Impact of off‐farm income on food expenditures in rural Bangladesh: an unconditional quantile regression approach

This study examines the effects of off‐farm income on food expenditures of rural Bangladeshi households. Our analysis yields unbiased estimates of the unconditional impact of off‐farm income on food expenditures and reveals the heterogeneous effects that occur across the distribution of total food consumption expenditures. The findings suggest that the impacts of off‐farm income are uniformly positive across the unconditional quantile regression and significantly increase food consumption expenditures for all quantiles, except for the 25th quantile. In addition, we found that schooling, experience, and location of the household increase the food expenditures of rural households. Most importantly, this article argues that female‐headed rural households in which the female works off the farm tend to have significantly lower food expenditures.     

Estimating multiproduct and product‐specific scale economies for agricultural cooperatives

This article estimates multiproduct and product‐specific scale economies, scope economies, and cost efficiency with single and annual cost frontiers using a nonparametric approach. Multiproduct scale and scope economies are found that suggests increasing scale and product diversification can reduce cost for agricultural cooperatives. Many agricultural cooperatives experience economies of scale indicating that variable returns to scale as opposed to constant returns to scale is the appropriate technology for modeling agricultural cooperatives. Product‐specific scale economies for all outputs are close to one indicating that individual outputs are operating close to constant returns to scale. Annual frontier estimates show that cooperatives have become less cost efficient over time, but scale and scope economies remain relatively consistent across years. Further, results show that economic measures obtained from the single frontier are statistically different from those measures calculated from annual frontiers, suggesting that the cost frontier has shifted over time. The trade‐off between cost efficiency and multiproduct scale economies indicates that smaller cooperatives can reduce a higher percentage of cost by increasing the scale of operations rather than just becoming cost efficient. Because larger incentives exist for small cooperatives to increase scale, mergers will likely continue until economies of scale are exhausted in the industry.     

Does the estimated impact of wildfires vary with the housing price distribution? A quantile regression approach

Hedonic property models are commonly applied in the environmental economics literature to estimate values of environmental amenities or hazards. Most hedonic property models are estimated using linear regression techniques where the coefficient on the environmental variable of interest is the “marginal implicit price.” Linear regression estimates one coefficient for the entire distribution of the dependent variable, and thus in hedonic property models a single marginal implicit price. In contrast, quantile regression estimates a range of marginal impacts for different quantiles of the distribution for the dependent variable, consequently providing a significantly more “complete picture” of the true impact of the explanatory variable (Koeneker and Hallock, 2001). We contribute to the existing hedonic property literature by estimating the impact of repeated wildfires on house prices in Southern California using quantile regression. We find that the impact of a wildfire differs significantly across the distribution of house prices, with estimated coefficients varying as much as 73% from the 25th quantile relative to the 75th quantile. We also find that OLS results under-estimate impacts relative to the median quantile, yet over-estimate impacts for lower quantiles. Our results indicate that a quantile regression approach can provide policymakers and researchers more information about the marginal implicit price in hedonic models as it relates to the distribution of the dependent variable.     

State‐contingent analysis of farmers’ response to weather variability: irrigated dairy farming in the Murray Valley,Australia

The agricultural sector is commonly regarded as one of the most vulnerable to climate change. Current understanding of the impact of climate change on this sector relies on the underlying assumptions about farmers’ possible responses to weather variability, including changes in crop choice, input combinations and land management practices. Many previous analyses rely on the implicit (and restrictive) assumption that farmers operate under a fixed technology set across different states of nature. This assumption, represented through stochastic production or profit functions, is commonly made but seldom tested and may understate farmers’ responses to climate change if state‐contingent production technologies are, in reality, more flexible. The potential for farmers to adapt production technologies in response to unforeseen events is at the core of the state‐contingent approach. Advanced in Chambers and Quiggin (2000), the theory contends that producers can manage uncertainty through the allocation of productive inputs to different states of nature. In this article, we test the assumption that farmers’ observed behaviour is consistent with the state‐contingent production theory using farm‐level data from Australia. More precisely, we estimate the milk production technology for a sample of irrigated dairy farms from the southern Murray–Darling Basin over the period from 2006–2007 to 2009–2010.     

