Recent work challenges the notion that attracting creative workers to a place is sufficient for generating local economic growth. In this article, we examine the problem of sustaining robust growth in the periphery of the USA, demonstrating the contingent nature of talent as an engine for economic growth. We test the hypothesis that rural growth in the knowledge economy is dependent on the ability to utilize new knowledge, perhaps generated elsewhere, in addressing local economic challenges. Tests confirm that the interaction of entrepreneurial context with the share of the workforce employed in the creative class is strongly associated with growth in the number of new establishments and employment, particularly in those rural counties endowed with attractive outdoor amenities.

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Conservation agriculture (CA) systems are based upon minimal soil disturbance; crop residue retention and crop rotation and/or intercrop association are increasingly seen to recycle nutrients, increase yield and reduce production costs. This study examines the effects of CA practices on crop productivity, profitability and soil quality under the conditions encountered by smallholder farmers in two farming communities from 2005 to 2011 in Malawi, as part of the contribution to remedy a lack of supporting agronomic research for these relatively new systems. The drier agroenvironment of Lemu of Bazale Extension Planning Area (EPA) is characterized by sandy clay loam soils and lower rainfall. Here, CA showed positive benefits on maize yield after the first season of experimentation, with highest increases of 2.7 Mg ha (US$176) spent under conventional tillage practices. In Lemu, both CA systems resulted in gross margins three times higher than that of the conventional control plot, while in Zidyana, CA monocrop maize and CA maize-legume intercrop resulted in 33 and 23% higher gross margins, respectively, than conventional tillage. In Zidyana, the earthworm population was highest (48 earthworms m −2 in the first 30 cm) in CA monocrop maize, followed by a CA maize-legume intercropping (40 earthworms) and lowest (nine earthworms) in conventionally tilled treatment. In both study locations CA monocrop maize and CA maizelegume intercrop gave higher water infiltration than the conventional treatment. Improvements in crop productivity, overall economic gain and soil quality have made CA an attractive system for farmers in Malawi and other areas with similar conditions. However, for extensive adoption of CA by smallholder farmers, cultural beliefs that crop production is possible without the ubiquitous ridge and furrow system and residue burning for mice hunting have to be overcome.

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Interactions among environmental factors, management decisions, and field characteristics cause temporal and spatial variability in corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] yields. The objectives of this paper are (i) to test whether yield response of corn to N and P and of soybean to P are spatially and temporally stable, and (ii) to evaluate the profitability of a variable rate (VR) N and P fertility management strategy over a 5-yr, corn-soybean rotation using this response information. A field near Windom, MN, USA, was cropped with corn (1997, 1999, and 2001) and soybean (1998, 2000). Three replications of 13 N and P treatments were established in a split-plot arrangement of a randomized complete block design. Treatments were applied at constant rates in strips across the entire field. Fertilizer N treatments were 0, 67, 112, 157, and 202 kg ha 21 and P treatments were 0, 56, and 112 kg P 2 O 5 ha 21. The field was partitioned into sub-blocks for spatial analysis of yield response. Corn and soybean response to these inputs was estimated for each block, each year. Results indicate that spatial variation of crop response to these inputs is significant, and that response of corn and soybean to P is temporally stable in some parts of the field, but not others. Response to N was not temporally stable. Results of an ex post profitability analysis found that average returns over the 5-yr period from the VR N and P management strategy were $28 ha 21 higher than returns from a uniform application strategy.

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Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the intensity of precision agriculture technologies adopted by cotton farmers. Particular attention is given to the role of spatial yield variability on the number of precision farming technologies adopted, using a count data estimation procedure and farm-level data. Results indicate that farmers with more within-field yield variability adopted a higher number of precision agriculture technologies. Younger and better educated producers and the number of precision agriculture technologies used were significantly correlated. Finally, farmers using computers for management decisions also adopted a higher number of precision agriculture technologies.

This research note examined the performance of Geographically Weighted Regression (GWR) using two calibration methods. The first method, Cross Validation (CV), has been commonly used in the applied literature using GWR. A second criterion selected an optimal bandwidth that corresponded with the smallest spatial error Lagrange Multiplier (LM) test statistic. We find that there is a tradeoff between addressing spatial autocorrelation and reducing degree of extreme coefficients in GWR. Although spatial autocorrelation can be controlled for by using the LM criterion, a substantial degree of extreme coefficients may remain. However, while the CV approach appears to be less prone to producing extreme coefficients, it may not always attend to the problems that arise in the presence of spatial error autocorrelation.