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Characterizing situations in ASEAN cities: Using the Human Security Index
City, Culture and Society xxx (2015) xxx–xxx
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Characterizing situations in ASEAN cities: Using the Human Security Index David A. Hastings a,⇑, Venkatesh Raghavan b a b
Human Security Index, United States Osaka City University, Japan
a r t i c l e
i n f o
Article history: Received 26 September 2013 Received in revised form date 10 April 2014 Accepted 3 May 2014 Available online xxxx Keywords: Human security Well-being Indicator ASEAN Cities Communities
a b s t r a c t The Human Security Index discussed in Hastings (2013a, this issue) can help assess situations and strategize (1) improved and fair competitiveness, (2) benefits from regional cooperation, and (3) improved individual and community well-being. ASEAN countries are compared here with global peers, and with each other – with respect to well-being situations in their cities and other communities. ASEAN leaders tend to lag some of their global peers in delivery of Human Security and well-being – where lowerincome ASEAN countries tend to slightly lead their global peers in such outcomes. Further, a prototype HSI for Thailand is presented and discussed for situations in its cities and their surrounding territories. City-provincial situations are seen to be highly diverse, with some relatively poor (in monetary income) provinces leading in home ownership and other factors in Human Security. Formulation of HSIs for additional ASEAN countries, preferably at district-town levels, will likely increase our understandings of the concept and situations of well-being versus vulnerability in cities of such countries. Such exercises could lead to evolving better strategies for national – including urban – development planning and also help monitoring impacts of sustainable development initiatives. Published by Elsevier Ltd.
Introduction How to characterize the well-being, quality-of-life, and resilience potential versus vulnerability of cities, in the context of other communities such as countries, provinces surrounding – and dependent on – cities, and socio-economic groupings within cities? Considering the significant improvements in quantitative measurements and other indicators, on various aspects of the human condition at national and sub-national level, can we make progress in quantifying such issues? If so, we may be able to make progress in our understandings of causes, influences, and making progress on well-being – at national to local levels. The Human Security Index was designed to help address such issues. The Global HSI (Hastings, 2008, 2009b, 2011a, 2013a) has been used to discuss the concept and measurement of Human Security, and as a framework for assessing the well-being versus vulnerabilities of communities ⇑ Corresponding author. E-mail addresses: [email protected] (D.A. Hastings), raghavan@ media.osaka-cu.ac.jp (V. Raghavan).
around the world. A prototype county-level HSI for the USA (Hastings, 2011b) is being used for similar purposes at a local level for a country generally considered to be highly developed, but which some have argued (and the global HSI appears to perceive) may not be so highly developed at present. The Global HSI and a prototype for Thailand have been used to explore scenarios for supporting communities against possible stresses as ASEAN pursues greater global integration (ASEAN, 2008, 2009). This paper builds on that effort – focusing more on the situation of communities in ASEAN and Thailand, than on ASEAN integration. Community situations can better be detected, thanks to improving diversity and perceptiveness of data and indicators at national and local resolutions, and also benefiting from advances in spatial and thematic analytical tools. Besides a R&D effort in indicator formulation (see Hastings, 2013a – this issue), the HSI is an ongoing engagement in design, formulation, refinement, awareness, and use of such a development indicator. Engagements have included individuals, video-workshops, conferences, publications and Web modalities (HumanSecurityIndex.org,
http://dx.doi.org/10.1016/j.ccs.2014.05.005 1877-9166/Published by Elsevier Ltd.
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ResilienceSystem.org and elsewhere). Evolving issues include: How to be more perceptive, yet more geographically comprehensive than many legacy indicators? How to benefit from – and support – data, indicators, and other contributions made by intergovernmental, civil society, and academic-governmental-private organizations – while mitigating sensitivity to imperfections in data or process? How to successfully harmonize left–right, east–west and north–south political-social-cultural sensitivities – to focus on societal and governance deliveries & tangible outcomes? How to make the indicator perceptive and comprehensive, but also understandable and used? How to structure data management, results, and documentation to facilitate adding more data, selective deletion of components, rescaling and re-weighting inputs to create localized HSI? How to use differing sub-national and global data types to, nevertheless, perceive economic, environmental, and social situations among communities? How to strengthen such processes by incorporating contemporary methodologies such as video conferencing, thematic analysis tools (spreadsheets, etc.), spatial analysis tools (geographical information systems, etc.), Web design and tools? How to optimize use of open-source tools, to facilitate adoption and use by anyone? The HSI has received diverse engagements, including on its use as a tool for improving assessments of socio-economic and environmental situations, enhancing development strategies and programmes, and strengthening the monitoring of same. One example inadequately detailed in published media, Exercise24 (Giasson, 2010; Wired; 2010) prototyped responses to a simulated earthquake near San Diego, integrating a dashboard including HSI
indicators for Mexico and southern Californian counties, crowdsourcing, and other knowledge management approaches. In another (Salinas, Shah, Abdelbary, Gay, and Saxton, 2012) the HSI has been used to assess the cumulative health risk burden in the USA State of Texas, at the county level. That study considered that application of the HSI to the assessment ‘‘provides a fuller and more nuanced understanding of socioeconomic and environmental conditions, and increases awareness of the role played by environmental, economic, and social factors in observed health disparities by race/ethnicity and geographic region” (Salinas et al., 2012, p.1831). Human Security situations are thought to result from any combination of: Innate resources and environment, Outcomes inherited from past social situations and governance, Outcomes resulting from current social situations and governance, and/or Outcomes resulting from thoughts, (in)actions and uncertainties about the future. Combining these with current social situations, policies and programmes, one may prudently use the HSI to help forecast future situations, as has been prototyped by Hastings (2013b, 2013c). In that assessment, countries/ economies/societies have tentatively been grouped into six clusters, each with somewhat similar situations which might influence their futures. Those clusters are: 1. Advancing, relatively wealthy countries: Norway, Australia, and Canada. 2. Advancing, moderate income countries: Indonesia, Malaysia, Thailand, and Viet Nam. 3. Advancing, lower income countries: Cambodia, Lao PDR, and Philippines. 4. High trade surplus or sovereign wealth funds: Brunei Darussalam and Singapore.
including including including including
Table 1 Human security index for ASEAN and selected comparator socio-economies. HSI*
Country
EconFI
EnvFI
SFI
HSI
Country
EconFI
EnvFI
SFI
.865|1 .842|4 .772|20 .754|26 .753|28 .753|29 .744|31 .743|32 .739|34 .732|41 .726|46 .726|47 .722|53 .712|63 .693|75 .671|91 .670|92 .668|93 .660|98 .650|100 .648|103 .646|106
Falkland Islands Norway Taiwan Czech Republic Hong Kong SAR Germany Australia New Zealand Japan Dominica French Polynesia Singapore Canada Korea, Rep. Chile Brunei Darussalam Costa Rica Greece Malaysia Oman Thailand Botswana
.924|6 .877|15 .858|20 .795|42 .733|68 .744|61 .733|67 .760|53 .795|41 .711|81 .820|32 .844|23 .756|54 .835|28 .646|118 .925|5 .614|133 .676|101 .740|65 .811|35 .688|92 .671|102
.815|1 .746|16 .666|78 .697|51 .695|53 .671|73 .665|80 .622|119 .658|92 .750|15 .640|105 .583|149 .595|141 .595|140 .725|29 .400|228 .703|41 .621|121 .552|161 .448|214 .680|63 .637|108
.857|9 .902|1 .793|31 .771|39 .831|16 .844|12 .835|15 .847|10 .764|42 .735|66 .718|75 .750|53 .817|24 .707|81 .710|78 .689|88 .694|85 .708|80 .688|89 .692|86 .576|150 .630|119
.640|112 .633|115 .626|120 .623 .609|133 .608|135 .597|147 .586|152 .586|155 .585|158 .584|159 .562|166 .559|170 .551|172 .535|179 .512|181 .499|189 .492|192 .488|195 .487|196 .336|231 .296|232
Bhutan Israel Median China Mean Values United Arab Emirates Mongolia USA Viet Nam Sri Lanka Turkey Indonesia Lao PDR India Ghana Philippines Myanmar Pakistan Bangladesh Cambodia Nepal Afghanistan Somalia
.612|134 .777|47 .685|97 .634 .793|43 .622|131 .602|140 .536|167 .575|150 .609|135 .638|125 .534|169 .656|111 .466|187 .563|156 .512|178 .606|137 .520|173 .439|199 .403|214 .305|227 .274|228
.713|35 .506|187 .598|137 .608 .306|231 .587|145 .518|179 .614|125 .674|69 .589|143 .540|164 .647|98 .521|176 .584|147 .514|180 .622|118 .502|192 .513|181 .532|171 .636|111 .522|175 .441|218
.593|141 .617|128 .594|140 .626 .729|69 .615|130 .662|99 .608|133 .508|180 .557|159 .573|151 .506|182 .500|183 .602|138 .530|170 .401|215 .391|219 .442|204 .494187 .422|209 .180|231 .172|232
* In each column but ‘‘Country” are two numbers in the format: Indicator|GlobalRanking of 232 countries in HSI Version 2. ASEAN countries are denoted in bold italics. EconFI is the Economic Fabric Index. EnvFI is the Environmental Fabric Index. SFI is the Social Fabric Index. Comparators are selected for possible strategic interest.
