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Working Paper No. 2011/17 APPLICABILITY OF THE HIGH PERFORMANCE ORGANISATIONS FRAMEWORK IN CENTRAL AFRICA: THE CASE OF RWANDA’S MINALOC André de Waal1 & Miriam Frijns 2 November 2011
© The authors, 2011 1. Associate professor Strategic Management at the Maastricht School of Management, the
Netherlands, and academic director of the research organisation Center for Organisational Performance, the Netherlands. 2. Miriam Frijns is lecturer at the Maastricht School of Management, the Netherlands, and director of
the training advice centre Nihil Admiraria.
The Maastricht School of Management is a leading provider of management education with worldwide presence. Our mission is to enhance the management capacity of professionals and organizations in and for emerging economies and developing countries with the objective to substantially contribute to the development of these societies. www.msm.nl
The views expressed in this publication are those of the author(s). Publication does not imply endorsement by the School or its sponsors, of any of the views expressed. THIS PAPER IS A DRAFT VERSION PREPARED FOR THE 1ST ANNUAL MSM RESEARCH CONFERENCE, 11-12 NOVEMBER 2011 – IT IS INTENDED FOR DISCUSSION PURPOSES ONLY
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ABSTRACT In the past seventeen years Rwanda has been in the process of recovering from the 1994 genocide. The country is currently rebuilding itself, with considerable success. One of the main components of the post-genocide reconstruction of Rwanda is the government’s development plan called Vision2020. This programme aims at overcoming poverty and division by initiating a wide range of improvement programmes for good governance and economic development. In practice, however, the roll-out of Vision2020 seems to be missing a coordinating framework to provide direction to and align the improvement initiatives of the various, often independently operating, governmental agencies. Such a framework could not only provide direction but also help to set priorities and offer an evaluation mechanism to monitor progress on improvement initiatives. This article describes exploratory research into the question whether the High Performance Organisations Framework could function as this coordinating framework. It was assumed that the empirically validated HPO Framework could be used in the Rwandan context as it had earlier been successfully applied in neighbouring country Tanzania. After a first application of the HPO framework at the Rwandan Ministry of Local Governance and Social Affairs (MINALOC), it was concluded that this framework could indeed be used to assess the status of a Rwandan governmental agency and that in addition it also shed light on possible improvement points for MINALOC. By strengthening its internal organisation, the HPO framework will help Rwanda’s MINALOC to focus on what is really important to improve and thereby it can advance the improvement process and the realisation of Vision 2020.
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INTRODUCTION Rwanda is working hard to recover from the genocide which took place in 1994. During this horrible period the structure and fabric of the country was virtually destroyed and the country has had to rebuild itself ever since, which it has done with considerable success (Ansoms, 2005; Isenberg, 2010). An important figure in the recovery process has been president Paul Kagame and his policies of reconciliation, unity and economic development (Waugh, 2004; Silva-Leander, 2008; Chu, 2009). He initiated Vision 2020, a vision for the future of Rwanda which was originally drafted based on the result of a national consultative process that took place in the village of Urugwiro in 1998-1999 (Ministry Of Finance And Economic Planning, 2000). The main objective of Vision 2020 is to transform Rwanda’s economy into a middle-income country with a per capita income of approximately 900 USD per year, from 230 USD in 2000 and currently USD 560 in 2010 (Rwanda Governance Advisory Council, 2010). Vision 2020 aspires for Rwanda to become a modern, strong and united nation, proud of its fundamental values, politically stable and without discrimination amongst its citizens. The vision was translated in a program consisting of six pillars: (1) Reconstruction of the nation and its social capital anchored on good governance, underpinned by a capable state; (2) Transformation of agriculture into a productive, high-value, market-oriented sector, with forward linkages to other sectors; (3) Development of an efficient private sector spearheaded by competitiveness and entrepreneurship; (4) Comprehensive human resources development, encompassing education, health and ICT skills, aimed at public sector, private sector and civil society; (5) Infrastructural development, entailing improved transport links, energy and water supplies and ICT networks; and (6) Promotion of regional economic integration and cooperation. As part of Vision 2020 the governmental agencies of Rwanda had to get a quality impulse in order to be able to support the pillars adequately (Ensign and Bertrand, 2010). It was clearly stated by the Rwanda Governance Advisory Council (2010) that good management in excellent governmental agencies is one of the main preconditions for Vision 2020 to be executed successfully (Gatune and Najam, 2011). As a result, many improvement programmes were started among which the Poverty Reduction Strategy Paper, which ties together the need for development in a sustainable fashion with the alleviation of poverty in the 4
country (Government of Rwanda, 2002); and the development of the Rwanda Governance Scorecard, which evaluates the state of governance in Rwanda with a multitude of performance indicators (Rwanda Governance Advisory Council, 2011). What has been lacking until now in the roll-out of Vision 2020 is a coordinating framework for the improvement initiatives. This framework should not only provide direction to the initiatives but should also set priorities and give the possibility to periodically evaluate progress on the initiatives, in the context of Rwanda. The lack of such a framework is not surprising as there is a shortage of studies on high performance conducted in Africa which could yield the desired coordinating framework (Hoskisson et al., 2000; Horwitz et al., 2002). A recent overview of studies on high performance (Waal, 2010) showed that only one such a study was conducted in an Africa country, Zimbabwe (Khumalo, 2001), and that there were three other HPO studies in which African organizations were part of a larger, multi-national research population. Unfortunately, there were no Rwandan organizations involved in these studies (Khanna and Palepu, 2006; Stuart-Kotze, 2006). This article describes the results of an exploratory study into the possibility of the High Performance Organization (HPO) Framework (Waal, 2008, 2010) providing the desired coordinating framework. This framework has been empirically validated and it was expected that this framework could be used in the Rwandan context as it had already been applied successfully in neighbouring country
Tanzania (Waal and Chachage, 2011). It is
important to evaluate whether the HPO Framework is useful in the Rwandan context as previous research has shown that African organizations with above-average output performance were the ones that had adapted global best practices successfully (Oosthuizen, 2005). Testing whether the HPO Framework can be applied successfully at Rwandan governmental organizations will make it possible for other Rwandan governmental agencies to achieve a sustainable increase in their performance if they also start applying the HPO Framework (Waal, 2010). Consequently, the research question of this study was as follows: Can the HPO Framework be applied in the Rwandan context and with that help improve performance at Rwandan governmental organizations?
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This article is structured as follows. First we describe the HPO Framework and the case organisation at which the framework was applied, the Rwandan Ministry of Local Governance and Social Affairs (MINALOC). After this, we describe the research approach and then discuss the results of the framework application at MINALOC. Part of this discussion is an overview of the attention points for MINALOC which the ministry has to address in order to become an HPO. We end the article with some concluding remarks. 1. THE HIGH PERFORMANCE ORGANIZATION FRAMEWORK Although the literature shows a large number of publications on high performance from a wide range of disciplines, none of these have actually led to a general theory, model or framework on high performance organisations (HPOs) (Waal, 2010). That is until 2008 when a general multi-disciplinary HPO framework was constructed after a descriptive review of 290 academic and practitioner publications on high performance (Waal, 2008). One of the outcomes of this review was the following definition of an HPO: “A high performance organization is an organization that achieves financial and non-financial results that are better than those of its peer group over a period of time of at least five to ten years.” Also for each of the 290 academic and professional studies found, those elements that the authors indicated as being important for becoming a HPO were identified. Because authors of the publications used different terminologies, the identified elements were grouped into categories which therefore constituted potential HPO characteristics. For each of the potential HPO characteristics the ‘weighted importance’ was calculated, i.e. the number of times that it occurred in the studies. Finally, the characteristics with the highest weighted importance were selected as the HPO characteristics. These characteristics were subsequently included in a HPO survey which was administered worldwide and which encompassed more than 3200 respondents. In this survey the respondents were asked to indicate how good they thought their organizations were performing on the HPO characteristics (on a scale of 1 to 10) and also what their organizational results were compared to their peer group. The competitive performance was calculated using two formulas: (1) Relative Performance (RP): performance of the organisation relative versus the performance of its peer group, RP = 1 – ([RPT - RPW] / [RPT]) in which RPT = total 6
number of peers and RPW = number of peers with worse performance; (2) Historic Performance (HP): performance of the organisation the past three to five years versus the performance of its peers during that time period (choices: worse, the same, or better). These subjective measures of organizational performance are scientifically proven indicators of real performance (Dawes, 1999; Devinney et al., 2005; Glaister and Buckley, 1998). By performing a non-parametric Mann-Whitney test, 35 characteristics which had the strongest correlation with organizational performance were extracted and identified as the HPO characteristics. The correlation was as expected: the high-performing group scored higher on the 35 HPO characteristics than the group with lower performances. This means that organizations which pay more attention to these 35 characteristics achieve better results than their peers, in every industry, sector and country in the world. Conversely, organizations which score low on the characteristics rank performance-wise at the bottom of their industry. This also holds true for the government and therefore managers in governmental agencies have to work on improving these factors and characteristics to create a high performance ministry. Subsequently, a principal component analysis with oblimin rotation of the 35 characteristics resulted in five distinct HPO factors. These five HPO factors and the underlying characteristics are given in Appendix 1 and described in more detail underneath. Further details on the statistics and the characteristics can be found in Waal (2010).
The five HPO factors are: 1. Management Quality. In an HPO, belief and trust in others and fair treatment are encouraged. Managers are trustworthy, live with integrity, show commitment, enthusiasm, and respect, and have a decisive, action-focused decision-making style. Management holds people accountable for their results by maintaining clear accountability for performance. Values and strategy are communicated throughout the organisation, so everyone knows and embraces these. 2. Openness and Action-Orientation. HPOs have an open culture, which means that management values the opinions of employees and involves them in 7
important organizational processes. Making mistakes is allowed and is regarded as an opportunity to learn. Employees spend a lot of time on dialogue, knowledge exchange, and learning, to develop new ideas aimed at increasing their performance and make the organization performance-driven. Managers are personally involved in experimenting thereby fostering an environment of change in the organization. 3. Long-term Orientation. An HPO grows through partnerships with suppliers and customers, so long-term commitment is extended to all stakeholders. Vacancies are filled by high-potential internal candidates, and people are encouraged to become leaders. The HPO creates a safe and secure workplace (both physical and mental), and dismiss people only as a last resort. 4. Continuous Improvement and Renewal. An HPO compensates for dying strategies by renewing them and making them unique. The organization continuously improves, simplifies and aligns its processes and innovates its products and services, creating new sources of competitive advantage to respond to market changes. Furthermore, the HPO manages its core competences efficiently, and sources out non-core competences. 5. Quality of Employees. An HPO assembles and recruits a diverse and complementary management team and workforce with maximum work flexibility. The workforce is trained to be resilient and flexible. They are encouraged to develop their skills to accomplish extraordinary results and are hold responsible for their performance, as a result of which creativity is increased, leading to better results.
An organization can evaluate its HPO status by having management and employees fill in a HPO questionnaire and calculating the average scores on the HPO factors. The HPO Framework has been applied at MINALOC to evaluate whether it could help the ministry to increase its performance.
