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Understanding Inflation and Controlling It

Inflation management is one of the hardest tasks an economic policymaker has to undertake. It would appear at first sight that one can rely entirely on common sense to carry it out. But that would be a mistaken notion. While inflation policy does require judgment and intuition, it is essential that these be backed up with statistical information and an understanding of economic theory. This paper tries to bring together the formal analytics that underlie inflation policy. It surveys some of the standard ideas and also questions some of them and, in the process, tries to push outwards the frontiers of our understanding.


Understanding Inflation and Controlling It

Kaushik Basu

Inflation management is one of the hardest tasks an economic policymaker has to undertake. It would appear at first sight that one can rely entirely on common sense to carry it out. But that would be a mistaken notion. While inflation policy does require judgment and intuition, it is essential that these be backed up with statistical information and an understanding of economic theory. This paper tries to bring together the formal analytics that underlie inflation policy. It surveys some of the standard ideas and also questions some of them and, in the process, tries to push outwards the frontiers of our understanding.

This paper is based on the first Gautam Mathur Lecture that was delivered in New Delhi on 18 May 2011 at the invitation of Santosh Mehrotra. I am grateful to Montek Singh Ahluwalia for his extensive and valuable comments following the lecture. In writing this paper I have benefited greatly from discussions with Surjit Bhalla, S Bhavani, Anil Bisen, Satya Das, Dipak Dasgupta, Supriyo De, R N Dubey, Russell Green, Vijay Joshi, Kalicharan, Rajiv Kumar, Ken Kletzer, Rajnish Mehra, Dilip Mookherjee, Sudipto Mundle, Debraj Ray, Rajashri Ray, T Rabi Sankar, Partha Sen, Nirvikar Singh and T N Srinivasan. I also thank Rangeet Ghosh and Shweta for research assistance.

Kaushik Basu ( is chief economic adviser, Ministry of Finance, Government of India.

1 Introduction

nflation is one of the most dreaded and most misunderstood of economic phenomena. We know from experience, combined with cogitation, that the prices of commodities will, over time, rise and fall in response to the pulls and pushes of d emand and supply. The failure of a particular crop or a sudden fad for a certain kind of clothing can cause the price of that crop or the cost of that kind of clothing to rise, just as an unexpected glut in the supply of onions will cause a fall in its price. These price movements are the market’s way of signalling to consumers that they should consume less of the commodity in short supply and more of the goods available in plenty, and to producers to produce more of what is in short supply and less of what is a bundant. To even out these ebbs and flows of prices would be folly, as we know from countless examples of misdirected g overnment interventions.

However, inflation has little to do with these changes in the relative prices of goods and services. It refers instead to a sustained rise in prices across the board; that is, a phenomenon where the average price of all goods is on an increasing trajectory for a stretch of time. Of course, this may be accompanied by changes in relative prices. For the common person, there is something threatening about inflation, especially on occasions when the rise in prices of goods is not matched by an equivalent i ncrease in the price of labour.

Inflation has been with humankind ever since we moved away from barter to the use of mediums of exchange, such as paper money, precious metals or even cigarettes, as happened in a prisoner of war camp during the second world war (Radford 1945). While it is true that we do not fully understand inflation and to that extent it remains a threat, what is comforting is that years of data collection and theoretical research have given us deep insights into this troubling phenomenon. And even though we do not fully understand its origins, as in the case of the emperor of all maladies, we have developed techniques and policy interventions that can control it. In using some of these antidotes, there is good reason to be cautious when deciding what dose to administer because each such policy intervention comes with side-effects. But it is testimony to the advance of economics as a science that the spiralling hyperinflations that occurred ever so often till even a few decades ago now seem to be banished to the history books.

Inflation is an emotive matter and it gives rise, understandably, to popular resentment. Yet, its solution cannot be left to “popular cures”. Those will only be as successful in controlling it as witchcraft was in controlling illnesses in the 16th and 17th centuries. Fortunately, despite many caveats, the science of inflation has made huge strides in recent years. The aim of this paper is to

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draw on these recent advances, point to some of the gaps in our knowledge, and show how at least some of these gaps can be bridged. It moves away from the everyday fire-fighting problems of inflation, away from what inflation will be the next week or the next month, and away from whether the repo rate will rise or fall over the next few six-week slices. Since those questions asked every few weeks elicit broadly the same answers, such a discussion adds little to our understanding of this intriguing e conomic malady.

I wish to use this occasion to mull over some of the deeper and more conceptual questions pertaining to inflation and its management. Such an exercise may not have any bearing on what policy we adopt next week or even next month but, in the long run, by advancing our understanding of inflation, it can yield benefits that are disproportionately high. If today we do not have to worry about the hyperinflations that shook Europe just before and after the second world war and continued to send shivers down the spines of Latin American economies well into the 1990s, it is because analysts, mainly in western, industrialised nations, beginning with John Maynard Keynes in the 1930s, paused from everyday firefighting to ask foundational questions about what gives rise to this emperor of economic maladies and what policies are best suited to arrest the run of this malignancy.

Many of the policies that we routinely use nowadays without sparing much thought are the outcome of research and contemplation carried out by economists of an earlier era. If today we do not have to worry about our 9% inflation zooming up to 30% or 100% or even a trillion per cent, as happened in Hungary in 1946 or Germany in 1923, it is because of the march of ideas and science. In this advance of fundamental ideas, most of the contributions have come from Europe and the US. That in itself is not a matter of concern. Knowledge generated anywhere is knowledge and of value to all of us. At the same time, the context matters in shaping our focus of attention. As has been pointed out in the case of medical science, our knowledge of tropical illnesses has not progressed far enough because these are of concern to the tropics and not to industrialised nations. Even in economics there are peculiarities that are specific to different regions and nations at different stages of development. It is therefore important to conduct fundamental analytical research on inflation when the backdrop is an emerging market economy such as India’s.

That is the spirit in which this paper is written. As such, it b egins with a brief description of the inflationary experience of India with some comparative descriptions from other nations. The analytical sections are organised as follows. Section 3, w ritten in the spirit of a digression, draws attention to a peculiar

– almost paradoxical – dilemma that government agencies entrusted with the twin tasks of monitoring inflation and controlling it face. The remaining three sections are concerned with policies for controlling inflation. Section 4 deals with income redistribution and inflation, Sections 5 and 6 with macroeconomic demand management and inflation, and Section 7 with the problems of inflation management in a globalised world and the scope for action by multilateral organisations such as the Group of Twenty (G20).

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2 Inflation in India

Before getting into an analysis of inflation, it is useful to have the basic facts on the table. India is right now in the midst of an inflationary episode that has gone on for 17 months. It began in D ecember 2009 when wholesale price index (WPI) inflation climbed to 7.15%,1 and continued to rise, peaking in April 2010 at just short of 11%. Thereafter, it has been on a broadly downward trajectory. But what has caused some concern again is that there was a small pick-up in inflation in December 2010 and that the movement of the downward trajectory has been disappointingly slow.2 Before this 17-month run, we had one year of negligible inflation. But just prior to that there was another rally from March to December 2008, when WPI inflation hovered in and around 10%. Before these two rallies in quick succession, India had very little inflation for a dozen years. There were occasional months when inflation would exceed 8% but not once did it go into double digits during these 12 years of relative price stability.3

For reasons of completeness it may be mentioned that independent India’s highest inflation occurred in September 1974 when it reached 33.3%. Arguably our worst inflationary episode was from November 1973 to December 1974 when inflation never dropped below 20% and was above 30% for four consecutive months starting June 1974. Table 1 in the Appendix (p 64) gives the i nflation data for the WPI and food prices from 1971 to the most r ecent available. What is good performance and bad performance depends on the yardstick used. Even during the dozen years of price stability, we had more inflation than virtually any industrialised country in recent times, but in comparison to most emerging market economies and developing nations in the world, India’s performance was creditable.4 One reason for the concern with the inflation of the past 17 months is that we had price stability from the mid-1990s to early 2008. This concern has led to talk of runaway inflation and hyperinflation. It is, however, important to get the perspective right.

We are nowhere near hyperinflation – usually described as inflation over 50% per month (Cagan 1956). The world’s biggest inflations occurred in Europe, once around 1923 and again around 1946. The record is held by Hungary from August 1945 to July 1946. During these 12 months, prices rose by 3.8 × 1027 times. That is, what cost 1 pengo on 1 August 1945 cost 38,000 … (26 such zeroes) pengos on 31 July 1946. In August 1946, the pengo was replaced with the forint in an effort to shed the trillions of zeroes that were needed to express prices in pengos. Comparable inflations occurred in Russia from December 1921 to January 1924, in Greece in 1943, in Zimbabwe in 2008, and in Germany in 1923. The German hyperinflation of 1923 may well be the most analysed and diagnosed inflation. It played havoc with the economy, created political tensions that contributed to the rise of Nazism, and also caused psychological disturbances. Doctors in Germany in 1923 identified a mental illness called “cipher stroke” that afflicted many people during the height of hyperinflation. It referred to a neurotic urge to keep writing zeroes and also to a propensity to meaninglessly add zeroes when responding to routine questions, such as saying two trillion when asked how many children a person had (Ahamed 2009).

Not quite as large as these European inflations but nevertheless staggeringly big were the ones that occurred till two or three decades ago in many Latin American countries (see Garcia, Guillen and Kehoe 2010). Being closer to our times, they may have greater relevance to us. One country that has coped with mega inflations, many times larger than what we have in India, but seems to have stabilised and now has one of the well-run economies among emerging market economies is Brazil. Between 1962 and 1997, the Brazilian economy did not have a single year when inflation was in single digits. There were only two years (1973 and 1974) when inflation was below 20%. The really bad period was 1988 to 1994 when prices increased close to 2000% per annum on an average. Brazil’s experience gives us some insight into what inflation does to growth. The data suggests that when inflation is below 10%, there is little correlation between the rate of inflation and that of growth. But at higher levels, inflation is usually associated with lower growth, especially when it starts at a high level and rises even further. During the six hyperinflationary years mentioned above, growth suffered a setback with gross domestic product (GDP) growing at negative rates in three of them. But it has to be noted that there are examples of nations sustaining more than 10% inflation with very high growth over multiple years.

