Market power, markup volatility and the role of cooperatives in the food value chain: evidence from Italy

Lee, Hyejin; Cayseele, Patrick Van

doi:10.1093/erae/jbac001

Cited by 10 publications

(8 citation statements)

References 115 publications

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“…Using data of a dairy cooperative in Italy from 2011 to 2016, Trestini and Chinchio (2018) found that mutual fund helped its member farmers reduce their feed cost vulnerability and thus protect their income. Lee and Van Cayseele (2022) found that while fruit and vegetable processor cooperatives enjoyed higher markups than non-cooperative processors, there was no significant difference in markup volatility between cooperative processors and non-cooperative processors. Thus, the role of agricultural cooperatives in stabilizing farm income is a complex and multifaceted issue that require further research to gain better understanding of the issue.…”

Section: Introductionmentioning

confidence: 82%

“…Second , the market power achieved by cooperatives may be used in part to buffer farming businesses from demand shocks in output markets. Cooperatives could commit to purchase relatively stable volumes of inputs at relatively stable prices, thus maintaining farmer revenues (Lee and Van Cayseele, 2022). Output marketing services are critical for farmers to access output market (Hellin et al ., 2009).…”

Section: Introductionmentioning

confidence: 99%

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Does cooperative membership stabilize farm income volatility? Evidence from the pig sector in China

Ji¹,

Zhuo²,

Deininger³

2023

CAER

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PurposeFarm income in the agricultural sector is susceptible to natural and market risks. A large body of literature has studied the effects of cooperative membership on household welfare, technical efficiency, productivity and production behavior, yet little has been known about the impact of cooperative membership on farm income volatility. This paper aims to fill this research gap by investigating the relationship between cooperative membership and farm income volatility of Chinese pig farmers and drawing policy implications.Design/methodology/approachThis paper examines the effect of cooperative membership on farm income volatility, using data from a two-round survey of pig farmers in China. The authors employ an endogenous switching regression model to address the selection bias issues associated with unobserved factors simultaneously affecting farmers' participation in agricultural cooperatives and income earning activities.FindingsUsing household panel from a two-round survey of 193 pig farmers in China, this analysis highlights two key findings: (1) agricultural cooperative membership has significant and positive effect on farm income stability and (2) the impact of cooperative membership on farm income stability varies with production scale.Originality/valueThis research makes two contributions to the literature. First, this study contributes to the scant literature exploring the relationship between agricultural cooperatives and farm income stability. Second, to the best of the authors' knowledge, this is the first study that explores such relationship in a livestock sector. The pig sector in China and around the developing world has been increasingly challenged by multifaceted risks (e.g. price fluctuations, epidemic diseases, environmental regulations), and understanding the role of agricultural cooperatives in farm income stability of pig farmers is of great practical and policy significance.

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Section: Introductionmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Does cooperative membership stabilize farm income volatility? Evidence from the pig sector in China

Ji¹,

Zhuo²,

Deininger³

2023

CAER

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“…Such a methodology requires firm microdata and, therefore, has the same data limitations as structural models. Nevertheless, there are some notable applications in EU dairy processing ( Čechura et al [25]; Koppenberg and Hirsch [57]; and Lee and Van Cayseele [58].…”

Section: Structural Modelsmentioning

confidence: 99%

Should We Cry over the Spilt Milk? Market Power and Structural Change along Dairy Supply Chains in EU Countries

Cavicchioli¹,

Cacchiarelli²,

Pretolani³

2022

Sustainability

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A “first-pass” test on a set of monthly prices index series from 2000 to 2015 was applied to detect market power exertion in the dairy value chain of 25 EU countries. Due to econometric and theoretical restrictions, the test yielded conclusive findings only in 11 over 25 EU Countries. Such results show that in Austria, Portugal, Slovakia, Hungary and Croatia, the downstream sector exerts market power. Other EU countries (Spain, UK, Denmark, Czech Republic, Bulgaria and Sweden) are characterised by perfectly competitive dairy chains. These results were consistent with the findings of previous studies based on structural and mark-up models. Results of the market power test in the subsample of 11 countries have been related to various structural characteristics of the dairy chains. Market power exertion is negatively related to the average farm size. Such variable may be seen as a proxy of the degree of supply concentration provided by Producers Organizations (POs) to increase the bargaining power of the farm sector along the food chain. To test such a hypothesis, comparable data on supply concentration by POs across EU Countries are necessary. On the other hand, the structural change, represented by the increase of average farm size over time and the concentration rate in higher classes (above 250,000 € of Standard Output) is almost unrelated to the perfectly competitive conduct along EU dairy chains.

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“…To our knowledge, no previous study of US food manufacturing productivity or markups has included non-Hicks-neutral productivity, particularly considering labour-augmenting technical 1 Melitz and Polanec (2015) explain how to describe this productivity in what they call 'dynamic OP decomposition of productivity'. 2 Analysis of production integrated with markups in food manufacturing was mainly addressed using the New Empirical Industrial Organisation (NEIO) approach (Bhuyan & Lopez, 1997;Lopez et al, 2002;Lopez et al, 2018;and Koppenberg & Hirsch, 2021;Lee & Van Cayseele, 2022; see Sexton &Lavoie, 2001, andKaiser &Suzuki, 2006 for a review of earlier NEIO studies).…”

Section: Introductionmentioning

confidence: 99%

Markups in US food manufacturing accounting for non‐neutral productivity

Jaumandreu,

Lopez

2024

J Agricultural Economics

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We examine the evolution of productivity and markups in US food and beverage manufacturing from 1959 through 2018. We account for non‐Hicks‐neutral (labour‐augmenting) productivity changes and compare markups with those in general manufacturing using the same dataset and model. We also compare our results with those of the increasingly popular De Loecker and Warzynski (2012, American Economic Review, 102, 2437) method, which does not account for non‐Hicks‐neutral productivity growth. Empirical results show that productivity growth in the food and beverage sector has been relatively slow and driven with equal intensity by Hicks‐neutral and labour‐augmenting productivity gains. General manufacturing shows higher productivity growth that is mostly labour‐augmenting, with markups comparable to those of food manufacturing. We find that accounting for labour‐augmenting productivity produces more moderate markup estimates than the De Loecker and Warzynski (2012) method. We also find no evidence of markups rising in either food manufacturing or general manufacturing in the last 20 years, in contrast to much of the recent economic literature.

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Market power, markup volatility and the role of cooperatives in the food value chain: evidence from Italy

Cited by 10 publications

References 115 publications

Does cooperative membership stabilize farm income volatility? Evidence from the pig sector in China

Does cooperative membership stabilize farm income volatility? Evidence from the pig sector in China

Should We Cry over the Spilt Milk? Market Power and Structural Change along Dairy Supply Chains in EU Countries

Markups in US food manufacturing accounting for non‐neutral productivity

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