Skip to main content
SpringerLink
Log in

The Microbehavioral Economic Models of Adaptation Behaviors to Global Warming

  • Chapter
  • First Online:
The Economics of Global Allocations of the Green Climate Fund

  • 408 Accesses

Abstract

From this chapter on, four scientific traditions that provide useful empirical information to both the decision-makers of the Green Climate Fund and the evaluators of the GCF decisions are explained, the first of which is the microbehavioral economic models of adaptation to global warming. The microbehavioral economics examines how an individual manager of agricultural and natural resources chooses an optimal portfolio of resources, taking the given climate factors into account, to maximize the profit earned from the portfolio over the long-term. This chapter explains major empirical findings from the microbehavioral studies conducted through the farm household surveys in Africa, Latin America, and South Asia. In response to or anticipation of climatic shifts, behavioral changes of individuals occur, among other things, by switching from one enterprise to another among the natural resource enterprises, or from one crop or animal species to another, or from a specialized portfolio to a diversified portfolio. The results offer valuable insights to the GCP policy-makers on which natural resource portfolio is most vulnerable as well as on how natural source mangers should adapt to future climatic changes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Adams R, Rosenzweig C, Peart RM, Ritchie JT, McCarl BA, Glyer JD, Curry RB, Jones JW, Boote KJ, Allen LH (1990) Global climate change and US agriculture. Nature 345:219–224

    Google Scholar 

  • Adams R, McCarl BA, Segerson K, Rosenzweig C, Bryant K, Dixon BL, Conner R, Evenson RE, Ojima D (1999) The economic effects of climate change on US agriculture. In: Mendelsohn R, Neumann J (eds) The impact of climate change on the United States economy. Cambridge University Press, Cambridge

    Google Scholar 

  • Ainsworth EA, Long SP (2005) What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytol 165:351–371

    Google Scholar 

  • Amundson JL, Mader TL, Rasby RJ, Hu QS (2006) Environmental effects on pregnancy rate in beef cattle. J Anim Sci 84:3415–3420

    Article  Google Scholar 

  • Anselin L (1988) Spatial econometrics: methods and models. Kluwer Academic Publishers, Dordrecht

    Book  Google Scholar 

  • Baethgen WE (1997) Vulnerability of agricultural sector of Latin America to climate change. Clim Res 9:1–7

    Article  Google Scholar 

  • Basist A, Peterson N, Peterson T, Williams C (1998) Using the special sensor microwave imager to monitor land surface temperature, wetness, and snow cover. J Appl Meteorol 37:888–911

    Article  Google Scholar 

  • Berkson J (1944) Application of the logistic function to bio-assay. J Am Stat Assoc 39:357–365

    Google Scholar 

  • Beron KJ, Vijberberg WPM (2004) Probit in a spatial context: a Monte Carlo approach. In: Anselin L, Florax RJGM, Rey SJ (eds) Advances in spatial econometrics: methodology, Tools and Applications. Springer, Heidelberg, pp 169–192

    Chapter  Google Scholar 

  • Biondi F, Gershunov A, Cayan DR (2001) North pacific decadal climate variability since 1661. J Clim 14:5–10

    Article  Google Scholar 

  • Bliss CI (1934a) The method of probits. Science 79:38–39

    Article  Google Scholar 

  • Bliss CI (1934b) The method of probits. Science 79:409–410

    Article  Google Scholar 

  • Bohme R, Christin N, Edelman B, Moore T (2015) Bitcoin: economics, technology, and governance. J Econ Perspect 29:213–238

    Article  Google Scholar 

  • Bourguignon F, Fournier M, Gurgand M (2004) Selection bias corrections based on the multinomial logit model: Monte-Carlo comparisons. DELTA working paper no. 20. De’partement et Laboratoire d’Economie The’orique et Applique’e (DELTA), Paris

    Google Scholar 

  • Byerlee D, Eicher CK (1997) Africa’s emerging maize revolution. Lynne Rienner Publishers Inc., Boulder

