1932
0
  1. Home
  2. A-Z Publications
  3. Annual Review of Resource Economics
  4. Volume 15, 2023
  5. Article

Annual Review of Resource Economics

Volume 15, 2023

The Role and Use of Mathematical Programming in Agricultural, Natural Resource, and Climate Change Analysis

Abstract

Climate change undeniably impacts agriculture and natural resources, enterprises and markets. For informed decision making, there is a need for information on climate change adaptation possibilities and mitigation alternatives. Mathematical programming has been used to address the economic aspects of such questions and allows analysis as climate change moves the environment into previously unobserved conditions. It allows us to model spatial and dynamic features of the issue and analyze heretofore unobserved adaptation and mitigation possibilities. This review provides an overview of and references for modeling techniques, conceptual issues, and major assumptions involved with using mathematical programming as a climate change economic analyzing engine, along with a brief comparison with other methods. We also review a number of studies applying mathematical programming to examine climate change impacts, adaptation, and mitigation issues in the agricultural and natural resources arena. Finally, we present a very brief discussion on research needs.

Keyword(s): adaptation, climate change effects, JEL C61, JEL Q1, JEL Q2, JEL Q4, JEL Q5, mathematical programming, mitigation
Loading

Article metrics loading...

/content/journals/10.1146/annurev-resource-101422-041745
2023-10-05
2025-04-20
Loading full text...

Full text loading...

/deliver/fulltext/resource/15/1/annurev-resource-101422-041745.html?itemId=/content/journals/10.1146/annurev-resource-101422-041745&mimeType=html&fmt=ahah

