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.     

Non‐parametric Modelling of Spatial Price Relationships

We apply non‐parametric methods to a consideration of price transmission processes within US egg markets at the turn of the nineteenth century. Gordon (National Bureau of Economic Research Working Paper 7833, 2000) labelled this as an era of ‘Great Inventions’ which contributed to the subsequent years of significant productivity growth and noted that the development of mechanical refrigeration and transportation technologies played an important role in this growth. Our models present certain advantages relative to parametric models traditionally employed in price transmission analyses. We compare results derived from local polynomial modelling with those obtained using non‐linear threshold models. Both techniques suggest that US egg markets were interrelated at the turn of the nineteenth century. However, non‐parametric techniques often suggest a higher degree of price transmission than that implied by threshold models. Results also suggest that threshold models may have difficulties in adequately capturing price relationship dynamics, especially when these are of a highly nonlinear nature.     

Specialization,diversification, and productivity: a panel data analysis of rice farms in Korea

This article examines the microeconomics of productivity associated with specialization/diversification in production activities, with an application to Korean rice farms. Korean rice farms tend to be very small and highly specialized. Our analysis examines the productivity effects associated with both farm size and farm specialization/diversification in Korean agriculture. Relying on farm‐level panel data, the analysis studies farm productivity in a multi‐input multi‐output context, accounting not only for changes in inputs and technical change in rice production, but also for the role of diversification in the production of other crops in current and previous periods. We find positive but small productivity gains from farm diversification. These gains come mostly from complementarity effects across farm outputs, with minimal effect of scale economies. The positive complementarity effects work against nonconvexity effects, which provide strong productivity incentives for rice farms to specialize.     

Production Efficiency of Jasmine Rice Producers in Northern and North‐eastern Thailand

The paper jointly evaluates the determinants of switching to Jasmine rice and its productivity while allowing for production inefficiency at the level of individual producers. Model diagnostics reveal that serious selection bias exists, justifying use of a sample selection framework in stochastic frontier models. Results from the probit variety selection equation reveal that gross return (mainly powered by significantly higher Jasmine rice price), access to irrigation and education are the important determinants of choosing Jasmine rice. Results from the stochastic production frontier reveal that land, irrigation and fertilisers are the significant determinants of Jasmine rice productivity. Significantly lower productivity in Phitsanulok and Tung Gula Rong Hai provinces demonstrate the influence of biophysical and environmental factors on productivity performance. The mean level of technical efficiency is estimated at 0.63 suggesting that 59% [(100 ? 63)/63] of the productivity is lost due to technical inefficiency. Policy implications include measures to keep Jasmine rice price high, increase access to irrigation and fertiliser availability, as well as investment in education targeted to farm households which will synergistically increase adoption of Jasmine rice as well as farm productivity.     

Environmental Production Factors and Efficiency of Smallholder Agricultural Households: Using Non‐parametric Conditional Frontier Methods

External environmental factors play a significant role in the agricultural production of smallholder farmers. This is especially the case in developing countries where production is less technologically intensive. These factors are mainly exogenous and affect both the farmers’ input choices and the final output levels. However, previous studies of technical efficiency of smallholder agricultural production either ignore these factors or assume separability between environmental factors and input choice, which is often not the case in developing counties. Using data on smallholder farmers in Ethiopia, we relax this separability assumption and investigate the importance of external environmental factors in farmers’ performance and efficiency variation across regions. The empirical analysis is based on a non‐parametric conditional order‐m estimation method that relaxes some of the traditional strong assumptions in efficiency modeling and, more importantly, the separability between environmental factors and the choice of physical inputs. Using data from four major agricultural regions of Ethiopia, we show the extent that environmental factors contribute to the technical efficiency and the significance of environmental factors in farmers’ performance.     

Socioeconomic aspects of rice‐fish farming in Bangladesh: opportunities,challenges and production efficiency*

In spite of the potential for rice‐fish farming in Bangladesh, it has been adopted by relatively few farmers because of socioeconomic, environmental, technological and institutional constraints. Rice monoculture remains the main farming system in Bangladesh even though integrated rice‐fish farming is the best farming system in terms of resource utilisation, diversity, productivity, production efficiency and food supply. Only a small number of farmers involve in integrated rice‐fish farming. This study concludes that rice‐fish farming is as production efficient as rice monoculture and that integrated performs better in terms of cost and technical efficiency compared with alternate rice‐fish farming. Integrated rice‐fish farming can help Bangladesh keep pace with the current demand for food through rice and fish production. However, a lack of technical knowledge of farmers, high production costs and risks associated with flood and drought are inhibiting more widespread adoption of the practice.     