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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5. Countries with trade, competitiveness or debt vulnerabilities: including Greece and the USA. 6. Countries which have not been progressing as others: including DPRK, Haiti and Sudan. Countries in groups 1–3 appear to have relatively bright futures, especially if they strengthen national and regional partnering toward improved global competitiveness befitting optimal situations for all their peoples. Countries in group 4 may have even more upbeat potentials, but also possible vulnerabilities depending on how they use, and where they place, their sovereign wealth funds. Countries in group 5 are highly vulnerable, as is currently being demonstrated by some Eurozone laggards, and has been demonstrated by several decades of currency slides, the prolongation of the ‘‘great recession” and the (oftdiscussed) relative decline the USA (e.g. NIC, 2012). Residents in group 6 countries tend to be vulnerable to a great diversity of socio-economic challenges. Situations of ASEAN members within the global community UNDP spawned sub-national, national and regional Human Development Reports (HDRs), for which it facilitated groups of experts to research and write the reports. Regional reports include the Arab Region, Southeast Asia (UNDP, 2005), and Asia and the Pacific (UNDP, 2012). Six ASEAN members (Cambodia, Indonesia, Lao PDR, Philippines, Thailand, and Viet Nam) have readily accessible National HDRs which include data amenable to at least basic prototyping of Human Security Indices. National HDRs reported for Malaysia and Myanmar are not generally
Web-accessible, for whatever reasons. Additional data are available from official and other sources for some ASEAN members – such as from the National Statistical Organization of Thailand, and from national censuses of Viet Nam. HSIs for two of these countries are in prototype. One such prototype, with sample uses, is sketched below. One way to assess the situations of communities and countries around the world is to compare their Economic, Environmental, and Social Fabric Indices, as well as their composite HSIs. Using the simpler HDI, Hastings (2009a) performed a similar analysis for Asian-Pacific Countries compared with those in other parts of the world. He found that such a juxtaposition, plus assessments of practices in those countries, suggested (1) areas where each country is relatively weak or strong (e.g. a component is relatively lower or higher than its HDI and those of its peers), (2) which peers may have better outcomes in specific areas of development, and (3) what policies and programmes from those other countries might be adaptable to one’s own situation for improving community situations. Table 1 shows ratings and global rankings for the HSI and its component Fabric Indices for ASEAN countries and some others. Several small island states (Falkland Islands, Dominica, French Polynesia and others omitted from Table 1) have relatively high human security despite potentially fragile economies, environments and pools of human resources. The USA’s longstanding trade deficit, poor performance in ‘‘legal corruption”, (Kaufmann & Vicente, 2005, 2011), low score on the Global Peace Index, low income equality, and globally leading incarceration rates contribute to its low rating compared with customary assumptions based on GDP, military prowess, mid-20th century economic
Table 2 Human security index vs. GDP per capita and HDI; same countries as for Table 1. HSI Rank – GDP pc Rank
Country
HSI Rank – GDP pc Rank
71 34 32 32
Dominica Bhutan Mongolia Myanmar
30
Falkland Islands Ghana Czech Republic French Polynesia Lao PDR New Zealand Taiwan Viet Nam Thailand China Costa Rica Bangladesh Germany
3
Japan
2
Indonesia
119
2 1
Norway India
136 138
30 28 23 20 19 19 19 17 14 13 12 5
Country
HSI Rank – HDI Rank
1 3 6 9
Sri Lanka Cambodia Australia Chile
76 70 56 35
12
Malaysia
27
12 13
Pakistan Hong Kong SAR
26 22
14
Philippines
18
16 16 17 27 40 45 48 68 69
Afghanistan Korea, Rep. Botswana Canada Singapore Oman Greece Turkey Israel
17 12 6 4 4 2 1 0 0
83
Brunei Darussalam United Arab Emirates USA .Equatorial Guinea
Country Bhutan Dominica Botswana Falkland Islands Ghana
HSI Rank – HDI Rank
Country
4 8 9 9
Viet Nam Chile Indonesia Cambodia
11
Costa Rica
13 13
Hong Kong SAR Oman
Taiwan Czech Republic French Polynesia Mongolia Lao PDR Thailand India New Zealand Bangladesh Pakistan China Malaysia
16
Sri Lanka
21 21 23 30 32 39 48 50 50
0
Myanmar
64
0
Germany
75
Australia Korea, Rep. Japan Singapore Philippines Canada Turkey Greece Brunei Darussalam United Arab Emirates Israel
0 1
Norway Afghanistan
97 117
Guam USA
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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Fig. 1. Scatter-plots of indicators for ASEAN and 222 other socio-economies.
‘‘might”, etc. Eight socio-economies in Asia and the Pacific (Norfolk Island and Niue plus those in Table 1), and 46 in the world, rank higher than ASEAN leader Singapore. Three (Solomon Islands plus those in Table 1) in Asia and the Pacific, and 37 globally, rank below Cambodia. Given such findings, how might communities in ASEAN countries fare? Though each country has unique situations, one might group ASEAN members into five loose clusters, compared with the mean value of the global HSI, which is .623: >.08 above the mean global HSI (.623): .04–.08 above the mean global HSI: Within .04 of the mean global HSI: .04–.08 below the mean global HSI: >.08 below the mean global HSI (.623):
Leading
Singapore
Mid+
Brunei Darussalam
Mid
Malaysia, Thailand, Viet Nam, Indonesia Lao PDR
Mid Trailing
Philippines, Myanmar, Cambodia
Table 2 compares the HSI with GDP per capita and HDI (the HSI and HDI both from Hastings, 2010). Negative numbers in Table 2 indicate HSI rankings exceeding GDP per capita or HDI values. In other words, such countries perform better in the more comprehensive HSI than in the simpler GDP or HDI. Note the high HSI performance of countries like Bhutan and Dominica. Bhutan’s policy of Gross National Happiness appears to deliver HSI outcomes un-measured by GDP and the HDI. Within ASEAN: Brunei Darussalam, Singapore, and modest-income Philippines are stronger in GDP and HDI than in the more comprehensive HSI. Lao PDR, Myanmar, Thailand and Viet Nam have higher HSI than implied by GDP per capita. Cambodia, Indonesia and Malaysia have roughly comparable HSI, HSI and GDP per capita rankings. Possible causes of such outcomes appear to be complex, and worth further assessment. Some economies which may have focused on ‘‘economic growth” may have performed
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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Fig. 1 (continued)
well in such regard. In some cases, benefits for people have not been forgotten (e.g. UAE is promoting enhanced local tertiary education through partnerships with major overseas universities, and has long had universal health care). In other cases (the USA over recent decades?), broader well-being may be weaker, as positive outcomes reach (increasingly?) fewer people. Some moderate-or-lower income countries may yet deliver good outcomes for their peoples. Bhutan and Dominica may be examples. Fig. 1 presents sample scatter-plots of HDI and HSI components vs. scaled GDP per capita1, similar to what was done for the HDI in Hastings (2009a). Large diamonds signify ASEAN members. The thin dashed line is a 2nd order polynomial trend line of non-ASEAN socio-economies. The thicker solid line plots the trend for ASEAN members. Higherincome ASEAN members tend to fall behind global peers in HSI vs. GDP. They outperform several peers in the Economic
1 Individual ASEAN members may be found in these plots by their scaled GDP per capita value: Myanmar = .343; Cambodia = .427; Lao PDR = .446; Viet Nam = .484; Philippines = .517; Indonesia = .531; Thailand = .637; Malaysia = .716; Brunei Darussalam = .900; Singapore = .902.
