Abstracts Working Papers
Abstracts of the professional publications by SOW-VU's staff since 1999.
Hard copies of SOW-VU's working papers are available from the Centre for World Food Studies.
About a decade ago, the main OECD countries decided to promote the use of biofuels so as to reduce greenhouse gases, to contribute to energy self-sufficiency and to create additional demand for agricultural commodities. The introduction of mandatory blending requirements and lavish subsidies spurred fast adoption of this technology. In the course of 2008, the already existing controversy about the effectiveness of this strategy culminated as the resulting upward shift in demand contributed to staggering rises in food prices on world markets. It is uncertain as yet whether this will tone done current ambitions among policy makers to expand biofuel production. The paper shows that high ratios of energy prices to food prices are needed to make biofuel production profitable without the mandatory blending and subsidies. Yet, even if food-based biofuels disappeared, the issue remains that rising high energy prices will promote intensified use worldwide of land for energy crops, requiring huge amounts of mineral fertilizers and putting nature under additional pressure. In policy terms, this defines three major tasks. The first is replacing the current excise taxes on energy carriers by a uniform carbon tax, so as to mitigate greenhouse gas emissions in an efficient manner, the second to prevent price fluctuations on the oil markets from destabilizing food markets, as happened in recent years. Introduction of upper limits on the use of food for biofuel could prove effective here. The third, much wider, task is to make the transition to a partly biomass based energy production possible and sustainable, that is establishing fair distribution of property and user rights over the lands, while safeguarding biodiversity and soil fertility and maintaining adequate labor standards and living conditions, also during periods that these become non-profitable following a drop in energy prices.
Prevalence rates of undernutrition among children and adult women are considerably higher in
In the present report an analysis is made of undernutrition prevalence rates in males and females (children, adolescents, adults), as these occur in South Asia and Sub Sahara Africa, and it is investigated whether this reveals a distinct nutritionally disadvantageous position of women relative to men in South Asia. It is followed by an analysis of the prevalence and characteristics of undernutrition in populations from Asian descent in other parts in the world, in particular
Results indicate that in children and adults differences in nutritional status between males and females are generally small, both in
It is hypothesized that, apart from the possible negative effects of a low status of women, there exists among people from Asian descent an ethnic predisposition for a low adult body mass index, which comes to expression under a relatively low or moderate level of standard of living. Through its effect on birth weight of babies, the low body mass index of women contributes to the high levels of child malnutrition in
Poor farmers find it difficult to cope with price-weather shocks through self-insurance, because they cannot afford to keep large stocks and to protect their crops through irrigation and other measures. Mutual insurance is not an option either, because all participants would be faced with the same price-weather conditions at the same time. The next option of market insurance is plagued by excessive monitoring cost in avoidance of moral hazard and adverse selection. Consequently, new types of insurance are needed.
Among the arrangements suggested, index-based insurance is currently receiving much attention. Index-based insurance offers an indemnification according to an index function that depends on agreed upon price and weather conditions rather than on an assessment of damage at individual farm level. Existing proposals and experiments present a synthetic index function whose effectiveness is established by assessing its capacity to stabilize revenues on the historical record.
The present paper proposes an approach that is different in that it enables the insurer to offer an indemnification that is optimal from the perspective of the farmer in preventing a fall below a specified poverty line and is self-financing up to a given subsidy. To this effect, we develop and apply a model that minimizes farmers’ risk of receiving an inadequate indemnification. The approach builds on methods from catastrophic risk management in insurance and support vector regression in statistics. It is applied to
It is speculated that, in particular in Sub Sahara Africa, controlled and site-specific application of micronutrients to crops, in combination with well-balanced usage of traditional fertilizer (N, P and K) might help break the vicious cycles of low yields, poverty, and poor human nutrition.
Boom, G.J.M. van den, S. Pande, ‘User manual for the SAS-facility to plot maps’, 38 pp.
In recent years spatial analysis has gained considerable attention at SOW-VU and the plotting of maps is increasingly used to present research outcomes. This note discusses the facility that has been developed for this plotting using the SAS software (SAS Institute Inc., 2003). It is linked to the gridding, regression, classification and polling software (Keyzer, 2005) but can also be used as a standalone package. It is an extension and revision of an earlier version of the facility (Overbosch, 2006). The main revision concerns the construction of (administrative) boundaries to overlay the basic raster map of grid cells. Whereas these boundaries had to be provided as a separate data set, they are now identified directly from the basic raster map itself following the edges of grid cells at the boundary of a specified (arbitrary) grouping. The extension of the facility consists of additional color schemes and added options to position the legend, to scale the legend and the plot, and to plot at higher or lower resolutions. Also, the parts of the facility that used to be specific to a certain application have been eliminated whereby the facility is now generic and can be initialized and tested through a simple batch-file.
Keyzer, M.A., S. Pande, ‘Classification by crossing and polling for integrated processing of maps and surveys. An addendum to GRCP-software’, Working Paper 07-04.