    Google Scholar 

  • Chung CE, Ramanathan V (2006) Weakening of North Indian SST gradients and the monsoon rainfall in India and the Sahel. J Clim 19:2036–2045

    Article  Google Scholar 

  • Commonwealth Scientific and Industrial Research Organization (CSIRO) (2018) Future feed. CSIRO, Canberra. Accessed from https://research.csiro.au/futurefeed/

    Google Scholar 

  • Curtis S, Adler RF, Huffman GJ, Nelkin E, Bolvin D (2001) Evolution of tropical and extratropical precipitation anomalies during the 1997 to 1999 ENSO cycle. Int J Climatol 21:961–971

    Article  Google Scholar 

  • Dahl GB (2002) Mobility and the returns to education: testing a Roy model with multiple markets. Econometrica 70:2367–2420

    Article  Google Scholar 

  • Dai A, Trenberth KE, Qian T (2004) A global dataset of palmer drought severity index for 1870–2002: relationship with soil moisture and effects of surface warming. J Hydrometeorol 5:1117–1130

    Article  Google Scholar 

  • Danielson JJ, Gesch DB (2011) Global multi-resolution terrain elevation data 2010 (GMTED2010). US Geo-logical Survey Open-File Report 2011–1073, 26 p

    Google Scholar 

  • Darwin RF, Tsigas M, Lewandrowski J, Raneses A (1995) World agriculture and climate change: economic adaptations. U.S. Department of Agriculture (USDA). Economic Research Service, Washington, DC

    Google Scholar 

  • Denman KL, Brasseur G, Chidthaisong A, Ciais P, Cox PM, Dickinson RE, Hauglustaine D, Heinze C, Holland E, Jacob D, Lohmann U, Ramachandran S, da Silva Dias PL, Wofsy SC, Zhang X (2007) Couplings between changes in the climate system and biogeochemistry. In: Solomon S et al (eds) Climate change 2007: the physical science basis. The Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Deschenes O, Greenstone M (2007) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. Am Econ Rev 97:354–385

    Article  Google Scholar 

  • Dinar A, Hassan R, Mendelsohn R, Benhin J (2008) Climate change and agriculture in Africa: impact assessment and adaptation strategies. EarthScan, London

    Google Scholar 

  • Driessen P, Deckers J, Nachtergaele F (2001) Lecture notes on the major soils of the world. Food and Agriculture Organization (FAO), Rome

    Google Scholar 

  • Dubin JA, McFadden DL (1984) An econometric analysis of residential electric appliance holdings and consumption. Econometrica 52(2):345–362

    Article  Google Scholar 

  • Dudal R (1980) Soil-related constraints to agricultural development in the tropics. International Rice Research Institute, Los Banos

    Google Scholar 

  • Easterling DR, Evans JL, Groisman PY, Karl TR, Kunkel KE, Ambenje P (2000) Observed variability and trends in extreme climate events: a brief review. Bull Am Meteorol Soc 81:417–425

    Article  Google Scholar 

  • Efron B (1981) Nonparametric estimates of standard error: the jackknife, the bootstrap and other methods. Biometrika 68:589–599

    Article  Google Scholar 

  • Evenson R, Gollin D (2003) Assessing the impact of the Green Revolution 1960–2000. Science 300:758–762

    Article  Google Scholar 

  • FAO (2005) Global agro-ecological assessment for agriculture in the twenty-first century (CD-ROM). FAO land and water digital media series. FAO, Rome

    Google Scholar 

  • FAO (2012) FAO STAT. FAO Statistics Division, Rome. Available at http://faostat.fao.org

    Google Scholar 

  • Fischer G, Shah M, Tubiello FN, van Velhuizen H (2005) Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990–2080. Philos Trans R Soc B 360:2067–2083

    Article  Google Scholar 

  • Fisher I (1906) The nature of capital and income. Macmillan, New York

    Google Scholar 

  • Fisher I (1930) The theory of interest. Macmillan, New York

    Google Scholar 

  • Fisher FM (1966) The identification problem in econometrics. McGraw-Hill, New York

