It should surprise no one that even as growth in the country’s gross domestic product (GDP) has remained among the fastest in Asia and the world, many still claim they have yet to feel significant improvement in their lives.
How well the economy is doing, as indicated by how fast total production is growing, is obviously not the same as how well people are doing. This is why the concept of gross national happiness has gained adherents, and more than just a tongue-in-cheek parody of gross national product or GNP, it is now the subject of serious efforts to measure it. While we may never be able to objectively quantify happiness and develop a satisfactory numerical measure for it, alternative indicators have come about to tell us much more than GDP can.
Perhaps the best known is the United Nations’ Human Development Index (HDI). First introduced in the late 1980s and now reported yearly for all UN member-countries, HDI combines a measure of income (GDP per capita), health (life expectancy) and education (years of schooling) into a composite index between 0 and 1. Norway has consistently topped the world’s HDI rankings, with a 2015 HDI of 0.949. The Philippines ranked 116th (HDI of 0.682) in a list of 188 countries, right behind Vietnam, Palestine and Indonesia. Interestingly, countries with much lower gross national income per capita well outrank us in HDI, such as Cuba (68th), Ukraine (84th), Belize (103rd), Samoa (104th), and Paraguay (110th). Sadly, we actually fared much better 16 years ago (in 2001), when we ranked 77th (with HDI of 0.754) out of 173 countries listed. Within countries, the HDI is now also being measured across states or provinces, revealing disparities in welfare across areas within the same country.
While the HDI provides a more complete picture than GDP, the information it contains is still quite limited. This led the government in the early 1990s to pursue a much more informative measure to assess household welfare, called the Minimum Basic Needs (MBN) indicator system. It began with identifying a number of basic needs that must be met by the average family. The system surveyed every household in every village in the country on their ability to meet their MBNs, including food (at least two meals in a day), shelter (a house that can last at least five years), clothing (at least two changes of clothes per week), access to potable water (within 50 meters of residence), sanitation facilities, health services and education. The system started out monitoring 33 items, including indicators of political empowerment. It aimed to permit addressing poverty and social welfare in a coordinated and more focused way according to the most critical needs of Filipino families.
The MBN system has since evolved into the now widely used Community Based Monitoring System or CBMS, which cut the list of monitored items into half for more manageability. CBMS is now being employed in at least 15 countries in Asia, Africa and Latin America. In the Philippines, CBMS is used in 77 provinces, 965 municipalities and 87 cities, covering 27,271 barangays. Apart from being a valuable planning information tool, the CBMS system has become a mechanism for empowering people in the local areas. Results of the CBMS survey are made known to and validated with the barangay residents themselves. In one such validation exercise I witnessed years ago in Barangay Salvacion in Puerto Princesa City, barangay officials and residents actively deliberated on their most pressing unmet needs (sanitary toilets, children’s access to schools). They not only attained deeper understanding of their community problems; they also discovered that solutions to many of them lay in their own hands. In turn, they were also better able to articulate their needs to the city planning office.
Armed with hard data on people’s plight, government planners and officials at the national and local levels could better plan for uplifting Filipinos’ lives and allocate budgets to meet most pressing needs. Effective evidence-based planning, policymaking and budgeting begin with gathering meaningful data, well beyond what GDP can ever tell us.
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