Quantitative cost-benefit analysis for typhoon resilient housing in Danang city, Vietnam

Quantitative cost-benefit analysis for typhoon resilient housing in Danang city, Vietnam Tran Huu Tuan a, ⇑ , Phong Tran b , Kate Hawley c , Fawad Khan d , Marcus Moench c a College of Economics, Hue University, 100 Phung Hung Street, Hue City, Vietnam b Institute for Social & Environmental Transition (ISET), No. 18, alley 1/42, Lane 1 Au Co, Tay Ho District, Hanoi, Vietnam c Institute for Social & Environmental Transition (ISET), 948 North Street, Suite 7, Boulder, CO 80304, USA d Institute for Social & Environmental Transition (ISET), Pakistan article info Article history: Received 6 March 2014 Revised 17 December 2014 Accepted 13 January 2015 Keywords: Climate change Cost-benefit analysis (CBA) Da Nang city Quantitative CBA Typhoon resilient housing Vietnam abstract Located in Central Vietnam, Da Nang city is experiencing rapid urbanization and development. In recent years, floods and storms have caused critical damage and losses to local communities and destroyed thousands of houses despite great efforts of local governments and agencies toward disaster risk reduction. Housing is one of the most vulnerable sectors to climate extremes, of which typhoons exhibit the greatest impact in comparison to other climate hazards. This paper examines the costs and benefits of applying typhoon resilient housing measures in Da Nang. The paper aims to test the hypothesis that using typhoon resilient housing has a positive economic return. The cost-benefit analysis (CBA) results show that the return on investment of typhoon resil- ient housing is positive when typhoon events occur early in the lifetime of the house, suggesting that the investment in typhoon resilient housing is economically desirable. The results from the research illustrate that positive returns exist in most of the scenarios tested, yet home owners are choosing not to make this investment. The findings have investigated the information asymmetry gap that exists between innovation and adoption and explores policy implications to reduce the gap. Ó 2015 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.uclim.2015.01.002 2212-0955/Ó 2015 Elsevier B.V. All rights reserved. ⇑ Corresponding author. Tel.: +84 54 3537432, mobile: +84 94 9819588; fax: +84 543529491. E-mail addresses: tuantranhuu@yahoo.com (T.H. Tuan), phongtran@i-s-e-t.org (P. Tran), kate@i-s-e-t.org (K. Hawley), fkhan@isetpk.org (F. Khan), moenchm@i-s-e-t.org (M. Moench). Urban Climate 12 (2015) 85–103 Contents lists available at ScienceDirect Urban Climate journal homepage: www.elsevier.com/locate/uclim 1. Introduction Housing and climate change have strong links in Vietnam; housing is considered one of the most valuable but also the most vulnerable area of local residents to climate change (MONRE, 2008; Nhu et al., 2011; Phong and Tinh, 2010). Located on the South Central Coast in the tropical storm belt, Da Nang experiences annual catas- trophes. The city is characterized by a sloped topography from west to east, with many mountain ranges, short rivers, deltas, and coastal areas, which creates a diversified ecosystem and perhaps one of the most disaster-prone regions in Vietnam. As a coastal city, Da Nang is affected by many types of climate hazards, including typhoons, floods, drought, coastline erosion, landslides, and so forth, and the risk of such hazards is increasing as a consequence of global climate change. The most dangerous hazards for Da Nang are storms (tropical lows and typhoons) and floods. The city is impacted by three to five storms per year. 1 Storms hit this city from May to December and are followed by long-lasting rains and inundation floods (ACCCRN, 2010). In recent years, strong storms and floods have caused critical damage and losses to local communities and have destroyed thousands of houses (e.g., flood in 1999, typhoon Xangsane in 2006, typhoon Nari in 2013) despite great efforts by local governments and agencies toward DRR. According to the Vietnam Central Committee for Flood and Storm Control (CCFSC), 80–90% of the population is affected by floods and storms. As reported by the national government, housing is one of the sectors most vulnerable to climate extremes (MONRE, 2008). Typhoons exhibit the greatest impact on housing as compared to other climate hazards (Nhu et al., 2011). Many studies have acknowledged the relationship between housing vulnerability and household poverty (Jones and Anh, 2010; McEntire, 2011; Wisner et al., 2004), but few studies deal with the eco- nomic aspects of climate resilient housing. This research, therefore, examines the performance of cli- mate resilient housing through an economic lens in order to analyze the costs and benefits brought by resilient housing. This paper tests the hypothesis that applying climate resilient-related principles to housing construction has a positive economic return to households in Da Nang. 2. Background