    Google Scholar 

  • Food and Agriculture Organization (FAO) (1978) Report on agro-ecological zones (vol. 1): methodology and results for Africa. FAO, Rome

    Google Scholar 

  • Food and Agriculture Organization (FAO) (2003) The digital soil map of the world (DSMW) CD-ROM. FAO, Rome

    Google Scholar 

  • Ford J, Katondo KM (1977) Maps of tsetse fly (Glossina) distribution in Africa, 1973, according to subgeneric groups on a scale of 1: 5000000. Bull Anim Health Prod Afr 15:187–193

    Google Scholar 

  • Fox NJ, Marion G, Davidson RS, White PCL, Hutchings MR (2012) Livestock helminths in a changing climate: approaches and restrictions to meaningful predictions. Animals 2:93–107

    Article  Google Scholar 

  • Geweke J (1989) Bayesian inference in econometric models using Monte Carlo integration. Econometrica 57:1317–1339

    Article  Google Scholar 

  • Gitay H, Brown S, Easterling W, Jallow B (2001) Ecosystems and their goods and services. In: McCarthy JJ et al (eds) Climate change 2001: impacts, adaptations, and vulnerabilities. The IPCC. Cambridge University Press, Cambridge

    Google Scholar 

  • Gordon C, Cooper C, Senior CA, Banks HT, Gregory JM, Johns TC, Mitchell JFB, Wood RA (2000) The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Clim Dyn 16:147–168

    Article  Google Scholar 

  • Green Climate Fund (GCF) (2011) Governing instrument for the Green Climate Fund. GCF, Songdo City

    Google Scholar 

  • Green Climate Fund (GCF) (2018a) Annex III: investment framework. GCF, Songdo City

    Google Scholar 

  • Green Climate Fund (GCF) (2018b) Status of pledges and contributions made to the Green Climate Fund, status date: 29 January 2018. GCF, Songdo City

    Google Scholar 

  • Green Climate Fund (GCF) (2018c) Projects + Programmes. GCF, Songdo City. Accessed from https://www.greenclimate.fund/what-we-do/projects-programmes

    Google Scholar 

  • Hahn GL (1981) Housing and management to reduce climate impacts on livestock. J Anim Sci 52:175–186

    Article  Google Scholar 

  • Hahn GL (1999) Dynamic responses of cattle to thermal heat loads. J Anim Sci 77:10–20

    Article  Google Scholar 

  • Hahn GL, Gaughan JB, Mader TL, Eigenberg RA (2009) Chapter 5: Thermal indices and their applications for livestock environments. In: DeShazer JA (ed) Livestock energetics and thermal environmental management. American Society of Agricultural and Biological Engineers, St. Joseph

    Google Scholar 

  • Hajivassiliou V, McFadden D (1998) The method of simulated scores for the estimation of LDV models. Econometrica 66:863–896

    Article  Google Scholar 

  • Hansen J, Sato M, Reudy R (2012) Perception of climate change. Proc Natl Acad Sci U S A 109:E2415–E2423

    Article  Google Scholar 

  • Harris I, Jones PD, Osborn TJ, Lister DH (2014) Updated high-resolution grids of monthly climatic observations – the CRU TS3.10 Dataset. Int J Climatol 34:623–642

    Article  Google Scholar 

  • Heckman J (1979) Sample selection bias as a specification error. Econometrica 47:153–162

    Article  Google Scholar 

  • Hotelling H (1931) The economics of exhaustible resources. J Polit Econ 39(2):137–175

    Article  Google Scholar 

  • Hristov AN, Joonpyo OH, Fabio Giallongo F, Tyler W, Frederick TW, Michael T, Harper MT, Holley L, Weeks HL, Antonio F, Branco AF, Peter J, Moate PJ, Matthew H, Deighton MH, SRO W, Kindermann M, Duval S (2015) An inhibitor persistently decreased enteric methane emission from dairy cows with no negative effect on milk production. Proc Natl Acad Sci 112(34):10663–10668