Fabric Index (partly due to strong fiscal governance), but tend to have weaker outcomes in income equality, Environmental and/or Social Fabric Indices. The plot of Environmental Vulnerability Index (SOPAC, 2005) vs. GDP per capita indicates that environmental vulnerability is not a simple function of GDP. Nor is it merely an indicator of risk from storms, tsunamis, and earthquakes. Singapore, Viet Nam and the Philippines are most vulnerable in the EVI – for diverse causes best understood by reading their respective profiles available at SOPAC (2005). Though ‘‘corruption” may be a sensitive subject in some circles, it is recognized that internal and external perceptions of corruption influence confidence in a place by investors, potential partners, and residents. ‘‘Perception of no corruption” plotted in Fig. 1 is a blend of illegal and ‘‘legal” corruption the first from WGI (2010), and the second developed following the approach of Kaufmann and Vicente (2005, 2011) using assessments by executives recorded in WEF (2010). Singapore, Malaysia, Indonesia, and Viet Nam lie above global and ASEAN trend lines for positive reputation compared to income level. However, virtually any country can improve governance by delivering a more
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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Fig. 1 (continued)
direct, transparent, and participatory focus on well-being of its entire populace. These are examples of analyses, which may be performed on the HSI and other data such as inputs to Global Competitiveness Reports (e.g. WEF, 2010) to assess economic, environmental, and social situations of ASEAN members and their peoples. The HSI, plus other context, may help assess reports such as Gallup (2012) claiming that Thais, Filipinos, Malaysians and Indonesians have the most positive outlooks of surveyed ASEAN (and East Asian) countries, with Singaporeans and Vietnamese being least positive. Further examples of assessments are presented by Hastings (2009a). Situations within ASEAN countries What might one perceive locally for cities and other communities within ASEAN countries, given progress (but also [as always with such data and indicators] some imperfections) in sub-national data?
HSI prototyping in two ASEAN countries is part of an effort to understand such situations. A HSI has been prototyped for Thailand, mostly using data from national Human Development Reports of Thailand over the past decade (UNDP, 2003, 2007, 2009). Fig. 2 illustrates mapping from UNDP (2009). That report, subtitled Human Security, Today and Tomorrow, describes an approach to Human Security built on the precepts of: Economic (growth, poverty, income, unemployment, poverty, social security safety net, situations for those in the informal economy, and high external dependence), Environmental (disasters, population growth and pressure, pollution and waste, and protection of natural resources), Food (quantity, quality, and sanitation), Health (infectious disease, cultural risk such as auto accidents, maintaining universal health care), Personal (crime, drug use, domestic and sexual violence), and
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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Fig. 1 (continued)
Political (political conflict and polarization, disruption of rights by actors in military coups, dominance by small groups, corruption, accusations of judicial bias). The potential inter-comparability of that effort and the HSI is high, noting that food, health, personal and political issues could be considered social aspects of Human Security. Figs. 3–5 map potential components of an Economic Fabric Index, Environmental Fabric Index, and Social Fabric Index, respectively, using a HSI approach. There are 77 provinces (Changwat in transliterated Thai) in Thailand [76 at the time of UNDP, 2003, 2007, 2009] – each named after and administered around the provincial city/municipality (Thetsaban in transliterated Thai) after which each province is named. In only a few provinces are the largest cities/towns other than the administrative main municipality. Examples of such exceptions are Chonburi Province (with several cities/towns including Pattaya and Laem Chabang), Prachuap Khiri Khan Province (with Hua Hin being larger than the eponymous municipality of the province) and Songkhla Province (with Hat Yai being the main city). Looking at the three levels of provinces,
their main district (Amphur Muang in transliterated Thai), and provincial municipality: Provinces range in population between about 185,000 and 2.6 million (plus Bangkok with an official population of about 8.3 million). Main districts range between about 38,000 and 460,000, with a median population of about 625,000 (and in percentages of provincial populations between 9% and 56% with a median of about 21% [not counting Bangkok’s 100%]). Main municipalities range in population between about 4600 and 315,000, with a median of about 36,000 (and in percentages of provincial populations between 1% and 27%, with a median of about 6% [not counting Bangkok’s 100%]). They are located in the main district of the province. Combined with regional and other diversity, Thailand offers an excellent opportunity to explore well-being situations across a wide range of community sizes and other characteristics – far beyond the scope of this initial study.
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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Fig. 2. Mapping of Thai national HDR data (UNDP, 2009).
Fig. 6 maps the three Fabric Indices and a prototype Human Security Index for Thailand. Fig. 6 also maps the Human Achievement Index (HAI) from UNDP (2009) using its original colour scheme (Fig. 6F) and the modified rainbow colour scheme used in the HSI (Fig. 6E). Note the similarity of the HAI from UNDP (2009) and the prototype HSI shown here, despite different selection and weighting of data. However, in the UNDP (2009) maps, there appears to be a somewhat similar broad trend to most or all maps but that for Family and Community Life – where the maps used in the HSI indicate significantly different situations among provinces for individual HSI themes. Might the approach of the HSI, and its three focused Fabric Indices offer increased nuance at the provincial level for Thailand, as was considered to be the HSI’s contribution to assessments in the countylevel study in Texas by Salinas et al. (2012)? Answering this question would require further investigation. The prototype Thai Economic Fabric Index shows several issues related to well-being. Though the north and northeast are often considered the poorest regions – patterns of income growth, poverty, expenditure and debt related
to income, and income equality is complex. The following discussion may illustrate possible approaches to finding opportunities for strengthening assessments and progress. 1. Technical opportunities for improving indicators: Example – Income Adjusted by Cost of Living: Globally, income is commonly represented by Gross Domestic Product per capita, adjusted for Purchasing Power Parity. Sub-nationally, the more on-target (for Human Security) median income is commonly used, but often lacks an adjustment for Purchasing Power Parity (or cost of living). The latter are often challenging to develop, but may be worthwhile. If the highest median incomes occur in the most expensive provinces, might the apparent disparity be somewhat mitigated by a cost of living adjustment? The ‘‘on-target” appropriateness of all inputs to the Economic Fabric Index (and to the other fabric indices) is worth considerable discussion. Redesign of datasets may provide opportunities for better perceptiveness of indicators, and thus understanding of some situations.
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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Fig. 3. Components of a prototype economic fabric index for Thailand.
2. Strategic opportunities: Figs. 3–6 indicate widely differing distributions of situations faced by different provinces. If one were attempting to improve community-level outcomes, assessment of such data may lead to beneficial strategies. For example, income equality. Perhaps a first test might be on the consistency of the indicator. If the data pass such a test, next steps might include assessing situations in trailing provinces such as Me Hong Son, Sa Kaeo, Surin, Loei, and Nong Bua Lamphu. Such assessment might uncover opportunities
for tactics and partnering to improve situations in provinces which lag in this indicator. Regarding household expenditure as a percentage of income – a first step might be to evaluate whether the indicator accurately represents situations in provinces such as Me Hong Son, Surin, Udon Thani and Nong Bua Lamphu. After such evaluation, assessment of situations, leading to better understanding and possible developmental partnerships, might help improve situations in lagging communities – thus strengthening the overall situation.
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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Fig. 4. Components of a prototype environmental fabric index for Thailand.
