Jan 17, 2022

Sovereign Gold Bonds of Government of India – a risk factored evaluation

Draft for discussion (email comments to tirumalakv@gmail.com)


Unconventional monetary instruments carry risks that needs to be quantified to help policymakers make an informed decision by allowing an objective cost-benefit analysis.  

This paper discusses Sovereign Gold Bonds (SGBs), a unique monetary instrument issued by the Government of India and quantifies the risk that the government bears while underwriting the guarantee on the future gold price. One way to quantify this risk could be by using Black-Scholes-Merton’s option valuation model. It is seen that quantified risk arrived this way outweighs potential benefit arising from cheaper money raised through SGBs. This helps policymakers to understand the true risk they are undertaking by promising future gold price linked returns. 

Sovereign Gold Bonds (SGBs)

Sovereign Gold Bond (SGB) scheme was launched during November 2015. The main objective of SGB is to act as an alternative to purchasing/holding of physical gold. These bonds are issued on payment of Indian Rupees and is denominated in grams of gold. The bond returns the Indian Rupees equivalent to the same number of grams of gold at the time of maturity. The bond has a maturity period of eight years. Bonds are issued on behalf of the Government of India by the Reserve Bank of India (RBI) and has a sovereign guarantee. The bonds are restricted for sale to resident Indian entities. The investment limits are presently 4 kgs per fiscal year, for individuals and Hindu Undivided Family (HUF) and 20 kgs per fiscal year for Trusts and similar entities. The ceiling will be counted on financial year basis and will include the SGBs purchased during the trading in the secondary market. The ceiling on investment will not include the holdings as collateral by Banks and Financial institutions. Interest payable on these bonds is half-yearly @ 2.50% per cent per annum. Interest on the Bonds are taxable as per the provisions of the Income- tax Act. The bonds are available both in demat and paper form and are tradeable in the Secondary Market. The capital gains tax arising on redemption of SGB to an individual has been exempted. The indexation benefits will be provided to long terms capital gains arising to any person on transfer of bond.  

(Technical details on SGBs may be found at Appendix C. FAQs on the SGB scheme: https://m.rbi.org.in/scripts/FAQView.aspx?Id=109).

Series of SGBs are released multiple times every year to the public for subscription. There is no specified upper value on the amount released for subscription, and the public can subscribe as per the eligibility guidelines when the series opens for subscription. The SGB subscription has grown significantly in last two years, indicating that the bond is gaining traction with public. 


Financial year (April-March)

Issue value in Rs. Crore

Issue value in USD million (1USD=75 rupees)



















2021-22 (till Nov)



Table 1: Subscription to SGBs over years – Data from RBI


Gold import countermeasures

 SGBs may be seen as one of the countermeasures against increasing gold imports. Some other measures taken by Government of India to curb gold imports in recent years include increase in customs duty on gold, direct curbs on gold imports through 80:20 scheme, gold monetization scheme and allowing gold-based exchange traded funds. However, the trend in gold imports indicate that gold demand in India is inelastic to usual countermeasures. There may be cultural and other reasons for the same which is not discussed here. Gold based exchange traded funds have lost their importance after introduction of SGBs due to interest return of 2.5% per annum under SGB, absence of fund management charges and tax benefits on capital gains. 


YearValue in USD Billion
2021 (Jan-Nov)51.1
Source - Trademap for all years except 2021. For 2021, source is DGCIS data

Figure 1: India's gold import over years 


Comparison of SGB and Treasury Bonds

 The government borrows from market through issue of treasury bills and bonds. SGBs on the other hand are unique instruments, prices of which are linked to gold price. SGBs are also budgeted in lieu of market borrowing by the government. Government may thus resort to raising money through SGBs, where it may be able to raise public money at a rate cheaper than through similar maturity sovereign bonds. For example, the regular 10-year bond issued by government of India in 2021 carried a coupon rate of 6.1% (with a yield of around 6.2% when it was listed, current YTM is around 6.5%), whereas the SGB issued in 2021 with 8-year maturity carried a coupon rate of 2.5% (considering the interest paid as coupon). 

