From Guesstimates to GPStimates : Land Area Measurement and Implications for Agricultural Analysis
Land area measurement is a fundamental component of agricultural statistics and analysis. Yet, commonly employed self-reported land area measures used in most analysis are not only potentially measured with error, but these errors may be correlated with agricultural outcomes. Measures employing Glob...
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| creator | Carletto, Calogero Gourlay, Sydney Winters, Paul |
| description | Land area measurement is a fundamental
component of agricultural statistics and analysis. Yet,
commonly employed self-reported land area measures used in
most analysis are not only potentially measured with error,
but these errors may be correlated with agricultural
outcomes. Measures employing Global Positioning Systems, on
the other hand, while not perfect especially on smaller
plots, are likely to provide more precise measures and
errors less correlated with agricultural outcomes. This
paper uses data from four African countries to compare the
use of self-reported and Global Positioning Systems land
measures to (1) examine the differences between the
measures, (2) identify the sources of the differences, and
(3) assess the implications of the different measures on
agricultural analysis focusing on the inverse productivity
relationship. The results indicate that self-reported land
areas systematically differ from Global Positioning Systems
land measures and that this difference leads to potentially
biased estimates of the relationship between land and productivity. |
| format | Book |
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component of agricultural statistics and analysis. Yet,
commonly employed self-reported land area measures used in
most analysis are not only potentially measured with error,
but these errors may be correlated with agricultural
outcomes. Measures employing Global Positioning Systems, on
the other hand, while not perfect especially on smaller
plots, are likely to provide more precise measures and
errors less correlated with agricultural outcomes. This
paper uses data from four African countries to compare the
use of self-reported and Global Positioning Systems land
measures to (1) examine the differences between the
measures, (2) identify the sources of the differences, and
(3) assess the implications of the different measures on
agricultural analysis focusing on the inverse productivity
relationship. The results indicate that self-reported land
areas systematically differ from Global Positioning Systems
land measures and that this difference leads to potentially
biased estimates of the relationship between land and productivity.</description><language>eng</language><publisher>World Bank, Washington, DC</publisher><subject>AGRICULTURAL DEVELOPMENT ; AGRICULTURAL INFORMATION ; AGRICULTURAL INNOVATION ; AGRICULTURAL PRODUCTION ; AGRICULTURE ; CONSTANT RETURNS TO SCALE ; COUNTRY CASE STUDIES ; CROPS ; DATA COLLECTION ; DEVELOPMENT ECONOMICS ; DEVELOPMENT POLICY ; DEVELOPMENT RESEARCH ; DRIVING ; ECONOMETRIC ANALYSIS ; ECONOMETRICS ; ECONOMICS ; ELASTICITY ; EQUATIONS ; FARMERS ; FARMS ; FIELD EXPERIMENTS ; GENDER ; GLOBAL POSITIONING SYSTEM ; GLOBAL POSITIONING SYSTEMS ; GPS ; INNOVATION ; inverse productivity relationship ; land measurement ; LIVING STANDARDS ; survey design</subject><creationdate>2013</creationdate><rights>CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo/ World Bank</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><relation>Policy Research Working Paper</relation></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>307,780,784,787,18982</link.rule.ids><linktorsrc>$$Uhttps://hdl.handle.net/10986/15910$$EView_record_in_World_Bank$$FView_record_in_$$GWorld_Bank$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Carletto, Calogero</creatorcontrib><creatorcontrib>Gourlay, Sydney</creatorcontrib><creatorcontrib>Winters, Paul</creatorcontrib><title>From Guesstimates to GPStimates : Land Area Measurement and Implications for Agricultural Analysis</title><description>Land area measurement is a fundamental
component of agricultural statistics and analysis. Yet,
commonly employed self-reported land area measures used in
most analysis are not only potentially measured with error,
but these errors may be correlated with agricultural
outcomes. Measures employing Global Positioning Systems, on
the other hand, while not perfect especially on smaller
plots, are likely to provide more precise measures and
errors less correlated with agricultural outcomes. This
paper uses data from four African countries to compare the
use of self-reported and Global Positioning Systems land
measures to (1) examine the differences between the
measures, (2) identify the sources of the differences, and
(3) assess the implications of the different measures on
agricultural analysis focusing on the inverse productivity
relationship. The results indicate that self-reported land
areas systematically differ from Global Positioning Systems
land measures and that this difference leads to potentially