The paper presents numerical procedures to compute conditional frequencies on large scale maps and surveys comprising mostly qualitative data, much in the way commonly done for ballots but with sufficient generality and computational power to support simultaneous processing of a large number of questionnaire entries, for categorical as well as for real-valued data. Specifically, we address the curse of dimensionality inherent in the crossing of a large number of qualitative answers by focusing on highest frequency outcomes and by applying sorting routines from database management in computation. In case real-valued explanatory variables appear jointly with categorical variables, we make use of kernel smoothing, which allows among others for the representation of spatial correlation, under a window size that maximizes the goodness of fit. The appendix describes the fully GAMS-controlled operation of the software tool, a new component of SOW-VU’s GRCP-package for grid level calculations, regression and classification. The tool also has options for spatial interpolation, for projection of survey data on maps, and vice versa, as well as for calculations on recursive sequences of conditioning variables (Markov chains).
Molini, V., M.A. Keyzer, G.J.M. van den Boom, W. Zant and N. Nsowah-Nuamah, ‘Social safety nets and index-based crop Insurance: historical assessment and semi-parametric estimation for Northern Ghana’, 33 pp.
Our paper considers past and present social safety net arrangements in
In recent years spatial features have gained considerable attention in economic research at SOW-VU, and maps have increasingly been used to present spatial data or outcomes of scenario simulations. Consequently, a growing need was felt for software facilities that would simplify the making of maps, as well as would allow for making these maps automatically as final step of scenario simulations. This note discusses such facilities for making maps in SAS, a statistical software package extensively used at SOW-VU and elsewhere in economic research
Results show that for zinc, there are strong opportunities for both increasing crop yields and increasing crop micronutrient contents for major crops such as wheat, maize and rice. For iodine, application to fodder crops might result in better growth of animals, higher iodine contents of animal products such as meat and milk, and on its turn contribute to improved human iodine status. For iron, positive effects on both yields and crop iron contents are, in principle, possible, but chemistry and physiology of iron is highly complex, and there is a strong need for further research into agriculturally based approaches aimed at increasing crop iron contents. For selenium, experiences in Finland and China have shown that crop selenium contents, and as a result human selenium intake, can be increased by adding selenium to common fertilizer.
Keyzer, M.A., M. Nubé, C.F.A. van Wesenbeeck, ‘Estimation of calorie intake in Africa: methodology, findings and implications for Africa’s record’, 29 p.
Whereas the international community has come in great need of obtaining reliable estimates on food and nutrition, after adopting the Millennium Development Goals while committing to monitor their realization, it appears that essential data are lacking and that current estimates depend on highly tentative assumptions. The present paper reports on estimation of undernutrition and calorie intake in Sub-Saharan Africa (SSA). It also needs tentative assumptions but unlike the official estimates published by FAO, invokes as an additional data source the anthropometric measurements available in the Demographic and Health Surveys (DHS) commissioned by USAID. Besides comparing the estimates on undernutrition, we also assess the calorie intake and the implication for agricultural production, and purchasing power in urban areas, all in the year 2000. We find substantially lower undernutrition rates than reported by FAO, while per capita consumption is only little higher on average but significantly higher in Central and Eastern Africa. This suggests that the agricultural production and the purchasing power of farmers should by and large have managed to keep up with both the rise in farm population and the growth of cities, which in turn would indicate that non-agricultural income has grown over the last decades as well. Some preliminary calculations on this basis show that common GDP estimates of past and projected growth in SSA may be too conservative as well. However, these positive findings need qualification. First, the very high child mortality in SSA as compared to other developing regions may in part explain the more favorable nutritional status of the surviving population. Second, large numbers of refugees are sustained from foreign food aid. Finally, the AIDS/HIV epidemic creates uncertainties in many respects, including the work capacity of the population and the demography itself.
The paper describes the structure and contents of the data set that has been compiled for the Chinagro general equilibrium model. The model is a 17-commodity, 8-region welfare model with 6 income groups per region and agricultural supply represented separately for as much as 2433 counties (virtually all). In every county several land use types in cropping and livestock production are distinguished, with in total 28 aggregate outputs. Apart from the 17 tradable commodities, local commodities such as manure, household waste and crop residuals are accounted for. Data are collected from various basic sources, reclassified into Chinagro taxonomy and made consistent for baseyear 1997. Consistency requirements for commodity balances and price margins follow from the general equilibrium structure of the model. The same data set is also used to provide benchmark information at county level to the spatially explicit partial models that have been developed as a parallel activity in the Chinagaro project. The construction of the data set is programmed in GAMS, with a modular set-up that shows the steps from source data to final data and facilitates revisions of specific components. The paper has a statistical appendix with a summary of baseyear tabulations.
The Chinagro-project has developed a series of single-commodity, spatially explicit partial equilibrium models covering China with around 94000 grid cells of 10-by-10 kilometer surface, as well as one 17-commodity, 8-region general equilibrium welfare model with 6 income groups per region and agricultural supply represented separately for as much as 2433 counties (virtually all), and describing, for every county, 14 land use types in cropping and livestock production, with 28 aggregate outputs. Both models are run in parallel. The present paper describes the structure of the general equilibrium model and its relation to the partial versions. It also shows how to compute the solution of this very large model, and how to calibrate it. The model is formulated as a welfare program of an open economy with transportation costs between regions and with tax distortions. It operates on an annual basis, evaluating a solution under given scenario-trends with respect to land availability, demography, economic growth, technological progress, international prices and government policies. Regarding validation, the Chinagro-model fully replicates for every county and region of China at 1997 base-year conditions, adequately mimics changes over the period 1997-2003 and provides interpretable results until 2030. It has fully integrated software that efficiently runs from basic data, via solution algorithms and simulation, to automatic production of detailed county-level maps and tabulation of results. The Chinagro-model is programmed in GAMS. Maps and other tabulations are controlled in GAMS or in user-friendly menus, even though they actually run in DOS, Fortran and SAS.