People living in flood and storm affected areas in Da Nang often belong to low-income groups. A significant amount of household income is spent on housing repairs or reconstruction after annual floods and storms (Norton and Chantry, 2008). In many cases, this causes a downward spiral into pov- erty because households borrow more money than they can afford from friends, relatives, or neigh- bors, which results in further debt. In addition, without technical guidance related to storm resistant construction techniques (see CECI, 2003), they reconstruct their homes using the same con- struction principles, thus reproducing vulnerabilities. In Vietnam after the Reform (Ðổimới) policy in 1986, households began to use new materials (cement blocks, steel bars, fired bricks, or corrugated sheeting) in their housing construction instead of traditional materials (timber, bamboo; (Norton and Chantry, 2008) but frequently without safety- related measures (Tinh et al., 2011). This failure has generated a so-called twofold source of vulnera- bility (Norton and Chantry, 2008). Over 70% of houses built during this period did not incorporate typhoon resistant features; flat roofs were constructed, limited attachments between building ele- ments were implemented, and structural bracings were lacking (Norton and Chantry, 2008). In addi- tion, houses in low-lying areas lack flood protection features; for example, they lack upper floors for safekeeping valuables during floods or have hard and heavy roofs that are difficult to open for escape. Literature review shows that there are not many studies done in the field of climate resilient hous- ing regarding economic dimensions. Pompe and Rinehart (2008) addressed the link between hurricane resistant construction and the role of the insurance system, where appropriate insurance measures could reduce people’s vulnerabilities to disasters. Sutter et al. (2009) talked about the reduction of 1 A storm with a wind speed of 118 kph (Category 12 on the Beaufort scale) is called a typhoon. 86 T.H. Tuan et al. /Urban Climate 12 (2015) 85–103 insured losses by applying disaster-mitigating measures in fragile buildings. Their studies found a positive net present value of safe construction in high-risk areas to natural disasters. However, there is an absence of the clear assumptions used for the economic return of utilizing climate resilient strat- egies. Thomas et al. (2010) conducted a study of Vietnam related to analyzing the impact of natural disasters on household welfare. In the area of cost-benefit analysis (CBA), Pearce et al. (2006) published a book of CBA with a focus on the calculation of losses and gains from an event or intervention. A more comprehensive approach is discussed in Boardman et al. (2011). Their approach is helpful in that it provides a tool to estimate and compare costs and benefits before moving forward with decision making. With regard to applying CBA in disaster risk management, several papers have addressed and evaluated the economic effi- ciency of different disaster risk interventions (Hochrainer et al., 2011; Kull et al., 2013; Mechler, 2005; Moench et al., 2009). However, none of these studies addressed typhoon resilient housing as an intervention strategy for disaster risk management. This paper investigates the economic return of typhoon resilient housing in Da Nang city, Vietnam. It is structured as follows. Section three highlights the study site, typhoon hazards, past impacts in the study site, and sampling framework for the household survey. Section four identifies typhoon resilient housing for CBA and its associated costs and benefits, provides analysis frameworks, and details related key assumptions. Section five discusses CBA results, scope, and limitations. Finally, section six presents conclusions and policy implications. 3. The study site 3.1. Da Nang city Located on the South Central Coast and on the tropical storm bell, Da Nang city experiences the largest annual catastrophes in Vietnam. Da Nang is characterized by aslope topography from west to east, with many mountainous ranges, short rivers, deltas, and coastal areas, which create a diver- sified ecosystem and perhaps one of the most disaster prone regions in Vietnam (ACCCRN, 2010). Da Nang is the most dynamically developed city in Central Vietnam, where both economic devel- opment and urbanization are occurring rapidly. The city’s gross domestic product is the highest in the country at just over 11% in recent years (Cu, 2008). The population of the city is nearly 1 million, with the average density at 721 persons per square kilometer. The annual population growth rate in Da Nang is 3.48%, with the population expected to reach 1.2 million in 2020 and 1.5 million in 2030. This uncontrolled population boom along with a high rate of unemployment are big challenges in Da Nang that contribute to an increase in climate risks and vulnerability (Da Nang UPI, 2012). 