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2. MINISTRY OF LOCAL GOVERNANCE AND SOCIAL AFFAIRS The Republic of Rwanda is a small landlocked country of 26,338 km2, in the Great Lakes region of East-Central Africa, and is bordered by Uganda, Burundi, the Democratic Republic of the Congo and Tanzania. Home to more than 10 million people (estimate of 2008), Rwanda supports the densest population in continental Africa (337 people per sq. km) most of whom engage in subsistence agriculture (Short, 2008). A country of fertile and hilly terrain, the small republic bears the title ‘Land of a Thousand Hills’. The capital of Kigali has about 1,000,000 inhabitants (estimate of 2006). Currently Rwanda is reforming its civil service in order to make governmental agencies better equipped to deal with the aftermath of the genocide and the continuous rebuilding of the country. The reform is a continues management process designed to bring about public service efficiency in ministries, public institutions and government bodies. A major effort in the reform process is the introduction by the government of a performance management system. Performance objectives have been formulated based on Vision 2020 and these are tracked and, since 2011, reported on. The Vision 2020 objectives have been cascaded down from country level, to sector level, to ministry level, to department level, and finally to individual performance levels. The implementation of performance management has recently been completed and therefore it has only been practised for the last two years. It seems that many people still have problems in formulating performance indicators as well as performance-related objectives related to the impact that the government tries to achieve with Vision 2020 (Meessen et al., 2006). Also, despite the fact that the same performance management system has been introduced in each ministry there are still big differences in results among different ministries. This means that the government currently is not able yet to fully take advantage of performance management. In addition, in some of the ministries there is a high turnover of people and at the same time there is a large number of consultants working for the government. However, in the future there will be a decrease in the budget for hiring consultants. No longer will there be a special budget for hiring outside expertise but ministries will have to pay consultants from their regular yearly budget. In general, despite the efforts of the government, governmental agencies cannot be called HPOs yet. 9
As part of the Rwandan government, the main mission of MINALOC is “promoting the well-being of the population by good governance, community development and social affairs” (Ministry Of Local Governance And Social Affairs, 2011). The Ministry has the following objectives: putting in place democratic, decentralised administrative structures which are able to mobilise the population in order to implement government programs and resolve their own problems; ensuring synergy, collaboration and complementarity between all government institutions in their support to decentralised administrative units; reinforcing human, material and financial capacities of decentralised administrative units, to allow them to fulfil their roles and responsibilities; rolling out to all the population insurance systems, savings facilities and social security mechanisms; putting in place mechanisms for assistance and autopromotion for vulnerable groups, especially genocide survivors; ensuring the implementation and functioning of coordination mechanisms for the management of risks and disasters; and reinforcing planning, coordination and mobilisation mechanisms of the necessary resources regarding good governance, community development and social protection. The main activities to achieve these objectives are the Good Governance, Decentralisation, Community Development, Local Finance and Social Protection programmes. These are executed by the Ministry itself, which is comparatively small (approximately 60 people), and several semi-independent units like the National Electoral Commission (NEC), the Rwanda Governance Advisory Council (RGAC), the National Assistance Fund for Needy Survivors of Genocide (FARG), the Rwanda Demobilisation and Reintegration Commission (RDRC), Rwanda Local Development Support Fund (RLDSF) and the National Decentralisation Implementation Secretariat (NDIS). MINALOC is known in Rwanda as being one of the most effective ministries and as such the Public Secretary (the first civil servant after the Minister) was very much interested in testing the HPO framework to evaluate whether it could help MINALOC to improve its performance toward HPO standard. 3. RESEARCH APPROACH AND RESULTS The research described in this paper was part of a World Bank funded capacity building program at RIAM, the Rwanda Institute of Administration and Management. As part of this program, several short executive courses on strategy and leadership and policy 10
development were conducted, as well as special projects. One such special project was the HPO seminar at MINALOC. One of the authors, detached at RIAM, contacted MINALOC to seek its cooperation. As a result, in August 2011 the HPO diagnosis was conducted at MINALOC during an HPO course with 15 representatives of the Ministry and its semi-independent units. During the first day of the seminar the HPO Framework was explained in detail to the representatives. Discussions took place on possible consequences for MINALOC of becoming an HPO and the benefits this will bring to the Ministry, its managers and its stakeholders. The participants also filled in the HPO questionnaire. In this questionnaire the participants evaluated to what extent MINALOC and its units were HPO. The filled-in questionnaires were processed by the authors and the results were presented the next day. The results gave a first indication of the HPO status of MINALOC as a ‘cooperative’ i.e. a ministry and its semiindependent units. A more representative picture can be obtained when more people from all units of MINALOC fill in the HPO questionnaire. During a break-out session the attention points, which MINALOC needs to address in order to become HPO, were discussed in two groups. Each group drafted a presentation with their analysis of the attention points and their suggestions on how to address these points. Each group presented its findings during a plenary session, in which each presentation was critical commented on by the other group and the authors. After the seminar a write-up was made of the results of the seminar and this was send to all participants. This write-up may serve as the starting document for the further roll-out of the HPO Framework in MINALOC. 1. MINALOC’s HPO results 2. Figure 1 depicts the scores of MINALOC on the five HPO factors, in comparison with the scores of an HPO (8.5 or higher). Appendix 1 provides the detailed scores on the 35 HPO characteristics. The average HPO score of MINALOC is 7.5 which shows that MINALOC is a good performing organization but not yet an HPO. MINALOC’s HPO line is almost level which means that MINALOC is a wellbalanced organization. This constitutes a good starting-point for improvement at MINALOC of all HPO factors. 3. 11
Figure 1: MINALOC’s HPO scores (August 2011, 15 representatives)
Figure 2 comp compares ares ares MINALOC’s average HPO scores with those of other Rwandan (as (as present present in in the the HPO HPO database maintained by one of the authors). Note Note that that the the HPO HPO score, score, and and the the subsequent subsequent analysis in this paper, is of the MINALOC ´cooperative´ ´cooperative´ as as the participants worked at the Ministry itself or at the semi semi-independent independent units of MINALOC. MINALOC. Also, Also, since since only 15 representatives filled in the HPO questionnaire, questionnaire, the the results results may may be be inflated. inflated. All scores, analyses and recommendations recommendations are are therefore therefore merely an indication of MINALOC’s ccurrent urrent status and by no means show the complete picture. picture. This This first first indication shows that MINALOC could be one of of the the better better organizations organizations in in Rwanda. Rwanda. This is stressed by the participants who state state that that what what distinguishes MINALOC from other ministries is th that at MINALOC seems to be better able to to fulfil fulfil its its targets targets because because it has focused on achieving continuous improvement improvement ever ever since since 2006 2006 and and that that in general, because many of MINALOC’s employees employees have have direct direct contact with the constituents, they feel more committed to the organisation than is the case at other ministries.
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Average HPO scores 10 09 8
07 06
6
4
2
0 Rwanda organisations (n=10)
MINALOC
HPO
Figure 2: MINALOC’s HPO scores in comparison with other Rwandan organisations
4. MINALOC’S ATTENTION POINTS As the HPO scores in Figure 1 show, MINALOC still has some efforts to do before it can become a real HPO. During the seminar four attention points were discussed, which MINALOC needs to address in order to become an HPO. At the same time, MINALOC scores high on several characteristics and the organisation should - when working on a transition to HPO - safeguard that it keeps these good scoring points: a unique strategy (in fact: a unique ministry)
(8.2); strong result-driven organisation (8.6) and
management (9.1); management with integrity (8.5) and confidence (8.0); a diverse and complementary workforce (8.1); a good performance measurement system (8.1); and a good focus on clients (8.4) and stakeholders (8.7). Four attention points, in the shape of contradicting HPO characteristics, were identified and discussed during the seminar.
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Attention point 1: The MINALOC processes are continuously improved (8.5) but they are not simplified (4.9). The reason why this is a contradiction is that MINALOC is a complex organisation because there are many demands placed on it at the same time: different intervention areas which have to be dealt with, such as governance, community development, social protection; coordination on local level of activities requested by other ministries, as MINALOC has the best system in place other ministries like to use it and MINALOC cannot deny them this and is also proud to help them; and the many emergency programs that are channelled through MINALOC to reach the local level for implementation. Possible solutions to deal with this attention point are to strengthen the local authorities, as they are the ones who should implement the programmes; harmonise the planning at central (Ministry) and local levels; and reinforce the decentralisation process for other ministerial processes so that these ministries can do it themselves. What is needed to actually improve is that the decentralisation process must be understood and implemented by all ministries, MINALOC should reduce or stop implementing programmes/activities of other governmental agencies as these must do them themselves; MINALOC should strengthen partnerships with the stakeholders, engaging them in dialogue about and involving them in MINALOC´s important processes; reinforce public awareness of MINALOC´s activities. Further suggestion for improvement is to finish a limited number of improvement projects/processes in time, within budget, with the required results before starting new improvements. This means MINALOC managers should show management discipline.
Attention point 2: Management welcomes change (7.7) but does not allow mistakes (4.9). The reason why this is a contradiction is that it is a ‘generally accepted principle’ for management in Rwandan governmental agencies to not accept mistakes openly. However, mistakes are frequently corrected in a collective process without publicity. Therefore the HPO score in itself is correct: MINALOC does not accept mistakes openly. But when made, mistakes are corrected by the group without punishing (and certainly not openly) the one who made the mistake. As such, the participants were of the opinion that no solutions were needed to deal with this attention point. However, the 14
group agreed that several questions still had to be answered in relation to this attention point: How innovative an organisation does MINALOC want to be, and what is then the room to experiment? What are ´failed experiments and how can the organisation learn from them? What should be labelled as a ‘mistake’ in MINALOC, and which mistakes should have consequences and which not?
Attention point 3: MINALOC has a diverse and complementary workforce (8.1) but nonperformers are allowed to stay (5.3) and new management is not promoted from within (5.6). The reason why this is a contradiction is that, when non-performing people are identified, MINALOC allows them to stay and gives them opportunities to improve by strengthening their capacities, giving them more resources and providing more coaching and mentoring. During this time the low-performing people are still around. The participants however discussed that MINALOC should set a time limit on how much time these people get to improve. Another reason is that there is the possibility of performance appraisal bias were some low-performing people get a performance rating which is too high. By law there is a time limit for government employees that if they three times get a performance appraisal score below 70 they will be fired. It is therefore highly likely that management rates employees rate according to the consequences of this rating system and give high enough performance appraisal scores that employees will not be fired. Another issue is that in collective societies, which exist in many African countries (Hofstede, 1980), it is difficult to evaluate people according to their achievements and results. The evaluator will take into account possible negative effects of his ratings (like not getting a bonus or loosing a job) and will likely rate the employee higher than warranted. This results in governments complaining that all employees have high appraisal scores while at the same time goals are not reached. Finally, labour law limits promotion from within, vacancies have to be offered to people outside the organisation so no nepotism can take place. As a result, promotions are driven by competition with people from outside MINALOC. Possible solutions to deal with this attention point are to make the performance appraisal process more objective and realistic (not everybody can score a high rating) and to use standards for the interpretation of rating scales. In a broader 15
context, the labour law should be changed to allow internal promotions and to develop an internal promotion process that is transparent, in order to prevent nepotism . This will increase motivation of employees, is more cost effective for the organization as no lengthy recruitment processes using outside recruitment consultants are needed anymore, and there is no loss of knowledge and skills.
