IFPRI Discussion Paper 01841 May, 2019 bEcon 4 Africa An overview of the literature on the economic assessment of GE crops in the continent, 1996-2016 Patricia Zambrano Namita Paul Judith Chambers José Falck-Zepeda Hillary Hanson Environment Production and Technology Division INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE The International Food Policy Research Institute (IFPRI), established in 1975, provides research-based policy solutions to sustainably reduce poverty and end hunger and malnutrition. IFPRI’s strategic research aims to foster a climate-resilient and sustainable food supply; promote healthy diets and nutrition for all; build inclusive and efficient markets, trade systems, and food industries; transform agricultural and rural economies; and strengthen institutions and governance. Gender is integrated in all the Institute’s work. Partnerships, communications, capacity strengthening, and data and knowledge management are essential components to translate IFPRI’s research from action to impact. The Institute’s regional and country programs play a critical role in responding to demand for food policy research and in delivering holistic support for country-led development. IFPRI collaborates with partners around the world. AUTHORS Patricia Zambrano* (a.p.zambrano@cgiar.org) is a Senior Program Manager in the Environment and Production Technology Division of the International Food Policy Research Institute (IFPRI), Washington, DC. Namita Paul (n.paul@cgiar.org) is a Research Analyst in the Director General’s Office of IFPRI, Washington, DC. Judy Chambers (j.chambers@cgiar.org) is Director of the Program for Biosafety Systems in the Environment and Production Technology Division of IFPRI, Washington, DC. José Falck-Zepeda (j.falck-zepeda@cgiar.org) is a Senior Research Fellow in the Environment and Production Technology Division of IFPRI, Washington, DC. Hillary Hanson (h.hanson@cgiar.org) is a Program Coordinator in the Environment and Production Technology Division of IFPRI, Washington, DC. *Corresponding author Notices 1 IFPRI Discussion Papers contain preliminary material and research results and are circulated in order to stimulate discussion and critical comment. They have not been subject to a formal external review via IFPRI’s Publications Review Committee. Any opinions stated herein are those of the author(s) and are not necessarily representative of or endorsed by IFPRI. 2 The boundaries and names shown and the designations used on the map(s) herein do not imply official endorsement or acceptance by the International Food Policy Research Institute (IFPRI) or its partners and contributors. 3 Copyright remains with the authors. The authors are free to proceed, without further IFPRI permission, to publish this paper, or any revised version of it, in outlets such as journals, books, and other publications mailto:a.p.zambrano@cgiar.org mailto:n.paul@cgiar.org mailto:j.chambers@cgiar.org mailto:j.falck-zepeda@cgiar.org mailto:h.hanson@cgiar.org iii ABSTRACT The International Food Policy Research Institute (IFPRI) published the first method-focused assessment of the applied economic literature about the ex ante and ex post impacts of genetically engineered crops in developing countries in 2009. The overall findings have since been documented by other authors and have been the subject of several other studies and meta-analyses. Of the 154 papers analyzed in the cited IFPRI 2009 publications, only 25 were focused on Africa. Ten years later, this paper shows that the number of publications for Africa has nearly tripled, reaching a total of 72 publications. We gathered, classified, and reviewed all 72 Africa-focused publications. Most of the papers continue to focus on South Africa, an early adopter of the technology and, until 2007, the only African country that had commercialized GE crops. Today, even after the commercialization of insect resistant crops in Burkina Faso, Egypt, and Sudan, and the recent approval for commercialization of insect resistant cotton in Nigeria and Ethiopia, South Africa continues to be the most represented country in the literature and is the focus of 30 of the 72 publications. Nevertheless, a shift is occurring. Whereas only 4 African countries were represented in 2006, there are now 24. Additionally, the crop-focus of this literature has also expanded from mainly cotton to include a wider variety of crop/technologies, such as bacillus thuringiensis (Bt)/nutritionally enhanced banana, Bt tomato, and drought-resistant maize, among others. In addition to documenting and analyzing this Africa-focused literature, this paper documents a total of 353 performance indicators related to the actual or projected changes in yields, gross income, and input use contained in the papers focus of this review. A summary of these performance indicators has also been compiled as a searchable database available to all potential users, including practitioners, interested decision and policy makers, as well as businesses and donors not only to facilitate further research, but also as reference to advance specific GE policies, and to increase awareness related to GE technology performance. Keywords: Genetically engineered crops, biotechnology, GM. Africa, literature review, findings http://54.160.157.145/Becon/ iv ACKNOWLEDGMENTS This work was undertaken as part of Biotechnology and Biosafety Rapid Assessment and Policy Platform (BioRAPP), led by IFPRI’s Program for Biosafety Systems (PBS.) BioRAPP is a project co-funded by the Bill and Melinda Gates Foundation and the U.S. Agency for International Development (USAID) and supported by the CGIAR Research Program on Policies, Institutions, and Markets (PIM), led by IFPRI and funded by CGIAR Fund Donors. This paper has not gone through IFPRI’s standard peer-review procedure. The opinions of the authors expressed herein do not necessarily state or reflect those of IFPRI, or CGIAR. All errors and interpretations are the sole responsibility of the authors. v Contents Abstract ........................................................................................................................................................ iii Acknowledgements ...................................................................................................................................... iv Tables ........................................................................................................................................................... vi Figures .......................................................................................................................................................... vi 1. Introduction ...................................................................................................................................... 1 2. Distilling the Africa-focused literature .............................................................................................. 2 3. bEcon 4 Africa ................................................................................................................................... 7 4. Summary of findings ....................................................................................................................... 10 4.1 Impacts on farmers ................................................................................................................... 11 4.2 Impacts on industry/sector ...................................................................................................... 13 4.3. Impacts on consumers ............................................................................................................. 14 4.4 Other emerging themes ........................................................................................................... 14 5. The political economy of GE crop adoption in Africa ..................................................................... 15 6. Conclusions and way forward ......................................................................................................... 16 References .................................................................................................................................................. 18 Annex .......................................................................................................................................................... 23 vi Tables Table 1 Count of Africa-focused publications, 2006. ................................................................................... 3 Table 2 Count of Africa focused publications cited in meta-analyses/reviews, by country. 2015 .............. 4 Table 3 Africa: Indicators for Africa, Areal et al., 2013 ................................................................................. 4 Table 4 South Africa: Meta-analysis, Finger et al., 2011. ............................................................................. 5 Table 5 bEcon 4 Africa: Count of papers, by country and crop* ................................................................. 9 Table 6 GE crops product pipeline in selected African countries, 2014/18 ............................................... 10 Table 7 bEcon 4 Africa: Number of farm-level indicators by country and crop ......................................... 12 Table 8 bEcon 4 Africa: Number of farm-level indicators by type ............................................................. 12 Table 9 bEcon 4 Africa: Farm level indicators, percentage difference between GE crops and conventional ............................................................................................................................................... 13 Table 10 bEcon 4 Africa: Industry/sector papers by country and crop, 2001-2016 .................................. 14 Table A 1 bEcon 4 Africa: Count of publications by country, crop, and trait, 1998-2016 ......................... 23 Table A 2 bEcon 4 Africa: Papers on the impacts of GE crops on farms, details and DOI links, 2001-2016 .................................................................................................................................................................... 24 Table A 3 bEcon 4 Africa: Papers on the impacts of GE crops on industry/sector, details and DOI links, 2001-2016 ................................................................................................................................................... 28 Table A 4 bEcon 4 Africa: Papers on the impacts of GE crops on consumers, details and DOI links, 2001- 2016 ............................................................................................................................................................ 