Peddisudheer

by Diya Uday.

Land is an important form of capital. In India, for most households, it is the dominant element of the household portfolio. About eighty per cent of all household assets in India, are in the form of real estate (land, buildings and other constructions owned by households, for residential, commercial or vacation purposes) (Ramadorai Committee Report, 2017, pg. 12). In the CMIE 'Consumer Pyramids' household surveys, almost all households own some land or real estate.

As with other factors of production, an efficient economy requires full utilisation of the resources in the country, efficient mechanisms for discovering its price, and frictionless transactions. This is not taking place well in India. For example, unsecured debt still accounts for two-thirds of the total liabilities for the very poor and one-third of the rich in India (Ramadorai Committee Report, 2017, pg. 6). Similarly, despite landlessness in rural areas, only fourteen per cent of all households reported leasing-in land (NSSO Report, 2013, pg. 30). In many states such as Maharashtra, the proportion of households leasing-out land is well below ten per cent (NSSO Report, 2013, pg. 30).

In the study of land economics in India, a key question that has to be pursued is: Why, despite the sizeable presence of land as an asset in household balance sheets, is there poor capitalisation of land in India? What obstructs harnessing the full productive capacity of land in India?

The idea of land as dead capital was made prominent by Hernando de Soto, who used the term to refer to something that could not be easily bought, sold or used for an investment. He showed that the poor possess far more capital than is evident, but institutional failures hinder utilisation of the land as wealth. For example, he found that in Egypt a person who wants to acquire and legally register a lot on either state-owned desert land or former agricultural land has to navigate a plethora of bureaucratic procedures, estimated to take anywhere between five to fourteen years. As a consequence, a large number of people chose to build dwellings illegally (de Soto 2000, pg. 20). This means that these properties cannot be used to access formal credit or be legally sold or rented.

There is a need for a comparable literature on India. How does the land market work? What are the impediments to translating land into value added? How can wealth in the form of land impact upon the life of the owner to a greater extent than is presently the case?

In this article, three questions are studied, treating Maharashtra as the environment under examination:

1. Do regulations on land hinder the effective utilisation of land as an asset in India?
2. What are the restrictions imposed?
3. What are the less visible effects of these restrictions?

Three pathways to harnessing land wealth

The value of land is unlocked in three ways:

1. A mortgage, whereby land is used as a security to access credit.
2. A sale, where the owner of the land transfers it to a buyer.
3. A license or lease on the land in exchange for regular payments.

There has been a considerable focus on mortgage transfers as a means of capitalising the value of land. Land titles and access to credit are now intricately connected in policy discourse on financial inclusion and access to finance. For example, the RBI has recognised the role of land titles in access to credit and consequently to financial inclusion (Mohanty Committee Report, 2015, pg. 26). Some court interventions too, have given creditor rights precedence over transfer restrictions on land.

The other two methods -- sale and lease -- have received less attention, but are no less important. The owner of an asset must be given the freedom to choose the method by which the asset is to be capitalised. Directing policy attention only towards land as a means of accessing credit, and ignoring reforms in sale and rental markets, reduces the choices available for a land owner.

A case study of land laws in Maharashtra

We now turn to identifying provisions of law that affect the transferability of land in Maharashtra.

Methodology. A list of laws was obtained from the website of the Bombay High Court. This list was examined to identify the laws that potentially affect transfers of both agricultural and non-agricultural land and real estate, by reading the names of the laws. The long titles of these short-listed laws were examined to assess the applicability of the law for this case study. This yielded the following list of laws that impact upon land transfers:

1. Maharashtra Land Revenue Code, 1966
2. Maharashtra Tenancy and Agricultural Lands Act, 1948
3. Maharashtra (Prevention of Fragmentation and Consolidation of Holdings) Act, 1947
4. Maharashtra Stamp Act, 1958
5. Registration Act, 1908
6. Maharashtra Rent Control Act, 1999

The analysis of these laws yields the following results:

• Restrictions on the transfer of agricultural land: There are two kinds of restrictions on the transfer of agricultural land. The first kind of restriction is that under the Maharashtra Tenancy and Agricultural Lands Act, 1948, agricultural land can only be transferred to a resident agriculturist. An agriculturist is defined as a person who cultivates land personally. A non-agriculturist can only buy agricultural land after obtaining the permission of the Collector, unless the property is specifically allocated to residential, commercial or industrial uses or is to be used for a bona fide industrial purpose. In all other cases, the restrictions on transfers continue to exist. These restrictions apply to subsequent transfers as well. Similarly, mortgages to lenders other than co-operative societies, also require permission of the Collector. In each case, the Collector may grant permission subject to conditions.

