Micro-simulation as a tool to assess policy concerning non-point source pollution: the case of ammonia in Dutch agriculture

Non-point source pollution is notoriously difficult to asses. A relevant example is ammonia emissions in the Netherlands. Since the mid 1980s the Dutch government has sought to reduce emissions through a wide variety of measures, the effect of which in turn is monitored using modeling techniques. This paper presents the current generation of mineral emission models from agriculture based on micro-simulation of farms in combination with a spatial equilibrium model for the dispersion of manure from excess regions with high livestock intensities within the country to areas with low livestock intensitie

Nutritional Status of Adolescent Girls from Rural Communities of Tigray, Northern Ethiopia

Background: Addressing the nutritional needs of adolescents could be an important step towards breaking the vicious cycle of intergenerational malnutrition. Objective: Assess nutritional status of rural adolescent girls. Design: Cross-sectional. Methods: Anthropometric and socio-demographic information from 211 adolescent girls representing 650 randomly selected households from thirteen communities in Tigray was used in data analysis. Height-for-age and BMI-for-age were compared to the 2007 WHO growth reference. Data were analyzed using SAS, Version 9.1. Results: None of the households reported access to adolescent micronutrient supplementation. The girls were shorter and thinner than the 2007 WHO reference population. The cross-sectional prevalence of stunting and thinness were 26.5% and 58.3%, respectively. Lack of latrine facilities was significantly associated with stunting (p = 0.0033) and thinness (p <0.0001). Age was strong predictor of stunting (r(2) = 0.8838, p <0.0001) and thinness (r(2) = 0.3324, p <0.0001). Conclusion: Undernutrition was prevalent among the girls. Strategies to improve the nutritional status of girls need to go beyond the conventional maternal and child health care programs to reach girls before conception to break the intergenerational cycle of malnutrition. Further, carefully designed longitudinal studies are needed to identify the reasons for poor growth throughout the period of adolescence in this population. [Ethiop. J. Health Dev. 2009; 23(1):5-11