30 Table A 5 bEcon 4 Africa: Papers on the impacts of GE crops on gender, cost of regulation, environment, and poverty; details and DOI links, 2001-2016 ........................................................................................... 31 Figures Figure 1 bEcon 4 Africa: Number of papers by year of publication, 1999-2016 ........................................... 8 Figure 2 bEcon 4 Africa: Count of publications by research question, 1998-2016 .................................... 11 1 1. Introduction Today genetically engineered (GE) crops are planted in 24 countries around the world (ISAAA 2017). The area planted with GE crops has expanded from 12.8 million hectares in predominantly high-income countries—the United States, Canada, and Australia—in 1996 (James 1997) to 189.8 million hectares in 2017 (ISAAA 2017). Brazil, Argentina, and India plant 45 percent of the total global area of GE crops, with 21 other non-high-income countries contributing another 9 percent (ISAAA 2017). Some authors have labeled this technology the fastest-adopted technology due to the unprecedented annual rates at which some countries have increased their planted areas of GE cotton, soybean, and maize (ISAAA 2016, Khush 2012). Despite this documented success, in the 23-year period since the first GE crop was commercialized in 1996, only 4 of the 54 African countries have commercially planted GE crops. The most notable of these is South Africa, where insect resistant (Bacillus thuringiensis - Bt) cotton was first planted in 1997. In later years, the area planted with GE crops in South Africa has expanded to include herbicide tolerant (HT) cotton, maize, and soybeans as well as stacked Bt/HT maize. Ten years elapsed between South Africa first planting Bt cotton and a second African county, Burkina Faso, commercializing a GE crop, specifically Bt cotton. The technology was a success among cotton farmers (Vitale et al. 2010) but the distribution of Bt seed had to be suspended in 2016 due to concerns related to cotton fiber length. Egypt was the third country in Africa to plant a GE crop (Bt maize) until 2012, when the Ministry of Agriculture suspended the registration of the Bt maize variety for planting and cultivation. The fourth and last country that joined this group of African GE adopters was Sudan with the commercialization of Bt cotton in 2012. More recently, Nigeria and Ethiopia have approved the commercialization of Bt cotton. This low proportion of African countries among the total GE crop adopting countries has meant that today, 23 years after the first GE crop was first planted in 1996, the area of GE crops planted in Africa represents less than 3 percent of the total GE area planted worldwide. Authors have proposed different explanations for the slow adoption of the technology by African countries (Chambers et al 2014). Explanations range from the lack of a functional regulatory system to the European-based opposition to the technology that impacts trade concerns and local decision makers (Paarlberg 2001, 2006, 2010). Special interest groups have also pointed to the lack of Africa-specific evidence regarding the actual and potential benefits of GE technology. In this paper, we address this latter concern showing that: (1) the literature on the potential and actual economic benefits of the technology has been increasing; and (2) the literature, overall, confirms positive impacts of the technology. 2 The paper presents a review of the existing literature with a focus on Africa. We gathered, classified, and analyzed a total of 72 Africa-focused publications covering 22 countries, 13 crops and 6 different traits. We have called this Africa-focused collection “bEcon 4 Africa.” This is a more detailed bibliographical review of the larger collection “bEcon”, a web-based bibliographic database developed by IFPRI researchers in 2008. The bEcon 4 Africa collection differs from its parent collection, bEcon, in that it provides not only the references but, also, documents the performance indicators for all papers. These indicators contain information related to the actual or projected changes in yields, gross income, and input use, among other information, which are available on IFPRI’s bEcon 4 Africa Indicators database (http://54.160.157.145/Becon/) This paper is organized as follows: After the introduction, we discuss the literature that has assessed the global benefits of GE technologies, distilling the Africa-focused publications. We then look at the results of the different meta-analyses and other comprehensive reviews. In section 3, we introduce the bEcon 4 Africa literature collection and give a detailed description of the criteria used in collecting and selecting papers to include in this review. Section 4 summarizes the main findings of bEcon 4 Africa literature by topic area. Categories include farmers, consumers, industry, international trade, and some new emerging themes. In Section 5 we discuss the results of this literature review in the political context of Africa. In the final section, we conclude with some overall findings and recommendations. 2. Distilling the Africa-focused literature The applied economics literature on impacts of GE crops have been the subject of numerous reviews and several meta-analyses. In 2009, Smale et al. documented the existence of 26 reviews and analyzed 154 publications about the economic impact of GE crops in developing economies. At the time, the representation of Africa in both the reviews and the applied economic assessments was very limited. Of the 26 reviews, 12 had a global focus, while 14 were concentrated on a specific country/region mostly (11) in non-industrialized parts of the world. None of the 6 reviews were specifically focused on Africa. Only 25 (23 percent) of the applied economic assessments in Smale et al. (2009) were focused on Africa, and almost all of them (18.75 percent) dealt mainly with the assessment of Bt cotton adoption in South Africa. The other mentioned papers were focused on 10 other countries: Kenya, Uganda, and 8 West African countries as detailed in Table 1. http://54.160.157.145/Becon/ 3 Table 1 Count of Africa-focused publications, 2006. Region/country Number Percentage Africa 26 16.9 • South Africa 18 11.7 • Kenya 2 1.3 • West Africa (Benin, Burkina Faso, Cameroon, CAR, Côte d’Ivoire, Mali, Senegal and Togo) 4 2.6 • Uganda 1 0.6 • Egypt 1 0.6 Other non-industrialized countries and global 128 83.1 All 154 100 Source: Compiled by authors from Smale et al. (2009). Meta-analyses and reviews published after 2009 show the number of Africa-focused economic assessment publications has been increasing gradually. Since 2011, 3 meta-analyses and 2 additional reviews have been published including Finger et al. (2011), Areal et al. (2013), Fischer et al. (2015), Racovita et al. (2015), and Klümper and Qaim (2015). We categorized each reference cited in these 5 meta-analyses and reviews, which add up to a total of 442 unique publications. Of these 442 references, 120 papers (27%) are focused on Africa. Table 2 groups the 118 papers by country of focus, excluding the two reviews. Like previous results, we find that most publications are focused on South Africa. Caution should be used in comparing the 118 papers cited in these meta analyses/reviews to the 24 collected and analyzed by Smale et al. (2009), as the selection criteria employed by the different authors are not homogenous across studies. Smale et al. (2009) included only peer-reviewed articles with an applied economic methodology, while other authors have a less restrictive criteria that includes reports published by governments as well as private organizations and non-governmental organizations. Nevertheless, the number of papers referencing GE crops in Africa indicates the increased interest of researchers in the region, even though such interest continues to be concentrated in South Africa. 4 Table 2 Count of Africa focused publications cited in meta-analyses/reviews, by country. 2015 Country/region Number % South Africa 82 68.6 Burkina Faso 11 9.2 Africa (as a continent) 7 5.9 Kenya 5 4.2 Mali 4 3.4 SSA 4 3.4 Ethiopia 2 1.7 Mozambique 1 0.8 Côte d’Ivoire, Malawi, Niger, Nigeria, Rwanda, Uganda, and Zambia 1 0.8 South Africa, Burkina Faso and Egypt 1 0.8 All 118 100 Source: Authors’ elaboration using references from Finger et al. (2011), Areal et al. (2013), Fischer et al. (2015), Racovita et al. (2015), and Klümper and Qaim (2015). Areal et al. (2013) provides detailed information on yield, cost, and gross income difference for each of the 55 papers the authors included in their meta-analysis. Unfortunately, the analysis does not separate Africa from other developing countries, since its focus was not any specific geographical region but rather the comparison between developed (11 papers) and developing economies (41). Table 3 presents a summary of all 12 references of Africa as published in Areal et al. (2012, 4-6). The mean differences show the advantage of Bt cotton and Bt maize over conventional strains in almost all studies. Table 3 Africa: Indicators for Africa, Areal et al., 2013 No. Country Trait/crop Mean difference* Author(s) Yield Cost Gross income 1 South Africa Bt cotton 0.5 4.9 72.0 Bennett et al. (2004) 2 Bt cotton 0.3 - - Bennett et al. (2005) 3 Bt cotton - 10.0 20.0 Fok et al. (2007) 4 Bt cotton 0.3 -3.8 - Gouse et al. (2003) 5 Bt cotton 0.1 14.0 - Hofs et al. (2006) 6 Bt cotton - - 26.0 Ismael et al. (2002) 7 Bt cotton 0.3 4.9 63.0 Morse et al. (2006) 8 Bt cotton - - - Bennett et al. (2003) 9 Bt cotton 0.1 -9.0 15.0 Thirtle et al. (2003) 10 Bt maize -0.1 29.0 -30.0 Gouse et al. (2009) 11 Bt maize - 11.0 - Gouse et al. (2005) 12 Mozambique Bt cotton - - 1.6 Pitoro et al. (2009) Source: Areal et al. (2013) *“absolute difference in yields, production costs and gross margins, between GM crops and conventional crops… Data collated included different measurement units for yield, production costs and gross margin. Currency units were normalized to EU/ha and deflated using year 2000 as the base year, while yield units were normalized to tonnes/ha” (Areal et al 2013) 5 These indicators along with all others collected by Areal et al. were used to compare GE crops against conventional crops in probabilistic terms using Bayesian, classical, and Bootstrap sampling statistics. The authors concluded that “the scientific evidence to date shows that adoption of GE crops is both economically and agronomically advantageous over conventional counterparts for farmers worldwide. In particular, Bt crops were found to