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Thursday, December 19, 2013

IGIDR FRG `Emerging Markets Finance' conference

The program is up. Don't worry about the computer security alert.

From clubs to States: The future of self-regulating organisations

by Ajay Shah, Arjun Rajagopal, Shubho Roy.

This post is based on talk at the 2013 National Convention of the Institute of Company Secretaries of India.

India's governance environment is undergoing rapid changes, and this will drastically re-shape the role of Company Secretaries. As a professional body, ICSI needs to understand and anticipate these changes, in order to ensure that its members are equipped to fulfill their critical role. While the ideas here pertain to ICSI, they also apply more generally to other self-regulating organisations.

The citizen-government interface is changing

The development of the government-citizen interface of a country can be divided into two phases. In the first phase, the interface is characterised by poorly written regulations, wide variation in practice and very bad infrastructure. Each government office uses its own unique processes and practices, and requires physical filings on forms that are difficult to fill. Different branches of government collect the same information in different ways, the same function and form are widely different in different states.

In such contexts, professionals invest time in learning to ``work'' the system, and create a valuable niche for themselves as indispensable intermediaries between citizens and the state. Twenty years ago filing a personal income tax return was challenging and often required professional help. This culture persists in many government offices: forms have `unique' requirements which only `experienced' persons know. This knowledge/experience comes from being a member of the professional organisation (the club) and the club prevents this knowledge from falling into the hands of non-members. As a result citizens and businesses are `forced' to approach the club members to comply with laws.

The second phase of development occurs when the State-Citizen interface improves. This is occurring in India through computerisation and standardisation of processes and forms on the one hand, and increased empowerment of citizens on the other. The internet is changing the interface in two ways:

  1. Many government services are moving on to the internet. While India has only 18% internet penetration, around 39% of railway tickets are sold online.
  2. Even with poor systems, the internet is helping citizens deal with poor state interface through HOWTO documents, computerised services, etc.

As a result, consumers of professional services begin to demand more of their service providers, and professionals are faced with an existential crisis.

The profession's response

Professional organisations have two choices:

  1. The knee-jerk reaction to defend their turf, fight to keep systems closed and inaccessible, try to increase the complexity of systems, and create and sustain non-transparent institutions.
  2. The enlightened response to focus on long-term survival by aligning itself with the interests of the consumer and industry they serve.

The knee jerk reaction causes frustration among customers and clients. This leaves the profession vulnerable to being side-lined by cost-driven innovations in the economy. An example of this is the rise of Legal Process Out-sourcing (LPO), which has allowed clients to access a broad range of legal services without hiring expensive lawyers. Worse, a profession can spiral into a vicious cycle of defensive and unethical behaviour, in which members to put the interests of the profession above those of their clients and customers, and in which standards of competence and conduct begin to suffer. In extreme cases, persistent self-interested or indisciplined conduct can invite a devastating response from the political establishment, as occurred when the Government took over management of the Medical Council of India in 2010.

By contrast, an enlightened response to a changing environment would try to preempt such crises and focus on the long-term survival of the profession. In the long-term, the profession will only survive if its interests are aligned with those of its clients, and if it provides a useful service to society at large. Strategically, it would make sense for the profession to focus on those roles in which it is truly irreplaceable, re-focussing its attention on its highest value services. And institutionally, the profession's governing body should move from being a ``club'' to being a ``state''.

The way forward

The state model recognises that modern professional organisations are like regulators, in that they incorporate the broad functions of the modern state: legislative, executive and judicial. As such, they ought to be designed with the same internal safeguards and processes as the modern state. These include, most critically, defining and separating out these functions. A good SRO will carry out its legislative functions by making codes of conduct and defining conditions of entry into the profession. It will carry out its executive functions by holding exams to restrict entry into the profession to qualified individuals, and by investigating complaints against its members. And it will carry out the judicial function of disciplining its members.

The record on performance of these functions in India is mixed. We have sometimes been successful in defining codes of conduct and entry conditions, sometimes not. In terms of executive functions, Indian SROs have paid extreme attention to maintaining entry barriers, often at the cost of efforts to investigate complaints against the profession. In terms of the judicial function, Indian SROs are highly averse to disciplining their members in public, fearing that this will be seen as a sign of failure of the SRO. It is possible to bolster each of these functions, and ensuring the long-term survival of the profession requires that this be done.

In order to exercise its legislative function effectively, a modern SRO must:

  • make detailed codes of conduct;
  • make these codes of conduct available to the public;
  • make these codes of conduct readable and comprehensible, through plain English guidance notes, FAQ pages, etc.;
  • provide information about how grievances can be addressed.

In order to exercise its executive functions effectively, a modern SRO must:

  • ensure that the entrance exams it runs are performing their function correctly. This requires analysis of test results and periodic review of the design and content of the tests, to ensure that they are relevant and of an appropriate level of difficulty;
  • engage in continuing professional education of its members, as opposed to voluntary and occasional seminars, and ensure that this continuing education reflects the rigour of the selection process for entry;
  • ensure that complaints against the profession are taken seriously, and investigated, and that the investigations are time-bound, and that the complainants are informed about the status of the investigation.

Too often in India, entrance tests are just a reflection of the person taking the exam and not the person who organised the exam. We do not bother to think whether the exam was fair. A recent data analysis of ICSE and ISC exams (high school exams) shows statistical evidence of poor exam design and manipulation of marks.

In a ``club'', standards of conduct are enforced by norms, not rules. Those norms are flexible, and defaulters are treated kindly. Clubs work well for small groups of professionals, who must rely on each other in an uncertain and unpredictable environment, which itself must be managed with a high degree of flexibility and discretion. A club is thus an appropriate model for a SRO in an early stage of its development. But as the environment changes, as processes become technologised and standardised, and customers become empowered, the club model will have to give way to a ``state'' model, which is less discretionary, less cosy, and less forgiving to defaulters.

Regarding the judicial function of a modern SRO, the organisation must:

  1. have an impartial and effective judiciary;
  2. have a fair system for addressing complaints;
  3. have a detailed procedure for adjudication;
  4. make rules allowing the complainant to participate;
  5. ensure that adjudication proceedings are time bound.

Achieving this requires three ingredients: The first is a law, which will clearly set the bounds within which the SRO will operate. This law should be ``anti-professional'' in that it must be designed to protect the interests of society rather than the interests of the profession. Punishments should not only be meted out but publicly shown to have been meted out. In 2012, the New York city Disciplinary Committee publicly disciplined 65 lawyers (See pg. 32) which include 13 disbarments. Many jurisdictions even go to individual practitioner level information about disciplinary actions. We rarely see any comparable level of disciplinary actions against professionals in India. The ones that do happen are usually after a big `scandal' like the Satyam failure and soon die out of public memory. No comparable data is publicly available for Indian professional organisations. They seem to hide the data about disciplinary actions and therefore should be presumed to have not carried out much.
India is going through an interesting time. The nature of the state is changing. RTI, Lokpal, E-governance, etc., are just examples of a move to a more perfect republic. SRO's have a choice, get in the way or join the change.

Wednesday, December 18, 2013

The future of the Insitute of Company Secretaries of India

On 7 November 2013, I did a talk at the 41st National Convention of Company Secretaries, about the future evolution of ICSI from a club towards a State organ:

You may like to look at other content on the video channel of the Macro/Finance Group at NIPFP.

Monday, December 16, 2013

Small samples from big populations shouldn't bother us

by Rajeeva Karandikar, Director, Chennai Mathematical Institute.

In the last few weeks, there has been a lot of discussion about opinion polls. Some people have questioned if these have a scientific basis. Indeed, each time we disclose our findings based on an opinion poll, someone raises this question.