  These restrictions induce three problems. First, they increase the cost of transacting on such land. Second, the law does not prescribe a time limit for granting such approvals. Neither are these permissions covered under the Maharashtra Right to Public Services Act, 2015. Without statutory timelines, the procedure for transfer could be time-consuming and tedious. Discretion in delay creates the possibility of corruption. Third, since these restrictions continue to apply even after the land the purchased, they also handicap future purchasers.

  A second class of restrictions kicks in after the sale is completed. Where the law has done away with the requirement for permission, the land must be put to the intended and permitted use within five years from the date of transfer. Failure to do so incurs a penalty of two per cent of the market value and even forfeiture. Further, when a purchaser of this land wants to sell it without utilising the land for a non-agricultural purpose, she can do so only with the permission of the Collector and after payment of a transfer fee of twenty five per cent of the market value of the property. If sold within ten years, these restrictions continue to apply to the transferee as well. There are further restrictions placed on certain classes of agricultural land, such as the payment of fifty per cent of the purchase price to the Collector. In case of a delay in the payment of price, this amount increases to seventy five per cent of the purchase price.

• Restrictions on the transfer of tribal land: The Maharashtra Land Revenue Code, 1966, places three types of restrictions on the transfer of tribal land. First, for sale of tribal land to a non-tribal, the permission of the Collector with the previous approval of the State Government has to be obtained. Before the grant of this approval, the Collector has to first offer the land to tribal persons residing in the village of the transferor or within five kilometres of the land. In scheduled areas, the additional sanction of the Gram Sabha has to be taken, unless it is for a 'vital government project' such as for highways, canals, etc. In all cases, the Collector is permitted to grant approval for transfer, with conditions. These restrictions would apply upon a lender, who might repossess land, also.

  The second type of restriction relates to the mortgage of such land. In case the mortgage is below five years, the permission of the Collector has to be taken for transfer. In the event that the mortgage is above five years, the permission of the Collector with the previous approval of the State Government has to be obtained. In case of a mortgage to a non-tribal, the same procedure of offering it first to a tribal person within the village or within a five kilometre distance from the land is undertaken. Further, the law permits the Collector to restore possession of the land to the tribal person at the end of the mortgage period, regardless of any court order or law. This means that if a tribal person defaults on a loan where land is taken as collateral, at the end of the term of loan, regardless of a court order to the contrary, the land can be restored to the mortgagee at the discretion of the Collector. These restrictions hamper lending against such land. In a field study conducted across twenty villages in Maharashtra, respondents were unanimous in stating that if they defaulted on a loan for which land was collateral, nothing would happen and that when land is used as collateral it was rarely enforceable if there was a default (Narayanan et. al, 2019). Court rulings on this subject have been conflicting, sending mixed signals to lenders (Zaveri, 2017). Poor transferability also hampers the establishment of a credit history and thus access to credit.

  The third type of restriction relates to lease of such land. The provisions requiring permission of the Collector and State Government and the requirement of offering the land to a tribal person within the village or within a five kilometre distance from the land, also apply to lease transactions. These provisions make leasing of such land to anyone but tribals, a lengthy and expensive procedure. Where there are no takers from among the tribal community, the owner of such land is effectively left with one less tool for capitalising the value of her asset.

• Restrictions on the transfer of notified fragments: A fragment of land is defined as a plot of land which measures less than the notified standard area. The Maharashtra (Prevention of Fragmentation and Consolidation of Holdings) Act, 1947 imposes two types of prohibitions and restrictions on such land. First, any land which is notified as a fragment, can only be sold to the owner of a contiguous parcel of land. In addition to limiting the owner's access to the land market, as in the case of tribal land, these sale restrictions also inhibit recoveries of lenders.

  Any land which is notified as a fragment can only be leased to the cultivator of a contiguous parcel of land. This provision is problematic in that it operates within an already restrictive lease market, where incentives to lease are few. Further in the event that the cultivator of a contagious parcel is not interested in leasing-in the land, the owner is either forced to cultivate the land herself or to let it lie fallow, effectively making it a dead asset.

