8 research outputs found
Estimating Disaggregate Production Functions: An Application to Northern Mexico
Get PDFThis paper demonstrates a robust method for achieving disaggregation in the estimation of flexible-form farm-level multi-input production functions using minimally-specified data sets. Since our ultimate goal is to address important questions related to the distributional effects of policy changes, we place emphasis on the ability of the model to reproduce the characteristics of the existing production system and to predict the outcomes of these changes at a high level of disaggregation. Achieving this requires the use of farm-level models that are estimated across a wide spectrum of sizes and types, which is often difficult to do with traditional econometric methods, due to limitations of data. The approach to estimating flexible-form production functions used in this paper overcomes these limitations, and also avoids the problems that frequently hinder the application of budget-based representative farm models to these type of analyses namely, that of poor calibration to observed behavior. In our estimation procedure, we use a two-stage approach that first generates a set of observation-specific shadow values for incompletely priced inputs, such as irrigation water or family labor, which are used in the second stage, along with the nominal input prices, to produce estimates of crop-specific production functions using Generalized Maximum Entropy (GME) methods. These functions are able to capture the individual heterogeneity of the local production environment, while still allowing the production function to replicate the input usage and outputs produced in the sample data. Since we are able to generate demand, supply, and substitution elasticities, a wide range of policy responses can be modeled. Our paper demonstrates this methodology through an empirical application to Mexico, drawing from a small set of cross-section data collected in the northern Rio Bravo regions. The estimates show that there is considerable heterogeneity in the behavioral response of farmer households of different sizes, both in terms of the returns to scale, as well as in the elasticities of substitution and derived demands for water. Compared to the aggregate-level estimation, we obtain much more accurate and informative policy response behavior, when shocks are imposed on the model.Research Methods/ Statistical Methods,
Kuchunguza Ubiblia Katika Tamthiliya za Emmanuel Mbogo
Get PDFLengo kuu la utafiti huu lilikuwa kuchunguza ubiblia katika tamthiliya za Emmanuel Mbogo kupitia tamthiliya zake za Nyerere na Safari ya Kanaani (2015) na Sadaka ya John Okello (2015). Ili kufikia lengo kuu tulikuwa na malengo mahsusi mawili; kubainisha utokezaji wa Ubiblia katika tamthiliya za Emmanuel Mbogo na kueleza sababu za utokezaji wa Biblia/mwangwi wa Biblia katika kazi hizo teule za Emmanuel Mbogo. Sampuli ya utafiti huu iliteuliwa kwa kutumia mbinu ya usampulishaji lengwa. Tamthiliya teule za Sadaka ya John Okello na Nyerere na Safari ya Kanaani, ziliteulewa kwa maksudi kabisa kwa kuwa ndizo ambazo zimeweza kumpatia mtafiti data alizozihitaji. Data zilikusanywa kwa kutumia mbinu ya usomaji makini. Uchambuzi wa data katika utafiti huu ulifanywa kwa kutumia mkabala wa kimaelezo. Aidha ukusanyaji, uchambuzi na kujadili data kuliongozwa na nadharia ya mwingilianomatini. Matokeo ya utafiti huu yameonesha kuwa kuna Ubiblia mwingi katika tamthiliya za Emmanuel Mbogo alizoziandika miaka ya karibuni. Vipengele vya kifani ndivyo vimetumika katika kubainisha ubiblia huo. Vipengele hivyo ni jina la kitabu, hadithi za kibiblia, wahusika wa kibiblia, nukuu za kibiblia na mtindo wa ushairi. Tamthiliya hizi mbili tulizozitafiti za Emmanuel Mbogo; Sadaka ya John Okello na Nyerere na Safari ya Kanaani zimeakisi mwangwi mkubwa wa Biblia. Kwa mfano kisakale cha wana wa Israel kukaa utumwani Misri na kisha kuanza safari kurejea kwao Kanaani katika Biblia kinapatikana kitabu cha “Kutoka”. Kisakale hiki kimeakisiwa kwa wingi katika tamthiliya ya Nyerere na Safari ya Kanaani, Kanaani ni nchi iliyojaa maziwa na asali kwa mujibu wa kisakale hicho
Wanted: institutions for balancing global food and energy markets
Get PDFFood security, Biofuel, Food prices, Agricultural policy, Energy policy,
Farming smarter, not harder: securing our agricultural economy
Get PDFIn the context of rising global demand, resource scarcity, and environmental pressures, this report considers the future of Australian agriculture.