Asian countries have in general had more stable prices. South Korea, which has grown at astonishingly high rates from the late 1960s to recently, had high inflation but nowhere near that of Latin American economies like Brazil. Average inflation in South Korea in the 1970s was in double digits, with it peaking in 1980 (Appendix Table 2, p 64). While this coincided with high growth for quite some time, it eventually seemed to have had a restraining effect on the growth of GDP. Tighter monetary and fiscal measures brought inflation down in the 1980s and eventually restored high growth.

This wide range of experience from around the world and prodigious amounts of research have vastly enhanced our understanding of inflation. The relatively good inflation record among all industrialised nations and emerging market economies over the last two decades is testimony to this. However, this experience has also taught us that there is a lot that we do not understand and that the drivers of inflation, like the strains of bird flu, can change over time, rendering standard antidotes less effective and calling for fresh research and maybe even new medicines. For years, the US Federal Reserve System kept a control on prices by buying and selling government bonds, which was the other side of releasing money into the economy and absorbing money from it. However, money is not the only medium of exchange. There are “near monies” that can do some of the work for money. People can use all kinds of other commodities and papers to trade goods. If, for instance, government bonds were fully acceptable as a medium of exchange, then a central bank selling bonds and collecting money would have very little impact on the economy. It is the appearance of “near monies” that compelled the US Fed to change some of its strategies for maintaining stable prices.

Since these endogenous features of an economy can vary from one country to another, it calls for independent research in each nation. Over the last few years, there is a sense that the nature of inflation faced by emerging economies is changing, necessitating not just greater resolve but also new ideas to achieve price s tability.5 Rakshit (2011) points to the somewhat unusual divergence between consumer price index (CPI) inflation and WPI inflation in recent times, though it should be noted that the two have converged once again over the last six months. We can see from Figure 1 (p 53) that the volatility of inflation also seems to have changed. The use of the WPI in deciding policy has often come under criticism (see Patnaik, Shah and Veronese 2011; Rakshit 2011). However, it can be argued that for most purposes and certainly in the context of this paper it does not matter very much which particular index is used. It is true that there was considerable divergence in 2010 between the WPI and the several CPIs that India tracks but this was exceptional; by and large inflation measured by these indices tend to converge over time.6 Moreover, theoretically, it is not clear that one is better than the other. It is true that the WPI does not track the price of services, which is increasingly becoming a major part of India’s value added in GDP. However, services constitute an important input for manufacturing and agricultural products and it can be argued that the price of services gets indirectly reflected in the WPI. Further, in a nation with as much disparity in incomes and living conditions as India, it is difficult to think of a representative consumer in a meaningful way.

Three Indices

India tries to get around this problem by computing at least three different kinds of CPIs for three different classes of consumers. This raises the vexing question of which of these to use for crafting national policy. The most popular among the CPIs, the one for industrial workers or CPI(IW), has a rather interesting problem. Let me briefly touch on it at the risk of being digressive. For most bureaucrats and government workers, salaries in India are indexed by using the inflation rate as measured by the CPI(IW). Since it is bureaucrats and government workers who collect the data for constructing the CPI(IW), there is a potential conflict of interest, with the possibility that higher numbers are recorded whenever the opportunity arises. A direct study of the WPI and the CPI(IW) shows that the latter has consistently grown faster since around August 2008. This can, of course, happen for natural reasons because some of the commodities tracked by the two indices are different. So one possibility is taking the commodities common to the two indices, and changing the weights in one to match those in the other. This still leaves a problem. The CPI(IW) is computed with 2001 as the base year whereas the WPI is computed with 2004-05 as the base year. But it is easy to change both indices to the same base year, and once we make this change, we can see if there is an upward bias in the CPI(IW).

Doing this7 and plotting the two indices on the same graph r eveals a very small but systematic upward bias in the CPI(IW). In this exercise, we made 2006 the base for both indices. So both indices start off at 100 in April 2006. Almost immediately after that, the CPI(IW) moves up faster than the WPI and, barring six or seven months, outperforms it. This was a quick preliminary exercise and will need more careful study but it does suggest a small upward bias in the CPI(IW) on which the salary increases of the people engaged in computing it are based. On the other hand, it turns out that if we calculate the inflation between the two

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indices between April 2006 and January 2011, there is little difference. So, for policy and analysis, the differences between the WPI and the CPI are not sufficient to warrant preferring one over the other, especially since our instruments for managing inflation are at best blunt. With this digression behind us, let me now r eturn to the main concerns of this paper.

As is evident from Figure 1, while inflation, both for the WPI and food, is clearly on the rise since 2000, it seems to be distinctly less volatile than it used to be, for instance, before the mid-1980s. There is also a marked divergence between food and non-food inflation since October 2008, as is clear from Figure 2.

Figure 1: Year-on-Year Inflation since 1972 (%)

should not be castigated under all circumstances. It can lead to price stabilisation. Also, many big retail suppliers need to store food before they can take them to retail outlets. Thoughtless use of the Essential Commodities Act, 1955, treating all acts of storing and hoarding as unlawful, can do a lot of damage. The aim of the law should be to stop hoarding that is used by large traders to deliberately manipulate prices. Reactive hoarding in response to price cycles, on the other hand, has much to commend.

Some of the above discussion explains (albeit in a somewhat tautological way) why the difference between CPI inflation and WPI inflation has been more marked in recent times. However,






-20 4/72 8/73 12/74 4/76 8/77 12/78 4/80 8/81 12/82 4/84 8/85 12/86 4/88 8/89 12/90

Before 1982, we had some stretches of very low inflation but also peaks of a kind that, fortunately, we do not see any longer. This is in part a sign of learning by the government and the Reserve Bank of India (RBI), which has made them better at managing price instability than in the past, but it could also be an indicator of the changing character of inflation.








-5 4/08 6/08 8/08 10/08 12/08 2/09 4/09 6/09 8/09 10/09 12/09 2/10 4/10 6/10 8/10 10/10 12/10 2/11

All Commodities Food

Figure 3 (p 54) reveals another interesting pattern. In this, we show the comparative price movements of perishable and non-perishable food items. Non-perishables can be stored and we would expect rational people to store in times of plenty and draw on the stored food in times of shortage. This would lead us to expect less volatility and less inflation for non-perishables. The figure seems to bear this out, especially over the last decade. This underlines one important point. It makes us realise that hoarding food

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All Commodities Food

4/92 8/93 12/94 4/96 8/97 12/98 4/00 8/01 12/02 4/04 8/05 12/06 4/08 8/09 12/10

this also points to a newfound resilience of the Indian economy. Our overall inflation was earlier powerfully driven by the agricultural sector. What happened to food prices affected everything else and so the two indices moved more or less in tandem. Over time, the share of agriculture in the total GDP has fallen and the growing strength of the economy means that food prices alone may not be in the driver’s seat the way they were in the first several decades after independence. This has an immediate p olicy implication worth noting – in controlling overall inflation, food prices may not be as important as they were in the past. Of course, controlling food inflation is important in itself since a large section in India continues to be poor and any inflation in food prices hurts them disproportionately. This is discussed at some length in this year’s Economic Survey (Government of India 2011). But to control overall inflation, we have to turn our attention much more to macro demand management – fiscal and mone tary – though even here we will need to look for newer channels of policy action.

Before going off the topic of food and commodities management and inflation8 it should be put on record that even apart from the connection of commodities to inflation, this is a topic of considerable importance in itself. A lot of our basic commodities

– for instance, foodgrains, kerosene and liquefied petroleum gas (LPG) – are supported by government subsidies. This is as it should be in a developing economy. The idea is that the poor need to be especially aided to get access to these critical items. However, most of the debate is centred on the fiscal viability of the

53 subsidy. What this misses out on is that how we administer this subsidy has huge implications for efficiency, even when it is fiscally neutral (Basu 2011).

Consider foodgrains. Studies show that an astonishingly high fraction of the grain meant to be given to the poor and vulnerable through our public distribution system (PDS) gets diverted, and presumably sold off at illegally high prices or wasted. According to a study by Khera (2010), in 2001-02, 39% of the foodgrains meant to reach the poor through India’s PDS was lost to leakage and diversion. A more recent study by her (Khera 2011; see also Jha and Ramaswami 2010) shows that the problem has got worse. In 2007-08, the diversion of foodgrains was 43.9%. It had risen to as high as 54% in 2004-05. This disappointing story is mirrored in that only a fraction of the poor get their food from PDS stores. In 2004-05, only 17% of the poorest quintile households received food from PDS stores. And for some poor states such as Bihar and Uttar Pradesh this figure was as low as 2% and 6% respectively (Parikh 2011). Clearly, this is unacceptable because it tends to bloat fiscal expenditure, causing inflation across the board. We have to think of a major overhaul of our PDS and give subsidies, as far as possible, by making direct transfers to the poor, who should then be allowed to buy their food from any store, private or public. Fortunately, the government has taken steps to move towards a major overhaul with an announcement in the Union Budget presented in February 2011 that we will move over to direct transfers to targeted people in lieu of trying to d eliver subsidised kerosene, LPG and fertilisers to all. There has

Figure 3: WPI Index for Food Perishables and Food Non-Perishables







Food non-perishables Food perishables

4/71 4-73 4-75 4/77 4/79 4/81 4/83 4/85 4/87 4/89 4/91 4/93 4/95 4/97 4/99 4/01 4/03 4/05 4/07 4/09 4/10

also been some discussion in the government on improving the supply chain management through modern retailing to help cut down the gap between farm gate prices and retail prices but there have been some contrary opinions expressed on this (see, for instance, Singh 2011). The method of direct transfers also has to contend with the average preson not having any access to banks and stores. A survey by Reetika Khera in nine states found that the average distance of a household to a bank or a post office was 5.2 km and the average distance to a fair price shop was 1.4 km. More importantly the average time taken to get to these was, respectively, 3.25 hours 2.10 hours.

