Measuring technical efficiency in the stochastic varying coefficient frontier model

Due to the assumption that the best practice methods refer to each input separately instead of the whole set of inputs used by a firm, the benchmark technology as defined in the stochastic varying coefficient frontier model may be infeasible and theoretically improper whenever the maximum response coefficients are not coming from the same production unit. To overcome this problem, we propose alternative measures of output-oriented and single-factor technical efficiencies inspired from the maximum likelihood formulation of the nonneutral frontier model. The empirical results indicate that there are significant differences between the two in terms of the estimated efficiency scores but not significant differences we detected in terms of the efficiency ranking.     

Differences in agricultural returns: an empirical test of efficiency in factor input allocation using Vietnamese data

We study whether rural households in Vietnam allocate their factor inputs efficiently. Factor returns and technical rates of substitution (TRS) between production activities are compared. We estimate two translog production functions and conduct three tests: First we test the equality of bootstrapped returns. Second, we use a bootstrapped t -test comparing the equality of TRS. Finally, we derive a set of nonlinear restrictions on our estimated parameters, which, if held, would imply that we cannot reject efficiency. The article concentrates on the allocation of factors between the cultivation of the two most important agricultural crops—sugar cane and rice. We cannot reject the possibility that households are efficient in their input allocation. These results are consistent and stable over different estimation techniques and support the assumption of profit maximization.     

A nonparametric analysis of the determinants of family farm efficiency dynamics in Lithuania

This article presents insights into the efficiency of Lithuanian family farms. The research covers the years 2004–2009 and is based on farm‐level Farm Accountancy Data Network data. Bootstrapped data envelopment analysis was employed to obtain efficiency scores, whereas stochastic kernels and multivariate methods, viz. fuzzy clustering and nonparametric regression, were utilized to assess the impact of selected determinants on efficiency. Clustering analysis indicated that the efficiency change paths specific for the analyzed sample differed in both their average levels and ranges. Furthermore, it was concluded that Lithuanian agricultural policy should focus on increasing the efficiency of crop farms. Cluster analysis suggested that production subsidies might be having a negative effect on efficiency.     

Adoption of organic farming in Germany and Austria: an integrative dynamic investment perspective

Farm‐level adaptation to changing economic environments is often slower than expected. Technological innovations, for instance, are frequently adopted at a later date than the net present value of investment suggests. This can be explained by a model of “investment under uncertainty,” which consistently accounts for uncertainty, sunk costs, and the flexibility of investment timing. Its essential conclusion is that, due to temporal opportunity costs, critical incremental cash flows that trigger investments might be higher than those needed for simple cost recovery. This accounts for an ostensible reluctance to invest (economic hysteresis). In this article, we demonstrate how slow conversion to organic farming in general, and the different rates of conversion in Germany and Austria in particular, can be explained by the new investment theory.     

Economic efficiency in farm households: trends, explanatory factors, and estimation methods

Factors explaining differences in economic efficiency between farms are of major interest to owners, managers, and other stakeholders as they strive to improve earnings and improve the chances of firm survival. This study is undertaken to improve our understanding of interfarm differences in, and opportunities to improve, farm household efficiency in utilizing their land, labor, and capital resources to achieve household objectives. The technical, allocative, and scale efficiencies of farm households are estimated using a nonparametric, output-based data envelopment analysis (DEA) of a panel data set from 1993 to 2006. Single and double bootstrapping procedures are used to estimate technical efficiency. Initial technical efficiency assuming variable returns to scale (TEV) is estimated to be 0.83. Using single bootstrapping, the average bias-corrected TEV estimate is 0.70; using double bootstrapping, the TEV estimate is 0.72. Allocative efficiency is estimated to be 0.81. Scale efficiency is estimated to be 0.93. The only factor that is consistently associated with higher technical efficiency across analysis methods and years is larger farm size (as measured by the log of farm income). The significance of other factors changes with analysis methods.     

Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture

Stated choice models based on the random utility framework are becoming increasingly popular in the applied economics literature. The need to account for respondents' preference heterogeneity in such models has motivated researchers in agricultural, environmental, health, and transport economics to apply random parameter logit and latent class models. In most of the published literature these models incorporate heterogeneity in preferences through the systematic component of utility. An alternative approach is to investigate heterogeneity through the random component of utility, and covariance heterogeneity models are one means of doing this. In this article we compare these alternative ways of incorporating preference heterogeneity in stated choice models and evaluate the sensitivity of estimated welfare measures to which approach is selected. We find that a latent class approach fits our data best, but all the models perform well in terms of out-of-sample predictions. Finally, we discuss what criteria a researcher can use to decide which approach is most appropriate for a given data set.     