Attention point 4: Management frequently engages in dialogue with employees (7.3) but employees do not go into dialogue with colleagues and do not share knowledge enough with other MINALOC parts (5.7). The reason why this is a contradiction is that the thinking of creating high performance individuals (HPI) and HPOs is not shared and actively encouraged yet within MINALOC. Therefore, especially in the decentralised MINALOC organization, the institutions still operate mainly independently and do not actively get together to share knowledge, ideas and experiences. In addition there is so much work to do that there simply is no time available or taken for knowledge sharing activities. Besides, there is no sharing attitude in the organization. Possible solutions to deal with this attention point are to actively develop a culture which develops knowledge sharing skills; actively develop a culture that strives for HPI and HPO; and reward people for sharing knowledge. The participants agreed that they are part of a bigger entity and that, even if individuals or units perform well but MINALOC as a whole is not, no one working at or under MINALOC is regarded successful by society. Another point in this respect is that MINALOC should focus more on outcome than on output. The Ministry can achieve the targets which the organisation itself sets (the output has been achieved) but that does not necessarily mean that civilians are happy with this output because not enough is changing in society (the outcome has not been achieved). Therefore MINALOC should loom better at what the Ministry wants to bring about in Rwandese society. Further suggestions for improvement were to regular visit the other units of MINALOC, helping the other units with own experiences and ideas, and to organise structural knowledge exchange sessions.
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5. CONCLUSION The research described in this paper shows that the HPO Framework can be used to assess the strength of a Rwandan governmental agency. Combined with the workshop, the framework provided information on the improvement points the ministry needs to work at. In this respect, the HPO framework helped MINALOC to focus on what is really important to improve and thereby supports the improvement process and realization of Vision 2020. As the seminar with MINALOC showed, the wish to become an HPO is present among MINALOC’s representatives, but the efforts have to be guided as many of these initiatives are not sufficiently directed and also management supervision and discipline has to be tightened. The participants stated that the HPO Framework could provide MINALOC with the coordinating framework to direct and guide future improvement efforts. Therefore, the research question posed at the beginning of this article, ‘Can the HPO Framework be applied in the Rwandan context and with that help improve performance at Rwandan governmental organizations?’, can be answered affirmative. This means that other Rwandan governmental agencies can also use the HPO Framework in their quest to becoming world-class agencies, as the framework gives them the factors to focus on in order to increase their performance. A warning, however, is here in order. The difficulties encountered during the creation of a worldclass governmental organisation in Africa should, even when using the HPO Framework, not be underestimated (Gatune and Najam, 2011). As Wang (2001) points out there are additional factors that influence the chances of success which should be taken into account, like the limited degree of openness in African culture, the relative undemocratic leadership in many African institutions, and the required autonomy to which many African cultures are not used yet. Consequently, not only attempts to create world-class governmental organisations should be made but also establishing high performance partners (i.e. suppliers investors, employers, society, local authorities) in the complete governance value chain (Makkar et al., 2008) should be included in order to create a truly high-quality governmental sector in Africa. This gives opportunities for further research. Firstly, the application of the HPO framework can be tested at other governmental agencies, both in Rwanda and in other African countries. Also, longitudinal research could identify whether MINALOC actually increases its 17
performance if it applies the HPO Framework. Finally, involving the partners in value chain research could be beneficial for raising the overall quality of the governmental sector and thereby achieving the objectives of Vision 2020. REFERENCES Ansoms, A. (2005), Resurrection after civil war and genocide: growth, poverty and inequality in post-conflict Rwanda, The European Journal of Development Research, 17, 3: 495–508 Chu, J. (2009), Rwanda Rising, Fast Company, 134: 80-91 Dawes, J. (1999), The relationship between subjective and objective company performance measures in market orientation research: further empirical evidence, Marketing Bulletin, 10: 65-76 Devinney, T.M., Richard, P.J. ,Yip, G.S. and Johnson, G. (2005), Measuring organizational performance in management research: a synthesis of measurement challenges and approaches, Research paper, www.aimresearch.org Ensign, M.M. and Bertrand, W.E. (2010), Rwanda, history and hope, University Press of America, Lanham Gatune, J. and Najam, A. (2011), Africa 2060: what could be driving the good news from Africa?, foresight, 13, 3: 100-110 Glaister, K.W. and Buckley, P.J. (1998), Measures of performance in UK international alliances. Organization Studies, 19, 1: 89-118 Government of Rwanda (2002), Poverty Reduction Strategy Paper, Ministry of Finance and Economic Planning Hofstede, G. (1980), Culture’s Consequences: International differences in work-related values, Thousand Oaks: Sage Publications Horwitz, F.M., Kamoche, K. and Chew, I.K.H. (2002), Looking East: diffusing high performance work practices in the southern Afro-Asian Context, Int. J. of Human Resource Management, 13,7: 1019-1041
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Hoskisson, R.E., Eden, L., Lau, C.M. and Wright, M. (2000), Strategy in emerging economies, Academy of Management Journal, 43, 3:249-267 Isenberg, D.J. (2010), How to start an entrepreneurial revolution, Harvard Business Review, June: 40-50 Khanna, T. and Palepu, K.G. (2006), Emerging giants. Building world-class companies in developing countries, Harvard Business Review, October: 60-69 Khumalo, R. (2001), Concern for others. A management attribute of excellent companies, South African Journal of Business Management, 32, 1: 57-66 Makkar, U., Gabriel, E.O. and Tripathi, S.K. (2008), Value chain for higher education sector - case studies of India and Tanzania, Journal of Services Research, Special Issue, February: 183-200 Meessen, B., Musango, L., Kashala, J.P.I. & Lemlin, J. (2006), Reviewing institutions of rural health centres: the performance initiative in Butare, Rwanda, Tropical Medicine and International Health, 11, 8: 1303–1317 Ministry Of Finance And Economic Planning (2000), Rwanda Vision 2020, Kigali, July, http://www.gesci.org/assets/files/Rwanda_Vision_2020.pdf, accessed September 2, 2011 Ministry of Local Government and Social Affairs (MINALOC) (2000), Implementation strategy for National Decentralization Policy, May, Kigali Ministry
of
Local
Government
and
Social
Affairs
(2011),
http://www.minaloc.gov.rw/index.php?id=11, accessed September 2, 2011 Oosthuizen, H. (2005), The relationship between strategic process dimensions and organisational output performance – A South African investigation in relation to global best practices, S.Afr.J.Bus.Management, 36, 4: 69-79 Rwanda Governance Advisory Council (2010), Governance for production and development, understanding the concept and exploring its applicability in Rwanda, Rwanda Governance Review, vol.1, special issue Rwanda Governance Advisory Council (2011), Rwanda Governance Scorecard 2010, RGAC, Kigali 19
Short, T. (2008), Sustainable Development in Rwanda: Industry and Government, Sustainable Development, 16: 56–69 Silva-Leander, S. (2008), On the danger and necessity of democratisation: trade-offs between short-term stability and long-term peace in post-genocide Rwanda, Third World Quarterly, 29, 8: 1601–1620 Stuart-Kotze, R. (2006), Performance. The secrets of successful behaviour, FT Prentice Hall, Harlow Waal, A.A de (2008), The Secret of High Performance Organizations, Management Online Review, http://www.morexpertise.com/view.php?id=88, accessed July 4, 2011. Waal, A.A. de (2010), The Characteristics of a High Performance Organization, Social Science Research Network, http://ssrn.com/abstract=931873, accessed September 2, 2011 Waal, A.A de and Chachage, B. (2011), Applicability of the high-performance organization framework at an East African university: the case of Iringa University College, International Journal of Emerging Markets, 6, 2: 148-167 Wang, Y. (2001), Building the world-class university in a developing country: universals, uniqueness, and cooperation, Asia Pacific Education Review, 2, 2: 3-9 Waugh, C.M. (2004), Paul Kagame and Rwanda. Power, genocide and the Rwandan Patriotic Front, McFarland & Company Inc, Jefferson, NC
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APPENDIX 1: THE HPO FACTORS AND THEIR CHARACTERISTICS In this Appendix the 35 characteristics are listed per HPO factor, and the scores for MINALOC are given. MINALOC
HPO CHARACTERISTIC
scores
Continuous improvement and renewal 1. The organisation has adopted a strategy that sets it clearly apart from 8.2 other organisations. 2. In the organisation processes are continuously improved.
8.5
3. In the organisation processes are continuously simplified.
4.9
4. In the organisation processes are continuously aligned.
7.6
5. In the organisation everything that matters to performance is explicitly 8.1 reported. 6. In the organisation both financial and non-financial information is 7.1 reported to organisational members. 7. The organisation continuously innovates its core competencies.
8.0
8. The organisation continuously innovates its products, processes and 7.8 services. Openness and action-orientation 9. Management frequently engages in a dialogue with employees.
7.3
10. Organisational members spend much time on communication, 5.7 knowledge exchange and learning. 11. Organisational members are always involved in important processes.
7.8
12. Management allows making mistakes.
4.9
13. Management welcomes change.
7.7
14. The organisation is performance driven.
8.6
Management quality 15. Management is trusted by organisational members.
7.7
16. Management has integrity.
8.5
17. Management is a role model for organisational members.
7.6
18. Management applies fast decision-making.
7.9
19. Management applies fast action-taking.
7.8
20. Management coaches organisational members to achieve better results. 7.7 21. Management focuses on achieving results. 21
9.1
22. Management is very effective.
8.5
23. Management applies strong leadership.
7.7
24. Management is confident.
8.0
25. Management is decisive with regard to non-performers.
5.3
Quality of Employees 26. Management always holds organisational members responsible for their 7.9 results. 27. Management inspires extraordinary results.
organisational
members
to
accomplish
7.5
28. Organisational members are trained to be resilient and flexible.
7.1
29. The organisation has a diverse and complementary workforce.
8.1
Long-term orientation 30. The organisation grows through partnerships with suppliers and/or 7.9 customers. 31. The organisation maintains good and long-term relationships with all 8.7 stakeholders. 32. The organisation is aimed at servicing the customers as best as possible. 8.4 33. Management has been with the company for a long time.
