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Abstract
Climate change is often related to various adverse effects, among those are endangering food security and raising the risk of conflict. Some scholars go as far as identifying climate change as the main driver of civilisational crisis. But empirical evidence is rather inconclusive so far, particularly about its relationship to violence, and even more so, genocide. In this article, we provide a literature review of studies explaining certain forms of violence and especially the connections between climate change and violence as well as an empirical study about the connections of climate variables (temperature and rainfall) and agricultural production in sub-Sahara Africa. Further, we also provide an assessment of institutional risk factors given the historical record of sub-Saharan African states with respect to genocide and projections about the future development of agricultural production for the first half of the twenty-first century to also assess environmental risk. In doing so, we are able to identify countries of joint risk and promising directions of further research. In this context, we chose sub-Saharan Africa as our focus area for various reasons: first, because of widespread poverty, institutional weakness and dependence on rain-fed agriculture, sub-Saharan Africa is the macro region where the effects of climate change will very likely play out most adversely; further, it also assembles a pronounced historical record of violent conflict, notably including genocidal episodes; finally, mutual enforcement and endogeneity issues are particularly viable there, not the least in the form of a large potential impact of technological and institutional improvements.
Acknowledgements
We thank Alvaro Caldazilla (Kiel Institute for the World Economy) for improving the quality of projections, Ian Harris (East Anglia University) for providing updated climate data, the participants of a session of the 2011 annual meeting of the Austrian Economic Association in Graz, the participants of a session of the 2013 Jan Tinbergen Peace Science Conference in Milan, and an anonymous referee for valuable comments on earlier versions of this article.
Notes on Contributors
Andreas Exenberger is assistant professor of economic and social history at the Leopold-Franzens-University of Innsbruck (Austria) and speaker of the cluster ‘World order and extremes’ of the research platform ‘Religion – politics – art: platform for conflict and communication research’. His main interests are globalization history, hunger and violence, with an increasing focus on Africa, especially the Congo region and the Horn of Africa. His publications include the edited volumes Afrika: Kontinent der Extreme? (2011) and Facetten der Umweltkrise (2010), both with innsbruck university press. Besides that he has published about fifty articles and book chapters, among those (with Simon Hartmann) ‘Extractive institutions in the Congo: checks and balances in the longue durée’, and (co-)published or (co-)edited another ten books. In 2009, he achieved the venia docendi with an essay collection about ‘The economic and social history of globalization with special consideration of the hunger problem’. Further, he is vice president of the Society for Communication and Development in Salzburg.
Andreas Pondorfer is PhD candidate and researcher at the Kiel Institute for the World Economy, funded by BIOACID (Biological Impacts of Ocean Acidification). His current research interests are African agricultural development in historical perspective, conflicts, climate change and risk. In 2011, he graduated in management and economics from the University of Innsbruck (Austria) with an empirical diploma thesis in economic and social history about ‘Small scale farming: the impact of climate change on agricultural production in Sub-Sahara African countries from 1961 to 2000’.
Notes
1 See Nicolas Stern, Stern Review on the Economics of Climate Change (London: HM Treasury Cabinet Office, 2006); and IPCC, Climate Change 2007: Fourth Assessment Report (Geneva: Intergovernmental Panel on Climate Change, 2007).
2 Jürgen Zimmerer, ‘From the Editors: Environmental Genocide? Climate Change, Mass Violence and the Question of Ideology’, Journal of Genocide Research 9, no. 3 (2007): 350.
3 UNDP, Human Development Report 2007/2008: Fighting Climate Change: Human Solidarity in a Divided World (New York: United Nations Development Programme, 2007), 90.
4 Charles H. Anderton, ‘Choosing Genocide: Economic Perspectives on the Disturbing Rationality of Race Murder’, Defence and Peace Economics 21, nos 5–6 (2010): 459–86.
