Monday, October 24, 2011

Project Tanzanite: Obtaining fundamental progress in the macroeconomics of developing countries

I was at a meeting in London recently, organised by the IGC, on the subject of the research agenda in macroeconomics for developing countries. This made me think about how to make progress.

The US as the shared dataset for mainstream macroeconomics

All existing knowledge on macroeconomics is rooted in data about the US economy. The US is seen as a canonical developed country. Economists all over the world have treated it as a common object of study, when building macroeconomics. It is a shared dataset. Researchers and Ph.D. students routinely pull out a paper from the literature, and replicate the results, as a first stage of offering innovations: all this is rendered convenient by using the US as a shared dataset. New work is generally obliged to demonstrate value-add in the context of the US dataset.

The US works as a shared dataset because it has high quality data. Good quality data starts right after 1945, because there was no destruction within the country, hence the early post-war years are not distorted by unusual reconstruction. There was a steady shift away from dirigisme from 1945 onwards, but for the rest there has been no regime change: events like the breakdown of communism or the rise of the European Union or the Euro have not taken place.

In the US, a high quality statistical system has produced good aggregative data. Organisations like NBER have processed this data nicely to create datasets about the business cycle. High quality datasets are available about households, firms and financial markets. Household- and firm-level data has been nicely utilised to obtain numerical values for parameters in macroeconomic models: why estimate something using macro data when you know it using gigantic and well trusted micro datasets? Finally, the major question for macro today is the fusion with finance, and the US has nice data for the financial system.

As a consequence, facts about the US are the shared dataset used in all mainstream macro research across the world.

The insights developed in this literature, which has examined the US economy, have been transported with fair success, into other developed countries. Thus, this emphasis on the US as a common dataset has delivered good results. As an example, the revolution in monetary policy which was thought through by Friedman, Lucas, etc. was created using US data. It has usefully reshaped central banks worldwide. US data was essential for inventing inflation targeting, but inflation targeting has worked well outside the US.

The major obstacle on building a macroeconomics for developing countries

The major obstacle that interferes with doing macroeconomics in developing countries is data.

India is a good example of what goes wrong. The standard GDP data is in bad shape. The annual GDP data is deplorable, and the quarterly GDP data that is so essential for doing macroeconomics is worse. The IIP is untrustworthy. Put these together, and we don't have an output series, really.

The BOP data is measured fairly well. Some plausible inflation data is now starting to come together. The statistical system run by the government does not produce seasonally adjusted data [succor]. Given the absence of the Bond-Currency-Derivatives Nexus, the bulk of data about interest rates that is required is missing; policy makers are flying blind. The standard household survey (NSSO) is in bad shape: it does not produce panel data, surveys are only conducted once in a few years, and there are incentive issues about the front-line staff who interact with households.

The large firms are observed using the CMIE database; the small firms are not observed using the ASI dataset. The CMIE household survey is starting to generate knowledge about households, but this only got started a few years ago. While the CMIE datasets (on firms and households) can be aggregated up to create many interesting macro series, so far this process has only begun in a small way.

Faced with these problems, it is not surprising that little is known, at present, about macroeconomics in India. We know numerous important questions, and we know that we don't know the answers. The roadmap to progress is often, though not always, blockaded by data constraints.

Many such problems bedevil the statistical system in other developing countries also.

Economists have complained about bad data in developing countries for decades, and that hasn't changed things. And there is a uniquely perverse problem. Incremental progress with a gradually improving statistical system does not get the job done for us: By the time a country gets to good institutions and thus a good statistical system (e.g. Taiwan, South Korea, Israel, Chile), the country is not a developing country anymore and is thus not a useful dataset for studying the macroeconomics of developing countries. Chile has world class databases on households and firms, but you can't extract microeconomic facts using these datasets and use them in calibration if your object of inquiry is the canonical developing country.

A proposal

How can we make progress? I feel the first idea that we need to agree on is that we do not need many developing countries to build a great literature. We need a shared dataset, a lingua franca, a replication platform, using which we will build a literature. We need a country that will play the role, for the macroeconomics of developing countries, that has been played by the United States in conventional macroeconomics.