Gold price risk in SGBs 

While raising money through such unique instruments, the issuer bears the associated risks and should suitably price the instrument to account for such risks. If the government is the issuer, then such risks are ultimately borne by taxpayers and citizens unless they are nullified. In the case of SGBs, the gold price is anchored to the bond value at the time of issue.  Gold price fluctuation is a risk which the government bears.  In case of significant price appreciation of gold between the time of issue and maturity, the initial gains of the government may turn into losses. On the other hand, a drop in gold price may lead to additional gains for the government. 

One possible strategy to counter gold price risk could be to purchase equivalent amount of physical gold as a hedge, when the government issues the SGBs. However, this would be counter to the objective of the SGB – which aims to act as an alternative to purchasing/holding physical gold. Government would also incur storage and security costs on such physical gold. Additionally, government would incur a cost of 2.5% per year that is paid out as interest. Therefore, this strategy is not optimal. This paper therefore assumes that government doesn’t undertake any gold purchase to offset gold price risk. 

Central banks around the world buy gold for forex management and other purposes. RBI too buys/sells Gold for central banking/forex management purposes. It is not linked to SGB. SGB is a debt instrument issued by RBI on behalf of Government of India, which is a separate function of RBI under its responsibility as the public debt manager for the government. Thus, it is assumed for this paper that any fluctuation of gold assets in the forex reserves basket of RBI is also not to be linked to potential SGB hedging activities of the government. 

 A better way then, perhaps, to account for gold price risk would be to quantify it and account for the same in the instrument price. To do so, we shall start with quantification of gold price risk. 


Risk quantification for SGB 


Government earns an interest differential when it raises money through SGB over regular sovereign bonds. The yield on regular sovereign bonds of 8-years maturity is over 6 percent (based on yield curve), and such bonds would be listed for auction with annual coupons of around 6 percent. The annual coupon payout on SGB is 2.5% per annum. The differential of over 3.5% is the potential gain for the government when it chooses the SGB route to borrow from public. This potential gain comes with the gold price risk. One possible approach to quantify this gold price risk would be to treat SGB as a risky asset and use hedging techniques to arrive at the valuation for the underlying risk. 


We shall take a simple approach and compare whether the gains arising out of raising money through SGB outweighs the quantified risk. We may use a standard similar maturity sovereign bond for comparison. A sovereign bond has no risk for the purpose of our calculations. The mechanics would involve arriving at the gains coming from borrowing money using SGB over a standard sovereign bond, and check if this compares well with the risk involved. 


Let’s assume that an SGB worth 1000 crore Rupees (10 Billion Rupees) is issued at the same time as a sovereign bond of same par value with similar maturity period (8 years) during a reference year, say late 2021. The sovereign bond gives coupons, paid out semiannually at 6.1% per annum rate, until maturity and pays out the par at maturity along with last semiannual coupon. The SGB on the other hand pays 2.5% interest per annum, paid semiannually, and let’s assume for now that it also pays out par value at maturity along with the last installment of interest. The assumption of payout of par value (Rs. 1000 crore) at the time of maturity is to make the comparison with sovereign bond easier. If this plays out in real, the SGB would be a better way to borrow money from public as the interest rates to be paid on SGB is far lesser than that on a standard sovereign bond. However, the last par value payout on SGB might not be Rs 1000 crore, but it can be more or less than Rs 1000 crore depending on where the gold price prevails at the time of maturity. This risk is what we quantify now.  


