bonndata (Rheinische Friedrich-Wilhelms-Universität Bonn)
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Survey on under-five children in Fogera and Mecha districts of Amhara regional state, Ethiopia, 2014
No full textThe child module questionnaire was used to collected information about child feeding practices such as exclusive breastfeeding during the first six months of life, current breastfeeding and complementary foods, prevalence of illness in the previous two weeks period (such as diarrhea, malaria, fever, pneumonia, and cough), immunization records and anthropometric measurements.
Purpose: To examine the health and nutrition status of under-five children in the study areas
Factionalised Elites, Cohesion Indicator (Fragile State Index) 2018
No full textThe Factionalized Elites indicator considers the fragmentation of state institutions along ethnic, class, clan, racial or religious lines, as well as and brinksmanship and gridlock between ruling elites. It also factors the use of nationalistic political rhetoric by ruling elites, often in terms of nationalism, xenophobia, communal irredentism (e.g., a “greater Serbia”) or of communal solidarity (e.g., “ethnic cleansing” or “defending the faith”). In extreme cases, it can be representative of the absence of legitimate leadership widely accepted as representing the entire citizenry. The Factionalized Elites indicator measures power struggles, political competition, political transitions, and where elections occur will factor in the credibility of electoral processes (or in their absence, the perceived legitimacy of the ruling class).
Quality/Lineage: The data is downloaded from the above link http://fundforpeace.org/fsi/indicators/c2/ and manipulated only table format keeping the value same for all the countries as the requirement of the Strive database. The map is created based on the values of the country using rworldmap package in R
Follow-up survey on under-five children in Fogera and Mecha districts of Amhara regional state, Ethiopia, 2014
No full textThe follow-up surveys were administered between April and July 2014 after completing the baseline survey by the end of March 2014. The aim of the survey was to collect information on under-five children heath status—such as diarrhea, fever, vomiting, constant cough, stomach pain/cramps and skin infections in the preceding two weeks. This data collection process requires multiple successive visits to the households, and each household has been visited every fortnightly for a period of three months to record the health status of the children. For this purpose, one-page child health calendar questionnaire was developed to record information about symptoms of a particular illness; how long the symptoms stay; and what treatment they seek for if any. The data collection was done by health and agriculture extension workers who work in the selected kebeles. Training was given to the enumerators during the field organization for the follow-up household survey. In most cases, the data collectors ask the child’s primary caretaker—usually the mother or another adult woman household member.
Purpose: To examine the longitudinal diarrheal prevalence among under-five children in the study areas
Macroeconomic model (GAMS) for poverty reduction in Mexico
No full textA Computable General Equilibrium (CGE) model in a bottom-up approach - based on microfoundations - and a Social Accounting Matrix (SAM) for the regional economy of Chiapas are built.
Methodology: This research applies a Computable General Equilibrium (CGE) model. It is a system of equations that describes an entire economy and all the interactions between productive sectors, commodity and factor markets, and institutions. All of the equations are solved simultaneously to find an economy-wide equilibrium in which demand and supply quantities are equal in every market at a certain level of prices (Burfisher, 2011). Two of the features of this model are that, on one hand, it implements a “bottom-up” approach, that is, it is focused on individual markets and economic agents. On the other hand, it is partially synthetic. In other words, most parameters can be calibrated with data from the SAM.
Data framework: A Social Accounting Matrix (SAM) is a balanced square matrix that represents all income and expenditure flows between productive sectors, markets, and economic agents of an economy at a given period of time (Müller, Perez & Hubertus, 2009). It is based on the double entry bookkeeping in accounting, which requires that total revenue equals total expenditure in each single account included in the SAM (Breisinger, Thomas & Thurlow, 2010).
The main features of the Chiapas SAM are that production activities are broken down in 10 sectors, according to the North American Industry Classification System (NAICS). There is one commodity per economic activity. Factors of production are disaggregated into formal and informal labor, and capital. Direct taxes are broken up into activity tax, social security contributions, household and corporate income taxes, ‘tenencia’ tax (ownership tax, i.e. a tax associated with the possession or use of vehicles), and regional payroll tax (‘nomina’). Indirect taxes, in turn, are value-added, sales and export taxes, and import tariffs. Subsidies on production by economic activity are also included. Households are disaggregated by income quintiles. Social transfers are split in non-conditional (Procampo, universal pension, PAL-Sin Hambre , temporary employment program, and the regional program Amanecer ) and Oportunidades. The latter is also broken down into its five components: food, elderly, education, child, and energy. The introduction of conditional cash transfers in the SAM is particularly relevant because it allows assessing the impact of changes in their amount and distribution on household income, poverty reduction, income inequality, and economic growth at the regional level.