Literature Cited

  1. Adams DM, Alig RJ, McCarl BA, Murray BC. 2005. FASOMGHG conceptual structure, and specification: documentation Tech. Rep. Texas A&M Univ. College Station, TX: http://agecon2.tamu.edu/people/faculty/mccarl-bruce/papers/1212FASOMGHG_doc.pdf
    [Google Scholar]
  2. Adams RM. 1999. On the search for the correct economic assessment method. Clim. Change 41:3–4363
     [Google Scholar]
  3. Adams RM, Fleming RA, Chang CC, McCarl BA, Rosenzweig C. 1995. A reassessment of the economic effects of global climate change on US agriculture. Clim. Change 30:2147–67
     [Google Scholar]
  4. Adams RM, Glyer JD, McCarl BA 1989. The economic effects of climate change on US agriculture: a preliminary assessment. The Potential Effects of Global Climate Change on the United States, Append. C, Vol. 1 RO Mendelsohn, A Dinar Washington, DC: US Environ. Prot. Agency
     [Google Scholar]
  5. Adams RM, McCarl BA, Dudek DJ, Glyer JD. 1988. Implications of global climate change for western agriculture. Western J. Agric. Econ. 13:2348–56
     [Google Scholar]
  6. Adams RM, McCarl BA, Mearns LO. 2003. The effects of spatial scale of climate scenarios on economic assessments: an example from US agriculture. Clim. Change 60:1131–48
     [Google Scholar]
  7. Adams RM, McCarl BA, Segerson K, Rosenzweig C, Bryant KJ et al. 1999. Economic effects of climate change on US agriculture. The Impact of Climate Change on the United States Economy RO Mendelsohn, JE Neumann 18–54. Cambridge, UK: Cambridge Univ. Press
     [Google Scholar]
  8. Adams RM, Rosenzweig C, Peart R, Ritchie JC, McCarl BA et al. 1990. Global climate change and US agriculture. Nature 345:219–24
     [Google Scholar]
  9. Aisabokhae RA, McCarl BA, Zhang YW. 2011. Agricultural adaptation: needs, findings and effects. Handbook on Climate Change and Agriculture A Dinar, RO Mendelsohn 327–41. Cheltenham, UK: Edward Elgar
     [Google Scholar]
  10. Alig RJ, Adams DM, McCarl BA, Callaway JM, Winnett SM. 1997. Assessing effects of mitigation strategies for global climate change with an intertemporal model of the U.S. forest and agriculture sectors. Environ. Resour. Econ. 9:3259–74
     [Google Scholar]
  11. Antle JM, McCarl BA. 2002. The economics of carbon sequestration in agricultural soils. Int. Yearb. Environ. Resour. Econ. 2003:278–310
     [Google Scholar]
  12. Attavanich W, McCarl BA. 2014. How is CO2 affecting yields and technological progress? A statistical analysis. Clim. Change 124:4747–62
     [Google Scholar]
  13. Attavanich W, McCarl BA, Ahmedov Z, Fuller SW, Vedenov DV. 2013. Effects of climate change on US grain transport. Nat. Clim. Change 3:638–43
     [Google Scholar]
  14. Babatunde KA, Begum RA, Said FF. 2017. Application of computable general equilibrium (CGE) to climate change mitigation policy: a systematic review. Renew. Sustain. Energy Rev. 78:61–71
     [Google Scholar]
  15. Baker TG, McCarl BA. 1982. Representing farm resource availability over time in linear programs: a case study. North Cent. J. Agric. Econ. 4:159–68
     [Google Scholar]
  16. Beach RH, McCarl BA. 2010. U.S. agricultural and forestry impacts of the Energy Independence and Security Act: FASOM results and model description Final Rep. US Environ. Prot. Agency, Off. Transp. Air Quality Washington, DC: https://www.rti.org/publication/us-agricultural-and-forestry-impacts-energy-independence-and-security-act/fulltext.pdf
    [Google Scholar]
  17. Beach RH, Zhang YW, McCarl BA 2017. Modeling bioenergy, land use, and GHG mitigation with FASOMGHG: implications of storage costs and carbon policy. Handbook of Bioenergy Economics and Policy, Vol. II: Modeling Land Use and Greenhouse Gas Implications M Khanna, D Zilberman 239–71. New York: Springer
     [Google Scholar]
  18. Bergman L 2005. CGE modeling of environmental policy and resource management. Handbook of Environmental Economics, Vol. 3 K-G Mäler, JR Vincent 1273–306. Amsterdam: Elsevier
     [Google Scholar]
  19. Buckwell AE, Hazell PBR. 1972. Implications of aggregation bias for the construction of static and dynamic linear programming supply models. J. Agric. Econ. 23:2119–34