The following laws do not place direct restrictions on sale, lease or mortgage transfers, but have provisions that affect these transactions (Category 2 provisions):

• Rental market restrictions: There are two main laws that govern rental markets in Maharashtra, one for agricultural land and one for constructed property. While these laws, unlike those in some other states, do not prohibit leasing of land, they do impose other restrictions. First, the Maharashtra Tenancy and Agricultural Lands Act, 1948, which applies to agricultural land, prescribes rent ceilings. The prescribed formula for determining the maximum amount of rent payable is that the rent must not exceed five times the assessment or twenty rupees per acre, whichever is lower. Similarly, the Maharashtra Rent Control Act, 1999 controls rents in specified properties by imposing a statutory maximum rent which is below the equilibrium rent (determined on the basis of the market value of the property). The law also limits the percentage of yearly escalation in rent chargeable to tenants.

  Rent ceilings reduce the rental revenues of owners. In addition to prescribing the value of the agreements, these laws also prescribe other terms such as the grounds of termination exhaustively. This means that the parties have little or no freedom to contract grounds of termination beyond those prescribed in the law. Further, the recovery of possession of the premises is a difficult process which will most likely require administrative or court intervention, which means additional costs to the owner. These features coupled with rent ceilings, leave no incentive to owners who wish to capitalise their asset by means of a lease. In fact, anecdotal data from land-owner farmers in Palghar and Mulshi Districts in Maharashtra suggests that the fear of non-recovery of leased out land is a key reason for not leasing out of land.

• Registration of transfers and stamp duties: The Registration Act, 1908 requires certain deeds used to effect transactions in immovable property, to be registered with the office of the registrar or sub-registrar. A document has to be registered by payment of a registration fee. In Mumbai, this amount is thirty thousand rupees. The biggest problem with this system is that while registering this deed, the registrar is not under any obligation to confirm the veracity of the contents of the deed or the marketability of title. The registration of fraudulent documents of transfer thus is possible. For example, in a recent episode, an examination of property documents revealed forged signatures and non-existent parties to the transaction. This system therefore adds to the cost of the transaction, without any real benefit to the parties. A purchaser, borrower or lessee is incurring the cost of registration without actually having the assurance of marketability of the land or identity of the parties.

  Stamp duty is incurred before the registration. Like other taxes upon transactions, stamp duty is a `bad tax' in public finance parlance. The Maharashtra Stamp Act, 1958 imposes a stamp duty of five per cent on the market value of the property in a sale transaction. Recently, a surcharge was introduced which has further increased the applicable stamp duty.

• Presumptive titles: The Maharashtra Land Revenue Code, 1966 requires the updation of land records each time a transfer takes place. For this, the transferee has to make an application for updation of the record. The concerned officer will invite objections. If there are no objections, the record is updated. If there are objections, the dispute will be adjudicated before updating the record. Despite this lengthy procedure, land records do not have any value in terms of proof of title. The Supreme Court recently reiterated that entries of transactions in revenue records, do not create title to land.

  Purchasers demand the issue of a certificate of marketability of title from the seller. This involves a process of legal due diligence or examination of title by legal experts. In most cases, the purchaser also conducts their own diligence in addition to demanding this certificate, adding further costs to the transaction.

• Form of land records: There are two types of textual records in the state of Maharashtra: the 7/12 extract for agricultural/rural land, and the Property Rights Card in urban areas. A study on urban records in Mumbai reveals that the fields of information required to be recorded under the rules of Maharashtra Land Revenue Code, 1966, only serve the purpose of collection of revenue (Sheikh et. al., 2018). These records are therefore fiscal cadastres and information contained in these records is limited. Vital information such as easementary rights, restrictive covenants on the land, litigation and encumbrances are not recorded.

  Insufficient information in land records increases the cost to and risk borne by the buyer. In case of a mortgage, the cost of lending is also likely to increase as it will take into account these risks, making borrowing more expensive for land owners.