Data sources:
- National Institute of Statistics and Geography (INEGI):
2012 National Employment and Occupation Survey
2013 Chiapas Statistical Yearbook
2012 National Household Income-Expenditure Survey
2012 Chiapas Statistical Perspective
2003-2012 Goods and Services Accounts (SCNM)
2003-2012 Institutional Sector Accounts (SCNM)
2008 Input-Output Table
2008 Supply and Use Tables
- Chiapas State Committee of Statistical and Geographical Information (CEIEG):
2012 Chiapas Employment and Occupation Survey
2012 Chiapas Monthly Statistical Reports of IMSS-insured Workers
- Federal Ministry of Labor and Social Welfare (STYPS):
2012 IMSS-registered Daily Salary by Economic Activity
2012 IMSS-insured Workers
Quality/Lineage: With the raw data a Social Accounting Matrix for the regional economy of Chiapas was built
Features:
- Oportunidades broken down by component
- Other non-conditional social transfers such as Procampo, PAL-Sin Hambre, Employment program, Universal pension, and the regional program 'Amanecer'
- Informal wages
- Satellites tables of formal and informal employment
- Productive activities according to the North American Industry Classification System (NAICS) used in Mexico, Canada, and the United States of America
- 10 economic activities
- 10 Commodities (one per economic activity)
- Factors of production: formal and informal labor and capital
Purpose: 1. To assess the opportunity cost of financing "Oportunidades", Mexico's conditional cash transfers program, and its implications for rural development and rural economic growth in the regional setting of Chiapas. Moreover,
2. Pro-growth and pro-poor tax structures are also evaluated by applying standard economic analysis tools and modeling to substantially raise the federal non-oil tax revenue to finance social policy for poverty and inequality reduction.
Dissertation:
Viveros Añorve, J. L. (2015): The opportunity cost of financing "Oportunidades": a general equilibrium assessment for poverty reduction in Mexico. Ph.D. dissertation. Center for Development Research, Faculty of Agriculture, University of Bon
Getting Credit, Ranking of Economy, 2017
No full textEconomies are ranked on their ease of doing business, from 1–186. A high ease of doing business ranking means the regulatory environment is more conducive to the starting and operation of a local firm. The rankings are determined by sorting the aggregate distance to frontier scores on 10 topics, each consisting of several indicators, giving equal weight to each topic. The rankings for all economies are benchmarked to June 2017.
Quality/Lineage: The data is downloaded from the above link http://www.doingbusiness.org/rankings and manipulated only table format keeping the value same for all the countries as the requirement of the Strive database. The map is created based on the values of the country using rworldmap package in R
Agronomic Radiation Use Efficiency (RUE) in Maize Biomass in Ashanti region and Brong-Ahafo region in Ghana (Map) under three fertilizer application rates i.e., 4 kg/ha Nitrogen (current application rate); 45 kg/ha Nitrogen and 15 kg/ha Phosphorous; and 135 kg/ha Nitrogen and 45 kg/ha Phosphorous, 1992-2010
No full textAgronomic Radiation Use Efficiency (RUE) for maize biomass in Ashanti region and Brong-Ahafo region in Ghana has been estimated under three different fertilizer application rates using crop model LINTUL5 embedded into the modeling framework SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management.
Purpose: To increase food production, identifying the regions with untapped production capacity is of prime importance and can be achieved by quantitative and spatially explicit estimates of Agronomic Radiation use efficiency, thus considering the spatial variation in environment and the production system
Average Bioeconomy Typology Indicators of World, 2010 -2015
No full textThe file consists of country wise database of whole world related to bioeconomy typology indicators collected from different online sources with following headings which are as follows: Importance of bio-based economic sectors in agriculture, Forestry, High-tech bioeconomy and bioenergy, Natural Resources Endownment, Evaluate against indicator of Bioeconomy strategy, value added sector data, Fragile state indexes, Income inequality and gini coeffiecient, social progress index.