The paper considers the updating of datasets with census data and grid maps, as well as the parameter estimation and micro-simulation of models based on these datasets, while accounting jointly for (i) survey data such as expenditures from households, rainfall data from weather stations and data on land classification; and (ii) aggregate data at district or sector level as published by statistical agencies. Various rule-based gridding, regression and classification algorithms to conduct these tasks are presented that rely on kernel smoothing, nearest neighbor and support vector techniques. Beyond this incorporation of census and grid map data within the survey based regression/classification itself, as opposed to their use in prediction only, the intended contribution is to allow for formulations with discrete data other than single, binary and multiple class choice, such as ranking with known and unknown class bounds and a consumer model with discrete choice and to present GRCP, a software package designed for this purpose, through which the user can readily navigate between gridding, regression and classification, controlling by simple GAMS commands all operations from the basic data down to the automatic preparation of tables and geographic maps with appropriate legends and 2D and 3D plotting of functions.
The paper specifies a spatially explicit model with a very large number of, say, about 50000 cells, to represent hydrological flows in the Jordan basin within a welfare context. Its main emphasis is on specifying a new homotopy algorithm to solve this model in the presence of market imperfections (missing markets) through which no payment is received for outflows from designated sites of arbitrary spatial configuration (lines, dots, closed objects). Hence, it can represent any coalition of territories within the basin, who refuse to pay to downstream districts as well as imperfections in the monitoring system. It can be run for several years in sequence, as the future can be considered to lie downstream of the present, and in the absence of imperfections will yield an intertemporally efficient path. The equilibrium is unique. The homotopy algorithm is based on price iteration over a sequence of dual convex programs, which are solvable in closed form, on a site-by-site basis, in decreasing order of elevation. We also discuss extensions, including market imperfections, dynamics and the treatment of uninhabited sites.
Support Vector (SV)-regression, a common tool in statistical learning, estimates functions as linear combinations of given (nonlinear) kernel functions. To this representation corresponds through duality a weighted, possibly infinite sum of generally unknown eigenfunctions. The paper proposes to start from given eigenfunctions, as these can be thought of as representing a known micro based model, say, the sum of known Marshallian demand functions of all individual consumers and applies SV-regression to estimate a more compact and macro representation to replace this micro-model. The method applies to any single valued and bounded, possibly discontinuous eigenfunction and we show that it can accommodate multiple equations as well as constraints on parameters and function derivatives. The existing SV-algorithm can solve this micro-based problem at moderate computational cost, even when the number of individuals is very large, say, running in the millions because it can store all the necessary information in a Gram-matrix whose dimensions do not depend on this number. Among various problems in the range between micro and macro, optimal aggregation is the most micro. It amounts to finding an optimal, as sparse as possible vector of weights, so that the individuals with positive weights fit the true aggregate model with sufficient accuracy. Next, comes the competition between the micro-model and a given macro-model, and a we gradually attribute a more modest to the micro a priori, we eventually reach pure kernel approaches, the Gram-matrix is postulated as a covariance-like measure of the distance between observations and is applied to the macro-model directly. Finally, beyond the macro models lay the essentially descriptive non-parametric data enveloping techniques that only postulate a Gram-matrix. While the same SV-algorithm of dual quadratic programming applies throughout, it appears that the consistency properties of the estimators become weaker along this path, and whereas stochastic quasigradient methods achieve convergence almost surely, SV-regression only reaches convergence in probability.
Anthropometric information on the prevalence of undernutrition in children, such as the prevalence of a low weight-for-age, is increasingly used as an indicator of poverty or food insecurity at the level of countries or regions within countries. However, little is known how, at this level, the nutritional status of children is related to the nutritional status of other age segments such as adolescents or adults. Without such information, the undernutrition prevalence among children cannot be interpreted as an overall indicator of poverty or food insecurity.
In the present study, utilizing in particular results from the Demographic and Health Studies, an analysis is made of the relationships between undernutrition prevalence rates among children and adults, both at the level of countries and at the level of smaller geographical subunits within countries (districts, provinces). At the level of countries, results reveal a strong positive relationship between undernutrition prevalence rates among children and adults. These results are in support of the concept that national undernutrition prevalence rates among children can be considered a proximate of overall nutritional conditions in a country.
At the level of smaller geographical units relationships are different. High levels of undernutrition among children may or may not be associated with high levels of undernutrition in adults. It is hypothesized that a combined high prevalence of undernutrition both among children and adults is in particular associated with insufficient household level access to food, while a combination of a high level of child undernutrition with an adequate or reasonable nutritional condition of adults points to non food factors, such as poor water and sanitation conditions and poor education, as major causes of undernutrition.