Is Input Mix Inefficiency Neglected in Agriculture? A Case Study of Pig‐based Farming Systems in England and Wales

The principal concern of this article is the relative importance of input mix as a source of inefficiency. Emphasis in efficiency analysis studies in agricultural production has historically focused on technical inefficiency as a single concept until methodological advances enabled it to be decomposed into pure technical inefficiency and scale inefficiency. But, this advance was insufficient to identify what we consider to be the major source of inefficiency in agricultural production, namely mix inefficiency. We consider that farm enterprises may be particularly susceptible to input mix inefficiency because of restrictions on movement around the frontier isoquant; delays in the adoption of improved technologies embodied in new vintages of production processes; risk as a source of friction in input allocation decisions; and the potential for inconsistency in simultaneously attempting to reach points of allocative efficiency and mix efficiency in input use. We use non‐parametric methods to calculate a Hicks–Moorsteen productivity index using panel data for a sample of specialised pig producers in England and Wales. This index is then decomposed into measures of technology, technical efficiency, scale efficiency and mix efficiency for an input orientation. Results of the analysis show that the estimated mean mix inefficiency (0.736) was substantially larger than mean technical inefficiency (0.975) and mean scale inefficiency (0.957) over the study period.     

Resource use efficiency under self‐selectivity: the case of Bangladeshi rice producers

The paper jointly evaluates the determinants of switching to modern rice and its productivity while allowing for production inefficiency at the level of individual producers. Model diagnostics reveal that serious selection bias exists, justifying the use of a sample selection framework in stochastic frontier models. Results revealed that modern variety selection decisions are influenced positively by the availability of irrigation and gross return from rice and negatively by a rise in the relative wage of labour. Adoption of modern rice is higher in underdeveloped regions. Seasonality and geography/location does matter in adoption decisions. Stochastic production frontier results reveal that land, labour and irrigation are the significant determinants of modern rice productivity. Decreasing returns to scale prevail in modern rice production. The mean level of technical efficiency (MTE) is estimated at 0.82. Results also demonstrate that the conventional stochastic frontier model significantly overestimates inefficiency by three points (MTE = 0.79). Policy implications include measures to increase access to irrigation, tenurial reform and keeping rice prices high to boost farm returns and offset the impact of a rise in the labour wage which will synergistically increase the adoption of modern rice as well as farm productivity.     

Modern Rice Technologies and Productivity in the Philippines: Disentangling Technology from Managerial Gaps

Using cross‐sectional farm‐level data from 3,164 rice‐farming households in the Philippines, we measure the impact of modern rice technologies on farm productivity while disentangling technology gaps (the distance between production frontiers) from managerial gaps (differences in technical efficiency). To do so, we combine a recently developed stochastic production frontier framework with impact evaluation techniques to control for biases stemming from observables and unobservables. First, we find an adequate control group using propensity score matching to mitigate the effect of biases from observable variables. Then, we test for biases that might arise from unobserved variables using a stochastic frontier framework corrected for self‐selection. Finally, we estimate meta‐frontiers to assess productivity differences between adopters and non‐adopters. The analysis shows that the adoption of certified seeds has a significant and positive impact on productivity, efficiency and net income in rice farming.     

Heterogeneity of Long‐run Technical Efficiency of German Dairy Farms: A Bayesian Approach*

In parametric efficiency studies, two alternative approaches exist to provide an estimate of the long‐run efficiency of firms: the dynamic stochastic frontier model and the generalised true random‐effects model. We extend the former in order to allow for heterogeneity in the long‐run technical efficiency of firms. This model is based on potential differences in firm‐specific characteristics and in firms’ inefficiency persistence. The model is applied to an unbalanced micro‐panel of German dairy farms over the period 1999 to 2009. Estimation of long‐run technical efficiency and inefficiency persistence is based on an output distance function representation of the production technology and estimated in a Bayesian framework. The results suggest that heterogeneity in long‐run technical efficiency of farms is mostly attributed to discrepancies in farm‐specific factors rather than differences in farms’ inefficiency persistence. Farm size is positively related to long‐run technical efficiency while subsidies exert a negative effect on the long‐run technical efficiency of farms. Inefficiency persistence is found to be very high, but heterogeneity in this persistence is low.     