     [Google Scholar]
  20. Butt TA, McCarl BA, Angerer J, Dyke PT, Stuth JW. 2005. The economic and food security implications of climate change in Mali. Clim. Change 68:3355–78
     [Google Scholar]
  21. Butt TA, McCarl BA, Kergna AO. 2006. Policies for reducing agricultural sector vulnerability to climate change in Mali. Clim. Policy 5:6583–98
     [Google Scholar]
  22. Carpenter CW, Fei CJ, McCarl BA. 2022. Climate change shifting locations of the U.S. agricultural processing industry Work. Pap. Texas A&M Univ. College Station, TX:
     [Google Scholar]
  23. Chang CC, Chen CC, McCarl BA. 2011. Evaluating the economic impacts of crop yield change and sea level rise induced by climate change on Taiwan's agricultural sector. Agric. Econ. 43:2205–14
     [Google Scholar]
  24. Chen CC, Gillig D, McCarl BA, Williams RL. 2005. ENSO impacts on regional water management: case study of the Edwards Aquifer (Texas, USA). Clim. Res. 28:2175–82
     [Google Scholar]
  25. Chen CC, McCarl BA, Adams RM. 2001. Economic implications of potential ENSO frequency and strength shifts. Clim. Change 49:1–2147–59
     [Google Scholar]
  26. Chen CC, McCarl BA, Chang CC. 2012. Climate change, sea level rise and rice: global market implications. Clim. Change 110:3–4543–60
     [Google Scholar]
  27. Chen CC, McCarl BA, Schimmelpfennig DE. 2004. Yield variability as influenced by climate: a statistical investigation. Clim. Change 66:1239–61
     [Google Scholar]
  28. Chen XQ, Önal H. 2012. Modeling agricultural supply response using mathematical programming and crop mixes. Am. J. Agric. Econ. 94:3674–86
     [Google Scholar]
  29. Cho SJ, McCarl BA. 2017. Climate change influences on crop mix shifts in the United States. Sci. Rep. 7:40845
     [Google Scholar]
  30. Cho SJ, McCarl BA. 2021. Major United States land use as influenced by an altering climate: a spatial econometric approach. Land 10:5546
     [Google Scholar]
  31. Choi H, Schneider UA, Rasche L, Cui J, Schmid E, Held H. 2015. Potential effects of perfect seasonal climate forecasting on agricultural markets, welfare and land use: a case study of Spain. Agric. Syst. 133:177–89
     [Google Scholar]
  32. Ciarli T, Savona M. 2019. Modelling the evolution of economic structure and climate change: a review. Ecol. Econ. 158:51–64
     [Google Scholar]
  33. De La Torre Ugarte DG, English BC, Jensen K. 2007. Sixty billion gallons by 2030: economic and agricultural impacts of ethanol and biodiesel expansion. Am. J. Agric. Econ. 89:51290–95
     [Google Scholar]
  34. de Lima CZ, Buzan JR, Moore FC, Baldos ULC, Huber M, Hertel TW. 2021. Heat stress on agricultural workers exacerbates crop impacts of climate change. Environ. Res. Lett. 16:4044020
     [Google Scholar]
  35. De Salvo M, Begalli D, Signorello G. 2014. The Ricardian analysis twenty years after the original model: evolution, unresolved issues and empirical problems. J. Dev. Agric. Econ. 6:3124–31
     [Google Scholar]
  36. De Siano R, Leone Sciabolazza V, Sapio A 2020. Resilience to climate change: spatial Ricardian analysis. Regional Resilience to Climate and Environmental Shocks: A Spatial Econometric Perspective R De Siano, V Leone Sciabolazza, A Sapio 73–88. New York: Springer
     [Google Scholar]
  37. Dicks MR, Campiche J, De La Torre Ugarte DG, Hellwinckel C et al. 2009. Land use implications of expanding biofuel demand. J. Agric. Appl. Econ. 41:02435–53
     [Google Scholar]
  38. Donaghy KP 2019. CGE modeling in space: a survey. Handbook of Regional Growth and Development Theories R Capello, P Nijkamp 467–504. Cheltenham, UK: Edward Elgar
     [Google Scholar]
  39. Ebi KL, Padgham J, Doumbia M, Smith JB, Butt TA, McCarl BA. 2011. Smallholders adaptation to climate change in Mali. Clim. Change 108:3423–36
     [Google Scholar]
  40. English BC, Short C, Heady EO. 1981. The economic feasibility of crop residues as auxiliary fuel in coal-fired power plants. Am. J. Agric. Econ. 63:4636–44
     [Google Scholar]