Global populations are growing and food prices are skyrocketing. This creates new market opportunities for Australian agriculture. But Australia has fragile and vulnerable soils, which are being degraded at an unsustainable rate.
If we continue with ‘business as usual’, we will keep losing soils faster than they can be replaced. Acting now to improve soil condition could increase agricultural production by up to 2.1 billion per year. It could also help farmers cut costs on fertiliser and water use.
“Winners of the food boom will be countries with less fossil fuel intensive agriculture, more reliable production, and access to healthy land and soils” said the report’s lead author Laura Eadie. “How we manage our land and soils will be key to whether Australia sees more of the upsides or downsides of rising global food demand.”
Farming Smarter, Not Harder finds that Australian agriculture can build a lasting competitive advantage through innovation that raises agricultural productivity, reduces fuel and fertiliser dependence, and preserves the environment and resources it draws on. To achieve this, Australia needs to:
Invest in knowledge: increase government investment in research and development by up to 7% a year; increase funding for extension programs; implement the Productivity Commission’s recommendation to set up Rural Research Australia; fund the national soil health strategy with an endowment sufficient to support ongoing research and monitoring for at least 20 years.
Stop chopping and changing support for regional natural resource management:
Federal and State governments should commit to a 10-year agreement to provide stable longterm funding for regional Natural Resource Management (NRM) bodies, including specific funding to monitor long-term trends in natural resource condition.
Enable accountable community governance of land and soil management: To enable farming communities to protect themselves from free-riding, they should be supported to develop stewardship standards based on a shared understanding of what it takes to maintain productive agricultural landscapes over the long term.
Align financial incentives with the long-term needs of sustainable farming communities: In addition to the drought policy reforms announced on October 26, drought assistance policies should support farming communities to take a lead in preparations for more frequent and severe droughts, and should be linked to community stewardship standards.
“Recent projections indicate the potential doubling of exports by 2050, according to the National Food Plan and ANZ-commissioned Greener Pastures report. Our work looks at how to support farmers dealing with the practical challenges of seizing this opportunity, in the context of soil degradation and rising input costs”, said Laura Eadie.
The case to increase research funding and foster innovative farming is made even stronger by the likely impacts of climate change. Without action to adapt to more variable and extreme weather, by 2050 Australia could lose 6.5 billion per year in wheat, beef, mutton, lamb and dairy production.
The report profiles leading farmers who are already seeing the benefits of innovations in sustainable farming. It proposes simple measures to support them and the agricultural communities that depend on healthy farming landscapes.
Download Farming Smarter, Not Harder report in full
[Australia\u27s newly appointed Advocate for Soil Health, Michael Jeffery, also chairs the non-profit organisation Soils for Life which is already actively encouraging wider adoption of smarter farming. The Soils for Life report Innovations for Regenerative Landscape Management showcases a range of case studies of these farming innovations in practise, and the positive economic, environmental and social outcomes they are achieving. Read the case studies, learn more about the challenges landscape degradation will bring and what we can do about it at www.soilsforlife.org.au.
Game-theoretic models of water allocation in transboundary river basins
No full textOnderzoeksvragen zijn hoe samenwerking in waterverdeling kan worden verbeterd, en hoe internationale verdragen zo kunnen worden ontworpen dat ze niet worden verbroken. Onderliggende onderwerpen zijn de aanwezigheid van betwiste eigendomsrechten op water en het ontwerp van aantrekkelijke verdeelregels voor rivierwater. Het doel van dit proefschrift is het analyseren van waterverdeling in grensoverschrijdende rivieren met behulp van speltheoretische modellen. Dit type modellen is geschikt voor het analyseren van strategische interactie tussen landen die een rivier delen, in hun beslissingen omtrent watergebruik
Modelling the seasonal and spatial variation of malaria transmission in relation to mortality in Africa
Get PDFAbout three billion people worldwide are estimated to be at risk of malaria transmission. In developing countries, malaria is believed to be a major cause of morbidity and mortality, mostly in children under five years. It is among the indirect causes of maternal mortality and infants’ deaths due to low-birth-weights. Malaria brings huge economic burden due to number of days lost during sickness and deaths, sustaining a vicious cycle of disease and poverty in sub Saharan Africa (SSA) and high attribute of disability-adjusted life years.
