Data Quality Control
- Data Quality:
- Frontier Strategy Group (FSG) analysts update the raw data every six months by pulling the most recently available data from each source. Forecasts are developed using guidance from FSG’s research analysts via a proprietary algorithm, or are pulled directly from the source if available. Additionally, analysts also spot-check all of the data and index scores to ensure high quality information.
- Technical Data Information:
- Data can be accessed via Excel files at this link: http://www.ricebowlindex.com/the-index/technical-aspects/sources/
- The format of the Excel files includes a tab with the raw data for each of the index scores, as well as a tab at the end with the aggregated index values. Sources can be found for each data series in the last column of each of the index tabs.
- We recommend site visitors use Excel for most types of analysis of our data sets. For more sophisticated analysis, we recommend site visitors use R.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License
The Four Rubrics
The RBI consists of four rubrics: Farm-level Factors, Environmental Factors, Policy and Trade, and Demand and Price. Each rubric in turn comprises a set of indicators (metrics or proxies) which may be considered to have a direct or indirect enabling or disabling effect on food security. Each metric is given a weight to indicate its relative importance in this rubric.
Policy and Trade
|Ecosystem vitality, biodiversity and habitat||1%|
|Ecosystem vitality, agriculture||3%|
|Ecosystem vitality, Fisheries||3%|
|Production of biodiesel and ethanol, gallons millions||2%|
|Political stability and absence of violence/terrorism||3%|
|Logistics performance index||3%|
|Ease of doing business ranking||3%|
|Government spending, US$ per capita||2%|
|Intellectual property rights index||3%|
|Net trade in agricultural products, US$ ‘000||2%|
|Road density per 100 square km of land area||3%|
|Domestic credit to private sector, % of GDP||3%|
|Arable land, ‘000 ha||4%|
|Land equipped for irrigation, ha||2%|
|Cereal yield, kg per ha||4%|
|Mobile phone subscriptions, per 100 people||3%|
|Unit labor cost index, %YOY||2%|
|Improved water source, rural, % of rural population with access||3%|
|Adult literacy rate, % aged 15 and above||1%|
|Vulnerability to extreme weather||4%|
|Vulnerability to sea-level rise||4%|
|Vulnerability to agricultural productivity loss||4%|
|Ecosystem vitality, forestry||3%|
|Electric power consumption, kWh per capita||2%|
|Total internal renewable water resources, qm per capita||5%|
|Freshwater withdrawal as % of total renewable water resources||3%|
Demand and Price
|Domestic food price level index||3%|
|Food supply per capita, calories per day||4%|
|Change in oil imports, %YOY, ‘000 bbl per day||1%|
|Consumer price index, %YOY||5%|
|Urban population, number %YOY||3%|
|Protein supply quantity, g per capita per day||4%|
The set of metrics comprising each rubric is not intended or claimed to be exhaustive; however, the conceptual framework used in the Rice Bowl Index is a pragmatic one and selection of metrics is based not only on their importance to the rubric but also on the availability and consistent quality of data across most countries. At times, specific metrics are used as proxy (e.g. mobile phone subscribers as a proxy for access to information).
The weights for each metric are intended to reflect the significance or ‘importance’ of each metric in determining the result of the index. As currently developed and contained in the RBI, the weights were determined subjectively by Syngenta in consultation with Frontier Strategy Group and approved by the RBI Board of food security experts. The weights as they stand represent one view and can be changed should it be considered appropriate and to also support “what-if” analysis. The weights for each metric are used to calculate a country score for a particular metric. A formula is used to calculate the weighted score of each metric for each country, relative to other countries in a set.
The metrics included across the RBI have a variety of units, for example, kg, ha or $. However, the calculations normalize each value relative only to its ‘peers’ within the same metric across countries. Since values are being normalized relative only to values with like units, the index does not conflate disparate dimensions within or across countries.
An illustrative example of an estimated country score is shown below:
Metric = A single economic or industry data point. For example, the metric for Bangladesh’s Cereal yield, in kg/ha, for year 2000 is 3,384.3 kg.
Series = A list of countries for a given metric, e.g. a Cereal yield series for Asia.
Weight = A value, out of 100, assigned to the metric, e.g. 5% for Cereal yield.
The automatic calculations performed by the system treat the weighting as though the total were 1,000 as opposed to 100, so when doing manual calculations everything should be adjusted by a factor of 10.
» read more...
Cereal yield, kg/ha for year 2000
Source: World Bank.
Cereal yield, measured as kilograms per hectare of harvested land, includes wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains.
Production data on cereals relate to crops harvested for dry grain only.
Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.
Last Updated: December 2011
Weighted scores estimated using MarketView formula for year 2000
|Step||Calculation||Rounding Formula||Rounded Values|
Calculating for Bangladesh, Year 2000, using data in the table above.
Absolute value of (3384.3 – 2294.1)/ (2294.1-6435.7) = 0.2632
Multiply by weighting for cereal yield, 5% = 0.2632*5 = 1.3162
Multiply by 10 to account for manual calculation = 13.162
Rounded-off as 13.
» read less...