A general approach is presented to value the stocks and flows of water as well as the physical structure of the basin on the basis of an arbitrary process-based hydrological model. This approach adapts concepts from the economic theory of capital accumulation, which are based on Lagrange multipliers or shadow prices that reflect market prices in the absence of markets. This permits us to derive a financial account complementing the water balance in which the value of deliveries by the hydrological system fully balances with the value of resources, including physical characteristics reflected in the shape of the functions in the model. The approach naturally suggests the use of numerical optimization software to compute the multipliers, without the need to impose an immensely large number of small perturbations on the simulation model, or to calculate all derivatives analytically. A novel procedure is proposed to circumvent numerical problems in computation and it is implemented in a numerical application using AQUA, an existing model of the Upper-Zambezi River. It appears, not unexpectedly, that most end value accrues to agriculture. Irrigated agriculture receives a remarkably large share, and is by far the most rewarding activity. Furthermore, according to the model, the economic value would be higher if temperature was lower, pointing to the detrimental effect of climate change. We also find that a significant economic value is stored in the groundwater stock because of its critical role in the dry season. As groundwater comes out as the main capital of the basin, its mining could be harmful.
In this study, we apply novel tools for data exploration to a detailed environmental and crop yield database from a spatially very variable farmer's field in SW Niger. Rather than the entire field, as we did in earlier studies, we now consider two individual field parts that derive from different parent materials (coversands). The objective is to verify if site-specific yield function analysis leads to a better understanding of soil chemistry-yield relationships and if these then allow fine-tuning of possible external input technologies. Our findings show that the type of variables that explain millet yield well across soil types are also important at the level of individual field parts. However, the functional forms for the two parts are quite different: they conform better to theoretical knowledge than the overall equation; they are easier to interpret; they indeed identify site-specific operating mechanisms; and, consequently, they lead to different promising input technologies. These findings confirm earlier observations that farmers in this environment need to apply low-tech precision farming in order to achieve greater efficiency of external input use. Regarding analytical methods, this study highlights the importance of the selection of variables and the functional form, which should not be imposed from the outset, but derived from the data themselves. We further conclude that process-based crop growth models, as yet, cannot accommodate the full complexity of soil chemistry and its effect on crop yield. Empirical on-farm research, as presented in this paper, could be the answer and identify the most significant soil fertility complexities that need to be addressed in real-world situations aiming at the design of external input technologies that combine low cost with substantial yield improvement.
A comparison has been made of developments with respect to food security over the period 1980-2000 in four regions of Sub Sahara Africa: coastal West Africa, the Sahel, Central and Eastern Africa, and Southern Africa. On the basis of trends in food production and consumption and trends in human outcomes (child malnutrition, life expectancy), it appears that developments have been relatively positive in coastal West Africa (with the exception of Liberia and Sierra Leone), and also in the Sahel region, and relatively unfavorable in Central and Eastern Africa and Southern Africa. Regional differences have been identified with respect to natural resources conditions, with respect to the occurrence of emergencies and disasters, and with respect to international assistance in the form of food aid. It is concluded that awareness and understanding of regional differences between various regions of Sub Sahara Africa is important in further analysis of food security developments and prospects of Sub Sahara Africa.
CPB Report 2003/2
In 2003, the EU member states are expected to agree on a reform of its Common Agricultural Policy that could have far-reaching consequences for the ongoing Doha round of WTO-negotiations as well as the rural countryside all over Europe. There is growing appreciation of the role of agriculture in maintaining rural landscapes and keeping the rural country-side inhabited and maintaining cultural heritage: agriculture is seen to deliver "green services". The mainstay of current EU proposals for CAP reform is to decouple the present support by transforming the area and animal premiums into a single farm-specific payment. This offers a unique opportunity for a transition to a system that makes these payments contingent on the provision of green services, and can liberalize trade while keeping the countryside populated. However, the current proposals are insufficiently articulate for a credible transition to such a system, and even contain elements that may hamper this transition.
Very local spatial soil variability on Sudano-Sahelian coversands hampers the interpretation of agro-pastoral research and is an obstacle for the dissemination of research findings. Site characterization and the establishment of site-specific plant performance and yield responses to external inputs are therefore of fundamental importance to achieve agricultural development. In an earlier paper we applied novel tools for data exploration such as non-parametric kernel density regression and spatial econometrics to spatially explicit data on topsoil N, P and K and could explain 81 percent of the millet yield variation. However, the macronutrients explained a modest portion of millet yield only, while the good explanatory power largely derived from spatial autocorrelation. In the present paper we use the same tools to identify and characterize the sources of soil variability/spatial autocorrelation within a single farmers’ field. Three soil types are identified, the essential differences of which refer to the cation exchange complex: different proportions of the cations (Ca, Mg, K and Na), in combination with a different Al saturation profile as well as absolute levels of K. Millet yields are high when low levels of topsoil Mg and Na occur in combination with high levels of Al saturation in the deeper subsoil. Conversely, yields are low when Al saturation in the subsoil is lower and when the proportion of Mg and Na is high. Since Al saturation is caused by water percolation, the empirical evidence thus suggest that high levels of Mg and Na in the topsoil reduce water infiltration. The possible operating mechanism is the destabilizing effect these elements have on the clay fraction, which in turn is the cause of surface sealing. Moisture availability and the effect of surface sealing on seedling establishment may thus be a key source of local millet growth variation on Sudano-Sahelian coversands. The above variables explain millet yield better than N, P and K, without spatial autocorrelation being present in the residuals, and thus constitute the true source of millet growth variability. The variables involved and stratigraphical evidence suggest a parent material connection to the local soil variability: coversands of different source materials and age occurring as shallow layers. We propose further experimental research to investigate if Ca and K applications, which reduce the proportion of Mg and Na in the topsoil, ameliorate moisture availability, improve seedling establishment and raise crop yields.
