Population and Poverty: The Real Score*

By

Ruperto P. Alonzo, Arsenio M. Balisacan, Dante B. Canlas, Joseph J. Capuno, Ramon L. Clarete, Rolando A. Danao, Emmanuel S. de Dios, Benjamin E. Diokno, Emmanuel F. Esguerra, Raul V. Fabella, Ma. Socorro Gochoco-Bautista, Aleli P. Kraft, Felipe M. Medalla, Nimfa F. Mendoza, Solita C. Monsod, Cayetano W. Paderanga, Jr., Ernesto M. Pernia, Stella A. Quimbo, Gerardo P. Sicat, Orville C. Solon, Edita A. Tan, Gwendolyn R. Tecson

University of the Philippines

SCHOOL OF ECONOMICS

December 2004

Contents

Introduction................................................................................................... 2

Key messages

What Macro Data Show................................................................................ 3

What Household Data Reveal........................................................................ 5

What People Say......................................................................................... 10

Is the Government’s Poverty Goal Achievable?............................................ 11

Why the Need for Population Policy?........................................................... 12

Why Must Population Policy Be National in Scope?..................................... 13

What are the Elements of an Effective Population Policy?.............................. 14

What about the Prospect of a “Demographic Winter”?................................. 14

Conclusion.................................................................................................. 15

References.................................................................................................. 16

Appendix.................................................................................................... 18

Population and Poverty: The Real Score

Salus populi suprema lex

Introduction

The public debate on the population issue – long settled in most of the developing world – remains unresolved in the Philippines. We aim in this paper to contribute to the debate, in particular to highlight the role the government must play to face up to this development challenge.

On one extreme, there are those who say that there is no population problem and, hence, that there is nothing the government needs to do about it. On the other, some view population growth as the principal cause of poverty that would justify the government resorting to draconian and coercive measures to deal with the problem (e.g., denial of basic services and subsidies to families with more than two children).

We consider these extreme views and arrive at what we think is a balanced, more reasoned and, hopefully, more widely acceptable position. Our review of the extensive literature and our analysis of relevant empirical data lead us to the following key messages:

· Poverty is a complex phenomenon, and many factors are responsible for it. Rapid population growth alone cannot explain poverty. Bad governance, high wealth and income inequality and weak economic growth are the main causes. But rapid population growth and high fertility rates, especially among the poor, do exacerbate poverty and make it harder for the government to address it. The government’s target of reducing poverty incidence to 20% or lower by 2010 would not be feasible, given historical growth rates of population and the economy.

· Time and again, Filipino women across all socioeconomic classes have expressed their desire for fewer children. But many, particularly the poor and the less educated among them, have more children than they want and are unable to achieve their desired number of children. Moreover, an overwhelming majority of Filipinos have affirmed the importance of the ability to plan one’s family or control one’s fertility, and believe that rapid population growth impedes the country’s development.

· An unequivocal and coherent national population policy – backed by an adequately funded family planning program that provides accurate information and enables access to methods of contraception of choice – is pro-poor, pro-women, pro-people, and pro-life. Any government that cares about the poor cannot be blind to the fact that many of them have no access to effective family planning services.

· Good population policy and programs are not costly and, based on the results of surveys, are likely to be widely welcomed. But political will and commitment are needed to make them effective.

· The threat of the so-called “demographic winter” (birth dearth, aging, etc.) for the Philippines is greatly exaggerated, and using it as an argument against a sensible population policy is a plain and simple scare tactic.

What macro data show

Population growth in the Philippines declined slowly from 3.0% per annum in the early 1970s to 2.5% in the mid-1980s, then leveling to 2.36% in the 1990s and remaining at this rate today. This pattern of growth deceleration roughly corresponds to the relative waxing and waning of the country’s population program.

The leveling of the Philippines’ population growth decline in the late 1980s through 1990s has resulted in a population size that is larger than the United Nations (UN) medium variant population projections. The UN (1986) projected RP’s population to reach 86 million by 2010; in fact, that size would already likely be reached by 2005.

By comparison, Thailand’s and Indonesia’s population growth rates, which were similar to the Philippines’ in the early 1970s, are down to 1.4% and 1.5%, respectively (Chart 1). Likewise, while Thailand’s poverty incidence is down to 9.8% and Indonesia’s to 18.2%, the Philippines’ poverty incidence remains high at 33% (all official figures reported in ADB 2004)[1].

