Hybrid journal (It can contain Open Access articles) ISSN (Print) 0165-1587 - ISSN (Online) 1464-3618 Published by Oxford University Press[410 journals]
Authors:Canavari M; Drichoutis A, Lusk J, et al. Pages: 862 - 922 Abstract: AbstractIn this paper, we review recent advances in experimental auctions and provide practical advice and guidelines for researchers. We focus on issues related to randomisation to treatment and causal identification of treatment effects, design issues such as selection between different elicitation formats, multiple auction groups in a single session and house money effects. We also discuss sample size and power analysis issues in relation to recent trends in experimental research about pre-registration and pre-analysis plans. We position our discussion with respect to how the agricultural economics profession could benefit from practices adapted in the experimental economics community. We then present the pros and cons of moving auction studies from the laboratory to the field and review the recent literature on behavioural factors that have been identified as important for auction outcomes. PubDate: Fri, 29 Nov 2019 00:00:00 GMT DOI: 10.1093/erae/jbz038 Issue No:Vol. 46, No. 5 (2019)
Pages: 923 - 926 Abstract: The editors and the Editorial Board of the European Review of Agricultural Economics would like to thank the colleagues below who acted as referees during the period 1 July 2018 to 30 June 2019. PubDate: Tue, 10 Dec 2019 00:00:00 GMT DOI: 10.1093/erae/jbz043 Issue No:Vol. 46, No. 5 (2019)
Authors:Neuenfeldt S; Gocht A, Heckelei T, et al. Pages: 713 - 768 Abstract: AbstractIn this paper, we analyse the drivers of farm structural change in the EU-27, applying a novel analytical framework in the field of agricultural economics known as the multiplicative competitive interaction (MCI) model. MCI offers a more parsimonious specification for estimating models of regional farm group shares compared to the often-applied Markov approach. The MCI framework enables farm group-specific equations, which are used to account for drivers specific to certain farm groups. The MCI framework explains farm group shares at the regional level taken from the Farm Structure Survey (FSS) using socio-economic variables from the Farm Accountancy Data Network (FADN) and other databases for the period 1989–2013. We consider eight production specialisations and two size classes at the NUTS 2 regional level. The results indicate that the past farm structure explains approximately 36 per cent of the EU farm structure variation across regions and time, followed by natural conditions (16 per cent), agricultural prices (14 per cent), macroeconomic variables (9 per cent), subsidies (7 per cent), population (6 per cent) and agricultural income (6 per cent). Further, we have run a simulation experiment where we derived elasticities of structural change with respect to time-varying variables. The structural change appears to be the most elastic with respect to income and macroeconomic variables. PubDate: Thu, 15 Nov 2018 00:00:00 GMT DOI: 10.1093/erae/jby037 Issue No:Vol. 46, No. 5 (2018)
Authors:Cerroni S; Notaro S, Raffaelli R. Pages: 769 - 799 Abstract: AbstractOutcomes of food policies are highly uncertain. Therefore, the public’s support for these policies depends on individuals’ beliefs and the provision of scientific information. Using data collected from a discrete choice experiment survey, we explore whether new information regarding a food-safety policy influences respondents’ support, while controlling for risk and time preferences. Additionally, we examine if support depends on whether information is perceived as either good or bad news. Results from the estimation of parametric error component logit models, based on expected utility theory and rank dependent utility theory, suggest that good and bad news affects preferences and welfare measures. PubDate: Wed, 14 Nov 2018 00:00:00 GMT DOI: 10.1093/erae/jby038 Issue No:Vol. 46, No. 5 (2018)
Authors:Pindado E; Sánchez M. Pages: 800 - 833 Abstract: AbstractUsing a multilevel approach, this study examines how new entrants’ resources, capabilities and context influence growth-oriented new agricultural ventures. Results indicate that growth orientation is largely self-determined. The knowledge base of the new entrants, their social ties with entrepreneurs, together with the capabilities to identify and exploit opportunities, as well as those to effectively offer new products, trigger these growth-oriented ventures. Industry contexts also influence them, as those operating in less agriculturally competitive countries have a greater probability of becoming growth-oriented, suggesting convergence forces. Lastly, results reveal that competitiveness positively moderates the relationship between product innovation capabilities and growth orientation. PubDate: Tue, 13 Nov 2018 00:00:00 GMT DOI: 10.1093/erae/jby039 Issue No:Vol. 46, No. 5 (2018)
Authors:Thiene M; Franceschinis C, Scarpa R. Pages: 834 - 861 Abstract: AbstractCongestion levels in protected areas can be predicted by destination choice models estimated from choice data. There is growing evidence of subjects’ inattention to attributes in choice experiments. We estimate an attribute non-attendance latent class–random parameters model (LC–RPL) that jointly handles inattention and preference heterogeneity. We use data from a choice experiment designed to elicit visitors’ preferences towards sustainable management of a protected area in the Italian Alps. Results show that the LC–RPL model produces improvements in model fit and reductions in the implied rate of inattention, as compared to traditional approaches. Implications of results for park management authorities are discussed. PubDate: Sat, 17 Nov 2018 00:00:00 GMT DOI: 10.1093/erae/jby041 Issue No:Vol. 46, No. 5 (2018)
Hybrid journal (It can contain Open Access articles)
[410 journals]