A number of malaria control interventions to reduce intensity of transmission have been successfully implemented in the regions of SSA, however, elimination of malaria is still a dream in many developing countries today. Failures in global eradication are related to resistance in insecticides and anti-malarial drugs, and health systems related factors. The Roll Back Malaria (RBM) partnership reinforced new strategies to combat malaria with long-term goal of eradicating the disease globally. This was facilitated by increasing funding for malaria research, improve multi disciplinary initiatives and make malaria among the main agenda of all international health and development forums. The reduction in mortality, especially in children has been reported recently and is associated with achievements in intervention strategies, improvements in malaria diagnosis and treatment. However, poor natural acquisition of malaria immunity in children as a consequence of weak or no exposure is a major epidemiological concern and brings a fear of higher mortality rates or shifting of age of death to older children. Understanding and quantify links between transmission, intervention, immunity and mortality is key for sustainable progress towards malaria control targets.
A comprehensive analysis of information on malaria transmission, vital events, drivers of transmission and mortality-related risk factors is required to achieve that. Lack of vital registration systems in developing countries hinders availability of appropriate data to conduct such analysis. Establishment of Demographic Surveillance Systems (DSS) in many developing countries aims to fill these information gaps. One of the initiatives integrated within DSSs is the Malaria Transmission Intensity and Mortality Burden across Africa (MTIMBA) project. The project compiled a database of mosquito collections at selected sites in Africa over a large number of locations, using standardized methodologies for a period of three years. The entomological parameters were linked with routinely monitored vital events within the DSS. The MTIMBA database is the most comprehensive entomological database ever collected in Africa which allows studying spatial-temporal variation in malaria transmission in relation to mortality.
Malaria is an environmental disease hence transmission varies with climate as it modifies population, survival, distribution and infectivity of malaria vectors. Quantification of association between climate and transmission is important to allow prediction of risk even in areas that field data cannot be easily obtained. Development in geographical information systems (GIS) and availability of remote sensing (RS) data facilitates availability of environment and climate data at high space and time resolutions allowing accurate estimation of outcome-factor relationship.
However, DSS data are large, sparse, zero-inflated and are characterized by seasonal patterns, spatial and temporal correlations. Standard models assume independence between observations, an assumption which do not hold for correlated data, hence utilizing these models might result into biased estimates. Geostatistical modeling of large, sparse and zero inflated space-time data is computational challenging specifically in the estimation of the spatial processes. The spatial correlation is accounted by introducing location-specific random effect parameters which are assumed to arise from a spatial process quantified by a multivariate normal distribution. The models are highly parameterized and their fit is computationally intensive. Bayesian computational algorithms such as Markov Chain Monte Carlo (MCMC) can be used to fit these models. Estimation of the spatial process requires inversion of the covariance matrix at each simulation point. The dimension of the matrix increases exponentially with number of locations and the inversion becomes infeasible when the size is too large. Recent techniques overcome this problem by approximating the spatial process from a subset of locations. These methods have been applied on Gaussian outcomes observed over a grid. Extension and formulation of rigorous methods to efficient model MTIMBA data are needed to allow precise prediction of malaria transmission at locations with mortality data to enhance studying the association. Lastly, seasonality in climatic conditions which introduces seasonal patterns in transmission and mortality data, should be accounted for when modelling such data.
The objectives of this thesis were to i) develop Bayesian geostatistical models to analyze very large and sparse geostatistical and temporal non-Gaussian data with seasonal patterns and ii) apply these models to (a) estimate space-time heterogeneity in malaria transmission (b) assess mortality variations between different ages during the first year of life while adjusting for seasonality and (c) determine the relation between transmission intensity and risk of mortality in children and adult population after taking into account control interventions. This work used an extract of MTIMBA data from the Rufiji DSS (RDSS) collected between October 2001 and September 2004.