  41. Fajardo D, McCarl BA, Thompson RL. 1981. A multicommodity analysis of trade policy effects: the case of Nicaraguan agriculture. Am. J. Agric. Econ. 63:123–31
     [Google Scholar]
  42. Fan XX. 2018. An integrated analysis of federal milk marketing order price differential policy and climate change effects in dairy industry PhD Diss. Texas A&M Univ. College Station, TX:
     [Google Scholar]
  43. Fei CJ, Jägermeyr J, McCarl BA, Mencos Contreras E, Mutter C et al. 2023. Future climate change impacts on U.S. agricultural yield, production, and market. Anthropocene 42:100386
     [Google Scholar]
  44. Fei CJ, McCarl BA, Thayer AW. 2017. Estimating the impacts of climate change and potential adaptation strategies on cereal grains in the United States. Front. Ecol. Evol. 5:62
     [Google Scholar]
  45. Fei CJ, McCarl BA, Yang YQ, Ayana E, Srinivasan R et al. 2022. Impacts of climate change on water management. Appl. Econ. Perspect. Policy 44:31448–64
     [Google Scholar]
  46. Frank S, Beach R, Havlík P, Valin H, Herrero M et al. 2018. Structural change as a key component for agricultural non-CO2 mitigation efforts. Nat. Commun. 9:11060
     [Google Scholar]
  47. Frank S, Havlík P, Tabeau A, Witzke P, Boere E et al. 2021. How much multilateralism do we need? Effectiveness of unilateral agricultural mitigation efforts in the global context. Environ. Res. Lett. 16:10104038
     [Google Scholar]
  48. Gambhir A, Butnar I, Li PH, Smith P, Strachan N. 2019. A review of criticisms of integrated assessment models and proposed approaches to address these, through the lens of BECCS. Energies 12:91747
     [Google Scholar]
  49. Havlík P, Valin HJP, Herrero MT, Obersteiner M, Schmid E et al. 2014. Climate change mitigation through livestock system transitions. PNAS 111:103709–14
     [Google Scholar]
  50. Hertel TW 1999. Global Trade Analysis: Modeling and Applications Cambridge, UK: Cambridge Univ. Press
     [Google Scholar]
  51. Hertel TW, Rose SK, Tol RSJ 2009. Land use in computable general equilibrium models: an overview. Economic Analysis of Land Use in Global Climate Change Policy TW Hertel, SK Rose, RSJ Tol 23–50. London: Routledge
     [Google Scholar]
  52. Hill DL, Wall E. 2015. Dairy cattle in a temperate climate: the effects of weather on milk yield and composition depend on management. Animal 9:1138–49
     [Google Scholar]
  53. Himics M, Fellmann T, Barreiro-Hurle J. 2020. Setting climate action as the priority for the common agricultural policy: a simulation experiment. J. Agric. Econ. 71:150–69
     [Google Scholar]
  54. Howitt RE. 1995. Positive mathematical programming. Am. J. Agric. Econ. 77:2329–42
     [Google Scholar]
  55. IPCC (Intergov. Panel Clim. Change) 2014. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge, UK: Cambridge Univ. Press
     [Google Scholar]
  56. Jackson RB, Jobbágy EG, Avissar R, Roy SB, Barrett D et al. 2005. Trading water for carbon with biological carbon sequestration. Science 310:57561944–47
     [Google Scholar]
  57. Janssens C, Havlík P, Krisztin T, Baker J, Frank S et al. 2020. Global hunger and climate change adaptation through international trade. Nat. Clim. Change 10:9829–35
     [Google Scholar]
  58. Janssens C, Havlík P, Krisztin T, Baker J, Frank S et al. 2021. International trade is a key component of climate change adaptation. Nat. Clim. Change 11:11915–16
     [Google Scholar]
  59. Kaiser HM, Riha SJ, Wilks DS, Rossiter DG, Sampath R. 1993. A farm-level analysis of economic and agronomic impacts of gradual climate warming. Am. J. Agric. Econ. 75:387–98
     [Google Scholar]
  60. Kung CC, McCarl BA. 2020. The potential role of renewable electricity generation in Taiwan. Energy Policy 138:111227
     [Google Scholar]
  61. Kung CC, McCarl BA, Cao X. 2013. Economics of pyrolysis-based energy production and biochar utilization: a case study in Taiwan. Energy Policy 60:317–23
     [Google Scholar]
  62. Lagomarsino E. 2020. Estimating elasticities of substitution with nested CES production functions: Where do we stand?. Energy Econ. 88:104752
     [Google Scholar]