This paper proposes to use a mollifier mapping, a general and flexible
tool for smoothing the response by the players of a game for the selection
of a robust equilibrium (refinements) as well as for procedures converging
to a unique equilibrium: tracing, smoothing of best response, testing of
evolutionary stability and superimposing of aggregate shocks on replicator
The safety of a given food item may be expressed as a product characteristic that is uncertain at the time of transaction. It can be represented through a probability distribution. Improving food this safety amounts to changing the shape of the distribution, through prevention measures. Extreme risks will lead to prohibition, but if financial compensation of losses is conceivable, the situation becomes more complex, as economic agents have to decide simultaneously on quantities and probabilities, for example in the calculation of expected utility and expected profits. This creates a non-convexity that may cause market failure, even in situations where all safety characteristics are priced competitively. The paper follows two lines of investigation to avoid this problem. The first considers restrictions on the functional forms of utility and prevention functions, and the second introduces the institution of standard-based labeling as a filter on possible distributions, essentially to discretize them. Starting from a partial equilibrium model with one consumer, one producer and one unsafe commodity, in which various options prove effective, we gradually extend the analysis to cover several agents and commodities, eventually arriving at a general equilibrium formulation. At every step, we eliminate unsuitable options, eventually to find labeling as sole viable option.
The paper formulates a static general equilibrium model in which crime is represented as a unilaterally enforced income transfer. Individuals choose between an honest and a criminal career while investing in prevention to avoid robbery or arrest. We explore the conditions under which the criminal career becomes unattractive. We show, without recurring to higher penalties, better competition and improvement of employment opportunities, and under a broad class of market distortions, that crime is eliminated if individual robbers are obliged to share the proceeds with their peers, while the robbed also share their losses, essentially because this taxes away their gains. Conversely, the individualization of incentives under decollectivization is seen to disrupt this redistribution mechanism and hence to foster crime.
The identification of local soil variability caused by within-field differences of macronutrients and ecological features is of paramount importance for the effectiveness of precision agriculture. We present several spatial statistical and econometric techniques to capture local differences in soil variation, ecological characteristics, and yield more effectively than the analytical techniques traditionally used in agronomy. The application of these techniques is illustrated in a case study dealing with precision agriculture in the West African Sahel. The production of millet on acid sandy soils constitutes a typical example of low soil fertility areas exhibiting small absolute but large relative differences in crop production conditions over short distances.
Kernel learning offers tools for semiparametric regression and classification that have made their proofs in the field of pattern recognition, especially in optical reading, voice recognition, and genomics (Schölkopf and Smola, 2002). In this paper, we describe its possible contribution to the construction of poverty maps, especially its potential to improve the flexibility of the functional forms in regression and shows how to use census information for estimating these. We have implemented the kernel learning algorithms in GAMS and found to be numerically effective, as they essentially rely on convex quadratic programming.
Insecurity management differs from risk management in that it takes the distribution of uncertain events to be under the control of economic agents, rather than given. This effectively turns these distributions into public goods for all who are affected by them, and therefore calls for dedicated institutional arrangements, to avoid market failure and inefficiency. Once distributions become variable, market failure may also result via the product of the density and the utility function in expected utility maximization, that loses concavity. The paper discusses two ways to maintain concavity, one in which the actions other than those that shape the distributions can be postponed until after uncertainty has been revealed, another in which new institutions restrict the possible probability profiles to a finite number of alternatives. Under central planning, this can be effectuated via standardization. Standard-based labeling offers a decentralized solution that enables individuals to compose a mix from given profiles, either collectively, or individually.
The paper presents an algorithm to solve a spatially explicit dynamic model in which substances flow downward over a relief of arbitrary shape and material balances are maintained in every cell of the spatial grid. On the basis of the downstream extraction prices and amenity values, the algorithm, implemented in Fortran, also calculates in a numerically effective way the upstream prices of the flows, for problems of very large dimensions, say, with a few million cells. We distinguish between a linear version, in which the directional outflow fractions of every cell are kept independent of the flows, and a nonlinear one, which may also exhibit discontinuities, and can accommodate an arbitrary valuation criterion that is not necessarily separable over sites. Next, we indicate how, at given prices of the flows, we can in a fully decentralized calculation on a site-by-site basis, impute prices of stocks and generally of model parameters, in the static version of the model as well as in the steady state of a dynamic version, with carryover stocks. Moreover, we present conditions under which the algorithm can determine the optimal extraction at every site as well optimal routing between sites, and locate sites where uphill pumping would be profitable. We also indicate that the valuation criterion that is being maximized might be a likelihood function, in which case the model parameters become the key variables for valuation, with their prices pointing to directions of change that would improve the fit to observed data.
