Charting Progress 4 – Productivity
Over time and across countries, differences in living standards ultimately come down to the differences in productivity. Productivity growth in developing countries, in turn, reflect two processes: structural changes in the economy; and adoption of new technologies and better practices from more advanced economies (the so-called ‘catch up’ growth). Bangladesh has been experiencing both processes over the past few decades.
Hungry times
For most people, macroeconomic indicators are gobbledegook — what does the difference between 5% and 8% GDP growth mean? For most people, economic indicators that matter are the ones that animate dinner table conversations — jobs and incomes, and the cost of living. In the advanced economies with higher quality data, it is jobs numbers that resonate most — one might not understand what GDP stands for, but it is very clear what a rise in the unemployment rate means if one’s neighbour has been laid off.
In developing economies with large informal sectors, however, quality employment numbers are hard to come by in real time. Data on the prices of essentials — proverbial chaal, daal, tel, noon — are much more readily available, as are wage rates of different types of workers. Mix those essentials and voila, there is a plate of khichuri. Using the data on prices and wages, we can calculate the number of plates of khichuri an average worker could afford a day.
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Political impact of remittances
Along with the garments industry and the NGOs, there is a broad consensus that remittances have played a key role in Bangladesh’s economic development over the past decades. Notwithstanding that broad consensus, the economic impact of remittances may be more nuanced than one might think, as I conjectured a long time ago:
Well, how about a stylised, and very speculative, story along this line — while RMG has meant women entering the formal workforce, migrant worker boom has sent a lot of risk-taking men overseas; aided by the NGOs and microcredit, households have smoothed consumption and invested in human capital of their children; but they have not invested in physical capital, avoided entrepreneurial activities, and have not pushed for a more investment-friendly polity.
We would want to explore this story further. We would also want to explore the income side of GDP, and tie it into a political economy analysis.
The remittance boom, for example, should see the labour share of the economy rise. Of course, the question is, what happens to the money that is remitted back? It’s reasonable to assume that unskilled labourers are from the poorer parts of the society. So, in the first instance, any remittance back to the villages is a good thing in that it reduces the direst type of poverty — that is it stops things like famine or malnutrition. But what happens after that? My tentative hunch is that a lot of remittance has been saved but not invested in a productive way, rather they ended up fuelling land/stock prices —this is an area that needs to be explored in detail.
Needless to say, I have not followed up on these questions. But at least the economic impact of remittances is something people have thought about. What about the political impacts? That’s the question Shafiqur Rahman of Oregon University explores.*
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Ramadanomics
Ramadan fasting is like no other Islamic ritual. In the month of Ramadan, those who never perform the pre-dawn Fajr prayer get up even earlier to eat, only to abstain until dusk. And after a month of that, even those who would otherwise never set foot in a mosque line up in unison to kneel towards Mecca. For an entire month, from cooking, attire, TV to intimacy — the very lifestyle of a billion plus people change. Except perhaps the aversion to pork, observance of, or at least respect to, the Ramadan fasting is arguably the most ubiquitous characteristic of Muslims.
Given its prevalence and ubiquity, Ramadan must have observable economic impacts. Exactly what might they be? In a fascinating paper, Filipe Campanile and David Yanagizawa-Drott of Harvard’s Kennedy School provide us with some answers.* Summary — fasting makes us happier, if poorer.
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Khichuri index
A staple of political rhetoric in Bangladesh is to ensure affordability of rice, lentil, oil and salt. Throw in a kilogram of coarse rice, 250 grams of red lentil, 40 ml soya bean oil and 10 mg salt and we get a rather bland plate of khichuri. CEIC Asia database provides monthly retail prices of these essentials in Dhaka with a lag. Currently, the latest data point is August 2014. Still, using the bland recipe and prices (and smoothing the data by taking a 12-month moving average), we can get a sense of how the price of our plate of khichuri has evolved over time — for example, when BNP was turfed out in January 2007, such a plate cost around 35 taka, which rose to around 60 taka when the Awami League returned to power in January 2009, and was around 70 taka when its five year term expired.