Thus, we have a depiction of how the landscape of laws in Maharashtra interferes with the translation of land into value added. There are three limitations of this work. First, the list of laws is not exhaustive. There are other laws, regulations, government orders, which affect the transferability of the property, which do not find mention in this case study. For example, there are a number of transfer restrictions in urban areas, such as restrictions on change of land use and development under the Maharashtra Regional and Town Planning Act, 1966, the Development Control Regulations, the imposition of transfer fees payable by apartment owners to co-operative societies and transfer fees paid on Collector's land. Second, at present, there is no empirical evidence, that links these provisions to the impact on land economics. Third, this study is theoretical and does not analyse how these provisions will play out on-ground. Depending on the administrative processes, these provisions may have either a large or small impact in obstructing transactions.

Conclusion

The aim of this study was to examine the regulatory restrictions imposed on land transfers and their potential role in creating dead capital. This study documents two classes of restrictions: Category 1 provisions, which directly restrict transfers in the land market and Category 2 provisions, which affect the ease of doing transactions. Both these categories of provisions create a complex web of conditions for transfer, which may contribute to create dead capital in land markets, with varying effects. For example, a land owner may not be able to capitalise land by transfers on account of Category 1 provisions for two reasons. First she may be outright prohibited from undertaking a transaction, or second, the provision generates an unseen restriction of some kind, which operates to effectively disallow her from capitalising her asset. Category 2 provisions, again may affect the effective capitalisation of land by transfers in two ways. First, by creating disincentives to capitalisation in some manner; rent ceilings are a classic example of this. Second, these restrictions impose costs which reduce the benefits from capitalisation.

Furthermore, this study highlights the unseen consequences of economic policies and the regulations made to implement them. There is a need for policy makers to think about the secondary consequences of any regulation. Each instance listed above is a case of the proverbial coin with two sides, one of which has been overlooked. In the area of land markets in particular, it appears that policies have been unidirectional; predominantly discounting the impact of these policies on capitalisation of land. Recent amendments to the law too reflect this fallacy. For example, the 2016 amendment to the Maharashtra Land Revenue, 1966, introduced the requirement of additional permission Gram Sabha for transfers in scheduled areas. While the argument for this was that it would would lend more accountability to the transfer process, one must also recognise that this increases the complexity and cost of the transfer process which might reduce demand for such land, leading to a situation where even a willing owner, is left with no market for capitalisations.

The effects of these restrictions will be greater in states which have more restrictive regimes. In solving these problems, therefore, the first step is a comprehensive study, at the level of each state, which documents these restrictions. As an example, for Maharashtra, this would be a more complete version of this article. The impeding provisions must be categorised in the manner described by this case study. The reason for this is that different categories of restrictions will require different action points. The second step is to determine empirically if each category of these restrictions affect the capitalisation of land as an asset. Field studies are required which determine the on-ground effects of these provisions on aspects such as (i) the costs of lending, (ii) the cost to the owners of the land and (iii) the transaction frequency.

References

Narayanan et. al., 2019, Land as collateral in India, Sudha Narayanan and Judhajit Chakraborty, Indira Gandhi Institute of Development Research, February 2019.

Sheikh et. al., 2018, Rethinking urban land records: A case study of Mumbai, Gausia Sheikh and Diya Uday, The Leap Blog, November 1, 2018.

Zaveri, 2017, Distortions in the Indian land collateral market, Bhargavi Zaveri, The Leap Blog, February 1, 2017.

Ramadorai Committee Report, 2017, Report of the Household Finance Committee, Reserve Bank of India, July 2017.

Mohanty Committee Report, 2015, Report of the Committee on Medium-term Path on Financial Inclusion, Reserve Bank of India, December 2015.

NSSO Report, 2013, Household Ownership and Operational Holdings in India, National Sample Survey Office, December-January 2013.

de Soto, 2000, The Mystery of Capital: Why Capitalism Triumphs in the West and Fails Everywhere Else, Hernando de Soto, Basic Books, 2000.

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Diya Uday is a researcher at the Indira Gandhi Institute of Development Research, Mumbai and visiting faculty at the Tata Institute of Social Science, Mumbai. The author would like to thank the three anonymous referees for their comments and suggestions.

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by Renuka Sane.

Policy decisions on pensions should be shaped by an evaluation of the link between various parameters of the pension scheme and potential outcomes. For example, the setting of fees, investment guidelines, annuity policies, should be designed after a careful study of how these will affect the pension received. This is especially important in defined-contribution pension systems where there is considerable uncertainty about returns that may be obtained. Pension outcomes must, therefore, be understood through the lens of the risk-return trade-off.

