Efficiency and Technical Change in the Philippine Rice Sector: A Malmquist Total Factor Productivity Analysis

Regional differences in total factor productivity, efficiency, and technological change in the Philippine rice sector are examined for the post-Green Revolution era. Malmquist productivity indices were constructed for 1971–90 and were decomposed into efficiency and technological change. The average annual Malmquist productivity growth was only slightly positive. Productivity growth was negative during the early 1970s, and was followed by a period of positive growth. Growth was negative again in the late 1980s. The period of positive growth coincided with the introduction of new rice varieties while the declines are likely to have been caused by intensification of rice production in lowland farming systems. Certain regions such as Central Luzon, Western Visayas, and Southern and Northern Mindanao had higher rates of technological change than others. This may be due to higher investments in infrastructure and education, increased adoption of tractors, and a better agroclimatic environment.     

Sources of productivity growth on Finnish dairy farms—application of an input distance function

The objective is to examine sources of productivity change on Finnish dairy farms in the 1990s. The decomposition of productivity change into technical and technical efficiency change is widely recognized but it neglects the scale effect. Generalized decompositions incorporating all three components are calculated for a sample of Finnish dairy farms from 1989-2000. This period is of interest because of the drastic change in agricultural policy when Finland joined the European Union (EU) in 1995. The results indicate that productivity growth was on average low, approximately 0.15% per year. Neutral technical change was identified as the most important source of productivity growth (1.1%). Technical efficiency decreased by almost 0.5% annually. The contribution of the scale effect in productivity change increased towards the end of study period.     

Sawmill production in the interior of British Columbia: A stochastic ray frontier approach

We examined the productive efficiency of the interior sawmilling industry in British Columbia using stochastic frontier analysis. Prior sawmilling studies using this method have neglected the multi-output nature of sawmills. To accommodate both lumber and chips as outputs, we used a ray production function and adopted it into the stochastic frontier framework. A translog functional form was specified with three inputs (i.e., capital, labour, and roundwood) and applied to five years (2003–2007) of mill specific production data. The ray production function is flexible allowing factor productivity to vary with the output mix. Results indicated the presence of both economies of scale and technical inefficiency. This suggested that a long-run equilibrium had not yet been reached during this time and might explain recent restructuring occurring in this region.     

Impact of de-coupling agricultural support on dairy investment and milk production volume in Finland

This study analyses the impacts of de-coupling of agricultural support from production in Finland. A dynamic agricultural sector model, which includes 17 production regions and endogenous investments and technical change, is used in the analysis. Investment in different production techniques is dependent on the relative profitability and the spread of each technique in the population of heterogeneous farms. There are relatively few large farms which use efficient production techniques in Finland. De-coupling weakens the incentive for investment in dairy production and causes a temporary but significant slow down in dairy investments and technical change. Consequently, de-coupling is likely to result in a significant drop in milk and beef production in the next 10-20 year period if no corrective measures are taken in agricultural policy in less-favoured areas such as Finland. However, a slow recovery of investment and output levels are expected in the long run.     

A multi-sector intertemporal optimization approach to assess the GHG implications of U.S. forest and agricultural biomass electricity expansion

This study applies an intertemporal partial equilibrium model of the U.S. Forest and Agricultural sectors to assess the market, land use, and greenhouse gas (GHG) implications of biomass electricity expansion. Results show how intertemporal optimization procedures can yield different biomass feedstock portfolios and GHG performance metrics at different points in time. We examine the implications of restricting feedstock eligibility, land use change, and commodity substitution to put our results in the context of previous forest-only modeling efforts. Our results highlight the importance of dynamic considerations and forest and agricultural sector interactions on projecting the GHG effects of biomass electricity expansion in the U.S.     

A review of recent developments and applications of partial equilibrium models of the forest sector

Recent history has seen an increase in the utilization of partial equilibrium based forest sector models to identify potential impacts of various policies or timber market shocks. These models are particularly useful in that they employ economic theory to capture the interaction of supply and demand in a framework where commodity prices are endogenous to the policy or shock simulated. We present recent developments and linkages between models and review applications of these models to forest policy questions over the previous decade. We conclude with a discussion of potential future directions for such research.     