Challenging Small‐Scale Farming: A Non‐Parametric Analysis of the (Inverse) Relationship Between Farm Productivity and Farm Size in Burundi

We use a non‐parametric approach to investigate the (inverse) relationship between farm productivity and farm size. A kernel regression is used on data of mixed cropping systems to study the determinants of production including different factors that have been identified in literature as missing variables in the testing of the inverse relationship such as soil quality, location and household heterogeneity. Household data on farm activities and crop production were gathered from 640 households in 2007 in two Northern provinces of Burundi. Our results do not reject the findings of an inverse relationship between farm size and productivity. However, we find that size returns vary substantially with farm size, that is, between 0.2 for the smallest farms and 0.8 for the largest farms. Other factors that significantly affect production include soil quality. Finally, we find a significant positive association between food security and farm size.     

Off‐farm work,technical efficiency,and rice production risk in Taiwan

This article investigates the differences in yield production, production efficiency, and yield risk for farmers both with and without off‐farm work. Using a nationwide survey of rice farmers in Taiwan, we estimate two stochastic production frontier models that accommodate technical inefficiency and production risk simultaneously for farmers both with and without off‐farm work. The stochastic dominance criterion is then applied to compare the differences in the distributions of the estimated technical efficiency and yield risk between groups. The empirical results indicate that these two groups of farmers use resources in different ways, and off‐farm work is not necessarily associated with lower technical efficiency. For farmers in the lower percentiles of the efficiency distribution, those with off‐farm work are more efficient than their counterparts without off‐farm work. In addition, farmers with off‐farm work face higher production risk and this result is robust for the entire distribution.     

Sense and sustainability revisited: the limits of total factor productivity measures of sustainable agricultural systems

Many economists have advocated and applied total social factor productivity (TSFP) (i.e., total factor productivity estimated with both market and non‐market inputs and externalities, and with all factors valued at social prices) as a single all‐embracing measure of agricultural sustainability. This paper reviews the conceptual and practical issues in measuring TSFP and shows that no one measure alone will be theoretically or empirically robust as an indicator of sustainability. TSFP is a conceptually flawed measure since inclusion of non‐market inputs and outputs and social price‐based valuation, in most cases, violates the theoretical basis underlying those estimates. Trends in TSFP also have limited value in diagnosing the nature of sustainability problems, unless changes in productivity are related to underlying changes in technology, human and physical infrastructure, and indicators of resource quality. More attention needs to be given to defining key indicators of agro‐ecosystem health and relating these measures to trends in productivity. This analysis must be sufficiently disaggregated and for a long enough time period to allow for spatial and temporal variability inherent in agricultural production. Secondary data at the district level on both conventional inputs and outputs and resource quality have recently allowed more quantitative estimates of sustainability and its causes. With limited data, yield growth decomposition analysis can often be used to provide valuable insights into sustainability problems. Meanwhile, there is a need to invest in long‐term experimental and panel surveys of farmers and their fields for key production systems in order to provide long‐term data that will allow full productivity accounting, using more formal statistical procedures. Regardless of the approach selected, the findings of this paper strongly suggest a need for economists, agronomists and soil scientists to collaborate in integrating approaches in order to provide more robust and informative measures of sustainability.     

Impact of land fragmentation and resource ownership on productivity and efficiency: The case of rice producers in Bangladesh

The paper analyzes the impact of land fragmentation and ownership of resources on productivity and technical efficiency in rice production in Bangladesh using farm level survey data. Results reveal that land fragmentation has a significant detrimental effect on productivity and efficiency as expected. The elasticity estimates of land fragmentation reveal that a 1% increase in land fragmentation reduces rice output by 0.05% and efficiency by 0.03%. On the other hand, ownership of key resources (land, family labour, and draft animals) significantly increases efficiency. The mean elasticity estimates reveal that a 1% increase in family labour and owned draft animal improve technical efficiency by 0.04% and 0.03%, respectively. Also, a 1% increase in the adoption of modern technology improves efficiency by 0.04%. The mean technical efficiency in rice production is estimated at 0.91 indicating little scope to improve rice production per se using existing varieties. Policy implications include addressing structural causes of land fragmentation (e.g., law of inheritance and political economy of agrarian structure), building of physical capital (e.g., land and livestock resources), improvements in extension services and adoption of modern rice technology.     

