{"doc_desc":{"title":"WLD_1955-2011_EDAI_v01_M","idno":"DDI_WLD_1955-2011_EDAI_v02_M","prod_date":"2011-02-11","version_statement":{"version":"DDI Document  - Version 02 - (04\/27\/21)\n This version is identical to DDI_WLD_1955-2011_EDAI_v01_M but country field has been updated to capture all the countries covered by survey.\n\n Version 01 (February 2011)"}},"study_desc":{"title_statement":{"idno":"WLD_1955-2011_EDAI_v01_M","title":"Estimates of Distortions to Agricultural Incentives 1955-2011","alt_title":"EDAI 1955-2007","identifiers":[{"type":"DOI","identifier":"https:\/\/doi.org\/10.48529\/7kew-g205"}]},"authoring_entity":[{"name":"Kym Anderson","affiliation":"University of Adelaide"},{"name":"Signe Nelgen","affiliation":"University of Adelaide"},{"name":"Ernesto Valenzuela","affiliation":"University of Adelaide"}],"distribution_statement":{"contact":[{"name":"Development Research Group","affiliation":"World Bank","email":"research@worldbank.org","uri":"http:\/\/go.worldbank.org\/B9W4QTDHR0"}]},"series_statement":{"series_name":"Macroeconomics - Indicators"},"study_info":{"abstract":"The World Bank\u2019s research project on \u201cDistortions to Agricultural Incentives\u201d has produced a core database of Nominal Rates of Assistance to producers, or NRAs, together with a set of Consumer Tax Equivalents, or CTEs, for farm products and a set of Relative Rates of Assistance to farmers in 75 focus countries. This is a detailed core database. \n\nThe vast majority of the world\u2019s poorest households depend on farming for their livelihood. In the past their earnings were often depressed by pro-urban and anti-agricultural biases of their own country\u2019s policies. While progress has been made over the past two decades by numerous developing countries in reducing those policy biases, many trade-reducing price distortions remain intersectorally as well as within the agricultural sector of low-, middle- and high-income countries.\n\nThis project, in seeking to understand the extent, effects of and reasons behind that transformation, began by compiling new estimates of price distortions over the past half century. National country studies were undertaken in more than 50 countries in Africa, Asia, Latin America, and Europe\u2019s transition economies. They were supplemented with similar estimates and analytical narratives of policy trends in 20 high-income countries. Together those countries account for more than 90 percent of the value of global agricultural output. \n\nThe core database provides nominal rates of assistance estimates for the main individual commodities that together account for about 70 percent of the value of farm production in those countries, as well as guesstimates of the NRA for the 30 percent of farm production not covered. Also estimated is the NRA for non-agricultural tradables so as to compute a relative rate of assistance. Consumer tax equivalents are also provided for the covered products in each focus country, along with value of production and consumption at undistorted prices and of trade for each covered product and for non-covered farm products. The working paper no. 4612, available as external resources, serves as the \"methodology paper\" for this first database.","coll_dates":[{"start":"1955","end":"2011","cycle":""}],"nation":[{"name":"Argentina","abbreviation":"ARG"},{"name":"Australia","abbreviation":"AUS"},{"name":"Austria","abbreviation":"AUT"},{"name":"Belgium","abbreviation":"BEL"},{"name":"Benin","abbreviation":"BEN"},{"name":"Burkina Faso","abbreviation":"BFA"},{"name":"Bulgaria","abbreviation":"BGR"},{"name":"Brazil","abbreviation":"BRA"},{"name":"Canada","abbreviation":"CAN"},{"name":"Switzerland","abbreviation":"CHE"},{"name":"Chile","abbreviation":"CHL"},{"name":"China","abbreviation":"CHN"},{"name":"C\u00f4te d'Ivoire","abbreviation":"CIV"},{"name":"Cameroon","abbreviation":"CMR"},{"name":"Colombia","abbreviation":"COL"},{"name":"Cyprus","abbreviation":"CYP"},{"name":"Czech Republic","abbreviation":"CZE"},{"name":"Germany","abbreviation":"DEU"},{"name":"Denmark","abbreviation":"DNK"},{"name":"Dominican Republic","abbreviation":"DOM"},{"name":"Ecuador","abbreviation":"ECU"},{"name":"Egypt, Arab