A Quantile Regression Analysis of the Effect of Farmers’ Attitudes and Perceptions on Market Participation

The objective of this study is to investigate the subjective determinants of farmers’ participation in output markets in five EU New Member States (NMS) characterised by large semi‐subsistence sectors. It employs quantile regression to model market participation reflecting the heterogeneity amongst farmers. The study also uses the Bayesian adaptive lasso to simultaneously select important covariates and estimate the corresponding quantile regression models. The empirical results show that only two variables affect all quantiles, while their effect varies across quantiles. Some of the remaining variables affect the share of output sold at the lower quantiles (i.e. for subsistence‐ and semi‐subsistence‐oriented farmers) only, whereas other variables are only significant at the upper quantiles (i.e. for more commercially oriented farms). Advisory services, and particularly agricultural business advice, and information and advice on markets and prices can facilitate the market participation of subsistence‐oriented farms.     

Estimating product‐specific and multiproduct economies of scale with data envelopment analysis

Nonparametric cost frontier estimation and subsequent analysis of the relative efficiency of firms has historically been conducted without critically examining the shape of the cost frontier. The shape of the cost frontier has been examined using additional parametric estimation methods to recover potential cost savings from multiproduct and product‐specific economies of scale. This paper presents and tests an approach to estimate multiproduct and product‐specific economies of scale using data envelopment analysis. Data for the study are simulated assuming an underlying production technology. Nonparametric estimates of efficiency, multiproduct scale, product specific scale, and scope economies are compared to those of the assumed production technology. Results show that the nonparametric approach accurately estimates multiproduct economies of scale and product‐specific economies of scale under alternative inefficiency distributional assumptions.     

Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach

The pig meat production plays a significant role in the Spanish agrofood system. The assessment of the efficiency performance with which farmers are operating is necessary to define adequate policy and management strategies. In this context, this study aimed to determine the technical efficiency (TE) performance of pig farms and to examine the key factors that may affect the production system in Spain. To do so, the analysis relies on the quantile stochastic frontier model using a sample of Spanish pig farms. Results show a significant difference between production frontier parameters across the selected quantiles, which support the relevance of using the quantile regression approach. The optimal quantile for the stochastic frontier indicates an average TE level of 75%. In addition, empirical findings suggest that pig farmers in Spain give more importance to the adoption of high technology to improve their economic and technical performance as well as their competitiveness at the European pig market.     

Distributional heterogeneity in climate change impacts and adaptation: Evidence from Indian agriculture

This study estimates the distributional heterogeneity in the effects of climate change on yields of three major cereal crops: rice, maize, and wheat in India using district-level information for the period 1966–2015. We distinguish between the effects of changes in growing season weather from those due to changes in long-term climate trends and the heterogeneity in these effects across the distribution of crop yields by estimating naïve and climate penalty inclusive models using fixed-effect quantile panel models. We observe an absence of adaptation against rising temperatures for rice and wheat. However, we find a statistically significant presence of adaptation for wheat and maize for changes in precipitation, though the magnitude is small. Moreover, we find that the effects are asymmetric, and are larger at the lower tail of productivity distribution and smaller at the upper tail of the distribution. A 1°C increase in temperature lowers rice and wheat productivity by 23% and 9%, respectively at the first quantile, but the damage is only 6% and 5% at the ninth quantile. Heterogeneity in impacts and adaptation estimates over the yield distribution curve and across crops suggests the importance of customizing strategies for adaptation to changing weather and climate conditions across regions, crops, and current productivity levels.     

Extreme Measures of Agricultural Financial Risk

The agricultural marketing environment is inherently risky. Having accurate measures of risk helps farmers, policy‐makers and financial institutions make better informed decisions about how to deal with this risk. This article examines three tail quantile‐based risk measures applied to the estimation of extreme agricultural financial risk for corn and soybean production in the US: Value at Risk, Expected Shortfall and Spectral Risk Measures. We use Extreme Value Theory to model the tail returns and present results for these three different risk measures using agricultural futures market returns data. We compare estimated risk measures in terms of size and precision, and find that they are all considerably higher than Gaussian estimates. The estimated risk measures are also quite imprecise, and become more so as the risks involved become more extreme.     

