Farm Cost Allocation Based on the Maximum Entropy Methodology - The Case of Saskatchewan Crop Farms

Agriculture and Agri-Food Canada (AAFC) has an ongoing research program to provide information on the effect of potential agricultural policy and technology scenarios on the environment and the economic conditions, behavior and performance in the agriculture sector. Included in this work program is a project to improve our farm level data on cost of production and farm management practices for economic and environmental analysis. As part of this effort to improve our data, this report evaluates an analytical method, called Maximum Entropy (ME), for its effectiveness in extracting detailed, enterprise level, cost of production information from whole-farm data. The ME method has been shown to be a promising and cost-effective option for obtaining these enterprise-level estimates from whole-farm data sets already available.Research Methods/ Statistical Methods,

The Fast Decay Process in Recreational Demand Activities and the use of Alternative Count Data Models

Since the early 1990s, researchers have routinely used count data models (such as the Poisson and negative binomial) to estimate the demand for recreational activities. Along with the success and popularity of count data models in recreational demand analysis during the last decade, a number of shortcomings of standard count data models became obvious to researchers. This had led to the development of new and more sophisticated model specifications. Furthermore, semi-parametric and non-parametric approaches have also made their way into count data models. Despite these advances, however, one interesting issue has received little research attention in this area. This is related to the fast decay process of the dependent variable and the associated long tail. This phenomenon is observed quite frequently in recreational demand studies; most recreationists make one or two trips while a few of them make exceedingly large number of trips. This introduces an extreme form of overdispersion difficult to address in popular count data models. The major objective of this paper is to investigate the issues related to proper modelling of the fast decay process and the associated long tails in recreation demand analysis. For this purpose, we introduce two categories of alternative count data models. The first group includes four alternative count data models, each characterised by a single parameter while the second group includes one count data model characterised by two parameters. This paper demonstrates how these alternative models can be used to properly model the fast decay process and the associated long tail commonly observed in recreation demand analysis. The first four alternative count data models are based on an adaptation of the geometric, Borel, logarithmic and Yule probability distributions to count data models while the second group of models relied on the use of the generalised Poisson probability distribution. All these alternative count data models are empirically implemented using the maximum likelihood estimation procedure and applied to study the demand for moose hunting in Northern Ontario. Econometric results indicate that most of the alternative count data models proposed in this paper are able to capture the fast decay process characterising the number of moose hunting trips. Overall they seem to perform as well as the conventional negative binomial model and better than the Poisson specification. However further investigation of the econometric results reveal that the geometric and generalised Poisson model specifications fare better than the modified Borel and Yule regression models.fast decay process, recreational demand, count data models, Borel, Yule, logarithmic and generalised Poisson regression models, Resource /Energy Economics and Policy,

THE FAST DECAY PROCESS IN RECREATIONAL DEMAND ACTIVITIES AND THE USE OF ALTERNATIVE COUNT DATA MODELS

Since the early 1990s, researchers have routinely used count data models (such as the Poisson and negative binomial) to estimate the demand for recreational activities. Along with the success and popularity of count data models in recreational demand analysis during the last decade, a number of shortcomings of standard count data models became obvious to researchers. This had led to the development of new and more sophisticated model specifications. Furthermore, semi-parametric and non-parametric approaches have also made their way into count data models. Despite these advances, however, one interesting issue has received little research attention in this area. This is related to the fast decay process of the dependent variable and the associated long tail. This phenomenon is observed quite frequently in recreational demand studies; most recreationists make one or two trips while a few of them make exceedingly large number of trips. This introduces an extreme form of overdispersion difficult to address in popular count data models. The major objective of this paper is to investigate the issues related to proper modelling of the fast decay process and the associated long tails in recreation demand analysis. For this purpose, we introduce two categories of alternative count data models. The first group includes four alternative count data models, each characterised by a single parameter while the second group includes one count data model characterised by two parameters. This paper demonstrates how these alternative models can be used to properly model the fast decay process and the associated long tail commonly observed in recreation demand analysis. The first four alternative count data models are based on an adaptation of the geometric, Borel, logarithmic and Yule probability distributions to count data models while the second group of models relied on the use of the generalised Poisson probability distribution. All these alternative count data models are empirically implemented using the maximum likelihood estimation procedure and applied to study the demand for moose hunting in Northern Ontario. Econometric results indicate that most of the alternative count data models proposed in this paper are able to capture the fast decay process characterising the number of moose hunting trips. Overall they seem to perform as well as the conventional negative binomial model and better than the Poisson specification. However further investigation of the econometric results reveal that the geometric and generalised Poisson model specifications fare better than the modified Borel and Yule regression models.Fast Decay Process, Recreational Demand, Count Data Models, Borel, Yule, logarithmic and generalised Poisson regression models, Resource /Energy Economics and Policy,

Agriculture’s inter-industry linkages, aggregation bias and rural policy reforms

As agricultural policy reform and its effects have become increasingly territorialised, analyses which attempt to explain or predict impacts need to be more localised but also identify spillover effects. In addition to the predictions of policy shocks predicted by sectoral partial equilibrium models, local and regional general equilibrium approaches which establish the wider effects of such policy shocks have become popular. However, these neglect a major, underexplored difficulty: agriculture is usually described as a single sector in input-output accounts, whereas policy shocks with differential impacts have effects on other industries which are different to those implied by average input-output coefficients. Regionalisation of aggregated input-output tables adds further to these difficulties. The objective of this paper is to develop a relatively simple method for dealing with these problems. It establishes the theoretical basis for aggregation bias and shows how it can be measured, in two contrasting case study regions in the United Kingdom and Sweden. Having established that this is a significant problem, a simple but effective procedure is demonstrated, based on additional information on variable costs, which transforms policy shocks from a direct change in agricultural output to that transmitted to the suppliers of inputs. This method provides an impact close to that which could be calculated if the general equilibrium system had indeed been disaggregated, and supports use of this approach in impact studies where the researcher does not have the time or funding available for completely disaggregating the agricultural sector’s regional accounts.agricultural and rural development policy evaluation, CAP, input-output analysis, aggregation bias, Agricultural and Food Policy,