A related but distinct problem occurs in the case of diesel and petrol. If we try to help consumers by holding the price of petrol low and constant, they will not economise on it and switch to substitutes when the supply runs short and the global price rises. By holding prices constant, a major signal for altering behaviour to suit changing supply conditions gets switched off. This is a

54 much more important consideration than the impact on the fiscal deficit. Since we have till recently by and large held the price of diesel constant, we have contributed to these inefficiencies. People in India ply large luxury cars unmindful of whether the global price of fuel is high or low. It should be pointed out that even the government indulges in a fair amount of waste and that this is hard to control through price changes. Since many users of fuel do not have to pay for it out of their own pockets, they tend to use this resource without being adequately sensitive to the level of its price. This is an embarrassing topic and, maybe for that reason, is seldom talked about. But it is important to face up to these inconvenient questions so that we can devise new mechanisms to increase overall efficiency. A lot of our problems are rooted in these micro inefficiencies and we need to work to improve them. However, we shall now turn to the subject of macroeconomic policies for combating inflation.

3 Paradox of Predicting Inflation and Controlling It

Before turning to the subject of macro demand management, I shall briefly call attention to another intriguing problem with inflation management. There are agencies in every nation that are entrusted with the task of both forecasting inflation and trying to adopt policies that keep it under control. A nation’s central bank tries to do this, as does its treasury or ministry of finance. But this twin-tasking gives rise to an intriguing conundrum, which is specific to the social and economic sciences and has few parallels in engineering and the natural sciences though Heisenberg’s uncertainty principle could be thought of as a counterpart to this from the natural sciences. Discussing US President Herbert Hoover’s effort to boost confidence in the economy in the aftermath of the Great Crash of 1929, Ahamed observes,

To some extent he was caught in a dilemma that all political leaders face when they pronounce upon the economic situation. What they have to say about the economy affects its outcome – an analogue to H eisenberg’s principle. As a consequence they have little choice but to restrict themselves to making fatuously positive statements which should never be taken seriously as forecasts (2009: 363, italics added).

This is an interesting observation and one worth elaborating on. I shall point out, drawing on another mathematician-philosopherscientist, L E J Brouwer, how we can rescue ourselves from Ahamed’s trap of forecasts that should “never be taken seriously”.

It is widely believed and is to an extent true that when a wellinformed and responsible government or quasi-government agency makes an inflation forecast, that in itself can cause the future course of inflation to change. This is because, at least in the short run, the actual inflation rate depends in part on what people expect the inflation rate to be. Inflation can be worsened by higher inflationary expectations, and likewise prices can be stabilised, to some degree, by leading people to expect that prices will be stable. Thus, we often hear about how a policymaker stoked inflation by saying in public that it would go up. Usually, behind such an observation is the critique that no one should be so irresponsible as to fuel inflation by making such statements. But this immediately places the central bank and the treasury in the dilemma that Ahamed alludes to and may be logically impossible to resolve.

To understand this, suppose that inflation will be 5% per a nnum if no public forecast is made by the treasury about future

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inflation. This is shown by the horizontal line A in Figure 4. Now, suppose the treasury forecasts an inflation number and this influences human expectations and behaviour in such a way that a ctual inflation turns out to be halfway between 10% and what the treasury forecasts.9 This is shown in Figure 4 by the line slanting upwards, B. In this figure, the horizontal axis represents the forecast made by the treasury and the vertical axis the actual inflation. For all inflation forecasts by the treasury, we can infer what the actual inflation will be from line B. Let me call all such graphs that plot the relation between forecasts and actual inflation the “forecast function”. A more complex model with dynamic features would allow for adjustments to this forecast function based on the forecaster’s past record of accuracy. But I shall stay away from that here. What is of interest here is that though the actual inflation moves with the forecast, it does not mean that we can never make an accurate forecast. What we need to do is to look for the “fixed points” of this forecast function.10

Assuming that the forecast function in the economy under consideration is depicted by graph B in the figure, what should the treasury do? Assume for simplicity sake that inflation forecasts can only be a non-negative number. In this model, when the treasury tries to forecast inflation it has to treat its own forecast as one of the determinants of inflation. If, for instance, it makes a forecast of zero inflation, actual inflation will be 5%. If it forecasts inflation to be 5%, actual inflation will be 7.5%. It is now easy to see that if the treasury wants to accurately forecast inflation, it has to make a forecast of 10% inflation. No other forecast will be borne out in practice. Basically, an accurate forecast is a search for the fixed points of the forecast function. Now suppose that the treasury takes its job of holding inflation down seriously. Then, keeping in mind that its own forecast of inflation is one of

Figure 4: Inflation Forecasting Paradox


B Inflation

10% A



Inflation 5% 10%


the causes of inflation, what forecast should it make? Clearly, it should forecast inflation to be 0%. It will turn out to be wrong but inflation will be as low as possible, to wit, 5%. So, the objectives of accurate forecasting and of inflation control pull in different directions.

In that lies a dilemma. It is not always possible for the treasury to carry out the two tasks that it is entrusted with – accurately forecasting inflation and minimising inflation. There are situations, as illustrated above, where a problem of internal consistency arises between the two tasks. Do one task perfectly and the other gets thrown out of gear. Do the other task diligently and the first one goes out of control. This is not a problem specific to India or China or the US. This is a problem with the way the world is.

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There is no way to resolve this; all policymakers having to make public forecasts have to live with this dilemma. If the forecast function is non-linear and has more than one fixed point (that is, it cuts the 450 line in multiple places), each fixed point would be an accurate forecast. In such a situation, the task of predicting inflation accurately and trying to keep it low can have significant content. It would mean that we should forecast the lowest value of inflation, which is also a fixed point of the forecast function.

Before moving away from this topic it is worth briefly pointing out an interesting connection between expectations and government policy. In the above discussion, I did not elaborate on why greater inflationary expectations lead to greater actual inflation. One class of analysts have argued that widespread expectations of inflation lead governments to behave in ways that fulfil those expectations – such as running large deficits (Sargent 1982; Mankiw 2010, Chap 13). One way of breaking this link is for governments to visibly alter their rules of behaviour, such as making an open and credible commitment to maintain lower deficits in the foreseeable future.

4 Benefits for the Poor and Inflation

Let us now turn to more routine matters of inflation management and control. I begin by examining a particular argument that has been used in India during the last 17 months of inflation, which began with a sharp upward rally of food prices. Food price inflation peaked in the early months of 2010 when it exceeded 20%. Non-food inflation picked up a little later. It has been argued that the sharp rise in food prices in 2009 and the early months of 2010 was probably caused by the drought of 2009 that led to a decline in the production of foodgrains. A contributory cause cited is that the government considerably expanded income support to the poor – for instance, through the Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS) and loan waivers to indigent farmers. This explanation has run into controversy. Unfortunately so because much of it can be sorted out through economic theory.

Montek Singh Ahluwalia, Deputy Chairman of the Planning Commission, said, as did several others (see Government of India 2011), that the greater benefits given to the poor may have caused some of the initial food price inflation in 2009 and early 2010. Let me refer to this as the “benefits-based inflation hypothesis”. This hypothesis has led to a raucous debate with some wrongly paraphrasing it as “the poor are to be blamed for the inflation”. As far as I know, no one has made that claim and it can be safely put aside. A more serious criticism of this claim that has been made may be summed up as follows: If it were indeed true that it is the greater demand for food on the part of the poor that caused the i nflation, then we would expect to see the poor consuming more. But (so goes this argument) there is no evidence for this. Hence, the benefits-based inflation hypothesis is invalid. For ease of reference I refer to this challenge to the hypothesis in italics as the “consumption-based challenge”.

What is easy to see is that the consumption-based challenge, though interesting prima facie, does not stand up to scrutiny. And the benefits-based inflation hypothesis does have plausibility though it may not be empirically established. To understand this, note that the poorest quintile of the rural population devotes approximately 67% of its consumption to food. We know this from 2004-05 National Sample Survey Organisation (NSSO) household survey data (Government of India 2011). The rich spend nowhere near that proportion of their money on food. So, if money and financial benefits are diverted to the poor from the rich, it only stands to reason that the demand for food will rise. If that happens, the price of food will rise disproportionately. Since this is exactly what was happening in late 2009 and early 2010, the benefits-based inflation hypothesis seems to have plausibility.

But then what about the consumption-based challenge, which claims that there is no evidence that the poor are consuming more food and that this destroys the thesis that redistribution in favour of the poor has contributed to inflation? A little thought will show that there is no contradiction between the two. Even if we do not contest the claim that the poor have not been consuming more food, it is possible to maintain that their higher income is contributing to the higher inflation. To see this, it is important to understand that a greater demand for food does not necessarily mean a greater consumption of food. Figure 5: Income Subsidy and Food Inflation






S D1D0
0 Food

Let D, in Figure 5 be the aggregate demand curve for food of


the poor people. Now suppose that the poor get an income supplement that raises their demand for food. Then the new demand curve will be like D1. This, however, does not in itself mean that the poor will actually consume more. If the supply of food that is available to the poor is unchanged, or in other words, the supply curve of food is inelastic, the increased demand will not translate into greater consumption of food but it nevertheless will be the cause of food prices rising. It should be evident from the figure that the fact that the beneficiaries do not manage to consume more after their demand increases is the reason why prices rise even more. If the supply curve of food were merely slanting upwards instead of being vertical, the price increase would be less. Interestingly, this phenomenon is also logically compatible with the poor becoming worse off. We know from theoretical studies how the recipient of a benefit can end up worse off because his or her receiving a benefit causes such an adverse movement in the prices of goods that are consumed in large quantities by the r ecipient that the net benefit, in equilibrium, is negative (see Basu 1997, Chap 5).


