Considering Technical and Allocative Efficiency in the Inverse Farm Size–Productivity Relationship

Henderson, Heath

doi:10.1111/1477-9552.12086

Cited by 67 publications

(40 citation statements)

References 40 publications

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“…() on sugarcane CF schemes in Kenya. Also, the results, put together support the inverse farm size relationship as smaller farmers benefit more from CF than medium and larger farms (Carletto, Savastano, & Zezza, ; Henderson, ; Khataza, Hailu, Doole, Kragt, & Alene, ). This is because small farms have advantages in labor supervision and knowledge.…”

Section: Resultsmentioning

confidence: 68%

Participation in contract farming and farm performance: Insights from cashew farmers in Ghana

Dubbert

2019

Agricultural Economics

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The global demand for cashew nuts continues to increase steadily. However, many African countries face difficulties in marketing and adding value to the product. Using recent survey data of 391 cashew farmers in Ghana, this paper contributes to the growing evidence on the significance of contract farming (CF) in improving the welfare of rural households in developing countries. Specifically, the paper analyzes the factors that influence cashew farmers' decisions to participate in CF, and the impact of participation on farmers' performance. We employ a recently developed switching regression model with endogenous explanatory variables and endogenous switching to control for selection bias caused by observable and unobservable factors. The empirical results show that participation in CF significantly increases labor productivity and price margins, as well as cashew yields, and net revenues. A disaggregated analysis of the sample into farm size categories reveals that small-sized cashew farms tend to benefit more through CF, compared to medium-and large-sized farms.

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Section: Resultsmentioning

confidence: 68%

Participation in contract farming and farm performance: Insights from cashew farmers in Ghana

Dubbert

2019

Agricultural Economics

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“…If technical efficiency is highly volatile due to leapfrogging and falling-behind processes for each company, market exit may occur randomly, and predictions about industry development will not be possible. However, if instead the 11 See, for example, Latruffe et al (2004); Bokusheva and Hockmann (2006;Henderson (2014). position or rank of the companies is stable, verifiable statements regarding structural change are possible.…”

Section: Heterogeneity In Efficiencymentioning

confidence: 99%

Heterogeneity in Production Structures and Efficiency: An Analysis of the Czech Food Processing Industry

Čechura

Hockmann

2017

Pacific Economic Review

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The present study analyses firm heterogeneity and sector‐specific technology. The theoretical model stands on the assumption of maximizing the return on capital and overcomes problems involved in simple profit maximization. The results show that a random parameter model with sector dummies and heteroscedasticity is the most appropriate model specification for distinguishing firm‐level and sector‐level efficiency and heterogeneity. The heterogeneity among firms as well as among sectors was found to be an important characteristic in Czech food processing. This holds for production technology as well as for technical efficiency. Moreover, the decomposition of total variance shows that intrasectoral differences in technologies are much more pronounced than the intersectoral differences. The differences in intrasector heterogeneity also suggest that the food processing industry will be subject to accelerated structural change in the coming years. Moreover, we found that on average the companies highly exploit their production possibilities. However, some companies cannot keep pace with competitors. Because leapfrogging does not appear to be present in selected industries (except for Milling), structural change is expected to occur in such a way that the most successful companies will strengthen their position.

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“…In addition, (ii) not supporting the IR, either partially or completely. Labour market imperfections are the driving force behind the inverse relationships in Nicaragua and Rwanda [18], [19]. Land yields increased with plot size both by season and over the year in China [20].…”

Section: Review Of Related Literaturesmentioning

confidence: 99%

Estimating the Optimal Land Management Scale of Big Grain Production Households and Comprehensive Family Farms Based on the Decision Graph

Luo¹

2017

IJEFM

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Farmland scale management can bring large scale benefits to producers, promote labour productivity and increase farmers' income. However, excessive concentration of farmland also has a few shortcomings, such as decreases in intensive farming, farmland productivity, and employment efficiency. Identifying the optimal land management scale is an effective means to improve agricultural production efficiency. Regression analysis is used to estimate the optimal land management scale under current productivity in China. Further, a decision graph has been drawn, which shows that the scale of big grain production households and comprehensive family farms is generally less than the optimal level, and an inverse relationship exists between farm size and productivity. Lastly, the suggestions that scattered land should be concentrated in the hands of big grain production households and family farms, and that land-lost farmers should work in their local agricultural industry, participating in the profit from land production are made.

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Considering Technical and Allocative Efficiency in the Inverse Farm Size–Productivity Relationship

Cited by 67 publications

References 40 publications

Participation in contract farming and farm performance: Insights from cashew farmers in Ghana

Participation in contract farming and farm performance: Insights from cashew farmers in Ghana

Heterogeneity in Production Structures and Efficiency: An Analysis of the Czech Food Processing Industry

Estimating the Optimal Land Management Scale of Big Grain Production Households and Comprehensive Family Farms Based on the Decision Graph

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