#FromMyReadings, Issue 5, 2021
Exploring Threshold Inflation Rates for India; Using the Past to Understand the Present; Informal Work and Maternal Health in Delhi
[Before you read on, I urge you to take a look at the beginning of my earlier post and donate to those causes if you can. India can do with more COVID-19 relief efforts. Thank you.]
1. Exploring Threshold Inflation Rates for India (Dholakia et. al)
The Reserve Bank of India’s Development Research Group (RBI DRG) released a new publication in May, (henceforth Dholakia et. al) which explores the idea of ‘threshold inflation’ in Indian contexts.
Macroeconomists generally agree that a small amount of price rise is good for the economy, but inflation becomes a problem once it crosses a certain limit. This limit is what threshold inflation is supposed to represent — it’s the inflation rate beyond which, price rise becomes detrimental to economic growth.
The question worth asking is — can an economy have an ideal threshold inflation rate, that policymakers can aim for to increase economic growth? The existence of such a rate can be very useful, as it allows central bankers to plan their targets (especially long-term targets) better. This is what the RBI paper’s authors seek to understand.
This is a fairly technical paper requiring some knowledge of macroeconomic theory. The authors’ central argument is that a threshold inflation rate can indeed be defined. For any economy (they say), the threshold inflation rate is equal to
“…the long-run equilibrium rate of inflation that maximises the steady state growth (SSG) within the relevant range of values”.
There are three points a layperson must note before unpacking that jargon-laden definition.
First, it’s important to remember that terms like ‘inflation’, ‘economic growth’ and ‘long run’ have multiple definitions within formal economic practice. Each of these definitions is narrow, technical, and meant for specific situations. They come loaded with a history of discourse which distinguish it from similar-sounding terms. Thus, a term like “steady state growth” is different from more common ideas of growth, such as year-on-year GDP growth rates (which a layperson is more likely to read about in a newspaper).
Second, a huge amount of economic practice involves making choices between difficult options (what is usually called a ‘trade-off’). If you have studied Operations Research in business school, you would have already encountered two types of trade-offs — maximisation (increasing the value of something good, given specific constraints) and minimisation (decreasing the impact of something bad, given specific constraints). In this paper, the authors talk about threshold inflation “maximising” steady state growth, subject to certain constraints. For any reason, if these constraints change, then our frameworks, approaches, and conclusions about threshold inflation need to change as well.
Third, it’s really important to remember that economics is far from being a settled science, particularly in macroeconomics. While the field is dominated by a few schools of thought, there is considerable debate and contention over the validity of basic frameworks and models often used by practitioners. Very often, economic crises (like the 2008 Recession or the 1970s American Stagflation trend) can trigger re-evaluation. Therefore, we must keep in mind that the ideas discussed in papers like these are always works in progress, subject to re-evaluation as more knowledge comes to light.
Threshold inflation for India has been explored before, even within the Reserve Bank. Dholakia et. al has two useful tables — one that documents theoretical, and another that documents empirical investigations into threshold inflation. The authors argue that recent theoretical literature (see Table 1 above) make a case for GDP growth rates that can go both up and down as inflation rates increase (technical term: a ‘non-monotonic’ relationship).
If valid, this implies that there is some point where growth rates reach a maximum level (in relation to inflation rates) before declining. This point would be a threshold level for inflation.
If theory suggests that threshold inflation rates are possible, then what is that rate for India? The table on empirical investigations (see table above) provides us with a summary of inquiries into this. As with most macroeconomic studies, empirical investigations are complicated by differences in the availability of data and types of frameworks and methods employed by the scholars. Should one use annual inflation data to calculate estimates of threshold inflation? Monthly? Quarterly? Should we measure wholesale prices or retail prices? What kind of econometric regression should investigators employ? Each question is answered differently by different investigators, leading to different conclusions.
However, this is not a bad thing. On the contrary, if multiple approaches and methods lead to a fairly similar band of results, then that’s usually better than a single framework yielding a single value. The table above suggests that most scholars recommend threshold inflation rates for India to be between 4% and 6%, if we measure wholesale prices. Adding to this literature, Dholakia et. al employ a cross-country comparison approach from which they derive India-specific estimates (this is too technical to explain here— please see this section of the paper, if interested).
Here, they argue that threshold inflation depends on two key factors — the country’s Fiscal Deficit (FD) and its Current Account Deficit (CAD), measured as percentages of the GDP.
Essentially, their estimates of a threshold rate implies an annual consumer price index measuring between 6.08% and 6.15%, depending on fiscal deficit and CAD levels. These estimates are slightly on the higher side compared to most other studies in Table 2 above. Dholakia et. al suggest that higher fiscal deficits, assuming CADs between 2 and 2.5% of the GDP, lead to lower threshold inflation rates, when measuring annual consumer prices. In an ideal scenario, a low fiscal deficit of 5% of GDP, with a CAD of 2% can lead to an inflation rate of 6.15% and a GDP growth rate of 7.74%.