Of course, to say anything sensible about prices, we need to have a sense of income. From the same source, we can get daily wage of a skilled factory worker. Her wages went from around130 taka a day in January 2007 to over 210 taka two years later to over 300 taka further five years on.
Putting the two together, we can get what I am going to call the Khichuri Index — plates of khichuri an average industrial worker can buy in Dhaka. The chart below shows how the index has evolved between January 2000 and August 2014 (the period I have data for).
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Ideas that went nowhere…..
….. because life got in the way.
Okay, that’s a bit melodramatic. Let’s start again. It used to be the case that to have a professional career as an economist in America, you needed a PhD. That’s changing a lot. There’s a general glut of PhDs. And organisations such as the IMF are now more interested in people with practical experiences than half a decade or more of often impractical academic training. In any case, outside America, PhDs were always for those who wanted to pursue an academic career. So, other than the vanity of being addressed as Dr Rahman, I’ve never really seen much return from doing a PhD.
And yet, every now and then, I think about the ideas over the fold and wonder what might have been.
Demographic transition in Bangladesh
Like a match box full of sticks —that’s how the Farmgate over bridge was once described to me. It was the early 1990s, when six or so million people lived in Dhaka, while Bangladesh’s population was around 110 million. I can’t think of any match box that, once full, can pack in a significant rise in the number of sticks, and yet, Bangladesh has somehow found room for extra people. In the two decades since my visiting friend saw the teeming multitudes of Farmgate, the country’s population has risen to 150 million, and depending on how one counts, Dhaka is home to 15 or more million people.
The headcount, however, does not quite capture the fact that Bangladesh is going through a demographic transition. A transition that is perhaps as remarkable as, and probably related to the Bangladesh paradox. As Chart 1 shows, over the past three decades, population growth has slowed significantly and the fertility rate (the number of children each woman bears on average) has declined markably. Given the fertility rate is already close to the replacement rate of around 2%, it is quite possible that population growth may well slow even further from current 1% a year.
Decoding The Bangladesh Paradox — A Research Agenda
The macroeconomic fact is, in the last decade, under all three governments, per capita GDP have grown by around 4½ per cent a year. At that rate, average real (that is, inflation-adjusted) income doubles in 16 years. …. This is impressive stuff, for which every recent government deserves some credit.
That’s the conclusion from the post on real GDP per capita growth under different governments. Of course, real GDP per capita is a means to the end, not the end in itself. What we really care more about is the standard of living that higher real GDP per capita entails —that is, it’s the development record, and not just the growth, under different governments that we want to know.
This, however, raises two questions. First, how do we attribute to any particular government the growth and development record when policies under any particular government are likely to have long term consequences? And second, how do we explain the Bangladesh Paradox:
The belief that growth brings development with it—the “Washington consensus”—is often criticised on the basis that some countries have had good growth but little poverty reduction. Bangladesh embodies the inverse of that: it has had disproportionate poverty reduction for its amount of growth.
That quote is from a November 2012 Economist article. That article, and accompanying editorial, had a go at explaining the paradox. Joseph Allchin had a crack more recently at the NY Times. The suspects are usual: garments, remittance, NGOs. But we economists are a parsimonious lot, or so we like to think. We would like to know exactly what contribution each of these factors made, what was the channel through which the factors affected growth and development, what role, if any, did government policy play, and what all that means for future.
I haven’t seen a comprehensive analysis of the Bangladesh Paradox. And no, I am not going to provide the answer in this post. Rather, over the fold is a research agenda on how to analyse the Paradox.
Deshi workers in the Kingdom
Recently, The Economist published: “Bangladesh and Saudi Arabia: The revenge of the migrants’ employer,” on their website. The article tracks data over the last few years of Bangladeshi migrant workers to Saudi Arabia. The data is what it is, and it is fair to say that the sources can be trusted.
However, The Economist’s take on the matter, where the lower number of Bangladeshi workers migrating to Saudi Arabia can be attributed to retaliation by the Saudis to the war crimes trials (WCT) in Bangladesh that are now seeking the death penalty for leaders of Jamaat, may or may not be true. It’s not the only possible story. And I am not even sure it’s the right story. If one analyses the same data from a different perspective, the interpretation can be very different.
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