Predicting long-term food demand, cropland use, and prices

Annual Review of Resource Economics

Volumn 8, Issue 1, 2016, Pages 417-441

  Hertel, Thomas W ^a   Baldos, Uris Lantz C ^a   Van Der Mensbrugghe, Dominique ^a  

^a PURDUE UNIVERSITY   (United States)

Author keywords

Agricultural output; Crop prices; Food security; Land use; Projections; Total factor productivity

Indexed keywords

EID: 84990973744     PISSN: 19411340     EISSN: 19411359     Source Type: Journal    
DOI: 10.1146/annurev-resource-100815-095333     Document Type: Review

References (55)

1. Abbott P, Hurt C, Tyner WE. 2009. What's driving food prices? March 2009 update. Iss. Rep., Farm Found., Oak Brook, IL
2. Abbott P, Hurt C, Tyner WE. 2011. What's driving food prices in 2011? Iss. Rep., Farm Found., Oak Brook, IL
3. Ahmed SA, Hertel T, Lubowski R. 2008. Calibration of a land cover supply function using transition probabilities. Res. Memo. 14, Cent. Glob. Trade Anal. Proj., Dep. Agric. Econ., Purdue Univ., West Lafayette, IN
4. Alexandratos N, Bruinsma J. 2012. World agriculture towards 2030/2050: The 2012 revision. Work. Pap. 12-03, Food Agric. Organ., Rome
5. Alston JM, Beddow JM, Pardey PG. 2009. Agricultural research, productivity, and food prices in the long run. Science 325:1209-10
6. Baldos ULC, Hertel TW. 2013. Looking back to move forward on model validation: insights from a global model of agricultural land use. Environ. Res. Lett. 8:034024
7. Baldos ULC, HertelTW. 2014. Bursting the bubble: a long run perspective on crop commodity prices. Work. Pap. 80, Cent. Glob. Trade Anal. Proj., Dep. Agric. Econ., Purdue Univ., West Lafayette, IN. http://www. gtap. agecon. purdue. edu/resources/res-display. asprecordID=4574
8. Brown L, Eckholm EP. 1974. By Bread Alone. New York: Praeger
9. Chen Y-HH, Paltsev S, Reilly JM, Morris JF, Babiker MH. 2015. The MIT EPPA6 model: economic growth, energy use, and food consumption. Tech. Rep., MIT Joint Prog. Sci. Policy Glob. Change, Cambridge, MA
10. Dietrich JP, Schmitz C, Lotze-Campen H, Popp A, Müller C. 2014. Forecasting technological change in agriculture-an endogenous implementation in a global land use model. Technol. Forecast. Soc. Change 81:236-49
11. Ehrilch PR. 1970. The Population Bomb. New York: Sierra Club/Ballantine
12. Foresight. 2011. The future of food and farming: challenges and choices for global sustainability. Rep., Gov. Off. Sci., London
13. Fuglie KO. 2012. Productivity growth and technology capital in the global agricultural economy. In Productivity Growth In Agriculture: An International Perspective, ed. KO Fuglie, SL Wang, VE Ball, pp. 335-68. Cambridge, MA: CAB Int.
14. Fujimori S, Masui T, Matsuoka Y. 2012. AIM/CGE [basic] manual. Disc. Pap. 2012-01, Cent. Social Environ. Syst. Res., Natl. Inst. Environ. Stud., Ibaraki, Jpn.
15. Griffith R, Redding S, Reenen JV. 2004. Mapping the Two Faces of R&D: productivity growth in a panel of OECD industries. Rev. Econ. Stat. 86:883-95
16. Hertel TW. 2011. The global supply and demand for agricultural land in 2050: A perfect storm in the making? Am. J. Agric. Econ. 93:259-75
17. IEA (Int. Energy Agency). 2014. World Energy Outlook. Paris: OECD
18. Just RE, Pope RD. 2001. The agricultural producer: Theory and statistical measurement. In Handbook of Agricultural Economics, ed. B Gardner, GC Rausser, pp. 631-75. New York: North-Holland
19. Kavallari A, Conforti P, van der Mensbrugghe D. 2016. The Global Agriculture Perspectives System (GAPS): Version 1. 0. ESA Work. Pap., Food Agric. Organ., Rome
20. Keeney R, Hertel TW. 2009. Indirect land use impacts of US biofuels policies: The importance of acreage, yield and bilateral trade responses. Am. J. Agric. Econ. 91:895-909
21. Kriegler E, O'Neill BC, Hallegatte S, Kram T, LempertRJ, et al. 2012. The need for and use of socio-economic scenarios for climate change analysis: a new approach based on shared socio-economic pathways. Glob. Environ. Change 22:807-22
22. Lotze-Campen H, Müller C, Bondeau A, Rost S, Popp A, LuchtW. 2008. Global food demand, productivity growth, and the scarcity of land and water resources: a spatially explicit mathematical programming approach. Agric. Econ. 39:325-38
23. Ludena CE, Hertel TW, Preckel PV, Foster K, Nin A. 2007. Productivity growth and convergence in crop, ruminant, and nonruminant production: measurement and forecasts. Agric. Econ. 37:1-17
24. Malthus TR. 1888. An Essay on the Principle of Population. Edinburgh/London: Ballantyne. 9th ed.
25. McCalla AF, Revoredo CL. 2001. Prospects for global food security: a critical appraisal of past projections and predictions. Disc. Pap., Int. Food Policy Res. Inst., Washington, DC
26. Meadows DH, Meadows DL, Randers JIII WWB. 1972. The Limits to Growth: A Report for the Club of Rome's Project on the Predicament of Mankind. New York: Universe
