Evaluating spatial and temporal variation in agricultural output elasticities in Turkey

Yu, Tun‐Hsiang; Cho, Seong‐Hoon; Koc, A. Ali; Bölük, Gülden; Kim, Seung Gyu; Lambert, Dayton M.

doi:10.1111/agec.12064

Cited by 5 publications

(3 citation statements)

References 20 publications

(27 reference statements)

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“…The overall effect of agricultural labor and tractors were not significant because of their spatial spillover or indirect effect. These findings are consistent with Yu et al (2014) that suggested agricultural labor and tractors had positive and significant direct effect on the output in Turkey but their total effect was not significant due to the influence of spillover effects.…”

Section: Resultssupporting

confidence: 91%

“…Their findings suggest that the fiscal supports produced positive direct and spillover effects on farmer income over the study period; while the spatial spillover effect of financial supports had become negative after the policy reinforcement in 2004. Yu et al (2014) applied a spatial agricultural output model to measure the effects of national agricultural policy reform introduced in 2001 in Turkey by using the 2000 and 2007 provincial-level data. Without including particular agricultural policy variables, their results implicitly suggest that policy reform created diverse spatial spillover effects on output in different regions.…”

Section: Introductionmentioning

confidence: 99%

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Effects of government supports and credits on Turkish agriculture

Koc¹,

Kıymaz³

et al. 2019

JADEE

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Purpose Domestic supports on Turkish agriculture have substantially increased over the past decade while empirical evaluation of their output impact is limited. Also, the existing literature often neglects potential spatial spillover effects of agricultural policies or subsidies. The purpose of this paper is to quantify the direct and spillover effects of Turkish agricultural domestic measures and agricultural credits use on the added agricultural value. Design/methodology/approach This study applied a spatial panel model incorporating spatial interactions among the dependent and explanatory variables to evaluate the impact of government support and credit on Turkish agricultural output. A provincial data set of agricultural output values, input factors and government subsidies from 2004 to 2014 was used to model the spatial spillover effects of government supports. Findings Results show that a one percent increase in agricultural credits in a given province leads to an average increase of 0.17 percent overall in agricultural value-added per hectare, including 0.05 percent from the direct effect and 0.12 percent from the spillover effect. Contrary to agricultural credits, a one percent increase in government supports in a province generates a mixed direct and spillover effects, resulting in an overall reduction of 0.13 percent in agricultural value-added per hectare in Turkey. Research limitations/implications This study could be extended by controlling for climate, biodiversity and investment factors to agricultural output in addition to input and policy factors if such data were available. Originality/value This study fills the gap in the literature by determining the total effect, including direct and spatial spillover effect, of domestic supports and credits on Turkish agricultural value. The findings provide crucial information to decision makers regarding the importance of incorporating spatial spillover effects in the design of agricultural policy.

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Section: Resultssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Effects of government supports and credits on Turkish agriculture

Koc¹,

Kıymaz³

et al. 2019

JADEE

Self Cite

View full text Add to dashboard Cite

show abstract

“…The spatial autocorrelation detection highlights the spatial structure and aggregation levels of the producing regions. Therefore, different surveys have used spatial variation techniques for the analysis of agricultural productivity [29][30][31][32].…”

Section: Discussionmentioning

confidence: 99%

Spatial-Temporal Patterns of Bean Crop in Brazil over the Period 1990–2013

Clemente

Júnior

Guimarães

et al. 2017

IJGI

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Abstract:The understanding of spatial dependence and distribution of agricultural production factors is a key issue for the territorial planning and regional development. This study evaluates the spatial-temporal dynamics of bean crops in Brazil over the period 1990-2013. Common bean (Phaseolus vulgaris L.) is one of the staple foods for the Brazilian population, with nationwide production and cultivated mostly by family farmers. The analyzed variables of this crop included harvested area, produced quantity, and average crop yield. We investigated spatial autocorrelations using the Global and Local Moran Index. The global spatial autocorrelation statistics demonstrated a general spatial dependence of bean production over Brazil, while the local spatial autocorrelation statistics detect statistically significant zones of high and low bean-production attributes. Maps of growth and acceleration rate of the variables were constructed, showing the areas that increased, decreased, or stagnated during the time series. The results showed a considerable reduction of the bean harvested area, but there were significant increases in produced quantity and average crop yield. Results showed distinct and significant patterns of bean-production variables in Brazilian territory over the different years. Regional differences and peculiarities are evident, emphasizing the need for directing investments to agricultural research and public policy.

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