The gold price risk for the Government can be modeled as the price for writing a European Call Option maturing in 8 years at a price equal to current value which equals the assumed par value that is paid out at maturity. The assumption is that the call buyers (public) would encash the option at any price, but from the SGB issuer’s point of view, any payout above par value is the gold price risk that is being borne over and above that of a normal sovereign bond. The call writer thus bears the risk of any upward movement in the price of Gold beyond the existing price. This paper uses Black-Scholes model to arrive at the call price for the European Option. One may also model Black’s equation for European future Option in this case. As the value for a European future Option and European Call Option contract maturing at the same time is same for both Black and Black-Scholes models, this paper shall use Black-Scholes. 


The SGB gold price risk modeled as a European Call Option is justified on the basis that SGBs are usually redeemed at maturity upon completion of eight years. While there is an option to list and trade the SGBs on secondary exchange from the fifth year onwards, it is noticed that the liquidity of SGBs is extremely limited and most of the bonds are kept in custody of investors and redeemed at maturity. This assumption may come under challenge once the SGB market develops further, and we may then need to revise the calculations to an American type Option. However, for now, we may use the assumption of European Call without losing accuracy. 


(Appendix B - calculations and formulae for Black-Scholes and Black’s model)


The calculation has the following steps:  


Step1: Calculate present value of all payments over eight years for a normal government bond. 

Step 2: Calculate present value of all payments over eight years for an SGB.

Step 3: Find the difference between present value of payouts at Step 1 and Step 2. This would give us the gains the government derives from issuing an SGB over a normal bond of eight-year maturity. 

Step 4: Calculate the price of writing a European Call Option with a strike price equal to the current price of gold. This is the quantified gold price risk. 


If the quantified value of risk at Step 4 is larger than the value arrived in Step 3, it means that the policymakers need to justify the additional price paid to raise money through SGB. 


Risk-free rate for Option price calculation


Black Scholes model uses the risk-free rate to discount for present value of future strike price of the Option. The current analysis relies upon the existing bond return rates on similar maturity duration bond (by interpolating the rates if required), to arrive at the risk-free rate (Appendix A). As government of India has never defaulted on its obligations, this paper considers the government bond rate for similar duration (8 years) as practically risk-free for the purpose of estimation.

The risk-free rate thus comes out to 6.1 % for an 8-year maturity bond. 


Standard deviation of Gold prices for Option price calculation 


The standard deviation (sigma for Black-Scholes) is arrived from historical estimation of fluctuation in gold prices in INR. 

Three different annualized standard deviations for the returns are calculated to generate three scenarios: 


·      Standard deviation for the returns covering period over 40 years from 1979 to mid-December 2021. The prices on weekly basis are used to calculate the annualized log returns and standard deviation. The standard deviation for this period comes to 0.189. 

·      For the period covering 8 years ending in mid-December 2021. The standard deviation for this period comes to 0.141. 

·      For the period covering 3 years ending in mid-December 2021. The standard deviation for this period comes to 0.152. 


These standard deviations look reasonable when compared against implied volatility in the gold futures market. For long term gold futures ending in December 2026, the implied volatility is around 17.15% (link). Thus, the standard arrived to generate the scenarios using historical data appears to be erring on the conservative side. 


Calculations and findings


a)    Benefit from issuing SGB over normal bonds


Differential gain arising due to coupon and par value payouts between regular bond raised at risk free rate of 6.1% with a semi-annual coupon payout of 6% per annum versus SGB raised at 2.5% per annual coupons paid out semi-annually is shown below. 


The government gains a total of 219.6 crore rupees measured in terms of present value (discounted at risk free rate) by issuing an SGB of Rs 1000 crores in place of a standard eight-year bond. 

Comparison calculation of SGB vs Normal Sovereign Bond

b)    Price to write the call option

The Black-Scholes equation is used to price the call option. The amounts required to write the Call option depends on the scenario using the Standard Deviation. The values in Rupee crores for a strike price of Rs 1000 crore are as shown below: 


Standard deviation

0.189 (40 yr)

0.141 (8 yr)

0.152 (3 yr)

Call option value/Quantified risk (in Rs Crores)





 The quantified risk arising from increase in gold price ranges from 426.6 to 402.5 crore rupees for every issue of 1000 crore rupees worth of SGBs depending on the standard deviation considered. The corresponding benefit arising out of lower coupon/interest on SGB is around 219.6 crore rupees. Thus, the quantified risk outweighs the benefit in all cases.   