3.2. Typhoon hazards and impacts in Da Nang Surrounded by mountains, Da Nang is not only prone to the effects of typhoons but is also at risk from floods. These challenges, together with other natural hazards such as drought, high tides, coastal erosion, salinization, and landslides, are major concerns for city residents and local authorities and are likely to be exacerbated by climate change (ACCCRN, 2010). Of these natural hazards, the most dan- gerous climate hazard in Da Nang is typhoons. From 1997 to 2011, there were 25 typhoons and 39 floods, which killed 206 people, injured thousands, and caused 15,410 houses to collapse (Da Nang CFSC, 2012). Global climate change contributes to higher intensity typhoons (IMHEN, 2013). It is assumed that typhoon trends will become more abnormal and unpredictable. Approximately 40% of households in Da Nang are affected when a typhoon occurs. Those most affected are people living in coastal areas, particularly the poor, women, and children. Other highly impacted groups are fishermen and farmers (ACCCRN, 2010; Da Nang People’s Committee, 2011). Housing damage is not only caused by climate hazards, but also by inappropriate housing solutions and poor construction techniques. There are several barriers to safe housing construction in Da Nang, including the additional costs of disaster resistant measures; limited awareness by home owners; T.H. Tuan et al. /Urban Climate 12 (2015) 85–103 87 social pressures on owners to build more rooms or more living space for larger families; limited finan- cial capacity or insufficient money to build; and limited professional and technical assistance in typhoon resistant housing. Adverse effects of existing patterns of typhoons already greatly impact the housing sector and local livelihoods; such impacts will worsen as climate change makes the area more vulnerable. 3.3. Damage by typhoons Xangsane (2006) and Ketsana (2009) in study wards Xangsane was the strongest typhoon to hit Da Nang city in 40 years. More than 15,000 people were evacuated to safe havens such as schools, hospitals, and government offices. In total, there were 14,138 totally collapsed houses and 107,962 unroofed and badly ruined houses (Da Nang CFSC, 2012). Typhoon Ketsana hit Da Nang on October 2, 2009, with storm winds that reached a 9-to-10 magnitude. According to city statistics, there were 283 totally collapsed houses and 6396 unroofed and ruined houses (Da Nang CFSC, 2012). Fig. 1 shows the study area locations of the surveyed households. In order to select study wards that are representative of the city in terms of vulnerability to typhoons, several shared learning dia- logues (SLDs) with local authorities and experts were organized in Da Nang city. Based on the SLDs’ results, three wards were selected for household surveys to collect information about housing damage due to the 2006 and 2009 typhoons: Man Thai (Son Tra district), Hoa Quy (Ngu Hanh Son district), and Hoa Hiep Bac (Lien Chieu district). Hoa Hiep Bac and Man Thai are representative of wards located in coastal areas, which were directly impacted by typhoon winds. Hoa Quy is located in a low-lying area of Da Nang city, which is often affected by typhoons and floods. For these selected wards, damage to houses caused by typhoons Xangsane and Ketsana are reported in Table 1. Fig. 1. Map of Da Nang city and the study wards. Source: ISET-international, based on Da Nang Department of Construction’s geographical information system database. 88 T.H. Tuan et al. /Urban Climate 12 (2015) 85–103 Figures from Table 1 reveal that housing damage caused by typhoon Ketsana was significantly less as compared to housing damage caused by Xangsane. There are several reasons explaining for this difference. The first reason is due to the 2006 typhoon is significant stronger than that of the 2009 event (i.e. the typhoon in 2006 with Category 11 to 12 on the Beaufort scale vs. Category 9 to 10 for the 2009 event). The second reason is due to fast economic growth in local economy and households have more resources for investing in housing construction. The third reason is that local people have experienced significant damage during the 2006 event, thus they become more aware of the importance of building houses using typhoon resistant techniques. Since Xangsane in 2006, local communities in Da Nang have become more aware of the importance of building houses using typhoon resistant techniques. In effect, autonomous adaptation has occurred. However, poor and lower income households are not necessarily adapting autonomously without incentives from the government. 