The second idea is that we should be a little more ambitious. We should not merely sit around hand-wringing, complaining about a problem that isn't going to solve itself. When scientists in other disciplines identify questions that call for evidence, they write funding proposals (sometimes running to billions of dollars) and organise themselves to create those datasets. Could we do similarly?

Specifically, imagine that we pick one canonical developing country. It's got to be a typical developing country in most respects. And, it should not be a conflict zone, it should have the basics of law and order and physical safety so that operations can be mounted in it. Christopher Adam of Oxford suggests that Tanzania is a good choice.

Imagine that, the system of interest (a developing country) keeps running, but it gets instrumented up to world class. In essence, we try to place first world instrumentation into a third world country. (To the extent that this data improves decision making in the country, we would suffer from `Heisenberg' effects).

This will call for financial resources and, more importantly, organisational capability. The physicists know how to organise themselves to build the Large Hadron Collider. Most of the time, economists do not organise themselves as laboratories or teams doing complex projects. This will be a bridge that we will have to cross.

As with the Large Hadron Collider, this is not a short-term project. It is a project that needs to run for 25 years, in order to generate a strong dataset.

At first, the project will generate useful facts for calibration, drawing on household survey and firm databases. Gradually, as the span of the time-series builds up, the full picture will start becoming clear.

If this works, it can ignite a literature where researchers from all across the world do replicable work off a common dataset. Perhaps Tanzania could then play a role, for the macroeconomics of developing countries, that is comparable with the role played by the United States in mainstream macroeconomics.

Sunday, October 23, 2011

Fighting back inflation is cheaper when there is credibility: A numerical example

A few days ago, I wrote a blog post about India's inflation crisis. For five years now, in every single month, the y-o-y CPI inflation has exceeded 5%. Under these conditions, economic agents have little confidence that RBI cares about inflation. They are now reporting double digit inflationary expectations. Under these conditions, inflation will be persistent. By itself, inflation is not going to go back to the target range of 4 to 5 per cent. This blog post made certain qualitative claims about fighting inflation under two scenarios: when the central bank has credibility and when it does not.

I recently came across a fascinating paper which is about a similar situation: it is about the problems faced in Ghana recently, in fighting back an inflation. It gives numerical values which are interesting for us. Their inflation was a bit worse than ours - they were at 20%. But for the rest, this analysis illuminates what we face in India today. The paper is : A model for full-fledged inflation targeting and application to Ghana, by Ali Alichi, Kevin Clinton, Jihad Dagher, Ondra Kamenik, Douglas Laxton and Marshall Mills, IMF Working Paper, 2010.

Here is the main story. First, look at the projected trajectory for what happens to the short term interest rate and inflation under conditions of weak credibility of the central bank:

The nominal rate is required to go all the way out to 26%. Inflation responds slowly. It is projected to get to the target (with some overshooting at first) by 2016. The cumulative damage to GDP growth, in this process of exorcising inflation, works out to roughly 20 per cent of GDP. (This is the sum total of the output cost over all the years taken in wrestling this inflation down).

Compare this against the picture obtained when the central bank has high credibility:

This is much nicer story. The nominal interest rate starts out high (18%) but inflation responds rapidly and the interest rate can also come down rapidly. By 2013, inflation is at the target. The cumulative damage to GDP growth, in this process of exorcising inflation, works out to only 4% of GDP.

This difference is striking. Lacking credibility, the central bank has to force a total output loss of 20% of GDP, and they get to target inflation by 2016. With credibility, the job gets done three years sooner, and at a cost of only 4% of GDP of output loss.

This is an essential insight into our inflation crisis today. In the end, raising rates will get the job done. No matter how bad is the monetary policy transmission, no matter how deeply ingrained inflationary expectations have become, raising rates will ultimately deliver price control. The choice that we face is between being bloody-minded about it, or simultaneously undertaking RBI reforms which involve zero output loss, and improve RBI's credibility.

