Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in SummaryMost 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.JEL classification: O12, O13, O18, O53, R11 Key words: Poverty dynamics, non-farm sector, micro-growth regression Acknowledgements Our greatest debt is to Lina Marliani. She faithfully compiled the datasets used in this paper and produced many of the graphs and tables. In addition we would like to thank BPS for use of the data and DFID for funding the work of the INDOPOV team in the World Bank Office in Jakarta under which most of this work was done. Finally we would like to thank numerous colleagues in Jakarta, Göttingen, Washington and elsewhere for useful comments and suggestions. In particular, we would like to thank Stephan Klasen for very helpful comments and suggestions. Furthermore, a very useful set of comments from Vijaya Ramachandran has not been incorporated in this version of the Working Paper, but will be in a subsequent revision. All remaining imperfections are our own.

This paper has the aim of contributing to the existing research by analysing two particular topics. First of all, we show that the model specifications by Alesina et al. (J Econ Growth 8:155-194, 2003), which connects high ethnic fractionalisation to lower growth via bad policy variables, cannot fully explain the negative ethnic fractionalisation effect of the 1990s Sub-Saharan African growth experience. Moreover, we show that the remaining negative effect of ethnic fractionalisation on growth in Sub-Saharan Africa in the 1990s is due to an increased importance of adverse governance. Second, and on a very different note, we empirically investigate if ethnic fractionalisation might have a positive effect in a nation which is ethnically diverse due to immigration. There is evidence that it is important to distinguish between these two different kinds of ethnic fractionalisation.

No abstract

INTRODUCTION AND OVERVIEW most Sub-Saharan African nations' economic growth record is characterised by the persistence of low income and low growth equilibria, which implies a relative economic retardation in relation to the OECD countries. In contrast, most South East Asian nations' economic growth record was sufficiently good to facilitate an income catch-up towards the rich countries' high income and medium growth equilibria. However, whether this is the case, the global cross-national distribution of income should display at least two, or even more, distinct components. This in turn would imply the need for policy intervention to move nations from a low income and low growth equilibrium towards a self-sustaining fast growth trajectory, allowing an income catch-up to the richer countries. Hence, the question, whether past economic growth has led to an income per capita convergence among all countries has received much attention in the recent literature.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in SummaryMost 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.JEL classification: O12, O13, O18, O53, R11 Key words: Poverty dynamics, non-farm sector, micro-growth regression Acknowledgements Our greatest debt is to Lina Marliani. She faithfully compiled the datasets used in this paper and produced many of the graphs and tables. In addition we would like to thank BPS for use of the data and DFID for funding the work of the INDOPOV team in the World Bank Office in Jakarta under which most of this work was done. Finally we would like to thank numerous colleagues in Jakarta, Göttingen, Washington and elsewhere for useful comments and suggestions. In particular, we would like to thank Stephan Klasen for very helpful comments and suggestions. Furthermore, a very useful set of comments from Vijaya Ramachandran has not been incorporated in this version of the Working Paper, but will be in a subsequent revision. All remaining imperfections are our own.