A general equilibrium analysis of conjunctive ground and surface water use with an application to Morocco

Groundwater resources (GW) account for nearly 30% of the world's sustainable water supplies. Yet, this resource, which is fraught with externalities, has largely been left unregulated. The economic literature on GW is predominantly of a partial equilibrium type. We analyze GW regulation in a general equilibrium setting, focusing on the stabilization value of GW under natural (drought) and economic (rural–urban water transfer) shocks. A general equilibrium approach allows evaluating direct and indirect effects of GW regulation on agriculture and nonagriculture sectors and extends the scope for water policy. The analysis is applied to Morocco by extending an existing computable general equilibrium (CGE) model to include ground and surface water (SW) resources. We study effects of (i) an increase in GW extraction cost (e.g., as a result of prolonged extraction beyond natural recharge that lowers the aquifer's water table), (ii) a transfer of SW from rural (irrigation) to urban (domestic) use, and (iii) a reduction of water availability due to severe drought. We estimate the value of GW and assess the direct (partial equilibrium) and indirect (general equilibrium) impacts. We find that GW plays a critical role in mitigating the negative effects of these types of shocks.     

A cross-section analysis of household demand for food and nutrients in Tanzania

Undernutrition and malnutrition are still problems of unacceptable proportions in many developing countries. However, the debate on the roles of income and other socio-economic variables such as women’s education and household size on food and nutrient demand continues. This study examines the demand for food and nutrients amongst households in Tanzania, using recent survey data. A quadratic almost ideal demand system (QUAIDS) is employed to estimate price and expenditure elasticities, as well as the impact of socio-economic variables on food demand patterns. A moment-based instrumental variable approach is then used to analyse the determinants of nutrient demand. The results show that income and other socio-economic variables exert significant effects on the demand for food and nutrients. The estimated expenditure elasticities for the nutrients range from 0.307 for iron to 1.26 for Vitamin B₁₂. The elasticities are higher for those micronutrients that are consumed through animal products and lower for those micronutrients that are mainly obtained through staple foods. These results reflect the higher expenditure elasticities for meat, fish, eggs, milk, and milk products, as well as fruits and vegetables, relative to cereals and pulses, reinforcing the assertion that the demand for Vitamins A and B₁₂, as well as calcium and zinc will increase with rising income.     

Temporal and spatial modelling of tropical deforestation: a survival analysis linking satellite and household survey data

We estimate a spatially explicit model of the forest clearance process among smallholder farmers in an agricultural frontier of southern Mexico. Our analysis takes as its point of departure a simple utility‐maximising model that suggests many possible determinants of deforestation in an economic environment characterised by missing or thin markets. Hypotheses from the model are tested on a data set that combines a time series of satellite imagery with data collected from a survey of farm households whose agricultural plots were geo‐referenced using a global positioning system (GPS). We implement a survival analysis to identify the effect of household level explanatory variables on the probability of deforestation. This approach allows us to introduce a measure of the time until clearance as a covariate, thereby affording a control for the effect of potentially important explanatory variables that vary through time but are not directly observable. In addition to identifying several variables relevant for policy analysis, including household demographics, proximity to roads, and government provision of agricultural support, model results suggest that the deforestation process is characterised by non‐linear duration dependence, with the probability of forest clearance first decreasing and then increasing with the passage of time.     

Wine market prices and investment under uncertainty: an econometric model for Bordeaux Crus Classés

This paper describes an econometric assessment of wine market prices for 21 of the Crus Classés châteaux in the Bordeaux region of France. The model developed in the analysis attempts to define the relationship between factors that influence wine quality and those that influence wine prices. Characteristics of the models are: (1) climate influences on grape composition (acid and sugar levels), (2) grape composition influences on market prices, (3) subjective quality evaluations (Parker‐points) on market prices, and (4) the effects of age of the wine on market prices. The results indicate that composition levels of Merlot‐dominated wines are more climate sensitive than those from Cabernet Sauvignon‐dominated wines. Overall, warm, dry summers result in high sugar and low acid levels at harvest which in turn lead to higher quality wines. Wine market price sensitivity to Parker‐point ratings indicates that properties with high Cabernet Sauvignon‐dominated wines are highly dependent on the external ratings while Merlot‐dominated wines have a decreased rating sensitivity. Smaller properties tend to gain over proportionally from high ratings indicating great jumps in price from year to year. Additionally, châteaux that have experienced high ratings for past vintages exhibit great sensitivity to point steps in ratings for current vintages. Aging has a positive effect on Bordeaux wine pricing. This is due to the increasing maturity as well as the increasing absolute scarcity. Absolute scarcity of product is expressed by the size of the property, with small properties producing less per vintage and therefore having less in the market. Additionally, Merlot‐dominated wines exhibit more maturing potential and profit more from aging than Cabernet Sauvignon‐dominated wines. Average per château real annual profit ranges from 1 to 10%. High levels of grape ripeness, absolute scarcity, and smaller properties that are dominated by Merlot in their blend lead to the highest profits. Forecasts for a vintage not yet on the market indicates that 1995 is better than 1994 for both Cabernet Sauvignon and Merlot‐dominated wines, but that 1996 and 1997 are not as good as 1995, especially for Merlot‐dominated wines.     

