Farm productivity in Rwanda: effects of farm size,erosion, and soil conservation investments

This paper examines the effects of farm size, soil erosion, and soil conservation investments on land and labor productivity and allocative efficiency in Rwanda. There were several key results. First, there is a strong inverse relationship between farm size and land productivity, and the opposite for labor productivity. For smaller farms, there is evidence of allocative inefficiency in use of land and labor, probably due to factor market access constraints. Second, farms with greater investment in soil conservation have much better land productivity than average. Those with very eroded soils do much worse than average. Smaller farms are not more eroded than larger farms, but have twice the soil conservation investments. Third, land productivity benefits substantially from perennial cash crops, and the gains to shifting to cash crops are highest for those with low erosion and high use of fertilizer and organic matter. Program and policy effort to encourage and enable farmers to make soil conservation investments, to use fertilizer and organic matter, and to participate in cash cropping of perennials will have big payoffs in productivity. Land markets that allow smaller farmers to buy land could also increase aggregate productivity.     

Transition and agricultural labor

Reforms have strongly affected agricultural employment in transition countries but in remarkably different ways. We present a theoretical model and an empirical analysis to explain differences in labor adjustment during transition. We show that the differences are due to a combination of variations in initial conditions and differences in reform policies and effects. The removal of price distortions and subsidies caused wage and price adjustments during transition and a reduction in labor demand in agriculture. Surplus labor outflow from agriculture was further stimulated by the privatization of the farm assets as they improve incentives and remove constraints for optimal factor allocation and structural adjustment. The shift to individual farms, which was especially strong in labor‐intensive production systems with low labor productivity in agriculture, has reduced the outflow of labor from agriculture by improving farm governance and labor efficiency, although this effect was mitigated by losses in scale economies due to disruptions and market imperfections in transition. In general, labor outflow was considerably lower on individual farms than on corporate farms, due to a combination of factors related to human capital, access to finance, and physical capital. In the last section of the article we present a general framework for understanding labor adjustments in transition countries. Specifically, we show that there are several patterns of labor transition. In one pattern, followed by, e.g., the Czech Republic and Hungary, there is initially a strong survival of the restructured large‐scale corporate farms that have laid off many workers. In the second phase of transition, gradually the importance of individual farms increases. In other countries, such as Romania, the opposite has happened. In these countries there is an immediate strong shift to individual farms, while labor use increases on average in agriculture. After this initial phase, the shift to individual farms continues, albeit more slowly, and labor use in agriculture starts to decline. Finally, our analysis shows that in countries such as Russia and Ukraine much of the surplus labor is still employed by little‐reformed former collective and state farms. Major adjustments await more progress in agricultural and general reforms.     

Exploring Farm Investment Behaviour in Transition: The Case of Russian Agriculture

This paper analyses the investment behaviour of Russian farms during the period of economic stabilisation that followed Russia’s financial crisis of 1998, and is the first to apply the error‐correction investment model to describe farms’ investment behaviour in the transitional context. Additionally, the paper employs the error‐correction and the adjustment‐cost model to test for differences in the investment behaviour between various farm categories. The results show that in general Russian farms exhibited an error‐correcting behaviour in the period under investigation. From 1999 to 2005 the output–capital gap was closed by an average rate of 10% per year. Estimates of the adjustment‐cost model show that Russian farm investments are very sensitive to the sales–capital ratio, suggesting that Russian farms exhibit increasing returns to scale and positive expectations about future revenues. Yet, such farm characteristics as ownership structure, access to input markets and also regional specifics were found to be decisive for farm investment not only in the short but long term too. Finally, the results show that the adjustment‐cost model is adequate for the evaluation of differences in short‐term investment behaviour, whereas it is noticeably less powerful for investigating differences in the farms’ long‐term investment behaviour.     

Efficiency estimation in a profit maximising model using flexible production function

This paper uses a flexible (translog) production function to estimate efficiency of 227 farms from West Bengal, India. We consider estimation of technical and allocative inefficiencies using a profit maximising framework which accommodates both endogenous and exogenous inputs. The maximum likelihood method of estimation developed in this paper is based on the production function and the first-order conditions of profit maximisation. Farm-specific technical and allocative inefficiencies are also estimated. Empirical results show that the mean level of technical efficiency is 75.46% while the best farm is 85.87% efficient (technically). So far as allocative efficiency is concerned the majority of the farms are found to be under-users of the endogenous inputs, viz., fertiliser, manure, human and bullock labour.     