Bio-economic household modelling for agricultural intensification

This study contributes to the quest for sustainable agricultural intensification through the development of a quantitative bio-economic modelling framework that allows assessment of new technology and policy measures in terms of household welfare and sustainability indicators. The main aim of the study is the development of a farm household model to aid policy dialogues. The study consists of three parts. The first part is a general introduction into the context of the research, a justification of the approach and a general description of issues underlying the modelling framework. The second part explains the methodological details of the modelling framework. The third part contains some applications of the approach to specific questions related to agricultural intensification in the Cercle de Koutiala in southern Mali.The bio-economic model developed in this study combines elements from different existing methodologies into a flexible framework that is able to capture the peculiarities of household agriculture in West Africa. The methodology is sufficiently general to be applied in other settings as well, and contains a number of innovations, viz. a direct utility function, a robust goal weighting procedure and the use of metamodelling to analyse mathematical programming outcomes.Part 1Soil degradation is regarded as a serious problem threatening the livelihoods of present and future generations in West Africa. To bring soil degradation to a halt, a combination of appropriate technology and an enabling policy environment is needed (Chapter 1). To assess new technology and policy measures, information from biophysical and socio-economic disciplines are combined into a quantitative framework.Over the past decade a number of quantitative studies have been conducted that aim at combining biophysical and socio-economic information in such a way that the results are relevant for both social and biophysical sciences. These approaches are termed bio-economic modelling. A review of the methodologies (Chapter 2) reveals that none of them are able to tackle simultaneously the analysis of the causes and effects of soil degradation in combination with household decision making to assess the effects of policy change. The studies do however provide valuable building blocks for the present methodology.A framework to characterise the bio-economic models according to the spatial and temporal scales assists in finding appropriate methods for different research questions. Two critical issues emerge from the review. The first concerns the choice of objective function in economic models. The second refers to the interface between economic behaviour and biophysical processes.This critical interface between biophysical processes and economic behaviour is wrought with difficulties due to differences in scientific paradigms (Chapter 3). Biophysical sciences use the concept of efficiency in the analysis of technology options. The concept differs from the way economists use it. As a result there is a disparity between the way biophysical scientists and economists view production and damage functions. Whereas economists tend to use well-behaved continuous Cobb-Douglas production functions, biophysical scientists describe production activities in terms of the outcomes of biophysical processes, which more often than not yield nasty functions. This is due to the synergistic effects of inputs and the interrelations between causes and effects of soil degradation.The implications for bio-economic modelling are that Leontief production functions best describe the biophysical processes. Biophysical modelling frameworks exist that generate point data for this type of production function. One such framework, the technical coefficient generator (TCG) is used for generating the biophysical information needed in the household model.Part 2The household model is based on the standard theoretical model of a farm household (Chapter 4). The theoretical model although developed for econometric estimation is difficult to implement in such a way, due to the existence of failures and imperfections in commodity and input markets, the occurrence of risk, data limitations and the complexities in the production functions. As a result a complex non-separable household model is needed, which in turn cannot be estimated econometrically.Instead of estimating a full econometric model the present methodology proposes an alternative through the use of mathematical programming models that have been parameterised with partial econometric studies and expert knowledge. The basic structure of this bio-economic model consists of six separate modules. The production activities module describes the biophysical processes and their interrelationships using information generated by the TCG. Different technological options are defined in terms of input-output combinations for both current agricultural practices and alternative technologies. The price module includes information on factor and commodity markets. Price bands are used to describe market imperfections and results from the household models in terms of aggregate supply are used to calculate new market-clearing prices.A separate module describes different household types in terms of their resource endowments, real time preference and savings capacity. The savings capacity is linked to a savings and investment module that describes consumption smoothing and investment behaviour. Investment in soil conservation measures is one way of halting ongoing soil degradation.The expenditure module warrants separate mention (Chapter 6). The use of non-separable farm household models implies that consumption and production decisions are considered simultaneously. As a result the commonly used profit maximisation objective function cannot be used. Instead a utility function is used that describes household preferences for consumables. The direct utility function is estimated econometrically from a cross-sectional budget survey that is considered the revealed preference generated by an underlying utility function.The study develops a procedure to derive such a utility function. Because direct measurement of utility is impossible careful procedures are needed to test if the derived function is statistically robust. Next to consumption households also consider soil degradation in their decision making. The consequence is that multiple objectives have to be considered and a procedure is needed to combine those objectives (Chapter 5). The study presents a methodology for estimating the weights of different household objectives by comparing simulation model results with empirical evidence. To obtain statistically robust results maximum entropy econometrics is used.Part 3Application of the modelling framework to the case study area of Cercle de Koutiala in southern Mali is done for specific research questions. The first question concerns the validity of the model itself (Chapter 7). The model generates a base run that is consistent with empirical evidence. Applying sensitivity analysis to key parameters, analysing the near-optimal solution space and by applying the model to a separate data-set tests the robustness of those results. The model turns out to be robust for the most important variables while insight is gained into those areas for which the model does not give adequate answers.The model is also used to analyse new technology (Chapter 8). New technologies were chosen on biophysical grounds. Using partial budget analysis a first indication of the possibilities of the new technology is obtained. The approach is too partial to capture farm household goals and aspirations nor the resource constraints they face. Bio-economic model results indicate that most of the alternative technologies that seemed promising from a biophysical point of view do not fit well into the production systems of farm households in Cercle de Koutiala. A metamodelling approach is used to analyse the outcomes of the farm household model for a large number of variations in key exogenous parameters, thus obtaining fluid response surfaces.The model is also used to assess the possibilities of using policy instruments to create an enabling environment to induce farm households to adopt more sustainable technologies (Chapter 9). Two key instruments that figure in the forefront of policy debates in West Africa are analysed, viz. fertiliser price subsidies and infra-structural development resulting in lower transaction costs. Model results analysed in a metamodelling framework indicate that although the direction of the change in both income and soil organic matter balance is as would be expected, viz. simultaneous improvement of household-welfare and agro-ecological sustainability indicators, the magnitude of the improvements is limited. The policy measures in combination with the available new technologies are effective but not efficient.</p

Nutritional Status of Adolescent Girls from Rural Communities of Tigray, Northern Ethiopia