7.1
34. New management is promoted from within the organisation.
5.6
35. The organisation is a secure workplace for organisational members.
7.0
Abstract There are two main responses to climate change. One is adaptation and other is mitigation. The adaptation process includes three essential stages i.e. vulnerability assessment, capacity building and implementation of adaptation measures. The fundamental goal of adaptation strategies is the reduction of the vulnerabilities to climate-induced change. In India 700 million rural populations directly depend on climate-sensitive sectors like agriculture, forest and fisheries and natural resources such as water, biodiversity, mangroves, coastal zones, and grass lands for their subsistence and livelihood. Forests are not just carbon stores. Forests are home to the 22
people who are entirely or partly dependent on forests for their livelihood. In India about 300 million rural poor are dependent on forest for livelihood and more than half of them are tribal and depend on non-timber forest products (NTFPs). Forest as the vulnerable sector and constitute an integral part of social life of tribals and others living in and around forest areas and contribute substantially to the food supply and livelihood security of tribal populations in India. The objectives of the paper are four fold. First, the paper attempts to measure quantitative vulnerability assessment for the forest dependent communities where drought hazards are prevalent and to identify household adaptation strategies to reduce vulnerability due to climate change. Second, the paper tries to estimate the factors responsible for decisions of adaptation to climate change using probabilistic model of Heckman’s two-step process. Third, the paper tries to discuss how Security Diagram Approach and Fuzzy Inference system are used to measure drought vulnerability in India. Lastly, the paper also examines the development policies of the Government of India including the role of micro-insurance and weather-indexed insurance to enhance the resilience of climate change. The paper is an empirical study based on data collected through field survey. This study covers four villages- Rangakula, Khayarakura, Dhansimla and Bandhgaba, both are scheduled tribal based villages located in Sonamukhi forest area in the District of Bankura, one of the drought prone districts of West Bengal, consisting of 100 households in 2010. Socio-Economic Vulnerability Assessment for each village has been calculated. In this study, six factors i.e., public health facility, sanitation, educational status; live stock assets, food sufficiency from agriculture and awareness to climate change have been incorporated for socioeconomic vulnerability assessment of each village. Vulnerability Indices have been calculated using Three Categorized Ranking Method (TCR) assigning scores of 1 to 3, 1 being the least vulnerable. Besides, this paper has identified the households’ adaptation strategies like out-migration; formation of self-help group (SHGs), water harvesting, accessibility of non-timber forest products and livestock rearing. The paper has identified key vulnerabilities as education, health hygiene and food insufficiency. The socio-economic factors and climatic factors both affect the decisions of adaptations to climate change. Microinsurance and weather indexed insurance are providing services to marginalized section of the community in developing countries including India. The Government of India has undertaken little policy action to reduce climate-related vulnerability particularly in the drought- prone regions of West Bengal. This paper has important policy implications for poverty, livelihood vulnerability and migration.
Key words: vulnerability, adaptation, security diagram, socio-economic vulnerability assessment, fuzzy inference system, migration, micro-insurance 23
24
6. INTRODUCTION Climate change is considered to be one of the major threats to sustainable development because of its effects on health, infrastructure, agriculture and food security, and forest ecosystem (IPCC, 2007a). Forest as the vulnerable sector and constitute an integral part of social life of tribals and others living in and around forest areas and contribute substantially to the food supply and livelihood security of tribal populations in India. In India 700 million rural populations directly depend on climatesensitive sectors like agriculture, forest and fisheries and natural resources such as water, biodiversity, mangroves, coastal zones, and grass lands for their subsistence and livelihood. Of this about 300 million rural poor are dependent on forest for livelihood and more than half of them are tribal and depend on non-timber forest products like food, fuelwood, medicine, sal leaves, kendu leaves and mushrooms etc. The forest dwellers and adjacent farmers identified by Byron and Arnold (1999) are particularly at risk due to climate change. The impact of climate change on forest dependent communities has been documented in Bhutan (Tshering, 2003), Vietnam (Trieu, 2003), India (Sharma, 2003), China (Shougong et al., 2003), Malawi (Fisher 2004), Mozambique (Lynam et al., 2004), Ethiopia (Mamo et al., 2007). The vulnerability of many communities in developing countries is immense and their capacity to adapt to future climate change impact is assumed to be very low (Huq et al., 2004; Mertz et al., 2009a). The presence of adaptive capacity is necessary condition for the design and implementation of effective adaptation strategies so as to reduce the likelihood and the magnitude of harmful outcomes resulting from climate change (Brooks and Adger, 2005). Adaptive capacity refers to communities’ capacity to take advantage of the benefits and opportunities associated with a changing climate. The IPCC’s Third Assessment Report (AR3) proposes that the main features of a community’s adaptive capacity comprise economic resources, infrastructure technology, infrastructure, information and skills, institutions and equity (IPCC, 2001). Studies carried out after AR3 led the Fourth Assessment Report (AR4) to acknowledge the influence of social factors such as human capital and governance structures (IPCC, 2007b). The fundamental goal of adaptation strategies is the reduction of the vulnerabilities to climate-induced change. The paper focuses on understanding and quantifying the 25
vulnerability & adaptation strategies taken by forest dependent communities in West Bengal. Climate change and variability is not new, and many societies have adeptly coped with and adapted to climate variability and many other stressors during the past centuries (Mertz et al., 2009a). A growing number of literatures in the past two decades has examined climate change as the most important issue in global environment and also analyzed vulnerability to climate change. According to Intergovernmental Panel on Climate Change (IPCC), the vulnerability due to climate change of a region depends to a great extent on its wealth, and that poverty limits adaptive capabilities (IPCC, 2001). Further, they argue that socio-economic systems “typically are more vulnerable in developing countries where economic and institutional circumstances are less favorable”. Vulnerability is often reflected in the condition of the economic system as well as the socioeconomic characteristics of the population living in that system. This paper attempts to construct a picture of socioeconomic context of vulnerability by focusing on indicators that measure both the state of development of the region as well as its capacity to progress further. There is growing interest in the potential of insurance as part of an effective ex ante risk-management strategy (Linnerooth-Bayer, Mechler and Pflug, 2005). Currently, only 1% and 3% of households and businesses in low- and middle-income countries, respectively, have insurance coverage against catastrophe risks, compared with 30% in high income countries (Munich Re, 2005). Furthermore, the poor are often exposed to multiple shocks such as illness and natural hazards at the same time. Without savings or family support, disasters may lead to a “cycle of poverty,” as victims take out highinterest loans or default on existing loans, sell assets and livestock, or engage in lowrisk, low-yield farming to lessen their exposure to extreme events. Micro insurance can break the “cycle of poverty” by providing low-income households, farmers, and businesses with access to post disaster liquidity, thus securing their livelihoods and providing for reconstruction. As insured households and farms are more creditworthy, insurance can also promote investments in productive assets and higher- risk/higher-yield crops. Moreover, insurance can encourage investment in disaster prevention if insurers offer lower premiums to reward risk-reducing behavior. 26
Thus, micro insurance is treated as an effective risk transfer mechanism, risk management strategy and ex post coping measures. Microfinance is a tool that can reduce the vulnerability of the poor and the possibility of linking this tool to climate change adaptation is of considerable importance (Hammill et.al. 2008). The Self Employed Women’s Association (SEWA) in India offers housing loans to repair or replace roofs, reinforce walls, or rebuild houses to reduce vulnerability to extreme events such as floods, droughts and storms (Pantoja, 2002). Migration by the poor as a response to natural calamities and other shocks have been documented (Murthy, 1991; Mukherjee 2001). This migration is called distressed migration (Mukherjee, 2001). During the past ten years, a number of indices related to vulnerability, sustainability, and quality of life gained prominence in the literature. Among them are the Environmental Vulnerability Index (Kaly et al. 1999; SOPAC 2005), Environmental Sustainability Index (Esty et al. 2005), Human Development Index (UNDP 1990; 2005), Human Well-being Index (Prescott-Allen 2001) and Prevalent Vulnerability Index (Cardona (2005).
These studies are useful for cross country comparison of
vulnerability. However, the most of the above studies fail to provide critical insights in terms of effective adaptation strategies at the micro or household level. Studies on the impact of climatic change (in particular rainfall and temperature) and climate-related adaptation measures on forest dependent people are very scanty in India. In addition, much of the early research work on adaptation focused on identifying potential impact of future climate change using General Circulation Models (GCMs). But the models proved to be extremely limited in telling us about regional impacts of climate change and therefore did not really provide a basis for catalyzing immediate and practical action on local level adaptation. Given the backdrop the objectives of the study are as follows. First, the paper attempts to measure quantitative vulnerability assessment for the forest dependent communities where drought hazards are prevalent and to identify household adaptation strategies to reduce vulnerability due to climate change. Second, the paper tries to estimate the factors responsible for decisions of adaptation to climate change 27
using probabilistic model of Heckman’s two-step process. Third, the paper tries to discuss how Security Diagram Approach and Fuzzy Inference system are used to measure drought vulnerability in India. Lastly, the paper also examines the development policies of the Government of India including the role of micro-insurance and weather-indexed insurance to enhance the resilience of climate change. The paper is organized as follows. In section 1 analysis of vulnerability by IPCC’s definition and security diagram approach and fuzzy Inference system is presented. Section 2 discusses methodology and data. Section 3 utilizes socio-economic vulnerability assessment of four forest dependent villages in the drought prone district of West Bengal and adaptation options taken by households. Section 4 discusses the determinants of adaptation by Heckman’s two-step process. Section 5 discusses the experiences of micro insurance in developing countries in the context of climate change research. Conclusions and governmental policies are presented in section 6.
7. ANALYSIS OF CLIMATE CHANGE VULNERABILITY ACCORDING TO IPCC DEFINITION There are two ways of assessing vulnerability and determining appropriate adaptation options. One is hazards-based adaptation approach while other is vulnerability reduction- based adaptation approach. In the hazards-based adaptation approach, adaptation is carried out in response to the observed and experienced impacts of climate change on society (including ecosystems). These responses ensure that the vulnerability to the impacts is reduced. This in turn risk is reduced. With reduced risk, development can be more sustainable. In short, the process is given below: Adaptation to climate change impacts → Vulnerability reduction → Development On the other hand, vulnerability-based approach is referred to as “second-generation vulnerability assessments”,
gives explicit consideration to various non climatic
determinants of vulnerability and adaptive capacity, including poverty, economic inequality, health, effectiveness of government institutions, literacy, and education levels. The primary advantage of this approach is that it allows for incorporating a 28
range of both climatic and non climatic vulnerability factors into adaptation planning. In this view, development processes help reduce vulnerability to climate change. By reducing the vulnerability, impacts of climate hazards are also reduced, as there is less sensitivity and exposure to the hazards. This translates into a process of adaptation to climate change. Climate-aware development → Vulnerability reduction → Impact reduction → Adaptation Understanding the vulnerability of forest dependent people is a first step towards designing effective adaptation. Two main approaches to vulnerability assessments are generally applied to social-ecological systems. One is impact-based approaches (or impact studies) and other is vulnerability-based approaches. Impact-based approaches start with assessing the potential impacts of climate change on forest or forest people under different climate scenarios. Vulnerability-based approaches start with assessing social sensitivity and adaptive capacity to respond to stresses and, if necessary, combine this information with impact studies (Kelly and Adger 2000). With vulnerability-based approaches, vulnerability is determined by the existing capacity rather than by any predicted future impacts (Ribot 2009). To facilitate adaptation processes for forest dependent people, vulnerability-based approaches seem more adequate than impact studies (Burton et al. 2002). According to the conceptualization of IPCC, vulnerability to climate stimuli is a broader concept than potential impact of climate change as determined by climate impact assessments. Vulnerability assessment is an extension of a climate change impact assessment. This assessment is discussed under two headings, viz. first generation vulnerability and second generation vulnerability. Figure 1 describes the main components of the first generation vulnerability assessment.