Saturday, October 22, 2011

Household behaviour that counteracts fiscal expansion

Suppose a government tries to boost demand in the economy by boosting the deficit.

A fascinating feature of the situation is: Households are not wood, households are not stones, but men. And being men, they will look forward, they will optimise. Households know that all government expenditure requries taxation: all that is achieved by running a deficit today is postponing taxes to tomorrow.

India's fiscal stance is now likely to lead to increased taxation in the future. We have a nice wide deficit today, but it's increasingly likely that fresh taxation will come up in the future.

A core feature of human beings is that we do not like to deal with fluctuations in our consumption. So faced with the prospect of taxation tomorrow, we are prone to cut back on consumption today.

Through this, when a government raises the deficit today, some of this effect is counteracted by households that pull back on expenditure. Raising the fiscal deficit is less expansionary than some would think.

Economists have a fancy name for this: it's called Ricardian Equivalence. This was originally thought up by David Ricardo, but made famous by Robert Barro. It is one of the many ways in which forward looking households are of essence in thinking about macroeconomics. "You are not wood, you are not stones, but men; and being men, you will optimise".

Sunday, October 16, 2011

Saturday, October 15, 2011

Reining in the inflationary dragon

A lot is being written about inflation in India today. I thought it's worth writing about the fascinating insights into inflation that come from focusing on the distinction between tradeables and non-tradeables.

What is a tradeable

A tradeable is a product which can be transported across the world at relatively low cost. As an example, steel is tradeable while cement or paint are mostly non-tradeable barring special short-hop opportunities like Gujarat-Karachi or Amritsar-Lahore or Calcutta-Chittagong or Trivandrum-Colombo.

Steel is a nice tradeable that one can think clearly about. There are no barriers to the movement of steel worldwide. Hence, there is only a world price of steel. The quoting convention used worldwide is to express the price of steel in USD. The price of steel in India is thus the world price of steel multiplied by the INR/USD exchange rate, plus a markup for freight (The cif/fob ratio).

If there is a customs duty of (say) 10%, then the price of steel in India is 1.1 times the world price of steel expressed in rupees. For the rest, nothing changes when a customs duty is introduced. Gram for gram, every fluctuation in the INR/USD or the world price of steel shows up in the domestic price of steel.

Non-tradeables are things like cement (which are hard to transport) or haircuts (which are impossible to transport).


Before we can analyse and control inflation, we must measure it well. Inflation is defined as the rise in the price of the average household consumption basket. The CPI is the best measure of inflation in India.

Everything in the CPI basket can be classified into the two categories: tradeable vs. non-tradeable. As a thumb rule, WPI non-food non-fuel is a rough measure of tradeables inflation. Fluctuations in food and services prices, which make the CPI diverge away from WPI non-food non-fuel, are a measure of non-tradeables.

Year-on-year inflation reflects an averaging over 12 months. If you want to get a faster sense of what is going on, you need to look at point-on-point seasonally adjusted changes. These yield early warnings of inflation, which are 5.5 months ahead on average. Such data is updated every Monday by us. The shift from y-o-y inflation, to p-o-p SA inflation, is a free lunch in measurement and monitoring.

The WPI is a useful database of many price time-series in India. But the overall WPI is useless in thinking about inflation in India: there is no household in India which consumes the WPI basket.

The use of WPI inflation, and the exclusive use of y-o-y inflation, are litmus tests of professional competence in the Indian landscape.

The function of the central bank

The job of RBI is to deliver low and stable inflation: to deliver y-o-y CPI inflation of between 4 to 5 per cent.

They have failed in this task. From February 2006 onwards, in every single month, y-o-y CPI inflation has exceeded 5 per cent. This is an important time for introspection at RBI and outside it. What have we done wrong, in the structuring of RBI, which has got us into this mess?

It is useful to think of this as a principal-agent problem. The people of India are the principal. RBI is the agent. The principal hires the agent and gives him resources. In return, the agent has to be held accountable. Delivering low and stable inflation is the accountability mechanism. It is a quantitative monitorable measure of the performance of the central bank. That we have sustained failure on this function, from February 2006 onwards, suggests that we should be modifying the nature of the contract between the principal (the people of India) and the agent (RBI).