    Article  Google Scholar 

  • Hulme M, Doherty RM, Ngara T, New MG, Lister D (2001) African climate change: 1900–2100. Clim Res 17:145–168

    Article  Google Scholar 

  • Indian Institute of Tropical Meteorology (IITM) (2012) Homogeneous Indian monthly rainfall data sets & Indian regional monthly surface air temperature data set. IITM, Pune

    Google Scholar 

  • Intergovernmental Panel on Climate Change (IPCC) (1990) Climate change: the IPCC scientific assessment. Cambridge University Press, Cambridge

    Google Scholar 

  • Intergovernmental Panel on Climate Change (IPCC) (2014) Climate change 2014: the physical science basis. The fifth assessment report of the IPCC. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Janowiak JE (1988) An investigation of interannual rainfall variability in Africa. J Clim 1:240–255

    Article  Google Scholar 

  • Johnson HD (1965) Response of animals to heat. Meteorol Monogr 6:109–122

    Google Scholar 

  • Johnston J, DiNardo J (1997) Econometric methods, 4th edn. McGraw-Hill, New York

    Google Scholar 

  • Kafle K, Winter-Nelson A, Goldsmith P (2016) Does 25 cents more per day make a difference? The impact of livestock transfer and development in rural Zambia. Food Policy 65:62–72

    Article  Google Scholar 

  • Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47:263–291

    Article  Google Scholar 

  • 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 75:387–398

    Article  Google Scholar 

  • Kala N (2015) Ambiguity aversion and learning in a changing world: the potential effects of climate change from Indian agriculture. Ph.D. dissertation, Yale University, New Haven

    Google Scholar 

  • Kazianga H, Udry C (2006) Consumption smoothing? Livestock, insurance, and drought in rural Burkina Faso. J Dev Econ 79:413–446

    Article  Google Scholar 

  • Keane M (1994) A computationally practical simulation estimator for panel data. Econometrica 62:95–116

    Article  Google Scholar 

  • Kempton TJ, Murray RM, Leng RA (1976) Methane production and digestibility measurements in the grey kangaroo and sheep. Aust J Biol Sci 29:209–214

    Article  Google Scholar 

  • Koopmans TC (1951) Efficient allocation of resources. Econometrica 19:455–465

    Article  Google Scholar 

  • Koopmans TC (1965) On the concept of optimal economic growth. Academiae Scientiarum Scripta Varia 28(1):1–75

    Google Scholar 

  • Kurukulasuriya P, Mendelsohn R, Hassan R, Benhin J, Diop M, Eid HM, Fosu KY, Gbetibouo G, Jain S, Mahamadou A, El-Marsafawy S, Ouda S, Ouedraogo M, Sène I, Maddision D, Seo SN, Dinar A (2006) Will African agriculture survive climate change? World Bank Econ Rev 20:367–388

    Article  Google Scholar 

  • Kurukulasuriya P, Kala N, Mendelsohn R (2011) Adaptation and climate change impacts: a structural Ricardian model of irrigation and farm income in Africa. Clim Change Econ 2:149–174

    Article  Google Scholar 

  • Le Treut H, Somerville R, Cubasch U, Ding Y, Mauritzen C, Mokssit A, Peterson T, Prather M (2007) Historical overview of climate change. In: Solomon S et al (eds) Climate change 2007: the physical science basis. The fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Lee LF (1983) Generalized econometric models with selectivity. Econometrica 51:507–512

    Article  Google Scholar 

  • Mader TL, Davis MS (2004) Effect of management strategies on reducing heat stress of feedlot cattle: feed and water intake. J Anim Sci 82:3077–3087

    Article  Google Scholar 

  • Mader TL, Frank KL, Harrington JA, Hahn GL, Nienaber JA (2009) Potential climate change effects on warm-season livestock production in the Great Plains. Clim Chang 97:529–541