5 See for example Jürgen Scheffran, Michael Brzoska, Jasmin Kominek, P. Michael Link, Janpeter Schilling, ‘Climate Change and Violent Conflict’, Science 336 (18 May 2012): 870, for a schematic view of the nexus between the climate system, natural resources, human security and societal stability; David D. Zhang, Harry F. Lee, Cong Wang, Baosheng Li, Qing Pei, Jane Zhang and Yulun An, ‘The Causality Analysis of Climate Change and Large-Scale Human Crisis’, Proceedings of the National Academy of Sciences 108, no. 42 (2011): 17298, for a general model of the relations between climate change and economy, society and human ecology; and Halvard Buhaug, Nils Petter Gleditsch and Ole Magnus Theisen, Implications of Climate Change for Armed Conflict (Washington, DC: World Bank, 2008), for the multifaceted relationship between adverse climate change and the increased risk of armed conflict.
6 Nils Petter Gleditsch, ‘Whither the Weather? Climate Change and Conflict’, Journal of Peace Research 49, no. 1 (2012): 6.
7 This is also the essential argument in UNDP, Human Development Report 2007/2008, 90–2.
8 See the PITF homepage, especially http://www.systemicpeace.org/inscr/PITFGenoPoliticides2010.xls.
9 See the Genocide Watch homepage, especially http://genocidewatch.net/alerts-2/newalerts/. The Central African Republic has recently been added to the list of emergencies.
10 For the concept of ‘democide’ see Rudolph J. Rummel, Death by Government (New Brunswick, NJ: Transaction Publishers, 1994).
11 See, for example, Matthew Krain, ‘State-Sponsored Mass Murder: The Onset and Severity of Genocides and Politicides’, Journal of Conflict Resolution 41, no. 3 (1997): 331–60, especially on opportunity; Paul Collier and Anke Hoeffler, ‘On Economic Causes of Civil War’, Oxford Economic Papers 50, no. 4 (1998), 563–73, the origin of quantitative civil war studies of the resource curse type; James D. Fearon and David D. Laitin, ‘Ethnicity, Insurgency, and Civil War’, American Political Science Review 97, no. 1 (2003): 75–90, especially (critical) on ethnicity; Joshua W. Busby, Todd G. Smith, Kaiba L. White and Shawn M. Strange, ‘Climate Change and Insecurity: Mapping Vulnerability in Africa’, International Security 37, no. 4 (2013): 132–72, who virtually map multifaceted vulnerabilities on a regional scale in all of Africa.
12 See Paul Collier and Anke Hoeffler, ‘Beyond Greed and Grievance: Feasibility and Civil War’, Oxford Economic Papers 61, no. 1 (2009), 1–27.
13 Barbara Harff, ‘No Lessons Learned from the Holocaust? Assessing Risks of Genocide and Political Mass Murder Since 1955’, American Political Science Review 97, no. 1 (2003): 61.
14 Harff, ‘No Lessons Learned’, 67. But there is large uncertainty and the 95% confidence interval in the presence of all risk factors ranges from 67 to 98%. However, Harff was also able to ‘postdict’ episodes (genocides and non-genocides alike) with a remarkable accuracy of 74%.
15 Ibid., 61.
16 See William Easterly, Roberta Gatti and Sergio Kurlat, ‘Development, Democracy, and Mass Killings’, Journal of Economic Growth 11, no. 2 (2006): 129–56.
17 Ibid., 146.
18 See Frank W. Wayman and Atsushi Tago, ‘Explaining the Onset of Mass Killing, 1949–87’, Journal of Peace Research 47, no. 1 (2010): 3–13.
19 Deborah Mayersen and Stephen McLoughlin, ‘Risk and Resilience to Mass Atrocities in Africa: A Comparison of Rwanda and Botswana’, Journal of Genocide Research 13, no. 3 (2011): 247–69.
20 Jon Barnett and W. Neil Adger, ‘Climate Change, Human Security, and Violent Conflict’, Political Geography 26, no. 6 (2007): 644.
21 Ole Magnus Theisen, Helge Holtermann and Halvard Buhaug, ‘Climate Wars? Assessing the Claim that Drought Breeds Conflict’, International Security 36, no. 3 (2011–12): 105.