29
…………………
Emissions
. Mitigation
Concentration s Climate Change
Non-climatic factors
Climate Variability
Adaptation
Exposure
Sensitivity
Impacts Vulnerability to climate change
Figure 1. Conceptual framework for a first generation vulnerability assessment
Source: Füssel and Klein 2006
Climate variability is a new component in the above diagram implying variations in the mean state and other statistics of the climate on all temporal a spatial scales beyond that of individual weather events. It is an important component of a system’s exposure to climate stimuli. Global climate change will affect climate variability in terms of frequency, intensity and location of extreme events. Non-climatic factors consists a wide range of environmental, economic, social, demographic, technological and political factors. These factors affect both sensitivity and exposure to climate change stimuli. Second generation vulnerability assessments determine realistically the vulnerability of certain systems or regions to climate changes, along with other stress factors. The following figure 2 describes the components of second generation vulnerability assessments. It adds two components, viz. ‘Non-climatic drivers’ and ‘Adaptive Capacity’ to the previous diagram.
30
…………………
Emissions
.
Non-climatic drivers
Concentration s Climate Change
Mitigation
Non-climatic factors
Climate Variability
Adaptation
Exposure
Sensitivity
Adaptive capacity
Impacts Vulnerability
Figure 2. Conceptual framework for a second generation vulnerability assessment
Source: Füssel and Klein 2006
The adaptive capacity of a system or society refers to its ability to modify its characteristics or behavior according to the changes to the external factors. According to figure 2, non-climatic factors determine adaptive capacity of a system or society. IPCC definition of adaptive capacity does not segregate between social and natural system. However, Brooks (2002) classifies factors that determine adaptive capacity into hazard specific and generic factors, and into endogenous and exogenous factors. Nonclimatic drivers affect relevant non-climatic factors which in turn determine the sensitivity of a system to climate change. In this context globalization and urbanization are two non-climatic drivers and mitigation also influences non-climatic factors (Fussel & Klein 2006). The main purpose of the adaptation policy assessment is to provide specific recommendations to planners and policy makers on the enhancement of adaptive capacity and the implementation of adaptation policies. According to Scheraga and Furlow (2001) decision-makers require very specific types of information in order to 31
design and implement effective adaptive responses, and that uncertainties about future climate change and its impacts are a crucial issue in this context. The following figure 3 shows the components of this final stage. Impleme ntation
…………………
Emissions
.
Non-climatic drivers
Concentration s Climate Change
Mitigation capacity
Mitigation Facilitatio n
Non-climatic factors
Climate Variability
Implem entatio
Exposure
Sensitivity
Adaptive capacity Facilitati
Adaptatio on n
Impacts
Vulnerability to climate change
Figure 3. Conceptual framework for a second generation adaptation policy assessment
Source: Füssel and Klein 2006
The above figure 3 distinguishes two types of adaptation activities, viz. facilitation and implementation. Facilitation refers to activities that enhance adaptive capacity such as scientific research, data collection, awareness raising, capacity building, and the establishment of institutions, information networks, and legal frameworks for action. Implementation refers to activities that actually avoid adverse climate impacts on a system by reducing its exposure or sensitivity to climatic hazards, or by moderating relevant non-climatic factors.
The relationship between adaptive capacity and
adaptation in the conceptual framework is two-fold. Adaptive capacity determines the feasibility of the implementation of adaptation, and it is itself influenced by measures that would be considered as facilitation of adaptation. 32
7.1
Analysis of vulnerability by security Diagram and Fuzzy Inference system
The Security Diagram has three components, namely, environmental stress, state susceptibility and crisis probability curves. The Security Diagram is used to measure drought vulnerability. It depends on both water stress and socio-economic susceptibility. The assumption behind the Security Diagram is that the higher the water stress, the higher the likelihood of crises. At the same time, the higher the socioeconomic susceptibility (i.e. the lower the adaptive capacity), the lower the stress required to cause a crisis. Within the framework of the Security Diagram vulnerability is expressed in the functional form as z = f (x, y) where z are some measurable indicators of the level of vulnerability, which are a function of two explanatory variables – socio-economic susceptibility (x) and water stress (y). The contour line of the Security Diagram is shown in Figure 4. The assumption of contour lines represent the higher the contour lines away from the origin shows the higher vulnerability and vice versa.
Figure 4 Contour lines of the security diagram
Source: Lilibeth Acosta-Michlik et al, 2005
The contour lines z1, z2 and z3 are the different levels of vulnerability at varying combinations of socio-economic susceptibility x and water stress y. correspondingly, vulnerability is quite low at z1 and high at z3. The Security Diagrams assumes that crisis is likely to occur at say, points between z2 and z3, where the levels of socioeconomic susceptibility are highest or, in other words, the adaptive capacity to impacts of water stress are lowest. These contour lines are treated as “crisis probability curves”. 33
The low crisis probability curve (CPCL) and high crisis probability curve (CPCH) correspond to z2 and z3 in Figure 5, respectively. The probability curves are a convenient yardstick for measuring the degree of vulnerability of the state over time.
Figure 5 Contour lines of the security diagram
Source: Lilibeth Acosta-Michlik et al, 2005 7.2
Fuzzy Inference System
Fuzzy Inference System is used to measure drought vulnerability (Bhattacharya and Das 2007; Lilibeth Acosta-Michlik et al, 2005). Fuzzy set theory is useful to translate linguistic statements such as ‘high’ or ‘low’ into numerical values. This involves translation of propositions into quantitative values using membership functions. A fuzzy set is the set of real numbers characterized by a membership function in the interval (0, 1). The degree of membership lies between zero and unity. Membership function may be of trapezoidal, triangular, bell-shaped and others. The ‘Low’ and ‘Very High’ vulnerabilities are defined by trapezoid membership functions while the ‘Moderate’ and ‘High’ vulnerabilities are defined by triangle membership functions. Intrinsic vulnerability was scaled arbitrary from 1 to 100. Trapezoidal membership function is given by
34
0, x < a x−a ,a ≤ x < b b−a Trapezoidal ( x : a, b, c, d ) = { 1, b ≤ x < c d−x ,c ≤ x < d d −c 0, x ≥ d Triangular membership function is given by
0, x < a ( x − a) ,a ≤ x ≤ b (b − a ) Triangle( x : a, b, c) = (c − x ) ,b ≤ x ≤ c (c − b ) 0, x > c Membership Function
1
0.4 M
L o w
0.4
High
Very High
0.2 0 20
40
60
35
80
100
Intrinsic Vulnerability
8. METHODOLOGY AND DATA 8.1
Methodology
This study was conducted in four villages- Bandhgaba, Dhansimla, Rangakula, Khayarakura, both are tribal based villages located in Sonamukhi forest area in the District of Bankura, one of the drought prone districts of West Bengal, consisting of 100 households in 2010. 25 households from each village have been selected on the basis of random sampling. The field work combined interviews and discussions with the local people and interviews with local experts and school teachers and other knowledgeable elders in the village. A total of 100 structured household interviews were conducted. In most households the interviewees were mixed gender. Although women were in some cases formally considered the head of household, most often male members responded to the questions. In addition, data on socio-economic variables, like age, sex, education, land holdings, sources of credit, physical assets, livestock assets, income from various sources, public health facilities, adaptation measures like migration, non-timber forest products; self-help groups have been collected from the field survey. The socioeconomic indicators and adaptation diagram of four villages are presented in the Appendix. 8.2
Basic Profile of the Drought prone district of Bankura
The socio-economic condition of the district of Bankura is shown in table 1. It is observed from table 1 that 71.1% of households use safe drinking water and 11.9% households have toilet facilities. On the other hand, the district has 27.7% electrified households and 79 per 1000 are under five mortality rate. The female literacy rate is 48.9%. Fifteen years’ (1995-2009) average actual rainfall is 1285 mm but normal rainfall is 1378 mm. Fifteen years’ (1995-2009) average maximum temperature is 44.36 degree Celsius and minimum temperature is 8.2 degree Celsius. Agro-climatically, the region mainly occupies red and laterite soil zone. The trend of rainfall over fifteen year is declining (see Fig.6). The trend in maximum and minimum temperature for the district of Bankura is on the rise (see Fig.7 and Fig.8).
36
Table 1: Socio-economic indicators of the district of Bankura in all India perspective Indicators
%
Rank in India
Index value
% of households 71.1 using safe drinking water
373
0.69878
% of households 11.9 with toilet facility
538
0.07741
% of Electrified 27.7 households
451
0.25508
Under –five 79.0 mortality rate per 1000
122
0.83776
% of female literacy 49.8 rate
341
0.40364
Source: International Institute for population sciences, India, 2006 Deviation of actual rainfall from normal
Trends in maximum temperature
300
Rainfall in m m
100 0 -100
1
3
5
7
9
11
13
Deviation from normal
15
-200 -300
maximum temperature in centigrade
46
200
45 44 43
Maximum temperature
42 41 40 39 38
-400
1
Year ( 1995-2009)
3
5
7
Figure 6 Trends in rainfall in the District of Bankura
minimum temperature
12 10 8 Minimum temperature
6 4 2 0 3
5
7
11
13
15
Figure 7 Trends in max temperature
Trends in minimum temperature
1
9
Year ( 1995-2009)
9
11
13
15
Year ( 1995-2009)
Figure 8 Trends in minimum temperature 37
9. SOCIO-ECONOMIC VULNERABILITY AND ADAPTATION For the study of socio-economic vulnerability, six factors like public health facilities, sanitation, educational status; live stock assets, food sufficiency from agriculture and awareness to climate change have been incorporated of each village. Vulnerability Indices have been calculated using Three Categorized Ranking Method (TCR) assigning scores of 1 to 3, 1 being the least vulnerable. The basic assumptions are the following; First, lower level of educational facilities is associated with higher vulnerability Second, lower level of sanitation is associated with higher vulnerability Third, higher level of livestock assets is associated with lower vulnerability Fourth, lower level of awareness to climate change is associated with higher vulnerability Fifth, higher food insufficiency is associated with higher vulnerability Sixth, higher health care facility is associated with lower vulnerability. The socio-economic vulnerability was assessed which identified Bandhgava village as the highest vulnerable among four villages, because of its weak adaptive capacity including highest (92%) illiteracy, almost 100 % of village respondents had less than three months food sufficiency to sustain their livelihood and 100% of households do not have any health care facilities (Table 2).
Table 2: Vulnerability Assessment for four villages in West Bengal Village
Educ Sanita ation tion
Livestock assets
Climate awareness
Food sufficiency < 3 months
Health care facility
Comb Vulnera ined bility.