Quality/Lineage: The data were downloaded from different sources and arranged as per the countries database in a single table.
Purpose: The data was collected to analyze the bioeconomy status in the countries of the whole world
Crop calender of Maize in Ethiopia, 1950-2005
No full textThe table includes sowing, harvesting dates, sowing/planting rates of Maize in different Agro-ecological zones in Ethiopia.
Quality/Lineage: FAO (http://www.fao.org/agriculture/seed/cropcalendar/welcome.do)
Classification of Business Challenges and Opportunities in Ethiopia, 2008-2011
No full textThe potential of different business approaches to reduce poverty and marginality depends on the characteristics of different regions and people living in these regions. Here, (a) population density, (b) accessibility, e.g. in terms of mobile phone, internet and road connections, as well as (c) the predominant form of livelihood and/or farming systems may be important factors determining market sizes and transaction costs and thus incentives to invest in these markets.
This map is an overlay of these different indicators.
Greenish colors show irrigated or perennial areas, brownish colors pastoralist, agro-pastoralist and arid areas and reddish colors indicate areas dominated by different other farming patterns. The lighter the color the lower the population and road density. For the classification of population and connectivity values being ‘high’ or ‘low’ the national mean value is used as threshold.
Data:
Population density: CIESIN (2011) Connectivity: CSA et al. (2008)
Farming systems: HarvestChoice (2001)
Quality/Lineage: Data is from different time periods and different sources. To identify the data sources, please look at the abstract.
Purpose: Amongst other factors, the potential of different business approaches to reduce poverty and marginality depends on the characteristics of different regions and people living in these regions. Here, (a) population density, (b) accessibility, e.g. in terms of mobile phone, internet and road connections, as well as (c) the predominant form of livelihood and/or farming systems may be important factors determining market sizes and transaction costs and thus incentives to invest in these markets:
If population density is low, it is more difficult to create a market as, ceteris paribus, market size is smaller. Transaction costs might increase, amongst other reasons, because the search for customers is likely to be more difficult if people are widely dispersed.
Accessibility in terms of road connections is important to reduce transportation costs. Furthermore, transaction costs rise even more than proportionally with distance (Staal et al., 1997). However, such costs can be reduced by reducing the need to travel, i.e. the possibilities to exchange information with other means such as ICT (De Silva and Ratnadiwakara, 2008). Thus, accessibility in the sense of a general connection to other areas and people is an important element determining transaction costs and thus incentives for companies to invest in a certain region.
And finally, in a country like Ethiopia the predominant form of livelihood may play an important role. Pastoralists move around and are thus more difficult to locate. As a result, it may be more costly to create a market because it is more difficult to establish stable supply chains or the established supply chains are only usable for a certain part of the year. In non-pastoralist areas, people in regions where two or three harvests per year are possible may enjoy less volatile cash flows, which allows for stabler consumption. Furthermore, risk is reduced as incomes do not depend on only one harvest per year. Less volatility in consumption reduces transaction costs for firms as they need to spend less on information about and adaptation to seasonal changes. Furthermore, especially for companies selling agricultural inputs, it may be more worthwhile to invest in supply chains in regions where more harvests per year are possible as people may buy inputs more than once a year
Agronomic Radiation Use Efficiency (RUE) in Maize Stover Biomass in Ethiopia (Map) under unfertilized conditions and under two fertilizer application rates i.e., 20 kg/ha Nitrogen and 6.6 kg/ha Phosphorous and 225 kg/ha Nitrogen and 75 kg/ha Phosphorous, 2004-2010
No full textAgronomic Radiation Use Efficiency (RUE) for maize stover biomass across the Ethiopia has been estimated under unfertilized conditions and under two different fertilizer application rates using crop model LINTUL5 embedded into the modeling framework SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management.
Purpose: To increase food production, identifying the regions with untapped production capacity is of prime importance and can be achieved by quantitative and spatially explicit estimates of Agronomic Radiation use efficiency, thus considering the spatial variation in environment and the production system