Technical,Allocative, Cost and Scale Efficiencies in Bangladesh Rice Cultivation: A Non‐parametric Approach

Applying programming techniques to detailed data for 406 rice farms in 21 villages, for 1997, produces inefficiency measures, which differ substantially from the results of simple yield and unit cost measures. For the Boro (dry) season, mean technical efficiency was 69.4 per cent, allocative efficiency was 81.3 per cent, cost efficiency was 56.2 per cent and scale efficiency 94.9 per cent. The Aman (wet) season results are similar, but a few points lower. Allocative inefficiency is due to overuse of labour, suggesting population pressure, and of fertiliser, where recommended rates may warrant revision. Second‐stage regressions show that large families are more inefficient, whereas farmers with better access to input markets, and those who do less off‐farm work, tend to be more efficient. The information on the sources of inter‐farm performance differentials could be used by the extension agents to help inefficient farmers. There is little excuse for such sub‐optimal use of survey data, which are often collected at substantial costs.     

The allocative efficiency and conservation potential of water laws encouraging investments in on-farm irrigation technology

Agricultural water conservation statutes are emerging in the West encouraging private irrigators to improve on‐farm irrigation efficiency as a basinwide conservation measure. We investigate whether private improvements promote the economic efficiency and conservation of water use basinwide under a wide variety of hydroeconomic circumstances. The standard of efficiency is how an irrigation district manager should optimally invest in improving the irrigation efficiencies of individual farms located along a stream while internalizing intrabasin allocative externalities of these investments. The results indicate that the popular Oregon legislative model may be the least effective in conserving water and promoting economically efficient water allocation.     

Effects of machinery‐sharing arrangements on farm efficiency: evidence from Sweden

The effects of partnerships, in the form of machinery‐sharing arrangements, on farm efficiency are analyzed using data for Swedish crop and livestock farms. Efficiency scores are obtained using Data Envelopment Analysis and the findings suggest that efficiency is, on average, higher among partnership farms compared to nonpartnership farms. Moreover, partnership farms that are characterized by the most extensive form of collaboration, that is, that share all machinery with one or several other farms, display the highest average efficiency. In a two‐stage procedure in which efficiency determinants are analyzed in the second stage, the bootstrap procedures suggested by Simar and Wilson (2007) are applied in addition to the conventionally used Tobit regression. Participation in partnership arrangements is found to have a positive and statistically significant impact on farm efficiency.     

Feed use intensification and technical efficiency of dairy farms in New Zealand

In recent years, the traditionally pasture‐based dairy farms in New Zealand have become more intensive by using higher proportions of supplementary feed. This trend has been attributed to a range of factors, such as productivity enhancement, overcoming pasture deficits and the improvement of body condition scores. However, there is a lack of knowledge as to how feed use intensification affects the technical efficiency of dairy farms in New Zealand. This paper addresses the research gap by estimating the impact of feed use intensification on the technical efficiency of New Zealand dairy farms, using a fixed effects stochastic production frontier model and a balanced panel of 257 farms from 2010 to 2013. The empirical results show that technical efficiency on New Zealand dairy farms is positively and significantly influenced by feed use intensification, herd size and milking frequency.     

The extent of resource use inefficiencies in cotton production in Pakistan's Punjab: an application of Data Envelopment Analysis

This paper attempts to identify sources of resource use inefficiency for cotton production in Pakistan's Punjab. The use of a non‐parametric method, Data Envelopment Analysis (DEA), is developed to study the relative technical and allocative efficiencies of individual farms which use similar inputs, produce the same product and operate under comparable circumstances. In the ‘cotton‐wheat’ system of Pakistan, there are a considerable number of farms that are both technically and allocatively inefficient. The use of DEA shows that the technique provides a clear identification of both the extent and the sources of technical and allocative inefficiencies in cotton production. However, both the interpretation of the farm level results generated and the projection of these results to a higher level require care, given the technical nature of the agricultural production processes.     

Farm size,relative efficiency and agrarian policy in Côte d'Ivoire: profit function analysis of rice farms

This paper examines the relative economic efficiency of small and large rice farms in Côte d'Ivoire using a profit function approach. No differences in the relative economic efficiency of small and large farms were found. This conclusion is robust under alternative model specifications. Agrarian reforms directed towards further concentration of landholding for large farms in Côte d'Ivoire cannot be justified based on economic efficiency. Results show that access to credit and use of modern rice varieties significantly increase profits. To improve technical efficiency of rice farms, an accelerated program to provide information, credit, improved seeds and other inputs is needed. When all the farms (i.e. large and small) are taken together, there is evidence of allocative inefficiency. Strategies are needed to remove such management related inefficiencies in rice production either through the development of a better market price information system or effective farmer-oriented technical training programs by rice extension workers.     