    Article  Google Scholar 

  • Magrin G, Garcia CG, Choque DC, Gimenez JC, Moreno AR, Nagy GJ, Nobre C, Villamizar A (2007) Latin America. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Climate change 2007: impacts, adaptation, and vulnerability. Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 581–615

    Google Scholar 

  • Markowitz H (1952) Portfolio selection. J Financ 7:77–91

    Google Scholar 

  • Mata LJ, Campos M et al (2001) Latin America. In: McCarthy JJ, Canziani OF, Leary NA, Dokken DJ, White KS (eds) Climate change 2001: impacts, adaptation, and vulnerability. Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • May W (2011) The sensitivity of the Indian summer monsoon to a global warming of 2 degrees C with respect to pre-industrial times. Clim Dyn 37:1843–1868

    Article  Google Scholar 

  • McFadden DL (1974) Conditional logit analysis of qualitative choice behavior. In: Zarembka P (ed) Frontiers in econometrics. Academic, New York, pp 105–142

    Google Scholar 

  • McFadden D (1999) Sampling and selection. Lecture note. University of California, Berkeley

    Google Scholar 

  • McFadden D, Train K (2000) Mixed MNL models for discrete response. J Appl Econ 15:447–470

    Article  Google Scholar 

  • Meehl GA, Hu A (2006) Megadroughts in the Indian monsoon region and southwest North America and a mechanism for associated multidecadal Pacific sea surface temperature anomalies. J Clim 19:1605–1623

    Article  Google Scholar 

  • Mendelsohn R, Nordhaus W, Shaw D (1994) The impact of global warming on agriculture: a Ricardian analysis. Am Econ Rev 84:753–771

    Google Scholar 

  • Mendelsohn R, Kurukulasuriya P, Basist A, Kogan F, Williams C (2007) Measuring climate change impacts with satellite versus weather station data. Clim Chang 81:71–83

    Article  Google Scholar 

  • Mollick E (2014) The dynamics of crowdfunding: an exploratory study. J Bus Ventur 29:1–16

    Article  Google Scholar 

  • Moran PAP (1950a) Notes on continuous stochastic phenomena. Biometrika 37:17–23

    Article  Google Scholar 

  • Moran PAP (1950b) A test for the serial dependence of residuals. Biometrika 37:178–181

    Article  Google Scholar 

  • Nakicenovic N, Davidson O, Davis G, Grübler A, Kram T, La Rovere EL, Metz B, Morita T, Pepper W, Pitcher H, Sankovski A, Shukla P, Swart R, Watson R, Dadi Z (2000) Emissions scenarios. A special report of Working Group III of the Intergovernmental Panel on Climate Change. IPCC, Geneva

    Google Scholar 

  • Nash J (1951) Non-cooperative games. Ann Math 54(2):286–295

    Article  Google Scholar 

  • National Aeronautics and Space Administration (NASA) (2018) Missions: Earth Observing System (EOS). NASA, Washington, DC. Accessed from https://eospso.nasa.gov/mission-category/3

    Google Scholar 

  • National Research Council (NRC) (2015) Critical role of animal science research in food security and sustainability. National Academies Press, Washington, DC

    Google Scholar 

  • New M, Lister D, Hulme M, Makin I (2002) A high-resolution data set of surface climate over global land areas. Clim Res 21:1–25

    Article  Google Scholar 

  • Nordhaus WD (1973) The allocation of energy resources. Brook Pap Econ Act 1973(3):529–576

    Article  Google Scholar 

  • Porter JH, Parry ML, Carter TR (1991) The potential effects of climatic change on agricultural insect pests. Agric For Meteorol 57:221–240

    Article  Google Scholar 

  • Rahmstorf S, Coumou D (2011) Increase of extreme events in a warming world. Proc Natl Acad Sci U S A 108:17905–17909

    Article  Google Scholar 

  • Ricardo D (1817) On the principles of political economy and taxation. John Murray, London

    Google Scholar 

  • Samuelson P (1938) A note on the pure theory of consumers’ behaviour. Economica 5:61–71