Dholakia et. al’s claim to speciality however, is in proposing a theoretical model that links fiscal deficit and current account deficit levels to threshold inflation and GDP growth. If more studies in the future validate their claim, it can provide policymakers with a useful framework by which they can estimate the impacts of fiscal and trade policies upon GDP growth rates via inflation. Once again however, please note that more studies and observations are needed before accepting the model as standard practice.
On an off-note: India’s Wholesale Price Index (WPI) is touching 13%, well above any threshold level noted in Table 2. However, please note that the WPI is not directly comparable to Dholakia et. al’s study, since the authors use consumer prices (the WPI measures wholesale prices). That being said, a 12.94% Year-on-Year jump in WPI is quite worrying.
2. Using the Past to Understand the Present (Ed Glaeser)
Urban economist Ed Glaeser has released a new working paper at NBER, where he asks what developing cities today can learn from the cities of the past. He points out that many common urban problems today, such as pollution, traffic congestion, and disease contagion, are not new issues and have affected cities for centuries.
He proposes using the past to better understand the present and outlines some key lessons from studying cities in history:
- Political power shapes drives growth of the world’s largest cities rather than commerce;
- Transportation infrastructure used to be more influential in shaping cities in the past (due to enabling market access), but its power has declined today;
- Infrastructure functions best when combined with incentives for adopting sewers but discouraging highways;
- In the west, cities depended on a nexus of property rights that are weak in other developing cities of the world;
- Local conditions determine the best choice for institutions that manage infrastructure.
I can see scholars from other disciplines rolling their eyes about economists saying the same things they’ve been saying for years. This may be particularly true for Lesson 1. That politics shapes space is now fairly well-established among urbanists (see Neil Brenner’s work on rescaling of statehood for example), and historians and urban planners have long studied (among other examples) Hausmann’s Paris as an example of how big cities can be shaped by political power, often far more than economy or trade.
However, Glaeser’s paper nevertheless carries value (see point 3 of my earlier post, where I’ve talked about people from other fields entering established domains). Some useful observations early in the paper are on the role of transportation technology. In a style reminiscent of Paul Krugman, he mentions how the invention of motor trucks has allowed goods to be transported directly to bigger cities, bypassing mid-sized towns along the way, thereby leading to a greater concentration of megacities in our current age.
I won’t go too much into the rest of the paper — it’s a fairly easy read and I strongly recommend laypersons to go through it for themselves.
However, I do want to say this paper caught my eye for its central argument — of using historical data (data going back centuries) to understand the present. I believe this to be an underrated methodology in both economics and urban/regional studies, with some fascinating uses, yielding interesting insights. What I’ve found particularly useful is its ability to place our present conditions within gigantic timescales, allowing us to appreciate our current predicaments within broader contexts.
Natural scientists, especially in geology, paleontology, and climate science have mastered this technique, leading to the now-famous framing of our times as the Anthropocene. In recent years, with the rise of interdisciplinary practices, this practice has spread to other fields as well. I was particularly intrigued by a book Ten Thousand Years of Inequality: The Archaeology of Wealth Differences edited by Dr. Timothy Kohler, an anthropology professor at Washington State University. The book explores research and methods to place current debates on inequality within the context of the entire Holocene era starting about 12,000 years ago.
I find the book fascinating for both its endeavour to place a contemporary political debate within a larger historical time-scale, as well as the use of archaeological and anthropological methods to understand an economic issue. I can only hope more such methods are explored and refined in the years to come.
3. PLUG | Breastfeeding knowledge and practices of working mothers in the informal economy in New Delhi (Antara Rai Chowdhury, Aditi Surie, Gautam Bhan)
My colleagues at the Indian Institute for Human Settlements have released a paper on a study they conducted before the pandemic, where they surveyed women workers in the informal economy of Delhi with young children.
The study aimed to understand how the nature of informal work can shape maternal practices like breastfeeding. Among their findings, they discovered that informal workers were more likely to go back to work within six months of birth, leading to early weaning of the children. Furthermore, the lowest paying category of informal work— home-based work — was strongly associated with exclusive breastfeeding. More broadly, the study suggests that the nature of informal work can shape maternal and child health practices. The authors also outline some probable interventions which could work towards improving health conditions for both mothers and children.
Since this was written by my colleagues, I’m not going to comment on the paper here. I’ll send them any feedback via institutional channels. However, I will point out that these arenas of interdisciplinary research highlight the importance of linkages between work and home, economy and society. Eventually, economic planning and policy design cannot afford to ignore these links.