outpace conventional crops in terms of yields and gross margins, at the expense of higher production costs” (Areal et al. 2013, 24). The Finger et al. (2011) meta-analysis compiles information from 203 publications and 721 observations contained in the papers. Within these 203 publications, the only African country assessed is South Africa, covered in 58 publications. Table 4 summarizes indicator statistics in the meta-analysis for South Africa. The statistics in Table 4 show a significant difference in gross margins with Bt cotton more than doubling the gross margin of conventional cotton. In addition, the meta-analysis shows a 52 percent reduction in pesticide costs for Bt cotton compared to costs for the conventional strains. However, the authors also conclude that the reported increase in yields cannot be generalized across South Africa or the continent, nor will this result necessarily hold over time. As underscored by the authors, this is not a surprising conclusion since pest resistant technologies protect against damage from specific insects or weeds, which need to be constitutively present for the technology to have a positive protective effect over yields. Since the data collected is from different years, pest pressures are likely to vary from one year to another due to the stochastic nature of pest attacks. Table 4 South Africa: Meta-analysis, Finger et al., 2011. Yield Gross margin Cost Seed Pesticide Mgmt. & labor Kg/ha ($/ha) Cotton • Conventional 879.6 50.2 20.1 30.3 43.3 • Bt 1133.0 107.5* 39.5*** 14.7*** 43.2 Difference % 28.8 114.0 96.8 -51.7 -0.3 Kg/ha ($/ha) Maize • Conventional 7,124 - - 19.3 46.2 • Bt 8,874 - - 8.5 46.0 Difference % 16.9 - - -62.4 0.0 Source: Finger et al. (2011) *, **, and *** denote significance at the 10, 5, and 1% level, respectively. The most recent meta-analysis was published by Klümper and Qaim in 2015. This analysis draws from the information included in 147 studies, both peer- and non-peer reviewed from around the world 6 including developed and developing economies. In these studies, the authors identified outcome variables for4 indicators: yield, pesticide use, total cost, and farmer profit, and used these results in their meta-analysis regression. Of the 147 studies, 22 papers are about Africa: 19 of them from South Africa, 2 from Burkina Faso, and 1 from Mali. Even though the authors make available all outcome observations, it is not possible to match these observations to specific studies, as the reference identification of these observations is a number that has no link to the specific study identifiers (author name, title, or publication type). To weight these outcome indicators and to bypass the problem – that many of the publications in the literature reviewed fail to publish measurement of variance of the estimated mean indicators – the authors use “the inverse of the number of impact observations per dataset as weights” (Klümper and Qaim 2015, 3). The authors run a regression using the difference of each of five outcomes: yield, pesticide quantity, pesticide cost, total cost, and farmer profit as dependent variables and include a series of independent variables. These independent variables are those identified by other authors as influencing the positive results of GE crops, such as results obtained from experimental trials, studies funded by the industry, and indicators drawn from partial budgets rather than regression models. The results of these meta-regressions are summarized as follow: Bt and HT crops have effectively increased yields (22 percent), decreased pesticide quantity (37 percent), decreased pesticide cost (39 percent), and increased farmer profit (68 percent). The results are proportionally and statistically more significant for Bt than for HT crops, which is probably explained by the fact that the HT trait substitutes for herbicide spraying. These results are consistent with those from Finger et. al (2011), in particular those summarized in Table 4, as well as the conclusions from Areal et al (2012). This is an interesting result since methodologies for data collection and analysis differ between studies, thus providing a robust support to the conclusions of Klümper and Qaim. Fisher et al. (2015) review shifted focus from economic to social impacts. The authors’ objective was to review the literature about the impact of GE crops from a social perspective, underscoring all previous reviews were addressing only economic impacts. The authors based their analysis on peer-reviewed literature published since 2004 that focused on the social impacts of GE crops at the farm level. The authors used the definition of “social” as stated by the Interorganizational Committee on Principles and Guidelines for Social Impact Assessment in the USA (2003). These guidelines define social impacts as “The consequences to human populations of any public or private actions that alter the ways in which people live, work, play, relate to one another, organize to meet their needs, and generally cope as 7 members of society. The term also includes cultural impacts involving changes to the norms, values, and beliefs that guide and rationalize their cognition of themselves and their society” as quoted by the authors (Fischer et al 2015, 8600). The authors found 99 publications, most them from developing economies or the “Global South,” in the authors’ classification, from countries that have already adopted the technology. Of these 99 papers only a few were focused on Africa, and as in the meta-analyses and earlier reviews, most come from South Africa. The authors found that most papers address the economic impacts of GE technologies, mainly yield and profitability, confirming the positive findings summarized above. 3. bEcon 4 Africa The reviews and meta-analyses described herein concentrate their attention on global or, at best, developing and industrialized countries. The representation of Africa in all of these papers is almost entirely limited to South Africa. Nevertheless, over the years, more publications on the economic assessment of GE technologies in Africa continue to be published, which merits a more careful compilation and analysis. We have used the references of both the meta-analyses and reviews, as well as other sources, to continue to populate bEcon, a web-based bibliography maintained and published by IFPRI since 2009. bEcon was initially developed as part of the Smale et al. 2009 review publication. bEcon will now include “bEcon 4 Africa”, a specific and detailed section that captures all the literature that focuses on Africa and is the basis of the analysis that follows. All papers included in bEcon 4 Africa use the selection criteria outlined in Smale et al. (2009) as well as in bEcon, which we summarize here. First, all selected papers examine the economic ex ante or ex post impact of one or more GE crops in at least one African country. Papers focusing on crop biotechnologies other than GE crops such as tissue culture are not included. Second, all papers have been published and have undergone some peer-review process. For this reason, papers published by local, state, or national governments, as well as by private organizations and non-governmental organizations, are excluded unless they explicitly indicated some level of peer review. Third, all papers use an economic method applied to specific data. Journal articles, book chapters and published conference proceedings are included. Working papers and papers accepted for presentation at conferences are not included, nor are purely theoretical studies, conceptual papers, critical essays, or opinion papers. http://ebrary.ifpri.org/cdm/search/collection/p15738coll6/order/creato 8 The final count of Africa-focused publications that follow the outlined criteria reaches 72 unique papers published from 1999 through 2016 (Figure 1). As detailed in Table 1 above, in 2006 there were only 24 Africa-focused papers documented and analyzed by Smale et al. (2009). This means that over the last 10 years, the number of publications focused on Africa has more than doubled. Figure 1 bEcon 4 Africa: Number of papers by year of publication, 1999-2016 Source: Authors’ elaboration Figure 1 not only shows the number of publications by year but also shows that over time researchers have been more focused on ex ante assessments, particularly after 2007, as the number of ex ante publications begins to outnumber ex post studies nearly every year thereafter. Interestingly, the increase in ex ante assessments follows the broader portfolio of countries and crops in the R&D pipeline. As previously shown in Table 1, Smale et al. (2009) found that in 2006 18 of the 26 Africa- focused publications were from South Africa and almost all articles (15 out of 18) were on Bt cotton. Table 5 shows that although the literature continues to be dominated by South African coverage, its share has dropped from 69 percent in 2006 (Table 1) to 42 percent in 2016. Among the 30 South African publications, 21 discuss the impact of Bt and Bt/HT stacked traits for cotton, 11 focus on Bt/HT maize and 1 looks at the impacts of Bt/HT soybean (see Table A-1, in the Annex). 