In this article, I offer a simple explanation of the scientific basis of an opinion poll. The key result is this: If the methodology is sound, an opinion poll based on a sample size of 25 thousand respondents in our country, where there are over 500 million voters, can yield surprisingly good projections of the vote shares of major parties.

Consider a lottery. Suppose you are told that a box contains lottery tickets and that each ticket has a number written on it: 1 or 1000. You can pay Rs 100, and then put your hand inside the box and draw one ticket from the box. The prize would be the amount written on the ticket (in Rupees). Most people would not agree to play unless they are told how many tickets in the box have the number 1 or 1000 written on them. However, if they are told that 99 percent of the tickets have the number 1000 on them, many may be willing to play. Indeed, even if the cost of playing the game was Rs 900, many would opt to play if 99 per cent of the tickets have 1000 written on them.

Suppose, instead, you are told that host of the casino will put his hand in the box and draw a ticket. There are still 99 percent tickets with the number 1000 and only 1 percent with the number 1. And you have ascertained that all tickets are identical in all aspects other than the number written on it. Even then, you would be a bit apprehensive, as the host might have put the tickets with the number 1 at the bottom of the box, and given a chance the host can dig deep in and draw a ticket from the bottom. If you are allowed to shake the box and mix the tickets well, you would probably still play.

Now let us consider another scenario. A political party has two claimants for a Lok Sabha constituency, say Raghu and Prasad. Suppose the constituency has 5 lakh voters. Let us imagine that we have lottery tickets with the following characteristics: Each ticket has the names of 2501 voters from the constituency and also that the ticket is coloured Red if 1251 or more voters on that list prefer Raghu over Prasad and the ticket is coloured Blue if 1251 or more voters on that list prefer Prasad over Raghu. Suppose all such lists are written out on otherwise identical lottery tickets.

Let us assume that there is at least a 5 percent gap in the support level of the two candidates. It can then be shown that over 99 percent of the tickets will have the name of the candidate with more support. This is just a question of counting and is purely arithmetical- no element of probability or statistics enters here. Thus it is a matter of fact and not of belief! Indeed, 99.3939507 percent of the tickets will have the colour of the candidate with more support.

Return to our example of two candidates with a gap of 5 percent or more. If the party draws a ticket out of the box after mixing it well, it will end up knowing which candidate is more popular. Here the logic is that since 99 percent of the tickets have the colour of the more popular candidate, we can assume that the colour of the ticket drawn has the winner's colour. Once again the decision maker should ensure that the tickets have been mixed well.

Here are the percentage of tickets that will have the colour of the winner for different combinations of population sizes and sample sizes. In each case, we assume that there is a 5 percent gap in the vote shares of the two candidates.

Sample size Population size (Total number of voters)
500000 1000000 2500000 5000000 10000000 25000000
1001 94.35 94.34 94.34 94.33 94.33 94.33
1201 95.87 95.87 95.86 95.86 95.86 95.86
1401 96.96 96.96 96.95 96.95 96.95 96.95
1601 97.75 97.75 97.74 97.74 97.74 97.74
2001 98.75 98.75 98.74 98.74 98.74 98.74
2501 99.39 99.39 99.39 99.38 99.38 99.38
3201 99.77 99.77 99.77 99.77 99.77 99.77

The remarkable thing about this is that while accuracy increases as sample size increases, the population size (total number of voters) has only a negligible influence on the accuracy. This is somewhat counter intuitive but true. A sample of size 2501 will give the same accuracy when the population size is 1 million or 25 million!

The following table gives the percentage of lists which have the colour of the winner when the gap between the winner and loser is only 2 percent. Here again we see that sample size determines the accuracy and population size has very little effect on it.

Sample size Population size (Total number of voters)
500000 1000000 2500000 5000000 10000000 25000000
1601 78.86 78.85 78.84 78.83 78.83 78.83
2501 84.2 84.17 84.16 84.15 84.15 84.15
3601 88.58 88.54 88.52 88.51 88.5 88.5
5001 92.24 92.19 92.16 92.15 92.15 92.14
8001 96.44 96.38 96.34 96.33 96.33 96.32
10001 97.83 97.78 97.75 97.74 97.73 97.73
15001 99.36 99.32 99.3 99.29 99.29 99.29

At the bottom of this article is a computer program written in Python which does these computations. You have to believe me or have a mathematical expert confirm the accuracy of the program and then run the same on a computer with Python installed (which is available freely at You can change the population size, the sample size and the gap between the support levels to get the accuracy level of the corresponding sampling scheme.

The same situation applies when we conduct an opinion poll. We select a group of 2501 voters, and ascertain the opinion of this group, called a sample. It is the percentage of votes for a party in this chosen sample that we report as the estimated vote share of the party. The crucial thing is that our choice should be as if we have written all possible lists on lottery tickets and put them in a box, mixed them well and then drew one and the names on the ticket constitute the group. This is what is called random sampling. One can use random number generators to generate such a random sample from any list of voters.

Colloquially, most people think that random means arbitrary. This is far from true in the scientific setting. Random sampling refers to the methodology of choosing a sample. In this context, it means choosing one list out of all possible lists as if we are drawing a lottery ticket (in the scenario described above). What I have described is the simplest sampling scheme. There are variations which may be more appropriate in a given situation.

Suppose we have access to a list of all telephone numbers in use in a constituency. We can use a computer program to generate a list of 2501 randomly generated phone numbers from this list. We can then call these numbers and ascertain the view of the owner. In this case we could estimate the opinion of the group of people who have phones. In this case, richer, urban, educated class will be over represented and our estimate could be biased. This methodology is used in the US and seems to work well (at least over the last 50 years, while it did not work in the '30s and '40s even in the USA when the telephones were not ubiquitous all across the country).

Thus the most important ingredient in the opinion poll is the methodology of sample selection. One must be sure of getting opinions from a representative sample. Unless the sampling is done properly, there is no statistical guarantee that the estimate would fall within 2.5 percent of the true vote share (with 99 percent probability for the sample size of 2501).

Readers can experiment with the program and obtain accuracy of random sample based prediction for a given sample size, population size and gap in the support for the winning candidate and the losing candidate. The program prints the total number of lists, number of lists where winner has majority and then the last line is the accuracy (in percent).

Python code:
g=5#Gap in percent support for winning candidate and the losing candidate
#population size
#sample size
def binomlist(N, R):
    '''Return [binom(N,0), ... , binom(N, R-1)]'''
    for k in range(1, R):
    return a

#Population size
print('Population Size :')

print('Gap in the level of support between the two candidates 
(in percent):')

#Total number of supporters of the winning candidate
print('Total number of supporters of the winning candidate :')

#Number of supporters of the losing candidate
print('Total number of supporters of the losing candidate :')

#Sample size
print('Sample Size :')

