In its December 18, 2019 report, Bangladesh Bureau of Statistics (BBS) claimed that the overall poverty rate dropped1.3 per cent to 20.5 per cent in the Fiscal Year 2018-19 compared to the preceding FY while the extreme poverty rate dropped to 10.5 per cent from the preceding FY's 11.3 per cent. BBS officials claimed that these estimates were based on economic growth rate and its impact on the state of poverty in the country.
After reading the report, I tried to relate the 8.15 per cent GDP growth to 1.3 per cent poverty reduction but failed to demystify BBS's claims. I am wondering how the BSS statisticians assessed the impact of growth on poverty level in the country. Obviously, these are guesstimates which are subjective statistics, and depend largely on statisticians' regression (forecasting) models and may or may not have much factual bearing with reality on the ground.
Several cross-country and individual country statistics consistently provided robust evidence that faster and sustained growth is the single most important precursor to poverty alleviation. A 14-country cross country study in the 1990s had predicted that a 1.0 per cent increase in per capita income alleviated poverty by 1.7 per cent. Among these countries, Vietnam's experience was particularly remarkable where poverty was halved by 50 per cent from 58 to 29 per cent between 1993 and 2002.
While Bangladesh has been admired for halving the poverty rate since 2000, the inescapable fact is that poverty trap is still deprecating the life of one-fifth of the country's population with over 20 million living in extreme poverty (FE, December 18, 2019). The large percentage decrease in poverty with economic expansion in Vietnam and Bangladesh and other poverty-ridden countries is realisation of bygone days, which cannot be replicated without causing country-wide inhibitive negative externalities such as pollution, industrial waste pile-up, traffic congestion etc. Those declines were achievable due to borderline poverty-ridden people moving out of poverty at a faster rate.
Lowering poverty level, below the currently estimated 20.5 per cent will need targeted policies while standing ready with contingencies to deter fresh addition to poverty line through joblessness among subsistence-level income earners. Besides, the parameters of forecasting models are not time invariant; they are functions of time, technology and changing information.
Any changes (increases/decreases) in remote rural poverty are not easily visible while rising number of slum inhabitants in Dhaka, Chattogram and other highly populated cities remind us that destitutions of the have-nots are not diminishing soon. One wonders, if the recent newly sanctioned 9 (nine) public work projects will alleviate even a modicum amount of suffering of the slum dwellers (FE December 18, 2019). Implemen-tation of these projects, except highway widening, would do little to make jobs available to poverty ridden unskilled workers. Expenditures on these projects would add to GDP (gross domestic product) but very little of that would trickle down to the unskilled job seekers. No money-making contractors would like to hire unskilled labour unless there is a contractual requirement to do so.
The nexus between economic growth and poverty alleviation is nonlinear, that is, there is no one-to-one inverse correspondence between the two. The 14-country study quoted above found poverty falling in 11 countries with substantial growth while rose in three that experienced low growth or stagnation. Economic literature argues that the impact depends on (a) what proportion of growth gets distributed or trickles down to the poverty ridden groups, (b) the channels of trickling down of that growth, (c) the level of inequalities that are prevailing in an economy, and (d) the prevailing rate of inflation.
Evenly distributed benefits of growth in both developed and developing economies are few and far between. This was confirmed by the International Monetary Fund (IMF), World Bank (WB) and the Organisation for Economic Cooperation and Development (OECD) studies in the last decade. In most of their studies, income inequality among the population was the main stumbling block to poverty alleviation. On the question of growth sharing and poverty reduction, Martin Ravallion, the former Head of research at the WB, reported that "a 1 per cent increase in income in the most unequal countries produces a mere 0.6 per cent reduction in poverty; however, in the most equal countries, it yields a 4.3 per cent cut." A study by OECD economists found that the top 1.0 per cent of income earners between 1976 and 2007 absorbed 47 per cent of income growth in the US, 37 per cent in Canada and 20 per cent in both Australia and the UK. These statistics were worrisome to all quarters since a gaping inequality is known to culminate in welfare loss to societies over time. Did any improvement happen after a decade or so? Not much to say the least.
Growth policies targeted for poverty reduction must be inclusive - one that facilitates the creation of income opportunities to all segments of society while ensuring equality and fairness. Exclusive growth policies, on the other hand, are politically/ideologically driven to benefit a select group or sector of the population at the dismay and deprivation of others. For example, the $1.5 trillion 2016 Republican tax cut disproportionately benefited the American millionaires and billionaires. In the United Kingdom (UK), the relative income gap has widened during the growth years of 1992 to 2008.
To get some indirect insight into the channels through which economic growth trickles down, one may examine the GDP measuring approaches: The Expenditure Approach and The Income Approach.
GDP = C + I + G + (X - M), where C = Consumption, I = Investment, G= Government (X - M) = exports - imports (net export).
The Income Approach:
GDP = W + R + I + P + T + D + F
Where W = salaries and wages, R = rental income, I = interest income, P = profits, T = sales tax, D = depreciation of physical capital, and F = foreign income (income earned by Bangladesh citizens abroad minus income earned by foreigners working in Bangladesh). The measure of GDP computed by factor payments as above with adjustments for T, D, and F is known as gross national income (GNI).
Both approaches to computing GDP generally yield similar results. For Bangladesh though, income approach produces higher number compared to the expenditure approach due to large net foreign income inflow.
The income approach sheds some insights about the channels through which income growth trickles down to the working population and the absence of any direct channels of benefit to the poverty ridden unemployed millions. In the absence of data for Bangladesh economy, one can have a glimpse of the four factors' (W, I, R, P) contribution to GDP of the US economy. In the United States (US), labour (wages and salaries) is the predominant factor of production, accounting for nearly 66 per cent of total factor payments, business profits in second position with 25.5 per cent while the return on land (R) is 4.5 per cent, and interest income accounts for 3.5 per cent.
The contribution of foreign income flow in alleviating poverty in Bangladesh is well documented. Of the four factors, high profits certainly help business expansion and job creation. However, these jobs are not meant for unskilled workers or people in poverty. The most important factor 'W' lumps wages, salaries, heath and retirement benefit of very low wage workers to the highest salaried public and private officials. If the policies are to narrow income inequality, then the strategy is obvious: raise the wages/salaries of low wage workers disproportionately compared to all others.
What about the 20.5 per cent citizens who have either no job or may be working on some odd jobs to buy 'two small cups of chal and dal" while not foreseeing what is in store for tomorrow? The appropriate strategy is inclusive growth policies having a longer-term perspective in which emphasis is placed on education and skill development, creating productive employment opportunities, in addition to a policy of income redistribution through government cash handouts and food support (such as food stamps as in the US).
The severity of poverty varies from region to region in the country. Understandably, physical head counts are not feasible. However, making guesstimate using forecasting models are often misleading. Therefore, BBS may consider making the estimate by using the extreme region as a microcosm for the entire country. That will eliminate any potential statistical discrepancies of underestimation to the benefit of the destitute people in society.
Finally, inflation can play havoc to both the borderline and extreme poverty-inflicted people. Per capita GDP increase has no impact on purchasing power of people who have little or no income. Therefore, inflation can easily drag more people into the poverty counts. Does BBS's poverty estimating model account for any impact of inflation on poverty?
Abdullah A Dewan, formerly a physicist and a nuclear engineer at Bangladesh Atomic Energy Commission (BAEC), is Professor of Economics at Eastern Michigan University, USA.