0 2 4 6 8 10 12 14 1999 2001 2003 2005 2007 2009 2011 2013 2015 Ex ante Ex post All 9 Table 5 bEcon 4 Africa: Count of papers, by country and crop* Country # Papers Cotton Maize Cowpea Banana Rice Other Sum South Africa 30 21 11 - - 1 33 Kenya 14 2 6 - 1 1 4 14 Burkina-Faso 10 8 - 2 - - - 10 Uganda 12 3 1 - 7 - 3 14 Nigeria 6 1 - 4 - 1 - 6 Ghana 3 1 - 1 - - 3 5 Tanzania 2 2 - - 1 - - 3 Ethiopia 3 1 2 - - 1 3 7 Other countries 15 11 - 6 3 1 -- 21 Source: Authors’ elaboration. *Count of papers by country and crops are not unique as many of the 72 unique papers included in bEcon 4 Africa focused on more than one crop or/and more than one country. Perhaps a more interesting observation than the drop in the share of South African papers in bEcon 4 Africa is the fact that the literature now includes an expanded and more diverse collection of countries, crops, and traits (see summary in Table A-1 in the Annex). Currently, the most researched GE crop continues to be cotton, mainly Bt cotton. Other crops include maize (Bt, drought resistant, and other traits), Bt cowpea, bacterial resistant bananas, and nitrogen efficient, water efficient, and salt tolerant rice. Other crops in the literature such as millet, sorghum, cassava, and potato are worth mentioning since they are staple crops in many African countries. The new crops/trait studies explain the spike in ex ante studies depicted in Figure 1. This observation is also consistent with the expanding GE crop pipeline in Africa. Table 6 summarizes the GE crop product line for some of the countries in the region. Most of the crops/traits listed in Table 6 are in an advanced regulatory stage. For this reason, the expectation of those working in the advancement of these technologies is that these GE crops will be ready for commercialization by 2020 10 Table 6 GE crops product pipeline in selected African countries, 2014/18 Country Crop Trait Ethiopia Cotton Insect resistance – approved for commercialization Maize Insect resistance and drought tolerance Potato Disease resistance Enset Virus resistance Ghana Rice Nitrogen Use Efficiency, Water Use Efficiency, Salt Tolerance (NEWEST) Cotton Insect resistance Cowpea Insect resistance Sweet Potato Nutritional improvement Nigeria Cassava Increased level of beta-carotene (Provitamin A) Cassava Nutrition enhancement for increase in iron level Cotton Insect resistance – approved for commercialization Cowpea Insect resistance Rice Nitrogen-use efficiency, salt tolerant, water efficiency Maize Insect resistance Sorghum Bioavailability of iron, zinc, protein, vitamin A Tanzania Maize Drought tolerance – WEMA Cassava Virus resistant Uganda Maize Drought tolerance WEMA Maize Insect resistance Banana Bacterial wilt resistance Banana Nutrition enhancement (Fe and Pro-Vitamin A) Banana Nematode resistance Cassava Virus resistance Cassava Brown streak virus resistance Cotton Insect resistance and herbicide tolerance Sweet potato Sweet potato weevil resistance Sweet potato Virus resistance Rice Nitrogen Use Efficiency, Water Use Efficiency, Salt Tolerance (NEWEST) Source: Chambers et al. (2014), Personal communication, Program for Biosafety Systems experts 4. bEcon 4 Africa: Summary of findings The 72 publications contained in bEcon 4 Africa have been classified under specific research questions, following the themes analyzed by Smale et al. (2016). Figure 2 is a graphic representation of the different questions addressed by bEcon 4 Africa from 1998 through 2016. 11 Figure 2 bEcon 4 Africa: Count of publications by research question, 1998-2016 Source: Authors’ elaboration Note: *Count of papers by research theme are not unique as many of the 72 papers included in bEcon 4 Africa address more than one research topic. 4.1 Impacts on farmers Most studies in bEcon 4 Africa address the research question related to the impacts on farmers of the potential or actual adoption of GE crops. As shown in Figure 2, of the 72 studies included in bEcon 4 Africa, 41 are classified under farmers. The number of publications has more than doubled since 2006, although it is not the fastest growing research topic over the last 10 years, as indicated in Figure 2. This is discussed further in the next sections. A comprehensive list of papers related to the impact on farmers can be found in Table A-2 in the annex to this paper. For all articles focused on farm impacts/assessments, we collected and organized indicators contained in these papers such as yield and gross income. The summary tables that follow include indicators for both ex ante and ex post economic assessments Table 7 summarizes the number of indicators collected by country and crop. South Africa and cotton continue to be the most represented country and crop respectively. South Africa is the only country on the continent – and one of the few developing countries – that has a 20-year record of planting GE crops. 6 1 1 3 1 2 21 7 0 3 1 11 13 25 Others Cost of regulation International trade Review of findings Consumers Industry Farmers 1998-2006 2007-2016 12 Table 7 bEcon 4 Africa: Number of farm-level indicators by country and crop Country All Cotton Maize Tomato Sweet potato Eggplant Cabbage Banana South Africa 255 184 71 Ghana 33 0 13 11 9 Burkina Faso 24 24 Uganda 19 12 7 Kenya 18 0 6 12 Mozambique 5 5 Grand Total 354 225 77 13 12 11 9 7 Source: Authors’ elaboration. The type and number of collected indicators are listed in Table 8 below. A more detailed summary is given in Table A-3, in the annex. Table 8 bEcon 4 Africa: Number of farm-level indicators by type Indicator N Indicator N Yield 72 Income - Total 11 Cost – Seed 45 Cost - Herbicide 11 Income – Net 43 Cost - Labor harvest 9 Cost - Total 36 Cost – Tractor 5 Cost - Insecticide 24 Cost - Labor spray 5 Cost - Labor 14 Cost - Variable 5 Cost - Fertilizer 14 Cost - Labor non-bollworm 3 Cost - Pesticides 13 Cost - Labor bollworm 3 Quantity - Seed 12 All others 29 Source: Authors’ elaboration. Most indicators are for yield, cost of seed, net income, total cost, and insecticide cost. Table 9 below summarizes the information for these indicators for cotton and maize, the main crops analyzed in the literature. 13 Table 9 bEcon 4 Africa: Farm level indicators, percentage difference between GE crops and conventional Indicator n Average Min Max SD Cotton Yield 39 41.3 3.9 93.2 0.23 Cost - Seed 34 355.0 -100.0 4000 8.03 Income - Net 34 494.0 -100.0 4000 11.29 Cost - Total 18 -3.6 -35.9 56.7 0.2 Cost - Insecticide 11 -99 -192 -9.7 60.1 Maize Yield 23 35.3 4.2 29.0 0.6 Cost - Seed 10 29.5 -8.26 76.0 0.24 Income - Net - - - - - Cost - Total 8 16.1 -7.89 78.8 0.32 Cost - Insecticide 9 -55.4 -100.0 25.0 0.4 Source: Authors’ elaboration. These results are consistent with the conclusions in Smale et al. (2009) and other meta-analyses introduced previously. These publications conclude that although there is variability in the technology impacts, farmers have benefited from the adoption of Bt cotton and maize due to increases in both yield and net income. The latter is an interesting result as, on average, GE seed costs are higher. However, these higher costs are more than offset by reductions in pesticide costs and increased revenues due to higher yield thus resulting in positive net incomes. 4.2 Impacts on industry/sector Smale et al. (2009) classified all papers that estimated the aggregation and distribution of benefits between producers (farmers) and the industry as sector-related papers. We follow this classification to be able to compare the literature with earlier literature reviews and assess progress over time. Up to 2006 there were only 2 papers that focused on the estimated (ex ante) impacts of the adoption of GE crops on sector/industry in Africa. This number increased to 14 by 2016 (see Table A-3 in the Annex). Of the 15 sector/industry papers, 14 are ex ante assessments. One paper by Vitale et al. (2010) is an ex post assessment that analyzes both farm and industry impact of the adoption of Bt cotton in Burkina Faso. Table 10 below presents details about the publications which describe impacts of GE crops on industry/sector. 14 Table 10 bEcon 4 Africa: Industry/sector papers by country and crop, 2001-2016 Country/ies Cotton Maize Banana Kenya 2 Burkina Faso* 1 Mali 1 1 Uganda 1 2 Benin, Burkina Faso, Mali, Senegal, Togo 1 Benin, Burkina Faso, Chad, Mali, Togo, Cote d'Ivoire, Cameroon, CAR 1 Benin, Burkina, Cameroon, CAR, Chad, Congo, Côte d'Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Mali, Mauritania, Nigeria, Senegal, Togo 1 Benin, Burkina Faso, Mali, Senegal, Togo 1 Burundi, DRC, Kenya, Rwanda, Tanzania, Uganda 1 Benin, Burkina Faso, Chad, Cameroon, Cote d'Ivoire, CAR, Mali, Togo 1 Egypt, Ethiopia, Kenya, Tanzania, Uganda, Zambia 1 Grand Total 8 3 4 Source: Authors’ elaboration. * Only ex post study The current situation in Burkina Faso, where the planting of Bt crops has been suspended for reasons unrelated to the GE traits, merits some attention. Vitale et al. (2010) demonstrate that farmers were the main beneficiaries of the adoption of Bt cotton. The authors also show that the observed increases in seed and harvest costs were more than offset by the increase in yields, which, on average, increased 18 percent over conventional cotton. Farmers captured a slightly higher proportion (53 percent of the benefits than the seed industry. 4.3. Impacts on consumers Perceptions and attitudes of consumers can often affect the commercialization of GE crops. The literature, as described in this paper, has shown that farmers have gained or could gain from the adoption of GE crops. But to realize and sustain these gains, consumers must be willing to accept and pay for these products. Ten years ago, the literature focused on consumers was very limited even at the global level. Of the 154 studies analyzed by Smale et al. (2009), only 28 addressed impacts on consumers. Of these 28 articles, most were centered on China or India, and no studies were related to Africa. By 2016, our compilation in bEcon 4 Africa includes 12 studies (see Table A-5). 4.4 Other emerging themes Over time, authors have expanded coverage to include topics such as gender, health, environment, poverty, cost of regulation, and impacts on innovation. However, these themes still represent a smaller share as compared against the total number of themes in the literature. A total of 15 publications fall under this category. 15 5. The political economy of GE crop adoption in Africa Authors face an interesting conundrum in Africa when writing about GE crop innovation and adoption. On the one hand, countries in the region (especially the national and international research systems) working in partnership with international donors and research organizations have invested significant resources in the development of GE crops and traits of local and regional importance. These investments have led to an important R&D pipeline and several GE products which are advancing through the regulatory approval process (Chambers et al. 2014). Additional crop/trait combinations and products from next-generation techniques such as gene editing are on the horizon with very promising results (NAS 2016). As documented in bEcon 4 Africa literature review, ex post and ex ante economic impact studies demonstrate positive benefits to farmers and the agriculture sector in the region, albeit with significant variability. A smaller number of additional publications show benefits to consumers. Nevertheless, few countries in the region have adopted the technology and current commercial adoption in Africa has been largely limited to those crops and traits developed by and for industrialized agriculture. The lack of significant progress raises questions about the underlying reasons for slow adoption of GE technology and the accompanying lack of documented socioeconomic research in Africa. The explanation is complex and likely results from a combination of economic, social, legal, political, and institutional forces that converge, thereby creating what Rittel and Webber (1973) defined as a “wicked problem”1. In particular, the political economy and various institutional factors in individual countries have a direct impact on the slow adoption of GE crops across Africa. Institutional issues related to regulatory and legal frameworks covering biosafety, intellectual property, seed registration, and trade have been slow to develop in Africa and generally reflect influence from Europe, lack of experience with the technology, and a public-sector-driven approach to agriculture research and development. Biosafety has one of the most important limiting steps, with African countries overly influenced by precautionary attitudes from Europe, the African Model Law, early capacity building efforts sponsored by UNEP-GEF and subsequent interpretations of the Cartagena Protocol on Biosafety. For many years, few decision makers have had the necessary experience to 1 Wicked problems have no definite formulation or true-or-false solution. Every solution is a one-shot operation, and every problem is unique and a symptom of another problem and can be explained in numerous ways that determine diverse solution paths. 