This, of course, does not resolve an empirical question: Are the poor actually worse off? While the answer to this is not germane to the argument here, from the piecemeal evidence that we have, it is possible to claim they are not. The most recent round of NSS data shows that poverty in India has declined from around 37% in 2004 to approximately 32% in 2009 (using the Tendulkar measure of poverty in both cases). While 32% is still high and no reason for complacency, the decline in poverty is commendable and suggests that the steps taken to transfer more buying power to the poor have had some effect.11

In the above analysis, I have steered clear of deeper general equilibrium questions. If larger benefits for the poor are made possible by transfers from the rich, there must be a deflationary pressure on the prices of goods consumed primarily by the rich. So, while the relative price of food may rise, why should overall inflation increase? Such questions take us to the heart of some of the most puzzling questions about the connection between the real and the financial economies, discussed, for instance, by Hahn (1982). In the discussion that follows I shall skirt around some of these matters. A full discussion of these still-unresolved matters of “money in general equilibrium” is beyond the scope of this paper. Luckily so, since it is also beyond the capability of the author.

5 Interest Rates and Liquidity

Inflation is one of those peculiar phenomena that we have learnt several techniques for controlling even without understanding its causes and triggers anywhere near fully. The controls are

o ften imperfect and each comes with side-effects,12 which calls for some judgment regarding how strongly we administer these medicines. But what is comforting is that thanks to sustained r esearch, we at least have several known antidotes.

It is worth clarifying that by inflation I refer to an overall increase in prices and not the relative increase in the prices of some goods. When the prices of some goods increase, we can respond by trying to supply more of those goods (by diverting effort from the production and supply of other goods). But if the prices of all or virtually all goods increase, there is little we can do in terms of supply because there is no known way of suddenly providing more of all goods. If there was a way of doing so, we would have already done so and made everybody better off. This is the r eason why when there is overall higher inflation we have no choice but to turn to some form of demand management,13 even while working on easing specific supply bottlenecks that may exist. The case for easing supply bottlenecks and enhancing productivity is there at all times, with or without inflation, since that increases welfare. Relative price increases are for the most part best left alone unless there is reason to believe that they are caused by sudden collusive behaviour or the artificial manipulation of markets by large sellers. Such relative price movements are the market’s way of equilibrating demand and supply.14

There is plenty of evidence on adverse effects from nations that try to control relative price rises by government decree. The result is the encouragement of black markets. And goods vanish from regular markets with consumers queuing up for long hours to get rationed supplies. Inflation, on the other hand, is a mismatch between overall supply and overall demand, and it

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c ertainly calls for appropriate policy action. Overall demand in the economy comes from many sources – corporates, farmers, l abourers, housewives and government. So what any single agent can do is limited. In addition, actions by other agents can undo what one agent does. This is what contributes to making inflation one of the hardest problems to manage – the emperor of economic maladies.

From this description it is obvious that certain rather blunt i nstruments can curb inflation though their political economy is questionable. Since inflation is caused by aggregate demand e xceeding aggregate supply at a certain point of time, one such blunt instrument is redistributing some of the demand from the present to the future. This can be done, for instance, by confiscating a certain amount of people’s income for a duration of time. It can take the form of a 5% temporary income tax, which is held by the government without being put to use (that would defeat the very purpose of withholding buying power) and eventually paid back to the taxpayers over the next four or five years once inflation eases out. A side-effect could be output declining if producers realise that demand will decline as a consequence of this move. But if executed suddenly, it can curb the pressure on prices though it is unlikely to make the government popular at the polls.

But before getting into matters of policy, we need to understand the causes of inflation at a more fundamental level. At an abstract, elemental level inflation is the product of our ability to make contracts and deliver on promises. If we were a totally u ntrustworthy people who never delivered on promises, we would have no inflation. Of course, we would also be crushingly poor and living in primitive conditions.15 While we think of promises mostly in bilateral terms, the most important “economic” promise, one that has made modern civilisation possible, is the mysterious promise represented by money. This means the currency note in your wallet or the balance in your bank account, which in itself is of no value but a record of work you did for which you are yet to redeem goods and services. Money is nothing but a generic promise from society – the government being the most important representative of that – that you will be able to change these useless bits of paper for actual goods and services in the future. It is this which enables the worker who toils all day to not insist that his or her employer hand over food, clothing and shelter material in the evening in exchange for the work put in. Instead, the worker accepts money, which is a kind of pledge to him or her by society at large. The worker can redeem that pledge at leisure and in small measures – buying food, shelter, education, and so on as and when he or she needs them.

Money was not discovered one day in a moment of scientific triumph. It emerged gradually, in small measures and through little innovations. But in terms of human achievement it must stand right there at the pinnacle of inventions. Without it we would have very little of what we know today as human society and a civilised life. It was soon realised that unlike most other products where we encourage multiple producers to get into business and to have competition, money is one area where competition is not desirable. Since money entails a generic promise, it creates scope for free-riding in a way that does not happen with other goods. If there are many entities that can create money and the value of

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money is a public good, with competition we risk creating excess money because at the time of creating money, the creator gets the value and the erosion of value in the future is borne by all. It was soon decided that this was one area where, far from boosting competition, what we wanted was a monopoly. Each economy must have at most one money-creating authority. It was with this principle in mind that the Bank of England was created in 1694, though its monopoly rights to creating money were firmed up only at the time of the renewal of its Royal C harter in 1742.16

Managing Liquidity

Inevitably, a nation’s central bank and its treasury became the managers of its liquidity and, through that, the value of money and the level of prices. In India, the major instruments for managing liquidity are the repo, reverse repo and cash reserve ratio (CRR).17 This system has evolved over time. The main instrument of liquidity management, the Liquidity Adjustment Facility (LAF), was introduced in 2000. The concept of repo auctions was introduced in May 2001. As Jalan has noted, the market responded to these changes positively “with an appreciable rise in turnover and a decline in volatility” (2001: 180).18 It is interesting to examine how well these policy instruments have succeeded in controlling inflation. In India, the government does not control interest rates, except a few such as the basic savings account interest rate for bank deposits. In adjusting the repo and reverse repo rates, it is expected that these changes will influence the behaviour of banks and cause free market interest rates, for instance on mortgages, fixed deposits and other lending plans, to move in similar directions.19 Hence, through the adjustment of repo and reverse repo rates, the RBI manages to influence interest rates in general.20 The idea is that this in turn will influence liquidity and, through that, inflation. In Figure 6 (p 58) we track the repo rate, the reverse repo rate and inflation. It is evident that while there is some connection between the two, especially with some appropriate time lags put in, there is also a lot of noise.

There can be no doubt that the reckless fuelling of demand by a nation’s treasury or its central bank will fuel inflation. When, in 1923, Rudolf von Havenstein, the president of the German R eichsbank (the predecessor of Deutsche Bundesbank), acquiesced to the government’s demand that more be spent by recklessly printing money, it was but inevitable that Germany would be embroiled in hyperinflation. On 17 August 1923, von Havenstein proudly announced that he would soon be issuing new money in one day equal to two-thirds of the money in circulation. He kept his word and Germany paid for it. Yet, in the relation between liquidity, as controlled by the central bank and the government, and prices there is a lot of white noise. The noise is important. It illustrates that there is much more to liquidity than what can be controlled through central bank action or the policies of a ministry of finance. What the corporates, the banks, the farmers and ordinary individuals do can also affect liquidity and, through that, the level of inflation.21

The management of inflation cannot be reduced to a mechanical engineering problem where the formula connecting what is to be done by the government or the RBI and what will be achieved is written in stone.22 For instance, a period of financial integration when ordinary people begin to keep their money in banks or in mutual funds instead of keeping it under their pillows can cause the velocity of circulation of money to rise, thereby putting an upward pressure on prices. Equally, there are stretches of time when emerging economies face financial deepening, with a

Figure 6: Policy Rates Changes and Inflation (%)


10 8 6 4 2 0

Inflation rate Reverse repo rate Repo rate


4/01 8/01 12/01 4/02 8/02 12/02 4/03 8/03 12/03 4/04 8/04 12/04 4/05 8/05 12/05 4/06 8/06 12/06 4/07 8/07 12/07 4/08 8/08 12/08 4/09 8/09 12/09 4/10 8/10 12/10

d ecreasing velocity of circulation. These are usually endogenous changes in the economy and may have little to do with explicit central bank action (see Lall 2011).

It is assumed in popular discourse that if interest rates are raised, the demand for credit will go down; and hence the total amount of liquidity in the system will be less.23 This is generally true. However, it can be shown that in certain contexts the opposite will occur. Consider the standard description of a credit market where the demand for credit is downward sloping while the supply of credit is upward rising, as shown in Figure 7. This means that as the interest rate is raised, people will be prepared to save more and hence supply more credit. On the other hand, those seeking to borrow money, say, to invest in projects, will now want to borrow less. It is the latter that leads to the standard wisdom that you can curb liquidity by raising interest rates.

Suppose the existing interest rate is at or above r*; that is, in the zone where there is excess liquidity.24 Then this standard logic works well. Raise the interest rate and the supply of credit will rise and the demand for credit will decline. Since in this region demand is the binding constraint, it is a decline in demand for credit that is of consequence. In other words, aggregate l iquidity dries up and this, hopefully, has a sobering effect on prices. While the direction of this effect is right, it is important to point out that how effective the interest intervention is depends on the elasticity of the demand curve for credit. It can be argued that if a large part of a nation’s credit demand comes from the government, which usually is not very cost-conscious and hence not interest-sensitive, the demand curve for credit will be less elastic and one will need a larger increase in the interest rate to achieve the same mopping-up effect as in a nation or a context where the bulk of the borrowing is done by private agents. Whether the effect is robust or feeble, it is evident that in an excess liquidity situation, an interest rate increase impels aggregate credit usage in the expected direction; that is, it causes it to increase.