This article presents penCalc, a new open source software system developed for conducting simulations on pension outcomes. It allows the key variables that may affect the pension to be changed, and presents the user with a range of possible pension amounts. This can help policy makers evaluate the impact of a policy change on pension outcomes. This can also be used by individuals for retirement planning.

penCalc

penCalc simulates pension scenarios based on assumptions on age of entry, exit, wage growth, contribution rate, portfolio allocation, asset returns, annuity prices, and inflation. It is developed using R, an open source programming language and software environment for statistical computing, supported by the R Foundation for Statistical Computing. The package may be installed as follows:

devtools::install_github("renukasane/penCalc")

Assumptions

The default assumptions made in penCalc are shown in Table 1. They have been chosen to be as close as possible to the National Pension System (NPS) in India. For example, the age at exit is the current retirement age. The returns assumptions are derived from a study of the Indian financial environment. The life-cycle allocation is sourced from the Deepak Parekh Committee Report set up by the PFRDA in 2009 on investment allocations. In a life-cycle portfolio allocation, the exposure to equity is very high at younger ages, and gradually reduces as one approaches retirement. The fees and expenses also reflect the current AUM charges in the NPS, as well as the flat fee charged by the Centralised Record-keeping Agency (even though this may not be exactly INR 100). The annuity price is taken from the current offerings of the Jeevan Akshay policy of the Life Insurance Corporation of India.

Table 1: Assumptions

Age
Age of entry	25
Age of exit	60
Wages and contributions
Starting wage	INR 25,000 per month.
Wage growth (nominal)	8% per annum
Contribution rate	20% of wage
Initial amount (already in the account)	0
Inflation (mean, sd)	(4%, 0)
Investment portfolio	Life-cycle
Returns (nominal)
GOI bonds (mean, sd)	(7%, 0)
Corporate bonds (mean, sd)	(10%, 0)
Equities (mean, sd)	(16%, 25%)
Fees
AUM	0.01%
Flat fee	INR 100 p.a.
Annuity parameters
Percent to be annuitised	40%
Price for an INR 1 a day nominal annuity	INR 4,087

These default numbers can be changed to reflect different views on NPS rules as well as the Indian macroeconomic environment. The tool can also be used for pension income simulation with assumptions that reflect the environment in different countries.

Using penCalc

The structure of the code is given below. The function consists of various parameters, and the default values set against the parameters. For example, age.entry is set to 25, while age.exit is set to 60. All of these parameters can be changed.

  x 

How the model works 
The starting wage and the yearly growth rate in wages are used to generate a vector of wages for the years the subscriber is expected to be in the system. The number of years is calculated as the difference between the age of entry and exit. In this particular instance, the number of years is 60-25+1, that is 36 years. 
The contribution rate is then used on this vector of wages to  arrive at the rupee value of contributions made each year in the  NPS. The wages are expected to stay the same in each month of the  year. For example, in this case, the contributions will be 20% of  the wage of INR 25,000 in the first year. 
The returns on each instrument are simulated from a normal  distribution with the mean and standard deviation of that particular instrument. The investment weights and returns are used to arrive at a portfolio return. The monthly fees and expenses are deducted from the portfolio returns. The contributions and returns are accumulated over each year in the system and give us the total accumulation in the pension account.
If the user has entered the "real=TRUE" option, then the rate of inflation is subtracted from all inputs. The results of the model in such a case will be in terms of today's rupee value, and not nominal values. The default inflation rate is 4%, but as discussed earlier, this can be easily changed. 
The simulation is done 1,000 times and generates a distribution of accumulated amounts in the NPS account. The amount to be annuitised (for example 40%) is subtracted from this accumulation. The annuity price is used to arrive at the monthly pension that can be purchased with this amount. The remainder (for example 60%) is available as a lump sum withdrawal. The model has the following outputs:
  
  In hand accumulation: This is the average amount of lump sum withdrawal available at retirement. In the case of 40% annuitisation, the in hand accumulation is the remainder 60% of the total accumulated balances. In the case of full annuitisation, this amount will be zero, as the entire accumulation is turned into an annuity.

   
 Monthly pension: This is the rupee value of the average monthly pension the retiree can expect to get after the purchase of the annuity.

