Agricultural training is a potentially effective method to diffuse relevant new technologies to increase productivity and alleviate rural poverty in Sub-Saharan Africa (SSA). However, since it is prohibitively expensive to provide direct training to all the farmers in SSA, it is critically important to examine the extent to which technologies taught to a small number of farmers disseminate to non-trained farmers. This paper investigates the technology dissemination pathways among smallholder rice producers within a rural irrigation scheme in Tanzania. As an innovative feature, we compare the performance of three categories of farmers: key farmers, who receive intensive pre-season training at a local training center; intermediate farmers, who are trained by the key farmers; and other ordinary farmers. By collecting and analyzing a unique five-year household-level panel data set, we estimate difference-indifferences models to assess how the gap in performance evolve as the technologies spill over from the trained farmers to the ordinary farmers. To disentangle the technology spillover process, we also examine the extent to which social and geographical network with the key and intermediate farmers influences the adoption of technologies by the ordinary farmers, by incorporating social relationship variables into spatial econometric models. We found that the ordinary farmers who were a relative or residential neighbor of a key or intermediate farmer were more likely to adopt new technologies than those who were not. As a result, while the key farmers' technology adoption rates rose immediately after the training, those of the non-trained ordinary farmers caught up belatedly. As the technologies disseminated, the paddy yield of the key farmers increased from 3.1 to 5.3 tons per hectare, while the yield of the ordinary farmers increased from 2.6 to 3.7 tons per hectare. Our results suggest the effectiveness and practical potential of farmer-to-farmer extension programs for smallholders in SSA as a cost effective alternative to the conventional farmer training approach.
Hedonic pricing analysis is conducted to determine the implicit values of various attributes in the market value of a good. In this study, hedonic pricing analysis was applied to measure the contribution of grain quality search and experience attributes to the price of rice in two rural towns in the Philippines. Rice samples from respondents underwent quantitative routine assessments of grain quality. In particular, gelatinization temperature and chalkiness, two parameters that are normally assessed through visual scores, were evaluated by purely quantitative means (differential scanning calorimetry and by digital image analysis). Results indicate that rice consumed by respondents had mainly similar physical and chemical grain quality attributes. The respondents’ revealed preferences were typical of what has been previously reported for Filipino rice consumers. Hedonic regression analyses showed that grain quality characteristics that affected price varied by income class. Some of the traits or socioeconomic factors that affected price were percent broken grains, gel consistency, and household per capita rice consumption. There is an income effect on rice price and the characteristics that affect price vary between income classes.
Climate change impacts on agriculture have become evident, and threaten the achievement of global food security. On the other hand, the agricultural sector itself is a cause of climate change, and if actions are not taken, the sector might impede the achievement of global climate goals. Science-policy engagement efforts are crucial to ensure that scientific findings from agricultural research for development inform actions of governments, private sector, non-governmental organizations (NGOs) and international development partners, accelerating progress toward global goals. However, knowledge gaps on what works limit progress. In this paper, we analyzed 34 case studies of science-policy engagement efforts, drawn from six years of agricultural research for development efforts around climate-smart agriculture by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Based on lessons derived from these case studies, we critically assessed and refined the program theory of the CCAFS program, leading to a revised and improved program theory for science-policy engagement for agriculture research for development under climate change. This program theory offers a pragmatic pathway to enhance credibility, salience and legitimacy of research, which relies on engagement (participatory and demand-driven research processes), evidence (building scientific credibility while adopting an opportunistic and flexible approach) and outreach (effective communication and capacity building).
Kuethe T. H. and Pede V. O. Regional housing price cycles: a spatio-temporal analysis using US state-level data, Regional Studies. A study is presented of the effects of macroeconomic shocks on housing prices in the Western United States using quarterly state-level data from 1988:1 to 2007:4. The study contributes to the existing literature by explicitly incorporating locational spillovers through a spatial econometric adaptation of vector autoregression (SpVAR). The results suggest these spillovers may Granger cause housing price movements in a large number of cases. SpVAR provides additional insights through impulse response functions that demonstrate the effects of macroeconomic events in different neighbouring locations. In addition, it is demonstrated that including spatial information leads to significantly lower mean-square forecast errors. [image omitted] Kuethe T. H. et Pede V. O. La variation cyclique regionale du prix du logement: une analyse geographico-temporelle des donnees sur les etats aux E-U, Regional Studies. A partir des donnees trimestrielles au premier trimestre de 1988 jusqu'au quatrieme trimestre de 2007, on presente ici une etude des effets des chocs macroeconomiques sur le prix du logement dans le sud-ouest des Etats-Unis. L'etude contribue a la documentation actuelle en incorporant explicitement les retombees geographiques par moyen d'une adaptation spatiale econometrique de l'autoregression vectorielle (spVAR). Les resultats laissent supposer que ces retombees pourraient entrainer une variation du prix du logement en de nombreuses situations. SpVAR fournit des apercus supplementaires par moyen des fonctions de reponse spontanee qui montrent l'impact des chocs macroeconomqiues dans divers endroits voisins. En plus, on demontre que l'inclusion des donnees spatiales reduit sensiblement les erreurs quadratiques moyennes prevues. Prix du logment Autoregression vectorielle Econometrie spatiale Kuethe T. H. und Pede V. O. Regionale Hauspreiszyklen: eine raumlich-zeitliche Analyse von Daten auf US-Bundesstaatsebene, Regional Studies. In dieser Studie verdeutlichen wir mit Hilfe von Quartalsdaten auf Bundesstaatsebene im Zeitraum vom ersten Quartal 1988 bis zum vierten Quartal 2007 die Auswirkungen makrookonomischer Schocks auf die Hauspreise im Westen der USA. Die Studie tragt zur vorhandenen Literatur bei, indem sie standortspezifische Ubertragungen mit Hilfe einer raumlichen okonometrischen Anpassung der Vektor-Autoregression (SpVAR) explizit einbezieht. Aus den Ergebnissen geht hervor, dass diese Ubertragungen in vielen Fallen Granger-kausal auf Veranderungen bei den Hauspreisen wirken konnen. Die SpVAR bietet zusatzliche Einblicke in Form von Impulsantwort-Funktionen, die die Auswirkungen makrookonomischer Ereignisse in verschiedenen angrenzenden Standorten nachweisen. Zusatzlich wird nachgewiesen, dass die Einbeziehung raumlicher Informationen zu signifikant niedrigeren mittleren quadratischen Prognosefehlern fuhrt. Hauspreise Vektorautoregression (VAR) Raumliche Okonometrie Kuethe T. H. ...
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