    Article  Google Scholar 

  • Samuelson P (1954) The pure theory of public expenditure. Rev Econ Stat 36:387–389

    Article  Google Scholar 

  • Schlenker W, Roberts M (2009) Nonlinear temperature effects indicate severe damages to crop yields under climate change. Proc Natl Acad Sci U S A 106(37):15594–15598

    Article  Google Scholar 

  • Schlesinger WH (1997) Biogeochemistry: an analysis of global change, 2nd edn. Academic, San Diego

    Google Scholar 

  • Schmertmann CP (1994) Selectivity bias correction methods in polychotomous sample selection models. J Econ 60:101–132

    Article  Google Scholar 

  • Schmidt GA, Ruedy R, Hansen JE et al (2005) Present day atmospheric simulations using GISS ModelE: comparison to in-situ, satellite and reanalysis data. J Clim 19:153–192

    Article  Google Scholar 

  • Schoengold K, Zilberman D (2007) The economics of water, irrigation, and development. In: Evenson R, Pingali P (eds) Handbook of agricultural economics, vol 3. Elsevier, Amsterdam, pp 2933–2977

    Google Scholar 

  • Seo SN (2006) Modeling farmer responses to climate change: climate change impacts and adaptations in livestock management in Africa. Ph.D. dissertation, Yale University, New Haven

    Google Scholar 

  • Seo SN (2010a) A microeconometric analysis of adapting portfolios to climate change: adoption of agricultural systems in Latin America. Appl Econ Perspect Policy 32:489–514

    Article  Google Scholar 

  • Seo SN (2010b) Is an integrated farm more resilient against climate change? A micro-econometric analysis of portfolio diversification in African agriculture? Food Policy 35:32–40

    Article  Google Scholar 

  • Seo SN (2010c) Managing forests, livestock, and crops under global warming: a microeconometric analysis of land use changes in Africa. Aust J Agric Resour Econ 54(2):239–258

    Article  Google Scholar 

  • Seo SN (2011a) An analysis of public adaptation to climate change using agricultural water schemes in South America. Ecol Econ 70:825–834

    Article  Google Scholar 

  • Seo SN (2011b) A geographically scaled spatial analysis of adaptation to climate change by agricultural systems in Africa. J Agric Sci 149:437–449

    Article  Google Scholar 

  • Seo SN (2012a) Adapting natural resource enterprises under global warming in South America: a mixed logit analysis. Economia 12:111–135

    Google Scholar 

  • Seo SN (2012b) Decision making under climate risks: an analysis of sub-Saharan farmers’ adaptation behaviors. Weather Climate Soc 4:285–299

    Article  Google Scholar 

  • Seo SN (2013a) An essay on the impact of climate change on US agriculture: weather fluctuations, climatic shifts, and adaptation strategies. Climate Change 121:115–124

    Article  Google Scholar 

  • Seo SN (2013b) Refining spatial resolution and spillovers of a microeconometric model of adapting portfolios to climate change. Mitig Adapt Strateg Glob Chang 18:1019–1034

    Article  Google Scholar 

  • Seo SN (2014a) Evaluation of agro-ecological zone methods for the study of climate change with micro farming decisions in sub-Saharan Africa. Eur J Agron 52:157–165

    Article  Google Scholar 

  • Seo SN (2014b) Adapting sensibly when global warming turns the field brown or blue: a comment on the 2014 IPCC report. Econ Aff 34:399–401

    Article  Google Scholar 

  • Seo SN (2015a) Micro-behavioral economics of global warming: modeling adaptation strategies in agricultural and natural resource enterprises. Springer, Cham

    Google Scholar 

  • Seo SN (2015b) Helping low-latitude, poor countries with climate change. Regul Winter 2015–2016:6–8

    Google Scholar 

  • Seo SN (2016a) Modeling farmer adaptations to climate change in South America: a micro-behavioral economic perspective. Environ Ecol Stat 23:1–21