#Majority mark in the sample
print('Majority mark in the sample :')

print('Total number of lists :')

z=sum([ c[r-k]*d[k] for k in range(0,t+1)])
print('Total number of lists in which winning candidate has majority support:')

print('Percentage of lists in which winning candidate has majority support:')
Output: Population Size: 500000
Gap in the level of support between the two candidates (in percent): 5
Total number of supporters of the winning candidate: 262500
Total number of supporters of the losing candidate: 237500
Sample Size: 2501
Majority mark in the sample: 1251
Total number of lists: 62231690581446480003124486564603608079722664287780679850769754811742042826440472887015830702924480575139486249657512804993096017025966527240485971677012460101302514218686266609441052100836909464169270524814906289825323267820948737888768638306721657325213500920099906234174550459916676877801122648015241862393226740611391693419690393435279384448846498164611917690485938916309022444186853678716540339720996823920632761895486203438380430254590374925296252761868287613362669749365125454631374879693160142819869304875906654921349095055838442562414668977024766179959130011021610575662910956134247564521738477313446196261604802302543410146068132670342155475007095024743323867045795400143176727384029281976933600168079297510291849445093067071083684685003730058946519710247034945376030279821029701472923740192102205025797475452531004667596413727636670465215729867754283833374385303145387948051359404453403594361525378558410033629759275932498192096982291800849470571518287063229431447959133385792138084490304666939123657615189822099874121079295131987178206767084477208423116361539422938568526859676309130466065888802081248462657939570182699815625453901386358318350022709995625288828603793916108904428008609734299699221437566336835240257534085393479491186665079655190103428237800738888006964700812940498236110822184478021780415260136866672164326231310650895521248121755859107866938779565130334913321094933601029730436184082485079029558170569819165053571542795991727217330966100414527221364686964529920726163238492293892228326948001117293468138858023516939457994664567261850006311933756947304285561086248788200803564375093003772848775681842197209982100478555863846338584281906599009475583222084487980818308040033671587984993515974558684475022277901970099053541223542134155842504516032224804445183451317380149589970032212804575628082098277081463957839077920898869597586620515995970008514248167231810555336158368760540858584640697240880859068759980546301544945173321069553721350972811702465776038261514751366432380505653269990734628912787921196828014924849957148325947484479478464943528525829530723712207177801854498505379313242978072796608415660424672105172137755545024900415945428256536045336980540671661266557344947764836566529722714879021182976140139129856559145427658178495007317534394739394235188377026548923486253173751616379130541552155758837114472809783850427754469844587936072840642351778220558057232669828423498123063458914684776588125631122103174618980604765576707899260689467306579408356058711623351399260178055917659963408455273580719144814560484832919904878765961591225700327651593973860864438116094850680456864518725262740928051582341539254987525019787256071659676928373298021282046954594050755383326687971809253561980088484298073161856459452325694037739274837365216230582263924667803583485781780218253284218391730866178085262881994066033816393829013721311131748672183078728900933581558734405974104874756534969248232592313582502037142672654121741282578372979805465908127950187274075397490336844923270342615399463969649554126623283032616619860556580636328136753628805680852851407963270089714073626621120839871909711594994253666342272359471320655869954863460407565986906474615595552330627592635455243206575046823339900668550971352633374485688587126074795047908585598712155945668417607256395345722088439538463447076588501001219788542858153049781833657942552401464715635534332260515218505056897905685877043364499338188335401451485749380823361891367165284575198795795706325965459245970820182968416588569262205864560967474390631523041120889653260589129456152566220058515917669342363795423128034942492225269840456119934077650384674330202082758512409968193166923108572334911544560155774100118425500347543423269124631844558114435125175017555500011451376956685419999212743508413967187310121355328643814596714505035428570563667905329220023568761920372318672748066491538386362503932919067623642006192288629490332239924529275660392604135364518178709645251568947829790968485350757937039473403892835221019104946380501456170261792541779653905610112609257982069288434883821539348456638978706277490266096785801912450185230638539829701924352942262894855270142930259031972046282586563892827754397261394135669853192369909536949252496489905384890519693644219374285311950869838840999862576449738089616498010247917038541443671710835200209258303429618341172828857210172546352033108320714086475275833013658816172562851640153013201594935921805444858511862222986921611649620787025702764928938030416878469784542178572899283792381712549547989957375712162715834971052306908424777553250398897933660688114626175343338296459105052106907815907800493632106153130371390265741118879621773827599268210510657654647567961805679873227774988494734117015705540753609174031970835793477945867907801468391170032234998449398312805494784365015754905261103496492914475522013784154069747889118167745622648817823453096293834552709425038099410751211010184684088478062229567458545385381873514215152003667097109597790568765198065077427946525045384254967053032767662079442599022863825992255697642670195087368061303544182026383279381793756537585195072034501032282072218014776155536686226067590207105059978962856264152015857329823054618874575107943555769313879322107342773045700458905454789107511870461578164581868782223102778218653491871855192270951818997164294958334974045773678167469423485625177317370915848177336736332836777996361609707902987046694214863048890113554854413050567534204094725686390362155721963672141096706581649992815877681713676063878647949708426533918893860041211338666717678506988337856766016039452351562182705851879530723219770661660390683134598036166887734683508116125393617837521663026650845446856218974787651129036755981552785539813024142173328570948759613346757263838152602944234205086327543051588254089090386593113031841672362875582419951045117676214677983892982215768091890388410459618648394701970636811984634408588565396887808598116836276413546396278428362439496050403104026679130181272599410000361010047778136678130879383747883747846895444550308537252212467158365879188315673992959209980186727731070450877815644643251764435971587530519135727567687253468334262068241333011975327403420996864840461485541038137569067936744784955690032673877577363436808601455485916733141230626610962300477240992891148835574452260329156066010179688692107195572679448377022660187493117482552354887255967959473828708949465982835085658015438685159219153348125861982966902706795929866032389611325518509983815234810190419913364567450264118122918625091636534133701922567413915709199174234722642774022748876761798838932368596471473383761819955993306073194192511980655731511111418734812039174839069481997922657860771600177158258301963426575629546453731005562602020307021534742971566271133060854173312518512084425581890020765636041299469386187750782069745075999996018174251440607754688000000
Total number of lists in which winning candidate has majority support: 61854535859474557855990802105237752997003079226915266398295566709786571570865126944390968210637518423542079527102570022999166688984274296235885139162890371514814845152010622805158620168912468690693188245682966954787357816511116779763733163402700476933630959164843305433201850578845370091288748854061390074747439388865845974202161930262599395731727353191068011590081152770196877407971636426951731994085907267804768852937825049803838100473521131063052926267944191522907342658317551764904960334072386631507754440746171433527467144733182012255305326199455319159497759562823152663968262865777457103271700128546028508185840232611523695405934728964035118237960868014973326447922706116544354336034347614678384022162974527037904321191181398534575569848882630055799910749797172304564491772423199336789851612216070203204275524094233112452914612289125662370386046257715156289616617574543451300214501841247096787674912979683070061713605543496243219427259075034171350439369320584086710980928379366489759203262100385124489235015029050551301074751781445992781257981654435667272527606697678067098831709443929240127929128547394461174871163509626564598556318324969348111671167120110424508155676842784775760059444981204834187739812753861969928971222420761131855788632604940532247374491023157683617994324064023325600495426562474895522481817088290306507602098761586556424183165192703406960550038339797967819973579603029824346542759436150333392596915015063750963940450511380855736879240949203056727957820806654033532382652697944335187351538193502302752677438979716069371383839023319581409715533431261519318056963567358615092916567918646344809017192689254441873194607032799176580005518847744513314944645132471407540662504364341425558288361717082939160655446029064670317732228963561205409737330114951013218590804768437809071092058235440817461936484573823922609954200258697063724572845222547780365519185476138723059149923014644555837546472430304327776379190867288941326831870645002682813073558114144397020856651396098641428245880407763399111302626215417904725128805326719787159608089308759310539659291511216704403271866844555932756610742675279329626214802593821101127278170409131325586212124151710165142757100487590767687382044871782315436075121171542572626492638808471680968040729208050469140926077912584273576340641257014821813020214765524809778864954507078512918888714254859177939535150020680594439865146499021168025610541634139341501484522062829556587659324452928788309544618343094453013332661828069966660143355367154612846409938357974206448260728642168060123578255631198332463974385754771418670196985850132396338939942461308023817769221799318621949923468227274010642413121733050935121767411991316887764568127280843446615938837129446630717759517950376477713807259688797866576252414083146600686650880207899667891677604126827061960251420067738418355966327207257392917436336731865485642950327130932493289464011591491047704107981756427219291055264143312206202230577972263205514048071843127797269511291476129899775547198248411450106880937713920234740112362636474232781683958078134701589591040282984364866200009733100910271820163097453414872456237992771088179902024383111236689464059435281063899471133588050088649308537531041274287153585336369394790451199357846698579951685792888991089679835339060335104126017261132825267018640531309505427477537620870911733521553658152454976725660963872168787051805718895517444599140932756344873557326427855400701615942270826310406658514734551562588662900750800729828396653844953945482326221733257969297201087018127132328768798046176023879900010060373993216522794747523289640979321071773794218866605017475730371283611610761350911346861500008729919019301067072919496561285987332861930046572860663808696120651875913544097783371879746140834717719015688160225361094599128341000683910024247665018933294496488786624226050404864707017014357988489253639376601921455654391172067437596345359240709330773941058600329053762687941644065922633145644130469148317865760411103692624307884683174819618671442069152710707134162672027346237374834097350336170928453416600244355207200811054739419529397124154126071051792133199895128726950214690751373964902723667255890924491013232603657299792685025004023713057058893428464868779315295174749486468550601318702477239163614341044641062996932687024872027811548077618001234615864548746268130250171192778617488138004967564306698248535187717421076365106348806106821537346949643846700449330358599365475382470246918611292871944809121969111017864598545829051438437850288221899022100184712042404754086803996345120912030499710004313022194682886744221708406796242511777371707223033713474614368940615606518938162404539717599572710179404281043850851420088512734477536989718707445595772395424620311444817067973609967777834700409297277415549465074115328057064442133675519804938678457212846870080100109455964899729071965181905612555945488493560180366058606748476317280119865991331975082418726690147297736709796082622562532706341896303468093693062647926409712747591212083935703258289194014940709114745569037161608333832469544837654632228442721822702724003627170996788824619104568972975934911932378037473120556765765762195941632676171512945909129242448444638553636536609594131129282152539412714009585868892428320440895663351867733881652239580949142684683481353248562798873757287916757580468627389991155852813550448917969327892911097933990419196015960374273051473175438993206323137256403186109363448282668586166311354485384932931804144339988774403004402405896945245725422702431733690124017022924657227323047668961814477218714072568186313359079987411940130396681799715540521231268441953447718529859895803980262710401387658027606656500057205126849851478255459358279161783808824363571309794095088890379247630444890577923100756584545549108006677956146637604172798742819492521507826898758791892006636607596635419708170718743967976837221333720083327132366807991394197404515600528862762389248905808587268155994320338244998724029406492065210164089814201328490050287743177666822378851971606713160006189128166640525745262825626356517895066557744597519977449314900187385212625277914375251622206262429685098796590400768356218087685302088179153086859311291523273637686891639986221244405181640484253991269897217169690609115907769063954029261659568602193333309944736964180426430695238571165245318661728551017255810873045429123026855411671804358355994634963743745030745365862888759330245538534977291471181991934485986474528502644452587454925992820425856177106615897073589580463926178212465336178760260176190531289730768305813149258314589213372104868616854925650428977268668149331635952396377069894057586620585416152265929820699770161781555434581354014880088969190425658318935898315061156729251402541740877913593377241246796287235439071594744201325364245711979195094423501588318728952447886937824706628041515791435885246207092104530611200000