 SGB as an investment instrument is becoming popular with public (it may touch Rs 20000 crores worth of subscription this year), and this paper attempts to understand the gold price risk that the government underwrites while issuing SGBs by quantifying the same by modeling it as a European type call written by the government. 

 For every 1000 crore rupees of SGBs issued, the Government is facing a risk which is quantified between Rs 402.5 crores to Rs 426.6 crores. It is partly offset by the gains that arise from cheaper money raised through SGBs. After this adjustment, the government is still underwriting around 180 - 207 crore Rupees worth of uncovered risk for every Rs 1000 crore raised. 

The main objective of SGBs is to act as an alternative to purchasing/holding of physical gold. 

It is for the policymakers to now examine if this level of risk underwriting is acceptable after examining the impact of SGBs on gold import over years and the gold purchase pattern of the public. 

Appendix A

Sovereign Gold Bonds of Government of India – a risk factored evaluation
Appendix B

Black-Scholes equation used to price the risky asset is shown below. 


Sovereign Gold Bonds of Government of India – a risk factored evaluation


Appendix C


SGBs are unique instruments, prices of which are linked to commodity price viz Gold. SGBs are also budgeted in lieu of market borrowing. The calendar of issuance is published indicating tranche description, date of subscription and date of issuance. The Bonds shall be denominated in units of one gram of gold and multiples thereof. Minimum investment in the Bonds shall be one gram with a maximum limit of subscription per fiscal year of 4 kg for individuals, 4 kg for Hindu Undivided Family (HUF) and 20 kg for trusts and similar entities notified by the Government from time to time, provided that (a) in case of joint holding, the above limits shall be applicable to the first applicant only; (b) annual ceiling will include bonds subscribed under different tranches during initial issuance by Government and those purchased from the secondary market; and (c) the ceiling on investment will not include the holdings as collateral by banks and other Financial Institutions. The Bonds shall be repayable on the expiration of eight years from the date of issue of the Bonds. Pre-mature redemption of the Bond is permitted after fifth year of the date of issue of the Bonds and such repayments shall be made on the next interest payment date. The bonds under SGB Scheme may be held by a person resident in India, being an individual, in his capacity as an individual, or on behalf of minor child, or jointly with any other individual. The bonds may also be held by a Trust, HUFs, Charitable Institution and University. Nominal Value of the bonds shall be fixed in Indian Rupees on the basis of simple average of closing price of gold of 999 purity published by the India Bullion and Jewelers Association Limited for the last three business days of the week preceding the subscription period. The issue price of the Gold Bonds will be ₹ 50 per gram less than the nominal value to those investors applying online and the payment against the application is made through digital mode. The Bonds shall bear interest at the rate of 2.50 percent (fixed rate) per annum on the nominal value. Interest shall be paid in half-yearly rests and the last interest shall be payable on maturity along with the principal. The redemption price shall be fixed in Indian Rupees and the redemption price shall be based on simple average of closing price of gold of 999 purity of previous 3 business days from the date of repayment, published by the India Bullion and Jewelers Association Limited. SGBs acquired by the banks through the process of invoking lien/hypothecation/pledge alone shall be counted towards Statutory Liquidity Ratio. The above subscription limits, interest rate discount etc. are as per the current scheme and are liable to change going forward. 