Bandhgaba
3
3
1
1
3
3
2.33
H
Dhansimla
3
2
1
1
3
1
1.84
L
Rangakula
2
3
1
1
2
3
2.00
M
Khairakura
2
3
1
1
2
3
2.00
M
Source: Field Survey Note: H stands for high, M stands for medium and L stands for low. 38
9.1
Analysis of Adaptation options by the households
We asked the sample households as to how they adapted with the adverse effect of climate change. They answered the accessibility minor forest products (say non-timber forest products), water harvesting by means of digging and drilling for drinking water, distress migration, formation of self- help group (SHGs) in the micro finance program, livestock rearing are the possible adaptation options. These options are presented in Table 3. The distress migration is acute in the village Bandhgaba. It is also found from Table 3 that the adaptation capacity of the village Bandhgaba is low due to lack formation of SHGs and the occurrence of maximum migration in that village.
Table 3: Adaptation strategy by the households in the four villages of the District Bankura Adaptation strategy
Bandhgaba Village
Dhansimla Village
Rangakula Village Khairakura Village (% of household (% of household (% of household responses (Yes) (% of household responses (Yes) responses (Yes) responses (Yes)
Water harvesting 100 in the form of digging and drilling for drinking water
20
100
100
Distress migration
76
56
4
8
Collection and 84 sale of nontimber forest products
92
76
84
Formation of 4 Self-Help Groups
8
24
24
Livestock rearing
88
92
92
92
Source: Field Survey In terms of income generation, the optimum adaptation option is the collection of non-timber forest products in both villages (Table 4).
39
Table 4: Yearly Mean Income of the households from different sources (1$= Rs 44)
Name of the Mean Villages annual income from agriculture (Rs)
Mean annual income from wage labour (Rs)
Mean annual income from nontimber forest products
Mean annual income from livestock
Mean annual income from others
(Rs)
(Rs)
Mean annual total income (Rs)
(Rs) Bandgaba
1808
6213
15945
532
72
24571
Dhansimla
1136
5337
11333
42
5712
23560
Khairakura
728
5393
14184
2298
0
22604
Rangakula
792
7162
13058
965
1920
23896
Source: Field Survey
10. DETERMINANTS OF ADAPTATION BY HECKMAN’S TWO-STEP MODEL 10.1 Empirical model Adaptation to climate change is a two-stage process involving perception and adaptation stages. The first stage is whether the respondent perceived there was climate change or not, and the second stage is whether the respondent adapted to climate change conditional on the first stage that he/she had perceived climate change. Because the second stage of adaptation is a sub-sample of the first stage, it is likely that our second stage sub-sample is non-random and different from those who did not perceive climate change creating sample selection bias. We therefore used the well known maximum likelihood Heckman’s two-step procedure (Heckman, 1976) to correct for this selectivity bias.
40
Heckman’s sample selection model assumes that there exists an underlying relationship which consists of: The latent equation given by: (1)
Yj*= Xj β+U1j
Such that we observe only the binary outcome given by the probit model as: Yj probit = (Yj* > 0)
(2)
The dependent variable is observed only if the observation j is observed in the selection equation: Yj select = ( Zj δ + U2 j >0)
(3)
U1 ~ N ( 0,1) U2 ~ N (0,1) Corr (U1, U2 ) = ρ Where, x is a k- vector of explanatory variables which include different factors hypothesized to affect adaptation and z is an m vector of explanatory variables which include different factors hypothesized to affect perception; U1 and U2 are error terms. The first stage of the Heckman’s sample selection model is the perceptions of changes in climate and this is the selection model (Equation 3). The second stage, which is the outcome model (Equation 1), is whether the people adapted to climate change, conditional on the first stage that she/he perceived a change in climate. When, standard probit techniques applied to equation (1) yield biased results. Thus, the Heckman probit provides consistent, asymptotically efficient estimates for all parameters in such models (Van de Ven and Van Praag, 1981). The Heckman probit selection model is employed to analyze the perception and adaptation to climate change for the forest dependent people in the drought prone area of West Bengal.
41
10.2 Model variables The variables hypothesized as affecting perceptions and adaptations to changes in climatic conditions along with their respective dependent variables as indicated below (Table 5). 10.3 Dependent variables for the outcome equation This study has identified the dependent variables for adaptations are migration, formation of Self-help Group (SHGs), accessibility of minor forest products (i.e., nontimber forest products) and livestock rearing. The adaptation measures reported by households might be profit driven rather than climate change. In terms of annual income generation we have chosen the accessibility of non-timber forest products as the dependent variable for the outcome model. 10.4 Explanatory variables for the outcome equation As indicated in Table 5 below, the explanatory variables for this study include: age of the head of the households, maritial status, operational holdings, physical asset value, livestock asset value, farm income, wage income, forestry income, temperature and family size. 10.5 Dependent variable for the selection Equation The analyses of the perception of the forest dependent communities to climate change indicate that most of them for this study are aware of the fact that temperature is increasing. To get information on their perceptions to climate change, people were asked two sets of questions. The first was asking people if they have observed any change on the amount of temperature over the 10 years. The second set consisted of asking the people if the numbers of hot have increased over the 10 years. 10.6 Explanatory variables for the Selection equation For the selection equation, it is hypothesized that, education, age of head of the household, maritial status, adult male in the family, operational holdings, physical asset value, livestock asset value and family size influence the awareness of the people to climate change.
42
10.7 Results and discussion The Heckman probit model was run and tested for its appropriateness over the standard probit model. The results indicated that the likelihood function of the Heckman probit model was significant (Wald χ 2= 88.25, with p < 0.0000) showing strong explanatory power of the model. The results from regression indicated that most of the explanatory variables affected the probability of adaptation as expected. Variables that positively and significantly
influenced the adaptation to climate change include the age of the household, farm income, forestry income, temperature and family size (Table 6). Age positively influence the decision to adopt. Because the elder people have more experience and are better assess to the non-timber forest products than younger one, and hence a higher probability of adopting the practice. Family size also influences decision to adapt. There is a possibility that the households with many family members may be forced to collect forest products to earn income to ease the consumption pressure imposed by a large family size. Adaptation to climate change increases with increasing temperature. The increasing temperature has damaging effect on agriculture and raises the food insecurity. They respond to this through the adoption of different adaptation methods. This result supports the results of Kurukulasuriya and Mendelsohn 2006. Income from forestry has significant and positive impact on adaptation. With higher income from forestry there is a possibility to enhance adaptation in order to minimize the risk of climate change. There is a negative association between operation holdings and adaptation. This means that the low holding farms have greater adaptation compared to the large holding farms. The negative association is also true in the case of physical asset value and wage income. These findings are contrary to the adaptation in the case of agricultural farmers. Variables say age, the numbers of adult male and operational holdings are found to be significant and positive impact on the perception of temperature increased (Table 6).
43
Table 5: Description of model variables for the Heckman probit model Outcome Equation ( Adaptation Model)
Selection Equation ( Perception Model)
Dependent variable
Dependent variable
Description
People reported to have adapted (%)
People reported not adapted (%)
Description
People perceived change in temperature (%)
People not perceived change in temperature (%)
Accessibility of non-timber forest products
93
07
Perception of temperature increased
97
03
Independent variables
Independent variables
Description
Mean
Standard deviation
Description
Mean
Standard deviation
Age ( in years)
42.04
11.03065
Age( in years)
42.04
11.03065
1.69
3.280475
Education ( in years)
1.69
3.280475
Maritial status ( Yes=1, No=0)
.96
.1969464
Maritial status ( Yes=1, No=0)
.96
.1969464
Operational holdings ( acres)
.2804
.4572777
Adult male ( in number)
1.74
.9808263
Physical asset value ( in rupees)
2503
4361.11
Operational holdings ( in acres)
.2804
.4572777
Livestock asset value( in rupees)
7034
7341.551
Physical asset value ( in rupees)
2503
4361.11
Farm income( in rupees)
558
1565.033
Livestock asset value ( in rupees)
7034
7341.551
Wage income( in rupees)
2012.2
959.6796
Forestry income ( in rupees)
9180.32
5358.226
Family size( number)
4.05
1.217507
42.716
1.31769
Education years)
(
in
in
in
Temperature ( in degree centigrade)
Source: Field survey
44
Table 6: Results of the Heckman probit selection model
Estimated coefficients outcome equation : adaptation model (Accessibility of non-timber forest products)
Estimated coefficients selection equation: perception model (Perception of temperature increased)
Regression
Regression
Explanatory variables
Coefficients
P-level
Coefficients
P-level
Age
.0071718*
.051
.0051122*
0.084
Education
-.0105356
.326
-.1283213
.340
Maritial status
-.3440105*
.061
3.397025
.587
1.570946**
.031
Adult male Operational holdings
-.189778*
.075
1.54126***
.001
Physical asset value
-.0000219**
.017
.0002927
.665
Livestock asset value
-3.23e-06
.544
-.0000769
.179
Farm income
.0000336
.267
Wage income
-.0000648*
.084
Forestry income
.0000259*** .001
Temperature
.0686993**
.014
Family size
.0789276**
.031
Cons
-2.237576
.066
-8.750143
.204
Total observations
100
Censored observations
59
Uncensored observations
41
Wald chi slopes)
square(zero 88.25***
0.000
Note: *** significant at 1% level, ** significant at 5% level and * significant at 10% level Source: Field survey
45
11. ROLE OF MICRO-INSURANCE IN DEVELOPING COUNTRIES INCLUDING INDIA Micro-insurance is characterized by low premiums or coverage for low-income people who are engaged in wide variety of income generation activities and who remain exposed to variety of risks. Micro-insurance covers a broad range of risks like life, health and weather risks (including crop and livestock insurance). The Weather-based Crop Insurance Scheme is the One of the largest micro-insurance schemes. Weather indexed insurance is defined as an index based on historical data (e.g. for rainfall, temperature, snow, etc) rather than the extent of loss (e.g. crop yield loss). The problem of moral hazard is minimized. Weather-indexed insurance can help farmers avoid major downfalls in their overall income due to adverse weather related events. This improves their risk profile and enhances access to bank credit, and hence reduces their overall vulnerability to climate variability TERI and IISD (2006). Let us present some experiences of index based insurance in developing countries including India. 11.1 India: Rainfall Index Insurance In 2003, BASIX (an MFI), partnering with ICICI Lombard (an insurer) and receiving technical assistance form the Commodity Risk Management Group of the World Bank, introduced a rainfall-index insurance to address high default rates and increase lending opportunities in rural sectors. BASIX conducted a pilot study, selling weather insurance to 230 farmers in Andhra Pradesh during the 2003 monsoon season, June to September. The 2003 pilot was designed to protect farmers from drought during the groundnut and castor-bean-growing season (Manuamorn, 2007). In 2004, BASIX sold rainfall index insurance to 700 farmers (Bryla & Syroka, 2007). By 2005, BASIX sold insurance to 6,703 customers in 6 states in India (Ibarra & Syroka, 2006). In 2006, BASIX provided rainfall insurance to 14,000 farmers. Due to the success of BASIX with the 2003 pilot, other insurers also began selling rainfall insurance in 2004. For instance, IFFCO-Tokyo also launched weather insurance contracts, selling over 3,000 policies to farmers throughout India. In addition, the state supported insurance program, the Agricultural Insurance Company of India (AICI), began offering index insurance in 2004,
46
reaching 13,000 farmers, and in 2005, it sold 120,000 of the 250,000 index insurance policies sold in India that year. 11.2 Mongolia: Index-based Livestock Insurance In 2001, an index insurance program, Index Based Livestock Insurance (IBLI) using a livestock mortality rate by species and county was recommended to the Government of Mongolia by the World Bank. The scheme was designed in response to massive livestock losses from severe winter weather that killed a third of all the livestock over the course of three years (2000–2002). The Government of Mongolia (GoM) was began a three year pilot program in three provinces of Mongolia, Bayankhongor, Uvs and Khenti, starting with sales in the spring/summer of 2006. During the initial pilot season in 2006, 2400 policies sold with a premium total of MNT (Mongolian Tugrik) 83,775,822 (~USD 70,000). In 2007, 3700 policies sold which represents close to 13 percent of eligible herders and 10 percent of livestock in the pilot areas. Total premium in 2007 were MNT 129,047,464 (USD 109,000). This is a 65 percent increase over the first year of sales. 11.3 Ethiopia: Index-linked Crop Insurance Ethiopia contains approximately 17 million farmers (Syroka & Wilcox, 2006).The entire Ethiopian economy and food security for rural households can be threatened by low rainfall that damages agricultural production (Skees et al., 2006). In 2006, the WFP purchased a weather index insurance contract to protect Ethiopia from extreme drought during its agricultural season. Purchased from a European reinsurer, AxaRe, the insurance contract is based upon rainfall data from 26 weather stations throughout Ethiopia for the March to October growing season of 2006 (Syroka & Wilcox, 2006). In the event of a drought, the WFP will use indemnity payments to fund some of the aid relief for food insecure households and needy agricultural producers. The specific value of the payments are contingent upon the level of rainfall; however, the amount of protection purchased is only a fraction of the total costs WFP would face in Ethiopia in the event of a severe drought, thus illustrating a risk management plan that blends ex ante financing and food reserves (Skees et al., 2006). 47
11.4 Malawi: Index-linked Crop Insurance Project Groundnut farmers in Malawi wanting to plant with certified groundnut seed were unable to obtain credit because of the high default risk in the event of a drought (Alderman& Haque, 2007). A drought in 2004–05 led to high default rates for agricultural loans ranged from 30 percent to 50 percent in Malawi resulting in many lenders refusing to offer credit for agriculture (Mapfumo, 2007). A pilot was launched in the 2005–06 growing season linking two lenders, the Insurance Association of Malawi, and NASFAM (a smallholder farmers union; Alderman& Haque, 2007). The two lenders provided loans to smallholders who agreed to purchase index insurance. The loan covered the costs of seed and insurance premiums (Opportunity International, 2005). Table 8 shows the summary of index based risk transfer products in lower income countries of the developing world.