Percentage of lists in which winning candidate has majority support: 99.39395070510206.

Friday, December 13, 2013

Pre-election polls: Do they work, do they influence voters, and shouldthey be banned?

by Rajeeva Karandikar, Director, Chennai Mathematical Institute.

I have been a psephologist for about 16 years and have had a fair amount of success in predicting seats in an upcoming election. Here is a post-mortem of what I said and what happened in the current round of elections.

From 2005, I have been working with CNN-IBN and Centre for Studies in Developing Societies (CSDS). CNN-IBN engages CSDS for the survey. CSDS does a great job of running surveys `by the book'. I use vote share data from the survey to come out with seat projections, which CNN-IBN carries on air.

How did we fare in the recent state elections?

Seat count predictions on air (CNN-IBN)





Madhya Pradesh




















The outcome





Madhya Pradesh




















These results show the power and the limitations of opinion poll based projections. If one simply counts the number of cases out of 13 that the actual results are within the interval projected, the score is just 4. However, one should see these as having correctly predicted clear and decisive victories for the BJP in Rajasthan and Madhya Pradesh. For Chhatisgarh, we predicted correctly that the BJP will win, with a much smaller gap than Madhya Pradesh and Rajasthan. So I would count all the three as being good predictions, with Chhatisgarh being very good.

As for Delhi, we underestimated AAP support and marginally overestimated BJP but we had the ordering right: Congress in third position with the possibility of touching a single digit, and BJP as the single largest party.

Vote share estimates on air (CNN-IBN)





Madhya Pradesh




















The outcome





Madhya Pradesh




















Here, the survey has worked well, and the errors are generally within the statistically acceptable range. The conversion from votes to seats is a non trivial transformation - since one needs to estimate the distribution of votes across the state in addition to the overall percentage of votes in the state. This requires building an appropriate statistical model. I will explain my methodology for this stage in a future article.

One can see that in MP and Rajasthan, there was underestimation of BJP votes by a few percentage points. The error in vote to seat conversion went in the same direction, and as a result our prediction was much lower than the outcome for the seats obtained by BJP. In Chhattisgarh on the other hand, the survey estimated the gap between BJP and Congress as 4% while the actual gap turned out to be less than one percent. In this case, the error in vote to seat conversion and the error in the vote share estimate cancelled out, and we got a result that was bang on. Of the four, I was the least confident about Chhattisgarh (and I had said so on air) since the estimated gap in vote shares was small.

In my experience, the predictive power of any opinion poll that is done a while before voting is rather poor. For one, any such poll can only measure the mood of state or nation at the time of poll and cannot estimate the potential change that can happen close to the voting day. Some psephologists claim to estimate this change by conducting polls at regular intervals and then extrapolate to get an estimate of this change. However, this assumes there are linear time trends in vote share, which is unlikely.

The other problem is the selection process that determines who in the general population (that is sampled in a survey) shows up to vote. The propensity to vote is not uniform across socio-economic stratums of the society. One can try to factor these in but that can inflate the error.

Exit polls are designed to take care of both these issues. However, choosing respondents in a randomised manner as they exit the booth is rather difficult and our experience has shown that it does not produce a representative sample (as measured by the gap between the socio-economic profile of the sample and population). Hence, we prefer to do a post-election poll, where in the days following actual voting, we do a household survey with sound methodology. In the current round, various exit polls had got numbers close to the actual results for MP, Rajasthan and Chhattisgarh. But for Delhi there was wide variation. And in the past, there have been occasions when exit polls had given an incorrect picture while we got it right with our post-poll.

Going beyond forecasting, these polls are valuable in understanding what was happening on the ground. As an example, the CSDS poll in MP, Rajasthan and Chhattisgarh showed that the gap between BJP and Congress vote shares was higher in rural areas. This diverges from the common view that the BJP is an urban party. The CSDS website gives the breakup of voting intention by various socio-economic groups, and this is valuable knowledge.

Regulation of opinion polls

Do opinion polls influence voter behaviour? In each of the surveys done by CSDS, one standard question is: `Who did the respondent vote for in the last election'. This refers to the last Vidhan Sabha election, if this is a poll for the Vidhan Sabha and the last Lok Sabha election, if the current one is for the Lok Sabha. Almost invariably the recall for whoever won the last time is much higher than the actual votes, even when the winner from previous poll is set to lose the current election.

Thus in 2011, a much larger percentage of voters seem to recall having voted for the left front in 2006 though in 2011 they were voting for Trinamool Congress. I may add that our estimate of the Trinamool vote share and seats in 2011 was very accurate. The same was true in Tamilnadu where, while voting out the DMK, a much larger number of respondents seem to recall having voted for them.