  63. Lambert DK, McCarl BA, He Q, Kaylen MS, Rosenthal W et al. 1995. Uncertain yields in sectoral welfare analysis: an application to global warming. J. Agric. Appl. Econ. 27:2423–36
     [Google Scholar]
  64. Langholtz MH, Stokes BJ, Eaton LM. 2016. 2016 billion-ton report: advancing domestic resources for a thriving bioeconomy, Vol. 1: economic availability of feedstock Rep. Oak Ridge Natl. Lab., Oak Ridge, TN, and US Dep. Energy Washington, DC:
     [Google Scholar]
  65. Leclère D, Havlík P, Fuss S, Schmid E, Mosnier A et al. 2014. Climate change induced transformations of agricultural systems: insights from a global model. Environ. Res. Lett. 9:12124018
     [Google Scholar]
  66. Lee HC, McCarl BA, Gillig D. 2005. The dynamic competitiveness of US agricultural and forest carbon sequestration. Can. J. Agric. Econ. 53:4343–57
     [Google Scholar]
  67. Lobell DB, Asseng S. 2017. Comparing estimates of climate change impacts from process-based and statistical crop models. Environ. Res. Lett. 12:015001
     [Google Scholar]
  68. Malcolm SA, Aillery M, Weinberg M. 2009. Ethanol and a changing agricultural landscape Rep. EIB-86 Econ. Res. Serv., US Dep. Agric. Washington, DC: https://ageconsearch.umn.edu/record/55671/
    [Google Scholar]
  69. Malcolm SA, Marshall E, Aillery M, Heisey P, Livingston M, Day-Rubenstein K. 2012. Agricultural adaptation to a changing climate: economic and environmental implications vary by U.S. region. Econ. Res. Rep. ERR-136 U.S. Department of Agriculture, Economic Research Service, Washington, DC, USA. Econ. Res. Serv., US Dep. Agric. Washington, DC: https://www.ers.usda.gov/publications/pub-details/?pubid=44989
    [Google Scholar]
  70. Marshall E, Caswell M, Malcolm SA, Motamed M, Hrubovcak J et al. 2011. Measuring the indirect land-use change associated with increased biofuel feedstock production: a review of modeling efforts: report to Congress Adm. Publ. 292118 US Dep. Agric. Econ. Res. Serv. Washington, DC: https://ideas.repec.org/p/ags/uersap/292118.html
    [Google Scholar]
  71. McCarl BA. 1982. Cropping activities in agricultural sector models: a methodological proposal. Am. J. Agric. Econ. 64:4768–72
     [Google Scholar]
  72. McCarl BA. 2015. Elaborations on climate adaptation in US agriculture. Choices 30:21–5
     [Google Scholar]
  73. McCarl BA, Adams DM, Alig RJ, Chmelik JT. 2000. Competitiveness of biomass-fueled electrical power plants. Ann. Oper. Res. 94:37–55
     [Google Scholar]
  74. McCarl BA, Hertel TW. 2018. Climate change as an agricultural economics research topic. Appl. Econ. Perspect. Policy 40:160–78
     [Google Scholar]
  75. McCarl BA, Musumba M, Smith JB, Kirshen P, Jones R et al. 2015. Climate change vulnerability and adaptation strategies in Egypt's agricultural sector. Mitig. Adapt. Strateg. Glob. Change 20:1097–109
     [Google Scholar]
  76. McCarl BA, Schneider UA. 2000. US agriculture's role in a greenhouse gas emission mitigation world: an economic perspective. Rev. Agric. Econ. 22:134–59
     [Google Scholar]
  77. McCarl BA, Schneider UA. 2001. Greenhouse gas mitigation in U.S. agriculture and forestry. Science 294:55512481–82
     [Google Scholar]
  78. McCarl BA, Spreen TH. 1980. Price endogenous mathematical programming as a tool for sector analysis. Am. J. Agric. Econ. 62:87–102
     [Google Scholar]
  79. McCarl BA, Thayer AW, Jones JPH. 2016. The challenge of climate change adaptation for agriculture: an economically oriented review. J. Agric. Appl. Econ. 48:321–44
     [Google Scholar]
  80. McCarl BA, Villavicencio X, Wu XM. 2008. Climate change and future analysis: Is stationarity dying?. Am. J. Agric. Econ. 90:51241–47
     [Google Scholar]
  81. Medellín-Azuara J, Harou JJ, Olivares MA, Madani K, Lund JR et al. 2008. Adaptability and adaptations of California's water supply system to dry climate warming. Clim. Change 87:175–90
     [Google Scholar]
  82. Mendelsohn R, Nordhaus WD, Shaw D. 1994. The impact of global warming on agriculture: a Ricardian analysis. Am. Econ. Rev. 84:4753–71
     [Google Scholar]