Fig. 6 shows the composite Fabric Indices, and the HSI, compared with the Human Achievement Index of UNDP (2009) shown in original colours as well as in the colour legend used for the HSI. Strategists and enablers in education, health, and other issues may better be able to set and justify priorities by their own presentations of such data. Thailand’s leading efforts in assessing Human Security Issues (through its Ministry and reportage such as UNDP, 2009) suggest that such work may benefit countries if appropriate data were available to provincial or district levels, ASEAN-wide. However, a comparison of current the presentation style (Fig. 6F) with refinements (as
exemplified by Fig. 6E) suggests that improved nuance is possible by such refinement (to Fig. 6E or other). Comparing individual indicators to Fabric Indices or the HSI can help assess the situations of individual communities, and for the country as a whole. Fig. 7 provides an example of such plots. In this case, the percentage of a province’s population attributed to its main metro area (Amphur Muang) is presented as one (of several alternatives) proxy for the main district’s influence on a province. The Education Index is a composite of negative indicators (percentage of a province’s population without schooling, or with only primary schooling) and positive indicators
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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Fig. 5. Components of a prototype social fabric index for Thailand.
(secondary school completions and higher) on education. One may note correlations between both HSI and the Education Index with the percentage of a province’s population attributed to its main metro area. A correlation with, perhaps, less scatter, is indicated between HSI and the Education Index. Additional analysis is planned along these lines – but is beyond the scope of the present paper. What is indicated so far is the considerable potential for such approaches to better understand, and illustrate situations within communities of such countries as Thailand. Though Thailand is used as an example here (because of its leading development of data and thought partly
represented by UNDP (2009)) somewhat similar strategies might be helpful in other ASEAN countries. Mainstreaming HSI-like data and handling tools support improved perceptions and solutions Socio-economic data are expected to continue to improve over time. Access should improve via primary sources and respected secondary compilers – strengthened by geoinformatics methodologies (Raghavan, Phisan Santitamnont, & Kiyoshi Honda, 2003; Raghavan, Phisan Santitamnont, & Tatsuya Nemoto, 2004), and other resources. Sources may include national and local
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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Fig. 6. Composite fabric indices and human security index for Thailand.
governments, other data compilers, organizations such as UN System components and the World Bank (e.g. WDI, 2012), and perhaps ASEAN-affiliated efforts (on standards, or on data coordination/collection/compilation). Such diversity of sources, however, may increase potential confusion on best-possible versions and sources for specific applications. Improvements in coverage, quality, and accessibility, should support evolving improvements in assessing socio-economic-environmental situations of communities with ASEAN. Perceptive and comprehensive indicators are assets for pro-active researchers, policymakers, strategists,
implementers, civil society groups, supportive but analytical media outlets, and the general public. This process should support steadily improving assessments, strategies, and outcomes for people from local, national, ASEAN, Asia–Pacific, and globally focused development strategies. Mainstreaming the use of such indicators can strengthen understanding, and thus progress toward better outcomes for people and communities. Data for the Global HSI are available for download from http://www.humansecurityindex.org Source materials are cited, and most are directly reachable via links from that site.
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Fig. 7. HSI situations in Thai Provinces.
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Developing forward-looking strategies This paper reviews the HSI and some of its uses, for improved assessment of national and community-level situations. It notes that ASEAN members cover much of the global range in developmental situations. It cites previous global and Asian-Pacific situational assessments, based on analyses of individual components of the HDI and HSI – and adds some additional supportive analytical materials in the ASEAN context. It suggests some approaches for developing strategies, and partnerships, to move forward at national and community scale – most notably around focusing on improving the situations of lagging countries and provinces – theme by theme. The next steps in assessing background information to support developmental strategies might involve: 1. Further assessment of data at the provincial level, assisted by traditional research on selected provinces, districts, and municipalities – for Thailand or another country. 2. An attempt to develop and assess a database to district or finer disaggregation, for Thailand or another country. Summary The Human Security Index has been presented as a tool to help increase perceptiveness of national and community-level strengths and challenges for ASEAN members, in comparison with peers in Asia and elsewhere. Such perceptiveness may be used to feed local, national, and regional strategy development to strengthen ASEAN integration and progress. Tables 1 and 2 may suggest some peer groupings between ASEAN and other countries. Though some results from the HSI may initially be surprising, an inspection of the data values for respective countries may shed light on those ratings and rankings. Assessments such as the comparisons of Fig. 1 (plus many other comparative assessments) suggest that ASEAN members often fit with their global peers, but also sometimes are differentiated from several countries with similar levels of GDP per capita, Human Development Index, or Human Security Index. Figs. 2–7 present examples of strategic assessments which can improve assessments and strategic responses. Further strategic assessments of ASEAN countries are possible. Some further approaches should be apparent from the examples in this paper, from papers cited herein, and from proactive reader perspectives. References ASEAN (2008). ASEAN economic community blueprint. Jakarta: ASEAN Secretariat. Online at: http://www.asean.org/5187-10.pdf. ASEAN (2009). ASEAN socio-cultural community blueprint. Jakarta: ASEAN Secretariat. Online at: http://www.asean.org/5187-19.pdf. Gallup, 2012. Latin Americans most positive in the world. Gallup Polls Website, online at: http://www.gallup.com/poll/159254/latin-americans-positiveworld.aspx.
Giasson, Jeff, 2010. Exercise24 media coverage report. Online at http:// www.inrelief.org/updates/exercise24mediacoveragereport. Hastings, David A., 2008. Describing the human condition – from Human Development to Human Security. Proceedings, GIS-IDEAS2008. Online at: http://gisws1.media.osaka-cu.ac.jp/gisideas08/viewabstract.php?id=299. Hastings, David A., 2009A. Filling Gaps in the Human Development Index: Findings for Asia and the Pacific. United Nations Economic and Social Commission for Asia and the Pacific, Working Paper WP/09/02. Online at: http:// www.unescap.org/publications/detail.asp?id=1308. Hastings, David A., 2009B. From Human Development to Human Security: A prototype human security index. United Nations Economic and Social Commission for Asia and the Pacific, Working Paper WP/09/03. Online at: http://www.unescap.org/publications/detail.asp?id=1345. Hastings, David A., 2011A. The Human Security Index: An Update and A New Release. Online at: http://www.humansecurityindex.org/wordpress/wpcontent/uploads/2012/02/hsiv2-documentation-report1_1.pdf. Hastings, David A., 2011B. The Human Security Index. Earthzine. V.2. No.5. Online at: http://www.earthzine.org/2011/05/04/the-human-security-indexpotential-roles-for-the-environmental-and-earth-observation-communities/. Hastings, David A., 2013A. Measuring quality-of-life: The Human Security Index. City, Culture, and Society – this issue. Hastings, David A., 2013C. Well-being and resilience; conflict and vulnerability. What can we foresee? In preparation. Kaufmann, Daniel and Pedro C. Vicente, 2005. Legal Corruption. World Bank, Washington, DC. http://siteresources.worldbank.org/INTWBIGOVANTCOR/ Resources/Legal_Corruption.pdf. Kaufmann, Daniel and Pedro C. Vicente, 2011. Legal Corruption. Economics and Politics. v.23, no.2, pp. 195-219. Online at: http://www.pedrovicente.org/ legal.pdf. NIC (2012). Global trends 2030: Alternative worlds. Washington, DC: National Intelligence Council. Online at: http://www.dni.gov/files/documents/GlobalTrends_ 2030.pdf. Raghavan, Venkatesh, Phisan, Santitamnont, Shinji, Masumoto, & Kiyoshi, Honda (2003). Open source software solutions in geoinformatics – implications for the Greater Mekong Subregion. Regional Conference on the Greater Mekong Subregion: Closing the Digital Divide. PathumThani, Thailand: Asian Institute of Technology. p. 26–28 February 2003. Online at: http://www.cp-idea.org/documentos/ tecnologia/0_ geoinformatica.pdf. Raghavan, Venkatesh, Phisan Santitamnont, Shinji Masumoto, and Tatsuya Nemoto, 2004. Implementation of Web Map Server Test-bed and Development of Training Material for Advancing FOSS4G Solutions. Proceedings of the FOSS/ GRASS Conference. Chulalongkorn University, Bangkok. Online at: http:// www.gisdevelopment.net/proceedings/fossgrass/papers/Implementation of Web Map Server Test-bed and.pdf. Salinas, Jennifer J., Shah, Mansai, Abdelbary, Bassent, Gay, Jennifer L., & Saxton, Ken (2012). Application of a novel method for assessing cumulative risk burden by county. International Journal of Environmental Research and Public Health, 9, 1820–1835. SOPAC, 2005. Environmental Vulnerability Index. South Pacific Applied Geosciences Consortium, Suva, Fiji. Online at: http://www.vulnerabilityindex.net. Hastings, David A. (2013b). Attempting to measure and understand well-being/ vulnerability: The Human Security Index for nations and communities. Osaka City University International Symposium, 17–19. UNDP, 2003. Community Empowerment and Human Development. Thailand Human Development Report, 2003. Online at: http://hdr.undp.org/en/reports/ national/asiathepacific/thailand/thailand_2003_en.pdf. UNDP, 2005. Southeast Asia Human Development Report. United Nations Development Programme. Online at: http://dirp3.pids.gov.ph/seahdr/ seahdr.html. UNDP, 2007. Sufficiency Economy and Human Development. Thailand Human Development Report, 2007. Online at: http://hdr.undp.org/en/reports/national/ asiathepacific/thailand/THAILAND_2007_en.pdf. UNDP, 2009. Human Security, Today and Tomorrow. Thailand National Human Development Report 2009. Online at: http://hdr.undp.org/en/reports/national/ asiathepacific/thailand/NHDR_2009_Thailand.pdf. UNDP, 2012. Sustaining Human Progress in a Changing Climate. Asia-Pacific Human Development Report. United Nations Development Programme, Colombo. Online at: http://asiapacific-hdr.aprc.undp.org/climate-change. WDI, 2012. World Development Indicators. World Bank, Washington, DC. Online at: http://data.worldbank.org and http://data.worldbank.org/data-catalog/worlddevelopment-indicators. WEF, 2010. Global Competitiveness Report. World Economic Forum. Online at http://www3.weforum.org/docs/WEF_GlobalCompetitivenessReport_2010-11. pdf. WGI, 2010. Worldwide Governance Indicators, 2010. World Bank, Washington, DC. Online at: http://info.worldbank.org/governance/wgi/index.asp. Wired, 2010. Exercise 24: imaginary massive earthquake in San Diego. Online at: http://www.wired.com/2010/09/exercise-24-imaginary-massive-earthquake-insan-diego/.