We have observed this time and again across various states and consistently over the last 15 years. The only explanation that I could come up with is that there is a general tendency to go with the winner.

This raises the concern that a political party may run a media campaign claiming that it is ahead in the polls. This justifies regulation (though not a ban). I feel this regulation could be self regulation by the media, e.g. through the Press Council. The regulation should require that each published poll reveals, in public domain, the detailed methodology of sample selection, the sample size, the socio-economic profile of the sample, the dates when sampling was done, the names of the core team members who supervised the survey and the methodology used to convert vote estimates to seat conversion. All agencies that release such information should be open to an audit by an expert group formed by an autonomous body such as Press Council.

CSDS and I have been very open about our methods. The sampling methodology is on the CSDS website, the sample size is always given on air and the socio economic profile of the sample is also given on the CSDS website. I have written about the vote to seat conversion in an academic article: Predicting the 1998 Indian parliamentary election, Karandikar, R. L.; Payne, C.; Yadav, Y., Electoral Studies; 21, 1; 69-89, and have been talking about it in seminars.

Fortunately, over the years, the visibility of any one opinion poll has declined, with so many agencies doing polls and making contradictory predictions. In the recent Delhi elections, the range of seats projected for the Aam Admi Party was from 6 to 31 out of 70 seats! Hence, the salience of this debate has probably declined greatly.

I do believe that there is a feedback loop: if all surveys point in a certain direction, at least some voters tend to get influenced. But this is no reason for a ban. After all, newspapers and TV channels also talk about their assessment of the political situation and if they all seem to point in a certain direction, this too has an effect on the electorate. In addition, under the Indian legal system, while the government can easily do censorship on television, this is harder with newspapers and more generally on the Internet. Hence, even if a ban were desirable, it is not feasible.

Thursday, December 12, 2013

Gold smuggling explains the decline in the CAD?

The changing role of women in India

The three modernisations

The trajectory of a country is about three modernisations: social, political and economic. Social modernisation is about establishing freedom and rights of individuals. Political modernisation is about achieving democracy, where there is rule of law, where State power is dispersed and restricted, where elections generate contestability. Economic modernisation is about achieving a high growth modern market economy, about a government that gets away from expropriation and central planning to a government that is focused on solving market failures.

All three modernisations interact in complex ways and fuel each other. As an example, Milton Friedman's `Capitalism and Freedom' hypothesis is the idea that political modernisation fuels economic modernisation and vice versa. This is a well established idea in the discourse. I find it also interesting to think about the other two legs of the stool: the interlinkages between social modernisation and the other two kinds of modernisation.

The role of women

When we think of social modernisation and economic modernisation, the big thing that leaps out is the role of women. A society that does not respect women is under-utilising half its labour force. We would expect to see a causal impact of greater equality of women upon growth.

We in India are sometimes complacent about the role of women in India. India is famous for having women in leadership roles. In a dinner meeting by Larry Summers, I once said that India was world #1 on one measure of the role of women: the fraction of the top 100 financial firms that are headed by women. I once met Andre Beteille, and asked him: When compared with 1947, in what aspect have things in India worked out much different from what you expected. He said: The role of women in the elite. He said that for upper class women in India today, it's better than even Japan, which is otherwise a very advanced country. The daughters of the elite in India have no glass ceiling, which is better than what we see in most places.

On a population scale, however, things are vastly worse. Paramita Ghosh reports, in the Hindustan Times, on a crime victimisation survey of women with scary results. The India Today survey (link, link) shows us that 79.3% of men believe that marital rape is okay. We don't know how many men in India act out on this belief, but the report Why do some men use violence against women and how can we prevent it? by the United Nations, shows us scary facts from some Asian countries that have men who think similarly to what the Indian data is showing. The Supreme Court ruling of yesterday is a reminder of the distance that we have to go on achieving social modernisation.

Things are changing dramatically with the young

With human capital measures like literacy or graduating high school, a person tends to achieve them when young. If a person has not become literate or graduated high school by age 20, things are unlikely to change later on. Hence, the analysis of the cross section in the population is tantamount to looking at the history: what we see for (say) 50 year olds today is a description of what things were like, 30 years ago, for 20-year olds. Age-specific rates are like rings of a tree.

Literacy of the cohort aged 22.5
(Time-series reconstructed from age-specific rates visible in the cross section)

The graph above shows the literacy of the cohort entering the labour force, which I approximate as being the cohort at age 22.5. The blue vertical line stands for today. This is constructed using the cross-section visible in March 2013 from CMIE Consumer Pyramids, a quarterly panel dataset with 150,000 households covering 700,000 individuals. With children, high literacy rates are found early on, and this yields projections for literacy of the age 22.5 cohort in the future.

We see that overall literacy of the cohort entering the workforce has gone up from roughly 70% in 1990, when India began opening the economy, to roughly 90% today and will go up to 100% in the coming 15 years. In addition, there was a big gender gap, which has been significantly reduced and will fully go away.

Let's turn to high school graduation.

High school graduates in the cohort aged 22.5
(Time-series reconstructed from age-specific rates in the cross section)

It seems shocking to think that in 1990, roughly 7% of the cohort starting off into the labour force, at age 22.5, had passed 12th standard. This has gone up dramatically to 20%. Sharp growth is visible into the future when today's 15 year olds become age 22.5, and there is no gender gap with today's 15 year olds.

The third thing that I want to show from household survey data is the ownership of mobile phones.

Age-specific rates of mobile phone ownership

All of us have been hearing about miraculous growth of mobile phones in India for a while, and have become a bit inured to the story. While a lot has happened, however, a lot remains to be done. The black line shows that with males, roughly 75% of the young and 80% of the old have mobile phones. The work is progress lies in taking this up to 100% for everyone. What's striking is the women. The upper red line, for March 2013, shows that 40% of girls have mobile phones, and this decays to 20% at age 45. On a related note, Avjit Ghosh, writing in the Times of India, talks about a paper by Yvonne MacPherson and Sara Chamberlain which finds that only 9% of adult women in Bihar have ever sent an SMS. There is a high rate of change with mobile telephony, in even the short timespan between the latest data (March 2013) and the first data from CMIE (June 2010) which is the lower red line.


I feel that in the early decades after independence, we had a progressive elite, which was able to bring up daughters well and we made amazing strides at the top. But social modernisation took place only in the elite. For the bulk of the population, attitudes and indoctrination and levels of violence remained neanderthal.

M. N. Srinivas has emphasised the extent to which the rest of society aspires to catch up with the lifestyle and the values of the elite. In the early years, there was little catch up on the treatment of women: the elite and the proletariat coexisted like oil and water. Perhaps budget constraints came in the way of translating aspirations. Maybe poor households shortchanged daughters on nutrition and education and mobile phones and such like, thus encouraging subservience in daughters. In my opinion, the economic growth of the last 20 years is creating a new wave of households within which daughters are growing up differently. Daughters who have high school education and a mobile phone are going to engage with the world differently. As an example, they are less likely to accept sexual harassment and sexual assault. We may now be at the early stages of something very big.

Economic modernisation has created this phase of social modernisation. The rise of capable women who will not be pushed around will, in turn, fuel economic growth because we are then getting a superior labour force. There is an enormous distance to cover. In my opinion, it will be a story spread over two generations (50 years) starting from 2000, through which we will endup with something satisfactory on the role of women. Economic growth will create opportunities for women and for sensibly bringing up daughters, and the rise of capable women will fuel economic growth.