There is, however, no reason why we should assume that the initial interest rate in an economy will always be at or above

where the demand and supply curves intersect. Credit markets are subject to interventions by central banks and governments and they also have other external rigidities, which can deflect the interest rate from the neoclassical market equilibrium rate r* to a rate where demand is not equal to supply. In particular, to a rate below r*; that is, a zone where there is li

quidity deficiency. There are also endogenous explanations for why a credit market may not maintain an equilibrium and, in particular, market imperfection can lead to credit rationing (Stiglitz and Weiss 1981). Hence, it is possible that the initial interest rate is below r*. Let us now see what would happen if that were the case. Suppose, specifically, that the interest rate is at r0 as in Figure 7. So the demand for credit exceeds the supply of credit. Now suppose the government or the central bank raises the interest rate to r1. What

happens to total credit in the economy? To answer this, note that the demand for credit falls and the supply of it rises. However, since it was the supply that was the binding constraint, this rise in i nterest means that the total amount of money lent in the economy will increase. In this case, the total credit goes up from r0c0 to r1c1.

Since there was an excess demand for credit in the original equilibrium, a small decline in demand is of no consequence. Hence, we get a paradoxical response to the interest-rate tightening, whereby there is not only no reduction in liquidity but also a possible increase in it, assuming that the supply curve of credit is upward sloping. Lillienfeld-Toal, Mookherjee and Visaria (2011) have reported on some empirical corroboration of this and a similar line can also be found in a recent review in the EPW (EPW R esearch Foundation 2011, sec 1.4). This has important policy implications. If we are in a predicament where raising interest rates has a feeble effect on inflation, we may consider using this policy more aggressively. But if we are in an economic context where

Figure 7: Interest Rates and Liquidity

Interest Rate







c1 c0 m1 m0 D0 S0


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interest rates have no effect on liquidity, or have a pathological reverse effect on liquidity, we may have to desist from using this policy and look to other kinds of interventions. It should, however, be kept in mind that there is a difference between raising the call money rate (maybe via interventions in the repo market) and raising the cap on the interest rate on ordinary bank savings.25 There is also an open question concerning the very concept of liquidity. Why should banks lending more mean greater liquidity? After all, greater lending simply means an altered portfolio of assets for people and not an increase or d ecrease in assets. This points to some deep theoretical issues regarding the difference between money and various forms of near monies – deep enough to be considered beyond the pale of this paper.

This is also related to the fascinating question about the units into which a nation’s aggregate money supply is divided. Considering a polar case makes this easy to understand. If the entire currency in circulation in a nation (that is, M0 minus bankers’ and other deposits with the central bank) consists of one largedenomination note (the denomination being the size of the a ggregate currency in circulation), it would be a very illiquid n ation. And unless there was some sophisticated substitute for signing contracts for exchange over time, most people would be starved of money at all times because there is only one note in the hands of one agent. It immediately follows that not only do the monetary aggregates in the nation matter, but also that a lot d epends on how finely these aggregates are broken up – into notes of thousands, five-hundreds, hundreds and so on. It can even be said that it is the granularity of the aggregate money that matters more than the aggregate money when it comes to measuring liquidity and inflationary pressure.

What the above analysis does is to warn us about possibilities. Economic theory alerts us to the need for empirical and statistical analyses to make sure that the overall conditions in an economy are appropriate for us to use interest-rate tightening as a measure for controlling inflation. The theory also tells us where the empirical study ought to be focused. In this case, we are told to check out the prevailing conditions in the credit market, in particular, whether there is an excess demand for credit, before we use interest-rate tightening to control inflation. It warns us that there exist situations where interest-rate tightening will have no effect and we will pay the price for such tightening without the attendant benefit of reduced inflation.

Recent unconventional moves by Turkey’s central bank and the response of the economy certainly add further weight to the need for out-of-the-box thinking. Turkey has in recent times been f acing high inflation, akin to India and many other emerging economies. In April 2010, its year-on-year inflation was at 10.19%. However, taking stock of the unusual global situation where i ndustrialised economies have near-zero interest rates, the central bank decided to move contrary to what is conventionally done. It began lowering its one-week repo. This initially caused some shock and confusion in the market but the central bank persisted with a gentle lowering of the interest rate during 2010 and 2011. Interestingly, Turkey’s inflation rate has been on a steady downward journey since April 2010 and stood at 6.30% in July 2011. And in terms of growth, in the first quarter of 2011, it topped the

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G20 chart at 10.1%. From some numbers coming in as this is being written, it is clear that the growth will come down to around 8% in the second quarter but even with that it is likely to be among the top three performers among the G20 nations. An economy is far too complex an object for us to jump quickly to making causal connections between policy moves and inflationary outcomes based on Turkey’s experience. However, the o bverse is also true. We must not remain rooted to the textbook doctrine; it is important to examine contrarian policy. It is interesting that in September 2011, Brazil’s central bank followed Turkey and lowered the interest rate despite inflation being high.

While persisting with a policy, it is worth remembering that the zone in which an economy is situated can change rapidly. Suppose that in India in early 2010 the economy was in the excess liquidity zone, that is, the prevailing interest rate was at or above r*. Once the celebrated auction for the third generation of mobile communications systems (3G) began in India, firms scrambled to raise credit to be able to bid for spectrum. In other words, this auction caused a rise in the aggregate demand for credit. That is, the curve, D0, shifted to the right. Note that this could easily mean that the economy shifted from an excess liquidity zone to a liquidity deficient zone even without any change in the interest rate. Did the 3G auction actually cause this? The answer is we do not know. But the direction of move of the demand curve must have been exactly as explained here. To know whether this caused a zonal shift would require empirical investigation. What this paper tries to do is to draw attention to the kinds of questions that deserve empirical and theoretical investigation, and how the efficacy of standard monetary policy could depend critically on the results that such an investigation yields.

6 A Digression on Capital Controls

The above analysis draws our attention to the importance of d etail in designing economic policy. Minor flaws can have large unintended consequences. This is a good occasion to illustrate a similar point about polices to restrict capital flows. There are contexts where it is reasonable for a nation to place restrictions on capital flows. Even the International Monetary Fund (IMF) has recently endorsed the need for such restrictions in certain situations. Suppose for some form of credit, the Indian demand and the international supply are as illustrated in Figure 8 (p 60), for instance, external commercial borrowings (ECBs). For simplicity, let me go along with a neoclassical analysis. Left to itself, the amount of borrowing that would occur in this market is shown by L*.

Let us now suppose that the government decides that so much of foreign borrowing is undesirable and we should restrict the total borrowing to L. So, the government decides to place a restriction on debt inflows into India to ensure that the total flow r emains within L. I am not questioning the merit of this decision, but simply taking it as given. The aim is to illustrate how different microeconomic ways of achieving this macroeconomic target can have very different implications for the economy. Suppose that the government decides to implement this limit by restricting the supply of credit that comes into the nation. This will leave the demand curve, DD’, unchanged but the supply curve will now be shown by SBM. By locating the point of intersection between the new supply curve and the demand curve, it is easy to see that the total credit will be L. An alternative intervention would be to leave the supply unchanged but place restrictions on the aggregate demand for credit by suitably rationing the amount that I ndian firms can borrow. In this case, the supply curve remains SS’, whereas the demand curve becomes DAL. Once again the t otal credit coming into India will be L.

Figure 8: Two Kinds of Capital Controls

Interest rate S’







L * Quantity of credit

Both interventions achieve the objective of limiting credit flows into India, but there is one big difference. In the former i ntervention, the interest rate will be rL, whereas in the latter i ntervention, the interest will be rH. Thus, in one case Indian borrowers will get credit at a much lower interest rate than in the other, with large implications for efficiency, corporate profitability and growth. Evidently, a policy intervention without careful attention to detail could easily see us make a mistake on this.

7 Salad Bowl Stagflation

Another problem of using standard macroeconomic demand management for controlling inflation in today’s altered world has to do with globalisation. In our increasingly flat world, there is the need to worry about thy neighbour’s money in a way that we never had to in the past (see, for instance, Subbarao 2011a). One gets a sense of this by looking at the landscape of growth and i nflation across nations.26 It becomes evident from such a study that the world is suffering from stagflation, albeit of an unusual kind. One sees evidence of stagnation in virtually all industrialised nations, including the US, European countries and Japan; and one sees inflation on a high in virtually all emerging market economies, including India, Argentina, Brazil, Vietnam and China. In other words, what we have is a world economy in which some parts are caught in a “stag” mode and some in a “flation” mode, which may together be referred to as “salad bowl stagflation”.

This has much to do with the nature of contemporary globalisation. Following the recession of 2008 and the painfully slow recovery in most industrialised nations, they continue to resort to liquidity easing and monetary expansion to boost demand. As Ahluwalia (2011a) has noted, this was not the outcome of a formal agreement but was facilitated by the informal process of the G20.

60 However, instead of boosting demand, as would have happened pre-globalisation, now a large part of the extra liquidity is flowing to emerging market economies that have growth potential and the ability to use the money. The resort to a second round of quantitative easing (QE2) by the US economy is the most discussed such action. But there have been similar actions across the board in developed market economies, all amounting to a combination of keeping interest rates low and expanding money supply. However, this extra liquidity, instead of fuelling growth in industrialised nations, has gone over to the emerging economies that are already growing well and fuelled inflationary pressures in them.27 This is what lies behind the salad bowl stagflation that we see in the world today. It must, however, be pointed out that, unlike in the pre-Lehman days, there is no evidence of disproportionate direct capital flows into India from the US. There are, however, indirect channels through which global liquidity can exert an upward pressure on prices.