Are farms in less favored areas less efficient?

This article investigates farm technical efficiency (TE) and the effect of heterogeneity on production among farms using the Slovenian Farm Accountancy Data Network sample of farms in the period 2007–2013. We model production technology with a random parameter model that allows us to examine both the direct effect of heterogeneity on production and the indirect effect through the interaction of unobserved heterogeneity with time and input variables. Additionally, we consider intersectoral heterogeneity among types of farming. Results confirm the importance of all these sources of heterogeneity. The second contribution of the article is that, in addition to using conventional statistical methods, we examine the differences between less favored area (LFA) and non‐LFA farms using matching techniques. Results indicate that there is only a minor and statistically nonsignificant difference in TE between these groups. However, the difference is highly significant in terms of heterogeneity and technology. In other words, results show that farms in LFAs are not more inefficient but rather use different, production–environment‐specific technologies. These findings call attention to the fact that omitting the effect of heterogeneity on production technology leads to biased TE estimates and, in turn, leads to potentially imperfect policy choices.     

Effects of management information from FADN on profitability of Dutch potted-plant firms

The Dutch Farm Accountancy Data Network (FADN) provides managerial reports to participants of the network. This article analyzes the impact of this type of management information on the profitability of agricultural producers. A dual system of input demand and output supply equations is applied to measure the effect of management information. The approach is applied to a panel data set of Dutch potted‐plant firms over the period of 1975–1995. Management information provided by the FADN resulted in savings in materials and services and a more intensive use of energy. Shadow prices of structure, machinery, and labor increased as a result of management information. The results show that management information is more likely to have a positive effect on profitability of potted‐plant firms in the long run than in the short run. The results suggest that the availability of management information allows firms to operate on a larger scale in the long run.     

Examining the relationship between farm size and productive efficiency: a Bayesian directional distance function approach

Achieving sustainable food security and increased farm income will depend on how efficient production systems are in converting available inputs to produce outputs. Using data from Malawi, we estimate a Bayesian directional technology distance function to examine the relationship between farm size and technical efficiency. Our results support the existence of an inverse relationship between farm size and productive efficiency, where small farms are more efficient than large farms. On average, farms exhibit inefficiency levels of 60%, suggesting that productivity could be improved substantially. Improving productive efficiency and food security will require farms to operate in ways where the size of cultivated area is matched by nonland production inputs such as labor, fertilizer, and improved seeds. The results highlight the need for policies that could incentivize farmers to adopt productivity‐enhancing technologies and, where possible, to allocate excess land to lease markets.     

Estimation of Profit Functions When Profit is Not Maximum

This paper deals with derivation and implications of profit functions when profit is not maximum due to the presence of either technical inefficiency or allocative inefficiency, or both. We show that input demand and output supply, elasticities, and returns to scale are, in general, affected by these inefficiencies. We also show that the overall profit efficiency is not necessarily the product of technical and allocative efficiencies, meaning that technical and allocative inefficiencies are not necessarily independent. Estimation techniques are developed for both cross-sectional and panel data models. Working of the model is illustrated using a panel of 60 salmon farms.     

Outsourcing and efficiency: the case of Spanish citrus farming

Outsourcing in agriculture has traditionally been seen as a managerial strategy of smaller farms to achieve higher levels of efficiency. In this article, we provide empirical evidence supporting the existence of a positive relationship between outsourcing and efficiency in Spanish citrus farming. Outsourcing is measured by the proportion of outsourced labor and capital in farms' total use of these production factors, i.e., the higher the proportion of outsourced inputs, the higher the degree of outsourcing. Making use of data envelopment analysis techniques, we compute input‐specific reductions required to achieve technical efficiency at the farm level. Our results show that attainment of technical efficiency leads to a reduction in the use of both farms' own and outsourced production factors. Furthermore, the degree of outsourcing increases as farms move to their technically efficient productive plans. In addition, outsourcing labor and capital allows farms to achieve efficiency regardless of their size. In our view, this result has a clear implication for policy makers. Instead of trying to improve Spanish citrus farms' competitiveness by pursuing an increase of their average size, policy measures should be adopted to enhance farmers' managerial skills and the efficiency of those external service firms and co‐operatives that are effectively performing basic cultivation tasks.     