Background: Addressing the nutritional needs of adolescents could be an important step towards breaking the vicious cycle of intergenerational malnutrition.Objective: Assess nutritional status of rural adolescent girls.Design: Cross-sectional.Methods: Anthropometric and socio-demographic information from 211 adolescent girls representing 650 randomly selected households from thirteen communities in Tigray was used in data analysis. Height-for-age and BMI-for-age were compared to the 2007 WHO growth reference. Data were analyzed using SAS, Version 9.1.Results: None of the households reported access to adolescent micronutrient supplementation. The girls were shorter and thinner than the 2007 WHO reference population. The cross-sectional prevalence of stunting and thinness were 26.5% and 58.3%, respectively. Lack of latrine facilities was significantly associated with stunting (p = 0.0033) andthinness (

Household welfare, investment in soil and water conservation and tenure security: Evidence from Kenya

In Kenya, conservation and sustainable utilization of the environment and natural resources form an integral part of national planning and poverty reduction efforts. However, weak environmental management practices are a major impediment to agricultural productivity growth. This study was motivated by the paucity of literature on the poverty-environment nexus in Kenya, since poverty, agricultural stagnation and environmental degradation are issues of policy interest in the country¿s development strategy. The paper builds on the few existing studies from Kenya and explores the impact of household, farm and village characteristics as well as the development domain dimensions on household welfare and investment in soil and water conservation. The results show that strengthening the tenure security improves household welfare. Further, soil quality, topography and investments in soil and water conservation affect household welfare. Agroecological potential, which is related to environmental conservation, is also a key correlate of poverty. Results for investment in water and soil conservation confirm the importance of tenure security in determining adoption and also the intensity of SWC investments. We also find that household assets, farm characteristics, presence of village institutions and development domain dimensions are important determinants of adoption and intensity of soil and water conservation investments. The results for both poverty and investment in soil and water conservation suggest the existence of a strong poverty-environment link in our sample. The results also suggest that rural poverty can be alleviated by policies that improve environmental conservation and strengthen land tenure security. The study also underscores the importance of village institutions in both investment adoption of soil and water conservation and in improving household welfare

Kansen voor innovatie in melkvee- en varkenshouderij

De kansen voor duurzame innovaties in de melkveehouderijsector bij verdergaande schaalvergroting en die voor de varkenshouderij bij stijgende voerprijzen zijn op verzoek van het ministerie van Economische Zaken in beeld gebracht. Dit is gedaan op basis van een systeembenadering en vanuit het ondernemersperspectief. De systeemanalyse is zowel kwalitatief uitgevoerd op basis van de veranderingstheorie als kwantitatief met het bedrijfseconomisch optimalisatiemodel FLAME. Het ondernemersperspectief is gebruikt voor het in kaart brengen van het huidige innovatiegedrag op basis van de LEI Innovatiemonitor-enquete. Daarnaast zijn vertegenwoordigers uit beide sectoren gevraagd naar de volgens hen benodigde innovaties voor een toekomstbestendige landbouw

MAMBO visie en strategisch plan 2012 - 2015

Het model MAMBO (Mineralen- en AmmoniakModel voor Beleidsondersteuning) berekent op basis van economische principes de meststromen in Nederland en de bijbehorende emissies van ammoniak en broeikasgassen. Het model wordt onder andere toegepast voor monitoring van de mestmarkt, voor evaluaties van het mestbeleid en voor verkennende studies op het gebied van ammoniakemissies

MAMBO 2.x : design principles, model structure and data use

This report describes MAMBO, the model for calculation of manure and fertilizer distribution based on economic principles. Six key processes regarding animal manure and artificial fertilizer are included in MAMBO: (1) Manure and mineral production on farms; (2) Maximum allowed application of manure on farms within statutory and farm level constraints using micro-simulation and mathematical programming techniques; (3) Manure surplus at farm level (production minus maximum application amount); (4) Manure distribution between farms (spatial equilibrium model); (5) Application of manure and artificial fertilizer within the remaining bounds resulting in soil loads with minerals; (6) emission of ammonia and other pollutants at all stages described above. MAMBO is a complex model that uses large amounts of data, the structure of the model and the data used as well as examples of key model results are included. Finally both design principles and quality control are discussed at length