Productivity and farm size in Australian agriculture: reinvestigating the returns to scale

A positive relationship between farm size and farm productivity is often considered to be largely due to increasing returns to scale in farm production. However, using farm‐level data for the Australian broadacre industry, we found that constant or mildly decreasing returns to scale is the more typical scenario. In this study, the marginal returns to various farm inputs are compared across farms with different sizes. We found that large farms achieved higher productivity by changing production technology rather than increasing scale alone. The results highlight the disparity between ‘returns to scale’ and ‘returns to size’ in the industry, suggesting that productivity improvement among smaller farms can be made through increasing their ability to access advanced technologies, rather than simply expanding their scale.     

Scale Economies,Technical Efficiency,and the Sources of Total Factor Productivity Growth of Quebec Dairy Farms

Canada's average cost for milk production is among the highest in the world. This paper focuses on specific potential causes by estimating economies of scale and technical efficiency for a panel of Quebec dairy farms that spans the 2001–10 period. Additionally, this paper investigates the sources of total factor productivity growth. The stochastic frontier analysis, based on an input‐distance function, is used to estimate returns to scale relationships across dairy farms. The results show that there is significant economies scale to be exploited and that cost of production could also be reduced by improving technical efficiency. Accordingly, the paper indicates that input‐mix effect is the main source of total factor productivity growth. The results have important implications for Canada's supply management policy, and more specifically for the trading of production quota between dairy farmers, as well as for the delivery of targeted extension services.     

Empirical properties of duality theory

This research examines selected empirical properties of duality relationships. Monte Carlo experiments indicate that Hessian matrices estimated from the normalised unrestricted profit, restricted profit and production functions yield conflicting results in the presence of measurement error and low relative price variability. In particular, small amounts of measurement error in quantity variables can translate into large errors in uncompensated estimates calculated via restricted and unrestricted profit and production functions. These results emphasise the need for high quality data when estimating empirical models in order to accurately determine dual relationships implied by economic theory.     

Small U.S. dairy farms: can they compete?

The U.S. dairy industry is undergoing rapid structural change, evolving from a structure including many small farmers in the Upper Midwest and Northeast to one that includes very large farms in new production regions. Small farms are struggling to retain competitiveness via improved management and low‐input systems. Using data from USDA's Agricultural Resource Management Survey, we determine the extent of U.S. conventional and pasture‐based milk production during 2003–2007, and estimate net returns, scale efficiency, and technical efficiency associated with the systems across different operation sizes. We compare the financial performance of small conventional and pasture‐based producers with one another and with large‐scale producers. A stochastic production frontier is used to analyze performance over the period for conventional and pasture technologies identified using a binomial logit model. Large conventional farms generally outperformed smaller farms using most economic measures—technical efficiency, various profitability measures, and returns to scale.     

On the Function Coefficient, Euler's Theorem, and Homogeneity in Production Theory

This paper makes three related points useful in teaching first-year graduate production theory. First, the local applicability of the classical function coefficient idea for short-run nonhomogeneous production technologies is shown for returns to scale, satisfaction of second-order and total conditions for profit maximization, and delineation of the economic region of production in factor space. Second, the general applicability of Euler's Theorem results to nonhomogeneous (variable-proportional-return) cases is developed. Lastly, it is shown that short-run, nonhomogeneous production/yield functions are fully consistent with long-run linear homogeneity.     

Scale Economies and Inefficiency of U.S. Dairy Farms

This study employs data drawn from the 2000 Agricultural Resource Management Survey, a U.S. Department of Agriculture-sponsored farmers' survey. The article estimates returns to scale relationships across dairy farms of different sizes and across different regions, incorporating variables hypothesized to influence farm performance. Results point to significant scale economies in U.S. dairy farms and underscore the importance of taking account of inefficiency when estimating scale economies. Contrary to previous research, the preferred cost function specification does not show a region of decreasing returns to scale. This finding helps explain why the average size of dairy farms has been increasing.     

Water access,farm productivity,and farm household income: Sri Lanka's Kirindi Oya irrigation system

Income differences attributed to differential access to water in irrigation systems are common. Prior studies of farm‐level water use in developing areas have typically been limited to using number of irrigations as a proxy for water use. We develop a volumetric measure in Sri Lanka's Kirindi Oya Irrigation System through recent farmer recall and use it in production function estimation and welfare analysis. Findings indicate substantial differences in water use by farms across seasons and across subareas of the irrigation district. Alternative plans for allocating additional water among seasons and subareas to elevate net rice revenues are examined. The recommended plan predicts higher net returns from rice and greater equality in the distribution of household income than would be generated if the additional water were allocated based on the current allocation criteria. Concurrent application of fertilizer at recommended levels would further increase net revenues and reduce income inequality.     