   

 Replacement rate: This is the ratio of the pension to the last drawn wage. The replacement rate only makes sense for government employees. For those with varied contributions over their lifetime, it is not sensible to divide the pension with the last wage. The replacement rate should be ignored for subscribers other than regular salaried employees.


Example 1: Portfolio dominated by GOI bonds 
This example demonstrates the use of the calculator for an  investment allocation between government bonds and equity of 85%and 15% respectively. We have chosen the real=TRUE option. Hence all the results are in 2018 rupees.
Since the example is using all the default values and only  changing the investment weights (as the default weights are the life cycle model), we change that parameter in the model. We first create a weightmatrix where we specify the portfolio allocation into government debt and equity. We then supply the weightmatrix to inv.weights. The code is as follows:
library(penCalc)
weightmatrix 
Table 2 describes the results. The first three columns show the results for 40% annuitisation, while the next three show the results for 100% annuitisation. The results are in "real" terms. The numbers in the bracket represent the standard deviation - this reflects the uncertainty around the average lump sum and pension amounts.

    
      

Table 2: Portfolio dominated by GOI bonds 
      
 
  
 
 40%

      annuitisation 
 
 100% annuitisation


           
 

Average 
10th percentile 
 
90th percentile
 
 Average 
10th percentile 
 90th percentile

 
      
 
 Monthly Pension (in Rs.) 
	
23,297 (828)
	
22,196
	
24,361
	
 58,242 (2072)
	
55,491
	
60,902
      
       
      
 
 In hand accumulation (in Rs. million) 
	
4.7 (0.17)
	
4.4 
	
4.9 
	
 0.0  (0.0)
	
 0.0
	
 0.0
      

      
 
 Replacement rate 
	
23.6 (0.80)
	
22.5 
	
24.7
	
	
 59.0 (2.1)
      	
 56.2
	
 61.7
 

        
With 40% annuitisation, the average pension at the age of 60 is INR 23,297. This provides an average replacement rate of 24%and also provides a lump sum withdrawal of INR 4.7 million.  Pension at the 90th percentile of the distribution is INR 24,361, while at the 10th percentile is INR 22,196. The replacement rates are 25% and 22% respectively. 
With 100% annuitisation, the average monthly pension increases to INR 58,242 and the replacement rate to 59%. The 90th percentile of this distribution is INR 60,902, with a replacement rate of 62% while the 10th percentile is 55,491 with a replacement rate of 56%.
Example 2: Life-cycle portfolio investment 
The previous example is heavily skewed towards government  bonds. Given the huge equity premium in India, it is useful for the NPS to invest more heavily in equities. One way of increasing equity exposure is through a life-cycle portfolio allocation. The current example uses the default life-cycle portfolio weights indicated by the "lc" option. However, these weights can also be changed. The code is as follows: 
library(penCalc)
set.seed(111)
# 40% annuity
x 
Table 3 describes the results. The average pension at the age of 60 is INR 36,744 with 40% annuitisation. This provides a replacement rate of 37% and also leaves a lump sum amount of INR 7.4 million. The average here is higher than that obtained using a portfolio dominated by government bonds. However, the standard  deviation is also higher, suggesting that the risk is higher. This is not surprising because the exposure to equity is higher in the life-cycle investment portfolio.
  
    
      
Table 3: Life-cycle portfolio investment
      
 
  
 
 40% annuitisation 
        
 100% annuitsation


           
 

Average 
10th percentile 
 
90th percentile
 
 Average 
10th percentile 
 90th percentile


      
 
 Monthly Pension (in Rs.) 
	
36,744.3 (3702.4)
	
32,017.9
	
41,462.0
	
	
 91,860.8 (9256.1) 
        
 80,044.7
	
103,654.9 
 
	       
      
 
 In hand accumulation (in

	  Rs. million) 
	
7.41 (0.75)
	
6.45
	
8.35
	
 0.0
	
 0.0
	
 0.0
      

      
 
 Replacement rate 
	
37.2  (3.80)
	
32.4
	
42.0
	
 93.1 (9.4)
	
81.1
	
105.1
      

        
  