  83. Mérel P, Gammans M. 2021. Climate econometrics: Can the panel approach account for long-run adaptation?. Am. J. Agric. Econ. 103:41207–38
     [Google Scholar]
  84. Mosnier A, Havlík P, Valin H, Baker JS, Murray BC et al. 2013. Alternative U.S. biofuel mandates and global GHG emissions: the role of land use change, crop management and yield growth. Energy Policy 57:602–14
     [Google Scholar]
  85. Murray BC, Sohngen BL, Ross MT. 2007. Economic consequences of consideration of permanence, leakage and additionality for soil carbon sequestration projects. Clim. Change 80:127–43
     [Google Scholar]
  86. Murray BC, Sohngen BL, Sommer A, Depro B, Jones K et al. 2005. Greenhouse gas mitigation potential in US forestry and agriculture EPA Rep. 430-R-05–006 US Environ. Prot. Agency Washington, DC:
     [Google Scholar]
  87. Musser WN, McCarl BA, Smith GS. 1986. An investigation of the relationship between constraint omission and risk aversion in firm risk programming models. J. Agric. Appl. Econ. 18:2147–54
     [Google Scholar]
  88. Önal H, McCarl BA. 1991. Exact aggregation in mathematical programming sector models. Can. J. Agric. Econ. 39:2319–34
     [Google Scholar]
  89. Parton WJ 1996. The CENTURY model. Evaluation of Soil Organic Matter Models DS Powlson, P Smith, JU Smith 283–91. Berlin: Springer
     [Google Scholar]
  90. Pérez Domínguez I, Fellmann T, Weiss F, Witzke P, Barreiro-Hurlé J et al. 2016. An economic assessment of GHG mitigation policy options for EU agriculture (EcAMPA 2) JRC Sci. Policy Rep. EUR27973 EN Publ. Off. Eur. Union Seville, Spain:
     [Google Scholar]
  91. Pindyck RS. 2013. Climate change policy: What do the models tell us?. J. Econ. Lit. 51:3860–72
     [Google Scholar]
  92. Post WM, Amonette JE, Birdsey R, Rice C, Izaurralde RC et al. 2009. Terrestrial biological carbon sequestration: science for enhancement and implementation. Carbon Sequestration and Its Role in the Global Carbon Cycle BP McPherson, ET Sundquist 73–88. Washington, DC: Am. Geophys. Union
     [Google Scholar]
  93. Reilly JM, Hrubovcak J, Graham J, Abler DG, Darwin R et al. 2002. Changing climate and changing agriculture: report of the agricultural sector assessment team, US national assessment Rep. US Dep. Agric. Washington, DC: https://agecon2.tamu.edu/people/faculty/mccarl-bruce/papers/888.pdf
    [Google Scholar]
  94. Reilly JM, Tubiello FN, McCarl BA, Abler DG, Darwin R et al. 2003. U.S. agriculture and climate change: new results. Clim. Change. 57:1–243–67
     [Google Scholar]
  95. Reinsborough MJ. 2003. A Ricardian model of climate change in Canada. Can. J. Agric. Econ. 36:121–40
     [Google Scholar]
  96. Rose SK, McCarl BA. 2008. Greenhouse gas emissions, stabilization and the inevitability of adaptation: challenges for U.S. agriculture. Choices 23:115–18
     [Google Scholar]
  97. Schaible GD, McCarl BA, Lacewell RD. 1999. The Edwards Aquifer water resource conflict: USDA farm program resource-use incentives?. Water Resour. Res. 35:103171–83
     [Google Scholar]
  98. Schlenker W, Roberts MJ. 2009. Nonlinear temperature effects indicate severe damages to US crop yields under climate change. PNAS 106:3715594–98
     [Google Scholar]
  99. Schneider UA, McCarl BA. 2003. Economic potential of biomass based fuels for greenhouse gas emission mitigation. Environ. Resour. Econ. 24:4291–312
     [Google Scholar]
  100. Schneider UA, McCarl BA, Schmid E. 2007. Agricultural sector analysis on greenhouse gas mitigation in US agriculture and forestry. Agric. Syst. 94:2128–40
     [Google Scholar]
  101. Seo SN, McCarl BA. 2011. Managing livestock species under climate change in Australia. Animals 1:4343–65
     [Google Scholar]
  102. Seo SN, McCarl BA, Mendelsohn RO. 2010. From beef cattle to sheep under global warming? An analysis of adaptation by livestock species choice in South America. Ecol. Econ. 69:2486–94
     [Google Scholar]
  103. Seo SN, Mendelsohn RO. 2008. Animal husbandry in Africa: climate change impacts and adaptations. Afr. J. Agric. Resour. Econ. 2:65–82
     [Google Scholar]
  104. Spreen TH, Takayama T. 1980. A theoretical note on aggregation of linear programming models of production. Am. J. Agric. Econ. 62:1146–51
