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Investigating Volatility in Coffee Prices Along the Ethiopian Coffee Value Chain
The coffee sub-sector is a major contributor to the Ethiopian economy. In addition to accounting for approximately 40 per cent on average of total export earnings, coffee production provides a livelihood for a large proportion of the Ethiopian population in the form of jobs for farmers, local trader...
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Published in: | Agrekon 2011-09, Vol.50 (3), p.90-108 |
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description | The coffee sub-sector is a major contributor to the Ethiopian economy. In addition to accounting for approximately 40 per cent on average of total export earnings, coffee production provides a livelihood for a large proportion of the Ethiopian population in the form of jobs for farmers, local traders, transporters and exporters. Volatility in the price of coffee thus influences a large proportion of the population all along the coffee commodity chain within Ethiopia. This study uses the Autoregressive Conditional Heteroscedasticity/Generalized Autoregressive Conditional Heteroscedasticity (ARCH)/(GARCH) approach to quantify the volatility in the price of coffee. A distinction is made between producer, wholesale and export prices in order to compare the price risk as faced by the respective participants in the coffee chain. The volatility in coffee prices within Ethiopia is also compared to the volatility levels in Brazilian coffee prices, since Brazil is a major coffee producing country in the world. Coffee prices within Ethiopia were found to be more volatile than in Brazil. Producer prices were found to be the most volatile, followed by wholesale prices and export prices respectively. The high level of volatility in producer prices emphasises the need for efficient price risk management tools that should be available to coffee producers in Ethiopia. |
doi_str_mv | 10.1080/03031853.2011.617865 |
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Coffee prices within Ethiopia were found to be more volatile than in Brazil. Producer prices were found to be the most volatile, followed by wholesale prices and export prices respectively. The high level of volatility in producer prices emphasises the need for efficient price risk management tools that should be available to coffee producers in Ethiopia.</description><identifier>ISSN: 2078-0400</identifier><identifier>ISSN: 0303-1853</identifier><identifier>EISSN: 2078-0400</identifier><identifier>DOI: 10.1080/03031853.2011.617865</identifier><language>eng</language><publisher>Taylor & Francis Group</publisher><subject>ARCH/GARCH ; Cash crops ; Coffee ; Commodity market ; crop production ; Economics ; employment ; Export prices ; Exports ; farmers ; heteroskedasticity ; livelihood ; Price rises ; Price volatility ; prices ; Producer price ; risk ; Risk management ; supply chain ; transporters ; Uncertainty ; Volatility</subject><ispartof>Agrekon, 2011-09, Vol.50 (3), p.90-108</ispartof><rights>Copyright Agricultural Economics Association of South Africa 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c459t-f413b98d312a2619106418fc27265dc1602f2acc7bcd1b56750ef1e3dba1d86c3</citedby><cites>FETCH-LOGICAL-c459t-f413b98d312a2619106418fc27265dc1602f2acc7bcd1b56750ef1e3dba1d86c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924,33223</link.rule.ids></links><search><creatorcontrib>Worako, T.K</creatorcontrib><creatorcontrib>Jordaan, H</creatorcontrib><creatorcontrib>van Schalkwyk, H.D</creatorcontrib><title>Investigating Volatility in Coffee Prices Along the Ethiopian Coffee Value Chain</title><title>Agrekon</title><description>The coffee sub-sector is a major contributor to the Ethiopian economy. In addition to accounting for approximately 40 per cent on average of total export earnings, coffee production provides a livelihood for a large proportion of the Ethiopian population in the form of jobs for farmers, local traders, transporters and exporters. Volatility in the price of coffee thus influences a large proportion of the population all along the coffee commodity chain within Ethiopia. This study uses the Autoregressive Conditional Heteroscedasticity/Generalized Autoregressive Conditional Heteroscedasticity (ARCH)/(GARCH) approach to quantify the volatility in the price of coffee. A distinction is made between producer, wholesale and export prices in order to compare the price risk as faced by the respective participants in the coffee chain. The volatility in coffee prices within Ethiopia is also compared to the volatility levels in Brazilian coffee prices, since Brazil is a major coffee producing country in the world. Coffee prices within Ethiopia were found to be more volatile than in Brazil. Producer prices were found to be the most volatile, followed by wholesale prices and export prices respectively. The high level of volatility in producer prices emphasises the need for efficient price risk management tools that should be available to coffee producers in Ethiopia.