15 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,
Data and code for study "Effect of changes in population density and crop productivity on farm households in Malawi"
No full textAuthor to who correspondence may be addressed: Adam Komarek (https://orcid.org/0000-0001-5676-3005)
Most recent edit: April 1st, 2019
Details: the zip file 'analysis.zip' has two main folders for the code and data required to replicate the results in the study
"Effect of changes in population density and crop productivity on farm households in Malawi". The study DOI is
https://doi.org/10.1111/agec.12513. Study authors are Adam M. Komarek and Siwa Msangi
1) a folder 'gams' that requires six steps to run the GAMS model. The GAMS model was run on GAMS version 24.8.5
The GAMS model is the DAHBSIM (Dynamic Agricultural Household Bio-Economic Simulation Model)
Six steps:
I. ensure all files and folders inside the folder 'gams' are inside the same one folder
II. open project file 'model.gpr' inside 'gams' folder
III. open settings.gms. The directory settings are on lines 17 to 21, no need to write out the file paths
as '$setglobal filelocation' sets the file path to wherever model.gpr is located
IV. open and run 'set_database.gms' in gams\model, to ensure the database is there
V. open and run 'gen_baseline.gms' in gams\model, this runs the baseline model and the scenarios using the toggle on L199, if needed
include 's=dahbsim rf=dahbsim' in the command line without the single quotation marks
VI. scenario data in \gams\data_raw\cropcoef_raw.xlsx and scenario code in gams\model\scenario_model.gms
2) a folder 'r' with five main items that include the R project and four main folders:
I. 'cropProdMWI.Rproj' is the R project. It must be opened to set the project directory, which is needed to read in the data
II. the R scripts are in the folder 'scripts'. There are 7 scripts, which are ordered sequentially
III. the folder 'data' contains the data used in the scripts
IV. output from the scripts are in the folder 'output'
V. livestock data, relevant for manure application, are in the folder 'livestock
Data and code for study "Effect of changes in population density and crop productivity on farm households in Malawi"
No full textAuthor to who correspondence may be addressed: Adam Komarek (https://orcid.org/0000-0001-5676-3005)
Most recent edit: April 1st, 2019
Details: the zip file 'analysis.zip' has two main folders for the code and data required to replicate the results in the study
"Effect of changes in population density and crop productivity on farm households in Malawi". The study DOI is
https://doi.org/10.1111/agec.12513. Study authors are Adam M. Komarek and Siwa Msangi
1) a folder 'gams' that requires six steps to run the GAMS model. The GAMS model was run on GAMS version 24.8.5
The GAMS model is the DAHBSIM (Dynamic Agricultural Household Bio-Economic Simulation Model)
Six steps:
I. ensure all files and folders inside the folder 'gams' are inside the same one folder
II. open project file 'model.gpr' inside 'gams' folder
III. open settings.gms. The directory settings are on lines 17 to 21, no need to write out the file paths
as '$setglobal filelocation' sets the file path to wherever model.gpr is located
IV. open and run 'set_database.gms' in gams\model, to ensure the database is there
V. open and run 'gen_baseline.gms' in gams\model, this runs the baseline model and the scenarios using the toggle on L199, if needed
include 's=dahbsim rf=dahbsim' in the command line without the single quotation marks
VI. scenario data in \gams\data_raw\cropcoef_raw.xlsx and scenario code in gams\model\scenario_model.gms
2) a folder 'r' with five main items that include the R project and four main folders:
I. 'cropProdMWI.Rproj' is the R project. It must be opened to set the project directory, which is needed to read in the data
II. the R scripts are in the folder 'scripts'. There are 7 scripts, which are ordered sequentially
III. the folder 'data' contains the data used in the scripts
IV. output from the scripts are in the folder 'output'
V. livestock data, relevant for manure application, are in the folder 'livestock
Halving hunger: Meeting the first millennium development goal
Get PDF"In 2000, the world’s leaders set a target of halving the percentage of hungry people between 1990 and 2015. This rather modest target constitutes part of the first Millennium Development Goal, which also calls for halving the proportion of people living in poverty and achieving full employment. However, the effort to meet the hunger target has swerved off track, and the world is getting farther and farther away from realizing this objective. The goal of halving hunger by 2015 can still be achieved, but business as usual will not be enough. What is needed is “business as unusual”—a smarter, more innovative, better focused, and cost-effective approach to reducing hunger. The five elements of this new approach are as follows: Invest in Two Core Pillars: Agriculture and Social Protection The first step in reducing poverty and hunger in developing countries is to invest in agriculture and rural development. Most of the world’s poor and hungry people live in rural areas in Africa and Asia and depend on agriculture for their livelihoods, but many developing countries continue to underinvest in agriculture. Research in Africa and Asia has shown that investments in agricultural research and extension have large impacts on agricultural productivity and poverty, and investments in rural infrastructure can bring even greater benefits. Scaled-up investments in social protection that focus on nutrition and health are also crucial for improving the lives of the poorest of the poor. Although policymakers increasingly see the importance of social protection spending, there are still few productive safety net programs that are well targeted to the poorest and hungry households and increase production capacity. Bring in New Players New actors in global development—the private sector, philanthropic organizations, and emerging economy donors—have important roles to play in reducing hunger in developing countries. But the opportunities presented by these development partners have not been fully harnessed. Given the right incentives, the private sector, for example, can provide effective and sustainable investment and innovation to help in the fight against hunger. In many countries, however, private companies face a lack of incentives and a poor business operating environment, including poor property rights. Emerging economy donors are now playing an increasing role in providing development assistance, but have not yet been fully integrated into the global food security agenda. Adopt a Country-Led, Bottom-Up Approach Effective, efficient, and sustainable policies that are well