Wednesday, November 20, 2013

Bangalore safety is not the job of banks

A PTI story about the attack on a woman at an ATM in Bangalore says:
... Karnataka government today bluntly told banks to close down such kiosks unless they provide security. As the shocking episode continued to grab media attention in Bangalore and across India, with the CCTV footage of the gory act being beamed into homes and offices on TV and the net, Home Minister K J George held a high-level meeting to discuss measures to curb such incidents.

George said more than 600 of the total 2,580 ATMs in the city have no security guards.
"We want them to deploy security guards immediately or close down the things until suitable arrangements have been made... that's why the Police Commissioner (Raghavendra Auradkar) will take appropriate action," he told reporters.
This is an appalling cop-out.

It is convenient and comfortable for the police to not take responsibility for safety. It is convenient and comfortable for the police to impose restrictions on citizens to make their job convenient. But we should not organise society in a way that's convenient for the police. The job of the police is difficult, and we should hold them accountable for delivering on it.

Look at any civilised country. Do banks put a guard on every ATM? Or does the government produce an umbrella of safety over society as a whole? The criminal justice system produces a public good called safety. Safety is non-rival and non-excludable. It is a public good. Mr. George and Mr. Auradkar are wrong when they want to transfer this responsibility down to citizens, asking them to produce safety as a private good.

In economic policy, when a central banker says the central bank cannot control inflation, I say that the person should resign. If you can't deliver low and stable inflation, please leave the central bank, and let someone else try to do your job better. In similar fashion, when a policeman says that the police cannot deliver safety, I would suggest that the policeman should resign. If you can't deliver safety, don't be in the police.

Thursday, November 14, 2013

India macro policy review

On 19 November, we have a day-long meeting, India Macro Policy Review at NIPFP. All are welcome.

Seminar on Collateral and monetary policy

Manmohan Singh of the IMF will do a talk at NIPFP on 18 November titled Collateral and monetary policy. We start at 4 PM. It will be followed by coffee and snacks. All are welcome.

The spirit of the NPS

In continuation of my blog post Implications of the Pensions Act (4 September), and the collection of links NPS: The day after (16 September), I have an article in the Economic Times today titled The spirit of the NPS. This is about rebooting the NPS with a focus on its founding principles.

Sunday, November 10, 2013

Interesting readings

A most interesting speech by P. Chidambaram: text, and a web page with an audio recording of the speech and the discussion.

The price of a tiger, an editorial in the Business Standard.

Adil Rustomjee on Firstpost on the elaborate racket that is Indian banking.

Clarifying RBI's role and purpose by Ila Patnaik in the Indian Express.

Remove restrictions on foreign investment in rupee denominated debt by Ila Patnaik in the Financial Express.

RBI gears up to try to do interest rate futures again by Ila Patnaik in the Financial Express.

Forcing managers of firms to gift away 2% of the money belonging to their shareholders is a bad idea. It is depressing, how comfortable the Indian State is in using its coercive powers to interfere in the right to property and right to contract of private citizens. In the Business Standard today, Shekhar Shah wonders how we can salvage some sense out of this.

Ullekh NP in the Economic Times tells a story of an extremely important new project: the Delhi-Bombay Industrial Corridor.

Response to SEBI's Discussion Paper: Review of policy for trade cancellation/annulment by Nidhi Aggarwal and Chirag Anand of IGIDR FRG.

Impact of restrictions on currency derivatives on market quality by Rajat Tayal of IGIDR FRG.

New research by Biggerstaff, Cicero, Puckett on unethical CEOs.

People who are steeped in Europe of the 20th Century know that social and political catastrophes are always possible. Accominotti and Eichengreen look back at the end of the First Globalisation, and find that the sudden stop that hit Austria, Germany and Hungary (1925-1932) was similar to what hit Greece, Italy, Portugal, Spain and Ireland (2006-2012).

Jon Krakauer in the New Yorker resolves a mystery involving the outdoors, rooted in plant biology and linking back to World War II.

A video with a discussion with Frank Dikotter on the early days of the Chinese revolution, which helps us better understand the notion of `land reform'.

A great story by Colin Dickey in the most excellent Lapham's Quarterly, about the early explorations of the seas and of the Arctic Circle, and the conquest of scurvy.

Why Microsoft Word must Die: a nice explanation of why people who know about computers have a problem with Microsoft Word, by Charlie Stross.

The Nazi Anatomists by Emily Bazelon on Slate.

Sunday, November 03, 2013

Macroeconomic and financial policy challenges of China and India: A special issue of the Journal of International Money and Finance

Joshua Aizenman, Kees Koedijk and I co-edited a special issue of the Journal of International Money and Finance, December 2013, which has:

  1. Overview: Macroeconomic and financial policy challenges of China and India; Joshua Aizenman, Ajay Shah.
  2. Is China or India more financially open; Guonan Ma, Robert N. McCauley.
  3. Why do emerging markets liberalize capital outflow controls? Fiscal versus net capital flow concerns; Joshua Aizenman, Gurnain Kaur Pasricha. Summary.
  4. The investment technology of foreign and domestic institutional investors in an emerging market; Ila Patnaik, Ajay Shah. Materials.
  5. How do foreign investors impact domestic economic activity? Evidence from India and China; Chotibhak Jotikasthira, Christian Lundblad, Tarun Ramadorai.
  6. The financing and growth of firms in China and India: Evidence from capital markets; Tatiana Didier, Sergio L. Schmukler. Summary.
  7. The financial crisis and Indian banks: Survival of the fittest? Barry Eichengreen, Poonam Gupta.
  8. Macro-prudential policies to mitigate financial system vulnerabilities; Stijn Claessens, Swati R. Ghosh, Roxana Mihet.
  9. China's financial linkages with Asia and the global financial crisis; Reuven Glick, Michael Hutchison.
  10. The growth of a shadow banking system in emerging markets: Evidence from India; Viral V. Acharya, Hemal Khandwala, T. Sabri Oncu.
  11. Impact of exchange rate movements on exports: An analysis of Indian non-financial sector firms; Yin-Wong Cheung, Rajeswari Sengupta. Summary.

Thursday, October 24, 2013

The investment technology of foreign and domestic institutional investors

Ila Patnaik and I have a recent paper in the Journal of International Money and Finance on the investment technology of foreign and domestic institutional investors.

The question

Do the firms chosen by FIIs do well? What is the stock market performance, and the operating performance, in the period after a firm has been selected for investment by FIIs?

This is an important question for many reasons. Investors (both foreign and domestic) would like to know the information content of seeing an FII or DII present in the shareholding of a firm. If, hypothetically, domestic financial regulation hampers DIIs, there may be a special role for FIIs in rationally allocating capital and alleviating financing constraints. If FIIs fare poorly in security selection, as has often been the case in the international finance literature, these mistakes have consequences for the allocation of capital and the incentives of entrepreneurs. Perhaps what India requires is policies that foster deep engagement with international capital, through which FIIs would achieve better information and thus fare better in security selection.

The opportunity for measurement

There is strong evidence of home bias: foreigners own too little of most Indian firms with an ownership of 0 for most firms. Less than a thousand companies have over 1% investment by FIIs. This is true for DIIs also. This opens up the opportunity to see how the chosen companies fare against those that were not chosen. To construct a quasi-experiment, we identify three groups of firms: 
  1. Those chosen by FIIs but not DIIs
  2. Those chosen by DIIs but not FIIs
  3. Those chosen by neither.
On the 31st of each year, it is possible to make these three lists of firms. An examination of future performance would give us insights into the investment technology of FIIs and DIIs. Specifically, if the firms chosen by FIIs but not DIIs (i.e. Group 1) do much better than those in Group 3, then we would think that FIIs have a valuable investment technology.

Pitfalls in measurement

Institutional investors are different. Institutional investors are different from individual investors. Hence, a fair comparison is between FIIs and DIIs.