Sharecropping efficiency in Ethiopia: threats of eviction and kinship

We tested a theoretical model with the Marshallian inefficiency (H1) and threat of eviction (H2) hypotheses having opposite effects on land productivity on sharecropped plots. The model also assumes that kinship contracts may eliminate or reduce the Marshallian inefficiency (H3) and threat of eviction (H4) effects on land productivity. Our empirical findings were consistent with H2 and H4 being true. We found higher land productivity on sharecropped plots than on share tenants' own plots and higher land productivity on sharecropped plots of nonkin than of kin tenants. The nature of the data allowed controlling for unobservable household characteristics through household fixed effects and for observable plot characteristics. Analyses with and without plot characteristics revealed that these findings were stronger with plot characteristics than without them. Based on the plausible assumption that observable plot characteristics are positively correlated with unobservable plot characteristics this strengthens our conclusion. The results are also supported by first-order stochastic dominance analysis. Sharecropped plots' output value distribution unambiguously dominated the output value distribution from share tenants' own plots. Nonkin sharecropped plots' output value distribution also first-order stochastically dominated the output value distribution from kin sharecrop plots.     

Technical efficiency and impact of environmental regulations in farrow-to-finish swine production in Taiwan

This article demonstrates how technical efficiency and the impact of environmental regulations of Taiwanese farrow‐to‐finish swine production can be estimated in the presence of undesirable outputs. The issue of measuring technical efficiencies while considering undesirable outputs has been addressed by past studies. But the proper method of including undesirable outputs has always been a subject of debate. This article develops a data envelopment analysis (DEA)‐based model that includes undesirable outputs. The technologies of desirable output production and undesirable output control are considered simultaneously. This allows one to transform undesirable output into desirable output, whereby a traditional Shephard distance function can be used to measure technical efficiencies. An approach to measuring the impacts due to environmental regulations is then derived. Empirical results show that larger farms are more technically efficient than small‐sized farms, but no clear conclusions can be reached for the measures of regulatory impact among farms with different sizes. On average, the sample farms incurred an opportunity cost due to environmental regulations equivalent to 9.8% of market value. Opportunity costs rise with efficiency.     

Optimal farm size in an uncertain land market: the case of Kyrgyz Republic

This article applies a real options model to the problem of land development. Making use of the 1998–2001 Kyrgyz Household Budget Survey, we show that when the hypothesis of decreasing return to scale holds, the relation between the threshold value of revenue per hectare and the amount of land cultivated is positive. In addition, the relation between the threshold and the amount of land owned is positive in the case of continuous supply of land and negative when there is discontinuous supply of land. The direct consequence is that, in the first case, smaller farms will be more willing to rent land and exercise the option where, in the second case, larger farms will exercise first. The results suggest three main conclusions: (i) the combination of uncertainty and irreversibility is an important factor in land development decisions, (ii) farmer behavior is consistent with the continuous profit maximization model, and (iii) farming unit revenue tends to be positively related to farm size, once uncertainty is properly accounted for.     