22 See Zhang et al., ‘The Causality Analysis’; also Richard S.J. Tol and Sebastian Wagner, ‘Climate Change and Violent Conflict in Europe Over the Last Millennium’, Climatic Change 99, nos 1–2 (2010): 65–79, found that conflict was more likely in Europe in periods of cooling, but less likely so in the industrial era.
23 See William Cline, Global Warming and Agriculture: Impact Estimates by Country (Washington, DC: Center for Global Development and the Peterson Institute for International Economics, 2007).
24 Erik Gartzke, ‘Could Climate Change Precipitate Peace?’ Journal of Peace Research 49, no. 1 (2012): 177–92, argues that industrial development is at the same time promoting climate change but diminishing the likelihood of inter-state war.
25 See Melissa Dell, Benjamin F. Jones and Benjamin A. Olken, Climate Change and Economic Growth: Evidence From the Last Half Century, NBER Working Paper No. 14132 (Washington, DC: National Bureau of Economic Research, 2008).
26 See Quan Li and Rafael Reuveny, ‘Democracy and Environmental Degradation’, International Studies Quarterly 50, no. 4 (2006): 935–56.
27 Conor Devitt and Richard S.J. Tol, ‘Civil War, Climate Change, and Development: A Scenario Study for Sub-Saharan Africa’, Journal of Peace Research 49, no. 1 (2012): 141.
28 Vally Koubi, Thomas Bernauer, Anna Kalbhenn and Gabriele Spilker, ‘Climate Variability, Economic Growth, and Civil Conflict’, Journal of Peace Research 49, no. 1 (2012): 117.
29 See Christopher K. Butler and Scott Gates, ‘African Range Wars: Climate, Conflict, and Property Rights’, Journal of Peace Research 49, no. 1 (2012): 23–34.
30 See Cullen S. Hendrix and Idean Salehyan, ‘Climate Change, Rainfall, and Social Conflict in Africa’, Journal of Peace Research 49, no. 1 (2012): 45. Also Edward Miguel, Shanker Satyanath and Ernest Sergenti, ‘Economic Shocks and Civil Conflict: An Instrumental Variables Approach’, Journal of Political Economy 112, no. 4 (2004): 725–53, find comparable nonlinearities.
31 Clionadh Raleigh, ‘Political Marginalization, Climate Change, and Conflict in African Sahel States’, International Studies Review 12, no. 1 (2010): 69.
32 Busby et al., ‘Climate Change and Insecurity’.
33 For more details and discussions see Andreas Exenberger and Andreas Pondorfer, Rain, Temperature and Agricultural Production: The Impact of Climate Change in Sub-Sahara Africa, 1961–2009, Working Papers in Economics and Statistics, No. 26 (Innsbruck: Faculty of Economics and Statistics, 2011). We estimated the function log(ϒit) = β0 + β1log(Lit) + β2log(Vit) + β3log(Fit) + β4log(Kit) + β5log(Mit) + β6log(Rit) + β7log(PRCit) + β8log(TEMPit) + β9log(Droughtit), with β0 = log(A), i.e. productivity, i denoting country and t denoting year. ϒ represents the agricultural output (measured as the Food and Agriculture Organization (FAO) index in value terms), while L, V, F, K, M and R refer to input factors, i.e. labour, livestock, fertiliser, capital, land and irrigation. PRC, TEMP and Drought denote the climatic factors: precipitation, temperature and incidence of droughts. Considering the fact that there are unobserved country specific and time varying effects, a two-way error component regression model (two-way fixed effects) is chosen for the analysis. The methodology is based on Jess Benhabib and Mark M. Spiegel, ‘The Role of Human Capital in Economic Development, Evidence From Aggregate Cross-Country Data’, Journal of Monetary Economics 34, no. 2 (1994): 143–73, and Robert Solow, ‘A Contribution to the Theory of Economic Growth’, Quarterly Journal of Economics 70, no. 1 (1956): 65–94.