(Adopted from RBI’s website: https://rbi.org.in/Scripts/FAQView.aspx?Id=79, dt: Jan 4, 2022)


Jul 9, 2021

Dominant Currency Paradigm - An interesting progress in open economy macroeconomics after IS-LM-BoP

Does it matter if the exporters/importers of a country show preference for a certain currency while invoicing the trade? I had dabbled with this few years ago here, which was based on the Dominant Currency Paradigm presented by Gita Gopinath, Casas et.al. The expanded theory titled "Dominant Currency Paradigm" (DCP) was published at the AER in 2020 and the corresponding replication code with data is made available here

DCP is a significant development after Mundell-Fleming's model using IS/LM/BP curves which has been a workhorse model for decades. Mundell-Fleming (and the Devereux model) uses bilateral exchange rates to arrive at equilibrium rates, whereas DCP takes into account the additional factor that countries may use a third currency as invoicing currency while trading bilaterally. For example, traditional Mundell Fleming model for trade between India and Japan would use INR/Yen pair to understand disequilibrium whereas the actual invoicing of this trade may happen in  USD due to various factors. DCP corrects this by allowing usage of third currency, and goes on the prove that for the world that we are currently in, the USD is the dominant currency, with most third currency invoicing taking place in USD. India invoices around 86% of its imports in USD and around 10% in Euro as per the paper, the importance/pitfall of which would be clear in a moment. 

Let me summarize DCP's key takeaways: 

- The terms of trade for a country are uncorrelated with exchange rates in short and medium term: Mundell-Fleming predicts that, because prices are sticky in the producer's currency (Producer Currency Paradigm - PCP), a nominal exchange rate depreciation is associated with a depreciation of a country's terms of trade.  That is, currency depreciation would lead to increase in ratio of price of imports to price of exports. If INR/USD deprecates to Rs 100/USD, our import prices would shoot up leading to deteriorated terms of trade with the USA. A counter argument was given by Devereux et.al. that as the prices are sticky in destination country's currency (Local Currency Paradigm - LCP), a depreciation in exchange rate would lead to appreciation of country's terms of trade. With 100 Rs/USD, our exporters would now get more rupees for each dollar worth of goods exported and hence terms of trade would improve. 

DCP researchers find no such correlation. They find that the terms of trade are not correlated with bilateral exchange rates - neither PCP nor the LCP holds. This is counter-intuitive as it is usually believed that nominal appreciation/depreciation of currency would worsen/improve the terms of trade depending on whether the country imports more or exports more. Rather the terms of trade are defined in a way to align to this view and this mental model drives a lot of understanding about future direction of currency movement. If this is not true, a lot of other things that we know about forex markets appear to be standing on shaky grounds. The researchers have used non-commodities data, after excluding agri commodities (chapter 1 - 27) and certain engineering commodities (chapter 72-81) constituting almost 25% of total trade. Thus the research covers 75% of the international trade as per my estimates. (The paper says it covers 91% of trade, I am not sure how) 

- Dollar is the dominant currency and influences the international trade disproportionately: DCP takes a stand that neither PCP nor the LCP models hold true when it comes to international trade, but it is a small set of dominant currencies led by USD that determines the direction. The paper estimates that a 1% appreciation in USD against all other currencies leads to a 0.6% shrinking of global trade after controlling for business cycles.

The effect of dollar appreciation on exports outweighs bilateral currency appreciation (appreciation of recipient country's non-dollar currency).  If India is exporting to Japan, the effect of dollar appreciation would lead to greater fall in exports when compared with appreciation in Yen. This is the effect of invoicing Inso-Japan trade in dollars. 

- The price pass-through for non US economies  is directly in proportion to trade invoiced in USD, the dominant currency:  The trade mechanism for exchange rate adjustments work for all economies except the dominant currency economy, i.e. USA. This leads to two further findings. US economy is negligibly impacted by price changes in Dollar - which implies that the inflation targeting monetary policies run by other economies has insignificant impact on US. On the other hand, price changes in US arising out of monetary adjustment leads to impact on other economies through trade route (there may be other mechanisms of adjustments through capital flows which is not dealt directly). The exchange rate pass throughs are significant for all economies but US is immune to it. Any adjustment in US has to happen through other routes other than import price pass through. 