Pension at the 90th percentile of the distribution is INR 41,462, with a replacement rate of 42%, but at the 10th percentile is INR 32,018 with a replacement rates of 32%. Full annuitisation provides an average monthly pension of INR 92,000 and a replacement rate of 93%. At the 10th percentile, the replacement rate drops to 81%, but at the 90th percentile it jumps up to 105%.
Example 3: Varying contribution rates 
The assumption of a constant contribution rate is not realistic in the case of informal sector workers. The model handles this by using a vector of wages, and a contribution rate of 100% in the model. This effectively makes the values entered in the wage the actual contribution.  In the example described below, we simulate 36 values for wages from a normal distribution with a mean of INR 3,000 and a standard deviation of INR 100. We then use a contribution rate of 100%. The code is as follows: 
library(penCalc)
wage = round(rnorm(36, 3000, 100),0)
# 40% 
set.seed(111)
x 
Table 4 presents the results. As the replacement rate is  meaningless in this context, it is not shown in the table. An  informal sector worker with average monthly contribution of INR  3,000 every year for 36 years, can expect an average monthly pension of INR 13,454 with 40% annuitisation, or an average monthly pension of INR 33,635 with 100% annuitisation. 
  
    
      

Table 4: Varying contribution rates 
                
 
  
 
 40%

                    annuitisation 
                  
 100% annuitsation


           
 

Average 
10th percentile 
 
90th percentile
 
 Average 
10th percentile 
 90th percentile

      
 
 Monthly Pension (in Rs.) 
	
13,454 (1698.3)
	
11,305.8
	
15,623.4
	
 33,635.2 (4,245.9)
	
28,264.5
	
39,058.5
      
       
      
 
 In hand accumulation (in

	  Rs. million) 
	
2.7 (0.34)
	
2.3 
	
3.1 
	
 0.0  (0.0)
	
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Conclusion 
penCalc is a new open source software system developed to model pension outcomes. It allows the key variables of interest to be changed - and sets out a range of plausible outcomes using data on returns, equity premium and income from annuities purchased at retirement. The results are averages from the simulation. It is, therefore, useful to also look at the standard deviation to get a complete picture of the possible outcomes. As has been demonstrated in the examples, the outcomes can vary considerably, and retirees must factor in this uncertainty as they do their financial planning.
A recent working paper, Simulating Pension Income Scenarios with penCalc: An Illustration for India's National Pension System, demonstrates many examples of the use of this tool for different assumptions of equity returns, and annuity prices. We hope this software becomes a useful tool for policy makers and regulators as they develop pensions policy.
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Renuka Sane is an associate professor at the National Institute of Public Finance and Policy. I thank Arjun Gupta for collaboration on the software development, William Price for collaboration on the working paper. The work was supported through the FIRST Initiative in funding the engagement with India's Pension Fund Regulatory and Development Authority. 

Business TV keeps on asking this question why did it happen? Then, a range of experts are brought in to provide answers - the questions and answers are nothing to do with trading.

An interesting article discusses the stress of trying to find out why something happened: Read it Here.

Lines inside quotes are from the article mentioned in the link above.

"As an investor, my objective is not the pursuit of intellectual wealth –my objective is that of financial wealth.  Get that straight! "

Surely, sometimes our job is to follow the market, sometimes anticipate price movements, but always to go with market flow.

If the Nifty rises 200 points, Media provides many reasons why it went up. But how does this help traders? Traders have to identify the rise as it begins. Once the rally is complete, there is no buying opportunity, therefore, the reasons for the rally become  immaterial.

"With hindsight, I may eventually learn why an equity turned bullish or bearish, but that knowledge is just academically interesting."

"Believe in what your charts are telling you, and then focus on trading the “now” – it will free you from a lot of stress.  "

 Reasons for a move are found after the move has already come about. While it is good for TV, it is meaningless for a trader or investor.

We are in the business of trading for financial gains. We are not in the detective agency business, trying to find out what an event happened..

In this post, I am talking about 2 NBFCs; First Leasing Company of India Ltd and Tourism Finance Corporation of India Ltd. My objective is not to pass judgement about these companies, but to showcase why investing in NBFCs is full of unknown risks.

Cheers and happy investing!!!

When you buy computer hardware, and build a glass house in India, the costs incurred are those of:

1. Skilled and specialised labour
2. Electricity for computers
3. Electricity for cooling
4. Real estate
5. Depreciation of hardware
6. Cost of capital on all the equipment
7. The problems of achieving high availability on the above.

Firms all over the world are finding that the make vs. rent choice shifts in favour of cloud computing: You shut down your glass house and rent the services of computation in the cloud, run by the likes of Amazon or Google.

