The robustness of poverty profiles reconsidered

Poverty measures and profiles are used increasingly to guide antipoverty policies in low-income countries. An essential element in these analyses is the specification of a poverty line. However, there are many different methods for setting poverty lines, and different methods can yield strikingly different results, with correspondingly different policy implications. Using recent household survey data from Mozambique, this paper explores the differences that occur using the most common poverty line methodologies, the Food Energy Intake (FEI) and the Cost of Basic Needs (CBN) methods, over different levels of geographic specificity. We find that regional and provincial rankings of Foster, Greer, and Thorbecke poverty indices are not robust to the method of poverty line determination, but that the characteristics of the poor are reasonably similar under all methods. The FEI poverty lines often yield counterintuitive results, whereas the family of CBN poverty lines was more robust. Food consumption patterns of the poor show a high degree of substitution among basic staples from one region to another, which is consistent with observed differences in relative food prices, indicating that CBN poverty lines that allow for regional variation in the food consumption bundle may be most appropriate in these settings.Poverty. ,Household surveys Mozambique. ,Food consumption Mathematical models. ,

Simulating Farm Household Poverty: From Passive Victims to Adaptive Agents

Existing microeconomic models for simulating poverty heavily rely on static projection from statistical inference. When used for simulation these models tend to conceive farm households as passive victims and thereby underestimate their resilience and adaptive capacity. Farming systems research has much to contribute to the research on poverty by bringing in a detailed understanding of farm household decision-making, which directly relates to their adaptive capacity. This paper presents a novel methodology to simulate poverty dynamics using a farming systems approach. The methodology is based on mathematical programming of farm households but adds three innovations: First, poverty levels are quantified by including a three-step budgeting system, including a savings model, a Working-Leser model, and an Almost Ideal Demand System. Second, the model is extended with a disinvestment model to simulate farm household coping strategies to food insecurity. Third, multi-agent systems are used to tailor each mathematical program to a real-world household and so to capture the heterogeneity of opportunities and constraints at the farm level as well as to quantify the distributional effects of change. An empirical application to Uganda illustrates the methodology. The method opens exciting new prospects for applying farming systems research and multi-agent systems to poverty analysis and the ex ante assessment of alternative policy interventions.Food Security and Poverty,

Parametric families for the Lorenz curve: an analysis of income distribution in European countries

The European Union Survey on Income and Living Conditions (EU-SILC) is the main source of information about living standards and poverty in the EU member states. We compare different parametric models for the Lorenz curve (LC) with an empirical analysis of the income distributions of 26 European countries in the year 2017. The objective of our empirical study is to verify whether simple mono-parametric models for the LCs can represent similarities or differences between European income distributions in sufficient detail, or whether an alternative, more sophisticated multi-parametric model should be used instead. In particular, we consider the power LC, the Pareto LC, the Lamè LC, a generalised bi-parametric version of the Lamè LC, a bi-parametric mixture of power LCs and the recently introduced arctan family of LCs. Whilst the first three families are ordered, in that different parametric values correspond to a situation of Lorenz ordering, the latter three may also identify the ambiguous situation of intersecting LCs. Therefore, besides focusing on the goodness-of-fit of the models considered and their mathematical simplicity, we evaluate the effectiveness of multi-parametric models in identifying the non-dominated cases

Multivariate Typology of Farm Households Based on Socio-Economic Characteristics Explaining Adoption of New Technology in Rwanda

The challenge for agricultural policymakers and planners, particularly in the context of Rwanda with high population density and consequently food insecurity, is how to enable farmers to adopt new technology. It is known that adoption of new technology may vary among farm households because of socio-economic characteristics. This paper intends to typify farm households in Rwanda based on the exploration of factors explaining adoption of new technology. Ultimately, typical farms obtained from the typology will be used, later as basis to develop representative mathematical programming models. Multivariate statistical techniques offer the means of creating such typologies, particularly when an in-depth database is available. This multivariate analysis approach, combining principal component analysis (PCA) and cluster analysis (CA), has allowed us to identify clearly five typical farm households and their socio-economic characteristics explaining adoption of new technology.. Multivariate statistical techniques, such as PCA and CA, are great tools to envisage building mathematical programming models on the basis of typical farm households.Agricultural and Food Policy, Community/Rural/Urban Development, Consumer/Household Economics, Food Consumption/Nutrition/Food Safety, Food Security and Poverty, Land Economics/Use, Marketing, Production Economics, Research and Development/Tech Change/Emerging Technologies,

Small area estimation of general parameters with application to poverty indicators: A hierarchical Bayes approach