How RBI can influence the price of tradeables

RBI has absolutely no say on the world price of steel. In that sense, the prices of tradeables are beyond the control of RBI.

When RBI raises the interest rate, more capital comes into India, which tends to give an INR appreciation, thus making tradeables cheaper. Thus, an RBI rate hike does impact upon the domestic price of tradeables.

It is also worth pointing out that the central banks of most major countries are high quality inflation targeters. They deliver on their mandate of delivering low and stable inflation. As a consequence, inflation in the global tradeables basket tends to be low and stable. Tradeables prices are a helpful source of price stability, most of the time.

(That a large part of the CPI basket is tradeable, and seemingly beyond the control of the central bank, is no excuse. There are dozens of high quality central banks visible in the world, with very large shares of the CPI basket in tradeables, who are delivering on inflation targets. We in India should not accept excuses).

How RBI can influence the price of non-tradeables

Non-tradeables reflect aggregate demand and aggregate supply in India. RBI can influence these by raising or lowering the short-term interest rate. When interest rates are made slightly higher, household consumption and investment demand are slightly lowered.

A critical feature of non-tradeables inflation is expectations. If people expect 10% inflation, they tend to wire high price rises into their negotiation of wage and other contracts. This generates inflationary momentum. Particularly in a place like India, where the institutional structure of monetary policy is primitive, economic agents have little confidence in the ability of policy makers to rein in inflation. As a consequence, inflation is highly persistent. Once high inflation sets in, economic agents expect high inflation to continue. There is a great deal of momentum in inflation.

For years now, some economists have argued that inflation will subside by itself. It will not. Inflation does not mean-revert to the target zone of 4 to 5 per cent by itself. We are now in a trap of high inflationary expectations. This structure of expectations will need to be broken. This can happen in two ways. RBI needs to turn a new coat, and convince people that it now cares about inflation without any other conflicts of interest. And, rate hikes have to take place.

There are two paths to inflation control: changing the structure of expectations and reducing aggregate demand. The former is almost a free lunch. It only requires institutional change. The latter is hard work; it inflicts pain.

What about supply factors?

Some argue that supply bottlenecks in India - such as hideous rules about mandis - are the cause of inflation.

The trouble with this explanation is that the supply bottlenecks have always existed. They have existed in high inflation times and in low inflation times. It is, thus, not possible to claim that supply bottlenecks have caused the inflation crisis which began in February 2006.

Can rate hikes deliver inflation control?

When C. Rangarajan was RBI governor, there was an inflation crisis, and rate hikes did deliver on inflation control. The phase of price stability ushered in then lasted all the way till February 2006. This shows us that even in India, it can be done.

We have to remember that in his time, the monetary policy transmission was much weaker than what we see today. With a bigger wall of capital controls, domestic rate hikes did not deliver inflation control by impacting on the INR (through higher capital inflows). With a smaller and weaker Bond-Currency-Derivatives Nexus, the monetary policy transmission from the short rate into aggregate demand was inferior, then. Yet, he got it done.

Conversely, with a very primitive financial system and monetary policy transmission, the central bank of Zimbabwe delivered a nice hyperinflation. We can quibble about the potency of the monetary policy transmission, but we should not doubt the ultimate domination of monetary policy in shaping inflation. In the long run, little else matters in shaping inflation.

Part of the story of the 1990s lies in clarity of purpose at RBI and policy credibility. Rangarajan's period had good quality speeches, which did not dilute the message on inflation control as the dharma of the central bank. In contrast, in recent times, RBI has repeatedly written low quality speeches. To an expert reader, they have conveyed the lack of knowledge on monetary economics at RBI. To the non-expert reader, they have waffled on the subject of taking responsibility, and have encouraged the average economic agent to think that high inflation is here to stay.

Thursday, October 13, 2011

Steve Jobs and Dennis Ritchie

Steve Jobs and Dennis Ritchie both died within a few days of each other.