These comparisons are instructive in understanding the links between governance, population policy, and poverty. Thailand is arguably the best among the three countries on all three counts, suggesting that good population policy combined with good governance results in rapid economic growth and poverty reduction. Meanwhile, the experience of Indonesia, where governance and corruption ratings are worse than those of the Philippines, suggests that good population policy by itself can contribute to significant poverty reduction. In short, population policy does matter.

Moreover, the contrast between Indonesia and the Philippines shows that even a country with lower literacy and per capita income than the Philippines can reduce fertility rates, which, as is argued below, is very important for poverty reduction. This is so since it is the poor who have the highest fertility and the largest gap between desired and actual fertility.

The Philippines’ population growth rate is among the highest in the developing world. It had been widely accepted even in the 1970s-80s that rapid population growth (of 2% or more per annum then prevailing in many developing countries) was more likely to impede than promote economic development (World Bank 1984). This negative effect operates via reduced child care and human capital investment at the family level, lower household sector savings for business and government investments, and constraints on allocative efficiency, innovation and entrepreneurship. Population growth requires capital widening to maintain the amount of capital per worker, and the faster such growth the lesser the chances for capital deepening or raising the amount of capital per worker. Many developing countries have taken these lessons to heart, with positive results, and since have moved on – but not the Philippines.

The Philippines’ rapid population growth has a direct bearing on the labor market. It has prolonged the task of significantly reducing unemployment – a problem that is untenably large – and raising productivity. The current pool of unemployed and underemployed exceeds 5 million – a daunting challenge, indeed, for job creation.

A recent study (Mapa and Balisacan 2004) on the population-poverty nexus, using data on 80 developing and developed countries, gives the following results:

· total population growth exerts a negative and significant effect on economic growth (unfavorable saving and capital-shallowing effects);

· at the same time, working-age population growth (implying demographic dividend), life expectancy at birth (a health indicator), openness to trade, and quality of public institutions (denoting good governance) all show positive and significant effects on economic growth.

The study also carries out a simulation exercise – what if the Philippines had Thailand’s population growth trajectory? – with the following results:

· an increase of 0.77% per annum over 1975-2000 in average income per person or a cumulative increase of 22% in income per capita by 2000 – meaning a GDP per capita in 2000 of $1,210 instead of the actual $993 [or $4,839 instead of $3,971 in purchasing power parity (PPP) terms];

· basic education cost savings of P128 billion from 1991-2000, and basic health cost savings of P52 billion from 1996 to 2000;

· these cost savings could have been used to improve the quality of education and health services, or to finance agricultural sector investments that – along with lower population growth – could have sharply reduced rural poverty;

· the above estimates are conservative as they don’t fully capture the population-economy-poverty interaction effects.

It should be noted, however, that cross-country studies such as the above, which employ regression analysis of cross-country averages, have inherent shortcomings[2] and show mixed results (see Appendix). Other studies may be cited that show either a positive or no relationship between growth rates of population and per capita income.

We now turn to micro (household) data for a deeper look at the population-poverty link.

What household data reveal

The Philippines’ total fertility rate (TFR)[3] declined from 6.0 in 1973 to 4.1 in 1993, and more slowly to 3.5 in 2003 (NDHS 2003). By comparison, Thailand’s and Indonesia’s TFRs, starting at about the same level in the early 1970s as the Philippines’, are currently 1.7 and 2.6, respectively (Chart 2).

Again, this is instructive. Contrary to claims that significant fertility declines can happen only in countries at high income levels, Indonesia with lower per capita income and lower literacy rate was, in fact, able to reduce fertility faster than the Philippines. The same can be said of Bangladesh, Sri Lanka, and India’s Kerala state.

There is a close association between poverty incidence and family size, as borne out consistently by data over time. For example, data for 2000 show that poverty incidence rises monotonically from 9.8% for family size of one to 57.3% for family size of 9+ (Table 1). Moreover, poverty incidence declined the slowest for family size 9+, from 59.9% in 1985 to 57.3% in 2000 compared with 19% to 9.8% for family size 1. Further, family size is directly related to the vulnerability to poverty or the likelihood of falling into poverty owing to exogenous shocks, e.g., typhoons and droughts (Reyes 2002).