Table 8 Summary of index-based Risk Transfer Products in Lower income countries Country
Risk Event
Contract Structure
Index measure
Target user
Status
Bangladesh
drought
Index insurance linked to lending
Rainfall
Small holder rice farmers
In 2008
Caribbean Catastrophe Risk insurance facilities
Hurricanes earthquakes
Index insurance contracts with risk pooling
Indexed data from NOAA and USGS
Caribbean country governments
In 2007
Chiana
Low,intermittent rainfall
Index insurance
Rainfall storm count
Smallholder watermelon farmers
In June 2007
Ethiopia
drought
Index insurance
Rainfall
Index insurance
Rainfall
Ethiopia
Drought
and
48
and day
WFP operations Ethiopia
in
Small holder farmers
USD 7 million insured for 2006,Policy not renewed for 2007 due to lack of donor support 2006 pilot,currently closed due to
limited sales Ethiopia
Drought
Honduras
Drought
Weather derivative
Satellite and weather data
NGO
Rainfall
In 2007 In development
Drought and flood
Index insurance linked to lending and offered directly to farmers
Rainfall
Small holder farmers
In 2007
Drought
Index insurance linked to MPCI program
Rainfall
Medium and large farms
In development
Drought
Weather derivative
Satellite and weather data
NGO
In 2007
Mali
Drought
Weather derivative
Satellite and weather data
NGO
In 2007
Malawi
Drought
Index insurance linked to lending
Rainfall
Groundnut farmers who are members of NASFAM
In 2005
Mexico
Natural disasters impacting small holder farmers,primarily drought
Index insurance
Rainfall,wind speed, and temperature
State governments for disaster relief.Supports the FONDEN program
In 2002
Mexico
Major earthquake
Index linked CAT bond and index insurance contracts
Richter scale readings
Mexican governments to support FONDEN
In 2006
Mexico
Drought effecting livestock
Index insurance
Normalized difference vegetation index
Livestock breeders
Launched 2007
Mexico
Insufficient irrigation supply
Index insurance
Reservoir levels
Water users groups in the Rio Mayo area
Second pilot sales season of pilot completed in 2007; 14% participation
Mongolia
Large livestock loses due to sever
Index insurance
Area livestock mortality rate
Nomadic herders
Launched 2006
India
Kazakhstan
Kenia
49
in
in
weather
with direct sales to herders
Morocco
Drought
Index insurance
Rainfall
Smallholder farmers
Nicaragua
Drought and excess rain during
Index insurance
Rainfall
Groundnut farmers
Peru
Flooding,torrential rainfall from EI Nino
Index insurance
ENSO anomalies in Pacific Ocean
Rural financial institutions
Peru
Drought
Index insurance linkes t5o lending
Area-yield production index
Cotton farmers
Senegal
Drought
Index insurance linked to area-yield insurance
Rainfall and crop yield
Smallholder farmers
Tanzania
Drought
Index insurance linked to lending
Rainfall
Smallholder maize farmers
Pilot implementation in 2007
Thailand
Drought
Index Insurance linked to lending
Rainfall
Smallholder farmers
Pilot implementation in 2007
Ukraine
Drought
Index Insurance
Rainfall
Smallholders
Implemented in 2005, currently closed due to limited sales
Vietnam
Flooding during rice harvest
Index insurance linked to lending
River level
Smallholder rice farmers
-
Source: Barrett et al., 2007
50
Pilot implementation in 2007
12. CONCLUSIONS & GOVERNMENTAL POLICY The paper has made an attempt to quantitative assessment of vulnerability to climate change and adaptation action taken by the households in the drought prone area of West Bengal. Socio-economic vulnerability assessment has been used to measure vulnerability. In terms of the socio-economic vulnerability, the village Bandhgava has been identified as the highest vulnerable among four villages. The key vulnerabilities are identified as education, health hygiene and food insufficiency. This paper has also identified the household’s adaptation options like migration; formation of Self-help Group (SHGs), water harvesting and accessibility of non-timber forest products and livestock rearing. The results of perception to climate change revealed that age of the household head; number of adult male and operational holdings have significant impact on the perception to climate change. Moreover, the analysis of factors affecting adaptation to climate change indicates that the age of the head of the households, maritial status, operational holdings, physical asset value, forestry income, temperature and family size have significant impact on adaptation to climate change. In addition, the paper describes vulnerability assessment using “Security Diagram” approach to measure drought vulnerability in India. This approach utilizes water stress and socio-economic susceptibility. Fuzzy Inference System also is used to measure drought vulnerability in India. Developmental efforts by the Government of India help to build adaptive capacity through two levels of interventions. First, climate specific interventions such as drought proofing, rainwater harvesting, campaigning awareness about available drought-resistant varieties , better access to medium / long range weather forecasts, and possibly early warning networks. Secondly, to building up broader capacity through education, access to agricultural credit, health care, and infrastructure, etc. Micro-insurance and weather indexed insurance are providing services to marginalized section of the community in the developing countries including India. For developing countries like India, adaptation requires assisting the vulnerable population during adverse climate conditions and empowering them to cope with climate risks in the long-run for better living. The Government of India implements a series of central and centrally sponsored schemes under different ministries and 51
departments for achieving social and economic development. At present, while none of the schemes is explicitly referred to as Adaptation schemes; many contain elements (objectives and targets) that clearly relate to risks from climate variability. A recent initiative by the Department of International Development (DFID) and the World Bank in India seeks to identify how to integrate adaptation and risk reduction into their portfolio of programs. The programs include National Rural water and Sanitation Program, National Elementary Education Program (Sarva Shiksa Abhiyan), National Reproductive and Child Health Program Phase II, Kolkata Urban Services for the Poor, West Bengal Support to Rural Decentralization, West Bengal Health Systems Development Initiatives, Andra Pradesh Rural Livelihoods Program, Madhya Pradesh Rural Livelihood Program, and Madhya Pradesh Urban Services for the Poor, and Western Orissa Rural Livelihood Project. Besides, the housing scheme, Indira Awas Yojana, the Food for Work Programme, and the rural road building scheme, Pradhan Mantri Grameen Sadak Yojana. These schemes have provided relief in the aftermath of floods and cyclones, enabled recovery and rebuilding, and helped improve connectivity selling produce and finding alternative employment. The key message is that Government policies, public-private partnerships, corporate and voluntary initiatives all can be meaningfully harnessed to build resilience to climate change. This paper has important policy implications for poverty, livelihood vulnerability and migration.
52
REFERENCES Alderman & Haque, 2007. Alderman, H., & Haque, T. 2007. Insurance against Covariate Shocks: The Role of Index-Based Insurance in Social Protection in Low-Income Countries of Africa. Working Paper 95. Washington DC: Africa Region Human Development Department, The World Bank. Barrett, C. B., Barnett, B. J., Carter, M. R., Chantarat, S., Hansen, J. W., Mude, A. G., Osgood, D. E., Skees, J. R., Turvey, C. G., & Ward, M. N. 2007. Poverty Traps and Climate Risk: Limitations and Opportunities of Index-Based Risk Financing. Paper prepared for the Policy Roundtable on Climate Risk, Poverty Traps and Index-Based Financing, hosted by the International Research Institute for Climate and Society, Columbia University, September. Bhattacharya S and A. Das, 2007. Vulnerability to Drought,Cyclones and Floods in India. http://www.basicproject.net/. Brooks, N., W.N. Adger, P.M. Kelly 2005. The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation.” Global Environmental Change 15(2): 151-163. Brooks, S.: 2002. ‘Climate change, vulnerability and conservation in Costa Rica: An investigation of impacts, adaptive environmental management and national adaptation networks’. Ph.D. thesis, School of Geography and the Environment, University of Oxford. Bryla & Syroka, 2007. Developing Index-based Insurance for Agriculture in Developing Countries. Sustainable Development Innovation Brief, Issue 2, Policy Integration and Analysis Branch of the Division for Sustainable Development, United Nations, March Burton, I., Huq, S., Lim, B., Pilifosova, O. & Schipper, E.L. 2002. From impact assessment to adaptation priorities: The shaping of adaptation policy. Climate Policy 2: 145–149. Byron, N. & Arnold, J.E.M. 1999. What futures for the people of the tropical forests? World Development, 27(5): 789-805.