In my mind, there are four most important people in the story of computer software. The story begins with Ken Thompson and Dennis Ritchie, who figured out how to write an operating system (Unix). With this, we got the first powerful beasts.

The third person in the story is Bill Joy, who got the beasts to talk to each other (BSD). This gave us the Internet.

The fourth person in the story is Steve Jobs, who gave the networked beasts a pretty face, who got mere mortals to command the beasts.

Today, the wonders of the world of computing are: iPad, iPhone, Android, Kindle, Macbook Air. Every single one these is derived from the work of these four people. Wow.

(iPad, iPhone, Macbook Air run variants of Mac OS X, which is derived from NextOS which is a child of BSD. Android is derived from Linux, which is a ground-up rewrite of BSD. Some kindles run Linux, the others a forked Android).

Interesting readings

Shekhar Gupta in the Indian Express on the most important questions that the UPA-2 must now confront.

The 2G scandal is teaching us many things.

What ails asset reconstruction firms? and Reconstructing asset reconstruction firms by Tamal Bandyopadhyay in Mint.

An editorial in the Indian Express about SBI. Also see.

Remaking India, One T-Shirt at a Time, by Alex Frangos in the Wall Street Journal, about an interesting firm (Brandix India Apparel City) which is trying to break with the gloom on low-end garment manufacturing in India.

A. K. Bhattacharya in the Business Standard about Pulak Chatterjee taking over as principal secretary to the PM.

Revisiting SEBI's extreme step and An important case study while examining Jalan committee report by Mobis Philipose in Mint.

Mobis Philipose explains the SEBI order on some GDR issues.

The traffic of good quality talks in Delhi, in recent weeks, has been surprisingly good.

The Pakistan connection by Michael Meacher, in the Guardian, 22 July 2004.

You know a place is doing well when the performing arts flourish. Martin Petty writes about a rock concert in Kabul.

I was happy to see an open access economics journal -- Economics: The Open-Access, Open-Assessment E-Journal -- make it to rank 160 amongst the economics journals.

China Is An Economy On The Verge Of A Nervous Breakdown by Patrick Chovanec in the Business Insider.

Making top performers better, by Atul Gawande, in New Yorker magazine.

The end of the future by Peter Thiel, on National Review Online, and Innovation starvation by Neal Stephenson, write about a theme that I also worry about.

Wednesday, October 12, 2011

Policy and legal review of the Micro Finance Institutions (Development & Regulation) Bill: A new working paper

In response to the Second Micro Finance Crisis in Andhra Pradesh, which took place in October 2010, the Ministry of Finance has proposed a new ``Micro Finance Institutions (Development & Regulation)
Bill''. A new working paper by Shubho Roy, Renuka Sane and Susan Thomas analyses this bill from first principles of economics and law.

A great deal of traditional work in India, in the field of finance and public policy, has been poorly grounded in terms of logical thinking. A variety of government interventions are proposed, without fully showing the rationale for why a given intervention is valuable. I have often scented a socialistic impulse to intervene in the economy based on some vague notions of being a do-gooder. In addition, of course, there are interventions which cater to one special interest group after another.

I feel it is useful to work in a systematic way. The first task is to identify market failures (if any). All interventions must be considered guilty until proven innocent: an intervention must demonstrably tackle a manifestly visible problem. A useful classification scheme in finance is that all financial regulation falls under the three heads of consumer protection, prudential regulation and systemic stability. It is useful to pose problems under these three categories, then propose interventions which address them. At both levels, we need to move away from ex cathedra assertions towards logic and evidence that demonstrates that there is a problem, and logic and evidence that shows that the proposed intervention solves the identified problem without inducing collateral damage.

In the years to come, we need much higher quality drafting of law in India. This process will be assisted if independent analysis in the economy will critique draft law as has been done by the Roy, Sane and Thomas paper. We need more universities and think tanks who will subject all draft legislation and draft subordinate legislation to such scrutiny. On the government side, a greater effort on the formal rule-making process is required, whereby government is able to utilise such comments more effectively so as to strengthen the work.

Thursday, October 06, 2011

Should government put fresh equity capital into State Bank of India?