Treatment effects or selection effects or both. Why might a firm fare well after FII investment? There can be two channels. There can be a `selection effect' where FIIs identify better firms. There can be a `treatment effect' where FIIs exert governance, and push firms to behave better. Investment technology is about the overall effect, i.e. the reduced form outcome. The economists' perennial quest for separating out selection effects from treatment effects is inappropriate here.

Asset allocation versus security selection. It is well known that the firms chosen by foreign investors are different in many dimensions such as beta, size, liquidity, etc. This hampers comparison. As an example, when Nifty fares well, high beta firms tend to do well. In such times, the portfolio held by foreign investors will look good as they have loaded up on high beta firms.

In order to address this, we utilise the three Fama-French empirical asset pricing factors: size, B/P and beta. For each firm chosen by the FII (but not DII), we find the partner firm (that was chosen by neither FII nor DII) where the Mahalanobis distance in size, B/P and beta is the lowest. If a good match cannot be found, the firm is dropped. This gives us a series of pairs of firms, which are alike in size B/P and beta, where one got FII (but not DII) investment and the partner got neither.

Holding a money manager accountable for security selection after controlling for asset allocation is an old idea in finance. However, the application of this idea into the question of investment technology of FIIs and DIIs is new, as is the matching-based quasi-experimental strategy through which we control for the asset allocation.


We find that the firms chosen by FIIs have exuberant growth in fixed assets in the following 3 years. But their output growth is not commensurately strong; there is some evidence of a decline in productivity. In terms of stock market performance, these firms under-perform over the three years after observation date.

Firms chosen by DIIs are strikingly different. They seem to be firms that are retrenching: both capital and labour drop slightly. But output grows. There is productivity growth. In terms of stock market performance, these firms outperform by 18 percentage points over three years.

These results suggest that foreign investors have a weak investment technology. Their access to information, and their ability to process information, adds up to poor security selection. In contrast, DIIs -- who are present in India and are likely to have ample information about portfolio companies -- fare better.


Implications for persons analysing Indian securities. A firm which has FII investment but not DII investment is probably going to grow assets but not give strong results. Conversely, a firm which has DII but not FII investment is likely to have slow growth but improve productivity and deliver stock market returns.

Implications for foreign investors. The results of this paper are about the average foreign investor, and there are surely many foreign investors who fare very well on security selection. However, on average, foreign investors need to be more cautious about their activities in India. They need to either amplify their efforts in security selection, so as to achieve strong information and information processing on Indian firms, or not attempt security selection.

How can a foreign investor improve security selection? Two paths are visible: To establish operations in India, and hold the team accountable for security selection using the methods of this paper, or contract-out to money managers who have deep roots in India.

How can a foreign investor harness asset allocation to India without attempting security selection? It is possible to setup index funds for the three Fama-French factors and thus replicate the bulk of the desired portfolio characteristics.

Implications for policy makers. Many of the pathologies of international finance are rooted in asymmetric information and the lack of deep engagement of foreign investors. These results are a reminder that even a large emerging market like India suffers from these problems. It is in India's interest to have a deep engagement with foreign capital, so as to obtain higher allocative efficiency. This suggests a re-examination at the constraints placed against deep engagement by foreign capital:
  1. It is difficult for foreign investors to contract-out money management to locals.
  2. `Permanent establishment' rules by the tax authorities have encouraged foreign investors to not open offices in India. This hampers deep engagement. Offices in Singapore or London will not be able to match the information and information processing that can be done in India.
  3. Source-based taxation, capital controls, and taxation of transactions, give incentives for foreign investors to avoid transacting in India. It is cheaper for a foreign investor to invest through the PN and NDF markets. However, not being in India hampers deep engagement.

How might this change over time?

In my opinion, in the 2000s, a certain kind of Indian entrepreneur started producing companies that look good to foreign investors. But you can't fool all the investors all the time. I think many investors are now more circumspect. Wall Street is changing course, and this is changing incentives for entrepreneurs. When finance rewards honest businessmen, more honest businessmen will show up asking for capital from the financial system. Many years from now, we might say that the results of this paper described a moment in time in the evolution of Indian capitalism.

Thursday, October 10, 2013

The cleansing of downturns

There is universal gloom in India today about economic conditions. This perspective is flawed in two ways.

First, every market economy experiences business cycle fluctuations. Trend growth is roughly 7%. When we get 10% growth in an expansion, we should not conclude that trend growth has gone up to 10%, and when we get 4% growth in a downturn, we should not conclude that trend growth has gone down to 4%.

Second, downturns are an essential part of capitalism. I have an article in the Economic Times today titled The cleansing of downturns. I feel these effects are more important in India when compared with mature market economies, where ethical standards are superior and where the policy process is less vulnerable. If the economy was permanently kept in good times through artificial means, we would damage the foundations and reduce trend growth. 

Wednesday, October 02, 2013

Who's afraid of a big current account deficit?

A big CAD is a bad thing -- much like a big fiscal deficit.

A country is always better off with a small or zero CAD or ideally a surplus.

The CAD is a drag on growth.

The large CAD is a profound drag on India's outlook.

If we managed to reduce the CAD, things would get better.

Statements like this are rife. They are wrong.

What is the CAD?

The CAD is three things, all of which are identical. It is the gap between revenues from selling goods and services versus the payments made for buying goods and services. This has to be exactly matched by the capital inflow into the country. This is exactly equal to the gap between investment and savings. These three relationships are accounting identities.

What if there was no capital account?

If there was no capital account, then the proceeds from selling goods and services would have to exactly match the payments for goods and services, in every minute. Every small mismatch between the two would generate extreme currency fluctuations (large enough to incite a current account response).

The capital account is what smooths these things out. Let us imagine the currency market for one minute in which someone is buying \$1 billion in order to import something. In that very same minute, it is very unlikely that there will be a double coincidence of wants, in the form of an exporter who wishes to sell \$1 billion. What fills the breach is the capital account. Some speculator comes in and supplies that \$1 billion in the hope of scoring a short-term speculative profit. The real economy demands liquidity in the currency market and finance supplies this, through the capital account.
The CAD is exactly equal to the gap between savings and investment. A CAD of zero is tantamount to only investing what we have saved. In general, this is a bad idea. If the country is all set to invest 35% of GDP, and savings are only 30% of GDP, it is a good thing if capital flows of 5% of GDP show up, through which investment exceeds savings.

Should we bemoan the large Indian CAD?

Should you be unhappy that investment is bigger than domestic savings by 5 per cent of GDP? If we insisted that the CAD should be 0 (i.e. we had no capital account) then investment would have to be lower and savings would be higher (which in turn implies reduced consumption). This would give reduced GDP growth.

Financial autarky implies that we live within our means. With savings of 30% of GDP, investment is forced to 30% of GDP under autarky. Opening up to the world makes it possible for a country to import or export capital.

If a country has good prospects but low savings, running a CAD is a way to front-load the investment, and service the foreign capital through a stream of dividends, interest payments and debt repayments into the future. If a country has poor prospects, it is better off sending capital to good uses overseas, instead of investing it domestically. For these gains, we have to have an open capital account and run large and variable CADs.

(There are also gains from risk sharing from large gross capital flows, even if the CAD is 0, but that's a separate topic of discussion).

A big CAD got us into trouble in 1991. Won't that happen again?

In 1991, FERA (1973) was in force. Capital account transactions by private parties had been criminalised. The only mechanism that generated flows on the capital account was the government. The entire CAD had to be financed by government borrowing. When the government lost creditworthiness in the eyes of the world, we had a funding crisis on the capital account.

On a day to day basis, imports required dollars which came from the government. The Ministry of Finance monitored daily inflows and outflows of dollars, and controlled who could access foreign exchange.