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Contents lists available at ScienceDirect
City, Culture and Society journal homepage: www.elsevier.com/locate/ccs
Characterizing situations in ASEAN cities: Using the Human Security Index David A. Hastings a,⇑, Venkatesh Raghavan b a b
Human Security Index, United States Osaka City University, Japan
a r t i c l e
i n f o
Article history: Received 26 September 2013 Received in revised form date 10 April 2014 Accepted 3 May 2014 Available online xxxx Keywords: Human security Well-being Indicator ASEAN Cities Communities
a b s t r a c t The Human Security Index discussed in Hastings (2013a, this issue) can help assess situations and strategize (1) improved and fair competitiveness, (2) benefits from regional cooperation, and (3) improved individual and community well-being. ASEAN countries are compared here with global peers, and with each other – with respect to well-being situations in their cities and other communities. ASEAN leaders tend to lag some of their global peers in delivery of Human Security and well-being – where lowerincome ASEAN countries tend to slightly lead their global peers in such outcomes. Further, a prototype HSI for Thailand is presented and discussed for situations in its cities and their surrounding territories. City-provincial situations are seen to be highly diverse, with some relatively poor (in monetary income) provinces leading in home ownership and other factors in Human Security. Formulation of HSIs for additional ASEAN countries, preferably at district-town levels, will likely increase our understandings of the concept and situations of well-being versus vulnerability in cities of such countries. Such exercises could lead to evolving better strategies for national – including urban – development planning and also help monitoring impacts of sustainable development initiatives. Published by Elsevier Ltd.
Introduction How to characterize the well-being, quality-of-life, and resilience potential versus vulnerability of cities, in the context of other communities such as countries, provinces surrounding – and dependent on – cities, and socio-economic groupings within cities? Considering the significant improvements in quantitative measurements and other indicators, on various aspects of the human condition at national and sub-national level, can we make progress in quantifying such issues? If so, we may be able to make progress in our understandings of causes, influences, and making progress on well-being – at national to local levels. The Human Security Index was designed to help address such issues. The Global HSI (Hastings, 2008, 2009b, 2011a, 2013a) has been used to discuss the concept and measurement of Human Security, and as a framework for assessing the well-being versus vulnerabilities of communities ⇑ Corresponding author. E-mail addresses: [email protected] (D.A. Hastings), raghavan@ media.osaka-cu.ac.jp (V. Raghavan).
around the world. A prototype county-level HSI for the USA (Hastings, 2011b) is being used for similar purposes at a local level for a country generally considered to be highly developed, but which some have argued (and the global HSI appears to perceive) may not be so highly developed at present. The Global HSI and a prototype for Thailand have been used to explore scenarios for supporting communities against possible stresses as ASEAN pursues greater global integration (ASEAN, 2008, 2009). This paper builds on that effort – focusing more on the situation of communities in ASEAN and Thailand, than on ASEAN integration. Community situations can better be detected, thanks to improving diversity and perceptiveness of data and indicators at national and local resolutions, and also benefiting from advances in spatial and thematic analytical tools. Besides a R&D effort in indicator formulation (see Hastings, 2013a – this issue), the HSI is an ongoing engagement in design, formulation, refinement, awareness, and use of such a development indicator. Engagements have included individuals, video-workshops, conferences, publications and Web modalities (HumanSecurityIndex.org,
http://dx.doi.org/10.1016/j.ccs.2014.05.005 1877-9166/Published by Elsevier Ltd.
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ResilienceSystem.org and elsewhere). Evolving issues include: How to be more perceptive, yet more geographically comprehensive than many legacy indicators? How to benefit from – and support – data, indicators, and other contributions made by intergovernmental, civil society, and academic-governmental-private organizations – while mitigating sensitivity to imperfections in data or process? How to successfully harmonize left–right, east–west and north–south political-social-cultural sensitivities – to focus on societal and governance deliveries & tangible outcomes? How to make the indicator perceptive and comprehensive, but also understandable and used? How to structure data management, results, and documentation to facilitate adding more data, selective deletion of components, rescaling and re-weighting inputs to create localized HSI? How to use differing sub-national and global data types to, nevertheless, perceive economic, environmental, and social situations among communities? How to strengthen such processes by incorporating contemporary methodologies such as video conferencing, thematic analysis tools (spreadsheets, etc.), spatial analysis tools (geographical information systems, etc.), Web design and tools? How to optimize use of open-source tools, to facilitate adoption and use by anyone? The HSI has received diverse engagements, including on its use as a tool for improving assessments of socio-economic and environmental situations, enhancing development strategies and programmes, and strengthening the monitoring of same. One example inadequately detailed in published media, Exercise24 (Giasson, 2010; Wired; 2010) prototyped responses to a simulated earthquake near San Diego, integrating a dashboard including HSI
indicators for Mexico and southern Californian counties, crowdsourcing, and other knowledge management approaches. In another (Salinas, Shah, Abdelbary, Gay, and Saxton, 2012) the HSI has been used to assess the cumulative health risk burden in the USA State of Texas, at the county level. That study considered that application of the HSI to the assessment ‘‘provides a fuller and more nuanced understanding of socioeconomic and environmental conditions, and increases awareness of the role played by environmental, economic, and social factors in observed health disparities by race/ethnicity and geographic region” (Salinas et al., 2012, p.1831). Human Security situations are thought to result from any combination of: Innate resources and environment, Outcomes inherited from past social situations and governance, Outcomes resulting from current social situations and governance, and/or Outcomes resulting from thoughts, (in)actions and uncertainties about the future. Combining these with current social situations, policies and programmes, one may prudently use the HSI to help forecast future situations, as has been prototyped by Hastings (2013b, 2013c). In that assessment, countries/ economies/societies have tentatively been grouped into six clusters, each with somewhat similar situations which might influence their futures. Those clusters are: 1. Advancing, relatively wealthy countries: Norway, Australia, and Canada. 2. Advancing, moderate income countries: Indonesia, Malaysia, Thailand, and Viet Nam. 3. Advancing, lower income countries: Cambodia, Lao PDR, and Philippines. 4. High trade surplus or sovereign wealth funds: Brunei Darussalam and Singapore.
