Sources of inequality in the Philippines: Insights from stochastic dominance tests for richness and poorness

• Author: Maria Rebecca Valenzuela,Wing‐Keung Wong,Zhen Zhen Zhu
• Date: 01 October 2020
• DOI: http://doi.org/10.1111/twec.12772
• Published date: 01 October 2020

SPECIAL ISSUE ARTICLE

Sources of inequality in the Philippines: Insights

from stochastic dominance tests for richness and

poorness

Maria Rebecca Valenzuela

1

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Wing-Keung Wong

2,3,4

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Zhen‐Zhen Zhu

5

1

Queensland Productivity Commission & School of Economics, University of Queensland, Brisbane, QLD, Australia

2

Department of Finance, Fintech Center, and Big Data Research Center, Asia University, Taiwan

3

Department of Medical Research, China Medical University Hospital, China

4

Department of Economics and Finance, the Hang Seng University of Hong Kong, Hong Kong

5

School of Statistics, Shandong University of Finance and Economics, Jinan, Shandong, China

1

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INTRODUCTION

The Philippines has been recently described as one of the most dynamic economies in Asia,

1

with

GDP growth rates registered at 5.9% and 6.8% in 2015 and 2016 and with projections of continued

strong growth in the next 3 years. At the same time, however, both the World Bank and the

SWIID

2

databases—key sources of cross‐country inequality measures—rank the Philippines as one

of the most unequal societies in the region. Furthermore, both databases show that while most of

its Asian neighbours where the inequality levels have declined over time, the Philippines's Gini

inequality index varied very little around its 50‐year high average of 0.44. This indicates that the

country's level of inequality was not only relatively high but was also one which has seen the least

improvement over the long term.

The persistence of a highly skewed income distribution in a revitalised Philippine economy has

raised renewed concern for many analysts and policymakers alike, particularly that the country has

a social transfer system that is largely deficient or even absent in some local domains. One main

worry is that growth will not be sustainable—a common fear that is not without sound theoretic

underpinnings. The economic literature has shown that inequality can hamper growth by promoting

expensive fiscal policies (Alesina & Rodrik, 1994; Perotti, 1993; Persson & Tabellini, 1994); by

inducing an inefficient state bureaucracy (Acemoglu, Ticchi, & Vindigni, 2011); by hampering

human capital formation (Galor & Moav, 2004; Galor & Zeira, 1993); by promoting political insta-

bility (Bénabou, 1996); or by undermining the legal system (Glaeser, Scheinkman, & Shleifer,

2003). Particularly relevant for the Philippines is the multicountry panel data study of Barro

(2000) which showed that higher inequality tends to retard growth in poor countries and encourage

growth in richer places. And deepening this concern is the time dimension analysis in Halter,

Oechslin, and Zweimuller (2014) which finds that higher inequality helps economic performance

1

World Bank (2017).

2

Standardized World Income Inequality Database v5.1 (Solt, 2016).

Received: 15 November 2016

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Revised: 18 June 2017

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Accepted: 10 December 2018

DOI: 10.1111/twec.12772

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© 2019 John Wiley & Sons Ltd wileyonlinelibrary.com/journal/twec World Econ. 2020;43:2650–2673.

in the short term but reduces the growth rate of GDP per capita farther into the future. All these

imply that the positive economic outcomes achieved from the last few years of robust growth in

the Philippines may well be short‐lived.

Given such compelling evidence foreshadowing large negative effects of sustained high

inequality in the Philippines, it is imperative that this problem—the persistent gap betwee n the

rich and the poor—be directly addressed. It will, however, be hard to identify the appropriate

policy solutions without a full and clear understanding of the problem's underpinnings. What are

the causes of inequality in the Philippines? To what extent do national level measures capture

the rich–poor income gap across space and population groups? Are there structural factors that

help sustain high inequality levels? What is the role of fixed and time‐varying factors in its per-

sistence? To derive such understanding is of significant and immediate importance for at least

two reasons: first, not only will it be difficult to equalise opportunities in highly unequal soci-

eties, but the longer the duration of high inequality is, the greater the determination, resources

and time that will be required to equalise opportunities and restore economic balance. Pro-

grammes to improve income mobility, for example, will take longer to gain traction the wider

the gap in health and education outcomes across the population. Second, high inequality is self‐

reinforcing over time—as may be seen in the way wealth begets political power, which begets

more wealth, and more political power. For a country like the Philippines where there are mini-

mal checks and balances in the political system and where corruption thrives, such retrogression

is bound to happen at a faster rate over time—resulting in greater harm to greater numbers of

people.

In this paper, we revisit the issue of relative welfare and inequality in the Philippines and exam-

ine trends in the distribution of welfare in the recent past. Using a new approach and the latest

available data for the country, we undertake a detailed analysis of income and expenditure distribu-

tions in the Philippines to assess relative welfare changes in the country from 2000 to 2012. Our

paper will provide the literature with a unified and consistent framework of analysis of distribu-

tional welfare in the economy over time. We also wish to assist policy with our results. A major

contribution of the paper pertains to the use of stochastic dominance (SD) techniques in the distri-

butional analysis. SD analysis allows comparisons of full distributions of outcomes, and as such,

offers great capacity for eliciting deeper insights into the distributional changes over time and

space. Use of SD techniques avoids the common pitfalls of using singular indices, particularly the

lack of universal acceptance of value judgements of the underlying welfare functions which have

led to contradictory results in the past. For this paper, we will implement SD tests for richness and

poorness developed in Chow, Valenzuela, and Wong (2016) and use the five latest available

rounds of the Philippines's Family Income and Expenditure Survey data. Further, we will employ

decomposition techniques within our SD approach to identify structural, spatial and demographic

sources of change in inequality levels and drivers of persistently high inequality in the Philippi nes

over time. Our study updates inequality estimates for the country.

This paper has the following structure. After the brief introduction and overview in Sec-

tion 1, the paper proceeds with Section 2 which provides a conceptual framework for the

stochastic dominance approach to income distribution analysis. Here, the aim is to distinguish

between the standard (ascending) stochastic dominance approach and the new (descending)

stochastic dominance approach. Section 3 introduces and describes the SD tests used in our

analysis, their distributional characteristics and the bootstrap technique used. Section 4 presents

the data, variable definitions and some summary statistics. Section 5 presents the empirical

results, including our statistical analysis and economic policy discussions. Secti on 6 concludes.

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