There is reason to expect that this is going to be a stubborn problem. This is because the US Fed is caught in a bit of a bind. Much of its quantitative easing process consisted of buying up long-term securities. QE2 consisted of buying up $600 billion worth of long-term bonds. This was financed by using short-term credit in the form of borrowing from the excess reserves with private banks. These reserves could be borrowed at very low interest rates, usually 75 basis points. The long-term bonds, on the other hand, fetch the Fed interest as high as 3%. This made for a large profit and windfall gains for the Fed – the 12 Federal R eserve banks in the US posted an aggregate profit of more than $80 billion last year. There is, however, a downside to this. If, in an effort to tighten liquidity, the Fed decides to raise interest rates, its cost of borrowing will rise since it is using short-term borrowing to finance its long-term debt. This can cause a deterioration in its balance sheet and it is only natural that it will resist making such a move. This implies that the Fed’s easy money policy may end up lasting longer than it might have otherwise.

Another factor that will add to this brew over the next few months and probably longer is the expected revaluation of the renminbi. There are signs that China intends to do this and from its point of view, this is the right policy. China’s exchange rate policy has been widely misunderstood. If it were true that China would perpetually keep its currency undervalued and thus sell its products to the world at below cost price, it would be of little concern to other nations. However, it would be foolish of China to do this. What it is instead pursuing is a good strategy and is best u nderstood by considering habit goods. Certain products are habit forming, for instance, newspapers. Once you get used to a newspaper, you prefer to read that newspaper instead of another one. For habit goods, the right strategy for the producer is to sell a product initially at a special low price, if need be below cost, to get customers used to it, and then later raise the price and make up for the initial loss.

Buying from a particular country is a habit good. There are so many idiosyncrasies associated with each nation’s bureaucracy and infrastructure that once we get used to buying from a nation, it is not often worthwhile switching to another. China has played this strategy just right. Nations have got used to buying from

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China, even though it has profited little from this and may even higher degree of coordination in policies pertaining to macrohave incurred a loss. But this strategy would be useless unless it economic demand management across nations. Till this is achieved subsequently raised prices and redeemed its losses. We have we have to continue to use our somewhat impaired instruments every reason to believe that this is what China will do and we will of country-specific demand management to keep inflation in see a steady revaluation of the renminbi. Given that many nations c ontrol. In the long run, however, there is no escape from using have asked for this, why should this be of worry? The answer is multi-country agencies, such as G20, to work collectively to because this will also mean increased consumption on the part of a ddress problems such as that of inflation in emerging economies China as it redeems its earlier losses. This, in turn, will create an and stagnation in developed economies. upward pressure on prices, which was not there when China was Collective global action on this will not be easy because, as in its undervaluation mode. this paper argues, this is an area where our understanding of

Hence the problem of salad bowl stagflation is likely to last for complex economic processes and interlinkages is still limited. As some time and the need for coordination of macro-demand man-Subbarao observes, “[Because] our understanding of spillovers agement policies across nations becomes that much more urgent. and best practices remains limited, it is far too early to think of What the world is currently caught in is best understood by imag-reaching new formal agreements on policy behaviour” (2011a: ining an Indian economy in which we have high interest rates in 874). So what we can hope for at this stage is an exchange of in-Gujarat and low interest rates in Bihar. This would give rise to formation, peer review and informal agreements along the lines perverse capital flows from one region to another. The global of what G20’s Mutual Assessment Process (MAP) is attempting. economy being virtually a single economy, the prevalence of very What we have argued is that international coordination is impordifferent interest rates across nations presents a similar situation. tant not just for achieving strong, sustainable and balanced What this emphasises is that, like so many other domains of policy-growth as the MAP attempts, but also for the containment of exmaking in the modern world, there is now the need to achieve a cess liquidity and inflation.


1 All inflation numbers, unless explicitly stated otherwise, refer to annual inflation; that is, the growth rate of the price index on a year on year basis.

2 For a detailed, phased analysis of India’s inflationary experience during 2009 and 2010, see Mohanty (2011).

3 When analysing inflation in India, I use WPIbased inflation numbers. On the few occasions when other indicators are used, it is made explicit.

4 There is a lot of literature on what an “acceptable” or “threshold” level of inflation for India is, most of it clustered around numbers ranging from 4% to 7%. For a discussion, see Rangarajan (2009), Chap 1.

5 For an excellent analysis of the changing nature of this inflation, see Rakshit (2011). The multiple sources of India’s recent inflation are discussed by, among others, Mishra and Roy (2011) and M undle (2011).

6 Their divergence and causal links have recently been studied by Goyal and Tripathi (2011).

7 I am grateful to M C Singhi, Senior Economic A dviser, Ministry of Commerce and Industry, for suggesting this procedure for comparing the two data series and then doing the necessary statistical computation with remarkable competence. A similar exercise is being done in a paper in progress by Anant (2011), which will point to some rather interesting implications, including on the use and timing of monetary policy instruments.

8 I have written on this elsewhere: Basu 2011. For related discussions, see Dev and Sharma 2010, Himanshu and Sen (2011), Kotwal, Murugkar and Ramaswami (2011) and McCorriston et al (2011).

9 It could be that people earlier expected inflation to be 10% but on hearing the authoritative voice of the treasury make a different forecast, believe that actual inflation will be the average of 10% and the forecast; and this, in turn, makes them cut deals in the market in such a way that that is exactly the inflation that occurs.

10 The somewhat frivolous reference to Brouwer is because he specified a set of sufficient conditions under which a function will have a fixed point. If a forecast function has no fixed point, we are caught in the trap Ahamed points out and it is i mpossible to make an accurate forecast. We can otherwise make an accurate forecast but have to take account the self-referential problem of the forecast itself influencing the outcome.

11 For a general empirical investigation into in equality, poverty and inflation in India, see Mishra and Ray (2011, 2011a).

12 As Keynes noted, “There is no difficulty whatever in paying for the cost of the war out of voluntary savings, provided we put up with the consequences” (1940: 61; italics added).

13 This is broadly in keeping with the view expressed in V K R V Rao’s celebrated 1952 paper. For a critical assessment of this, see Patnaik (2011).

14 This is not to deny the substantial literature on non-Walrasian general equilibria, where markets remain stable without relative price movements (for a summary statement of this, see Basu 1992). While theoretically these models are of great scope and challenge, they rely on elaborate systems of rationing that have few counterparts in everyday economic life and will therefore be i gnored here.

15 This should make us understand that in economics, as in medicine, all policies come with side-effects. As Reddy points out, the trade-off is not simply between growth and inflation but between these and financial stability (2011, Chap 17). Interestingly, there are also connections to the policy of financial inclusion. In India, of approximately 6,00,000 human habitations, only around 30,000 are fully serviced by commercial banks (Subbarao 2011). The government’s financial inclusion policy is a plan to bring most of these habitations into the ambit of formal banking. It can be argued that this policy will enhance the velocity of circulation of money by bringing into the financial system currency that was lying dormant in the houses of villagers. But to recognise that the policy of financial inclusion leads to an upward pressure on inflation does not mean that we should abandon it. Likewise, to say that greater benefits directed to the poor will cause the price of essentials to rise does not mean that we should not give greater benefits to the poor. That antibiotics administered to a patient suffering from pneumonia is likely to cause acidity does not mean that you stop giving the antibiotics but that you take additional precautions to keep the acidity under control.

16 It has been argued elsewhere (see Government of India 2011, Chap 2) that this principle of one economy, one central bank has been weakened in recent times. With globalisation, the world economy is increasingly beginning to look like a single economy, but to the extent that the world has many central banks with the right to create money, we are tending to get back to the kind of world we worked hard to get out of. This is one phenomenon (multiple money creating authorities in an increasingly uniform global economy) that has been dramatically altering the nature of inflation in recent times. As Reddy warned in 2009, the injection of liquidity around the world to jump-start various economies caught in recession created the risk of inflation (2011, Chap 4). Subsequent experience has borne this out.

17 From now on, there will be no reason to treat the repo and reverse repo as separate variables b ecause at the time of the last monetary policy review, on 3 May 2011, the RBI declared that it was freezing the spread between the repo and reverse repo at 100 basis points. If the repo is set at x%, by definition the reverse repo will be (x-1)%.

18 For an analysis of the Indian repo market, see Bandopadhyay 2011.

19 This does not happen in a mechanical fashion. I ndian banking, in this sense, is not “boring” (Subbarao 2011). There is nevertheless a link and a certain amount of pass through between interbank interest rates and bank-to-customer interest rates.

20 Recently, the RBI has also tried to use the savings account interest rate as a monetary policy instrument, raising it in May 2011 from 3.5% to 4.0%

21 Inflation can also be affected by changes in the exchange rate regime and policy concerning capital account convertibility (for a discussion, see Tarapore 2001). These are, however, not discussed in this paper. Further, in recent years there has not been any major shift in these policies for that to be an important factor in explaining shifts in the inflation rate.

22 For philosophical accuracy, it may be pointed out that even in engineering it is not written in stone though the relationships are more stable there than in the science of banking.

23 The notion of “liquidity” is not as obvious as popular discourse makes it out to be. There is the question about why a mere change in the portfolio of what a person holds should alter liquidity. I am unable to answer this question here and

Economic & Political Weekly

october 8, 2011 vol xlvi no 41

anyway doubt there is a known answer to it. The problem is briefly elaborated on (without resolution) later.

24 The analysis from here till the end of this section was deeply influenced by discussion and correspondence with D Subbarao, RBI governor. However, the argument presented here and the positions taken are mine and do not necessarily reflect the RBI’s views.

25 The argument may also hinge critically on what the cause of the interest rigidity is in the first place. It is possible to argue that my analysis does not work, at least not in a straightforward m anner, when the initial rigidity is caused by the Stiglitz and Weiss (1981) type of argument. But, minimally, this warns us that the nature of the connection between interest rate and liquidity may be more complex than is popularly assumed. And it points to the need for research on the i ntricate connection between interest rates and liquidity.