     [Google Scholar]
  105. Szulczyk KR, McCarl BA. 2010. Market penetration of biodiesel. Renew. Sustain. Energy Rev. 14:82426–33
     [Google Scholar]
  106. Szulczyk KR, McCarl BA, Cornforth GC. 2010. Market penetration of ethanol. Renew. Sustain. Energy Rev. 14:1394–403
     [Google Scholar]
  107. Tack JB, Barkley AP, Nalley LL. 2015. Effect of warming temperatures on US wheat yields. PNAS 112:226931–36
     [Google Scholar]
  108. Takayama T, Judge G. 1971. Spatial and Temporal Price and Allocation Models Amsterdam: North-Holland
     [Google Scholar]
  109. Tanaka SK, Zhu T, Lund JR, Howitt RE, Jenkins MW et al. 2006. Climate warming and water management adaptation for California. Clim. Change 76:3361–87
     [Google Scholar]
  110. Thayer AW. 2018. Climate, water, water markets, and Texas agriculture: three essays PhD Diss. Texas A&M Univ. College Station, TX:
     [Google Scholar]
  111. Tyner WE, Bottum JC, Doering O, McCarl BA, Miller WL et al. 1979. The potential of producing energy from agriculture. Final Rep. Off. Technol. Assess., Purdue Univ. Sch. Agric. West Lafayette, IN: https://agris.fao.org/agris-search/search.do?recordID=US19820836957
    [Google Scholar]
  112. Upananda V, Abeysinghe HKIP. 2021. A review of literature in applying the Ricardian model to analyse economic impact of climate change on agriculture Presented at the 7th International Research Conference on Humanities & Social Sciences (IRCHSS) 2021, Univ. Sri Jayewardenepura Gangodawila, Sri Lanka: Mar. 18–19
    [Google Scholar]
  113. van Meijl H, Havlik P, Lotze-Campen H, Stehfest E, Witzke P et al. 2018. Comparing impacts of climate change and mitigation on global agriculture by 2050. Environ. Res. Lett. 13:6064021
     [Google Scholar]
  114. Wang ML, McCarl BA. 2021. Impacts of climate change on livestock location in the US: a statistical analysis. Land 10:111260
     [Google Scholar]
  115. Wang ML, McCarl BA, Wei H, Shiva L. 2021. Unintended consequences of agricultural participation in voluntary carbon markets: their nature and avoidance. Complex 2021:e9518135
     [Google Scholar]
  116. Wang ZM, Wlodarz M, McCarl BA. 2019. Asset fixity and economic competitiveness of US ethanol production. Biomass Bioenergy 122:37–44
     [Google Scholar]
  117. Weindl I, Lotze-Campen H, Popp A, Müller C, Havlík P et al. 2015. Livestock in a changing climate: production system transitions as an adaptation strategy for agriculture. Environ. Res. Lett. 10:094021
     [Google Scholar]
  118. West TO, Post WM. 2002. Soil organic carbon sequestration rates by tillage and crop rotation. Soil Sci. Soc. Am. J. 66:1930–46
     [Google Scholar]
  119. Weyant J. 2017. Some contributions of integrated assessment models of global climate change. Rev. Environ. Econ. Policy 11:1115–37
     [Google Scholar]
  120. Yu CH. 2014. Case studies on the effects of climate change on water, livestock and hurricanes PhD Diss. Texas A&M Univ College Station, TX:
     [Google Scholar]
  121. Zhang YW, Cai YX, Beach RH, McCarl BA. 2014. Modeling climate change impacts on the US agricultural exports. J. Integr. Agric. 13:4666–76
     [Google Scholar]
  122. Zhang YW, Hagerman AD, McCarl BA. 2013. Influence of climate factors on spatial distribution of Texas cattle breeds. Clim. Change 118:2183–95
     [Google Scholar]
  123. Zhang YW, McCarl BA. 2013. US agriculture under climate change: an examination of climate change effects on ease of achieving RFS2. Econ. Res. Int. 2013:e763818
     [Google Scholar]
/content/journals/10.1146/annurev-resource-101422-041745
Loading
The Role and Use of Mathematical Programming in Agricultural, Natural Resource, and Climate Change Analysis
Annual Review of Resource Economics 15, 383 (2023); https://doi.org/10.1146/annurev-resource-101422-041745
/content/journals/10.1146/annurev-resource-101422-041745
/content/journals/10.1146/annurev-resource-101422-041745
Loading

Data & Media loading...

  • Article Type: Review Article

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error