including including including including
Table 1 Human security index for ASEAN and selected comparator socio-economies. HSI*
Country
EconFI
EnvFI
SFI
HSI
Country
EconFI
EnvFI
SFI
.865|1 .842|4 .772|20 .754|26 .753|28 .753|29 .744|31 .743|32 .739|34 .732|41 .726|46 .726|47 .722|53 .712|63 .693|75 .671|91 .670|92 .668|93 .660|98 .650|100 .648|103 .646|106
Falkland Islands Norway Taiwan Czech Republic Hong Kong SAR Germany Australia New Zealand Japan Dominica French Polynesia Singapore Canada Korea, Rep. Chile Brunei Darussalam Costa Rica Greece Malaysia Oman Thailand Botswana
.924|6 .877|15 .858|20 .795|42 .733|68 .744|61 .733|67 .760|53 .795|41 .711|81 .820|32 .844|23 .756|54 .835|28 .646|118 .925|5 .614|133 .676|101 .740|65 .811|35 .688|92 .671|102
.815|1 .746|16 .666|78 .697|51 .695|53 .671|73 .665|80 .622|119 .658|92 .750|15 .640|105 .583|149 .595|141 .595|140 .725|29 .400|228 .703|41 .621|121 .552|161 .448|214 .680|63 .637|108
.857|9 .902|1 .793|31 .771|39 .831|16 .844|12 .835|15 .847|10 .764|42 .735|66 .718|75 .750|53 .817|24 .707|81 .710|78 .689|88 .694|85 .708|80 .688|89 .692|86 .576|150 .630|119
.640|112 .633|115 .626|120 .623 .609|133 .608|135 .597|147 .586|152 .586|155 .585|158 .584|159 .562|166 .559|170 .551|172 .535|179 .512|181 .499|189 .492|192 .488|195 .487|196 .336|231 .296|232
Bhutan Israel Median China Mean Values United Arab Emirates Mongolia USA Viet Nam Sri Lanka Turkey Indonesia Lao PDR India Ghana Philippines Myanmar Pakistan Bangladesh Cambodia Nepal Afghanistan Somalia
.612|134 .777|47 .685|97 .634 .793|43 .622|131 .602|140 .536|167 .575|150 .609|135 .638|125 .534|169 .656|111 .466|187 .563|156 .512|178 .606|137 .520|173 .439|199 .403|214 .305|227 .274|228
.713|35 .506|187 .598|137 .608 .306|231 .587|145 .518|179 .614|125 .674|69 .589|143 .540|164 .647|98 .521|176 .584|147 .514|180 .622|118 .502|192 .513|181 .532|171 .636|111 .522|175 .441|218
.593|141 .617|128 .594|140 .626 .729|69 .615|130 .662|99 .608|133 .508|180 .557|159 .573|151 .506|182 .500|183 .602|138 .530|170 .401|215 .391|219 .442|204 .494187 .422|209 .180|231 .172|232
* In each column but ‘‘Country” are two numbers in the format: Indicator|GlobalRanking of 232 countries in HSI Version 2. ASEAN countries are denoted in bold italics. EconFI is the Economic Fabric Index. EnvFI is the Environmental Fabric Index. SFI is the Social Fabric Index. Comparators are selected for possible strategic interest.
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5. Countries with trade, competitiveness or debt vulnerabilities: including Greece and the USA. 6. Countries which have not been progressing as others: including DPRK, Haiti and Sudan. Countries in groups 1–3 appear to have relatively bright futures, especially if they strengthen national and regional partnering toward improved global competitiveness befitting optimal situations for all their peoples. Countries in group 4 may have even more upbeat potentials, but also possible vulnerabilities depending on how they use, and where they place, their sovereign wealth funds. Countries in group 5 are highly vulnerable, as is currently being demonstrated by some Eurozone laggards, and has been demonstrated by several decades of currency slides, the prolongation of the ‘‘great recession” and the (oftdiscussed) relative decline the USA (e.g. NIC, 2012). Residents in group 6 countries tend to be vulnerable to a great diversity of socio-economic challenges. Situations of ASEAN members within the global community UNDP spawned sub-national, national and regional Human Development Reports (HDRs), for which it facilitated groups of experts to research and write the reports. Regional reports include the Arab Region, Southeast Asia (UNDP, 2005), and Asia and the Pacific (UNDP, 2012). Six ASEAN members (Cambodia, Indonesia, Lao PDR, Philippines, Thailand, and Viet Nam) have readily accessible National HDRs which include data amenable to at least basic prototyping of Human Security Indices. National HDRs reported for Malaysia and Myanmar are not generally
Web-accessible, for whatever reasons. Additional data are available from official and other sources for some ASEAN members – such as from the National Statistical Organization of Thailand, and from national censuses of Viet Nam. HSIs for two of these countries are in prototype. One such prototype, with sample uses, is sketched below. One way to assess the situations of communities and countries around the world is to compare their Economic, Environmental, and Social Fabric Indices, as well as their composite HSIs. Using the simpler HDI, Hastings (2009a) performed a similar analysis for Asian-Pacific Countries compared with those in other parts of the world. He found that such a juxtaposition, plus assessments of practices in those countries, suggested (1) areas where each country is relatively weak or strong (e.g. a component is relatively lower or higher than its HDI and those of its peers), (2) which peers may have better outcomes in specific areas of development, and (3) what policies and programmes from those other countries might be adaptable to one’s own situation for improving community situations. Table 1 shows ratings and global rankings for the HSI and its component Fabric Indices for ASEAN countries and some others. Several small island states (Falkland Islands, Dominica, French Polynesia and others omitted from Table 1) have relatively high human security despite potentially fragile economies, environments and pools of human resources. The USA’s longstanding trade deficit, poor performance in ‘‘legal corruption”, (Kaufmann & Vicente, 2005, 2011), low score on the Global Peace Index, low income equality, and globally leading incarceration rates contribute to its low rating compared with customary assumptions based on GDP, military prowess, mid-20th century economic
Table 2 Human security index vs. GDP per capita and HDI; same countries as for Table 1. HSI Rank – GDP pc Rank
Country
HSI Rank – GDP pc Rank
71 34 32 32
Dominica Bhutan Mongolia Myanmar
30
Falkland Islands Ghana Czech Republic French Polynesia Lao PDR New Zealand Taiwan Viet Nam Thailand China Costa Rica Bangladesh Germany
3
Japan
2
Indonesia
119
2 1
Norway India
136 138
30 28 23 20 19 19 19 17 14 13 12 5
Country
HSI Rank – HDI Rank
1 3 6 9
Sri Lanka Cambodia Australia Chile
76 70 56 35
12
Malaysia
27
12 13
Pakistan Hong Kong SAR
26 22
14
Philippines
18
16 16 17 27 40 45 48 68 69
Afghanistan Korea, Rep. Botswana Canada Singapore Oman Greece Turkey Israel
17 12 6 4 4 2 1 0 0
83
Brunei Darussalam United Arab Emirates USA .Equatorial Guinea
Country Bhutan Dominica Botswana Falkland Islands Ghana
HSI Rank – HDI Rank
Country
4 8 9 9
Viet Nam Chile Indonesia Cambodia
11
Costa Rica
13 13
Hong Kong SAR Oman
Taiwan Czech Republic French Polynesia Mongolia Lao PDR Thailand India New Zealand Bangladesh Pakistan China Malaysia
16
Sri Lanka
21 21 23 30 32 39 48 50 50
0
Myanmar
64
0
Germany
75
Australia Korea, Rep. Japan Singapore Philippines Canada Turkey Greece Brunei Darussalam United Arab Emirates Israel
0 1
Norway Afghanistan
97 117
Guam USA
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Fig. 1. Scatter-plots of indicators for ASEAN and 222 other socio-economies.