3.4. Sampling framework for the household survey Based on the secondary data on households’ damage by the 2006 Xangsane and 2009 Ketsana typhoons, 120 households were selected in the study wards for the final household survey sample. Based on the literature review and focus group discussions (i.e., SLDs), questionnaires were designed and pre-tested with 20 households in order to guarantee that all questions were answerable and all information was available to respondents. The questionnaire included four main sections. The first section was designed to collect demographic information and household economic condition of respondents. The second section was developed to collect the current status of house and household’s fragility. The third section was developed with questions related to household’s impacts and damages due to past typhoon events. The fourth section was used to collect information about typhoon knowl- edge and response. In the final survey, 98 questionnaires were completed with face-to-face interviews conducted dur- ing May and June of 2013. The distribution of household samples followed the sampling design (Table 2), and households that participated in the final survey were randomly selected in the study areas based on the list of households affected by the Xangsane (2006) and Ketsana (2009) typhoons. To increase the validity and accuracy of the data collected, 10 percent of completed questionnaires were randomly selected for doing re-interviews and cross-checks. The questionnaires completed each day were carefully checked to make sure that information was recorded in the correct manner. Finally, these questionnaires were entered in data analysis software for data cleaning and analysis. It is noted that this household survey contained at least two important limitations. The first limi- tation was that the respondents may have thought they could influence policy in favor of resilience by overstating the damage costs. The second limitation was the issue of recall bias because information Table 1 Damage by typhoons Xangsane and Ketsana in study wards. Housing damage Hoa Quy Man Thai Hoa Hiep Bac Damage by typhoon Xangsane in 2006 Number of houses totally collapsed 50 184 720 Number of houses with roof totally blown 236 584 658 Number of houses partly collapsed 73 – a 50 Number of houses with roof partly blown 1780 1107 1203 Damage by typhoon Ketsana in 2009 Number of houses totally collapsed 6 1 6 Number of houses with roof totally blown 28 7 156 Number of houses partly collapsed 14 3 – b Number of houses with roof partly blown 135 83 393 Note: Figures were pulled from Hoa Quy, Man Thai, and Hoa Hiep Bac wards’ reports on socio-economics. a The number of houses partly collapsed and the number of houses with roof totally blown by typhoon Xangsane in Man Thai ward were not provided as separate figures. b The number of houses partly collapsed and the number of houses with roof totally blown by typhoon Ketsana in Hoa Hiep Bac ward were not provided as separate figures. T.H. Tuan et al. /Urban Climate 12 (2015) 85–103 89 about household’s damages and losses were occurred several years in the past. To reduce these biases, during the interview we cross-checked their reported damage data against secondary damage data provided by the local authorities. 3.5. Estimation of total damage per household The household survey aimed to collect direct and indirect loss information. 2 Direct monetary losses included the structural and asset damages incurred by the household due to the typhoon. Indirect mon- etary losses included those costs that were incurred due to the disaster, but did not include damaged items. These costs included the number of working days lost due to spending time on repairing or recon- structing homes or temporarily staying in other houses; fees paid for medical treatment for injured peo- ple, if any; and the cost of hiring local builders and purchasing materials for housing repairs or reconstruction (see Table 3). Average household damage estimates due to typhoons Xangsane in 2006 and Ketsana in 2009 are reported in Table 4. Total damage per household is VND 42,812 3 million and VND 35,382 million for Xangsane and Ketsana, respectively. These were the damage figures in 2006 and 2009. However, in order to take into account the inflation of past years, it is reasonable to convert these figures using yearly infla- tion rates (CIA World Fact Book, 2011). The total damages in 2012 figures are reported in column 3 of Table 4. Results of the household survey show that the floor space of a typical house in 2006 was about 50 m 2 but was 81 m 2 in 2012 as living standards in the study site have improved over time. The figures have been adjusted to a standard house in 2012, as shown in column 4 of Table 4. Table 2 Sampling of the household survey by typhoons and wards. Typhoon Ward Total Hoa Quy Man Thai Hoa Hiep Bac Xangsane, 2006 7 15 38 60 Ketsana, 2009 9 23 6 38 Total 16 38 44 98 Note: Data based on 2013 survey of 98 households. Table 4 Total damage per house (in units of VND 1000). Typhoon Total damage Total damage in 2012 Total damage per standardized house Xangsane, 2006 42,812.16 74,701.10 121,015.79 Ketsana, 2009 35,382.18 60,167.40 85,437.70 2 This study does not include certain types of costs, such as the cost of deaths or injuries or the cost of social disruptions within a group or community. Typhoons lead to critical social disruptions, human causalities, and so forth, but due to the difficulty of quantifying these economic costs, the study does not include them in the overall analysis. Table 3 Quantifiable disaster impacts in monetary terms. Direct Indirect Housing partially damaged or totally destroyed Working days lost Evacuation costs Household assets damaged Health and medical fees Cost of hiring local builders Cost of purchasing materials for housing repair or reconstruction 3 The exchange rate is VND20.080/US$1. 