26 I have in this paper, for the most part, stayed away from the classic debate about macroeconomic trade-offs between inflation and other growth-related variables (see Chitre 2010 for a discussion in the Indian context). A recent paper by Dholakia and Sapre (2011) finds little evidence of the traditional Phillips curve-type negative r elation between inflation and unemployment in India and argues that a strategy of fast recovery from adverse shocks is unlikely to give rise to inflation, thereby implicitly suggesting that if there is inflation (as is the case at the time of writing this paper), its cause lies not in growth recovery but elsewhere.

27 There has been a lot of soul-searching in the US in recent times about the slow decline in its unemployment rate and the inadequate creation of new jobs. This can be seen as a natural side-effect of low interest rates and abundant liquidity. Given that productivity is rising, what this indicates is that firms are using relatively more capital-intensive techniques because of the availability of cheap capital. Even during the Great Depression in the US, the last indicator to pick up was employment. In 1936, seven years after the Great Crash, job creation was weak. This becomes less worrying once one realises that it is a natural sideeffect of the effort to jump-start an economy by easing credit.


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    october 8, 2011 vol xlvi no 41

    Appendix: Table 1: Inflation in India (1972-2011)
    All Commodity Combined Food* All Commodity Combined Food* All Commodity Combined Food* All Commodity Combined Food*
    April 1972 6.88 9.53 Sept 1977 4.85 6.13 Feb 1983 7.80 13.37 July 1988 9.74 12.14
    May 1972 7.23 9.27 Oct 1977 4.28 5.68 March 1983 8.72 16.10 Aug 1988 7.07 7.58
    June 1972 7.07 11.14 Nov 1977 4.30 6.50 April 1983 7.21 12.90 Sept 1988 6.93 8.03
    July 1972 8.11 13.69 Dec 1977 4.68 7.12 May 1983 8.66 17.47 Oct 1988 7.73 9.93
    Aug 1972 9.51 16.62 Jan 1978 3.19 5.65 June 1983 7.34 12.97 Nov 1988 6.57 8.03
    Sept 1972 8.93 15.24 Feb 1978 -0.71 -2.11 July 1983 7.06 11.76 Dec 1988 6.10 7.55
    Oct 1972 10.98 19.37 March 1978 0.00 -2.49 Aug 1983 6.70 9.77 Jan 1989 5.48 7.42
    Nov 1972 12.27 19.82 April 1978 -0.87 -4.47 Sept 1983 7.58 12.52 Feb 1989 5.41 5.87
    Dec 1972 13.96 22.78 May 1978 -2.29 -7.10 Oct 1983 7.98 14.12 March 1989 5.45 4.38
    Jan 1973 10.75 15.76 June 1978 -1.91 -6.66 Nov 1983 7.66 13.91 April 1989 5.60 4.78
    Feb 1973 12.71 18.39 July 1978 -1.01 -5.63 Dec 1983 7.77 14.28 May 1989 6.37 7.35
    March 1973 12.77 16.38 Aug 1978 -0.80 -5.33 Jan 1984 8.32 14.15 June 1989 6.18 6.50
    April 1973 13.89 17.38 Sept 1978 -0.85 -6.93 Feb 1984 7.40 10.94 July 1989 5.96 4.85
    May 1973 16.96 22.65 Oct 1978 1.19 -3.52 March 1984 7.19 9.51 Aug 1989 7.90 8.06
    June 1973 17.13 22.04 Nov 1978 1.68 -3.11 April 1984 6.54 6.88 Sept 1989 9.07 8.79
    July 1973 18.24 21.60 Dec 1978 -0.11 -6.73 May 1984 5.71 5.22 Oct 1989 7.88 3.85
    Aug 1973 16.70 17.09 Jan 1979 0.60 -6.15 June 1984 7.29 9.20 Nov 1989 7.58 2.07
    Sept 1973 16.57 16.04 Feb 1979 1.82 -4.81 July 1984 7.75 8.56 Dec 1989 7.55 1.06
    Oct 1973 17.67 15.89 March 1979 3.39 -1.90 Aug 1984 7.69 7.32 Jan 1990 7.83 1.73
    Nov 1973 21.61 19.12 April 1979 7.12 2.19 Sept 1984 6.52 3.45 Feb 1990 8.27 2.91
    Dec 1973 20.78 18.39 May 1979 8.41 5.19 Oct 1984 6.87 4.00 March 1990 8.62 5.14
    Jan 1974 25.99 22.91 June 1979 9.58 8.12 Nov 1984 6.41 3.19 April 1990 9.09 7.94
    Feb 1974 25.87 20.75 July 1979 13.33 12.89 Dec 1984 5.89 1.94 May 1990 8.73 7.10
    March 1974 29.20 20.78 Aug 1979 16.91 16.85 Jan 1985 5.58 2.06 June 1990 9.47 8.35
    April 1974 30.69 22.05 Sept 1979 18.54 18.36 Feb 1985 5.23 1.93 July 1990 9.60 8.44
    May 1974 29.70 20.02 Oct 1979 18.51 17.17 March 1985 5.57 2.34 Aug 1990 8.10 5.50
    June 1974 30.16 19.42 Nov 1979 18.40 14.83 April 1985 6.66 3.10 Sept 1990 7.49 5.28
    July 1974 30.33 21.35 Dec 1979 22.44 24.01 May 1985 6.43 2.01 Oct 1990 8.91 8.99
    Aug 1974 31.17 22.53 Jan 1980 22.68 23.02 June 1985 4.95 -0.09 Nov 1990 10.51 11.61
    Sept 1974 33.33 27.30 Feb 1980 25.23 29.40 July 1985 4.22 0.79 Dec 1990 12.00 15.27
    Oct 1974 29.45 23.97 March 1980 23.32 27.16 Aug 1985 3.53 1.26 Jan 1991 12.86 18.29
    Nov 1974 23.76 21.61 April 1980 20.20 23.38 Sept 1985 3.39 1.66 Feb 1991 13.51 20.43
    Dec 1974 23.43 20.62 May 1980 20.91 25.51 Oct 1985 3.21 1.07 March 1991 12.70 17.84
    Jan 1975 18.49 16.04 June 1980 22.13 23.94 Nov 1985 3.22 1.27 April 1991 11.57 14.75
    Feb 1975 15.94 14.33 July 1980 21.78 25.35 Dec 1985 4.07 3.12 May 1991 11.76 14.27
    March 1975 10.86 11.71 Aug 1980 19.13 22.85 Jan 1986 3.97 2.94 June 1991 12.15 15.93
    April 1975 8.41 10.30 Sept 1980 19.26 26.35 Feb 1986 4.89 3.68 July 1991 13.11 16.49
    May 1975 7.09 9.08 Oct 1980 19.08 28.07 March 1986 5.12 5.21 Aug 1991 16.09 20.42
    June 1975 4.04 5.88 Nov 1980 16.49 23.10 April 1986 4.30 8.39 Sept 1991 16.31 20.83
    July 1975 -0.34 -2.00 Dec 1980 13.26 15.32 May 1986 4.59 9.16 Oct 1991 14.68 19.15
    Aug 1975 -1.17 -2.05 Jan 1981 15.59 19.60 June 1986 4.80 8.48 Nov 1991 14.75 21.20
    Sept 1975 -2.47 -3.95 Feb 1981 16.21 18.94 July 1986 5.48 7.82 Dec 1991 14.26 19.84
    Oct 1975 -1.66 -2.80 March 1981 15.78 17.20 Aug 1986 5.87 8.78 Jan 1992 13.55 17.81
    Nov 1975 -2.31 -6.43 April 1981 17.32 21.10 Sept 1986 6.72 11.96 Feb 1992 12.94 16.49
    Dec 1975 -4.19 -11.35 May 1981 15.79 16.68 Oct 1986 7.02 14.07 March 1992 13.56 17.33
    Jan 1976 -5.94 -14.55 June 1981 13.19 14.92 Nov 1986 7.11 13.85 April 1992 13.80 18.72
    Feb 1976 -6.36 -15.02 July 1981 11.02 9.80 Dec 1986 6.23 11.22 May 1992 13.76 18.57
    March 1976 -6.87 -15.92 Aug 1981 11.10 8.80 Jan 1987 6.68 11.63 June 1992 12.95 16.19
    April 1976 -5.25 -12.96 Sept 1981 7.96 1.82 Feb 1987 5.53 9.27 July 1992 11.74 14.98
    May 1976 -4.99 -13.14 Oct 1981 7.37 0.55 March 1987 5.34 7.82 Aug 1992 9.37 11.95
    June 1976 -3.54 -11.06 Nov 1981 8.86 4.91 April 1987 5.37 6.44 Sept 1992 9.65 9.70
    July 1976 0.91 -3.71 Dec 1981 8.71 4.61 May 1987 5.93 7.49 Oct 1992 10.56 10.49
    Aug 1976 0.51 -4.49 Jan 1982 6.80 3.36 June 1987 6.10 6.21 Nov 1992 9.09 8.18
    Sept 1976 1.13 -3.98 Feb 1982 3.68 -0.77 July 1987 5.87 6.51 Dec 1992 8.54 8.52
    Oct 1976 0.28 -6.45 March 1982 2.63 -2.67 Aug 1987 8.09 9.13 Jan 1993 7.57 6.44
    Nov 1976 1.90 -3.58 April 1982 3.26 -1.70 Sept 1987 8.17 8.14 Feb 1993 7.58 6.19