    Article  Google Scholar 

  • Seo SN (2016b) The micro-behavioral framework for estimating total damage of global warming on natural resource enterprises with full adaptations. J Agric Biol Environ Stat 21:328–347

    Article  Google Scholar 

  • Seo SN (2016c) Untold tales of goats in deadly Indian monsoons: adapt or rain-retreat under global warming? J Extreme Events 3:1650001. https://doi.org/10.1142/S2345737616500019

    Article  Google Scholar 

  • Seo SN (2016d) Microbehavioral econometric methods: theories, models, and applications for the study of environmental and natural resources. Academic Press (Elsevier), Amsterdam

    Google Scholar 

  • Seo SN (2017) The behavioral economics of climate change: adaptation behaviors, global public goods, breakthrough technologies, and policy-making. Academic Press (Elsevier), Amsterdam

    Google Scholar 

  • Seo SN (2018) Natural and man-made catastrophes: theories, economics, and policy designs. Wiley-Blackwell, Hoboken

    Book  Google Scholar 

  • Seo SN (2019) Will farmers fully adapt to monsoon climate? J Agric Sci (under revision)

    Google Scholar 

  • Seo SN, Mendelsohn R (2008a) Measuring impacts and adaptations to climate change: a structural Ricardian model of African livestock management. Agric Econ 38:151–165

    Google Scholar 

  • Seo SN, Mendelsohn R (2008b) A Ricardian analysis of the impact of climate change impacts on South American farms. Chilean J Agric Res 68:69–79

    Google Scholar 

  • Seo SN, Mendelsohn R, Dinar A, Hassan R, Kurukulasuriya P (2009) A Ricardian analysis of the distribution of climate change impacts on agriculture across agro-ecological zones in Africa. Environ Resour Econ 43:313–332

    Article  Google Scholar 

  • Seo SN, McCarl B, Mendelsohn R (2010) From beef cattle to sheep under global warming? An analysis of adaptation by livestock species choice in South America. Ecol Econ 69:2486–2494

    Article  Google Scholar 

  • Shanahan TM, Overpeck JT, Anchukaitis KJ, Beck JW, Cole JE, Dettman DL, Peck JA, Scholz CA, King JW (2009) Atlantic forcing of persistent drought in West Africa. Science 324:377–380

    Article  Google Scholar 

  • Shaw MR, Zavaleta ES, Chiariello NR, Cleland EE, Mooney HA, Field CB (2002) Grassland responses to global environmental changes suppressed by elevated CO2. Science 298:1987–1990

    Article  Google Scholar 

  • Shiller RJ (2003) From efficient markets theory to behavioral finance. J Econ Perspect 17:83–104

    Article  Google Scholar 

  • Shiller RJ (2005) Irrational exuberance, 2nd edn. Princeton University Press, Princeton

    Google Scholar 

  • Steiger C (2006) Modern beef production in Brazil and Argentina. Choices Mag 21:105–110

    Google Scholar 

  • Strzepek K, McCluskey A (2006) District level hydroclimatic time series and scenario analyses to assess the impacts of climate change on regional water resources and agriculture in Africa. CEEPA discussion paper no. 13. Centre for Environmental Economics and Policy in Africa, University of Pretoria, Pretoria

    Google Scholar 

  • Sutherst RW (1991) Pest risk analysis and the greenhouse effect. Rev Agric Entomol 79:1177–1187

    Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498

    Article  Google Scholar 

  • Thaler RH (2015) Misbehaving: the making of behavioral economics. W.W. Norton Company, New York

    Google Scholar 

  • Train K (2003) Discrete choice methods with simulation. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Tubiello FN, Ewert F (2002) Simulating the effects of elevated CO2 on crops: approaches and applications for climate change. Eur J Agron 18:57–74

    Article  Google Scholar 

  • Tubiello FN, Amthor JA, Boote KJ, Donatelli M, Easterling W, Fischer G, Gifford RM, Howden M, Reilly J, Rosenzweig C (2007) Crop response to elevated CO2 and world food supply. Eur J Agron 26:215–223