90 T.H. Tuan et al. /Urban Climate 12 (2015) 85–103 4. Cost-benefit analysis Cost-benefit analysis (CBA) is an established tool for determining the economic efficiency of devel- opment interventions. CBA compares the costs of conducting such projects with their benefits and cal- culates the net benefits, or economic efficiency (Kull et al., 2013). 4.1. Identification of typhoon resilient housing for CBA and Its associated costs and benefits To apply CBA for typhoon resilient housing, it is necessary to define what forms of resilient housing can be used for CBA. To do this, this study uses the results of the architectural housing design compe- tition (details of the design competition’s results can be found in Anh and Phong, 2013; Thang et al., 2013). Objectives of the design competition are to identify housing design elements that will signifi- cantly reduce current typhoon and intermediate-term (30 years) climate risk. Main characteristics of typhoon resilient housing include (i) Interconnection of all key structural components in the house structure; (ii) Anchoring of roofing materials, particularly lighter ones made of corrugated iron with roof angles designed to deflect wind and reduced eves; (iii) Increasing wall thickness from the 10 cm common in low-income housing to a minimum of 15 cm (25 cm being stan- dard in housing constructed for more wealthy residents) with air pockets to improve thermal perfor- mance; (iv) Inclusion of a reinforced concrete ring beam at window level – mid way up most walls; (v) Strategic placement of concrete pillars to strengthen walls; (vi) Establishment of safe rooms within houses in case walls fail; and (vii) Avoidance of courtyards, verandas, setback entryways and other features that concentrate wind pressures differentially. 4.1.1. Assessment of benefits In a conventional CBA of investment projects, benefits are the additional outcomes generated by the intervention project (e.g., resilient housing measures) as compared with the situation without the project. In the disaster risk reduction case, benefits are the risks that are reduced or avoided (Mechler, 2005). Benefits of resilient housing measures are defined as the avoided damage and loss or the accrued benefits following the adoption and implementation of resilient housing measures. Avoided damage (benefits) is the difference in damages and losses under two circumstances: with and without undertaking the resilient housing measures. It is noted that this study does not include certain types of costs, such as the cost of deaths or inju- ries or the cost of social disruptions within a group or community. Typhoons lead to critical social dis- ruptions, human causalities, and so forth, but due to the difficulty of quantifying these economic costs, the study does not include them in the overall analysis. In addition, as mentioned by some focus group discussion’s participants that the most benefit of a resilient house is adding peace of mind during the typhoon season; building a resilience house could also bring in some socio-economic benefits to the owner such as he/she is proud of new house and easier to access credits and loans. These benefits can be considered as non-monetary ones and difficult to measure. This study mainly focuses on financial benefits of resilient house. 4.1.2. Assessment of costs Associated costs of a resilient house include (1) major investment cost for building a resilient house (construction cost) and (2) operation and maintenance expenses for the house incurred over time (O&M cost). The study focuses on the extra costs incurred by a standard non-storm-resistant house as compared to a storm resistant house. Finally, economic efficiency is assessed by comparing benefits and costs. Three economic instru- ments were used to measure the overall economic returns to resilient housing. They include (1) net present value (NPV), (2) benefit-cost ratio (BCR), and (3) internal rate of return (IRR). 4 4 For further explanation of these terms, see Appendix C. T.H. Tuan et al. /Urban Climate 12 (2015) 85–103 91 4.2. Analysis frameworks In this study, a combined backward- and forward-looking approach for cost-benefit analysis was applied to assess current and future typhoon risk. Review of past typhoon impacts provided estimates for current risk, while projected climate and exposure changes were used to estimate risk for the per- iod 2012 to 2030. 