Poverty maps are used to aid important political decisions such as allocation of development funds by governments and international organizations. Those decisions should be based on the most accurate poverty figures. However, often reliable poverty figures are not available at fine geographical levels or for particular risk population subgroups due to the sample size limitation of current national surveys. These surveys cannot cover adequately all the desired areas or population subgroups and, therefore, models relating the different areas are needed to 'borrow strength" from area to area. In particular, the Spanish Survey on Income and Living Conditions (SILC) produces national poverty estimates but cannot provide poverty estimates by Spanish provinces due to the poor precision of direct estimates, which use only the province specific data. It also raises the ethical question of whether poverty is more severe for women than for men in a given province. We develop a hierarchical Bayes (HB) approach for poverty mapping in Spanish provinces by gender that overcomes the small province sample size problem of the SILC. The proposed approach has a wide scope of application because it can be used to estimate general nonlinear parameters. We use a Bayesian version of the nested error regression model in which Markov chain Monte Carlo procedures and the convergence monitoring therein are avoided. A simulation study reveals good frequentist properties of the HB approach. The resulting poverty maps indicate that poverty, both in frequency and intensity, is localized mostly in the southern and western provinces and it is more acute for women than for men in most of the provinces.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS702 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

The impact of Inequality on Economic Growth: Evidence for Mexico 1895-1994

The aim of the paper is to explore the influences of initial inequality on the long run distribution of wealth. The paper presents two mathematical models that analyse the occupational choice of individuals in the presence of capital constraints and risk in entrepreneurial activities. The models show that inequality and particularly polarization hinder economic growth. The higher the initial level of polarization is, the lower the long run aggregate wealth of the economy and the higher the long run polarization will be. The models are calibrated using numerical simulations. The implications of the models are assessed empirically using data on economic growth, and income distribution in Mexico, during the period 1895-1994, as well as the "Doing Business" databases of the World Bank. Policy-wise it is found that a more egalitarian wealth distribution and less poverty can be achieved through wealth redistribution policies and by improving the business climate. This can be done by reducing the cost of setting-up firms (technology,bureaucratic and administrative costs), introducing labour-market reforms encouraging the hiring of those typically excluded such as the poor, improving the access to credit markets by reducing the costs of creating and/or registering collateral and broadening the credit bureau coverage. --

Measuring economic inequality and risk: a unifying approach based on personal gambles, societal preferences and references

The underlying idea behind the construction of indices of economic inequality is based on measuring deviations of various portions of low incomes from certain references or benchmarks, that could be point measures like population mean or median, or curves like the hypotenuse of the right triangle where every Lorenz curve falls into. In this paper we argue that by appropriately choosing population-based references, called societal references, and distributions of personal positions, called gambles, which are random, we can meaningfully unify classical and contemporary indices of economic inequality, as well as various measures of risk. To illustrate the herein proposed approach, we put forward and explore a risk measure that takes into account the relativity of large risks with respect to small ones.Comment: 29 pages, 4 figure

Surveillance and response systems for elimination of tropical diseases : summary of a thematic series in infectious diseases of poverty

The peer-reviewed journal Infectious Diseases of Poverty provides a new platform to engage with, and disseminate in an open-access format, science outside traditional disciplinary boundaries. The current piece reviews a thematic series on surveillance-response systems for elimination of tropical diseases. Overall, 22 contributions covering a broad array of diseases are featured - i.e. clonorchiasis, dengue, hepatitis, human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS), H7N9 avian influenza, lymphatic filariasis, malaria, Middle East respiratory syndrome (MERS), rabies, schistosomiasis and tuberculosis (TB). There are five scoping reviews, a commentary, a letter to the editor, an opinion piece and an editorial pertaining to the theme "Elimination of tropical disease through surveillance and response". The remaining 13 articles are original contributions mainly covering (i) drug resistance; (ii) innovation and validation in the field of mathematical modelling; (iii) elimination of infectious diseases; and (iv) social media reports on disease outbreak notifications released by national health authorities. Analysis of the authors' affiliations reveals that scientists from the People's Republic of China (P.R. China) are prominently represented. Possible explanations include the fact that the 2012 and 2014 international conferences pertaining to surveillance-response mechanisms were both hosted by the National Institute of Parasitic Diseases (NIPD) in Shanghai, coupled with P.R. China's growing importance with regard to the control of infectious diseases. Within 4 to 22 months of publication, three of the 22 contributions were viewed more than 10 000 times each. With sustained efforts focusing on relevant and strategic information towards control and elimination of infectious diseases, Infectious Diseases of Poverty has become a leading journal in the field of surveillance and response systems in infectious diseases and beyond