34 All agricultural inputs are taken from the FAOSTAT database (http://faostat.fao.org/), the agricultural output data Y are measured in international US$, indexed with relation to a base period 2004–2006. We introduce the variable R, which is irrigated area in thousands of hectares, including areas equipped for full and partial control of irrigation, equipped lowland areas, pastures and areas equipped for spate irrigation. Climate data (normalised average annual rainfall and temperature on country level) are taken from the Tyndall Centre for Climate Change Research and Ian Harris from East Anglia University (http://www.cru.uea.ac.uk/~timm/cty/obs/TYN_CY_1_1.html until 2000, Ian Harris from 2001 to 2009). Data about the droughts are taken from the international disaster database (http://www.emdat.be/). For details see Exenberger and Pondorfer, Rain, Temperature and Agricultural Production, 10–14.
35 For other examples of aggregate agricultural production functions in Africa, see for example, George Frisvold and Kevin Ingram, ‘Sources of Agricultural Productivity Growth and Stagnation in Sub-Saharan Africa’, Agricultural Economics 1, no. 1 (1995): 51–61; and Salvador Barrios, Bazoumana Ouattara and Eric Strobl, ‘The Impact of Climatic Change on Agricultural Production: Is it Different for Africa?’, Food Policy 33, no. 4 (2008): 287–98. Only the latter also include climate effects.
36 What we call ‘genocidal violence’ here is a summary of geno-/politicides according to the PITF definition: ‘Genocide and politicide events involve the promotion, execution, and/or implied consent of sustained policies by governing elites or their agents [ … ] that result in the deaths of a substantial portion of a communal group or politicized non-communal group. In genocides the victimized groups are defined primarily in terms of their communal (ethnolinguistic, religious) characteristics. In politicides, by contrast, groups are defined primarily in terms of their political opposition to the regime and dominant groups.’ Political Instability Task Force, State Failure Problem Set: Internal Wars and Failures of Governance, 1955–2012. http://www.systemicpeace.org/inscr/PITFProbSetCodebook2012.pdf (accessed 2 May 2013), 14–15.
37 In an interview study of 340 Rwandan households, it is shown that besides male sex and Tutsi ethnicity, also (higher) age and (larger) land ownership were relevant risk factors for being killed. See Philip Verwimp, ‘Testing the Double-Genocide Thesis for Central and Southern Rwanda’, Journal of Conflict Resolution 47, no. 4 (2003): 423–42. The same is shown for Burundi in 1993 by making use of a representative sample of 7520 households. See Tom Bundervoet, ‘Livestock, Land and Political Power: The 1993 Killings in Burundi’, Journal of Peace Research 46, no. 3 (2009): 357–76.
38 From , only the episode in Burundi, starting in October 1993, had a possible connection to bad weather, not even climate. In October and November 1993, the two first months of the wet season, rainfall fell short by three quarters compared to a 30-year average.
39 This may also be the case in Ethiopia in the 1970s and even more in the 1980s, when repression by the communist regime and secessionist war were also connected to a deterioration of food security.
40 A factor is regarded as being ‘present’ when the country performance is below the sample median.
41 A comparable approach is used by Devitt and Tol, ‘Civil War, Climate Change, and Development’, but their story is about civil war and drought risk as well as the effects of civil wars and climate change on economic growth until 2100.
42 See IPCC, Emission Scenarios. A Special Report of IPCC Working Group III (Geneva: Intergovernmental Panel on Climate Change, 2000). The A1 scenario family assumes a future world of rapid economic growth and convergence, increased interactions and low population growth (A1B referring to a ‘balanced’ use of fossil and non-fossil sources of energy). The A2 scenario family assumes a heterogeneous world of self-reliance, in which economic growth is slower, but population growth larger.