The Contribution of Unmeasurable Inputs to Fisheries Production: An Analysis of Technical Efficiency of Fishing Vessels in the English Channel

Variations in the efficiency of demersal trawlers operating in the English Channel were examined through the estimation of a stochastic frontier production function. The most important measurable factor affecting efficiency was the age of the vessel. However, unmeasurable factors accounted for about 65% of the variation in efficiency, and as much as 9% of the total variation in catches between boats. It is postulated that most of this variation was due to differences in skipper and crew skill. In contrast, "luck" accounted for around 11% of the variation in catches between boats.     

Exploring land use changes and the role of palm oil production in Indonesia and Malaysia

This study compiles and analyses national-level data on land use change (LUC) and its causes in Indonesia and Malaysia over the past 30 years. The study also explores the role that palm oil has played in past LUC and that projected growth in palm oil production may play in LUC until 2020 and suggests strategies to minimize negative effects. Data collection for the study revealed that the quality and quantity of data on LUC on a national scale over time are low. Despite these uncertainties, the overview of past LUC indicates that large changes in land use have occurred in Indonesia and Malaysia. In Indonesia, LUC can primarily be characterized by forest cover loss on 40 million ha (Mha) of land, a 30% reduction in forest land. Deforestation in Malaysia has been smaller in both absolute and relative terms, with a forest cover loss of nearly 5 Mha (20% reduction in forest land). Other large changes in Malaysia occurred in permanent cropland (excluding oil palm), which has decreased rapidly since the early 1990s, and in land under oil palm cultivation, which experienced a sharp increase. Projections of additional land demand for palm oil production in 2020 range from 1 to 28 Mha in Indonesia. The demand can be met to a large extent by degraded land if no further deforestation is assumed. In Malaysia, expansion projections range from 0.06 to 5 Mha, but only the lowest projection of oil palm expansion is feasible when only degraded land may be used. The role of palm oil production in future LUC depends on the size of the projected expansion as well as agricultural management factors such as implementation of best management practices, earlier replanting with higher yielding plants, and establishment of new plantations on degraded land. The current use of degraded land needs to be investigated in order to reduce possible indirect LUC, land tenure conflicts, or other social impacts. In addition to minimizing direct and indirect LUC by the palm oil sector, measures that reduce deforestation triggered by other causes must also be implemented. A key element for doing so is better planning and governance of land use, which entails more appropriate demarcation of forest land and protection of land that still has forest cover, improved monitoring of land use, and more research to uncover the complexities and dynamics of the causes and drivers of LUC.     

Credit constraints and smallholder dairy production in the East African highlands: application of a switching regression model

Accurate assessment of farmers' credit constraint condition is important in order to understand the circumstances under which credit would have its greatest impact. In this study a switching regression model was used to determine the impact of credit on smallholder dairy farms in the East African highlands using farm level data from Ethiopia and Kenya. Farmers were classified as credit constrained or credit non-constrained based on their responses from the farm level surveys. No consistent relationship was found between farmers' credit constraint condition and their borrowing status. Most of the variation in milk output per farm was explained by the number of crossbred milking cows in the dairy herd. As credit is likely to facilitate investment in crossbred dairy cows it will have substantial impacts on smallholder dairy farms especially if it is targeted to credit constrained farms.     

Global food demand,productivity growth,and the scarcity of land and water resources: a spatially explicit mathematical programming approach

In the coming decades, an increasing competition for global land and water resources can be expected, due to rising demand for food and bio‐energy production, biodiversity conservation, and changing production conditions due to climate change. The potential of technological change in agriculture to adapt to these trends is subject to considerable uncertainty. In order to simulate these combined effects in a spatially explicit way, we present a model of agricultural production and its impact on the environment (MAgPIE). MAgPIE is a mathematical programming model covering the most important agricultural crop and livestock production types in 10 economic regions worldwide at a spatial resolution of three by three degrees, i.e., approximately 300 by 300 km at the equator. It takes regional economic conditions as well as spatially explicit data on potential crop yields and land and water constraints into account and derives specific land‐use patterns for each grid cell. Shadow prices for binding constraints can be used to valuate resources for which in many places no markets exist, especially irrigation water. In this article, we describe the model structure and validation. We apply the model to possible future scenarios up to 2055 and derive required rates of technological change (i.e., yield increase) in agricultural production in order to meet future food demand.