Women’s Labour Contribution to Productivity and Efficiency in Agriculture: Empirical Evidence From Bangladesh

This article examines the contribution of women’s labour input to productivity and efficiency in crop farming using a large survey dataset of 1,839 households from 16 villages in two agro‐ecological regions of Bangladesh. Results reveal that female labour accounts for a substantial 28% of total labour use (mainly supplied from the family) and contributes significantly to productivity as well as technical efficiency. Contrary to expectation, the cost share of female labour input is significantly higher than the male share, and has a substitution relationship with all other inputs, including male labour. The estimated mean level of technical efficiency is 0.90, implying that crop output might be increased by 10% by eliminating technical inefficiency. Both male and female education have a significant impact on improving technical efficiency. Other significant technical efficiency shifters are farming experience, family size and crop diversification. Owner operators are found to be technically inefficient relative to the tenants. Policy implications include creation of a hired labour market for female labour so that more women can be involved in the production process, and can contribute to towards improving productivity and efficiency. In addition, investment in education for both men and women, strategies to promote crop diversification and effective regulation/modification of the tenancy market will significantly improve technical efficiency in this case.     

Measuring and decomposing agricultural productivity and profitability change*

Profitability change can be decomposed into the product of a total factor productivity (TFP) index and an index measuring changes in relative prices. Many TFP indexes can be further decomposed into measures of technical change, technical efficiency change, scale efficiency change and mix efficiency change. The class of indexes that can be decomposed in this way includes the Fisher, Törnqvist and Hicks–Moorsteen TFP indexes but not the Malmquist TFP index of Caves, Christensen and Diewert (1982). This paper develops data envelopment analysis methodology for computing and decomposing the Hicks–Moorsteen index. The empirical feasibility of the methodology is demonstrated using country‐level agricultural data covering the period 1970–2001. The paper explains why relatively small countries tend to be the most productive, and why favourable movements in relative prices tend to simultaneously increase net returns and decrease productivity. Australia appears to have experienced this relative price effect since at least 1970. Thus, if Australia is a price‐taker in output and input markets, Australian agricultural policy‐makers should not be overly concerned about the estimated 15 per cent decline in agricultural productivity that has taken place over the last three decades.     

Tenure Security and Farm Efficiency Analysis Correcting for Biases from Observed and Unobserved Variables: Evidence from Benin

We analyse the impact of land tenure security on the technical efficiency of a sample of smallholder farmers in Benin, based on an output‐oriented stochastic distance function. We use propensity score matching to correct for selection bias from observed variables. The Greene ( 2010 ) sample selection model is used to correct for selection bias due to unobserved variables. We estimate meta‐frontiers to analyse agricultural productivity and efficiency differences between landowners and non‐owners. Our results show that non‐owners have consistently higher levels of technical efficiency and productivity.     

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.     

Productivity growth and inter-sector spill-over in Dutch horticulture, 1976–1995

This article calculates nonparametric measures of total factor productivity growth on Dutch horticultural firms in the period 1976–1995. Individual components of total factor productivity growth, i.e., efficiency change and technical change are regressed on socioeconomic factors reflecting the effects of the world oil crises, household and demographic characteristics, location, and investment in physical capital. Also, the article investigates the presence of inter‐sector spill‐overs between groups of firms with different specializations in Dutch horticulture.     

Sources and Measurement of Agricultural Productivity and Efficiency in Canadian Provinces: Crops and Livestock

This paper measures and assesses the variation in total factor productivity (TFP) growth among Canadian provinces in crops and livestock production over the period 1940–2009. It also determines if agricultural productivity growth in Canada has recently slowed down as indicated by earlier studies. The paper uses the stochastic frontier approach that incorporates inefficiency to decompose TFP growth into technical change (TC), scale effect (SE), and technical efficiency change. The results indicate that productivity changes were mainly driven by TCs for crops, while the productivity changes in livestock was mainly driven by SEs and technical progress. Though change in technical efficiency is mainly positive (except for New Brunswick and Nova Scotia), its contribution to productivity growth was very little for the provinces. We also found that over the entire period, the productivity growth rates for the crop subsector are on average higher for the Prairie provinces than for the Eastern and Atlantic provinces. On the other hand, the productivity growth rates in the livestock subsector are on average higher in the Eastern and Atlantic provinces than in the Prairie region with the exception of Manitoba. Finally, we found that though there is some evidence of a recent decline in productivity growth for the crops subsector, there is no such evidence in the livestock subsector.