16 evaluate these new GE crops with independence and confidence, requiring significant capacity-building efforts to develop skills sets in risk assessment commensurate with best and global practices in regulatory science. In recent years, these efforts have resulted in a cadre of competent and confident regulatory professionals in Africa who are making independent biosafety decisions about GM crops. However, a critical mass is still lacking and science-based decision making, in some countries, is still overly influenced by political factors, as well as vocal and influential activist voices that remain opposed to the technology. In addition, while regulatory and legal frameworks function in the early stages of the regulatory process (e.g. confined field trials), clear and predictable regulatory pathway for commercial release remain somewhat elusive, compounded by issues related to competing legal instruments and lack of coordination among different ministries and agencies. This lack of regulatory clarity continues to impact farmer access to these new products in many countries and underscores the need for political and scientific leadership. The target then will be a science and knowledge-based global food system focused on sustainable and equitable productivity enhancement. This will be an outcome of advancing the scientific frontier, improving agricultural innovation and production policies, and researching links to emerging issues such as gender, health, and nutrition in addition to bioeconomy and sustainability. 6. Conclusions and way forward This review has shown that the economic literature assessing GE crops in Africa has been on the rise over the last 10 years, with new countries, crops, and traits being the focus of new research. Nevertheless, the literature focused on South Africa continues to dominate the existing portfolio. This is particularly true for the papers that focus on farm-level impacts and assessments. Today, several countries in Africa are working on the advancement of several GE crop projects that are at different development stages. Several GE crops are expected to reach commercialization in a few years, underscoring the need for meaningful data on the economic and social assessment of the benefits of GE crop technology. African countries require local answers to crops and traits of their interest, and they cannot look for answers about the economic assessment of these technologies from other countries that have characteristics that do not reflect their own geography or economic conditions. The data collected in this paper enrich the literature about the benefits of the technology and serve as guidance to the specific assessments that are or will be underway. Since these studies are by nature ex ante (before 17 commercialization), the indicators collected here can serve as a good basis for the assumptions on which all ex ante assessments need to rely for estimation purposes. We also expect that more papers in the literature will continue addressing broader questions by embracing complexity and dealing more with the institutional issues that seem to limit GE crop adoption in Africa. Only by embracing complexity and recognizing that many problems are indeed “wicked problems” can we develop more fruitful conversations, leading to better policies and roadmaps from discovery all the way to technologies in farmer hands. 18 References Ainembabazi, John Herbert, et al. "Ex-ante economic impact assessment of genetically modified banana resistant to Xanthomonas wilt in the Great Lakes Region of Africa." PloS one 10.9 (2015): e0138998. Anderson, Kym, Ernesto Valenzuela, and Lee Ann Jackson. "Recent and prospective adoption of genetically modified cotton: a global computable general equilibrium analysis of economic impacts." Economic Development and Cultural Change 56.2 (2008): 265-296. Anderson, Kym. "Economic impacts of policies affecting crop biotechnology and trade." New Biotechnology 27.5 (2010): 558-564. Andreu, Monica Lopez, et al. "Biotechnology and economic development: The economic benefits of maize streak virus tolerant maize in Kenya." Southern Agricultural Economics Association Annual Meeting, Orlando, Florida February. 2006. Areal, F.J., Riesgo, L. and Rodríguez-Cerezo, E., 2013. Economic and agronomic impact of commercialized GE crops: a meta-analysis. The Journal of Agricultural Science, 151(01), pp.7-33. Bennett, R. , Ismael, Y. and Morse, S. “Explaining contradictory evidence regarding impacts of genetically modified crops in developing countries. Varietal performance of transgenic cotton in India”, Journal of Agricultural Science 1 143 (2005): 35-41 Bennett, Richard, et al. "Reductions in insecticide use from adoption of Bt cotton in South Africa: impacts on economic performance and toxic load to the environment." The Journal of Agricultural Science 142.06 (2004): 665-674. Bennett, Richard, Stephen Morse, and Yousouf Ismael. "The economic impact of genetically modified cotton on South African smallholders: yield, profit and health effects." The Journal of Development Studies 42.4 (2006): 662-677. Bouët, Antoine, and Guillaume P. Gruère. "Refining opportunity cost estimates of not adopting GE cotton: An application in seven sub-Saharan African countries." Applied Economic Perspectives and Policy (2011): 260-279. Chambers, J.A., Zambrano, P., Falck-Zepeda, J.B., Gruère, G.P., Sengupta, D. and Hokanson, K., 2014. GE agricultural technologies for Africa: A state of affairs. Intl Food Policy Res Inst. Coulibaly, Ousmane, et al. "Baseline study for impact assessment of high-quality insect resistant cowpea in West Africa." African Agricultural Foundation (2008): 1-51. Crost, Benjamin, and Bhavani Shankar. "Bt-cotton and production risk: panel data estimates." International Journal of Biotechnology 10.2-3 (2008): 122-131. Demont, Matty, et al. "Ex ante impact assessment of herbicide resistant rice in the Sahel." Crop Protection 28.9 (2009): 728-736. Edmeades, Svetlana, and Melinda Smale. "A trait-based model of the potential demand for a genetically engineered food crop in a developing economy." Agricultural Economics 35.3 (2006): 351-361. Elbehri, Aziz, and Steve Macdonald. "Estimating the impact of transgenic Bt cotton on West and Central Africa: A general equilibrium approach." World Development 32, no. 12 (2004): 2049-2064. Finger, R., El Benni, N., Kaphengst, T., Evans, C., Herbert, S., Lehmann, B., Morse, S. and Stupak, N., 2011. A meta-analysis on farm-level costs and benefits of GE crops. Sustainability, 3(5), pp.743-762. Falck-Zepeda, J.D. Horna, and M. Smale. "Betting on cotton: Potential payoffs and economic risks of adopting transgenic cotton in West Africa." African Journal of Agricultural and Resource Economics 2.2 (2008): 188-207. 19 Falck-Zepeda, Jose, Daniela Horna, and Melinda Smale. The economic impact and the distribution of benefits and risk from the adoption of insect resistant (Bt) cotton in West Africa. Intl Food Policy Res Inst, 2007. Falck-Zepeda, José, et al. "Policy and institutional factors and the distribution of economic benefits and risk from the adoption of insect resistant (Bt) cotton in West Africa." Asian Biotechnology Development Review 11 (2008): 1-32. Fiedler, John L., Enoch M. Kikulwe, and Ekin Birol. An ex ante analysis of the impact and cost- effectiveness of biofortified high-provitamin A and high-iron banana in Uganda. Vol. 1277. Intl Food Policy Res Inst, 2013. Fischer, K., Ekener-Petersen, E., Rydhmer, L. and Björnberg, K.E., 2015. Social impacts of GE crops in agriculture: A systematic literature review. Sustainability, 7(7), pp.8598-8620. Fox, Michael, Jean Luc Hofs, Marnus House, Johann Kristen, “Contextual appraisal of GM cottonin South Africa” Life Science International Journal 1(4) (2007): 468-482 Gbègbèlègbè, S. D., et al. "The estimated ex ante economic impact of Bt cowpea in Niger, Benin and Northern Nigeria." Agricultural Economics 46.4 (2015): 563-577. Gouse, Marnus, Carl Pray, and David Schimmelpfennig. "The distribution of benefits from Bt cotton adoption in South Africa." (2005). Gouse, Marnus, et al. "A GE subsistence crop in Africa: the case of Bt white maize in South Africa." International Journal of Biotechnology 7.1-3 (2005): 84-94. Gouse, Marnus, et al. "Assessing the performance of GE maize amongst smallholders in KwaZulu-Natal, South Africa." (2009). Gouse, Marnus, et al. "Bt cotton in KwaZulu Natal: Technological triumph but institutional failure." AgBiotechNet 7.134 (2005): 1-7 Gouse, Marnus, et al. "Genetically Modified Maize: Less Drudgery for Her, More Maize for Him? Evidence from Smallholder Maize Farmers in South Africa." World Development 83 (2016): 27- 38. Gouse, Marnus, et al. "Three seasons of subsistence insect-resistant maize in South Africa: have smallholders benefited?" (2006). Gouse, Marnus, Johann F. Kirsten, and Lindie Jenkins. "Bt cotton in South Africa: Adoption and the impact on farm incomes amongst small-scale and large scale farmers." Agrekon 42.1 (2003): 15- 28. Gouse, Marnus. "GE maize as subsistence crop: The South African smallholder experience." (2012). Groote, H. D., et al. "Assessing the potential economic impact of Bacillus thuringiensis (Bt) maize in Kenya." African Journal of Biotechnology 10.23 (2011): 4741-4751. Gruère, Guillaume, and Debdatta Sengupta. "GM-free private standards and their effects on biosafety decision-making in developing countries." Food Policy 34.5 (2009): 399-406. Hofs, Jean-Luc, Bernard Hau, and Diana Marais. "Boll distribution patterns in Bt and non-Bt cotton cultivars: I. Study on commercial irrigated farming systems in South Africa." Field Crops Research 98.2 (2006): 203-209. Hofs, Jean-Luc, Michel Fok, and Maurice Vaissayre. "Impact of Bt cotton adoption on pesticide use by smallholders: A 2-year survey in Makhatini Flats (South Africa)." Crop Protection 25.9 (2006): 984-988. Horna, Daniela, et al. Insecticide use on vegetables in Ghana: Would GE seed benefit farmers? Intl Food Policy Res Inst, 2008. 