26 research outputs found

    Growth, Poverty and Inequality Dynamics

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    Since the Second World War the world has seen an economic growth spurt unprecedented in history. Economic growth is a necessary but not sufficient condition for improving human development, or in other words, economic growth is an important pre-requisite for the ultimate goal of human well-being. The four empirical essays of this book add to the general debate concerning dynamics of growth, poverty and inequality over the past 40 years from four different dimensions. The first chapter analyses the dynamics of the cross-country per capita income distribution and the existence of convergence clubs. The second chapter focuses on the dynamic development of the global income distribution and resulting implications for global income convergence, poverty reduction, pro-poor growth and the evolution of global inequality within and between countries. The third chapter investigates the deterministic relationship between ethnic fractionalisation and growth in a macro cross-country regression framework. Finally, the fourth chapter adds to the understanding of micro determinants of growth and poverty in the context of Indonesia

    The Pathways out of Poverty in Rural Indonesia: an empirical assessment

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    Since most poor live in rural areas, primarily engaged in low productivity farm activity, the pathway out of poverty must be strongly connected to productivity increases, whether they are realised in farming, rural non-farm enterprises or via urban migration. By utilizing the IFLS panel dataset for 1993 and 2000 from Indonesia, this paper shows, using empirical techniques, which pathways out of poverty were most successful in Indonesia?s past. Our findings suggest that the increased engagement of rural farmers in rural non-farm enterprises is a key way to alleviate rural poverty.

    Growth, Poverty and Inequality Dynamics

    Get PDF
    Since the Second World War the world has seen an economic growth spurt unprecedented in history. Economic growth is a necessary but not sufficient condition for improving human development, or in other words, economic growth is an important pre-requisite for the ultimate goal of human well-being. The four empirical essays of this book add to the general debate concerning dynamics of growth, poverty and inequality over the past 40 years from four different dimensions. The first chapter analyses the dynamics of the cross-country per capita income distribution and the existence of convergence clubs. The second chapter focuses on the dynamic development of the global income distribution and resulting implications for global income convergence, poverty reduction, pro-poor growth and the evolution of global inequality within and between countries. The third chapter investigates the deterministic relationship between ethnic fractionalisation and growth in a macro cross-country regression framework. Finally, the fourth chapter adds to the understanding of micro determinants of growth and poverty in the context of Indonesia

    Perspectives on the World Income Distribution - Beyond Twin Peaks Towards Welfare Conclusions

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    This paper contributes towards the growing debate concerning the world distribution of income and its evolution over that past three to four decades. Our methodological approach is twofold. First, we formally test for the number of modes in a cross-sectional analysis where each country is represented by one observation. We contribute to existing studies with technical improvements of the testing procedure, enabling us to draw new conclusions, and an extension of the time horizon being analyzed. Second, we estimate a global distribution of income from national log-normal distributions of income, as well as a global distribution of log-income as a mixture of national normal distributions of log-income. From this distribution we obtain measures for global inequality and poverty as well as global growth incidence curves.Convergence, Silverman\'s test, non-parametric statistics, bimodal, global income distribution, poverty, inequality, growth incidence curves

    Pathways Out of Poverty During an Economic Crisis: An Empirical Assessment of Rural Indonesia

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    Most poor people in developing countries still live in rural areas and are primarily engaged in low productivity farming activities. Thus pathways out of poverty are likely to be strongly connected to productivity increases in the rural economy, whether they are realised in farming, rural non-farm enterprises or via rural-urban migration. We use cross-sectional data from the Central Statistical Board (BPS) for 1993 and 2002, as well as a panel data set from the Indonesia Family Life Survey (IFLS) for 1993 and 2000, to show which pathways out of poverty were most successful over this period. Our findings suggest that increased engagement of farmers in rural non-farm enterprises is an important route out of rural poverty, but that most of the rural agricultural poor that exit poverty still do so while remaining rural and agricultural. Thus changes in agricultural prices, wages and productivity still play a critical role in moving people out of poverty.Poverty dynamics, non-farm sector, micro-growth regression