The impact of marketing systems on soil sustainability of agriculture in developing countries: a method and an application

This article is concerned with soil‐sustainability problems of agriculture in developing countries, in particular with soil erosion. The aim of our study is to develop a comprehensive model that explains the adoption of sustainable agricultural practices with respect to soil conservation. Our approach includes the following special features: (a) the model is comprehensive in that it includes a large number of institutional, personal–social, economic, and physical explanatory variables; (b) particular attention is paid to the influence of marketing systems on the adoption of sustainable agricultural practices, which to our knowledge has been neglected in past research; (c) the concept of adopting sustainable agricultural practices (ASAP) is differentiated into a limited number of basic components of soil conservation; and (d) the model is estimated by Principal Component Regression, which enhances efficient estimation of the impact of many explanatory variables on ASAP. Our model is applied to Cabuyal hillside farming in Colombia. The application demonstrates the usefulness of the proposed model. ASAP is differentiated into three basic components: soil‐disturbance control, soil‐protection practices, and run‐off control. It appears that soil‐disturbance control is particularly influenced by farmers' characteristics, such as education and managerial variables. The second component, soil‐protection practices, appears to be strongly influenced not only by farmers' managerial variables but also by their relationship with their environment, in particular marketing institutions. The third soil‐conservation component, run‐off control, is influenced by the physical characteristics of the plot and by the available farm labor. Our empirical results demonstrate the usefulness of the proposed model in designing agricultural policies, because it can determine which variables are more likely to influence the adoption of a specific type of soil conservation.     

Ranking farms with a composite indicator of sustainability

The assessment of sustainability at farm level has been growing in popularity over the last few years. This article contributes to this line of research by building up composite indicators for different facets—social, economic, environmental, and global—of farm sustainability using a methodological approach that combines data envelopment analysis (DEA) and multicriteria decision making (MCDM) methods, and assigns common weights to each individual sustainability indicator. This approach is applied to a database of 163 farms located in the Campos County, a region belonging to the dry lands of the Spanish Northern Plateau, using 12 individual indicators of sustainability. Our findings show that both economic and environmental composite sustainability indicators are positively correlated, but that this is not the case for the social indicator. We also check the influence of a set of variables on farm sustainability using bootstrapping statistical techniques, and showing that increasing farm size, membership in agricultural cooperatives and farmers’ medium and upper agricultural‐specific technical education, all exert a significant positive influence on sustainability. These results provide clues for policy makers that intend to design sustainability‐increasing structural agricultural policies.     

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.     

Price determinants in top-quality e-auctioned specialty coffees

We analyze the price determinants of specialty coffees traded at e-auctions. We hypothesize that since specialty coffees are a highly differentiated product, prices will be determined by both sensory and reputation attributes. To test our hypotheses, we estimate a hedonic price function using data from Central and South American e-auctions and calculate the implicit prices of sensory and reputation attributes. The results show that market clearing prices are a function of sensory characteristics and reputation variables including third-party quality ranking, country of origin, coffee variety, and quantity. The additional attribute information disclosed at e-auctions results in substantially higher prices relative to conventional commodity coffee market prices.     

Consumption inequality between farm and nonfarm households in Taiwan: a decomposition analysis of differences in distribution

Consumption has been recognized as a more reliable indicator of household well‐being than income. Although a considerable body of literature has examined income inequality between farm and nonfarm households, little is known about inequality in consumption. This research aims to fill this knowledge gap by investigating consumption disparity between farm and nonfarm households. Using a nationally representative household survey from Taiwan, we apply an unconditional quantile regression‐based decomposition method to decompose the differences in the distribution of household expenditure between these farm and nonfarm households. The results indicate that differences in the observed characteristics between these two types of households explain most of the consumption inequality. Moreover, the difference in the education level of the farm operator, household income, and the degree of urbanization are particularly important.     

The impacts of information on returns from farming: evidence from a nationally representative farm survey in India

Using a nationally representative sample of farm households from India, this paper examines the impact of use of information on net farm incomes. Employing methodologies that mitigate potential biases in the estimation of the impact, the empirical results show that farmers who use information realize over 12% higher net returns per hectare. The paper also establishes a pecking order in access to information. Small farmers and those at the bottom of social hierarchy (based on caste) have access to fewer information sources, and they depend more on informal social networks and input dealers for their information needs. The larger farmers and those from upper caste rely relatively more on sources such as radio, television and newspaper.     

Short‐run and long‐run dynamics of farm land allocation: panel data evidence from Denmark1

This study develops and estimates a dynamic multi‐output model of farmers’ land allocation decisions that allows for the gradual adjustment of allocations that can result from crop rotation practices and quasi‐fixed capital constraints. Estimation is based on micro‐panel data from Danish farmers that include acreage, output, and variable input utilization at the crop level. Results indicate that there are substantial differences between the short‐run and long‐run land allocation behaviour of Danish farmers and that there are substantial differences in the time lags associated with different crops. To our knowledge, this is the first dynamic micro‐model of land allocation estimated on data from the temperate climate zone. Since similar farming conditions are found in northern Europe and parts of the United States and Canada, this result may be of wider interest.