4.2.1. Backward-looking analysis Typhoon damage and loss due to the 2006 Xangsane and 2009 Ketsana typhoons were estimated using household surveys. The household surveys yielded direct loss information (direct damage) and indirect loss information (indirect damage) for housing, as seen in Table 3. As cost-benefit analysis must be performed under present conditions, losses (damages) from past typhoons in 2006 and 2009 were adapted to present conditions using yearly inflation rates as an adjustment factor to con- vert these amounts into 2012 Vietnamese Dong (VND). By utilizing this backward-looking approach, we are able to identify what damages an average household experienced in both the 2006 and 2009 typhoons and use this information to build the forward-looking analysis. 4.2.2. Forward-looking analysis The present value of the benefits from resilient housing are likely to be highly sensitive to the expected timing of the typhoon events that would cause damage, yet these typhoon events are sto- chastic, or random to climate change. The results of typhoon modeling are, so far, mixed at best. Thus, it is not possible to add probabilities to different intensities of typhoons. Moreover, the damage caused is related to the wind speed and direction, and it is difficult to correlate wind speed, damages, and return periods for typhoons (see Khan et al., 2012). Therefore, the study utilized a scenarios approach to investigate the future economic impacts of typhoons in Da Nang city. Specifically, the research investigated two scenarios: (1) Without climate change and (2) With climate change. 4.2.2.1. Without climate change. In this scenario, climate stays generally the same. This implies that the frequency and intensity of typhoons in the next 25 years will be similar to the frequency and intensity of typhoons over the past 25 years. 5 In other words, the 2006 Xangsane and 2009 Ketsana typhoons will be repeated once each over the next 25 years. 4.2.2.2. With climate change. This scenario is based on the assumption that in the future fewer but more intense typhoons will likely occur in the region, as suggested by IMHEN (2013). More intensity may lead to greater damage. 6 In this regard, we assume that two typhoons like the 2006 Xangsane typhoon will happen in the next 25 years. Using this assumption, we recalculate the avoided damages and estimate benefit-cost ratios, and compare the results with the ‘‘Without Climate Change” scenario. Each climate scenario is then run with typhoon events occurring at different time periods over the lifetime of the house. This ensures a complete view of what the overall economic returns will be in a range of occurrences and extreme cases. The first run was chosen with the assumption that there is equal probability that any of these events could occur over the lifetime of the house. Hence, this is a simplistic Monte Carlo simulation in which the past is represented in the future evenly distributing the benefits over the lifetime of the house. In effect, the probability of the event happening in any year is equal. However, in reality events do not occur in that manner (Dobes, 2010). Whether they happen earlier or later in the life of the investment has a big impact on the returns to the risk reduction invest- ment. 7 To show the ranges of potential returns, extreme scenarios were chosen for the beginning of the project or the end of the project, resulting in a range of benefit-cost ratios, as might be expected. 5 This is a conservative assumption as the fact is that there are many typhoons that happened in Da Nang in the last 25 years, but these two typhoons are happened in recent years with significant damage to communities in Da Nang. For example, during the period between 1976 and 2011 (36 years), there have been 59 storms and tropical low pressure storms that affect Da Nang, or about 1.6 storms and tropical low pressure storms occurring annually (Da Nang Hydro-Meteorological Station, 2012). 6 This is not a linear relationship. 7 Any loss that happens later in the life of the investment accounts for a small benefit. 92 T.H. Tuan et al. /Urban Climate 12 (2015) 85–103 4.3. Key assumptions Review of the risk analysis has identified a number of key assumptions driving the cost-benefit analysis design and results, as summarized in Table 5. 8 4.4. Sensitivity analysis A sensitivity analysis was performed on a range of discount rates due to the fact that these rates often vary among institutions and by year. In economic calculations, future benefits are discounted in relation to current benefits to reflect the cost of capital. This is justified on the assumption that the current value of future benefits from invest- ments should be compared to existing, secure investment alternatives for the same funds. Applying high discount rates expresses a strong preference for the present while potentially shifting large bur- dens to future generations. Standard practice in developing countries is to assume a discount rate of 10–12%. In this study, the discount rate of 10% is the common base for a CBA study, as widely cited in the existing literature (Truong, 2011; Tuan and Navrud, 2008). A range of discount rates from 5% to 15% was used for the sensitivity analysis. The discount rate of 5% was used because housing is a social welfare development program, with its effect mainly seen in the long term. The discount rate of 15% was used to describe a context of economic crisis. 