Evaluation of approaches to capture seasonal pattern is discussed in Chapter 2 and applied to estimate mortality peaks at different stages of infant life. In Chapter 3, models approximating the spatial process from a subset of locations were developed to assess effect of climate, seasonal and spatial pattern of sporozoite rate (SR) of An. funestus and An. gambiae in RDSS. A rigorous approach to analyze malaria transmission data using Entomology Inoculation Rate (EIR) data, which is the product of mosquito density and SR, is discussed in Chapter 4. Zero-inflated models were used to account for over-dispersion and zero-inflation in the data. High resolution EIR estimates were produced for the RDSS. Exposure surfaces obtained in Chapter 4, were aligned with mortality events to assess the relationship between all-cause mortality and malaria transmission. Geostatistical Bernoulli discrete-time regression models adjusted for age and ITN possession were used for that analysis. The results of these analyses are presented in Chapters 5 and 6. The EIR was incorporated in the model as a covariate with measure of uncertainty.
This work is a building block on the insight and understanding of association between malaria transmission and all-cause mortality. The strength of results of this work relies on EIR estimates predicted at high spatial (household level) and temporal resolution by employing rigorous geostatistical models fitted on large entomological data. The better exposure estimates obtained are able to more accurately estimate the mortality-transmission relation
Turn down the heat
Get PDFThis report provides a snapshot of recent scientific literature and new analyses of likely impacts and risks that would be associated with a 4° Celsius warming within this century. It is a rigorous attempt to outline a range of risks, focusing on developing countries and especially the poor. A 4°C world would be one of unprecedented heat waves, severe drought, and major floods in many regions, with serious impacts on ecosystems and associated services. But with action, a 4°C world can be avoided and we can likely hold warming below 2°C.
Without further commitments and action to reduce greenhouse gas emissions, the world is likely to warm by more than 3°C above the preindustrial climate. Even with the current mitigation commitments and pledges fully implemented, there is roughly a 20 percent likelihood of exceeding 4°C by 2100.
If they are not met, a warming of 4°C could occur as early as the 2060s. Such a warming level and associated sea-level rise of 0.5 to 1 meter, or more, by 2100 would not be the end point: a further warming to levels over 6°C, with several meters of sea-level rise, would likely occur over the following centuries
Abstracts of Tanzania Health Summit 2020
Get PDFThis book contains the abstracts of the papers/posters presented at the Tanzania Health Summit 2020 (THS-2020) Organized by the Ministry of Health Community Development, Gender, Elderly and Children (MoHCDGEC); President Office Regional Administration and Local Government (PORALG); Ministry of Health, Social Welfare, Elderly, Gender, and Children Zanzibar; Association of Private Health Facilities in Tanzania (APHFTA); National Muslim Council of Tanzania (BAKWATA); Christian Social Services Commission (CSSC); & Tindwa Medical and Health Services (TMHS) held on 25–26 November 2020. The Tanzania Health Summit is the annual largest healthcare platform in Tanzania that attracts more than 1000 participants, national and international experts, from policymakers, health researchers, public health professionals, health insurers, medical doctors, nurses, pharmacists, private health investors, supply chain experts, and the civil society. During the three-day summit, stakeholders and decision-makers from every field in healthcare work together to find solutions to the country’s and regional health challenges and set the agenda for a healthier future.
Summit Title: Tanzania Health SummitSummit Acronym: THS-2020Summit Date: 25–26 November 2020Summit Location: St. Gasper Hotel and Conference Centre in Dodoma, TanzaniaSummit Organizers: Ministry of Health Community Development, Gender, Elderly and Children (MoHCDGEC); President Office Regional Administration and Local Government (PORALG); Ministry of Health, Social Welfare, Elderly, Gender and Children Zanzibar; Association of Private Health Facilities in Tanzania (APHFTA); National Muslim Council of Tanzania (BAKWATA); Christian Social Services Commission (CSSC); & Tindwa Medical and Health Services (TMHS)