    Pathways out of poverty during an economic crisis : an empirical assessment of rural Indonesia

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    Most poor people in developing countries still live in rural areas and are primarily engaged in low productivity farming activities. Thus pathways out of poverty are likely to be strongly connected to productivity increases in the rural economy, whether they are realized in farming, in rural nonfarm enterprises, or by way of rural-urban migration. The authors use cross-sectional data from the Central Statistical Board for 1993 and 2002, as well as a panel data set from the Indonesia Family Life Survey for 1993 and 2000, to show which pathways out of poverty were most successful over this period. The findings suggest that increased engagement of farmers in rural nonfarm enterprises is an important route out of rural poverty, but that most of the rural agricultural poor that exit poverty still do so while remaining rural and agricultural. So changes in agricultural prices, wages, and productivity still play a critical role in moving people out of poverty.Rural Poverty Reduction,Population Policies,Achieving Shared Growth,Economic Theory&Research

    Rural Income Dynamics in Post-Crisis Indonesia

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    Indonesia is, what the World Development Report 2008 calls, a transforming country characterized by increasing rural-urban income disparities and high poverty rates. Bearing these facts in mind, it is striking how little is known about causes and mechanism of the underlying determinants of poverty in rural Indonesia. In this study we aim to shed more light on the determinants of rural incomes and poverty in Indonesia. Drawing on a unique and highly detailed rural household panel data set for Central Sulawesi we investigate what are the drivers of rural income growth. Moreover, exploiting the panel structure of our data set we are able to control explicitly for individual- and time-specific effects and for endogeneity issues in our estimations. In addition, in order to identify whether our findings might hold lessons for all of Indonesia, we upscale our analysis to the national level by comparing our results with the national household data survey SUSENAS. Our results indicate that a sharp increase in rural incomes took place in the post-crisis period. Moreover, the ability to alleviate poverty and to enjoy income growth has been strongly associated with a households ability to diversify into the non-farm sector of the economy, to focus on higher value-added agricultural activities and its ability to invest into new production techniques. These results seem to hold for most of rural Indonesia and are robust to various model specifications. --Rural non-farm income,agricultural productivity growth,rural poverty

    2008): Twin Peaks or Three Components? - Analyzing the World’s Cross-Country Distribution of Income. Working

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    Abstract In this paper we analyze the world´s cross-national distribution of income and its evolution from 1970 to 2003. We argue that modeling this distribution by a finite mixture and investigating its number of components has certain advantages over nonparametric kernel density estimation techniques. In particular, the components in the mixture have a clear interpretation as income groups, and in contrast to modes of the density their number does not depend on the chosen scale (original or logarithmic). Instead of so-called twin-peaks, we find that the distribution appears to have only two components in [1970][1971][1972][1973][1974][1975], but consists of three components from 1976 onwards, a low, average and high mean-income group, with group means diverging over time. Here we apply recently developed modified likelihood ratio tests for the number of components in a finite mixture. The intra distributional dynamics are investigated in detail using posterior probability estimates. JEL classification: C12, O11, O47, F0

    2008): Twin Peaks or Three Components? - Analyzing the World’s Cross-Country Distribution of Income. Working

    No full text
    Abstract In this paper we analyze the world´s cross-national distribution of income and its evolution from 1970 to 2003. We argue that modeling this distribution by a finite mixture and investigating its number of components has advantages over nonparametric inference concerning the number of modes. In particular, the number of components of the distribution does not depend on the scale chosen (original or logarithmic), whereas the number of modes does. Instead of so-called twin-peaks, we find that the distribution appears to have only two components in [1970][1971][1972][1973][1974][1975], but consists of three components from 1976 onwards, a low, average and high mean-income group, with group means diverging over time. Here we apply recently developed modified likelihood ratio tests for the number of components in a finite mixture. The intra distributional dynamics are investigated in detail using posterior probability estimates. JEL classification: C12, O11, O47, F0
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