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 AbstractWhile the majority of micro studies finds that rural education increases agricultural productivity, various recent cross-country regressions analyzing the determinants of agricultural productivity were only able to detect an insignificant or even surprisingly negative effect of schooling. In this paper, we show that this failure to find a positive impact of education in the international context appears to be a data problem related to the inappropriate use of enrolment and literacy indicators. Using a panel of 95 developing and middle-income countries from 1961 to 2002 that includes data on educational attainment, we show that education indeed has a highly significant, positive effect on agricultural productivity which is robust to the use of different control variables, databases and econometric methods. Distinguishing between different levels of education further reveals that only primary and secondary schooling attainment has a significant positive impact while the effect of tertiary education is insignificant. When distinguishing between income groups, our results indicate that even though the coefficient of the education variable is highly significant and positive for all quintiles, the returns to education are higher for the countries belonging to the richest three quintiles. This finding can be interpreted as support for the claim that education will have larger impacts on agricultural productivity in the presence of rapid technical change since it helps farmers to adjust more readily to the new opportunities provided by technological innovations.

Pro-poor growth has been identified as one of the most promising pathways to reduce poverty worldwide. Related research has developed a multitude of instruments to measure pro-poor growth using absolute and relative approaches and income and non-income data. This article contributes to the literature by expanding the toolbox with several new measures based on the concept of the growth incidence curve by Ravallion and Chen (2003) and the opportunity curve by Ali and Son (2007) that take into account the extraordinary importance of agriculture for poverty reduction in developing countries. The toolbox is then applied to three comparable household surveys from Rwanda (EICV data for the years 1999-2001, 2005-2006, and 2010-2011), a country that has experienced impressive economic growth since the genocide in the mid-1990s and that has undertaken considerable efforts to increase the population's access to social services over the last decade. Results indicate that Rwanda achieved in this time period enormous progress in the income, but also in the education and health dimension of poverty, which was in various cases even pro-poor in the relative and strong-absolute sense. The new tools further reveal that agricultural productivity of the labor productivity-poor increased relatively (but not absolutely) faster than for the labor productivity-rich. Lastly, we find indications that the labor productivity-poor dispose of less education than the labor productivity-rich which may imply further potential to increase the poor's productivity levels if their education levels increased.

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Various recent cross-country regressions have detected insignificant or even surprisingly negative effects of schooling on agricultural productivity. Applying advanced panel econometric techniques to a sample of 95 developing and emerging countries from 1961 to 2002, we show that these results are due to a problematic reliance on enrolment and literacy indicators. Using data on educational attainment, we instead find a sizeable and significant impact of schooling (avg. increase of approx. 3.2% per year of schooling) on agricultural productivity that is robust to estimation methods and model specification. We also find that returns from schooling are higher in technologically more advanced countries.