Productive efficiency and firm exit in the food sector

Dimara, Efthalia; Skuras, Dimitris; Tsekouras, Kostas; Tzelepis, Dimitris

doi:10.1016/j.foodpol.2007.08.003

Cited by 50 publications

(35 citation statements)

References 57 publications

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“…For example, Shee and Stefanou () apply traditional and endogeneity‐corrected stochastic production frontiers to a sample of Colombian food manufacturers and find the average technical efficiency of all food industry equaled 62.1%, with meat processing scoring the highest average efficiency of 66%. Using nonparametric DEA for Greek food manufacturing, Dimara, Skuras, Tsekouras, and Tzelepis () report a relatively low level of technical efficiency, with average values of 0.243, as well as a relatively high level of scale efficiency, scoring 0.674 on average. Also using the nonparametric framework, Ali, Singh, and Ekanem () address food manufacturing in India and find relatively high efficiencies for the gross sector, 0.902 in technical efficiencies and 0.870 in scale efficiencies.…”

Section: Introductionmentioning

confidence: 99%

Dynamic versus static inefficiency assessment of the Polish meat‐processing industry in the aftermath of the European Union integration and financial crisis

Kapelko

2017

Agribusiness

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This paper assesses the dynamic inefficiency of the Polish meatprocessing industry during the period between 2004 and 2012. This study employs also a comparison of dynamic with static inefficiency measures to address the importance of accounting for adjustment costs when measuring a firm's inefficiency. Dynamic and static cost inefficiencies and their decomposition into technical, allocative, and scale inefficiency are derived using Data Envelopment Analysis (DEA). Results show that firms' low levels of dynamic cost inefficiency are mainly due to dynamic allocative inefficiency rather than technical and scale inefficiency. The 2008 financial crisis appears to hamper firms' dynamic technical performance, but has also a positive influence on the dynamic allocative and scale inefficiencies. We further show that the average static measures tend to underestimate all inefficiency components compared to dynamic counterparts. [EconLit citations: C61, D61, L66].

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Section: Introductionmentioning

confidence: 99%

Dynamic versus static inefficiency assessment of the Polish meat‐processing industry in the aftermath of the European Union integration and financial crisis

Kapelko

2017

Agribusiness

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“…Dimara et al. () study food processing, while Gaigné and Le Mener () place a theoretical underpinning to trade and technology as drivers in exit choices among inefficient food processors. Pieralli et al.…”

Section: Introductionmentioning

confidence: 99%

Technical efficiency, herd size, and exit intentions in U.S. dairy farms

Dong

Hennessy

Jensen

et al. 2016

Agricultural Economics

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The U.S. dairy industry has seen major restructuring in recent decades. A sharp decline in the number of U.S. dairy farms and an increase in average herd sizes have accompanied exits, which have been concentrated among smaller herds. Given that more productive farms are better positioned to increase operation size and to continue operation, we hypothesize that the more technically efficient farms are better able to expand and also have stronger incentives to continue production. Using data from the USDA's 2010 ARMS Phase III, Dairy Production Practices and Costs and Returns Report, we estimate technical efficiency using stochastic production frontier analysis with endogenous inputs. The efficiency estimate is then incorporated into the analysis of exit intention and herd size. The results confirm our hypotheses that smaller and less efficient farms are more likely to exit and that more efficient dairy farms tend to expand herd size. Moreover, farms without successors but with older and more educated operators are more likely to exit. JEL classifications: D2, J2, Q12

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“…This phase of industrial development may be characterized by expansion of each farm. We examined whether such development was made possible at least partly by improved efficiency due to reallocation of resources brought about by the exit of less efficient firms and by productivity enhancement as a result of takeover (Hirschman, 1970;Lichtenberg and Siegel, 1987;Bertrand and Zitouna, 2008;Dimara et al, 2008;Plehn-Dujowich, 2009;Buddelmeyer et al, 2010).…”

Section: Descriptive Analysesmentioning

confidence: 99%

Industrial Development through Takeovers and Exits: The Case of the Cut Flower Exporters in Ethiopia

A¹

2015

J Entrepren Organiz Manag

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The exit and takeover of firms influence the structure and economic efficiency of an industry. The existing literature suggests that firms gradually learn about their own productivity. Some stagnate and ultimately exit if they encounter unfavorable prospects; others survive and grow. This selection process implies that the probability of firm exit initially increases with firm age as learning progresses before it eventually falls as learning is completed. We use a firm-level panel of Ethiopia's cut flower industry to confirm this theoretical implication. The empirical results also suggest that takeover improves productivity and profitability of average firms endowed with a favorable business environment.2

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Productive efficiency and firm exit in the food sector

Cited by 50 publications

References 57 publications

Dynamic versus static inefficiency assessment of the Polish meat‐processing industry in the aftermath of the European Union integration and financial crisis

Dynamic versus static inefficiency assessment of the Polish meat‐processing industry in the aftermath of the European Union integration and financial crisis

Technical efficiency, herd size, and exit intentions in U.S. dairy farms

Industrial Development through Takeovers and Exits: The Case of the Cut Flower Exporters in Ethiopia

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