.

"A New Approach to Modeling Early Warning Systems for Currency Crises : can a machine-learning fuzzy expert system predict the currency crises effectively?"

This paper presents a hybrid model for predicting the occurrence of currency crises by using the neuro fuzzy modeling approach. The model integrates the learning ability of neural network with the inference mechanism of fuzzy logic. The empirical results show that the proposed neuro fuzzy model leads to a better prediction of crisis. Significantly, the model can also construct a reliable causal relationship among the variables through the obtained knowledge base. Compared to the traditionally used techniques such as logit, the proposed model can thus lead to a somewhat more prescriptive modeling approach towards finding ways to prevent currency crises.

A Composite Fuzzy Indicator for Assessing Farm Household Potential for Non-farm Income Diversification

European politicians encourage the income diversification of rural households through various measures. Although being aware of farm households’ potential for non-farm income diversification seems important for finely-targeting such policy measures, no attempt has thus far been made to summarise the various determinants of income diversification in a single figure. This contribution aims to close this gap. A composite fuzzy indicator that measures farm household potential for non-farm income diversification is developed and applied to 1,053 farm households in Bulgaria, Hungary, Poland, Romania, and Slovenia. The indicator summarises the incentives of and capacities for non-farm income diversification on the individual household member level, and on the household and regional levels to a single measure using fuzzy logic methodology. The composite fuzzy indicator performs well, and the results for the single farm households can easily be retraced. The indicator not only singles out the households that have the potential for non-farm income diversification, but also shows the reasons for this. Thus, the result for 1,053 farm households is not only that most of them have a high potential for non-farm income diversification, but also that the majority of these households are pushed in diversification due to the smallness of their farms. Only a few of the farm households act under pull conditions, i.e. diversification is not a necessity, but they could opt for profitable non-farm employment due to favourable age, education, and regional conditions. Decision-makers could utilise the composite fuzzy indicator to finely-target diversification measures to the multifaceted conditions of farm households.composite indicator, fuzzy logic, rural non-farm income diversification, transition countries, Consumer/Household Economics, C65, J24, Q12, R23,