53
Cardona, O. D. 2005. “Indicators of disaster risk and risk management: Summary Report”. Washington, D.C., Inter-American Development Bank. Esty, D.C., M. Levy, T. Srebotnjak, and A. de Sherbinin 2005. “2005 Environmental Sustainability Index: Benchmarking National Environmental Stewardship.” New Haven, CT: Yale Center for Environmental Law & Policy. Fisher, M. 2004. Household welfare and forest dependence in Southern Malawi. Environment and Development Economics vol. 9, pp. 135-154. Fu¨ssel H-M, Klein RJT 2006. Climate change vulnerability assessments: an evolution of conceptual thinking. Climate Change 75(3):301–329 Hammill P, R. Matthew and E. Mc Carter 2008. Microfinance and climate change Adaptation. IDS Bulletin Vol. 39, No. 4, Sept. 2008, pp. 113-122. Heckman, J.J. 1976. The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models, Annals of Economic and Social Measurement, 5, pp. 475-492 Huq, S., A. Rahman, M. Konate, Y. Sokona, H. Reld 2003. Mainstreaming Adaptation to Climate Change in Least Developed Countries ( LDCs), IIED, London. Ibarra & Syroka, 2006. Case Studies for Agricultural Weather Risk Management. Risk Management in Agriculture for Natural Hazards. Rome: ISMEA. International Institute for Population Sciences 2006. Ranking and mapping of districts based on Socio-economic and demographic indicators, New Delhi, India. IPCC 2007. Summary for policymakers. In: Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL. Eds. Cambridge: Cambridge University Press. pp. 1-18
54
IPCC 2007a. Summary for policy makers. Climate change 2007: The Physical Science Basis. Contribution of Working Group 1 to the Fourth assessment Report of the Intergovernmental panel for climate change, S. Solomon, D. Qin, M. manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L.Miller ( Eds), cambridge University Press, Cambridge, 18 pp. IPCC. 2001. Climate change 2001. Impacts, adaptation and vulnerability. Cambridge: Cambridge University Press. Kaly, U., L. Briguglio, H. McLeod, S. Schmall, C. Pratt, and R. Pal 1999. “Environmental vulnerability index (EVI) to summarise national environmental vulnerability profiles.” SOPAC Tech. Rep. 275. Suva, Fiji: South Pacific Applied Geoscience Commission. Kelly, P.M. & Adger, W.N. 2000. Theory and practice in assessing vulnerability to climate change and facilitating adaptation.Climatic Change 47: 325–352. Kurukulasuriya, P. and R. Mendelsohn 2006. Crop selection: adapting to climate change in Africa. CEEPA Discussion Paper No. 26. Centre for Environmental Economics and Policy in Africa. Pretoria, South Africa: University of Pretoria. L. Acosta-Michlik, F. Eierdanz, K. Kumar, F. Galli, D. Tänzler, J. Alcamo, R.J.T. Klein, S. Campe, A. Carius, and D. Krömker, 2005. How vulnerable is India to climatic stress? Measuring vulnerability to drought using the Security Diagram concept, paper presented in the Human Security and Climate Change: An International Workshop, Holmen Fjord Hotel, Asker, near Oslo, 21–23 June 2005. Linnerooth-Bayer, J., Mechler R., and Pflug G. 2005. Refocusing Disaster Aid, Science, 309:1044–1046. Lynam, T, Cunliffe, R and Mapaure, I 2004. Assessing the Importance of Woodland Landscape Locations for Both Local Communities and Conservation in Gorongosa and Muanza Districts, Sofala Province, Mozambique, Ecology and Society vol. 9 (4), art. 1.
55
Mamo, G, Sjaastad, E and Vedeld, P. 2007. Economic dependence on forest resources: A case from Dendi District, Ethiopia, Forest Policy and Economics vol. 9 (8), pp. 916927. Manuamorn, 2007.Scaling up Microinsurance: The Case of Weather Insurance for Smallholders in India. Agriculture and Rural Development Discussion Paper 36. Washington DC: The World Bank. Mertz, O., Halsnæs, K., Olesen, J.E. & Rasmussen, K.2009a. Adaptation to Climate Change in Developing Countries. Environmental Management, vol.43: pp.743 – 752. Mukherjee S. 2001. Low Quality Migration In India: The Phenomena Of Distressed Migration And Acute Urban Decay, paper presented at the 24th Iussp Conference, Salvador, Brazil, August. Munich Re NatCatSERVICE 2005.
Natural Disasters according to Country Income
Groups 1980–2004, Munich Re, Munich, Germany. Opportunity International, 2005. Weather Index Insurance, Malawi. Online Pantoja, E.2002. Microfinance and Disaster Risk Management: Experiences and Lessons Learned' Prevention Consortium Draft Final Report (July2002). Prescott-Allen, R. 2001. The Wellbeing of Nations. Washington D.C.: Island Press. Ribot, J.C. 2009. Vulnerability does not just come from the sky: Toward Multi-scale Propoor Climate Policy. In: Robin, M.& Andrew, N. (eds.). Social Dimensions of Climate Change: Equity and Vulnerability in a Warming World. Washington, DC. The World Bank. Rupa Kumar, K., A.K. Sahai, K.Krishna Kumar, S.K. Patwardhan, P.K. Mishra, J.V. Revadekar, Scheraga JD, Furlow J. 2001. From assessment to policy: lessons learned from the US national assessment. Hum Ecol Risk Assess 7:1227–1246
56
Sharma, K.C. 2001. Micro Financing through Self-Help Groups, Indian Journal of Agricultural Economics, vol. 56, No. 3, July-Sept. Sharma, R.C. 2003. Forest for poverty alleviation: Chhattisgarh experience, in Forests for PovertyReduction: Changing Role for Research, Development and Training Institutions, Sim, HC, Appanah, S and Hooda, N (Eds), FAO, Bangkok. Shougong, Z, Weichang, L, Wenming, L and Huafeng, 2003. Community forestry in mountain development: a case study in Guizhou Province, China, in Forests for Poverty Reduction: Changing Role for Research, Development and Training Institutions, Sim, HC, Appanah, S and Hooda, N (Eds), FAO, Bangkok. South Pacific Applied Geoscience Commission and United Nations Environment Programme 2005. “Building resilience in SIDS: The Environmental Vulnerability Index.” Suva, Fiji: South Pacific Applied Geoscience Commission. Trieu, V.H. 2003. Forestry for poverty reduction in Viet Nam, in Forests for Poverty Reduction:Changing Role for Research, Development and Training Institutions, Sim, HC, Appanah, S and Hooda, N (eds), FAO, Bangkok Reduction: Changing Role for Research, Development and Training Institutions, Sim, HC.. UNDP, 1990. Human Development Report 1990. New York: Oxford University Press. UNDP, 2005. Human Development Report 2005. New York: United Nations Development Programme (UNDP). Van De Vwn, W. P& Van Praag, B.M. 1981. The Demand for deductibles in Private Health Insurance: A probit model with sample selection. Journal of Econometrics 17, 229-252.
57
APPENDIX Socio-economic indicators of the households for four villages Table 7 Distribution of households by age Age( in years)
Bandhgaba
Dhansimla
Khairakure
Rangakula
≤30
4(16%)
6(24%)
5(20%)
5(20%)
31-40
11(44%)
6(24%)
5(20%)
9(36%)
41-50
7(28%)
8(32%)
7(28%)
9(36%)
51-60
1(4%)
5(20%)
7(28%)
1(4%)
Above60
2(8%)
-
1(4%)
1(4%)
Total
25(100%)
25(100%)
25(100%)
25(100%)
Source: Field Survey Table 8 Distribution of households by family size Family size
Bandhgaba
Dhansimla
Khairakure
Rangakula
Male
39(37.86%)
36(37.89%)
55(52.38%)
44(43.13%)
Female
38(36.80%)
44(46.33%)
35(33.33%)
40(39.21%)
Children
26(25.34%)
15(15.78%)
15(14.29%)
18(17.66%)
Total
103(100%)
95(100%)
103(100%)
102(100%)
Source: Field Survey Table 9 Distribution of households by land holdings Landholding (in acre)
Bandhgaba
Dhansimla
Khairakure
Rangakula
Landless
17(68%)
18(72%)
9(36%)
14(56%)
≤2
8(32%)
7(28%)
16(64%)
11(44%)
Total
25(100%)
25(100%)
25(100%)
25(100%)
Source: Field Survey Table 10 Distribution of households by sex Sex
Bandhgaba
Dhansimla
Khairakure
Rangakula
Male
21(84%)
19(76%)
19(76%)
22(88%)
Female
4(16%)
6(24%)
6(24%)
3(12%)
Total
25(100%)
25(100%)
25(100%)
25(100%)
Source: Field Survey 58
Table 11 Distribution of households by electricity facilities Electricity facility
Bandhgaba
Dhansimla
Khairakure
Rangakula
Have
17(68%)
0(0%)
0(0%)
5(20%)
Haven’t
8(32%)
25(100%)
25(100%)
20(80%)
Total
25(100%)
25(100%)
25(100%)
25(100%)
Source: Field Survey Table 12 Distribution of households by housing status Housing status
Bandhgaba
Dhansimla
Khairakure
Rangakula
Mud
25(100%)
24(96%)
25(100%)
23(92%)
Pacca
0(0%)
1(4%)
0(0%)
0(0%)
Tiles
0(0%)
0(0%)
0(0%)
2(8%)
Total
25(100%)
25(100%)
25(100%)
25(100%)
Source: Field Survey Table 13 Distribution of households by assets holding Assets
Bandhgaba
Dhansimla
Rangakula
Khairakure
Physical Assets
18(72%)
17(68%)
24(96%)
22(88%)
Livestock Assets
23(92%)
22(88%)
23(92%)
23(92%)
Land Assets
8(32%)
7(28%)
11(44%)
16(64%)
Source: Field Survey
59
Sanitation facilities
RANGACULA
KHAIRAKURA
AK U R
U LA AC
AN
IR A
H D
N DHANSIMLA
BA
BANDHGABA
KH
AB D
HG
10 0
A
% of households (No)
A
30 20
% of households (yes)
G
Illiterate
AN
Literate
120 100 80 60 40 20 0 SI M LA
60 50 40
R
80 70
% of households
% of household
100 90
Villages
Villages
100 80 60
Livestock(Yes)
40
Livestock (N0)
20
RA AK U
AC
KH AI R
RA NG
DH
BA N
AN
DH
G
SI M
UL A
LA
0
AB A
% of household
Distribution of household by livestock
Villages
A Villages
120 100 80 60 40 20 0
Water harvesting Migration NTFPs
RA
A
AK U
UL KH
AI R
AC NG RA
AN DH
DH
G
SI M
AB A
LA
SHGs
BA N
% of households
Household level adaptation
Villages
60
AK U
UL
AI R KH
NG
AN DH
AC
SI M
AB A BA N
DH
G
KH AI R
Villages
RA
No
RA
RA
Yes
AK U
AC
SI M
DH
RA NG
AN
DH BA N
UL A
LA
Climate aware(NO)
120% 100% 80% 60% 40% 20% 0%
LA
Climate aware(YES)
% of households
Health care facility by the households
120 100 80 60 40 20 0
G AB A
% of households
Climate awareness