</description><subject>ARCH/GARCH</subject><subject>Cash crops</subject><subject>Coffee</subject><subject>Commodity market</subject><subject>crop production</subject><subject>Economics</subject><subject>employment</subject><subject>Export prices</subject><subject>Exports</subject><subject>farmers</subject><subject>heteroskedasticity</subject><subject>livelihood</subject><subject>Price rises</subject><subject>Price volatility</subject><subject>prices</subject><subject>Producer price</subject><subject>risk</subject><subject>Risk management</subject><subject>supply chain</subject><subject>transporters</subject><subject>Uncertainty</subject><subject>Volatility</subject><issn>2078-0400</issn><issn>0303-1853</issn><issn>2078-0400</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>8BJ</sourceid><recordid>eNqFkc1PGzEQxVdVkUqB_wCpe-DQS8KMvf7IqUKrlA8hgdTC1fJ67cSVs07tDSj_fY2WIm6c5h1-743mTVWdIswRJJwDBYqS0TkBxDlHITn7VB0SEHIGDcDnd_pL9TXnPwCESEEPq_vr4cnm0a_06IdV_RhDEcGP-9oPdRuds7a-T97YXF-EWIhxbevluPZx6_Ub8ajDztbtWvvhuDpwOmR78jqPqoefy9_t1ez27vK6vbidmYYtxplrkHYL2VMkmnBcIPAGpTNEEM56gxyII9oY0ZkeO8YFA-vQ0r7T2Etu6FH1fcrdpvh3V05QG5-NDUEPNu6yQkIQqSS0-RgFKqRYcCEK2kyoSTHnZJ3aJr_RaV8g9dK1-t-1eulaTV0X29lky7rzgx1V1na764qDEVDLmxZlI7BgPybMDy6mjX6OKfRq1PsQk0t6MD4r-sGib1OC01HpVSqGh18FKI8tKxhr6D-Dvphb</recordid><startdate>20110901</startdate><enddate>20110901</enddate><creator>Worako, T.K</creator><creator>Jordaan, H</creator><creator>van Schalkwyk, H.D</creator><general>Taylor & Francis Group</general><general>Taylor & Francis</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><scope>7ST</scope><scope>C1K</scope><scope>SOI</scope></search><sort><creationdate>20110901</creationdate><title>Investigating Volatility in Coffee Prices Along the Ethiopian Coffee Value Chain</title><author>Worako, T.K ; Jordaan, H ; van Schalkwyk, H.D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c459t-f413b98d312a2619106418fc27265dc1602f2acc7bcd1b56750ef1e3dba1d86c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>ARCH/GARCH</topic><topic>Cash crops</topic><topic>Coffee</topic><topic>Commodity market</topic><topic>crop production</topic><topic>Economics</topic><topic>employment</topic><topic>Export prices</topic><topic>Exports</topic><topic>farmers</topic><topic>heteroskedasticity</topic><topic>livelihood</topic><topic>Price rises</topic><topic>Price volatility</topic><topic>prices</topic><topic>Producer price</topic><topic>risk</topic><topic>Risk management</topic><topic>supply chain</topic><topic>transporters</topic><topic>Uncertainty</topic><topic>Volatility</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Worako, T.K</creatorcontrib><creatorcontrib>Jordaan, H</creatorcontrib><creatorcontrib>van Schalkwyk, H.D</creatorcontrib><collection>AGRIS</collection><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>Environment Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><jtitle>Agrekon</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Worako, T.K</au><au>Jordaan, H</au><au>van Schalkwyk, H.D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Investigating Volatility in Coffee Prices Along the Ethiopian Coffee Value Chain</atitle><jtitle>Agrekon</jtitle><date>2011-09-01</date><risdate>2011</risdate><volume>50</volume><issue>3</issue><spage>90</spage><epage>108</epage><pages>90-108</pages><issn>2078-0400</issn><issn>0303-1853</issn><eissn>2078-0400</eissn><abstract>The coffee sub-sector is a major contributor to the Ethiopian economy. In addition to accounting for approximately 40 per cent on average of total export earnings, coffee production provides a livelihood for a large proportion of the Ethiopian population in the form of jobs for farmers, local traders, transporters and exporters. Volatility in the price of coffee thus influences a large proportion of the population all along the coffee commodity chain within Ethiopia. This study uses the Autoregressive Conditional Heteroscedasticity/Generalized Autoregressive Conditional Heteroscedasticity (ARCH)/(GARCH) approach to quantify the volatility in the price of coffee. A distinction is made between producer, wholesale and export prices in order to compare the price risk as faced by the respective participants in the coffee chain. The volatility in coffee prices within Ethiopia is also compared to the volatility levels in Brazilian coffee prices, since Brazil is a major coffee producing country in the world. Coffee prices within Ethiopia were found to be more volatile than in Brazil. Producer prices were found to be the most volatile, followed by wholesale prices and export prices respectively. The high level of volatility in producer prices emphasises the need for efficient price risk management tools that should be available to coffee producers in Ethiopia.</abstract><pub>Taylor & Francis Group</pub><doi>10.1080/03031853.2011.617865</doi><tpages>19</tpages></addata></record> |
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source | International Bibliography of the Social Sciences (IBSS); Taylor and Francis Social Sciences and Humanities Collection |
subjects | ARCH/GARCH Cash crops Coffee Commodity market crop production Economics employment Export prices Exports farmers heteroskedasticity livelihood Price rises Price volatility prices Producer price risk Risk management supply chain transporters Uncertainty Volatility |
title | Investigating Volatility in Coffee Prices Along the Ethiopian Coffee Value Chain |
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