Where does that leave us? A revision is in order in the way people construct mental models about exchange rate effect on exports. A general thinking is that a depreciation in rupee is good for our exports as we become more competitive. The paper shows that it may be contrary and the trade may actually shrink when the dollar gets stronger. 

What next:

One concern I find in this paper is that there is no discussion about hedging of currencies at the time of invoicing. Usually, long term players cover their risk through currency positions they take while raising invoices in order to immunize against currency fluctuations in short and medium term. This is especially true for non-commodity trades. This, and the fraction of players who do this, may have a significant role in the way the pass through works. This needs investigation. 

Also, it is difficult to imagine that if a country mandates local currency pricing (imagine India issuing a fiat to quote all invoices in INR), it would somehow lead to lesser pass through. The exchange rates are an indirect indication of relative prices and to imagine that the way it is quoted leads to effect on trades is counter-intuitive. I will take time to get used to this new smell. To that extent Mundell-Fleming/Devereux made more intuitive sense. 

Jun 24, 2021

Fourth industrial revolution and India's demographic challenge

Klaus Schwas coined the term 'fourth industrial revolution' to describe the confluence of emerging technology breakthroughs, covering wide ranging fields such as artificial intelligence, robotics, telecommunication revolution such as 5G, the internet of things, driverless vehicles, 3D printing and additive manufacturing, nanotech, biotech, materials science, energy storage and quantum technology. On the surface, it appears to be the next logical step from the third industrial revolution where electronics and IT were leveraged for production and service delivery. However, as Schwas argues, the growth of these in future would lead to exponential impact on various spheres. The velocity, scope and impact of these changes may take directions that may not be wholly predictable, affecting all fields from agriculture, education, trade, warfare, manufacturing and everything in between. There is a good (and urgent!) reason why policymakers should be abreast of developments in more than a cursory way. It would not only preempt the adverse affect on the country, but it might also help to prepare policies to take advantage of the developments. 

The traditional economics still looks at manufacturing and trade from last century's perspective. This needs an urgent revision, especially when it comes to a developing economy context. The macroeconomists still dabble in general grand equilibrium models that went nowhere when financial crisis hit. The microeconomics still begin with economies of scale and theories of firm that could barely explain the growth of IT and services firms such as Amazons and Facebooks which operated without profits for long time. Theories based on Ricardo's comparative advantage are still being taught in graduate schools with wine and cloth being traded between England and Portugal. The sad truth is that trade practitioners still use indices such as Balassa's "Revealed Comparative Advantage" to arm themselves during negotiations, advised by advisors trained during last century. The theories are not to be blamed as they played vital role in understanding the factors that contribute to development. The models had their use. The blame must lie with people who have turned these theories into religion despite piling evidence that points to the staleness. 

There is an acknowledgement, lately, in the various circles about gaming of globalization by countries such as China and the backlash may be seen in terms of waning political appetite for further globalization. However, the firms in a capitalistic economy such as US would nevertheless push for optimization through supply chain relocation into countries where cost of production is cheap. However, the cost advantage gained through cheap labor price would erode through advancement in technology mentioned in fourth industrial revolution. The threat of automation displacing labor is being discussed at various places in the last five years. However, the exact mechanism is not well known and the suggested panacea of skilling the labor might at best produce mediocre results, or at worst might not work at all. This would have serious repercussions for young countries such as India unless we take remedial steps. 