adapted to the local context can help countries maximize the local impact of the global agenda and tap external development assistance, which increasingly requires approaches that are country led. Successful reforms will be not only country driven, but also local in nature, with poor people acting as a driving force in the development process. At the same time, some issues—like climate change, trade, and control of disease—must be addressed at the global level. The task for individual countries is then to digest and integrate these global issues in developing their own strategies at the country level. Design Policies Using Evidence and Experiments Pilot projects and policy experiments have the potential to improve policymaking by giving decisionmakers information about what works before policies are implemented across the board. Experimentation can improve the success rate of reforms as successful pilot projects are scaled up and unsuccessful policy options are eliminated. To succeed with this approach, policymakers need to allow impartial monitoring of experiments and rapidly transform the lessons learned into large-scale reforms. These changes can create an environment in which policies are continually tried, tested, adjusted, and tried again before being scaled up. Walk the Walk Decisionmakers at the global, regional, and national levels have made commitments to policies and investments for enhancing food security, but they have often failed to meet those commitments. For example, in 2003, African heads of state pledged that their governments would allocate 10 percent of national public budgets to the agricultural sector by 2008, but data for 2007 show that only a handful of countries had met the 10 percent target. These financial commitments must be supported with strong institutions and governance at the global, regional, and national levels and monitored in a timely and transparent fashion. Scaling Up “Business as Unusual” Some aspects of this “business as unusual” approach have already been successful in a few countries, but they need to be scaled up and extended to new countries to have a real impact on the reduction of global hunger. On a larger scale, the global food governance system itself needs to be reformed to work better. Reforms should include (1) improving existing institutions and creating an umbrella structure for food and agriculture; (2) forming government-to-government systems for decisionmaking on agriculture, food, and nutrition; and (3) explicitly engaging the new players in the global food system—the private sector and civil society—together with national governments in new or reorganized international organizations and agreements. A combination of all three options, with a leading role for emerging economies, is required. Finally, though global and national actors have distinct roles to play, it is important that they work together, combining their efforts to fight poverty and hunger. A stronger system of mutual accountability between the two groups would help keep progress on track." from TextAgricultural development -- Developing countries, Developing countries -- Economic policy, Hunger -- Developing countries, Millennium Development Goals (MDG), Policies, Poverty -- Developing countries, Rural development -- Developing countries, Social protection,
Predominance of Methicillin Resistant Staphylococcus Aureus -ST88 and New ST1797 causing Wound Infection and Abscesses.
Get PDFAlthough there has been a worldwide emergence and spread of methicillin-resistant Staphylococcus aureus (MRSA), little is known about the molecular epidemiology of MRSA in Tanzania. In this study, we characterized MRSA strains isolated from clinical specimens at the Bugando Medical Centre, Tanzania, between January and December 2008. Of 160 S. aureus isolates from 600 clinical specimens, 24 (15%) were found to be MRSA. Besides molecular screening for the Panton Valentine leukocidin (PVL) genes by PCR, MRSA strains were further characterized by Multi-Locus Sequence Typing (MLST) and spa typing. Despite considerable genetic diversity, the spa types t690 (29.1%) and t7231 (41.6%), as well as the sequence types (ST) 88 (54.2%) and 1797 (29.1%), were dominant among clinical isolates. The PVL genes were detected in 4 isolates; of these, 3 were found in ST 88 and one in ST1820. Resistance to erythromycin, clindamicin, gentamicin, tetracycline and co-trimoxazole was found in 45.8%, 62.5%, 41.6%, 45.8% and 50% of the strains, respectively. We present the first thorough typing of MRSA at a Tanzanian hospital. Despite considerable genetic diversity, ST88 was dominant among clinical isolates at the Bugando Medical Centre. Active and standardized surveillance of nosocomial MRSA infection should be conducted in the future to analyse the infection and transmission rates and implement effective control measures
Reconciling food security and bioenergy: priorities for action
Get PDFUnderstanding the complex interactions among food security, bioenergy sustainability, and resource management requires a focus on specific contextual problems and opportunities. The United Nations’ 2030 Sustainable Development Goals place a high priority on food and energy security; bioenergy plays an important role in achieving both goals. Effective food security programs begin by clearly defining the problem and asking, ‘What can be done to assist people at high risk?’ Simplistic global analyses, headlines, and cartoons that blame biofuels for food insecurity may reflect good intentions but mislead the public and policymakers because they obscure the main drivers of local food insecurity and ignore opportunities for bioenergy to contribute to solutions. Applying sustainability guidelines to bioenergy will help achieve near- and long-term goals to eradicate hunger. Priorities for achieving successful synergies between bioenergy and food security include the following: (1) clarifying communications with clear and consistent terms, (2) recognizing that food and bioenergy need not compete for land and, instead, should be integrated to improve resource management, (3) investing in technology, rural extension, and innovations to build capacity and infrastructure, (4) promoting stable prices that incentivize local production, (5) adopting flex crops that can provide food along with other products and services to society, and (6) engaging stakeholders to identify and assess specific opportunities for biofuels to improve food security. Systematic monitoring and analysis to support adaptive management and continual improvement are essential elements to build synergies and help society equitably meet growing demands for both food and energy
Invasive Bacterial Co-infection in African Children with Plasmodium falciparum Malaria: A Systematic Review.