20 Horna, Daniela, Patricia Zambrano, and José Falck-Zepeda. "Socioeconomic considerations in biosafety decisionmaking." Methods and implementation. International Food Policy Research Institute, Washington DC (2013): 212. ISAAA. 2017. Global Status of Commercialized Biotech/GE Crops: 2017. Biotech Crop Adoption Surges as Economic Benefits Accumulate in 22 Years. ISAAA Brief No. 53. ISAAA: Ithaca, NY. Available at https://www.isaaa.org/resources/publications/briefs/53/download/isaaa-brief-53-2017.pdf Ismael, Yousouf, et al. 2002"Efficiency effects of Bt cotton adoption by smallholders in Makhathini Flats, KwaZulu-Natal, South Africa." Economic and social issues in agricultural biotechnology: 325-349. Ismael, Yousouf, Richard Bennett, and Stephen Morse. 2002"Farm-level economic impact of biotechnology: smallholder Bt cotton farmers in South Africa." Outlook on Agriculture 31: 107- 111. Ismael, Yousouf, Richard M. Bennett, and Stephen Morse. 2002"Benefits from Bt cotton use by smallholder farmers in South Africa." James, C. 1997. Global Status of Transgenic Crops in 1997. ISAAA Briefs No. 5. ISAAA: Ithaca, NY Kagai, Kenneth Kinuthia. 2011: "Assessment of Public Perception, Awareness and Knowledge on Genetically Engineered Food Crops and their Products in Trans-Nzoia County, Kenya." Journal of Developments in Sustainable Agriculture 6.2 164-180. Kalaitzandonakes, Nicholas, John Kruse, and Marnus Gouse. "The Potential Economic Impacts of Herbicide-tolerant Maize in Developing Countries: A Case Study." (2015). Keetch, D. P., et al. "Bt maize for small scale farmers: a case study." African Journal of Biotechnology 4.13 (2005). Kikulwe, Enoch M., et al. "A latent class approach to investigating demand for genetically modified banana in Uganda." Agricultural Economics 42.5 (2011): 547-560. Kikulwe, Enoch M., Justus Wesseler, and Jose Falck-Zepeda. "Attitudes, perceptions, and trust. Insights from a consumer survey regarding genetically modified banana in Uganda." Appetite 57.2 (2011): 401-413. Kikulwe, Enoch Mutebi, José Falck-Zepeda, and Justus Wesseler. "‘If labels for GE food were present, would consumers trust them?’ Insights from a consumer survey in Uganda." Environment and Development Economics 19.06 (2014): 786-805. Kirsten, Johann, and Marnus Gouse. "The adoption and impact of agricultural biotechnology innovations in South Africa." Fuel 2 (2002): 318. Kirsten, Johann, and Marnus Gouse. "The adoption and impact of agricultural biotechnology in South Africa." The Economic and Environmental Impacts of Agbiotech. Springer US, 2003. 243-259. Klümper, W. and Qaim, M., 2014. A meta-analysis of the impacts of genetically modified crops. PloS one, 9(11), p.e111629. Kostandini, Genti, Bradford Mills, and Elton Mykerezi. "Ex Ante Evaluation of Drought-Tolerant Varieties in Eastern and Central Africa." Journal of Agricultural Economics 62.1 (2011): 172-206. Kostandini, Genti, et al. "Ex ante analysis of the benefits of transgenic drought tolerance research on cereal crops in low-income countries." Agricultural Economics 40.4 (2009): 477-492. Kostandini, Genti, Roberto La Rovere, and Zhe Guo. "Ex ante welfare analysis of technological change: The case of nitrogen efficient maize for African soils." Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie 64.1 (2016): 147-168. Khush, G.S., 2012. “Genetically modified crops: The fastest adopted crop technology in the history of modern agriculture.” Agriculture & Food Security, 1(1) https://www.isaaa.org/resources/publications/briefs/53/download/isaaa-brief-53-2017.pdf 21 Kushwaha, Saket, et al. "Consumer Acceptance of Genetically Modified (GM)—Cowpeas in Sub-Sahara Africa." Journal of International Food & Agribusiness Marketing 20.4 (2008): 7-23. Laibuni, Nancy M., et al. "Cost benefit analysis of transgenic cotton containing cry1ac and cry2ab2 genes and HART 89M: Evidence from confined field trials in Kenya." African Journal of Horticultural Science 6 (2012). Langyintuo, Augustine S., and Jess Lowenberg-DeBoer. "Potential regional trade implications of adopting Bt cowpea in West and Central Africa." (2006). Morse, S., Bennett, R., & Ismael, Y. (2005). Bt-cotton boosts the gross margin of small-scale cotton producers in South Africa. International Journal of Biotechnology, 7(1-3), 72-83. Morse, Stephen, and Richard Bennett. "Impact of Bt cotton on farmer livelihoods in South Africa." International Journal of Biotechnology 10.2-3 (2008): 224-239. Morse, Stephen, Richard Bennett, and Yousouf Ismael. "Environmental impact of genetically modified cotton in South Africa." Agriculture, Ecosystems & Environment 117.4 (2006): 277-289. Mulwa, Richard, et al. "Estimating the potential economic benefits of adopting Bt cotton in selected COMESA countries." (2013). NAS - National Academies of Sciences, Engineering, and Medicine. Genetically Engineered Crops: Experiences and Prospects (National Academies Press, Washington, DC, 2016). Paarlberg, R.L., 2001. The politics of precaution: Genetically modified crops in developing countries. Intl Food Policy Res Inst. Paarlberg, Robert. 2006. "Are genetically modified (GM) crops a commercial risk for Africa?" International Journal of Technology and Globalisation 2.1-2: 81-92. Paarlberg, R., 2010. GMO foods and crops: Africa's choice. New biotechnology, 27(5), pp.609-613. Piesse, Jenifer, and Colin Thirtle. "Genetically modified crops, factor endowments, biased technological change, wages and poverty reduction." International Journal of Biotechnology 10.2-3 (2008): 184-206. Pitoro, Raul, et al. "Can Bt Technology Reduce Poverty Among African Cotton Growers? An Ex Ante Analysis of the Private and Social Profitability of Bt Cotton Seed in Mozambique." 2009 Conference, August 16-22, 2009, Beijing, China. No. 51633. International Association of Agricultural Economists, 2009. Qaim, Matin. "A prospective evaluation of biotechnology in semi-subsistence agriculture." Agricultural Economics 25.2-3 (2001): 165-175. Qaim, Matin. "Potential benefits of agricultural biotechnology: An example from the Mexican potato sector." Review of Agricultural Economics (1999): 390-408. Racovita, M., Obonyo, D.N., Craig, W. and Ripandelli, D., 2014. What are the non-food impacts of GE crop cultivation on farmers’ health? Environmental evidence, 3(1), p.1. Raney, Terri. "Economic impact of transgenic crops in developing countries." Current Opinion in Biotechnology 17.2 (2006): 174-178. Regier, Gregory K., Timothy J. Dalton, and Jeffery R. Williams. "Impact of genetically modified maize on smallholder risk in South Africa." (2013). Rittel, H.W. and Webber, M.M., 1973. “Dilemmas in a general theory of planning.” Policy Sciences, 4(2), pp.155-169. Shankar, Bhavani, and Colin Thirtle. "Pesticide productivity and transgenic cotton technology: The South African smallholder case." Journal of agricultural Economics 56.1 (2005): 97-116. Shankar, Bhavani, Richard Bennett, and Stephen Morse. "Production risk, pesticide use and GE crop technology in South Africa." Applied Economics 40.19 (2008): 2489-2500. 22 Smale, M., Zambrano, P., Gruère, G., Falck-Zepeda, J., Matuschke, I., Horna, D., Nagarajan, L., Yerramareddy, I. and Jones, H. 2009. Measuring the economic impacts of transgenic crops in developing agriculture during the first decade: Approaches, findings, and future directions (Vol. 10). Intl Food Policy Res Inst. Takeshima, Hiroyuki. "Distribution of welfare gains from GE cassava in Uganda across different population groups and market margins." African Journal of Agricultural and Resource Economics 6.1 (2011). Thirtle, Colin, et al. "Can GM-technologies help the poor? The impact of Bt cotton in Makhathini Flats, KwaZulu-Natal." World development 31.4 (2003): 717-732. Vitale, J.D., Vognan, G., Ouattarra, M., & Traore, O. (2010). The commercial application of GMO crops in Africa: Burkina Faso’s decade of experience with Bt cotton. AgBioForum, 13(4), 320-332. Vitale, Jeffrey D., et al. "The commercial application of GMO crops in Africa: Burkina Faso's decade of experience with Bt cotton." (2011). Vitale, Jeffrey, et al. "Second-generation Bt cotton field trials in Burkina Faso: Analyzing the potential benefits to West African farmers." Crop Science 48.5 (2008): 1958-1966. Vitale, Jeffrey, et al. "The economic impacts of introducing Bt technology in smallholder cotton production systems of West Africa: A case study from Mali." (2007). Vitale, Jeffrey, Marc Ouattarra, and Gaspard Vognan. "Enhancing sustainability of cotton production systems in West Africa: A summary of empirical evidence from Burkina Faso." Sustainability 3.8 (2011): 1136-1169. 23 Annex Table A 1 bEcon 4 Africa: Count of publications by country, crop, and trait, 1998-2016 Country # Crop # Trait (#) Ex ante (#) Ex post (#) South Africa 30 Cotton 21 Bt (21), HT (1) 1 20 Maize 11 Bt (9), BR/HT (1), HT (4), AP (1) 2 9 Soybean 1 Bt (1), HT (1) - 1 Kenya 14 Cotton 2 Bt (2) 2 - Sweet Potato 2 VR (2), Bt (2) 2 - Maize 6 Bt (1), HT (1), Drought resistant (2), AP (1), VR (1) 6 - Banana 1 BR (1) 1 - Sorghum 1 Drought resistant (1) 1 - Wheat 1 Drought resistant (1) 1 - Rice 1 Drought resistant (1) 1 - Millet 1 Drought resistant (1) 1 - Potato 2 VR (1), Bt (1) 2 - Uganda 12 Banana 6 Bt (3), BR (1), NE (1) 6 - Cassava 1 - 1 - Cotton 3 Bt (3) 3 - Maize 1 Drought resistant (1) 1 - Sorghum 1 Drought resistant (1) 1 - Millet 1 Drought resistant (1) 1 - Burkina Faso 10 Cotton 8 Bt (7) 5 3 Cowpea 2 Bt (2) 2 - Nigeria 7 Cowpea 4 Bt (4) 4 - Rice 2 Bt (2) 2 - Cotton 1 Bt (1) 1 - Ghana 3 Cotton 1 Bt (1) 1 - Tomato 1 Bt (1) 1 - Cabbage 1 Bt (1) 1 - Eggplant 1 Bt (1) 1 - Cowpea 1 Bt (1) 1 - Tanzania 3 Banana 1 BR (1) 1 - Cotton 2 Bt (2) 2 - Other 17 Cotton 8 Bt (8) 8 - Maize 3 Bt (1), Drought Resistant (2) 3 - Wheat 1 Drought resistant (1) 1 - Millet 1 Drought resistant (1) 1 - Sorghum 1 Drought resistant (1) 1 - Banana 1 BR (1) 1 - Cowpea 3 Bt (3) 3 - Rice 2 HT (1), Drought Resistant (1) 2 - Source: Authors’ elaboration 24 Table A 2 bEcon 4 Africa: Papers on the impacts of GE crops on farms, details and DOI links, 2001-2016 Authors Year published Crop Trait Country DOI/ Link Qaim, M 2001 Sweet Potato VR, Bt Kenya http://dx.doi.org/10.1111/j.1574- 0862.2001.tb00197.x Ismael, Yousouf; Bennett, Richard; Morse, Stephen 2002 Cotton Bt South Africa http://dx.doi.org/10.5367/000000002101293949 Kirsten, J; Gouse, M 2002 Maize, Cotton Bt South Africa http://ageconsearch.umn.edu/record/18054/files/ wp020025.pdf Ismael, Yousouf; Richard Bennett; Stephen Morse. 