When GOI lost credit-worthiness in the eyes of overseas lenders, this was a collapse in the flow of dollars. If you wanted to import penicillin, you needed to get dollars, and RBI had none. That's where it came to crunch: when an importer is told that he cannot import as there are no dollars.

Nothing remotely like this can happen in the present environment. With capital account liberalisation, many channels have opened. There is FII investment in equity and debt, there is FDI, there is ECB, and so on. The money moving in these channels dwarfs the borrowing by the government. India is now well connected into financial globalisation. All these channels won't choke.

Suppose there is some big mess abroad and all fixed income funds stop buying Indian bonds. Under these circumstances, capital inflow will come through the other channels. The more we open up to a diverse array of investors into a diverse array of asset classes, the safer the environment becomes, the lower the exchange rate volatility becomes.

Why won't all channels choke all at once?

We require a capital inflow, on average, of Rs.20 billion per day. That's the gap, on the currency market, which has to be filled. If foreign capital does not come in, there is a supply-demand mismatch on the currency market. This gives a currency depreciation.

Ex-post, supply always equals demand. On the market, this demand will be met. Every day, the CAD of the day will equal the capital inflow of the day. The only question is: At what price?

When bad news comes out in India, foreign capital becomes more circumspect. They require a more attractive exchange rate at which to get in. Or, to say it differently, suppose INR/USD is at Rs.65 to the dollar. Suppose bad news come out. The inflow of Rs.20 billion is not forthcoming. The market has a gap. The rupee starts falling. At Rs.70 to the dollar, some foreign investors think `Hmm, maybe at this price, it's a good deal, and I should get in'.

How far does the depreciation go? Minute by minute, the rupee moves to elicit the net capital inflow (or outflow) required to clear the currency market. In response to bad news, the INR drops till a speculator feels that it might be a good idea to come into India, buy a 91 day treasury bill, and hope that the rupee will do well in a few minutes or few days. That's how the current account deficit always gets financed under a floating exchange rate.

Rupee depreciation makes Indian assets more attractive. It would be nice if foreign capital found Indian assets attractive for other reasons. But when all else fails, rupee depreciation is what gets the job done.

What kinds of foreign investors respond the most to rupee depreciation?

Sharp spikes of the rupee are fertile ground for currency speculators. The more currency speculators that we have, who are operating on the rupee market, the smaller is the INR movement associated with an event.

Imagine an INR depreciation of 5% in one day. A currency speculator believes this is over done and wishes to come in. What does he do? He sells dollars, buys INR, and invests in short-dated government bonds. This would add up to a pure play on INR. Currency speculators are not comfortable holding Nifty in India. They want a pure exposure to INR.

Hence, the best way to obtain a deep and liquid currency market, where shocks will lead to small exchange rate fluctuations, is to remove capital controls on the rupee denominated debt market.

A big CAD increases the damage caused by a sudden stop in capital inflows. What should the country do to forestall this?

Sudden stops are ultimately about asymmetric information in the hands of foreign investors. If India has a deep engagement with financial globalisation, then the informational asymmetry will be removed.

Our policy goal should be to have thousands of global financial firms who are running business activities connected with India, who have large scale organisational and human capital that is devoted to understanding India. This deep engagement will deter problems such as home bias, sudden stops, etc.

The Indian capital controls are damaging this deep engagement. As an example, repeated stop-go policies frustrate the development of teams inside global financial firms that have deep knowledge about India. When these teams know less about India, there is a greater likelihood of encountering the pathologies of international finance.

When India does silly things like trying to `crush the speculators' through various means fair and foul, this hinders a mature engagement with financial globalisation. When global capital feels that India operates on stable rules of the game and has mature policy makers, the resources committed for building organisational capital connected with India will be greater.

In order to avoid international finance pathologies such as sudden stops, our engagement with financial globalisation should be a deep engagement. While this issue becomes particularly salient when the CAD is large, but there is no short term solution. Over the years, we have to chip away at building a deep engagement with financial globalisation at all times, so as to reduce the risk when there is a large CAD.

This is like a rules versus discretion problem. When discretion is used at a time of a large CAD, it contaminates credibility at all times. A mature approach to public policy involves establishing capable institutions that implement stable rules of the game and not tactical dogfights.

What is the role of MOF or RBI in ensuring adequate capital comes into the country to match the CAD?

On a day to day basis -- nothing. It's a purely market process. The market does it. There are no gray men who look at the CAD and figure out how to finance it and then undertake actions through which it gets financed. The financing of the CAD is purely a market process.

The role for MOF and RBI is to get out of the way by removing capital controls, so as to reduce the magnitude of INR depreciation required when a certain negative event takes place.

Does this work differently for other countries?

A large CAD is dangerous when there is a managed exchange rate. Under a managed exchange rate, there is a propensity to borrow in foreign currency and leave it unhedged. These borrowers (whether corporations or governments) get into big trouble when there is a large exchange rate depreciation.
The central bank is much more likely to fail on exchange rate management when there is a large CAD.

The witches' brew that adds up to trouble is a central bank that believes there should be exchange rate policy + borrowers who believe the central bank will pursue exchange rate policy + a large CAD.
While India has a de facto floating exchange rate, RBI has not yet stopped talking about dreams of exchange rate management. We are relatively safe because borrowers don't believe RBI can do much about the exchange rate. Hence, there is no moral hazard and a large CAD poses no threat.

Why is a large CAD seen as a big problem?

With a large CAD, India is beholden to foreign capital inflows. If foreign investors are displeased, we get a big rupee depreciation. This generates accountability.

When India enacts capital controls, or the Food Security Bill, we get a rupee depreciation. This irritates policy makers, who feel that mirrors should reflect a little before throwing back images.
Nobody likes accountability. Hence, people in positions of power do not like a large CAD.

In a mature market economy, a key channel of accountability for the government is the bond market. When the government does bad things, their cost of financing goes up, and this directly hits the ability of politicians to spend on their pet projects. In India, the bond market has been muzzled by setting up a system of financial repression. The job of intimidating the authorities is then left to Nifty and the rupee. The voice of the latter is amplified when there is a large CAD.

If you look at the world from the viewpoint of the people who run the place, there is a desire to muzzle Nifty and the rupee (particularly when the latter is speaking loudly thanks to a large CAD). From that viewpoint, a large CAD is a bad thing. Because the establishment has a disproportionate impact upon the climate of ideas, we have started accepting their claim, that a large CAD is a bad thing.

If you care about India's future, a large CAD is a good thing, as it enhances accountability. By this logic, other things being equal, the Indian policy process generates superior outcomes when there is a large CAD. If we had a small CAD, Mr. Mukherjee might have been finance minister today.


Financial globalisation is work in progress. Capital controls and source-based taxation hinder international capital mobility. Even if there are no restrictions, it is hard for investors in country i to properly utilise the investment opportunities in country j, for reasons of `information distance'. All too often, there is home bias (people in a country holding vastly greater domestic assets than is optimal from the viewpoint of diversification). There are international finance pathologies such as capital surges, sudden stops, investments by foreigners in wrong assets, and so on. These are the hurdles along the road.

In the destination state, there is no good reason why the investment opportunities in country i at time t should match the savings of country i at time t. We should judge the success of the project of financial integration by the extent to which we are able to achieve large and variable current accounts.

In addition, in a place like India, a big CAD generates greater accountability on the part of the government. One would predict better economic policy when there is a large CAD.

The widespread mistrust of a large CAD may reflect two things. Some don't see the extent to which we're not in 1991 anymore: there is much more of a deep engagement with financial globalisation, and the exchange rate floats enough that the borrowers are not unhedged. And, establishment figures resent accountability.

I am grateful to Josh Felman for illuminating discussions on these issues.