Get PDFSevere malaria remains a major cause of pediatric hospital admission across Africa. Invasive bacterial infection (IBI) is a recognized complication of Plasmodium falciparum malaria, resulting in a substantially worse outcome. Whether a biological relationship exists between malaria infection and IBI susceptibility remains unclear. We, therefore, examined the extent, nature and evidence of this association. We conducted a systematic search in August 2012 of three major scientific databases, PubMed, Embase and Africa Wide Information, for articles describing bacterial infection among children with P. falciparum malaria using the search string '(malaria OR plasmodium) AND (bacteria OR bacterial OR bacteremia OR bacteraemia OR sepsis OR septicaemia OR septicemia).' Eligiblity criteria also included studies of children hospitalized with malaria or outpatient attendances in sub-Saharan Africa. A total of 25 studies across 11 African countries fulfilled our criteria. They comprised twenty cohort analyses, two randomized controlled trials and three prospective epidemiological studies. In the meta-analysis of 7,208 children with severe malaria the mean prevalence of IBI was 6.4% (95% confidence interval (CI) 5.81 to 6.98%). In a further meta-analysis of 20,889 children hospitalised with all-severity malaria and 27,641 children with non-malarial febrile illness the mean prevalence of IBI was 5.58 (95% CI 5.5 to 5.66%) in children with malaria and 7.77% (95% CI 7.72 to 7.83%) in non-malaria illness. Ten studies reported mortality stratified by IBI. Case fatality was higher at 81 of 336, 24.1% (95% CI 18.9 to 29.4) in children with malaria/IBI co-infection compared to 585 of 5,760, 10.2% (95% CI 9.3 to 10.98) with malaria alone. Enteric gram-negative organisms were over-represented in malaria cases, non-typhoidal Salmonellae being the most commonest isolate. There was weak evidence indicating IBI was more common in the severe anemia manifestation of severe malaria. The accumulated evidence suggests that children with recent or acute malaria are at risk of bacterial infection, which results in an increased risk of mortality. Characterising the exact nature of this association is challenging due to the paucity of appropriate severity-matched controls and the heterogeneous data. Further research to define those at greatest risk is necessary to target antimicrobial treatment
Susceptibility Status of Malaria Vectors to Insecticides Commonly used for Malaria Control in Tanzania.
Get PDFThe aim of the study was to monitor the insecticide susceptibility status of malaria vectors in 12 sentinel districts of Tanzania. WHO standard methods were used to detect knock-down and mortality in the wild female Anopheles mosquitoes collected in sentinel districts. The WHO diagnostic doses of 0.05% deltamethrin, 0.05% lambdacyhalothrin, 0.75% permethrin and 4% DDT were used. The major malaria vectors in Tanzania, Anopheles gambiae s.l., were susceptible (mortality rate of 98-100%) to permethrin, deltamethrin, lambdacyhalothrin and DDT in most of the surveyed sites. However, some sites recorded marginal susceptibility (mortality rate of 80-97%); Ilala showed resistance to DDT (mortality rate of 65% [95% CI, 54-74]), and Moshi showed resistance to lambdacyhalothrin (mortality rate of 73% [95% CI, 69-76]) and permethrin (mortality rate of 77% [95% CI, 73-80]). The sustained susceptibility of malaria vectors to pyrethroid in Tanzania is encouraging for successful malaria control with Insecticide-treated nets and IRS. However, the emergency of focal points with insecticide resistance is alarming. Continued monitoring is essential to ensure early containment of resistance, particularly in areas that recorded resistance or marginal susceptibility and those with heavy agricultural and public health use of insecticides
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.