2002 Cotton Bt South Africa http://dx.doi.org/10.5367/000000002101293949 Ismael, Y.; L. Beyers; C. Thirtle; J. Piesse; 2002 Cotton Bt South Africa http://www.cabi.org/cabebooks/ebook/20023100 393 Kirsten, J; Gouse, M 2003 Maize, Cotton Bt South Africa http://link.springer.com/chapter/10.1007/978-1- 4615-0177-0_13 Thirtle, C; Beyers, L 2003 Cotton Bt South Africa http://dx.doi.org/10.1016/S0305-750X(03)00004-4 M Gouse; J F Kirsten; L Jenkins 2003 Cotton Bt South Africa http://dx.doi.org/10.1080/03031853.2003.952360 7 Gouse, Marnus; Pray, Carl E; Schimmelpfennig, David 2004 Cotton Bt South Africa http://www.agbioforum.org/v7n4/v7n4a04- schimmelpfennig.pdf Bennett, R.; Ismael, Y.; Morse, S.; Shankar, B 2004 Cotton Bt South Africa http://dx.doi.org/10.1017/S0021859605004892 Shankar, B; Thirtle, C 2005 Cotton Bt South Africa http://dx.doi.org/10.1111/j.1477- 9552.2005.tb00124.x Keetch, D. P.; A. Ngqaka; R. Akanbi; P. Mahlanga 2005 Maize Bt South Africa http://biotechbenefits.croplife.org/paper/bt- maize-for-small-scale-farmers-a-case-study/ http://dx.doi.org/10.1111/j.1574-0862.2001.tb00197.x http://dx.doi.org/10.1111/j.1574-0862.2001.tb00197.x http://dx.doi.org/10.5367/000000002101293949 http://ageconsearch.umn.edu/record/18054/files/wp020025.pdf http://ageconsearch.umn.edu/record/18054/files/wp020025.pdf http://dx.doi.org/10.5367/000000002101293949 http://www.cabi.org/cabebooks/ebook/20023100393 http://www.cabi.org/cabebooks/ebook/20023100393 http://link.springer.com/chapter/10.1007/978-1-4615-0177-0_13 http://link.springer.com/chapter/10.1007/978-1-4615-0177-0_13 http://dx.doi.org/10.1016/S0305-750X(03)00004-4 http://dx.doi.org/10.1080/03031853.2003.9523607 http://dx.doi.org/10.1080/03031853.2003.9523607 http://www.agbioforum.org/v7n4/v7n4a04-schimmelpfennig.pdf http://www.agbioforum.org/v7n4/v7n4a04-schimmelpfennig.pdf http://dx.doi.org/10.1017/S0021859605004892 http://dx.doi.org/10.1111/j.1477-9552.2005.tb00124.x http://dx.doi.org/10.1111/j.1477-9552.2005.tb00124.x http://biotechbenefits.croplife.org/paper/bt-maize-for-small-scale-farmers-a-case-study/ http://biotechbenefits.croplife.org/paper/bt-maize-for-small-scale-farmers-a-case-study/ 25 Authors Year published Crop Trait Country DOI/ Link Gouse, M.; Kirsten, J.; Shankar, B.; Thirtle, C 2005 Cotton Bt South Africa http://www.grain.org/system/old/research_files/ Gouse_etal.pdf Gouse, M.; Pray, C. E.; Kirsten, J.; Schimmelpfennig, D 2005 Maize Bt South Africa http://dx.doi.org/10.1504/IJBT.2005.006447 Morse, S.; Bennett, R.; Ismael, Y.. 2005 Cotton Bt South Africa http://dx.doi.org/10.1504/IJBT.2005.006446 Bennett R; Morse S; Ismael Y. 2006 Cotton Bt South Africa http://dx.doi.org/10.1016/j.appet.2011.06.001 Hofs, Jean-Luc; Michel Fok; Maurice Vaissayre 2006 Cotton Bt South Africa http://dx.doi.org/10.1016/j.cropro.2006.01.006 Gouse, M.; Pray, C. E.; Schimmelpfennig, D.; Kirsten, J. 2006 Maize Bt South Africa http://www.agbioforum.org/v9n1/v9n1a02- gouse.pdf Hofs, J. L.; B. Hau; D. Marais 2006 Cotton Bt South Africa http://dx.doi.org/10.1016/j.fcr.2006.01.006 Morse, S.; R. Bennett; Y. Ismael 2006 Cotton Bt South Africa http://dx.doi.org/10.1016/j.agee.2006.04.009 Fok, M.; M. Gouse; J. L. Hofs; J. Kirsten. 2007 Cotton Bt South Africa https://hal.archives-ouvertes.fr/halshs- 00176546/document Shankar, B; R. Bennett; S. Morse 2008 Cotton Bt South Africa http://dx.doi.org/10.1080/00036840600970161 Horna, D.; M. Smale; R. Al- Hassan; J. Falck-Zepeda; S.E. Timpo 2008 Tomato, Cabbage, Eggplant Bt Ghana http://ageconsearch.umn.edu/bitstream/6506/2/ 462466.pdf http://www.grain.org/system/old/research_files/Gouse_etal.pdf http://www.grain.org/system/old/research_files/Gouse_etal.pdf http://dx.doi.org/10.1504/IJBT.2005.006447 http://dx.doi.org/10.1504/IJBT.2005.006447 http://dx.doi.org/10.1504/IJBT.2005.006446 http://dx.doi.org/10.1080/00220380600682215 http://dx.doi.org/10.1016/j.cropro.2006.01.006 http://www.agbioforum.org/v9n1/v9n1a02-gouse.pdf http://www.agbioforum.org/v9n1/v9n1a02-gouse.pdf http://dx.doi.org/10.1016/j.fcr.2006.01.006 http://dx.doi.org/10.1016/j.agee.2006.04.009 https://hal.archives-ouvertes.fr/halshs-00176546/document https://hal.archives-ouvertes.fr/halshs-00176546/document http://dx.doi.org/10.1080/00036840600970161 http://ageconsearch.umn.edu/bitstream/6506/2/462466.pdf http://ageconsearch.umn.edu/bitstream/6506/2/462466.pdf 26 Authors Year published Crop Trait Country DOI/ Link S. Morse; R. Bennett 2008 Cotton Bt South Africa http://dx.doi.org/10.1504/IJBT.2008.018355 V., Jeffrey; H. Glick; J. Greenplate; O. Traore 2008 Cotton Bt Burkina Faso http://dx.doi.org/10.2135/cropsci2008.01.0024 Demont, M.; J.E Rodenburg; M. Diagne; S. Diallo 2009 Rice HT Senegal http://dx.doi.org/10.1016/j.cropro.2009.05.012 Gouse, M.; Piesse, J.; Thirtle, C.; Poulton, C. 2009 Maize Bt, HT South Africa http://www.agbioforum.org/v12n1/v12n1a08- gouse.pdf Pitoro, R., Walker, T., Tschirley, D., Swinton, S., Boughton, D., & De Marrule, H. 2009 Cotton Bt Mozambique http://fsg.afre.msu.edu/mozambique/Can_Bt_Tec hnology_Reduce_Poverty_Among_African_Cotton _Growers_RP09_final.pdf Vitale, J. D.; G. Vognan; M. Ouattarra; O. Traore. 2010 Cotton Bt Burkina Faso http://www.agbioforum.org/v13n4/v13n4a05- vitale.pdf Vitale, J.; M. Ouattarra; G. Vognan. 2011 Cotton Bt Burkina Faso http://dx.doi.org/10.3390/su3081136 De Groote H; Overholt WA; Ouma JO; Wanyama J 2011 Maize Bt Kenya http://dx.doi.org/10.1080/03031853.2003.952360 7 Kostandini, G.; B. Mills; E. Mykerezi. 2011 Maize, Sorghum, Millet Drought resistant Kenya, Uganda, Ethiopia http://dx.doi.org/10.1111/j.1477- 9552.2010.00281.x Takeshima, H. 2011 Cassava Not available Uganda http://ageconsearch.umn.edu/bitstream/156959/ 2/Takeshima_06_01.pdf Kinuthia Kagai, Kenneth. 2011 - - Kenya http://doi.org/10.11178/jdsa.6.164 http://dx.doi.org/10.1504/IJBT.2008.018355 http://dx.doi.org/10.2135/cropsci2008.01.0024 http://dx.doi.org/10.1016/j.cropro.2009.05.012 http://www.agbioforum.org/v12n1/v12n1a08-gouse.pdf http://www.agbioforum.org/v12n1/v12n1a08-gouse.pdf http://fsg.afre.msu.edu/mozambique/Can_Bt_Technology_Reduce_Poverty_Among_African_Cotton_Growers_RP09_final.pdf http://fsg.afre.msu.edu/mozambique/Can_Bt_Technology_Reduce_Poverty_Among_African_Cotton_Growers_RP09_final.pdf http://fsg.afre.msu.edu/mozambique/Can_Bt_Technology_Reduce_Poverty_Among_African_Cotton_Growers_RP09_final.pdf http://www.agbioforum.org/v13n4/v13n4a05-vitale.pdf http://www.agbioforum.org/v13n4/v13n4a05-vitale.pdf http://dx.doi.org/10.3390/su3081136 http://www.ajol.info/index.php/ajb/article/view/94148 http://www.ajol.info/index.php/ajb/article/view/94148 http://dx.doi.org/10.1111/j.1477-9552.2010.00281.x http://dx.doi.org/10.1111/j.1477-9552.2010.00281.x http://ageconsearch.umn.edu/bitstream/156959/2/Takeshima_06_01.pdf http://ageconsearch.umn.edu/bitstream/156959/2/Takeshima_06_01.pdf http://doi.org/10.11178/jdsa.6.164 27 Authors Year published Crop Trait Country DOI/ Link Gouse, M. 2012 Maize Bt, HT South Africa http://www.agbioforum.org/v15n2/v15n2a05- gouse.pdf Regier, Gregory K.; Timothy J. Dalton; Jeffery R. Williams 2012 Maize BR/HT South Africa http://www.agbioforum.org/v15n3/v15n3a08- regier.pdf Laibuni, Nancy M.; L. C. Miriti; C. N. Waturu; W. Wessels; S. M. Njinju. 2012 Cotton Bt Kenya http://www.hakenya.net/ajhs/index.php/ajhs/arti cle/view/102/90 Fiedler, John L.; Enoch M. Kikulwe; Ekin Birol 2013 Banana NE Uganda http://ebrary.ifpri.org/cdm/ref/collection/p15738 coll2/id/127755 Mulwa, R., D. Wafula; M.t Karembu; M. Waithaka. 2013 Cotton Bt Egypt, Ethiopia, Kenya, Tanzania, Uganda, Zambia http://www.agbioforum.org/v16n1/v16n1a02- mulwa.pdf Horna, D.; M. Smale; R. Al- Hassan; J. Falck-Zepeda 2013 Cotton Bt Uganda http://dx.doi.org/10.2499/9780896292079 Ainembabazi, J. H.; L. Tripathi; J. Rusike; T. Abdoulaye; V. Manyong 2015 Banana BR Burundi, DRC, Kenya, Rwanda, Tanzania, Uganda http://dx.doi.org/10.1371/journal.pone.0138998 Kostandini, Genti; Roberto La Rovere; Zhe Guo. 2016 Maize AP Kenya, South Africa http://dx.doi.org/10.1111/cjag.12067 Gouse, Ma.; D. Sengupta; P. Zambrano; J. Falck Zepeda 2016 Maize Bt, HT South Africa http://dx.doi.org/10.1016/j.worlddev.2016.03.008 Source: Authors’ elaboration http://www.agbioforum.org/v15n2/v15n2a05-gouse.pdf http://www.agbioforum.org/v15n2/v15n2a05-gouse.pdf http://www.agbioforum.org/v15n3/v15n3a08-regier.pdf http://www.agbioforum.org/v15n3/v15n3a08-regier.pdf http://www.hakenya.net/ajhs/index.php/ajhs/article/view/102/90 http://www.hakenya.net/ajhs/index.php/ajhs/article/view/102/90 http://ebrary.ifpri.org/cdm/ref/collection/p15738coll2/id/127755 http://ebrary.ifpri.org/cdm/ref/collection/p15738coll2/id/127755 http://www.agbioforum.org/v16n1/v16n1a02-mulwa.pdf http://www.agbioforum.org/v16n1/v16n1a02-mulwa.pdf http://dx.doi.org/10.2499/9780896292079 http://dx.doi.org/10.1371/journal.pone.0138998 http://dx.doi.org/10.1111/cjag.12067 http://dx.doi.org/10.1016/j.worlddev.2016.03.008 28 Table A 3 bEcon 4 Africa: Papers on the impacts of GE crops on industry/sector, details and DOI links, 2001-2016 Authors Year published Crop Trait Country DOI/ Link Qaim, M 2001 Sweet Potato VR, Bt Kenya http://dx.doi.org/10.1111/j.1574-0862.2001.tb00197.x Elbehri, A; Macdonald, S 2004 Cotton Bt Benin, Burkina Faso, Chad, Mali, Togo, Cote d'Ivoire, Cameroon, CAR http://dx.doi.org/10.1016/j.worlddev.2004.07.005 Falck-Zepeda, J; D Horna; M Smale. 2008 Cotton Bt Benin, Burkina Faso, Mali, Senegal, Togo http://ageconsearch.umn.edu/bitstream/56962/2/020 2%20Falck-ZepedaFINAL.pdf Falck-Zepeda, J; Horna, D; Zambrano, P; Smale, M 2008 Cotton Bt Benin, Burkina Faso, Mali, Senegal, Togo https://scholars.opb.msu.edu/en/publications/policy- and-institutional-factors-and-the-distribution-of- economic-4 Falck-Zepeda, J; D Horna; M Smale. 2007 Cotton Bt Benin, Burkina, Cameroon, CAR, Chad, Congo, Côte d'Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Mali, Mauritania, Nigeria, Senegal, Togo http://ageconsearch.umn.edu/bitstream/42395/2/IFP RIDP00718.pdf Vitale, J. D.; G. Vognan; M. Ouattarra; O. Traore. 2010 Cotton Bt Burkina Faso http://www.agbioforum.org/v13n4/v13n4a05- vitale.pdf Ainembabazi, JH; L Tripathi; J Rusike; T Abdoulaye; V Manyong 2015 Banana BR Burundi, DRC, Kenya, Rwanda, Tanzania, Uganda http://dx.doi.org/10.1371/journal.pone.0138998 Mulwa, R; D Wafula; M Karembu; M Waithaka. 