International Variability in Biofuel Trade: An Assessment of U.S. Policies

Although the United States has typically been in a position to import ethanol, corn-based ethanol exports are surging as the domestic market becomes saturated and world prices rise due to high prices for sugar, the competing global feedstock. The U.S. is now the world’s leading ethanol producer but domestic demand is constrained because of technical limitations in the current vehicle fleet. Higher ethanol blends have been approved for use (15% rather than 10%) but a limited number of vehicles that can use such higher blends. Infrastructure constraints also affect the potential supply of higher ethanol blends. As a result of these factors, U.S. biofuel policies can have significant implications for the world ethanol market. Usage mandates under the Renewable Fuel Standard, blender tax credits, and the blend wall can interact to generate excess supplies of ethanol that are likely to be diverted to the world market. This paper examines how fluctuations in corn yield and gasoline prices affect the excess supply of U.S. corn-based ethanol in the presence of alternative assumptions about the maximum amount of ethanol that can be consumed domestically. Using stochastic simulations we also explore the impact of current policies on the mean and variance of export supply. The results highlight the complex interaction between technological constraints, economic incentives, and government policies in the U.S. biofuels sector, and point to the potentially destabilizing effect of such policies in international markets.Ethanol Exports, Biofuel Policies, Variability, International Relations/Trade, Resource /Energy Economics and Policy,

The Impact of Feedstock Supply and Petroleum Price Variability on Domestic Biofuel and Feedstock Markets – The Case of the United States

The promotion of biofuel use in preference to traditional petroleum-based transportation fuel has linked agricultural commodity markets and energy markets more closely together. Biofuel policies can involve multiple policy instruments, but studies examining their effects on biofuel feedstock and energy markets are scarce. In addition, the impact of alternative policy approaches in the context of variability in petroleum prices and the supply of biofuel feedstock has received limited attention. Focusing on the current situation in the United States, in which prohibitively high duties prevent imports of ethanol, this paper examines how variability in the price of petroleum and corn supply affects domestic market variability under three types of domestic policies, inclusive of their combinations, for promoting the use of ethanol: 1) the provision of a fixed subsidy (tax credit) for blending ethanol with gasoline; 2) the use of a blending mandate; and 3) the use of a consumption mandate. Varying relative variability in petroleum price and corn supply, we analyze numerically the implications of changes in domestic biofuel policy for variability (measured by the coefficient of variation) in ethanol use and corn prices. We also provide some brief insights into the design of market stabilization policies. Results obtained from Monte Carlo simulations show that in the absence of mandates the quantity of ethanol used under a subsidy policy is highly susceptible to fluctuations in oil prices and corn supply, providing that there are no constraints to adjustment in ethanol demand. The impact of oil price fluctuations on the price of corn is large, but corn supply fluctuations have no or a small impact on the equilibrium corn price, depending on the flexibility of the use of corn in ethanol refining. This is because variations in ethanol volume absorb shocks caused by corn supply fluctuations. Consequently, high fluctuations in the price of petroleum are expected to result in high variability in the corn price in the absence of mandates. With a mandate (with or without a subsidy), as the likelihood that the mandate becomes binding increases, variability in ethanol use declines, the impact of variations in petroleum price on corn prices is reduced, and the impact of variations in corn supply on prices is accentuated. Therefore, if the mandate is likely to be binding, high fluctuations in corn supply are expected to result in high variability in the corn price. If the likelihood that ethanol use exceeds the mandated level is high, the effects are similar to those in the absence of a mandate. The effects of changes in biofuel policy, such as a reduction in the level of tax credit under a mandate and an increase in its level, on the price of corn depend on the relative magnitudes of world oil price and domestic corn supply fluctuations.biofuels, subsidies, mandates, variability, Agricultural and Food Policy, International Relations/Trade, Resource /Energy Economics and Policy,

The Implications of Alternative U.S. Domestic and Trade Policies for Biofuels

The U.S. Renewable Fuel Standard program (RFS), which involves mandates for various biofuels, is complex and has been often misinterpreted or oversimplified in previous studies. In this paper we analyze the implications of the RFS for the U.S. domestic and international ethanol markets. We demonstrate the vital role of the advanced biofuel mandate within the RFS. Impacts of changes in tariffs on imported fuel ethanol and subsidies for U.S. domestic ethanol production are examined. One of our important findings is that the RFS could result in serious misallocation of resources in both a national and international context. There is a possibility that the United States could be required to import sugarcane-based ethanol to meet the advanced biofuel mandate, simultaneously exporting corn-based ethanol, while satisfying the national overall mandate. Since the provision of subsidies for domestic ethanol production can stimulate exports of corn-based ethanol, they are equivalent to export subsidies in this situation. The removal of tariffs can reduce the burden imposed on consumers in the United States from the operation of the RFS. Our analysis shows that it is extremely important to understand the potential impact of the RFS on agricultural and energy markets.Ethanol, trade liberalization, Renewable Fuel Standard, mandate, subsidies, Industrial Organization, F13, Q18, Q42, Q48,