Rep.","abbreviation":"EGY"},{"name":"Spain","abbreviation":"ESP"},{"name":"Estonia","abbreviation":"EST"},{"name":"Ethiopia","abbreviation":"ETH"},{"name":"Finland","abbreviation":"FIN"},{"name":"France","abbreviation":"FRA"},{"name":"United Kingdom","abbreviation":"GBR"},{"name":"Ghana","abbreviation":"GHA"},{"name":"Greece","abbreviation":"GRC"},{"name":"Hungary","abbreviation":"HUN"},{"name":"Indonesia","abbreviation":"IDN"},{"name":"India","abbreviation":"IND"},{"name":"Ireland","abbreviation":"IRL"},{"name":"Iceland","abbreviation":"ISL"},{"name":"Israel","abbreviation":"ISR"},{"name":"Italy","abbreviation":"ITA"},{"name":"Japan","abbreviation":"JPN"},{"name":"Kazakhstan","abbreviation":"KAZ"},{"name":"Kenya","abbreviation":"KEN"},{"name":"Korea, Rep.","abbreviation":"KOR"},{"name":"Sri Lanka","abbreviation":"LKA"},{"name":"Lithuania","abbreviation":"LTU"},{"name":"Latvia","abbreviation":"LVA"},{"name":"Morocco","abbreviation":"MAR"},{"name":"Madagascar","abbreviation":"MDG"},{"name":"Mexico","abbreviation":"MEX"},{"name":"Mali","abbreviation":"MLI"},{"name":"Mozambique","abbreviation":"MOZ"},{"name":"Malaysia","abbreviation":"MYS"},{"name":"Nigeria","abbreviation":"NGA"},{"name":"Nicaragua","abbreviation":"NIC"},{"name":"Netherlands","abbreviation":"NLD"},{"name":"Norway","abbreviation":"NOR"},{"name":"New Zealand","abbreviation":"NZL"},{"name":"Pakistan","abbreviation":"PAK"},{"name":"Philippines","abbreviation":"PHL"},{"name":"Poland","abbreviation":"POL"},{"name":"Portugal","abbreviation":"PRT"},{"name":"Russian Federation","abbreviation":"RUS"},{"name":"Sudan","abbreviation":"SDN"},{"name":"Senegal","abbreviation":"SEN"},{"name":"Slovak Republic","abbreviation":"SVK"},{"name":"Slovenia","abbreviation":"SVN"},{"name":"Sweden","abbreviation":"SWE"},{"name":"Chad","abbreviation":"TCD"},{"name":"Togo","abbreviation":"TGO"},{"name":"Thailand","abbreviation":"THA"},{"name":"Turkiye","abbreviation":"TUR"},{"name":"Taiwan, China","abbreviation":"TWN"},{"name":"Tanzania","abbreviation":"TZA"},{"name":"Uganda","abbreviation":"UGA"},{"name":"Ukraine","abbreviation":"UKR"},{"name":"United States","abbreviation":"USA"},{"name":"Viet Nam","abbreviation":"VNM"},{"name":"South Africa","abbreviation":"ZAF"},{"name":"Zambia","abbreviation":"ZMB"},{"name":"Zimbabwe","abbreviation":"ZWE"},{"name":"Czechoslovakia","abbreviation":"CSK"}],"data_kind":"Aggregate data [agg]","notes":"The core database files contain, among others, the following variables for each focus country or for regional aggregates of focus countries:\n*Nominal rates of assistance (NRA), by individual covered farm product and by policy instrument \n*Nominal rate of assistance for all agricultural tradables (incl. non-covered products) \n*Nominal rate of assistance for all non-agricultural tradables \n*Relative rate of assistance (RRA) \n*Consumer tax equivalent (CTE), by individual covered farm product \n*Official foreign exchange rate \n*Equilibrium exchange rate used in NRA calculations \n*Volume of production, by individual covered farm product \n*Domestic producer farmgate price, by individual covered farm product \n*Value of production at undistorted prices for each covered farm product \n*Value of consumption at undistorted prices for each covered farm product \n*Share of production exported, share of consumption imported, and self-sufficiency ratio, by individual covered farm product \n*Population, total and rural \n*Employment, total and agricultural \n*GDP per capita, in constant year 2000 US$ \n*Gross subsidy equivalent to farmers, in constant year 2000 US$"},"method":{"data_collection":{"coll_mode":"Other [oth]"}},"data_access":{"dataset_use":{"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n- the Identification of the Primary Investigator\n- the title of the survey (including acronym and year of implementation)\n- the survey reference number\n- the source and date of download\n\nExample:\n\nKym Anderson and Ernesto Valenzuela. Estimates of Distortions to Agricultural Incentives (EDAI) 1955-2007. Ref. WLD_2007_EDAI_v01_M. Dataset downloaded from http:\/\/microdata.worldbank.org on [date].","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}},"tags":[{"tag":"DOI"}],"schematype":"survey"}