Expert judgments are potentially a valuable source of information in land degradation assessment, especially in those areas where data paucity impedes the utilization and validation of quantitative models. However, these expert opinions are also much disputed because they are not tested for consistency, abstain from a formal documentation, while its quantitative interpretation is inherently unidentifiable. In this paper we aim to evaluate and formalize the use of expert judgments in order to conduct a nationwide water erosion hazard assessment in Ethiopia. We therefore test the experts' judgment for its consistency, the correlation with quantitative observations on soil loss and its reproducibility. The study uses an Ethiopian and an international data set for which groups of experts gave qualitative judgments on water erosion hazard, for well-described sites under different types of land uses. The experts have a relatively high consistency in their judgments on land degradation for similar sites. Comparing the ranked qualitative expert opinions to quantitative soil losses reveals that particularly the boundaries of the middle classes vary widely between experts and comprises a wide range of soil loss values. Reproducing expert opinions with an ordered logit model shows a reasonable accuracy in predicting the presence or absence of erosion, but the model is less precise in distinguishing between the higher erosion classes. In 58 per cent of the cases, the model gives a similar classification as the experts, in 19 per cent the model gives a higher and, more seriously, in 23 per cent a lower erosion class. Mapping the model results for Ethiopia demonstrates a high erosion hazard for land under annual crop cultivation, while erosion under perennial crops, rangeland and forest is absent or moderate. The likelihood of selecting the correct hazard class for rangeland is relatively high but low probabilities prevail for erosion classes of other land uses.
Information on the
prevalence of undernutrition in adults in developing countries is mainly
restricted to data on women. Literature reporting on the occurrence of
female deprivation in developing countries, in particular in South Asia,
suggests that differences between undernutrition prevalence in adult men and
adult women might occur, but systematic information on the subject is
We investigate the determinants of antenatal care use in Ghana using a large-scale living standard survey. Most previous studies on the subject have used surveys that focus on demography and fertility, and have used approximate indicators of economic variables such as income and cost of consultation. This leads to an overestimation of effects when explanatory factors pick up the effect of underlying economic conditions. We describe antenatal care demand as a three level nested multinomial logit model that includes more appropriate economic explanatory variables. The estimation results show that indeed income, cost of consultation and in particular travel distance to the health care facility are significantly associated with the demand for antenatal care. Use of sufficient antenatal care can thus be promoted effectively by extending the supply of antenatal care services in the rural area. In addition, education of the mother is positively associated to choice for sufficient antenatal care, while women having more pregnancy experience tend to underutilize antenatal care. This suggests that campaigns to promote sufficient antenatal care should pay special attention to education and to women who already gave birth. The results further indicate that, in contrast to findings elsewhere, a special targeting of antenatal care according to religion seems unwarranted.
Five Central West African
countries, Burkina Faso, Côte d’Ivoire, Ghana, Mali and Togo, cooperate in
the Réseau-SADAOC (Sécurité Alimentaire Durable en Afrique de l’Ouest
Central), which has as its major objective to increase food security in the
region. The present report aims to review the health and nutrition situation
in the five countries, to identify major bottlenecks in the functioning of
the health care system, and to suggest strategies for addressing identified
Research Report RR-02-03
IIASA Interim Report IR-02-021
The study compares schooling, experience and labor market outcomes in a sample of over 20,000 Ghanaians aged 15 to 65, who have been interviewed during four rounds of the GLSS and who represent the labor force as a whole over the period 1987-1999. Estimates of the coefficient of the years of schooling in a standard human capital model are combined with data on public and private schooling expenses. We find an average social rate of return (ROR) to basic education as low as 3 per cent, while the social ROR to secondary and tertiary schooling is 16 and 3 per cent, respectively. With estimates of 6, 25 and 15, the private ROR are higher, especially for tertiary education. As regards experience, estimates suggest positive and gradually decreasing returns. The first year of experience is estimated to increase earnings by around 5 per cent, while additional experience gradually yields less until earnings reach a peak around 35 years of experience. The results suggest that educational sector reform in Ghana be highly concerned with improvements of basic education, with the upholding of the quality of secondary schooling, and with opportunities to increase the share of private expenses in secondary and tertiary education.
Public authorities tend to be actively involved in the health sector through prevention programs, regulation of health insurance and control of access to treatment. Common explanations include asymmetries in information, the danger of epidemics and imperfect competition. This paper argues that these interventions may also be required to deal with the typical externality that probabilities depend on individual and collective decisions. We formulate a general equilibrium model, in which individuals face endogenous probabilities of incurring specified diseases and obtaining timely treatment. Health insurance organizations collect premiums and invest in treatment capacity, in accordance with the preferences of their customers, but because of limited treatment capacity and insurability, they may have to conduct lotteries to assign patients. The externality causes a non-convexity in the patient’s expected utility function. We show that the associated consumer demand functions are well behaved nonetheless, and that an equilibrium exists. Moreover, if bounds on insurability are not effective and the collective decisions on prevention follow Lindahl pricing, this equilibrium will be Pareto-efficient in terms of expected utility, despite the capacity constraints and the endogenous risk. We also discuss how subsidies, prohibition and equal access restrictions can be included, at the expense of efficiency.
The paper argues that current international projections of meat and feed demand may underestimate future consumption patterns for mainly two reasons. First, their demand projections are based on income extrapolation with an assumed demand elasticity, and on expert judgment. Second, feed requirements per unit of meat are taken to be fixed. Instead, we propose a structural specification of meat demand, that accounts for the differences in income between households within countries as well as for the nonlinear shape of the meat demand schedule since the poor segments of the population tend to abstain from meat consumption until their income reaches some lower threshold, while rich consumers become satiated beyond an upper threshold. Regarding feed requirements, we distinguish between traditional feeding technologies based on grazing, household residuals and harvest by-products, and more intensive livestock technologies. We formulate optimistic and pessimistic projections on technological advances in feeding efficiency, carcass weights, and offtake rates. Our finding is that under the growth rates of per-capita income assumed in the commonly accepted projections, world meat demand will be significantly underestimated in the coming thirty years, especially during the first half of this period, even under optimistic assumptions on technological advances. The fast increase in the demand for meat will together with the tendency towards urbanization make it more difficult to expand the branch of animal husbandry that feeds on residuals and grass. This creates a strong pressure on cereal markets, especially to satisfy demand in Asia.
