Spatial dynamic analysis of productivity growth of agri‐food companies

Martínez-Victoria, MCarmen; Maté‐Sánchez‐Val, Mariluz

doi:10.1111/agec.12486

Cited by 17 publications

(24 citation statements)

References 53 publications

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“…(), Skevas and Grashuis (), Martínez‐Victoria et al . () and Skevas () used exact geographical coordinates (i.e. latitude and longitude) to test for the presence of spatial spillovers in firms’ inefficiency/productivity scores, with the results verifying their existence.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Inefficiency and Spatial Spillovers in Dutch Dairy Farming

Skevas¹

2020

J Agricultural Economics

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This article examines the presence of spatial spillovers in farms' dynamic technical inefficiency scores using Data Envelopment Analysis and a second-stage spatial truncated bootstrap regression model. Dynamic inefficiency is measured in terms of variable input contraction and gross investment expansion, while the secondstage model allows an individual's dynamic inefficiency to be influenced by both own and neighbours' characteristics. The empirical application focuses on the panel data of specialised Dutch dairy farms observed over the period 2009-2016 and for which exact geographical coordinates of latitude and longitude are available. The results confirm the existence of spatial spillovers in farmers' dynamic technical inefficiency levels. Although changes in neighbours' subsidies do not significantly influence an individual's inefficiency, an increase in neighbours' age reduces an individual's performance, while an increase in neighbours' levels of intensification improves an individual's dynamic efficiency.

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Section: Introductionmentioning

confidence: 99%

Dynamic Inefficiency and Spatial Spillovers in Dutch Dairy Farming

Skevas¹

2020

J Agricultural Economics

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“…Subsequently, a binary matrix is constructed in which, for every farm, the k smallest distances receive a value of 1 while all others a value of 0 (see e.g. Martínez‐Victoria et al ., 2019). While IVD results in larger weights on characteristics of DMUs in closer proximity, this weight matrix implicitly assumes that spatial influences extend far beyond the nearby vicinity.…”

Section: Methodsmentioning

confidence: 99%

“…Journal of Agricultural Economics published by John Wiley & Sons Ltd on behalf of Agricultural Economics Society dependence in efficiency or productivity in non-agricultural applications (Glass et al, 2016;Tsionas and Michaelides, 2016;Pede et al, 2018). For the agricultural sector, Areal et al (2012) identified spatial dependence in technical efficiency of dairy farms in the UK, Martıńez-Victoria et al (2019) found spatial spillovers in productivity growth for Spanish agri-food companies and Skevas and Grashuis (2019) identified spatial spillover effects on efficiency scores among farm cooperatives in the USA. I.…”

Section: Introductionmentioning

confidence: 99%

“…(2012) identified spatial dependence in technical efficiency of dairy farms in the UK, Martínez‐Victoria et al . (2019) found spatial spillovers in productivity growth for Spanish agri‐food companies and Skevas and Grashuis (2019) identified spatial spillover effects on efficiency scores among farm cooperatives in the USA. I. Skevas and Oude Lansink (2020) and I. Skevas (2020) found spatial spillover effects on dynamic inefficiency of Dutch dairy farms.…”

Section: Introductionmentioning

confidence: 99%

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Spatial Spillovers on Input‐specific Inefficiency of Dutch Arable Farms

Schneider¹,

Skevas²

2020

J Agricultural Economics

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Traditional benchmarking implicitly assumes that decision making units operate in isolation from their peers. For arable production systems in particular, this assumption is unlikely to hold in reality. This paper quantifies spatial spillovers on input‐specific inefficiency using data envelopment analysis and a second‐stage bootstrap truncated regression model. The bootstrap algorithm is extended to allow for the estimation of the parameter of the spatial weight matrix, which captures the proximity between producers. The empirical application concerns Dutch arable farms for which latitudes and longitudes are available. The average inefficiency across years was 3.87% for productive inputs and 2.98% for damage abatement inputs under variable returns to scale. For productive inputs technical inefficiency, statistically significant spillover effects from neighbours’ age and their degree of specialisation depended on the type of the spatial weight matrix used (inverse distance or k‐nearest neighbours). Statistically significant spillover effects of subsidy payments were adverse while statistically significant spillover effects from insurance payments were beneficial. For damage abatement inputs technical inefficiency, statistically significant adverse effects were found for neighbours’ age and subsidy payments and beneficial effects from neighbours’ insurance payments and their degree of specialisation.

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“…They find a significant result showing that spatial spillover effects influence the technical efficiency of geographically close cooperatives. Martínez‐Victoria et al (2019) analyze the inherent spatial processes in the productivity growth of agri‐food firms located in the territory of Murcia (Spain). They corroborate previous studies finding a significant spatial interaction effect in the productivity growth of neighboring companies.…”

Section: Introductionmentioning

confidence: 99%

The impact of geographical positioning on agri‐food businesses' failure considering nonlinearities

Maté‐Sánchez‐Val

2020

Agribusiness

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This study applies spatial econometric techniques to evaluate the effect of external economic agents located in agri‐food business environments on the probability of those businesses failing. A logistic regression model that incorporates spatial interactions has been applied to the data. In addition, the article proposes an intermediate step in the modeling process based on generalized additive models to determine the specific functional relationships between the probit model and the explanatory variables. The results reveal that geographic location has a significant effect on the probability that agri‐food companies fail to find significant nonlinearities. [EconLit Citations: G33, Q14, R10]

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Spatial dynamic analysis of productivity growth of agri‐food companies

Cited by 17 publications

References 53 publications

Dynamic Inefficiency and Spatial Spillovers in Dutch Dairy Farming

Dynamic Inefficiency and Spatial Spillovers in Dutch Dairy Farming

Spatial Spillovers on Input‐specific Inefficiency of Dutch Arable Farms

The impact of geographical positioning on agri‐food businesses' failure considering nonlinearities

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