住宅投资、要素结构与配置效率——基于北京市各区县的实证研究

研究目的:估算各类资本存量、生产函数要素弹性系数和要素边际报酬率,实证研究住宅价格及其资本存量的内涵型和外延型资源配置机制,考察它们对要素配置效率和全要素生产率扭曲程度的影响。研究方法:理论模型法,面板校正标准误法(PCSE)。研究结果:(1)住宅开发主要通过投资而非价格产生影响,抵押担保效应、要素挤出效应和技术创新效应很显著,其他效应不显著;(2)住宅资本存量对要素配置效率和全要素生产率扭曲的影响也显著,而住宅价格的影响面和显著性都较低。研究结论:住宅资本存量比住宅价格的资源配置效应更强,都恶化了非住宅业资源配置扭曲度。因此,要盘活存量、优化增量和管好总量,完善住宅调控基础性制度安排,科学测度和控制住宅价格及增速。     

Production risk,risk aversion and the determination of risk attitudes among Spanish rice producers

Agricultural production is subject to risk and the attitudes of producers toward risk will influence input choices insofar as these affect production risk. Risk attitudes in turn may be affected by certain socioeconomic characteristics of producers. Using 2004 survey data from a cross‐section of 130 Spanish rice farms, we estimate risk‐aversion coefficients of farmers and investigate the influence of a series of socioeconomic variables on their risk attitudes. Our results show that farmers exhibit risk‐averse behavior and that risk attitudes are related to a series of socioeconomic characteristics. In particular, the belief that the farm will continue after the producer retires is found to increase the degree of risk aversion, while age is found to have nonlinear effects on risk aversion. Off‐farm income, especially from nonagricultural activities, is found to reduce risk aversion. Neither the educational level of the producer nor the presence of dependents on the household is found to have an effect on risk preferences. Regarding the production technology, we find that land, labor, and fitosanitary products are risk‐reducing inputs, whereas capital, seeds, and fertilizer all increase risk.     

Technical,allocative and economic efficiencies in swine production in Hawaii: a comparison of parametric and nonparametric approaches

Technical, allocative and economic efficiency measures arc derived for a sample of swine producers in Hawaii using the parametric stochastic efficiency decomposition technique and nonparametric data envelopment analysis (DEA). Efficiency measures obtained from the two frontiei approaches are compared. Firm-specific factors affecting productive efficiencies are also analyzed. Finally, swine producers, potential for reducing cost through improved efficiency is also examined. Under the specification of variable returns to scale (VRS), the mean technical, allocative and economic efficiency indices are 75.9%, 75.8% and 57.1%, respectively, for the parametric approach and 75.9%, 80.3% and 60.3% for DEA; while for the constant returns to scale (CRS) they are 74.5%, 73.9% and 54.7%, respectively, for the parametric approach and 64.3%, 71.4% and 45.7% for DEA. Thus the results from both approaches reveal considerable inefficiencies in swine production in Hawaii. The removal of potential outliers increases the technical efficiencies in the parametric approach anil allocative efficiencies in DEA, but, overall, contrary to popular belief, the results obtained from DEA are found to be more robust than those from the parametric approach. The estimated mean technical and economic efficiencies obtained from the parametric technique are higher than those from DEA for CRS models but quite similar for VRS models, while allocative efficiencies are generally higher in DEA. However, the efficiency rankings of the sample producers based on the two approaches are highly correlated, with the highest correlation being achieved for the technical efficiency rankings under CRS. Based on mean comparison and rank correlation analyses, the return to scale assumption is found to be crucial in assessing the similarities or differences in efficiency measures obtained from the two approaches. Analysis of the role of various firm-specific factors on productive efficiency shows that farm size has strong positive effects on efficiency levels. Similarly, farms producing market hogs arc-more efficient than those producing feeder pigs. Based on these results, by operating at the efficient frontier the sample swine producers would be able to reduce their production costs by 38-46% depending upon the method and returns to scale considered.     

Firm behaviour under uncertainty: a simple parametric model

In this paper, we model production technology in a state‐contingent framework. We assume that all the firms use the same stochastic technology, but they may have different risk attitudes and information sets, and ex post they may operate in different production environments. Firms maximise ex ante their preference function subject to a stochastic technology constraint; in other words, they are assumed to act rationally, thereby leaving no room for either technical or allocative inefficiency. We provide a simple parametric functional form to represent the state‐contingent technology. Using simple numerical examples, we illustrate how optimal input–output choices are dramatically affected when firms have different preferences and information sets. Thus, we show that the observed disparateness of production choices among different firms can actually be attributed to the stochastic nature of the decision environment.