    Article  Google Scholar 

  • Udry C (1995) Risk and saving in Northern Nigeria. Am Econ Rev 85:1287–1300

    Google Scholar 

  • United Nations Framework Convention on Climate Change (UNFCCC) (1992) United nations framework convention on climate change. UNFCCC, New York

    Google Scholar 

  • United Nations Framework Convention on Climate Change (UNFCCC) (2011) Report of the transitional committee for the design of Green Climate Fund. UNFCCC, New York

    Google Scholar 

  • United Nations Framework Convention on Climate Change (UNFCCC) (2015) The Paris agreement. Conference of the Parties (COP) 21. UNFCCC, New York

    Google Scholar 

  • United States Animal Health Association (USAHA) (2008) Foreign animal diseases-the gray book, 7th edn. Committee on Foreign and Emerging Diseases of the USAHA, St. Joseph

    Google Scholar 

  • United States Department of Agriculture (USDA) (2012) Census of agriculture 2012. USDA, Washington, DC. Accessed from https://www.agcensus.usda.gov/Publications/2012/#full_report

    Google Scholar 

  • University of Alabama in Huntsville (UAH) (2018) Global temperature record. The Earth System Science Center, UAH. https://www.nsstc.uah.edu/climate/

  • Vedeld P, Angelsen A, Bojø J, Sjaastad E, Kobugabe GK (2007) Forest environmental incomes and the rural poor. Forest Policy Econ 9:869–879

    Article  Google Scholar 

  • von Neumann J, Morgenstern O (1947) Theory of games and economic behavior, 2nd edn. Princeton University Press, Princeton

    Google Scholar 

  • von Thünen JH (1826) Der Isolierte Staat in Beziehung auf Landwirtschaft und Nationalökonomie, Hamburg, Perthes. (English trans. by Wartenberg CM (1996) The Isolated State. Pergamon Press, Oxford)

    Google Scholar 

  • Welch JR, Vincent JR, Auffhammer M, Moya PF, Dobermann A, Dawe D (2010) Rice yields in tropical/subtropical Asia exhibit large but opposing sensitivities to minimum and maximum temperatures. Proc Natl Acad Sci U S A 107:14562–14567

    Article  Google Scholar 

  • White N, Sutherst RW, Hall N, Whish-Wilson P (2003) The vulnerability of the Australian beef industry to impacts of the Cattle Tick (Boophilus microplus) under climate change. Clim Chang 61:157–190

    Article  Google Scholar 

  • World Bank (2008) World development report 2008: agriculture for development. World Bank, Washington, DC

    Book  Google Scholar 

  • World Bank (2009a) Africa Infrastructure and Country Diagnostics (AICD). World Bank, Washington, DC. Available from: http://www.infrastructureafrica.org/aicd/

    Google Scholar 

  • World Bank (2009b) Awakening Africa’s sleeping giant: prospects for commercial agriculture in the Guinea Savannah Zone and beyond. World Bank and FAO, Washington, DC

    Google Scholar 

  • World Bank (2017) Climate change knowledge portal for development practitioners and policy makers: Thailand. World Bank, Washington, DC

    Google Scholar 

  • World Resources Institute (WRI) (2005) World resources 2005: the wealth of the poor—managing ecosystems to fight poverty. WRI, Washington, DC

    Google Scholar 

  • Ziska LH (2003) Evaluation of yield loss in field-grown sorghum from a C3 and C4 weed as a function of increasing atmospheric carbon dioxide. Weed Sci 51:914–918

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Muaebak Institute of Global Warming Studies, Seorim-dong, Gwanak-gu, Seoul, Korea

    S. Niggol Seo

Authors
  1. S. Niggol Seo
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Seo, S.N. (2019). The Microbehavioral Economic Models of Adaptation Behaviors to Global Warming. In: The Economics of Global Allocations of the Green Climate Fund. Springer, Cham. https://doi.org/10.1007/978-3-030-18274-8_3

Download citation

Publish with us

Policies and ethics

Search

Navigation