In this paper I explore the possible effects of health policies in Burkina Faso on the health status of its population. Relations between health indicators for mothers and their young children and their determinants are estimated using data from a recent Demographic and Health Survey. Of the determinants, general education, the supply of safe water and sanitation, and the provision of health care can be influenced by health policies. In absence of price data the estimated equations include proximity indicators for health care facilities, for which three specifications are tried, but the results show only modest to low influence of these indicators. According to the estimations, better living standards have a positive impact on the nutritional status of mother and child, and reduce the prevalence of illness among children. Education of the mother positively influences her nutritional status and that of her young children, but does not seem to affect their illness frequency. Safe drinking water is positively related to the nutritional status of mothers and children, but its effect on illness of children is unclear. Toilet facilities do not seem to have any impact at all. Also a positive effect of health care on health is hard to establish, and health status is positively correlated to a few types of facilities only. Effects of private health facilities seem more pronounced than those of public ones, but may be biased due to selectivity. Of all vaccinations, only those against measles reduce the illness frequency of young children.
The application of continuous distributions from statistics in spatial modeling makes it possible to represent discrete choices in a spatial continuum, and to obtain efficiency results and competitive equilibrium prices where aggregate or discretized models fail. Along these lines, and combining principles established by Aumann and Hildenbrand in the sixties with recent results from stochastic optimization, the paper develops a practical modeling framework for land use planning and presents the associated stochastic algorithms for numerical implementation. We consider groups of consumers and producers whose activities are distributed over space, and who have to make decisions, say, about where to live, which marketplace to visit, and which infrastructure facilities to invest in. After presenting a general equilibrium model in which all consumers meet their own budget with given transfers, we focus on the case in which transfers among consumer groups adjust to support the maximization of a given social welfare criterion. It appears that this optimization problem becomes more tractable if it is treated as the minimization of a dual welfare function, that solely depends on prices but is evaluated after integration over space. Next, we apply the dual welfare function to represent (non-rival) demand that simultaneously benefits several agents, reflecting a general informational infrastructure as well as investments with uncertain outcomes. This leads to a minimax problem, in which the dual welfare function is to be minimized with respect to prices and maximized with respect to non-rival demand. Finally, we endogenize welfare weights jointly with prices to model, for example, a land consolidation process whereby none of the participants should lose relative to the initial situation, and the gains could be shared according to agreed principles. This gives rise to a bargaining problem whose solution can be found by jointly minimizing the dual welfare function over prices and welfare weights, subject to constraints.
This paper evaluates the future impact of soil degradation on national food security and land occupation in Ethiopia. It applies a spatial optimization model that maximizes national agricultural revenues under alternative scenarios of soil conservation, land accessibility and technology. The constraints in the model determine whether people remain on their original site, migrate within their ethnically defined areas or are allowed a trans-regional migration. Key to this model is the combination of a water erosion model with a spatial yield function that gives an estimate of the agricultural yield in its geographical dependence of natural resources and population distribution. A comparison of simulated land productivity values with historical patterns shows that results are interpretable and yield more accurate outcomes than postulating straightforward reductions in yield or land area for each geographic entity. The results of the optimization model show that in absence of soil erosion control, the future agricultural production stagnates and results in distressing food shortages, while rural incomes drop dramatically below the poverty line. Soil conservation and migration support a slow growth, but yet do not suffice to meet the expected food demand. In a trans-regional migration scenario, the highly degraded areas are exchanged for less affected sites, whereas cultivation on already substantially degraded soils largely continues when resettlement is confined to the original ethnic-administrative entity. A shift to modern technology offers better prospects and moderates the migration, but soil conservation remains indispensable, especially in the long term. Finally, an accelerated growth of non-agricultural sectors further alleviates poverty in the countryside, contributing to higher income levels of the total population and, simultaneously, relieving the pressure on the land through rural-urban migration.
We study the effect of aggregate risk on saving and investment in an illustrative two-period general equilibrium model with contingent contracts (possibly constrained) in the Arrow-Debreu tradition and rather standard functional forms. Risk is modeled in the form of independent sector-specific endowment shocks. Household classes maximize expected utility. In a partial setting this specification of preferences and behavior would imply that risk leads to precautionary saving, with the largest tendency for the poorest classes. Simulations with the two-period model show that precautionary saving persists also in the general equilibrium context, in spite of the equilibrium price variability and the smoothing provided by contingent contracts. However, the precautionary saving effect is drastically reduced if investment itself is stochastic, more precisely if its impact is positively correlated to the aggregate risk in the economy. Surprisingly, savings hardly react to constraints on contingent transactions. Only when the assumption of rational expectations is dropped and household classes are assumed to be optimistic or pessimistic in the perception of their expected utility, bounds on contingent transactions have a significant impact on saving rates. Furthermore, the simulations show that in an orthodox Arrow-Debreu context with aggregate risk, liquidity constraints are not necessarily detrimental to the poor.