Efficiency analysis under uncertainty: a simulation study

We model production technology in a state‐contingent framework assuming that the firms maximise ex ante their preference function subject to stochastic technology constraint; in other words, firms are assumed to act rationally. We show that rational producers who face the same stochastic technology can make significantly different production choices. Further, we develop an econometric methodology to estimate the risk‐neutral probabilities, efficiency scores and the parameters of stochastic technology when there are two states of nature and only one of which is observed. Finally, we simulate noiseless data based on our state‐contingent specification of technology. Our state‐contingent estimator recovers technology parameters and other economic quantities of interest without any error. But, when we apply conventional efficiency estimators to the simulated data, we obtain biased estimates of technical efficiency.     

新疆棉花生产要素成本收益及规模报酬变动趋势研究基于465户农户问卷调查数据

目的 由于生产要素的价格稳步攀升,新疆棉花生产成本过高,加上新疆棉花销售回归市场,价格不稳定,导致棉花生产风险增大,棉农种棉积极性降低。文章通过对新疆棉花成本收益及规模报酬变动趋势的研究,为棉农生产决策和政府政策提供参考。方法 在对新疆棉农问卷调查的基础上,研究棉花种植规模变动下生产要素的规模报酬。在二次函数的基础上寻找生产要素投入成本较低,收益最大的植棉规模,运用多元线性回归模型分析棉花生产要素投入对植棉成本的影响,以及不同植棉规模下生产要素对棉花产量增加的贡献程度。结果 新疆农户棉花生产的单位面积成本和收益随着户均种植规模的变化呈二次曲线变化;单位面积成本随着种植规模扩大,先下降,超过一定规模后上升,成本最低植棉规模为3.56hm²;单位面积收益随着种植规模扩大,先增加,超过一定规模后下降,收益最高的植棉规模为4.67~5.33hm²。研究发现,户均种植规模在2.5~4.5hm²时,土地费用、机械作业费、水电费、雇工费用投入对棉花产量的贡献较大,规模在7~10hm²时,化肥投入对棉花产量的贡献较大;农药、地膜、滴灌带等物质投入未体现规模趋势。结论 新疆农户棉花生产的成本和收益随着种植规模不同而变化的趋势符合规模经济原理,存在最优种植规模;在不同种植规模下,各种要素投入对新疆农户棉花产量的影响差异明显。因此,要引导棉农合理投入生产要素,降低成本,增加收益。     

农业技术培训、经营规模对农业生产效率的影响——以水稻栽培技术为例

目的 提高农业生产效率是推进农业现代化建设的重要指标。方法 文章基于江西省512份微观调研数据测算出农户的农业生产效率,运用Tobit模型、PSM模型以及分位数回归模型分析了农业技术培训、经营规模对农业生产效率的影响。结果 研究结果表明,农业技术培训对农业生产效率的提高具有显著促进作用,且参与农业技术培训可使农户的农业生产效率提高9.32%;不同经营规模农户参与农业技术培训对农业生产效率的提升效应存在差异,规模户提升效应为28.18%,显著高于小农户的6.97%;农地经营规模对农户农业生产效率具有显著影响,并呈现出“倒U型”关系;农业技术培训、经营规模对不同分位点的农户农业生产效率均具有显著正向作用,并有递增趋势,同时对高效率组的促进作用要明显高于低效率组的农户。结论 政府应积极拓宽农业技术推广渠道,加快转变技术推广方式,同时鼓励适度规模经营,进一步提高农户农业生产效率。     

On the nature and magnitude of cost economies in hog production

In this article, we assess the impact of farm size on production cost and evaluate the marginal costs and margins by considering that input prices may change with the scale of production. By using French hog farm data, we estimate a system of equations including a feed price function, input demand functions, and an output supply function based on a technology approximated by a combined generalized Leontief‐Quadratic form. Our results suggest that the marginal costs are over‐estimated when the adjustment of the feed unit prices to a change in farm size is not controlled for. More specifically, the cost economies for large farms (enjoying the highest profits) arise primarily from lower feed prices, with technological scale economies having little impact. In contrast, farms with no hired labor exhibit technological scale economies and reach higher price‐cost margins compared to larger farms.