The discussion about State Bank of India (SBI) has treated one proposition as a given: that it is the job of the Ministry of Finance to continually inject capital into SBI so as to enable the growth of the SBI balance sheet; that SBI has a legitimate claim upon fiscal resources at all times.

I'm not sure this is a good way to think about the business of banking. The first task of a bank should be to produce adequate retained earnings so as to support the desired growth. If a bank cannot produce retained earnings enough to grow, there is reason for thinking that it should not grow.

Let's compare the performance of the best private bank (HDFC Bank) and a good PSU bank (Bank of Baroda) from this perspective.

Growth of the balance sheet and leverage

Let's look at how the two banks have fared, from 1999-2000 onwards, on the core issues of balance sheet growth and leverage:

1999-2000 2010-11
Bank of Baroda
   Total assets 58,623 358,397
   Leverage 18.12 17.07
   Total assets 11,731 277,429
   Leverage 15.33 10.93

From 1999-2000 to 2010-11, there has been a sharply superior performance by HDFC Bank. At the start, it was a small bank - with a balance sheet of just Rs.11,731 crore while BOB was roughly 5x bigger. By the end, HDFC Bank was at a balance sheet size of Rs.277,429 crore while BOB was at Rs.358,397 crore.

What is more, HDFC Bank did this while being more prudent: they deleveraged in this period: They went from a leverage ratio of 15.33 to a leverage ratio of 10.93. In contrast, BOB stayed at a much higher leverage (18.12 at the start and 17.07 at the end).

The bottom line: BOB grew net worth by 6.5 times and the balance sheet by 6.11 times. HDFC Bank grew net worth by 33.17 times and the balance sheet by 23.65 times.

So how did the net worth grow?

In the naive intuition that's being bandied about in the discussion about SBI, there would be an expectation that the expansion of net worth would be obtained by asking shareholders (new or existing) for money. What happened in HDFC Bank and BOB was a bit different.

The hallmark of a healthy bank is the production of retained earnings which can be ploughed back into the business. HDFC Bank did that: over this period, it brought 13.23% of total assets (summing across the 12 years) back into the business, so as to grow net worth. BOB did not do as well: it brought only 7.86% of total assets back into the business.

In addition, HDFC Bank raised 13.66% of total assets by bringing in fresh capital. BOB, in contrast, brought in only 2.11% of total assets into the business. You could criticise the Ministry of Finance for being niggardly in giving BOB equity capital.


A well run bank must put retained earnings back to work. If a bank is unable to fund its own growth by increasing net worth through retained earnings, there is reason to be concerned about the health of the core business.

A steady flow of new capital from shareholders, in order to enable growth, is not that different from recapitalisation in response to bad assets.

Public money is precious. The Ministry of Finance would do well to be very, very stingy in doling out public money to PSUs. Each Rs.5000 crore that goes into a PSU comes at an opportunity cost of 1000 kilometres of NHAI highways which could have been built using that money.

If a PSU cannot grow its balance sheet, odds are the problem lies within: it needs to become a better run business and thus grow the balance sheet using retained earnings. Such PSUs are precisely the ones who are the least deserving to gain fresh capital. If anything, fresh capital should be directed into banks like HDFC Bank (as the private capital markets have), who are doing a great job of producing retained earnings.

Wednesday, October 05, 2011

Watching markets work: Spreads at a money changer

I was at a money changer at Heathrow, and saw a tariff card, for purchase and sale of a few currencies (all to the GBP). (This was a while ago: It was on 12 May 2011).

This makes you think: What countries land up in this display, and how bad are the spreads? It's useful to express these spreads as 100*(offer-bid)/(0.5*(bid+offer)).

Let's start with the tightest spreads: USD and EUR. The spread -- 19.98% for the Euro and 20.87% for the USD -- is a pretty huge one compared with the incredible transaction efficiencies that we're used to seeing on NSE and BSE. And, there is an additional charge of min(1.5%, GBP 3) charge. This is a very inefficient consumer front-end, atleast compared to what we have seen is possible in the Indian exchange industry.