    Dec 1976 4.85 3.37 May 1982 2.84 -2.59 Oct 1987 7.98 7.05 March 1993 7.07 5.74
    Jan 1977 7.45 7.67 June 1982 4.05 1.50 Nov 1987 9.03 8.99 April 1993 6.93 5.69
    Feb 1977 10.86 14.21 July 1982 3.01 2.13 Dec 1987 9.69 10.89 May 1993 6.95 5.44
    March 1977 12.48 18.59 Aug 1982 3.10 4.75 Jan 1988 10.06 9.95 June 1993 7.01 4.61
    April 1977 10.77 15.06 Sept 1982 4.20 7.25 Feb 1988 10.70 12.84 July 1993 7.28 4.83
    May 1977 10.69 14.98 Oct 1982 4.16 6.05 March 1988 10.66 13.84 Aug 1993 7.95 6.38
    June 1977 9.80 12.79 Nov 1982 5.72 8.63 April 1988 10.70 11.15 Sept 1993 8.76 9.24
    July 1977 6.25 7.13 Dec 1982 6.18 9.51 May 1988 9.52 8.19 Oct 1993 8.52 8.88
    Aug 1977 5.55 6.33 Jan 1983 5.88 9.08 June 1988 9.42 9.95 Nov 1993 8.59 8.37
    Economic & Political Weekly october 8, 2011 vol xlvi no 41 63
    Appendix: Table 1: Inflation in India (1972-2011) (Contd)
    All Commodity Combined Food* All Commodity Combined Food* All Commodity Combined Food* All Commodity Combined Food*
    Dec 1993 8.77 7.10 May 1999 3.33 5.41 Oct 2004 7.10 3.49 Feb 2008 5.68 3.93
    Jan 1994 9.11 6.42 June 1999 2.50 2.12 Nov 2004 7.47 6.06 March 2008 7.71 6.71
    Feb 1994 9.45 6.28 July 1999 1.99 1.01 Dec 2004 6.47 4.01 April 2008 7.86 6.63
    March 1994 10.51 6.70 Aug 1999 2.84 3.70 Jan 2005 5.86 2.85 May 2008 8.20 7.30
    April 1994 13.55 11.42 Sept 1999 3.20 3.03 Feb 2005 5.32 1.92 June 2008 10.89 8.00
    May 1994 13.24 12.96 Oct 1999 3.45 0.74 March 2005 5.63 2.46 July 2008 11.15 7.78
    June 1994 13.67 15.76 Nov 1999 3.09 0.17 April 2005 5.33 2.59 Aug 2008 11.12 7.82
    July 1994 13.25 14.39 Dec 1999 2.81 0.12 May 2005 4.59 1.49 Sept 2008 10.78 9.15
    Aug 1994 12.16 13.12 Jan 2000 3.55 2.36 June 2005 4.68 2.67 Oct 2008 10.66 10.64
    Sept 1994 10.52 10.28 Feb 2000 3.54 2.98 July 2005 4.84 4.07 Nov 2008 8.65 10.97
    Oct 1994 10.73 10.56 March 2000 5.58 4.46 Aug 2005 3.48 2.05 Dec 2008 6.68 10.42
    Nov 1994 11.49 11.78 April 2000 6.53 3.24 Sept 2005 4.38 3.18 Jan 2009 5.87 12.14
    Dec 1994 12.73 12.89 May 2000 6.30 2.46 Oct 2005 4.67 4.07 Feb 2009 3.61 9.10
    Jan 1995 13.95 16.63 June 2000 6.56 2.57 Nov 2005 3.94 3.08 March 2009 1.65 7.31
    Feb 1995 13.69 16.43 July 2000 6.54 1.40 Dec 2005 4.38 3.90 April 2009 1.21 8.76
    March 1995 12.45 14.34 Aug 2000 6.09 -0.58 Jan 2006 4.36 5.65 May 2009 1.45 9.37
    April 1995 10.98 10.32 Sept 2000 6.47 -0.84 Feb 2006 4.45 6.12 June 2009 0.39 10.42
    May 1995 10.99 8.01 Oct 2000 7.49 -0.97 March 2006 4.24 5.24 July 2009 0.31 11.10
    June 1995 9.73 5.29 Nov 2000 7.62 -1.49 April 2006 4.97 5.08 Aug 2009 0.54 12.97
    July 1995 9.63 6.34 Dec 2000 8.49 -0.05 May 2006 6.05 6.71 Sept 2009 1.40 13.21
    Aug 1995 8.94 5.97 Jan 2001 8.70 -0.04 June 2006 6.80 7.62 Oct 2009 1.79 12.66
    Sept 1995 8.94 7.04 Feb 2001 8.33 -0.42 July 2006 6.54 4.99 Nov 2009 4.73 17.17
    Oct 1995 8.43 7.10 March 2001 6.42 -1.72 Aug 2006 7.11 7.01 Dec 2009 7.15 20.21
    Nov 1995 8.22 7.18 April 2001 5.41 -1.01 Sept 2006 6.96 8.71 Jan 2010 8.68 19.80
    Dec 1995 6.64 5.85 May 2001 5.60 0.05 Oct 2006 6.93 8.35 Feb 2010 9.65 20.22
    Jan 1996 4.99 2.46 June 2001 5.30 0.57 Nov 2006 6.73 7.98 March 2010 10.35 18.50
    Feb 1996 4.45 2.79 July 2001 5.23 1.01 Dec 2006 6.96 9.82 April 2010 10.88 16.09
    March 1996 4.53 5.45 Aug 2001 5.41 1.96 Jan 2007 6.64 9.31 May 2010 10.48 15.85
    April 1996 3.69 6.75 Sept 2001 4.52 2.40 Feb 2007 6.63 9.22 June 2010 10.25 15.30
    May 1996 3.58 8.13 Oct 2001 2.91 2.35 March 2007 6.72 9.62 July 2010 9.98 14.31
    June 1996 3.65 8.84 Nov 2001 2.59 3.04 April 2007 6.22 10.04 Aug 2010 8.87 11.06
    July 1996 4.27 7.75 Dec 2001 2.08 3.47 May 2007 5.52 8.60 Sept 2010 8.98 11.49
    Aug 1996 4.93 8.47 Jan 2002 1.51 2.85 June 2007 4.46 6.26 Oct 2010 9.08 10.56
    Sept 1996 5.09 8.18 Feb 2002 1.39 3.71 July 2007 4.42 8.17 Nov 2010 8.20 6.76
    Oct 1996 4.58 7.81 March 2002 1.76 3.07 Aug 2007 4.04 6.92 Dec 2010 9.45 9.94
    Nov 1996 Dec 1996 Jan 1997 4.49 5.24 5.16 8.97 12.64 13.38 April 2002 May 2002 June 2002 1.50 1.56 2.43 2.65 2.41 3.39 Sept 2007 Oct 2007 Nov 2007 3.39 3.19 3.73 4.60 4.16 3.72 Jan 2011 Feb 2011 March 2011 9.47 9.54 9.04 10.28 6.77 6.81
    Feb 1997 March 1997 5.49 5.40 13.75 12.16 July 2002 Aug 2002 2.79 3.34 3.23 4.36 Dec 2007 Jan 2008 4.01 4.54 2.94 2.17 April 2011 8.66 7.60
    April 1997 5.82 10.28 Sept 2002 3.53 4.21 Table 2: Inflation in Korea and China
    May 1997 5.06 6.66 Oct 2002 3.08 2.89 Year-on-Year Inflation
    June 1997 5.04 5.79 Nov 2002 3.39 3.02 Year China Korea Year China Korea
    July 1997 3.62 4.89 Dec 2002 3.34 1.32 1971 -0.10 13.43 1991 3.40 9.33
    Aug 1997 Sept 1997 3.29 3.75 4.28 4.12 Jan 2003 Feb 2003 4.22 5.35 2.56 3.25 19721973 0.15 0.10 11.48 3.22 1992 1993 6.40 14.70 6.21 4.80
    Oct 1997 4.38 4.85 March 2003 5.99 3.75
    1974 0.64 24.53 1994 24.10 6.27
    Nov 1997 Dec 1997 3.98 4.05 2.64 2.54 April 2003 May 2003 6.65 6.51 4.61 5.66 19751976 0.44 0.29 25.21 15.27 1995 1996 17.10 8.30 4.48 4.93
    Jan 1998 5.07 6.30 June 2003 5.34 5.33
    1977 2.72 10.18 1997 2.80 4.44
    Feb 1998 March 1998 4.19 4.35 3.53 3.97 July 2003 Aug 2003 4.71 3.95 4.03 1.83 19781979 0.66 1.88 14.44 18.26 1998 1999 -0.80 -1.40 7.51 0.81
    April 1998 4.58 7.02 Sept 2003 4.90 3.16 1980 5.99 28.70 2000 0.40 2.26
    May 1998 June 1998 5.66 6.39 10.42 12.62 Oct 2003 Nov 2003 5.13 5.42 5.00 3.95 1981 2.38 21.35 2001 0.73 4.07
    1982 1.93 7.19 2002 -0.77 2.76
    July 1998 7.07 14.68 Dec 2003 5.74 4.50 1983 1.50 3.42 2003 1.17 3.52
    Aug 1998 Sept 1998 6.52 5.94 12.25 13.56 Jan 2004 Feb 2004 6.50 6.14 4.97 4.42 19841985 2.83 9.30 2.27 2.46 2004 2005 3.90 1.82 3.59 2.75
    Oct 1998 6.45 16.35 March 2004 4.78 3.59
    1986 6.50 2.75 2006 1.47 2.24
    Nov 1998 Dec 1998 7.14 6.28 18.18 14.04 April 2004 May 2004 5.50 5.86 2.91 2.68 19871988 7.30 18.80 3.05 7.15 2007 2008 4.77 5.90 2.54 4.67
    Jan 1999 4.53 7.60 June 2004 6.12 1.34
    1989 18.00 5.70 2009 -0.69 2.76
    Feb 1999 March 1999 April 1999 5.37 5.36 4.02 8.80 9.57 7.23 July 2004 Aug 2004 Sept 2004 7.15 8.48 7.20 4.16 6.80 4.31 1990 3.10 8.57 2010 3.33 2.96 Inflation figures from 1971 to 1979 are from the International Labour Organisation (ILO) and from 1980 onwards from the World Economic Outlook (WEO) database.
    64 october 8, 2011 vol xlvi no 41 Economic & Political Weekly

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