Although it seems natural to assess quality of statistical inferences, researchers have not been loud enough about the implications for decisions based on the underlying untested assumptions. In this study, we examine and evaluate the untested assumptions of the likelihood-ratio test. This can be regarded as a standard exercise for the evaluation of any hypothesis testing procedure, as such exercise should offer a framework as to how a test procedure is to be carried out.
Keywords: Hypothesis testing, the Likelihood-ratio test.
This study examines productivity, farm size, and the relationship between size and productivity in U.S. agriculture over the period 1982-1992. A nonparametric regression method was applied to detect ex post geographical patterns in changes in size and productivity. Estimations show that (i) in 1982 productivity per acre was high in the East, West, and South, modest in the middle part of the U.S., and low in the North, and this pattern remained the same in the period 1987-1992, while the level of productivity continuously increased over time; (ii) during 1982-1992 farm size remained unchanged, large farms being in the middle belt stretching from North to down South and small ones in the East, West and South; and finally (iii) over the period 1982-1992 an inverse relationship grew stronger between size and productivity per acre. Furthermore, Markov chains method was applied to project these ex post patterns into the future. Predictions suggest that at the national and regional levels (i) farms are likely to experience lower productivity per acre; (ii) small and large farms are likely to coexist as medium-sized farms to vanish; and (iii) the inverse relationship is likely to show a strong geographical pattern.
Key words: Farm size, productivity, geography, inverse relationship, U.S. agriculture, nonparametric regression, Markov chains.
This paper adapts an already existing non-parametric hypothesis test to the bootstrap framework. The test utilizes the non-parametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstrapped version of the test allows to approximate errors involved in the asymptotic hypothesis test.
Keywords: Hypothesis test, the bootstrap, non-parametric regression, omitted variables.
The possible non-representativity of household surveys can be addressed by reweighting the survey observations through a correction factor. This factor is usually computed on the basis of the frequency of a combination of household characteristics, say, the age and sex of the respondent, in the survey relative to its value in a population census. In this paper, a generalization of this technique is proposed that makes it possible to account for several household characteristics including real-valued ones. It applies kernel density regression to estimate the joint density over the survey of selected characteristics that are also recorded in the census. The weights are estimated by Monte Carlo integration of the estimated density over the census distribution. The efficacy of the procedure is tested in a simulation experiment that creates a large number of survey data sets as biased samples from the Ghana Living Standards Survey, applies the reweighting procedure to every sample, and confronts the resulting estimated mean with the known true mean of the census.
Keywords: Monte Carlo integration, kernel density regression, weighting scheme
Assigning economic value to renewable resources has become a major concern in environmental management. A common difficulty in this context is that a process-based representation of the underlying bio-physical processes necessarily causes the model specification to depart from the basic postulates of micro-economic theory, as it corresponds to a technology characterized by non-convexity, lack of free disposal, and no possibility of inaction. Consequently, regular valuation procedures do not apply, and current practice has become either to discard the irregularities in technology or to restrict the valuation procedure to impact assessments for a limited number of scenario simulations. In this paper, relying on capital theory, we describe a technique that enables us to effectuate a comprehensive valuation despite the non-standard features. It calculates marginal returns over an infinite time horizon of variations in inflows (raindrops) or adjustments in structural characteristics of the bio-physical process, in the steady state with all stocks. It can be implemented without analytical calculation of derivatives, because these marginal returns can be computed as the Lagrange multipliers of a mathematical program. We also discuss various extensions to account for random variability and for non-stationarity arising in as a consequence of, say, technical progress, population growth, and climate change.
Advocates of strict resource conservation are often accused of embracing an overly pessimistic worldview that underrates the scope for technological innovation. This paper argues that conservationism also fits within an optimistic perspective. We consider an overlapping generations model with several consumer goods and exhaustible resources that provide amenity value, in which technical progress allows for sustained growth of manmade goods that remain, however, imperfect substitutes for these natural amenities. We compare a grandfathering policy that ensures efficiency through privatization with a policy of enforced resource conservation. It is shown that strictly conservationist measures do not cause any Pareto inefficiency in this model, irrespective of whether they pass a cost-benefit test.
The data as presented in the Global Burden of Disease study, a collaborative undertaking between the Harvard School of Public Health and the World Health Organization, provide the opportunity to assess how the total burden of disease (mortality and morbidity) is distributed over age groups. The data indicate that in Sub Sahara Africa all age groups, including the economically most active (15-45 years), are subject to high levels of burden of disease, much higher in comparison with high income countries, and also much higher in comparison with other developing regions. In view of the impact of disability on household functioning in all its aspects, including income generating capacity, results call for detailed studies on burden of disease at household level, for which household survey data might be an appropriate source of information. With respect to specific causes, mortality and disability resulting from violence, accidents, and mental illness, are estimated to account together for more than 40% of the disease burden in the 15-45 years age group in Sub Sahara Africa. Other diseases or disorders that significantly contribute to the total disease burden for adults are AIDS, other sexually transmittable diseases, tuberculosis, maternal conditions, malaria, and respiratory diseases. On the other hand, the contribution of tropical diseases such as schistosomiasis, river-blindness, filariasis, leishmaniasis and trypanosomiasis (but excluding malaria) is relatively limited.