biased estimates of the relationship between land and productivity.</description><subject>AGRICULTURAL DEVELOPMENT</subject><subject>AGRICULTURAL INFORMATION</subject><subject>AGRICULTURAL INNOVATION</subject><subject>AGRICULTURAL PRODUCTION</subject><subject>AGRICULTURE</subject><subject>CONSTANT RETURNS TO SCALE</subject><subject>COUNTRY CASE STUDIES</subject><subject>CROPS</subject><subject>DATA COLLECTION</subject><subject>DEVELOPMENT ECONOMICS</subject><subject>DEVELOPMENT POLICY</subject><subject>DEVELOPMENT RESEARCH</subject><subject>DRIVING</subject><subject>ECONOMETRIC ANALYSIS</subject><subject>ECONOMETRICS</subject><subject>ECONOMICS</subject><subject>ELASTICITY</subject><subject>EQUATIONS</subject><subject>FARMERS</subject><subject>FARMS</subject><subject>FIELD EXPERIMENTS</subject><subject>GENDER</subject><subject>GLOBAL POSITIONING SYSTEM</subject><subject>GLOBAL POSITIONING SYSTEMS</subject><subject>GPS</subject><subject>INNOVATION</subject><subject>inverse productivity relationship</subject><subject>land measurement</subject><subject>LIVING STANDARDS</subject><subject>survey design</subject><fulltext>true</fulltext><rsrctype>book</rsrctype><creationdate>2013</creationdate><recordtype>book</recordtype><sourceid>VO9</sourceid><recordid>eNqdi8sKglAQQN20iOof5gcCpQfZTiItKAhqL6OOcvF6R2auiH8fQf1Aq8M5cOZBkQp3kA2k6k2HnhQ8Q_Z4_uwIN3QVJEIId0IdhDpyHj7x2vXWlOgNO4WaBZJGTDlYPwhaSBzaSY0ug1mNVmn15SLYpufX6bIeWWxVoGtz7sm1jkdLVUNCPavxLFMehfFhn0e7OAo3f25vKKhOVA</recordid><startdate>201307</startdate><enddate>201307</enddate><creator>Carletto, Calogero</creator><creator>Gourlay, Sydney</creator><creator>Winters, Paul</creator><general>World Bank, Washington, DC</general><scope>VO9</scope></search><sort><creationdate>201307</creationdate><title>From Guesstimates to GPStimates : Land Area Measurement and Implications for Agricultural Analysis</title><author>Carletto, Calogero ; Gourlay, Sydney ; Winters, Paul</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-worldbank_openknowledgerepository_10986_159103</frbrgroupid><rsrctype>books</rsrctype><prefilter>books</prefilter><language>eng</language><creationdate>2013</creationdate><topic>AGRICULTURAL DEVELOPMENT</topic><topic>AGRICULTURAL INFORMATION</topic><topic>AGRICULTURAL INNOVATION</topic><topic>AGRICULTURAL PRODUCTION</topic><topic>AGRICULTURE</topic><topic>CONSTANT RETURNS TO SCALE</topic><topic>COUNTRY CASE STUDIES</topic><topic>CROPS</topic><topic>DATA COLLECTION</topic><topic>DEVELOPMENT ECONOMICS</topic><topic>DEVELOPMENT POLICY</topic><topic>DEVELOPMENT RESEARCH</topic><topic>DRIVING</topic><topic>ECONOMETRIC ANALYSIS</topic><topic>ECONOMETRICS</topic><topic>ECONOMICS</topic><topic>ELASTICITY</topic><topic>EQUATIONS</topic><topic>FARMERS</topic><topic>FARMS</topic><topic>FIELD EXPERIMENTS</topic><topic>GENDER</topic><topic>GLOBAL POSITIONING SYSTEM</topic><topic>GLOBAL POSITIONING SYSTEMS</topic><topic>GPS</topic><topic>INNOVATION</topic><topic>inverse productivity relationship</topic><topic>land measurement</topic><topic>LIVING STANDARDS</topic><topic>survey design</topic><toplevel>online_resources</toplevel><creatorcontrib>Carletto, Calogero</creatorcontrib><creatorcontrib>Gourlay, Sydney</creatorcontrib><creatorcontrib>Winters, Paul</creatorcontrib><collection>Open Knowledge Repository</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Carletto, Calogero</au><au>Gourlay, Sydney</au><au>Winters, Paul</au><format>book</format><genre>book</genre><ristype>BOOK</ristype><btitle>From Guesstimates to GPStimates : Land Area Measurement and Implications for Agricultural Analysis</btitle><seriestitle>Policy Research Working Paper</seriestitle><date>2013-07</date><risdate>2013</risdate><volume>6550</volume><abstract>Land area measurement is a fundamental
component of agricultural statistics and analysis. Yet,
commonly employed self-reported land area measures used in
most analysis are not only potentially measured with error,
but these errors may be correlated with agricultural
outcomes. Measures employing Global Positioning Systems, on
the other hand, while not perfect especially on smaller
plots, are likely to provide more precise measures and
errors less correlated with agricultural outcomes. This
paper uses data from four African countries to compare the
use of self-reported and Global Positioning Systems land
measures to (1) examine the differences between the
measures, (2) identify the sources of the differences, and
(3) assess the implications of the different measures on
agricultural analysis focusing on the inverse productivity
relationship. The results indicate that self-reported land
areas systematically differ from Global Positioning Systems
land measures and that this difference leads to potentially
biased estimates of the relationship between land and productivity.</abstract><pub>World Bank, Washington, DC</pub><oa>free_for_read</oa></addata></record> |
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| subjects | AGRICULTURAL DEVELOPMENT AGRICULTURAL INFORMATION AGRICULTURAL INNOVATION AGRICULTURAL PRODUCTION AGRICULTURE CONSTANT RETURNS TO SCALE COUNTRY CASE STUDIES CROPS DATA COLLECTION DEVELOPMENT ECONOMICS DEVELOPMENT POLICY DEVELOPMENT RESEARCH DRIVING ECONOMETRIC ANALYSIS ECONOMETRICS ECONOMICS ELASTICITY EQUATIONS FARMERS FARMS FIELD EXPERIMENTS GENDER GLOBAL POSITIONING SYSTEM GLOBAL POSITIONING SYSTEMS GPS INNOVATION inverse productivity relationship land measurement LIVING STANDARDS survey design |
| title | From Guesstimates to GPStimates : Land Area Measurement and Implications for Agricultural Analysis |
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