5. Results and discussions 5.1. The CBA’s results In this section, the CBA (measured by NPV, IRR, and BCR) is assessed and the results compared. 5.1.1. Scenario 1: Without climate change With this assumption, the NPV, IRR, and BCR are calculated using typhoon events occurring at dif- ferent time periods over the lifetime of the house. The first option (i.e., the base case) was chosen with the assumption that there is equal probability that either of these two typhoon events could occur over the lifetime of the house (i.e., the probability of an event happening in any year is equal). Results of the base case (reported in Table 6) show that NPV is >0, BCR is >1, and IRR is >10% (i.e., market discount rate). This implies that the economic return on investment in typhoon resilient housing is desirable. It should be noted that this is a conservative result/estimate based on the assumption that only two typhoons occurred in the past 25 years. 9 Table 5 Key assumptions driving the cost-benefit analysis. Assumption Value Notes (sources) Construction costs per house 68,937.11 (VND 1000) Additional cost of resilient housing; cost of resilient housing minus cost of nonresilient housing per house (calculation based on the results of housing design competition) Lifetime of house 25 years Using market rate based on market lending rate in 2012 Discount rate 10% Market discount rate in 2012 Annual asset growth 2.46% per year Annual increase in exposure of household assets (authors’ calculation) Operation and maintenance (O&M) costs 2% per 5 years An increase in additional cost for housing resilience; occurs every 5 years Economic depreciation 2757.48 (VND 1000) Straight line economic depreciation method used; this refers to the allocation of the cost of housing assets to periods in which the assets are used (not the decrease in value of assets) 8 For further details, see Appendix C. 9 As discussed in footnote 3, many more typhoons have occurred in the past 25 years. T.H. Tuan et al. /Urban Climate 12 (2015) 85–103 93 Results show that if the typhoons happen very early in the project lifetime (particularly if the 2006 event happens in year 1 and the 2009 event happens in year 3 10 ), the returns are optimal (the best case). Conversely, if the typhoons happen very late in the project lifetime (the 2006 event happens in year 25 and the 2009 event happens in year 23), the results are the worst (the worst case). This implies that any loss happening later in the lifetime of the investment has a small benefit. In the base case, the results shows that IRR equals 14% (i.e., higher than the market discount rate of 10%), which implies that it is preferable to invest in resilient housing rather than the bank. The best case takes place when the typhoons happen very early in the project lifetime, and this seems to be somewhat reflected by recent typhoon Nari, 11 which struck Da Nang in mid-October 2013. It is critical to investigate at what point during the lifetime of the house the turning point or break- even point occurs (break-even case: from a positive NPV to a negative one). The analysis results show that the break-even case occurs if the 2006 event happens in year 16 and the 2009 event happens in year 18 (see Fig. 2). This means that if the 2006 event occurs after year 17 and the 2009 event occurs after year 19 of the project lifetime, the NPV becomes negative. Varying interest rates were used to test the sensitivity of the results. Fig. 3 shows the full range, from interest rate equals 5% to interest rate equals 15%; BCR results range from 2.99 to 1.38, respectively. 5.1.2. Scenario 2: With climate change As stated earlier, the ‘‘With Climate Change” scenario increases the amount of damage that occurs over the lifetime of the house. In other words, we assume that the 2006 typhoon (Category 12) may occur twice in the next 25 years. 12 The return on investment in typhoon resilient housing is reported in Table 7. Results of Scenario 2 show that the base case IRR is 20% (compared to 14% in Scenario 1), the BCRs for the sensitivity analysis range from 3.65 to 1.69 as seen in Fig. 4 (compared to 2.99 to 1.38 in Table 6 Calculation of the economic return without climate change. Base case Best case Worst case NPV (VND 1000) 66,069.35 152,941.30 À35,218.32 NPV (US$) 3290.31 7616.60 À1753.90 IRR (%) 14 132 5 BCR 1.93 3.15 0.50 10 We assume that it takes 1 year for housing reconstruction. 