Syncing poverty and growth statistics
Though it’s been over half a century since I took my first college course in it—later I did advanced degrees in it, taught it, and researched on it—I still harken back to the first definition of economics that I learned:
Economics is the study of how goods and services are produced, AND how they are shared, by the people.
This is my “kindergarten definition.” As in: “All I really know about economics is what I learned in kindergarten.” It is very old, very simple, and still very valid.
Economics is not only about production, but also about distribution. Production and distribution are equally important.
An economy is not inanimate. It is not a thing; it has people. People, as producers and as users of goods and services, are at the center of the definition. Economics is a social science because production and distribution are governed by social relations among people.
Economic development consists of more goods and services being produced, and also being more fairly shared, by the people. An increase in production, without greater fairness in its sharing, is not a definite gain for the people.
Economic development is sustainable when the people provide for continuity in the resources with which to keep on producing, and sharing fairly, such goods and services in the future. These resources, generically called capital, come in natural, human, social, institutional, technological and other forms. The key to future fair sharing is fair ownership, individually or collectively, of the various forms of capital.
Unfortunately, the sharing side of economics is very neglected. In my view, the failure to sync distributional statistics with production statistics is much to blame for this.
Kindergarten economic statistics. In principle, the statistics gathered and published about an economy should cover the production and distribution aspects in equal measure. Statistical parity of these two aspects is essential for the people, in a democratic setting, to assess what is happening to economic development.
Just last May 30, the National Statistical Coordination Board (NSCB) was proud to announce strong growth in the gross domestic product (GDP) by 7.8 percent, as well as in the gross national income (GNI) by 7.1 percent, between the first quarter of 2012 and the first quarter of 2013, after correction for inflation. (GNI is more relevant since it pertains to the Filipino people, and includes remittances from Filipinos abroad, whereas GDP pertains to Philippine territory, and includes non-Filipino entities.)
Naturally, such good news begs for counterpart statistics on whether the common Filipino gained from the growth over 2012Q1 to 2013Q1. Did poverty decline in that period? This question cannot be answered from official figures, since the newest official poverty report, “Poverty incidence unchanged, as of first semester 2012” (www.nscb.gov.ph, 4/23/2013), is a comparison of last year with 2009. Thus, its reference period is out of sync with the new GDP/GNI report.
The problem is that the growth statistics are quarterly, whereas the official poverty statistics are triennial. With data on GDP so plentiful, it’s no wonder that many institutions, public and private, constantly analyze it and compete in forecasting it. With official data on poverty so scarce, it’s also no wonder that they don’t research on it. (I think they do suspect that the growth actually trickles up to the rich, and not down to the poor.)
To give equity in distribution the same importance as growth in production, it is common sense that poverty statistics should also come out quarterly. (The official statistics are currently planned to be annual starting 2013, but I think they may as well go semestral already, since the last official poverty report was for the first semester of 2012.)
The need to sync distribution with production statistics is precisely why SWS tracks poverty quarterly. The percentage of families self-rated as poor was 55 in 2012Q1, 51 in 2012Q2, 47 in 2012Q3, 54 in 2012Q4, and 52 in 2013Q1 (“First Quarter 2013 Social Weather Survey: Families rating themselves as mahirap or poor at 52%,” www.sws.org.ph, 4/26/2013). Simple eyeballing of these numbers does not indicate much impact of the production growth on the poor.
Properly estimating the impact of production growth on poverty is not that simple, of course. The econometrics would involve estimating coefficients of models involving not only GNI and poverty, but also relevant variables like sectoral value-addeds, public spending for social services such as education, health, conditional cash transfers, and retirement benefits, unemployment, underemployment, price inflation, and wages. It would call for testing alternative mathematical forms (since relationships might not be linear) and time-lags (since effects of one quarter’s stimulus might be delayed, and/or last for multiple quarters).
What is essential is having a large number of observations over the time period to be analyzed, to allow enough so-called degrees of freedom for the many tests to be done. Using the self-rating approach, the Social Weather Surveys have produced 85 quarterly data points of poverty from 1992 to 2013; they will keep on producing them, indefinitely.
Producing poverty data from opinion-poll-like surveys is both valid and economical. I recommend it to research institutes everywhere.
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