Aug 22, 2020


(This post originally appeared at Swarajya magazine here

During the 1990s, computing faced a unique ‘memory wall problem’ due to increasing processor clock speeds but relatively slow memory speeds. While processor speeds increased at 50% year on year (Moore’s law) memory speeds increased only by 10%. Imagine a talented and quick chef bogged down by a slow assistant, who takes longer than usual to fetch ingredients from the pantry. The solution was found by using a ‘cache’, a smaller but faster memory placed nearer to the processor, thus avoiding multiple trips to the larger and slower main memory. This was like the chef getting a shelf that stocked all recently used or frequently used ingredients closer to his table. Today we have multiple caches at multiple levels in any given computer. Similar problem of earth-size arose when digital contents were to be served to multiple users across the globe. Imagine Netflix maintaining data centers only at US and trying to service the users across the world. The geographical distance that each data packet needs to travel would be huge and may clog the network affecting speed and user experience. The solution is again in a form of caching created by ‘Content Delivery Networks’whereby proxy servers and data centers are maintained nearer to the users, optimizing the content travel over the network. One of the largest firms in this field is Massachusetts headquartered Akamai which roughly covers a quarter of the web traffic today. Akamai is present wherever the users reside and maintains around 3 lakh servers in 136 countries and claims to have 85% of internet users within single network hop to an Akamai server. 


Going local as an optimization technique was a natural development in the above cases. This may also apply to the world of manufacturing. Supply chain management is known to use such optimization techniques while deciding on warehouse location. But when it came to manufacturing, scaling up at one location was usually considered an ideal way, especially in the recent decades. This is now changing, and China centered global production models is on the verge of being altered where production would take place in multiple geographies to cater to local markets. It will be the next logical step for production firms to survive in a de-globalizing world. Geopolitics, advancements in automated production techniques, declining appetite for globalization, rise in border barriers, and rogue behavior of China are the precipitating factors that would push this movement for change. We cannot term such optimization by production networks as ‘deglobalization’. A parallel term is ‘Akamaization’ – a solution where the firms go local in order to remain global.  Akamaization would arise in the beginning due to multinationals adjusting their international supply chains to the reversals in globalization by leveraging on Industry 4.0 advancements such as automated manufacturing, robotics and IoT. In the second stage, Akamaization would include growth of organizations that design their manufacturing processes to be agile and Akamaization friendly. 


The good years of globalization saw concentration of production in labor intensive countries. This was possible due to falling tariffs, technological developments, and logistics optimization such as containerization of cargo. The scale of concentrated production decreased costs and the decreased barriers to trade alongwith cheaper logistics ensured that geographical distances didn’t matter. The data suggests that this model peaked sometime around 2012-13, few years after the financial crisis.  Both in terms of merchandise trade as percentage of GDP as well as total merchandise trade as measured in current US Dollars terms has stagnated (or declined) after the recovery following financial crisis.  One may say that the world reached ‘peak trade’ during the first half of 2010s. The decades leading to peak trade were marked by growth and concentration of manufacturing in China and nearby countries including Taiwan, Korea and ASEAN. 

Akamaisation: Merchandise trade as percentage of GDP

 Fig: Merchandise trade as percentage of GDP - Source: World bank


Akamaisation: merchandise trade current USD

Fig: Merchandise trade in current USD - Source: World bank


There is no single explanation for peak trade. The most likely explanation is that the factors that drove the growth had run their course and there was not much that could be done further on. However, the decline starting thereafter and the expected decline in future would be of a different nature.  It’s easy to call it de-globalization, but for the adaptability of the firms that run the international value chains. 


In the last few years, after decades of embracing globalization, developed countries finally woke up to the unsavory side effects. ‘Hyper-globalization’ – a term used by Dani Rodrik – of the last three decades where capital as well as value chains cut across borders, is not proving to be a sustainable proposition in the long run as the free trade of hyper globalization type creates a losing side. The political setup of the losing side can’t explain away the job losses with consumer welfare or Ricardian theories. Free trade had peaked before the emergence of the protectionist political leaders who called it out. While the globalized model with zero barriers suit the multinationals, the politicians and policymakers increasingly realize the bad effects on domestic job growth and general prosperity. The backlash by the increasingly frustrated population is partially responsible for emergence of protectionist political leaders. Similar sentiments may also be seen in the prevailing mood of going local slogans such as ‘Make America Great’ and ‘Atmanirbhar Bharat’. While the free trade economists may rue the developments and sermonize about unlearnt lessons from history, it provides no solace to the multinationals who operate the international value chains and who need to explore alternative models to remain in business. Deglobalization by disengaging or shrinking their markets and business is not an option for the globalized firms. That’s where Akamaization steps in. 


