How did farmers act? : ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model

This study evaluates linear programming (LP) and positive mathematical programming (PMP) approaches for 3,400 farm-level models implemented in the SWISSland agent-based agricultural sector model. To overcome limitations of PMP regarding the modelling of investment decisions, we further investigated...
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Autor*in:	Mack, Gabriele [verfasserIn] Ferjani, Ali [verfasserIn] Möhring, Anke [verfasserIn] Ow, Albert von [verfasserIn] Mann, Stefan - 1968- [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Rechteinformationen:	Open Access Namensnennung 4.0 International ; CC BY 4.0

Übergeordnetes Werk:	Enthalten in: Bio-based and applied economics - Firenze : Firenze University Press, 2012, 8(2019), 1, Seite 3-19
Übergeordnetes Werk:	volume:8 ; year:2019 ; number:1 ; pages:3-19

Links:	Link aufrufen Link aufrufen

DOI / URN:	10.13128/bae-8144

Katalog-ID:	1727899032

Internformat


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Indexfelder

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allfields	10.13128/bae-8144 doi (DE-627)1727899032 (DE-599)KXP1727899032 DE-627 ger DE-627 rda eng C61 Q18 Q19 jelc Mack, Gabriele verfasserin (DE-588)171827554 (DE-627)309054796 (DE-576)132590239 aut How did farmers act? ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model Gabriele Mack, Ali Ferjani, Anke Möhring, Albert von Ow, Stefan Mann 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 This study evaluates linear programming (LP) and positive mathematical programming (PMP) approaches for 3,400 farm-level models implemented in the SWISSland agent-based agricultural sector model. To overcome limitations of PMP regarding the modelling of investment decisions, we further investigated whether the forecasting performance of farm-level models could be improved by applying LP to animal production activities only, where investment in new sectors plays a major role, while applying PMP to crop production activities. The database used is the Swiss Farm Accountancy Data Network. Ex-post evaluation was performed for the period from 2005 to 2012, with the 2003-2005 three-year average as a base year. We found that PMP applied to crop production activities improves the forecasting performance of farm-level models compared to LP. Combining PMP for crop production activities with LP for modelling investment decisions in new livestock sectors improves the forecasting performance compared to PMP for both crop and animal production activities, especially in the medium and long term. For short-term forecasts, PMP for all production activities and PMP combined with LP for animal production activities produce similar results. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ Ferjani, Ali verfasserin aut Möhring, Anke verfasserin aut Ow, Albert von verfasserin (DE-588)1216656258 (DE-627)1727902440 aut Mann, Stefan 1968- verfasserin (DE-588)137501102 (DE-627)593186869 (DE-576)169033252 aut Enthalten in Bio-based and applied economics Firenze : Firenze University Press, 2012 8(2019), 1, Seite 3-19 (DE-627)856722073 (DE-600)2852439-1 (DE-576)467996520 2280-6172 nnns volume:8 year:2019 number:1 pages:3-19 https://oaj.fupress.net/index.php/bae/article/view/8144/7671 Verlag kostenfrei https://doi.org/10.13128/bae-8144 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 8 2019 1 3-19 26 01 0206 3743139731 x1z 27-08-20 2403 01 DE-LFER 3758314666 00 --%%-- --%%-- n --%%-- l01 18-09-20 2403 01 DE-LFER https://doi.org/10.13128/bae-8144 2403 01 DE-LFER https://oaj.fupress.net/index.php/bae/article/view/8144/7671 26 00 DE-206 56 Agent-based sector model 26 00 DE-206 56 farm-level model 26 00 DE-206 56 linear programming 26 00 DE-206 56 positive mathematical programming 26 00 DE-206 56 ex-post validation
spelling	10.13128/bae-8144 doi (DE-627)1727899032 (DE-599)KXP1727899032 DE-627 ger DE-627 rda eng C61 Q18 Q19 jelc Mack, Gabriele verfasserin (DE-588)171827554 (DE-627)309054796 (DE-576)132590239 aut How did farmers act? ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model Gabriele Mack, Ali Ferjani, Anke Möhring, Albert von Ow, Stefan Mann 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 This study evaluates linear programming (LP) and positive mathematical programming (PMP) approaches for 3,400 farm-level models implemented in the SWISSland agent-based agricultural sector model. To overcome limitations of PMP regarding the modelling of investment decisions, we further investigated whether the forecasting performance of farm-level models could be improved by applying LP to animal production activities only, where investment in new sectors plays a major role, while applying PMP to crop production activities. The database used is the Swiss Farm Accountancy Data Network. Ex-post evaluation was performed for the period from 2005 to 2012, with the 2003-2005 three-year average as a base year. We found that PMP applied to crop production activities improves the forecasting performance of farm-level models compared to LP. Combining PMP for crop production activities with LP for modelling investment decisions in new livestock sectors improves the forecasting performance compared to PMP for both crop and animal production activities, especially in the medium and long term. For short-term forecasts, PMP for all production activities and PMP combined with LP for animal production activities produce similar results. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ Ferjani, Ali verfasserin aut Möhring, Anke verfasserin aut Ow, Albert von verfasserin (DE-588)1216656258 (DE-627)1727902440 aut Mann, Stefan 1968- verfasserin (DE-588)137501102 (DE-627)593186869 (DE-576)169033252 aut Enthalten in Bio-based and applied economics Firenze : Firenze University Press, 2012 8(2019), 1, Seite 3-19 (DE-627)856722073 (DE-600)2852439-1 (DE-576)467996520 2280-6172 nnns volume:8 year:2019 number:1 pages:3-19 https://oaj.fupress.net/index.php/bae/article/view/8144/7671 Verlag kostenfrei https://doi.org/10.13128/bae-8144 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 8 2019 1 3-19 26 01 0206 3743139731 x1z 27-08-20 2403 01 DE-LFER 3758314666 00 --%%-- --%%-- n --%%-- l01 18-09-20 2403 01 DE-LFER https://doi.org/10.13128/bae-8144 2403 01 DE-LFER https://oaj.fupress.net/index.php/bae/article/view/8144/7671 26 00 DE-206 56 Agent-based sector model 26 00 DE-206 56 farm-level model 26 00 DE-206 56 linear programming 26 00 DE-206 56 positive mathematical programming 26 00 DE-206 56 ex-post validation
allfields_unstemmed	10.13128/bae-8144 doi (DE-627)1727899032 (DE-599)KXP1727899032 DE-627 ger DE-627 rda eng C61 Q18 Q19 jelc Mack, Gabriele verfasserin (DE-588)171827554 (DE-627)309054796 (DE-576)132590239 aut How did farmers act? ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model Gabriele Mack, Ali Ferjani, Anke Möhring, Albert von Ow, Stefan Mann 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 This study evaluates linear programming (LP) and positive mathematical programming (PMP) approaches for 3,400 farm-level models implemented in the SWISSland agent-based agricultural sector model. To overcome limitations of PMP regarding the modelling of investment decisions, we further investigated whether the forecasting performance of farm-level models could be improved by applying LP to animal production activities only, where investment in new sectors plays a major role, while applying PMP to crop production activities. The database used is the Swiss Farm Accountancy Data Network. Ex-post evaluation was performed for the period from 2005 to 2012, with the 2003-2005 three-year average as a base year. We found that PMP applied to crop production activities improves the forecasting performance of farm-level models compared to LP. Combining PMP for crop production activities with LP for modelling investment decisions in new livestock sectors improves the forecasting performance compared to PMP for both crop and animal production activities, especially in the medium and long term. For short-term forecasts, PMP for all production activities and PMP combined with LP for animal production activities produce similar results. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ Ferjani, Ali verfasserin aut Möhring, Anke verfasserin aut Ow, Albert von verfasserin (DE-588)1216656258 (DE-627)1727902440 aut Mann, Stefan 1968- verfasserin (DE-588)137501102 (DE-627)593186869 (DE-576)169033252 aut Enthalten in Bio-based and applied economics Firenze : Firenze University Press, 2012 8(2019), 1, Seite 3-19 (DE-627)856722073 (DE-600)2852439-1 (DE-576)467996520 2280-6172 nnns volume:8 year:2019 number:1 pages:3-19 https://oaj.fupress.net/index.php/bae/article/view/8144/7671 Verlag kostenfrei https://doi.org/10.13128/bae-8144 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 8 2019 1 3-19 26 01 0206 3743139731 x1z 27-08-20 2403 01 DE-LFER 3758314666 00 --%%-- --%%-- n --%%-- l01 18-09-20 2403 01 DE-LFER https://doi.org/10.13128/bae-8144 2403 01 DE-LFER https://oaj.fupress.net/index.php/bae/article/view/8144/7671 26 00 DE-206 56 Agent-based sector model 26 00 DE-206 56 farm-level model 26 00 DE-206 56 linear programming 26 00 DE-206 56 positive mathematical programming 26 00 DE-206 56 ex-post validation
allfieldsGer	10.13128/bae-8144 doi (DE-627)1727899032 (DE-599)KXP1727899032 DE-627 ger DE-627 rda eng C61 Q18 Q19 jelc Mack, Gabriele verfasserin (DE-588)171827554 (DE-627)309054796 (DE-576)132590239 aut How did farmers act? ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model Gabriele Mack, Ali Ferjani, Anke Möhring, Albert von Ow, Stefan Mann 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 This study evaluates linear programming (LP) and positive mathematical programming (PMP) approaches for 3,400 farm-level models implemented in the SWISSland agent-based agricultural sector model. To overcome limitations of PMP regarding the modelling of investment decisions, we further investigated whether the forecasting performance of farm-level models could be improved by applying LP to animal production activities only, where investment in new sectors plays a major role, while applying PMP to crop production activities. The database used is the Swiss Farm Accountancy Data Network. Ex-post evaluation was performed for the period from 2005 to 2012, with the 2003-2005 three-year average as a base year. We found that PMP applied to crop production activities improves the forecasting performance of farm-level models compared to LP. Combining PMP for crop production activities with LP for modelling investment decisions in new livestock sectors improves the forecasting performance compared to PMP for both crop and animal production activities, especially in the medium and long term. For short-term forecasts, PMP for all production activities and PMP combined with LP for animal production activities produce similar results. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ Ferjani, Ali verfasserin aut Möhring, Anke verfasserin aut Ow, Albert von verfasserin (DE-588)1216656258 (DE-627)1727902440 aut Mann, Stefan 1968- verfasserin (DE-588)137501102 (DE-627)593186869 (DE-576)169033252 aut Enthalten in Bio-based and applied economics Firenze : Firenze University Press, 2012 8(2019), 1, Seite 3-19 (DE-627)856722073 (DE-600)2852439-1 (DE-576)467996520 2280-6172 nnns volume:8 year:2019 number:1 pages:3-19 https://oaj.fupress.net/index.php/bae/article/view/8144/7671 Verlag kostenfrei https://doi.org/10.13128/bae-8144 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 8 2019 1 3-19 26 01 0206 3743139731 x1z 27-08-20 2403 01 DE-LFER 3758314666 00 --%%-- --%%-- n --%%-- l01 18-09-20 2403 01 DE-LFER https://doi.org/10.13128/bae-8144 2403 01 DE-LFER https://oaj.fupress.net/index.php/bae/article/view/8144/7671 26 00 DE-206 56 Agent-based sector model 26 00 DE-206 56 farm-level model 26 00 DE-206 56 linear programming 26 00 DE-206 56 positive mathematical programming 26 00 DE-206 56 ex-post validation
allfieldsSound	10.13128/bae-8144 doi (DE-627)1727899032 (DE-599)KXP1727899032 DE-627 ger DE-627 rda eng C61 Q18 Q19 jelc Mack, Gabriele verfasserin (DE-588)171827554 (DE-627)309054796 (DE-576)132590239 aut How did farmers act? ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model Gabriele Mack, Ali Ferjani, Anke Möhring, Albert von Ow, Stefan Mann 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 This study evaluates linear programming (LP) and positive mathematical programming (PMP) approaches for 3,400 farm-level models implemented in the SWISSland agent-based agricultural sector model. To overcome limitations of PMP regarding the modelling of investment decisions, we further investigated whether the forecasting performance of farm-level models could be improved by applying LP to animal production activities only, where investment in new sectors plays a major role, while applying PMP to crop production activities. The database used is the Swiss Farm Accountancy Data Network. Ex-post evaluation was performed for the period from 2005 to 2012, with the 2003-2005 three-year average as a base year. We found that PMP applied to crop production activities improves the forecasting performance of farm-level models compared to LP. Combining PMP for crop production activities with LP for modelling investment decisions in new livestock sectors improves the forecasting performance compared to PMP for both crop and animal production activities, especially in the medium and long term. For short-term forecasts, PMP for all production activities and PMP combined with LP for animal production activities produce similar results. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ Ferjani, Ali verfasserin aut Möhring, Anke verfasserin aut Ow, Albert von verfasserin (DE-588)1216656258 (DE-627)1727902440 aut Mann, Stefan 1968- verfasserin (DE-588)137501102 (DE-627)593186869 (DE-576)169033252 aut Enthalten in Bio-based and applied economics Firenze : Firenze University Press, 2012 8(2019), 1, Seite 3-19 (DE-627)856722073 (DE-600)2852439-1 (DE-576)467996520 2280-6172 nnns volume:8 year:2019 number:1 pages:3-19 https://oaj.fupress.net/index.php/bae/article/view/8144/7671 Verlag kostenfrei https://doi.org/10.13128/bae-8144 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 8 2019 1 3-19 26 01 0206 3743139731 x1z 27-08-20 2403 01 DE-LFER 3758314666 00 --%%-- --%%-- n --%%-- l01 18-09-20 2403 01 DE-LFER https://doi.org/10.13128/bae-8144 2403 01 DE-LFER https://oaj.fupress.net/index.php/bae/article/view/8144/7671 26 00 DE-206 56 Agent-based sector model 26 00 DE-206 56 farm-level model 26 00 DE-206 56 linear programming 26 00 DE-206 56 positive mathematical programming 26 00 DE-206 56 ex-post validation
language	English
source	Enthalten in Bio-based and applied economics 8(2019), 1, Seite 3-19 volume:8 year:2019 number:1 pages:3-19
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container_title	Bio-based and applied economics
authorswithroles_txt_mv	Mack, Gabriele @@aut@@ Ferjani, Ali @@aut@@ Möhring, Anke @@aut@@ Ow, Albert von @@aut@@ Mann, Stefan @@aut@@
publishDateDaySort_date	2019-01-01T00:00:00Z