‘‘might”, etc. Eight socio-economies in Asia and the Pacific (Norfolk Island and Niue plus those in Table 1), and 46 in the world, rank higher than ASEAN leader Singapore. Three (Solomon Islands plus those in Table 1) in Asia and the Pacific, and 37 globally, rank below Cambodia. Given such findings, how might communities in ASEAN countries fare? Though each country has unique situations, one might group ASEAN members into five loose clusters, compared with the mean value of the global HSI, which is .623: >.08 above the mean global HSI (.623): .04–.08 above the mean global HSI: Within .04 of the mean global HSI: .04–.08 below the mean global HSI: >.08 below the mean global HSI (.623):
Leading
Singapore
Mid+
Brunei Darussalam
Mid
Malaysia, Thailand, Viet Nam, Indonesia Lao PDR
Mid Trailing
Philippines, Myanmar, Cambodia
Table 2 compares the HSI with GDP per capita and HDI (the HSI and HDI both from Hastings, 2010). Negative numbers in Table 2 indicate HSI rankings exceeding GDP per capita or HDI values. In other words, such countries perform better in the more comprehensive HSI than in the simpler GDP or HDI. Note the high HSI performance of countries like Bhutan and Dominica. Bhutan’s policy of Gross National Happiness appears to deliver HSI outcomes un-measured by GDP and the HDI. Within ASEAN: Brunei Darussalam, Singapore, and modest-income Philippines are stronger in GDP and HDI than in the more comprehensive HSI. Lao PDR, Myanmar, Thailand and Viet Nam have higher HSI than implied by GDP per capita. Cambodia, Indonesia and Malaysia have roughly comparable HSI, HSI and GDP per capita rankings. Possible causes of such outcomes appear to be complex, and worth further assessment. Some economies which may have focused on ‘‘economic growth” may have performed
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Fig. 1 (continued)
well in such regard. In some cases, benefits for people have not been forgotten (e.g. UAE is promoting enhanced local tertiary education through partnerships with major overseas universities, and has long had universal health care). In other cases (the USA over recent decades?), broader well-being may be weaker, as positive outcomes reach (increasingly?) fewer people. Some moderate-or-lower income countries may yet deliver good outcomes for their peoples. Bhutan and Dominica may be examples. Fig. 1 presents sample scatter-plots of HDI and HSI components vs. scaled GDP per capita1, similar to what was done for the HDI in Hastings (2009a). Large diamonds signify ASEAN members. The thin dashed line is a 2nd order polynomial trend line of non-ASEAN socio-economies. The thicker solid line plots the trend for ASEAN members. Higherincome ASEAN members tend to fall behind global peers in HSI vs. GDP. They outperform several peers in the Economic
1 Individual ASEAN members may be found in these plots by their scaled GDP per capita value: Myanmar = .343; Cambodia = .427; Lao PDR = .446; Viet Nam = .484; Philippines = .517; Indonesia = .531; Thailand = .637; Malaysia = .716; Brunei Darussalam = .900; Singapore = .902.
Fabric Index (partly due to strong fiscal governance), but tend to have weaker outcomes in income equality, Environmental and/or Social Fabric Indices. The plot of Environmental Vulnerability Index (SOPAC, 2005) vs. GDP per capita indicates that environmental vulnerability is not a simple function of GDP. Nor is it merely an indicator of risk from storms, tsunamis, and earthquakes. Singapore, Viet Nam and the Philippines are most vulnerable in the EVI – for diverse causes best understood by reading their respective profiles available at SOPAC (2005). Though ‘‘corruption” may be a sensitive subject in some circles, it is recognized that internal and external perceptions of corruption influence confidence in a place by investors, potential partners, and residents. ‘‘Perception of no corruption” plotted in Fig. 1 is a blend of illegal and ‘‘legal” corruption the first from WGI (2010), and the second developed following the approach of Kaufmann and Vicente (2005, 2011) using assessments by executives recorded in WEF (2010). Singapore, Malaysia, Indonesia, and Viet Nam lie above global and ASEAN trend lines for positive reputation compared to income level. However, virtually any country can improve governance by delivering a more
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Fig. 1 (continued)
direct, transparent, and participatory focus on well-being of its entire populace. These are examples of analyses, which may be performed on the HSI and other data such as inputs to Global Competitiveness Reports (e.g. WEF, 2010) to assess economic, environmental, and social situations of ASEAN members and their peoples. The HSI, plus other context, may help assess reports such as Gallup (2012) claiming that Thais, Filipinos, Malaysians and Indonesians have the most positive outlooks of surveyed ASEAN (and East Asian) countries, with Singaporeans and Vietnamese being least positive. Further examples of assessments are presented by Hastings (2009a). Situations within ASEAN countries What might one perceive locally for cities and other communities within ASEAN countries, given progress (but also [as always with such data and indicators] some imperfections) in sub-national data?
HSI prototyping in two ASEAN countries is part of an effort to understand such situations. A HSI has been prototyped for Thailand, mostly using data from national Human Development Reports of Thailand over the past decade (UNDP, 2003, 2007, 2009). Fig. 2 illustrates mapping from UNDP (2009). That report, subtitled Human Security, Today and Tomorrow, describes an approach to Human Security built on the precepts of: Economic (growth, poverty, income, unemployment, poverty, social security safety net, situations for those in the informal economy, and high external dependence), Environmental (disasters, population growth and pressure, pollution and waste, and protection of natural resources), Food (quantity, quality, and sanitation), Health (infectious disease, cultural risk such as auto accidents, maintaining universal health care), Personal (crime, drug use, domestic and sexual violence), and
Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005
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Fig. 1 (continued)
Political (political conflict and polarization, disruption of rights by actors in military coups, dominance by small groups, corruption, accusations of judicial bias). The potential inter-comparability of that effort and the HSI is high, noting that food, health, personal and political issues could be considered social aspects of Human Security. Figs. 3–5 map potential components of an Economic Fabric Index, Environmental Fabric Index, and Social Fabric Index, respectively, using a HSI approach. There are 77 provinces (Changwat in transliterated Thai) in Thailand [76 at the time of UNDP, 2003, 2007, 2009] – each named after and administered around the provincial city/municipality (Thetsaban in transliterated Thai) after which each province is named. In only a few provinces are the largest cities/towns other than the administrative main municipality. Examples of such exceptions are Chonburi Province (with several cities/towns including Pattaya and Laem Chabang), Prachuap Khiri Khan Province (with Hua Hin being larger than the eponymous municipality of the province) and Songkhla Province (with Hat Yai being the main city). Looking at the three levels of provinces,
their main district (Amphur Muang in transliterated Thai), and provincial municipality: Provinces range in population between about 185,000 and 2.6 million (plus Bangkok with an official population of about 8.3 million). Main districts range between about 38,000 and 460,000, with a median population of about 625,000 (and in percentages of provincial populations between 9% and 56% with a median of about 21% [not counting Bangkok’s 100%]). Main municipalities range in population between about 4600 and 315,000, with a median of about 36,000 (and in percentages of provincial populations between 1% and 27%, with a median of about 6% [not counting Bangkok’s 100%]). They are located in the main district of the province. Combined with regional and other diversity, Thailand offers an excellent opportunity to explore well-being situations across a wide range of community sizes and other characteristics – far beyond the scope of this initial study.
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Fig. 2. Mapping of Thai national HDR data (UNDP, 2009).
Fig. 6 maps the three Fabric Indices and a prototype Human Security Index for Thailand. Fig. 6 also maps the Human Achievement Index (HAI) from UNDP (2009) using its original colour scheme (Fig. 6F) and the modified rainbow colour scheme used in the HSI (Fig. 6E). Note the similarity of the HAI from UNDP (2009) and the prototype HSI shown here, despite different selection and weighting of data. However, in the UNDP (2009) maps, there appears to be a somewhat similar broad trend to most or all maps but that for Family and Community Life – where the maps used in the HSI indicate significantly different situations among provinces for individual HSI themes. Might the approach of the HSI, and its three focused Fabric Indices offer increased nuance at the provincial level for Thailand, as was considered to be the HSI’s contribution to assessments in the countylevel study in Texas by Salinas et al. (2012)? Answering this question would require further investigation. The prototype Thai Economic Fabric Index shows several issues related to well-being. Though the north and northeast are often considered the poorest regions – patterns of income growth, poverty, expenditure and debt related
to income, and income equality is complex. The following discussion may illustrate possible approaches to finding opportunities for strengthening assessments and progress. 1. Technical opportunities for improving indicators: Example – Income Adjusted by Cost of Living: Globally, income is commonly represented by Gross Domestic Product per capita, adjusted for Purchasing Power Parity. Sub-nationally, the more on-target (for Human Security) median income is commonly used, but often lacks an adjustment for Purchasing Power Parity (or cost of living). The latter are often challenging to develop, but may be worthwhile. If the highest median incomes occur in the most expensive provinces, might the apparent disparity be somewhat mitigated by a cost of living adjustment? The ‘‘on-target” appropriateness of all inputs to the Economic Fabric Index (and to the other fabric indices) is worth considerable discussion. Redesign of datasets may provide opportunities for better perceptiveness of indicators, and thus understanding of some situations.