Akamaization of a global firm involves higher level of integration and interdependence in terms of management, design, and product development while maintaining a network of production setups catering to limited geographies isolated by rising trade barriers. Imagine a global cell phone manufacturer rolling out new products every year but choosing to make similar models in different key geographies with significant market shares. Most components may be sourced locally to avoid border crossings. The manufacturing setup would cater to the domestic market, and export to those nearby markets where the market share is not significant enough to warrant setting up an independent manufacturing base. The optimization problem for an Akamaizing firm would involve variables such as direct and indirect cost of crossing borders, geographical distance, market size, investment and business costs etc. Akamaization may also happen due to geopolitical pressures. For example, Taiwan’s TSMC, the largest chipmaker in the world, has announced that it would be setting up manufacturing in US in response to Trump administration’s pressure to move critical technology back into US. 


For policymakers Akamaization starts with attracting ‘screw-driver’ technology where assembly operations would move in first, followed by indigenization of components. This can be engineered by carefully planned tariff and non-tariff barriers across the value chain starting with higher barriers for fully assembled products and moving down to smallest of the components in a graded manner.  A success story for India is the mobile phone manufacturing which got an upshot due to the border duty tweaks on mobile phones during 2016-17. Apple’s decision to set up assembly plants in India and further plans to increase local sourcing of components is an example of Akamaization. The growth of mobile phone exports from India may be seen below. 


Akamaisation: Export of mobile phone and parts from india

Fig: Export of mobile phones and parts from India in USD Billions - Source: UN COMTRADE


Now the Ministry of Electronics and IT is incentivizing production of electronics and mobile phone components in India through various capital investment and manufacturing linked support plans. This may further accelerate the trend shown above, not only for exports but also in terms of decreasing dependence on imports of electronics hardware. This support shall go hand in hand with border barriers for import of the components. It must also be noted that there would be limited scope for export led growth in an Akamaizing world in future, a factor that policymakers must consider while intervening. 


Akamaization would not remain restricted to fields such as automobile, electronics or technology products alone. Even in fields such as garments and footwear, there is a chance that the ever-changing fashion trends and the need to be nearer to the market may drive Akamaization. The high labor input in some of these fields may delay Akamaization, but beyond a threshold and with rising border costs, the cost benefit analysis shall tilt towards manufacturing near the markets, starting initially with the high-end segment. As the manufacturing technology improves with advances in technologies such as 3D printing and robotics, even the fields that were considered offshoring friendly would be relooked at. When Akamaization touches labor intensive fields, it may affect the employment potential of those fields. This would be a challenge for labor rich countries like India which should explore upskilling the future generation to cater to altered needs of the future industry. 

Akamaization also has the potential to divide world into groups based on mutual trust on intellectual property (IP) front. Like minded countries that are trusted with IP and show greater regulatory coherence would bond together. The experience of US and western firms with China has shown the importance of IP protection and preventing corporate espionage. This may build a new world order based on emerging alignments where trade and geopolitical interests converge, breaking away from the existing multilateral arrangements.  Firms would be more comfortable Akamaizing within the group. 


It is important to understand that Akamaization would happen under a certain set of conditions. These conditions include a significant market size and right policies for setting up manufacturing in the country. If the market size decreases, or if the border resistance rises to unsustainable levels where it no longer makes sense to transact anything across borders, firms may give up on the market over Akamaizing. The same goes for steps towards greater ease of doing business which facilitates easy Akamaization. It’s easy to miss the balance, and that would bring back the free trade economists who have been predicting doomsday since the time India tried to fix the distortions in trade arising out of poor policy choices in the past.