Philippines

Identifying the Vulnerable to Poverty from Natural Disasters: The Case of Typhoons in the Philippines

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1. Introduction and Motivation

With 60% of its population living in coastal areas, and sensitivity to the El Niño phenomenon, the Philippines is one of the countries with a high propensity to be exposed to typhoons and one of the top 10 countries worldwide at risk for both climate change and disasters. Forecasts on climate change predict an increase in extreme rainfall in the Philippines, with the number of days with heavy rainfall (greater than 200mm) expected to increase with global warming by the year 2020 and 2050 (Cruz et al., 2017 Philippine Climate Change Assessment).

Understandably, given their disruptive and destructive power, typhoons attract a lot of attention in the Philippines. For instance, as recently as September 2018, Typhoon Mangkhut struck the Philippines after thousands of people evacuated their homes to dodge the 550-mile wide storm as it roared across the Pacific with maximum sustained winds of 120 miles per hour (New York Times, Sep 14, 2018). Fortunately, Typhoon Mangkhut hit an area far less densely populated and, because of geography, much less vulnerable than Tacloban, a highly urbanized Philippine city devastated by Typhoon Haiyan, that struck in 2013 and resulted in 6000 deaths and destroyed so many homes across the central Philippines (Visayas) that it displaced nearly four million people.

Empirical evidence has shown that natural disasters, such as typhoons and cyclones, play an important role in preventing people from moving out of poverty and in pulling back into poverty people who were able to escape poverty. Disaster risk response is therefore an important component of poverty reduction, especially in the context of recurrent shocks. With the increased focus on fragility, transient poverty, disaster risk management and crisis response, the components of an effective disaster risk management program of countries subject to frequent natural disasters are twofold: ensuring that (i) that there is immediate liquidity in the aftermath of the disaster and (ii) there is a set of scalable social protection programs in place leveraging on existing social protection systems to rapidly provide support to the exposed and vulnerable sections of the population immediately after a disaster.

Fortunately, the Philippines has one of the most advanced Social Protection systems in the East Asia Pacific region, designed to help poor households manage risk and shocks. Undergoing rapid and comprehensive social welfare reform since 2007, the Government of the Philippines has developed a number of national social protection programs that are accompanied by advanced information and delivery systems. Among them is the large conditional cash transfer program, called Pantawid Pamilya Pilipino Program (4Ps). Households receive cash grants if children stay in school and get regular health check-ups, have their growth monitored, and receive vaccines. Pregnant women must get pre-natal care, with their births attended to by professional health workers. Started in 2007, the government expanded the program to reach a total of 20 million Filipinos belonging to 4.4 million households in June 2018. The program benefits about 20% of the population, the majority of the nation’s poor. Nine million children are currently benefiting from the program, 1.9 million of which are in high school.

Currently, the targeting for eligibility for the benefits of the 4Ps program is aimed primarily towards alleviating chronic poverty among eligible poor households and not towards identifying those that are vulnerable to poverty. Beneficiaries are objectively selected through the National Household Targeting System, also known as Listathanan, which is based from a survey of the physical structure of their houses, the number of rooms and occupants, their access to running water, and other factors affecting their living conditions (Velarde, 2018). The program has one of the most comprehensive poverty targeting databases in the world today, covering 75% of the country’s population. It has been used extensively to identify poor and near-poor beneficiaries for national and local government programs.

The rationale of scalable social protection programs is to expand coverage in the event of a disaster to include not only the poor but also some of those believed to be vulnerable to falling into poverty when exposed to a shock. The objective is to mitigate the direct impact on household asset and welfare losses in the direct aftermath of a disaster, but also to prevent some of the intermediate term impacts – including forced displacement, and negative coping mechanisms used by poor households to handle the shock – such as selling off productive assets.

This paper builds on the existing literature assessing ex-postthe quantitative effects of natural disasters on different dimensions of household welfare (e.g. Anttila-Hughes and Hsiang, 2013; Strobl, 2019; Ishizawa and Miranda, 2016) to make progress towards the ex-ante identification of households vulnerable to poverty due to natural disasters. A wind model for the Philippines is employed to estimate local wind speeds at any particular locality where a tropical typhoon directly passes over or nearby. The estimated wind speeds are merged to the household FIES survey at the barangay level and consumption expenditures are regressed against windspeed (or a related damage index) and socioeconomic household characteristics. The paper shows that different specifications of typhoon effects have negative impacts on consumption levels, especially food. The estimated coefficients from the regression model are then used to estimate ex-ante household vulnerability to poverty in the event of future natural disasters of different intensity.

The proposed approach applied to the case of typhoons is fully complementary to the proxymeans targeting (PMT) method used by Listahanan and the 4Ps, in the sense that in addition to the chronic poor currently identified by the PMT method of the 4Ps program, it allows identification (or targeting) of the households that are likely to fall below the poverty line in the event of a natural disaster shock. The ex-ante identification of those who are vulnerable to poverty combined with timely support for these households makes it possible to provide targeted support in a timely and cost-effective manner.