11 Typhoon Nari (typhoon No. 11) hit Da Nang city at midnight on October 14, 2013, with level 12 winds and level 13 gusts, equivalent to 130 km/h. (50,000) 0 50,000 1,00,000 1,50,000 2,00,000 0 5 10 15 20 25 N P V Years NPV Fig. 2. The break-even case. 12 Again, this is a conservative assumption. 94 T.H. Tuan et al. /Urban Climate 12 (2015) 85–103 [...]... of housing may not be resilient if there are typhoons of stronger intensity13 in the future 5.2.5 The cost of typhoon resilient housing is case specific The cost of typhoon resilient housing was estimated based on the winning model in the architectural design competition and is, therefore, case specific Even though this housing model was considered the best representative of typhoon resilient housing for. .. metal wall covering length 6 2 m Plastering outside walls, 1.5 cm thick, mortar cement grade 75 Flooring, ceramic floor tile, 400 Â 400 mm Reinforced foundation, reinforcement diameter 6 10 mm Reinforced foundation, reinforcement diameter 6 18 mm Reinforced columns, reinforced cylinder diameter 6 10 mm, height 6 4m Reinforced columns, reinforced cylinder diameter 6 18 mm, height 6 4 m Reinforcement steel... metal wall covering length 6 2 m Plastering outside walls, 1.5 cm thick, mortar cement grade 75 Flooring, ceramic floor tile 400 Â 400 mm Reinforced foundation, reinforcement diameter 6 10 mm Reinforced foundation, reinforcement diameter 6 18 mm Reinforced columns, reinforced cylinder diameter 6 10 mm, height 6 4 m Reinforced columns, reinforced cylinder diameter 6 18 mm, height 6 4 m Reinforcement, steel... Implications for public policy 6.2.2.1 Encouraging individual investment The quantitative CBA results show that typhoon resilient housing exhibits high benefit-cost ratios In order to encourage individual investment in typhoon resilient housing, the government should consider offering assistance to households that agree to undertake appropriate climate resilient housing measures This may take the form of... improvement in recent years, with more durable and costly materials being used in housing repair and construction instead of traditional materials However, a lack of guidance and instruction from professionals and authorities has resulted in housing that is more vulnerable to flooding and typhoons Results of the quantitative CBA show that the returns on investment in typhoon resilient housing are high in most... regulations (in the form of building permits) would help to create an enabling environment for resilience and enforce a resilient housing system in Vietnam into the future 14 For example, super -typhoon Haiyan (which reached Beaufort level 17) was forecasted to approach Central Vietnam in November 2013 99 T.H Tuan et al / Urban Climate 12 (2015) 85–103 Appendix A A.1 Estimated costs of a non -resilient. .. build resilient housing and plan for long-term development, and homeowners need better information about resilient housing options and their benefits 6.2.2.5 Bridging the gap between at-risk groups and in- field professionals Vulnerable communities in the study, such as the poor and low-income groups, experience economic constraints that hinder accessibility to professional services for better housing design... to the implications for public sector interventions 6.2.1 Implications for individual households The returns on typhoon resilient housing investments are positive and high, implying that local households prioritize this investment However, it should be emphasized that positive returns are a necessary but not sufficient condition to justify investment in typhoon resilient housing Individual households... cost of resilient housing This is the difference in the cost of resilient housing and the cost of non -resilient housing with the same floor area and at 2012 prices T.H Tuan et al / Urban Climate 12 (2015) 85–103 101 Based on the results of the design competition, the costs of resilient housing and that of non -resilient housing are calculated (see details in Appendices A and B) C.2 Operation and maintenance... not take into account typhoon resilience, and it is essential to include the issue of typhoon resilience in this program in order to increase housing resilience for the poor 6.2.2.2 Micro-insurance policy Micro-insurance mechanisms have been viewed as an efficient and reliable risk management tool for encouraging households in developing countries to adopt disaster risk reduction measures (Linnerooth-Bayer . of typhoon resilient housing for CBA and Its associated costs and benefits To apply CBA for typhoon resilient housing, it is necessary to define what forms of resilient housing can be used for. resulted in housing that is more vulnerable to flooding and typhoons. Results of the quantitative CBA show that the returns on investment in typhoon resilient housing are high in most scenarios, meaning. low-income housing to a minimum of 15 cm (25 cm being stan- dard in housing constructed for more wealthy residents) with air pockets to improve thermal perfor- mance; (iv) Inclusion of a reinforced