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Fig. 3. Components of a prototype economic fabric index for Thailand.
2. Strategic opportunities: Figs. 3–6 indicate widely differing distributions of situations faced by different provinces. If one were attempting to improve community-level outcomes, assessment of such data may lead to beneficial strategies. For example, income equality. Perhaps a first test might be on the consistency of the indicator. If the data pass such a test, next steps might include assessing situations in trailing provinces such as Me Hong Son, Sa Kaeo, Surin, Loei, and Nong Bua Lamphu. Such assessment might uncover opportunities
for tactics and partnering to improve situations in provinces which lag in this indicator. Regarding household expenditure as a percentage of income – a first step might be to evaluate whether the indicator accurately represents situations in provinces such as Me Hong Son, Surin, Udon Thani and Nong Bua Lamphu. After such evaluation, assessment of situations, leading to better understanding and possible developmental partnerships, might help improve situations in lagging communities – thus strengthening the overall situation.
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Fig. 4. Components of a prototype environmental fabric index for Thailand.
Fig. 6 shows the composite Fabric Indices, and the HSI, compared with the Human Achievement Index of UNDP (2009) shown in original colours as well as in the colour legend used for the HSI. Strategists and enablers in education, health, and other issues may better be able to set and justify priorities by their own presentations of such data. Thailand’s leading efforts in assessing Human Security Issues (through its Ministry and reportage such as UNDP, 2009) suggest that such work may benefit countries if appropriate data were available to provincial or district levels, ASEAN-wide. However, a comparison of current the presentation style (Fig. 6F) with refinements (as
exemplified by Fig. 6E) suggests that improved nuance is possible by such refinement (to Fig. 6E or other). Comparing individual indicators to Fabric Indices or the HSI can help assess the situations of individual communities, and for the country as a whole. Fig. 7 provides an example of such plots. In this case, the percentage of a province’s population attributed to its main metro area (Amphur Muang) is presented as one (of several alternatives) proxy for the main district’s influence on a province. The Education Index is a composite of negative indicators (percentage of a province’s population without schooling, or with only primary schooling) and positive indicators
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Fig. 5. Components of a prototype social fabric index for Thailand.
(secondary school completions and higher) on education. One may note correlations between both HSI and the Education Index with the percentage of a province’s population attributed to its main metro area. A correlation with, perhaps, less scatter, is indicated between HSI and the Education Index. Additional analysis is planned along these lines – but is beyond the scope of the present paper. What is indicated so far is the considerable potential for such approaches to better understand, and illustrate situations within communities of such countries as Thailand. Though Thailand is used as an example here (because of its leading development of data and thought partly
represented by UNDP (2009)) somewhat similar strategies might be helpful in other ASEAN countries. Mainstreaming HSI-like data and handling tools support improved perceptions and solutions Socio-economic data are expected to continue to improve over time. Access should improve via primary sources and respected secondary compilers – strengthened by geoinformatics methodologies (Raghavan, Phisan Santitamnont, & Kiyoshi Honda, 2003; Raghavan, Phisan Santitamnont, & Tatsuya Nemoto, 2004), and other resources. Sources may include national and local
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Fig. 6. Composite fabric indices and human security index for Thailand.
governments, other data compilers, organizations such as UN System components and the World Bank (e.g. WDI, 2012), and perhaps ASEAN-affiliated efforts (on standards, or on data coordination/collection/compilation). Such diversity of sources, however, may increase potential confusion on best-possible versions and sources for specific applications. Improvements in coverage, quality, and accessibility, should support evolving improvements in assessing socio-economic-environmental situations of communities with ASEAN. Perceptive and comprehensive indicators are assets for pro-active researchers, policymakers, strategists,
implementers, civil society groups, supportive but analytical media outlets, and the general public. This process should support steadily improving assessments, strategies, and outcomes for people from local, national, ASEAN, Asia–Pacific, and globally focused development strategies. Mainstreaming the use of such indicators can strengthen understanding, and thus progress toward better outcomes for people and communities. Data for the Global HSI are available for download from http://www.humansecurityindex.org Source materials are cited, and most are directly reachable via links from that site.
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Fig. 7. HSI situations in Thai Provinces.
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Developing forward-looking strategies This paper reviews the HSI and some of its uses, for improved assessment of national and community-level situations. It notes that ASEAN members cover much of the global range in developmental situations. It cites previous global and Asian-Pacific situational assessments, based on analyses of individual components of the HDI and HSI – and adds some additional supportive analytical materials in the ASEAN context. It suggests some approaches for developing strategies, and partnerships, to move forward at national and community scale – most notably around focusing on improving the situations of lagging countries and provinces – theme by theme. The next steps in assessing background information to support developmental strategies might involve: 1. Further assessment of data at the provincial level, assisted by traditional research on selected provinces, districts, and municipalities – for Thailand or another country. 2. An attempt to develop and assess a database to district or finer disaggregation, for Thailand or another country. Summary The Human Security Index has been presented as a tool to help increase perceptiveness of national and community-level strengths and challenges for ASEAN members, in comparison with peers in Asia and elsewhere. Such perceptiveness may be used to feed local, national, and regional strategy development to strengthen ASEAN integration and progress. Tables 1 and 2 may suggest some peer groupings between ASEAN and other countries. Though some results from the HSI may initially be surprising, an inspection of the data values for respective countries may shed light on those ratings and rankings. Assessments such as the comparisons of Fig. 1 (plus many other comparative assessments) suggest that ASEAN members often fit with their global peers, but also sometimes are differentiated from several countries with similar levels of GDP per capita, Human Development Index, or Human Security Index. Figs. 2–7 present examples of strategic assessments which can improve assessments and strategic responses. Further strategic assessments of ASEAN countries are possible. Some further approaches should be apparent from the examples in this paper, from papers cited herein, and from proactive reader perspectives. References ASEAN (2008). ASEAN economic community blueprint. Jakarta: ASEAN Secretariat. Online at: http://www.asean.org/5187-10.pdf. ASEAN (2009). ASEAN socio-cultural community blueprint. Jakarta: ASEAN Secretariat. Online at: http://www.asean.org/5187-19.pdf. Gallup, 2012. Latin Americans most positive in the world. Gallup Polls Website, online at: http://www.gallup.com/poll/159254/latin-americans-positiveworld.aspx.
Giasson, Jeff, 2010. Exercise24 media coverage report. Online at http:// www.inrelief.org/updates/exercise24mediacoveragereport. Hastings, David A., 2008. Describing the human condition – from Human Development to Human Security. Proceedings, GIS-IDEAS2008. Online at: http://gisws1.media.osaka-cu.ac.jp/gisideas08/viewabstract.php?id=299. Hastings, David A., 2009A. Filling Gaps in the Human Development Index: Findings for Asia and the Pacific. United Nations Economic and Social Commission for Asia and the Pacific, Working Paper WP/09/02. Online at: http:// www.unescap.org/publications/detail.asp?id=1308. Hastings, David A., 2009B. From Human Development to Human Security: A prototype human security index. United Nations Economic and Social Commission for Asia and the Pacific, Working Paper WP/09/03. Online at: http://www.unescap.org/publications/detail.asp?id=1345. Hastings, David A., 2011A. The Human Security Index: An Update and A New Release. 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Please cite this article in press as: Hastings, D.A., & Raghavan, V. Characterizing situations in ASEAN cities: Using the Human Security Index. City, Culture and Society (2015), http://dx.doi.org/10.1016/j.ccs.2014.05.005