Table 1: Poverty Incidence by Family Size (%)
Family Size	Poverty Incidence
	1985	1988	1991	1994	1997	2000
1	19.0	12.8	12.7	14.9	9.8	9.8
2	20.0	18.4	21.8	19.0	14.3	15.7
3	26.6	23.2	22.9	20.7	17.8	18.6
4	36.6	31.6	30.1	25.3	23.7	23.8
5	42.9	38.9	38.3	31.8	30.4	31.1
6	48.8	45.9	46.3	40.8	38.2	40.5
7	55.3	54.0	52.3	47.1	45.3	48.7
8	59.8	57.2	59.2	55.3	50.0	54.9
9 or more	59.9	59.0	60.0	56.6	52.6	57.3
National	44.2	40.2	39.9	35.5	31.8	33.7
Source: Orbeta (2004) based on NSO, Family Income and Expenditure Surveys, 1985-2000.

As expected, mean per capita income, expenditure and savings fall monotonically as family size rises (Table 2). Likewise, mean education spending per student drops from P5,558 for family size 1 to P682 for family size 9+, and average health spending per capita falls from P1,700 to P150 over that family size range (Table 3).

Table 2: Mean per Capita Income, Expenditure and Savings by Family Size, 2002
Family Size	Mean per Capita Income	Mean per Capita Expenditure	Mean per Capita Savings
1	39,658	33,885	5,773
2	25,712	20,858	4,854
3	21,342	18,307	3,035
4	18,429	15,480	2,950
5	15,227	13,159	2,068
6	12,787	11,416	1,371
7	11,147	9,341	1,806
8	9,259	8,168	1,091
9 or more	8,935	7,699	1,236
Total	14,280	12,252	2,028
Source: Orbeta (2004) based on Family Income and Expenditure Surveys, 1985-2000.
Table 3: Mean Education and Health Expenditures by Family Size, 2002
Family Size	Mean Education Expenditure per Student	Mean Health Expenditure per Sick Member	Mean Health Expenditure per Capita
1	5,558	2,437	1,700
2	3,135	1,969	922
3	2,243	2,124	802
4	1,787	1,464	438
5	1,558	1,454	336
6	1,090	1,311	299
7	858	940	206
8	1,081	744	166
9 or more	682	756	150
Total	1,369	1,400	466
Source: Orbeta (2004) based on Family Income and Expenditure Surveys, 1985-2000.

As noted in our earlier paper, “The Deepening Crisis: The Real Score on Deficits and the Public Debt” (August 2004), social sector services besides infrastructure have fallen victim to the fiscal crisis. National government expenditure on social services per capita has fallen sharply in real terms from P2,487 in 1997 to P1,999 in 2004 (Manasan 2004). For education the decline has been from P1,789 to P1,415, and for health from P266 to P141 over the same period. More specifically for education, annual real spending per student in public elementary and secondary schools has dropped precipitously from P8,439 to P6,554, with negative annual average growth rate, over that seven-year interval (Chart 3).

The prevalence of child labor rises, and school attendance falls, with the number of children in the family (Raymundo 2004). Moreover, the odds of a child becoming underweight and stunted are greater if he/she belongs to a household with 5 or more members (FNRI 1998). This partly explains why poverty tends to be transmitted and perpetuated from one generation to the next.

The average TFR masks the wide variance across wealth (asset) groups: 5.9 children for the bottom quintile, 3.5 for the middle quintile, and 2.0 for the top quintile (Table 4). Likewise, wanted fertility declines monotonically from the bottom to the top asset class: 3.8 for the bottom quintile, 2.6 for the middle, and 1.7 for the top. The large gap between actual and unwanted fertility among poor households (2.1 bottom quintile versus 0.9 middle and 0.3 top) suggests that family size adversely impacts on their living standards[4]. As expected, the actual-wanted fertility gaps are also evident by education level and urban/rural location.

Behind this gap is high unmet need for family planning services: 26.7% bottom quintile versus 15% middle and 12.4% top (Table 5). Hence, low contraceptive use or contraceptive prevalence rate (CPR) (any method): 37.4% bottom versus 52.7% middle, and CPR (modern method) of 23.8% versus 35.7% (Table 6). Poor households mostly depend on public sources of modern family planning methods (88% versus 74% among the middle quintile) (Table 7).

Table 4: Actual and Wanted Fertility (Number of Children) by Wealth Quintile, Education, and Urban/Rural Location
	Total Actual Fertility Rate	Total Wanted Fertility Rate	Difference
Wealth quintile
Lowest	5.9	3.8	2.1
Second	4.6	3.1	1.5
Middle	3.5	2.6	0.9
Fourth	2.8	2.2	0.6
Highest	2.0	1.7	0.3
Women’s education
No education	5.3	4.1	1.2
Elementary	5.0	3.3	1.7
High school	3.5	2.5	1.0
College or higher	2.7	2.2	0.5
Urban/Rural location
Urban	3.0	2.2