2013 Cotton NA Egypt, Ethiopia, Kenya, Tanzania, Uganda, Zambia http://www.agbioforum.org/v16n1/v16n1a02- mulwa.pdf http://dx.doi.org/10.1111/j.1574-0862.2001.tb00197.x http://dx.doi.org/10.1016/j.worlddev.2004.07.005 http://ageconsearch.umn.edu/bitstream/56962/2/0202%20Falck-ZepedaFINAL.pdf http://ageconsearch.umn.edu/bitstream/56962/2/0202%20Falck-ZepedaFINAL.pdf https://scholars.opb.msu.edu/en/publications/policy-and-institutional-factors-and-the-distribution-of-economic-4 https://scholars.opb.msu.edu/en/publications/policy-and-institutional-factors-and-the-distribution-of-economic-4 https://scholars.opb.msu.edu/en/publications/policy-and-institutional-factors-and-the-distribution-of-economic-4 http://ageconsearch.umn.edu/bitstream/42395/2/IFPRIDP00718.pdf http://ageconsearch.umn.edu/bitstream/42395/2/IFPRIDP00718.pdf http://www.agbioforum.org/v13n4/v13n4a05-vitale.pdf http://www.agbioforum.org/v13n4/v13n4a05-vitale.pdf http://dx.doi.org/10.1371/journal.pone.0138998 http://www.agbioforum.org/v16n1/v16n1a02-mulwa.pdf http://www.agbioforum.org/v16n1/v16n1a02-mulwa.pdf 29 Authors Year published Crop Trait Country DOI/ Link Andreu, M Lopez; H Hanaway Peterson; O Grunewald; D Norman. 2006 Maize VR Kenya http://ageconsearch.umn.edu/bitstream/35271/1/sp0 6an01.pdf Kalaitzandonakes, N; J Kruse; M Gouse. 2015 Maize HT Kenya http://www.agbioforum.org/v18n2/v18n2a08- kalaitzandonakes.pdf Vitale J; Boyer T Uaiene R; Sanders JH 2007 Cotton, Maize Bt Mali http://www.agbioforum.org/v10n2/v10n2a02- vitale.pdf Kikulwe, E; J Wesseler; J Falck- Zepeda. 2008 Banana Bt Uganda http://dx.doi.org/10.2499/9780896292079 Kikulwe, E M.; E Birol; J Wesseler; J Falck-Zepeda 2011 Banana Bt Uganda http://dx.doi.org/10.1111/j.1574-0862.2010.00529.x Horna, D; M Smale; R Al- Hassan; J Falck- Zepeda 2013 Cotton Bt Uganda http://dx.doi.org/10.2499/9780896292079 Source: Authors’ elaboration http://ageconsearch.umn.edu/bitstream/35271/1/sp06an01.pdf http://ageconsearch.umn.edu/bitstream/35271/1/sp06an01.pdf http://www.agbioforum.org/v18n2/v18n2a08-kalaitzandonakes.pdf http://www.agbioforum.org/v18n2/v18n2a08-kalaitzandonakes.pdf http://www.agbioforum.org/v10n2/v10n2a02-vitale.pdf http://www.agbioforum.org/v10n2/v10n2a02-vitale.pdf http://ageconsearch.umn.edu/bitstream/42323/2/ifpridp00767.pdf http://dx.doi.org/10.1111/j.1574-0862.2010.00529.x http://dx.doi.org/10.2499/9780896292079 30 Table A 4 bEcon 4 Africa: Papers on the impacts of GE crops on consumers, details and DOI links, 2001-2016 Authors Year published/accessed Crops Trait Country DOI/ Link Edmeades, S; M Smale 2006 Banana Not available Uganda http://dx.doi.org/10.1111/j.1574-0862.2006.00167.x Coulibaly, O; C Aitchedji; S Gbegbelegbe; H Mignouna; J Lowenberg- DeBoer. 2008 Cowpea Bt Benin, Burkina Faso, Mali, Niger, Nigeria http://aatf-africa.org/userfiles/Cowpea_Baseline_Study.pdf Kikulwe, E; J Wesseler; J Falck-Zepeda. 2008 Banana Bt Uganda http://dx.doi.org/10.2499/9780896292079 Kushwaha, S; A. S. Musa; J Lowenberg-DeBoer; J Fulton 2008 Cowpea Bt Nigeria http://dx.doi.org/10.1080/08974430802355325 Kimeju, S.C; De Groote, H 2008 - - Kenya http://dx.doi.org/10.1111/j.1574-0862.2007.00279.x Kikulwe, E; J Wesseler; J Falck-Zepeda. 2011 Banana Bt Uganda http://dx.doi.org/10.1016/j.appet.2011.06.001 Kikulwe, E.; E Birol; J Wesseler; J Falck-Zepeda 2011 Banana Bt Uganda http://dx.doi.org/10.1111/j.1574-0862.2010.00529.x Takeshima, H 2011 Cassava NA Uganda http://ageconsearch.umn.edu/bitstream/156959/2/Takeshima_06_01.pdf Kinuthia Kagai, K 2011 - - Kenya http://doi.org/10.11178/jdsa.6.164 Kikulwe, E. M.; Falck- Zepeda, J.; & Wesseler, J 2014 - - Uganda http://dx.doi.org/10.1017/S1355770X13000636 Gbègbèlègbè, S. D.; J. Lowenberg-DeBoer; R. Adeoti; J. Lusk; O. Coulibaly 2015 Cowpea Bt Benin, Niger, Nigeria http://dx.doi.org/10.1111/agec.12182 Kalaitzandonakes, N; J Kruse; M Gouse. 2015 Maize HT Kenya http://www.agbioforum.org/v18n2/v18n2a08- kalaitzandonakes.pdf Source: Authors’ elaboration http://dx.doi.org/10.1111/j.1574-0862.2006.00167.x http://aatf-africa.org/userfiles/Cowpea_Baseline_Study.pdf http://ageconsearch.umn.edu/bitstream/42323/2/ifpridp00767.pdf http://dx.doi.org/10.1080/08974430802355325 http://dx.doi.org/10.1111/j.1574-0862.2007.00279.x http://dx.doi.org/10.1016/j.appet.2011.06.001 http://dx.doi.org/10.1111/j.1574-0862.2010.00529.x http://ageconsearch.umn.edu/bitstream/156959/2/Takeshima_06_01.pdf http://doi.org/10.11178/jdsa.6.164 http://dx.doi.org/10.1017/S1355770X13000636 http://dx.doi.org/10.1111/agec.12182 http://www.agbioforum.org/v18n2/v18n2a08-kalaitzandonakes.pdf http://www.agbioforum.org/v18n2/v18n2a08-kalaitzandonakes.pdf 31 Table A 5 bEcon 4 Africa: Papers on the impacts of GE crops on gender, cost of regulation, environment, and poverty; details and DOI links, 2001-2016 Theme/ Authors Year published/ accessed Crop Trait Country DOI/ Link Gender Qaim, M 2001 Sweet Potato VR, Bt Kenya http://dx.doi.org/10.1111/j.1574- 0862.2001.tb00197.x Raney, T 2006 Cotton, Maize, Soybean Bt, HT China, India, South Africa, Mexico http://dx.doi.org/10.1016/j.copbio.2 006.02.009 Shankar, B; Thirtle, C 2005 Cotton Bt South Africa http://dx.doi.org/10.1111/j.1477- 9552.2005.tb00124.x Thirtle, C; Beyers, L 2003 Cotton Bt South Africa http://dx.doi.org/10.1016/S0305- 750X(03)00004-4 Kikulwe, Enoch; Justus Wesseler; José Falck-Zepeda. 2008 Banana Bt Uganda http://www.ifpri.org/publication/int roducing-genetically-modified- banana-uganda Kikulwe, Enoch M.; Justus Wesseler; Jose Falck-Zepeda. 2011 Banana Bt Uganda https://doi.org/10.1016/j.appet.201 1.06.001 Gouse, Marnus; Debdatta Sengupta; Patricia Zambrano; José Falck Zepeda 2016 Maize Bt, HT South Africa http://dx.doi.org/10.1016/j.worldde v.2016.03.008 Environment Vitale, Jeffrey; Marc Ouattarra; Gaspard Vognan. 2011 Cotton Bt Burkina Faso http://dx.doi.org/10.3390/su308113 6 Horna, Daniela; Melinda Smale; Ramatu Al-Hassan; José Falck-Zepeda; Samuel E. Timpo. 2008 Tomato, Cabbage, Eggplant Bt Ghana http://ageconsearch.umn.edu/bitstr eam/6506/2/462466.pdf http://dx.doi.org/10.1111/j.1574-0862.2001.tb00197.x http://dx.doi.org/10.1111/j.1574-0862.2001.tb00197.x http://dx.doi.org/10.1016/j.copbio.2006.02.009 http://dx.doi.org/10.1016/j.copbio.2006.02.009 http://dx.doi.org/10.1111/j.1477-9552.2005.tb00124.x http://dx.doi.org/10.1111/j.1477-9552.2005.tb00124.x http://dx.doi.org/10.1016/S0305-750X(03)00004-4 http://dx.doi.org/10.1016/S0305-750X(03)00004-4 http://www.ifpri.org/publication/introducing-genetically-modified-banana-uganda http://www.ifpri.org/publication/introducing-genetically-modified-banana-uganda http://www.ifpri.org/publication/introducing-genetically-modified-banana-uganda https://doi.org/10.1016/j.appet.2011.06.001 https://doi.org/10.1016/j.appet.2011.06.001 http://dx.doi.org/10.1016/j.worlddev.2016.03.008 http://dx.doi.org/10.1016/j.worlddev.2016.03.008 http://dx.doi.org/10.3390/su3081136 http://dx.doi.org/10.3390/su3081136 http://ageconsearch.umn.edu/bitstream/6506/2/462466.pdf http://ageconsearch.umn.edu/bitstream/6506/2/462466.pdf 32 Theme/ Authors Year published/ accessed Crop Trait Country DOI/ Link Bennett, R.; Ismael, Y.; Morse, S.; Shankar, B 2004 Cotton Bt South Africa http://dx.doi.org/10.1017/S0021859 605004892 Cost of Regulation Kirsten, J; Gouse, M 2002 Maize, Cotton Bt South Africa http://citeseerx.ist.psu.edu/viewdoc /download?doi=10.1.1.579.7290&re p=rep1&type=pdf Gruère, Guillaume; Debdatta Sengupta. 2009 - - South Africa, Namibia, Kenya http://dx.doi.org/10.1016/j.foodpol. 2009.04.002 Review of Findings Kirsten, J; Gouse, M 2002 Maize, Cotton Bt South Africa http://citeseerx.ist.psu.edu/viewdoc /download?doi=10.1.1.579.7290&re p=rep1&type=pdf Paarlberg, R 2006 - - - Are genetically modified (GM) crops a commercial risk for Africa? Raney, T 2006 Cotton, Maize, Soybean Bt, HT China, India, South Africa, Mexico http://dx.doi.org/10.1016/j.copbio.2 006.02.009 Gruère, Guillaume; Debdatta Sengupta. 2009 - - South Africa, Namibia, Kenya http://dx.doi.org/10.1016/j.foodpol. 2009.04.002 Poverty Bennett R; Morse S; Ismael Y 2006 Cotton Bt South Africa http://dx.doi.org/10.1080/0022038 0600682215 Piesse, Jenifer; Colin Thirtle. 2008 Cotton, Maize Bt/HT - https://opendocs.ids.ac.uk/opendoc s/bitstream/handle/123456789/129 02/Geneticallymodified_crops.pdf?s equence=1 Stephen Morse; Richard Bennett 2008 Cotton Bt South Africa http://dx.doi.org/10.1504/IJBT.2008 .018355 Source: Authors’ elaboration http://dx.doi.org/10.1017/S0021859605004892 http://dx.doi.org/10.1017/S0021859605004892 http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.579.7290&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.579.7290&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.579.7290&rep=rep1&type=pdf http://dx.doi.org/10.1016/j.foodpol.2009.04.002 http://dx.doi.org/10.1016/j.foodpol.2009.04.002 http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.579.7290&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.579.7290&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.579.7290&rep=rep1&type=pdf http://dx.doi.org/10.1504/IJBT.2008.018354 http://dx.doi.org/10.1504/IJBT.2008.018354 http://dx.doi.org/10.1016/j.copbio.2006.02.009 http://dx.doi.org/10.1016/j.copbio.2006.02.009 http://dx.doi.org/10.1016/j.foodpol.2009.04.002 http://dx.doi.org/10.1016/j.foodpol.2009.04.002 http://dx.doi.org/10.1080/00220380600682215 http://dx.doi.org/10.1080/00220380600682215 https://opendocs.ids.ac.uk/opendocs/bitstream/handle/123456789/12902/Geneticallymodified_crops.pdf?sequence=1 https://opendocs.ids.ac.uk/opendocs/bitstream/handle/123456789/12902/Geneticallymodified_crops.pdf?sequence=1 https://opendocs.ids.ac.uk/opendocs/bitstream/handle/123456789/12902/Geneticallymodified_crops.pdf?sequence=1 https://opendocs.ids.ac.uk/opendocs/bitstream/handle/123456789/12902/Geneticallymodified_crops.pdf?sequence=1 http://dx.doi.org/10.1504/IJBT.2008.018355 http://dx.doi.org/10.1504/IJBT.2008.018355 ALL IFPRI DISCUSSION PAPERS All discussion papers are available here They can be downloaded free of charge INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE www.ifpri.org IFPRI HEADQUARTERS 1201 Eye Street, NW Washington, DC 20005 USA Tel.: +1-202-862-5600 Fax: +1-202-862-5606 Email: ifpri@cgiar.org http://www.ifpri.org/publications?sm_content_subtype_to_terms=4&sort_by=ds_year&f%5B0%5D=sm_content_subtype_to_terms%3D1&f%5B1%5D=sm_content_subtype_to_terms%3A88 http://www.ifpri.org/ mailto:ifpri@cgiar.org ABSTRACT ACKNOWLEDGEMENTS Tables Figures 1. Introduction 2. Distilling the Africa-focused literature 3. bEcon 4 Africa 4. bEcon 4 Africa: Summary of findings 4.1 Impacts on farmers 4.2 Impacts on industry/sector 4.3. Impacts on consumers 4.4 Other emerging themes 5. The political economy of GE crop adoption in Africa 6. Conclusions and way forward References Annex