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topic_title	C61 Q18 Q19 jelc 26 00 DE-206 56 Agent-based sector model 26 00 DE-206 56 farm-level model 26 00 DE-206 56 linear programming 26 00 DE-206 56 positive mathematical programming 26 00 DE-206 56 ex-post validation How did farmers act? ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model Gabriele Mack, Ali Ferjani, Anke Möhring, Albert von Ow, Stefan Mann
topic	jelc C61 26 Agent-based sector model 26 farm-level model 26 linear programming 26 positive mathematical programming 26 ex-post validation
topic_unstemmed	jelc C61 26 Agent-based sector model 26 farm-level model 26 linear programming 26 positive mathematical programming 26 ex-post validation
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title	How did farmers act? ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model
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title_full	How did farmers act? ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model Gabriele Mack, Ali Ferjani, Anke Möhring, Albert von Ow, Stefan Mann
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title_sort	how did farmers act?ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model
title_auth	How did farmers act? ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model
abstract	This study evaluates linear programming (LP) and positive mathematical programming (PMP) approaches for 3,400 farm-level models implemented in the SWISSland agent-based agricultural sector model. To overcome limitations of PMP regarding the modelling of investment decisions, we further investigated whether the forecasting performance of farm-level models could be improved by applying LP to animal production activities only, where investment in new sectors plays a major role, while applying PMP to crop production activities. The database used is the Swiss Farm Accountancy Data Network. Ex-post evaluation was performed for the period from 2005 to 2012, with the 2003-2005 three-year average as a base year. We found that PMP applied to crop production activities improves the forecasting performance of farm-level models compared to LP. Combining PMP for crop production activities with LP for modelling investment decisions in new livestock sectors improves the forecasting performance compared to PMP for both crop and animal production activities, especially in the medium and long term. For short-term forecasts, PMP for all production activities and PMP combined with LP for animal production activities produce similar results.
abstractGer	This study evaluates linear programming (LP) and positive mathematical programming (PMP) approaches for 3,400 farm-level models implemented in the SWISSland agent-based agricultural sector model. To overcome limitations of PMP regarding the modelling of investment decisions, we further investigated whether the forecasting performance of farm-level models could be improved by applying LP to animal production activities only, where investment in new sectors plays a major role, while applying PMP to crop production activities. The database used is the Swiss Farm Accountancy Data Network. Ex-post evaluation was performed for the period from 2005 to 2012, with the 2003-2005 three-year average as a base year. We found that PMP applied to crop production activities improves the forecasting performance of farm-level models compared to LP. Combining PMP for crop production activities with LP for modelling investment decisions in new livestock sectors improves the forecasting performance compared to PMP for both crop and animal production activities, especially in the medium and long term. For short-term forecasts, PMP for all production activities and PMP combined with LP for animal production activities produce similar results.
abstract_unstemmed	This study evaluates linear programming (LP) and positive mathematical programming (PMP) approaches for 3,400 farm-level models implemented in the SWISSland agent-based agricultural sector model. To overcome limitations of PMP regarding the modelling of investment decisions, we further investigated whether the forecasting performance of farm-level models could be improved by applying LP to animal production activities only, where investment in new sectors plays a major role, while applying PMP to crop production activities. The database used is the Swiss Farm Accountancy Data Network. Ex-post evaluation was performed for the period from 2005 to 2012, with the 2003-2005 three-year average as a base year. We found that PMP applied to crop production activities improves the forecasting performance of farm-level models compared to LP. Combining PMP for crop production activities with LP for modelling investment decisions in new livestock sectors improves the forecasting performance compared to PMP for both crop and animal production activities, especially in the medium and long term. For short-term forecasts, PMP for all production activities and PMP combined with LP for animal production activities produce similar results.
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How did farmers act? : ex-post validation of linear and positive mathematical programming approaches for farmlevel models implemented in an agent-based agricultural sector model

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