Some of this flows from the universal logic of specialisation and economies of scale. Google hires Ph.D.s in aerodynamics to optimise airflow in data centres. Almost all end-user firms are unable to justify this scale of outlay. Google is able to put a data centre right next to a hydel plant and enter into a long-term contract for 100 years of electricity. Almost all end-user firms are unable to justify this kind of thinking for their data centres.

In addition to this, I think there are some interesting and uniquely Indian perspectives.

Cooling

If the ambient temperature is 5 C instead of 30 C, this reduces the cost of cooling.

Electricity

Electricity is very costly in India as the commercial sector is paying for subsidies and inefficiency. This is particularly after you take into account the complexities of ensuring high availability.

Real estate

Land is very costly in India.

Capital

Most important, the cost of capital is very high in India.

For Amazon or Google, the cost of debt capital is 4% and the cost of equity capital is 7 to 8% (in USD).

For a big listed company in India, the cost of equity capital is 15% and the cost of debt capital is 11% (in INR). For smaller companies it's much worse.

It makes a lot of sense to reduce the balance sheet size to the extent of the cost of the data centre, and replace it by a stream of rental payments to cloud computing providers outside the country.

This idea has many interesting implications. The propensity for Indian firms to rent from overseas cloud computing providers goes up when capital controls are introduced, goes down when inflation targeting works, etc.

Cloud vendors in India?

I don't see how cloud computing vendors in India can be competitive, as they face these same uphill problems of operating in India: expensive real estate, expensive electricity particularly after taking into account the HA issues, and expensive capital.

They might argue: The labour cost is lower; it's cheaper to get a Ph.D. in aerodynamics in India. My fear is that the labour cost component in the operations of a big data centre is quite small.

So far I have assumed that the core hardware (electronics + cooling) is at high seas prices. There are many mistakes in the Indian tax system, and this could easily not be the case.

Gains for end-users

Before cloud computing, if you were an end-user organisation in India, you had no choice but to deal with the problems: expensive hardware, low economies of scale in systems administration, the high cost of HA electricity and cooling, real estate and capital. Cloud computing is a big gain for India in terms of the reduction of costs that are given to end-users. Other countries will do what's their comparative advantage (producing cloud computing services); firms in India will import these services.

Swami Vivekanand:- Why has life become complicated now?

Ramkrishna Paramahansa:- Stop analyzing life.. It makes it complicated. Just live it.

Swami Vivekanand:- Why are we then constantly unhappy?

Ramkrishna Paramahansa:- Worrying has become your habit. That’s why you are not happy.

Swami Vivekanand:- Why do good people always suffer?

Ramkrishna Paramahansa:- Diamond cannot be polished without friction. Gold cannot be purified without fire. Good people go through trials, but don’t suffer. With that experience their life becomes better, not bitter.

Swami Vivekanand:- You mean to say such experience is useful?

Ramkrishna Paramahansa:- Yes. In every term, Experience is a hard teacher. She gives the test first and the lessons afterwards.

Swami Vivekanand:- Because of so many problems, we don’t know where we are heading…

Ramkrishna Paramahansa:- If you look outside you will not know where you are heading. Look inside. Eyes provide sight. Heart provides the way.

Swami Vivekanand:- Does failure hurt more than moving in the right direction?

Ramkrishna Paramahansa:- Success is a measure as decided by others. Satisfaction is a measure as decided by you.

Swami Vivekanand:- In tough times, how do you stay motivated?

Ramkrishna Paramahansa:- Always look at how far you have come rather than how far you have to go. Always count your blessing, not what you are missing.

Swami Vivekanand:- What surprises you about people?

Ramkrishna Paramahansa:- When they suffer they ask, “why me?” When they prosper, they never ask “Why me?”

Swami Vivekanand:- How can I get the best out of life?

Ramkrishna Paramahansa:- Face your past without regret. Handle your present with confidence. Prepare for the future without fear.

Swami Vivekanand:- One last question. Sometimes I feel my prayers are not answered.

Ramkrishna Paramahansa:- There are no unanswered prayers. Keep the faith and drop the fear. Life is a mystery to solve, not a problem to resolve. Trust me. Life is wonderful if you know how to live.

Any Person can make you realise how wonderful the world is..!
But only few will make you realise how wonderful you are in the world..!