27. Monfreda C, Ramankutty N, Hertel TW. 2009. Global agricultural land use data for climate change analysis. In Economic Analysis of Land Use in Global Climate Change Policy, ed. TWHertel, S Rose, R Tol, pp. 33-48. London: Routledge
28. MorrisMD. 1991. Factorial sampling plans for preliminary computational experiments. Technometrics 33:161-74
29. Muhammad A, Seale JL Jr., Meade B, Regmi A. 2011. International evidence on food consumption patterns: an update using 2005 international comparison program data. Tech. Bull. TB-1929, Econ. Res. Serv., US Dep. Agric., Washington, DC
30. Narayanan GB, Aguiar A, McDougall R, eds. 2015. Global Trade, Assistance, and Production: The GTAP 9 data base. Cent. Glob. Trade Anal., Purdue Univ., West Lafayette, IN
31. Nelson G, RosegrantMW, Palazzo A, Gray I, Ingersoll C, et al. 2010. Food security, farming, and climate change to 2050: scenarios, results, policy options. Res. Monogr., Int. Food Policy Res. Inst., Washington, DC
32. OECD (Organ. Econ. Coop. Dev.) 2001. Market Effects of Crop Support Measures. Paris: OECD
33. O'Neill B, Kriegler E, Riahi K, Ebi K, Hallegatte S, et al. 2014. A new scenario framework for climate change research: The concept of shared socioeconomic pathways. Clim. Change 122:387-400
34. Oxfam. 2011. Growing a Better Future: Food Justice in a Resource-Constrained World. Oxford, UK: Oxfam
35. Pant HM. 2002. Global Trade and Environment Model (GTEM): A computable general equilibrium model of the global economy and environment. Rep., Aust. Bur. Agric. Resour. Econ., Canberra, Aust.
36. Prins AG, Eickhout B, Banse M, Meijl HV, Rienks W, Woltjer G. 2011. Global impacts of European agricultural and biofuel policies. Ecol. Sci. 16:49
37. Ricardo D. 1817. On the Principles of Political Economy and Taxation. London: John Murray
38. Robinson S, Mason-D'Croz D, Islam S, Sulser T, Robertson R, et al. 2015. The International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT): model description for Version 3. Disc. Pap. 01483, Int. Food Policy Res. Inst., Washington, DC
39. Robinson S, MeijlHV, WillenbockelD, Valin H, Fujimori S, et al. 2014. Comparing supply-side specifications in models of global agriculture and the food system. Agric. Econ. 45:21-35
40. Sands R, Jones C, Marshall E. 2014. Global drivers of agricultural demand and supply. Econ. Res. Rep. ERR-174, Econ. Res. Serv., US Dep. Agric., Washington, DC
41. Schmitz C, van MeijlH, Kyle P, Nelson GC, Fujimori S, et al. 2014. Land-use change trajectories up to 2050: insights from a global agro-economic model comparison. Agric. Econ. 45 (1):69-84
42. Schultz TW. 1951. A framework for land economics. The long view. J. Farm Econ. 33:204-15
43. Schultz TW. 1953. The declining economic importance of agricultural land. In The Economic Organization of Agriculture, ed. Schultz TW, pp. 125-45. New York: McGraw-Hill
44. Sumner DA. 1982. The off-farm labor supply of farmers. Am. J. Agric. Econ. 64 (3):499-509
45. Tilman D, Balzer C, Hill J, Befort BL. 2011. Global food demand and the sustainable intensification of agriculture. PNAS 108:20260-64
46. Tweeten L, Thompson S. 2008. Long-term global agricultural output supply-demand balance and real farm and food prices. Work. Pap. AEDE-WP 0044-08, Ohio State Univ., Columbus, OH
47. Tyrchniewicz EW, Schuh GE. 1966. Regional supply of hired labor to agriculture. Am. J. Agric. Econ. 48 (3):537-56
48. Valin H, Havlík P, Forsell N, Frank S, Mosnier A, et al. 2013. Description of the GLOBIOM (IIASA) model and comparison with the MIRAGE-BioF (IFPRI) model. Rep., Ecofys, Sci. Glob. Insight, E4Tech, Utrecht, Neth.
49. Valin H, Sands RD, van der Mensbrugghe D, Nelson GC, Ahammad H, et al. 2014. The future of food demand: understanding differences in global economic models. Agric. Econ. 45:51-67
50. van der Mensbrugghe D. 2008. Environmental Impact and Sustainability Applied General Equilibrium (ENVISAGE) Model. Washington, DC:World Bank
51. von Lampe M, Willenbockel D, Ahammad H, Blanc E, Cai Y, et al. 2014. Why do global long-term scenarios for agriculture differ An overview of the AgMIP global economic model intercomparison. Agric. Econ. 45 (1):3-20
52. Westhoff P. 2010. The Economics of Food: How Feeding and Fueling the Planet Affects Food Prices. Upper Saddle River, NJ: Financ. Times
53. Wise M, Calvin K. 2011. GCAM 3. 0 Agriculture and land use: Technical description of modeling approach. Rep. PNNL-20971, Pac. Northwest Natl. Lab., US Dep. Energy, Richland, WA
54. Woltjer G, KuiperM. 2014. The MAGNET model. Man. LEI 4-057, Wageningen Univ., Wageningen, Neth. http://www. magnet-model. org/MagnetModuleDescription. pdf
55. World Bank. 2009. Global Economic Prospects 2009: Commodities at the Crossroads. Washington, DC: World Bank