Where is this spread coming from? The bid/offer spread on the wholesale market for the USD/GBP and the EUR/GBP is roughly zero. The inventory risk carried by the money changing firm must also be quite low given that many customers are likely to come by with such orders with both buy and sell traffic. The USD/GBP is a floating rate, which imposes price risk on inventory, but the inventory is likely to be small, and it's not hard for the firm to lay off this risk in realtime using an automated order placement strategy on a currency futures exchange. Hence, the values of the spread seen there primarily represent the pure cost of the retail front-end : paying rent, paying salaries, the cost of capital etc.

The lowest value seen -- a spread of 19.98% for the EUR/GBP -- should be interpreted as the frontier. This reflects pure order processing costs. Every other currency fares worse than this. It's hence interesting to subtract out this lowest value, and try to understand how far the various currencies are from the frontier.

Euro 0
USD 0.892
Japan 2.141
Australia 2.479
Saudi Arabia4.372
UAE 4.705
Russia 6.181
Malaysia 6.911
Thailand 7.695
China 8.860
Kenya 9.823
Sri Lanka 13.788
India 16.853

Japan and Australia are floating rates with full convertibility. There is no illegality involved. But the inventory risk is greater given that these are smaller countries; there would be fewer buyers/sellers of their currencies to the GBP. The vol is much like GBP/USD or GBP/EUR, so the enhanced spread reflects purely the greater inventory risk. It may also be the case that currency hedging is harder -- is there an exchange where you can have an algorithm placing orders for GBP/AUD? I doubt it.

Saudi Arabia and UAE have credible hard pegs to the USD. Their vol to the GBP is exactly the vol of the USD to the GBP. (And, they are as convertible as the US). But their spreads are much bigger than that seen for the USD. It must reflect a small number of transactions and hence inventory risk. They are small countries and few transactions would be taking place. Many of their nationals would probably hold the bulk of their liquid wealth in USD so the question of transacting through the local currency might not even arise.

Russia has full capital account convertibility, so there is no illegality. But it's a highly volatile currency, hedging is likely to be hard, and the transaction flow is small. So we get the next step up in the spread, to 6.18%.

China has near-zero volatility to the USD, which means they are a high volatility rate to the GBP. GBP/USD is a fair proxy for hedging GBP/CNY. It is a big country so there must be quite a bit of traffic; there would be low inventory risk. The real issue is the illegality. The enhanced spread is the price paid by people undertaking these transactions, for the capital controls of China.

And then we have India, the fattest spread in this group of countries, where I reckon it's a combination of illegality (akin to China), low volume of transactions (since India is a much smaller economy than China) and currency volatility (since India floats while China does not). INR/GBP currency futures trading through an algorithm is not available to a global firm, since they are prohibited from sending orders into India.

I wasn't able to make any sense of the list of countries that showed up in the list. Why Kenya and Sri Lanka, and why not Nigeria or Indonesia?

Saturday, October 01, 2011

Pakistan's ISI and Salafi groups

Quasim Nauman and Zeeshan Haider have a story on Reuters, where they quote Ahmed Shuja Pasha as saying:
We have never paid a penny or provided even a single bullet to the Haqqani network.
Would Jalalludin Haqqani have come to anything without the ISI? I was reminded of the phrase above, when I saw the following fragment from Peter Tomsen's fabulous book, The Wars of Afghanistan:
Pakistani Foreign Minister Assef Ali and ISI Director General Nasim Rana took Pakistan's message on noninterference in Afghanistan to Washington in February 1996, prior to a massive Taliban offensive from Pakistani soil planned for the summer. In a February 9 meeting with Acting Secretary of State Strobe Talbott at the State Department, Foreign Minister Assef ``categorically denied'' that Pakistan was giving military assistance to the Taliban. ... ISI Director General Rana asserted that ``not one bullet'' had been provided to the Taliban by Pakistan.
During the 199s and down to the present, Pakistan's military and civilian leaders became highly skilled at denying Pakistan's covert empowerment of its unholy alliance partners inside Afghanistan and in Pakistan -- in other words, lying.