43 We use population projections from Stuart R. Gaffin, Cynthia Rosenzweig, Xiaoshi Xing and Greg Yetman, ‘Downscaling and Geo-Spatial Gridding of Socio-Economic Projections from the IPCC Special Report on Emissions Scenarios (SRES)’, Global Environmental Change 14, no. 2 (2004): 104–23, using the same quantitative procedure for all countries in our sample. Concerning agricultural land, we apply FAOSTAT data and constant area for the A2 scenario, a continued trend (with respect to the average growth 1990–2010) for the A1B scenario, and an accelerated trend (1.5 times the average growth 1990–2010) for the A1B_TT scenario. Concerning livestock, we apply a linear trend and assume an increase by 50% until 2050 (with respect to the average stock 2005–2009) for the A2 scenario, and an increase by 150% for the A1B and A1B_TT scenarios. Concerning tractors, fertilisers and irrigation, we assume constant stocks (only in the A1B1_TT scenario, the elasticity of fertiliser and irrigation is constantly increasing to 0.1 in 2050, which is not overly optimistic, because Barrios et al., ‘The Impact of Climatic Change’, for example, estimated a coefficient of 0.078 in Asian countries for the use of fertilisers in the period 1961–2000).
44 Temperature and rainfall projections are calculated as comparisons of 30-year averages (from 14 years before until 15 years after the respective year) with base period averages (1961–1990), calibrated with Tyndall Centre for Climate Change Research data. Projections are based on Pete D. Falloon and Richard A. Betts, ‘The Impact of Climate Change on Global River Flow in HadGEM1 Simulations’, Atmospheric Science Letters 7, no. 3 (2006): 62–8; Peter A. Stott, Gareth S. Jones, Jason A. Lowe, Peter Thorne, Chris Durman, Timothy C. Johns and Jean-Claude Thelen, ‘Transient Climate Simulations With the HadGEM1 Climate Model: Causes of Past Warming and Future Climate Change’, Journal of Climate 19, no. 12 (2006): 2763–82; Timothy C. Johns et al., ‘The New Hadley Centre Climate Model HadGEM1: Evaluation of Coupled Simulations’, Journal of Climate 19, no. 7 (2006): 1327–53; and G.M. Martin, M.A. Ringer, V.D. Pope, A. Jones, C. Dearden and T.J. Hinton, ‘The Physical Properties of the Atmosphere in the New Hadley Centre Global Environmental Model, HadGEM1. Part 1: Model Description and Global Climatology’, Journal of Climate 19, no. 7 (2006): 1274–301.
45 IPCC, Climate Change 2007, WG2, Ch. 5, Section 5.8.1 ‘Findings and Key Conclusions’; these particular conclusions are made ‘with high confidence’ in a statistical sense.
46 The data used to construct a multiplicative index are taken from Angus Maddison (GDP) and FAOSTAT (nutritional energy); see http://www.ggdc.net/MADDISON/oriindex.htm and http://faostat.fao.org/ respectively.
47 Harff, ‘No Lessons Learned’; Krain, ‘State-Sponsored Mass Murder’.
48 Although Sudan is excluded from our analysis and Kenya does not figure prominently because of its relatively positive agricultural outlook, on average, a connected example for a study combining theoretical and empirical work is provided by Jürgen Scheffran, Tobias Ide and Janpeter Schilling, ‘Violent Climate or Climate of Violence? Concepts and Relations with Focus on Kenya and Sudan’, The International Journal of Human Rights 18, no. 3 (2014): 369–90.
49 On the interplay between climate change and culture in the case of the Pacific island of Chuuk, see Rebecca Hofmann, ‘Culturecide in Changing Micronesian Climates? About the Unintenionality of Climate Change’, The International Journal of Human Rights 18, no. 3 (2014): 336–49.
50 See Gregory Kent, ‘Crystallisations of the Global Western State in the Era of Climate Change’, The International Journal of Human Rights 18, no. 3 (2014): 320–35.
51 See Mark Levene and Daniele Conversi, ‘Subsistence Societies, Globalisation, Climate Change and Genocide: Discourses of Vulnerability and Resilience’, The International Journal of Human Rights 18, no. 3 (2014): 281–97.