30 tax-smart ways to plan your pay packet

1। The salary (basic + DA) should be low. The rest should come by way of such allowances on which the employer pays FBT and you don't pay any tax thereon. 2। Interest paid on housing loan is deductible u/s 24 up to Rs 1।5 lakh (Rs 150,000) on self-occupied property and without any limit on a commercial or rented house. 3। The repayment of housing loan from specified sources is also deductible irrespective of whether the house is self-occupied or given on rent within the overall ceiling of Rs 1 lakh of Sec। 80C. 4। Where the accommodation provided to the employee is taken on lease by the employer, the perk value is the actual amount of lease rental or 20 per cent of the salary, whichever is lower। Understandably, if the house belongs to a family member who is at a low or nil tax zone the family benefits। Yes, the maximum benefit accrues when the rent is over 20 per cent of the salary. 5। A chauffeur driven motor car provided by the employer has no perk value। True, the company would pay FBT. It is @30 per cent on 20 per cent of the value thereby bringing down the effective rate to 6 per cent. Better still, the employee owns the car and the employer pays the cost of petrol and maintenance. 6। Contributions up to Rs 1 lakh (Rs 100,000) per annum to Superannuation Fund of the employee is not taxed either as fringe benefit in the hands of the employer or as perk in the hands of the employee. 7। Contributions to some specified schemes (Company PF, PPF, NSC, life insurance premia, etc.) qualify for a deduction u/s 80C from gross total income with an overall ceiling of Rs 1 lakh. PPF has a ceiling of Rs 70,000 to contributions made to the accounts of self and minor children whereas the contributions to accounts of self, wife and children (major or minor) attract the deductions. 8। Employer's contribution to Company PF in excess of 12 per cent of employee's salary is taxable। Employee contributes equal (or more) amount to his PF account. Again, any excess over 27 per cent of salary contributed by the employer to company Provident Fund and Superannuation Fund put together is to be treated as perks. 9। Any death-cum-retirement gratuity received up to Rs 3।5 lakh (Rs 350,000) -- subject to certain conditions -- is exempt. 10। Leave Travel Allowance given as reimbursement of expenses incurred by the employee and his family for traveling while on leave is exempt, once in two years 11। Transport allowance for commuting between residence and place of duty is exempt up to Rs 800 per month। 12। Reimbursement, not exceeding Rs 15,000 in a year, for medical treatment from any doctor for himself and his family members is देदुक्टिब्ले 13। Under section 80D, deduction up to Rs 15,000 paid as medical insurance premiums on the health of assessee himself, his spouse, parents (dependent or not) and dependent children is allowed. Where an individual has insured a senior citizen (parent or himself) a higher ceiling of Rs 20,000 is available. Additional deduction up to Rs 15,000 on premiums paid for parent/s of the assessee has been made available w.e.f. 1.4.08. 14. Professional tax paid by an employee is deductible u/s 16(iii). 15. ESOP was brought under the purview of FBT by Finance Act 07. The employer has a right to collect the FBT tax paid by him on ESOP from the employee. In that case, it will be treated as tax paid by the employee. 16। In respect of HRA, the least of the following is exempt from tax u/s 10(13A): (a) 40 per cent of salary (50 per cent for Mumbai, Kolkata, Delhi and Chennai). (b) HRA for the period the house is occupied by the employee. (c) The excess of rent paid over 10 per cent of salary. An employee living in his own house or where he does not pay any rent is not eligible for this exemption। If you are staying in a house belonging to your family members (preferably not your wife), start paying rent to the owner and ask for HRA from the employer 17। A helper engaged for the performance of the duties of an office or employment of profit is not considered as a perk। 18। If the employer employs a gardener for the building premises belonging to the employer, it would not be treated as a perk। The possibility of it being extrapolated to other servants is logical. 19। Perk value of concessional loan to the employee for purchase of house or motor cars shall be the difference between the interest payable calculated at the rate of interest for similar loans, charged by SBI and the actual interest charged. 20। Loan for medical treatment specified in Rule-3A is exempt, provided it is not reimbursed under any medical insurance scheme. Where it is reimbursed, the perquisite value shall be charged from the date of reimbursement on the amount reimbursed but not repaid against the outstanding loan taken specifically for this purpose. 21। Small loans up to Rs 20,000 in the aggregate are exempt. 22। Expenses on meals provided to the employee during his hours of duty are not treated as perks. FA 08 has declared that expenditure on non-transferable pre-paid electronic meal cards is not a perk. 23। FA 08 has also declared that provision of creche facility for children of the employee and sponsoring of an employee sportsman is not a perk. 24। Employer pays FBT on the value of the gifts. Gifts up to Rs 50,000 received without consideration by an individual from any person are tax-free in the hands of the donee. However, the Department may claim that such gifts are in lieu of salary. 25। Employer pays FBT on the value of the facility of credit cards and expenses for the club. 26। Where a movable asset is transferred by an employer to his employee directly or indirectly, the perquisite value shall be the actual cost to the employer minus the cost of normal wear and tear @10 per cent for each completed year during which such asset was put to use. In the case of motor cars the normal wear and tear would be @20 per cent whereas in the case of computers, data storage and handling devices, digital diaries, printers, etc., it would be @60 per cent. These do not include household appliances (i.e., white goods) like washing machines, microwave ovens, mixers, hot plates, ovens etc. 27। Uniform allowance to meet the expenditure incurred on the purchase or maintenance of uniform for wear during the performance of the duties of an office or employment of profit is exempt। 28। Expenses for soft furnishings (table cloths, curtains, etc.) including maintenance at the residence for those officers entertaining guests at home for official purpose are also exempt. 29। Goods at concessional rates, membership of professional associations, subscriptions for technical and business journals and newspapers are not considered as taxable perks. 30. Payment or reimbursement by the employer towards bills on Telephones and cellular is not a perk. Caution: If employer is exempt from FBT, employee pays the tax Fringe Benefit Tax is not applicable to an employer who is an individual, HUF, any fund or trust or institution eligible for exemption u/s 10(23C), or registered u/s 12AA. Rule 3 has been amended so as to include valuation of perquisite in case of benefits provided by such employers to its employees w.e.f. FY 07-08 by Notification SO 1896(E) dt 7.11.07. Bad! Very greedy, indeed!

The real reason why oil prices are rising

By now it is becoming too obvious that the United States is playing the oil game all over again. And this is the desperate gamble of a country whose economy is neck deep in trouble. Given this scenario, managing prices of oil is central to the US economic architecture. Expectedly, this gamble has been played in a great alliance between the US government, US financial sector and the media. I have earlier written about: The impending collapse of the US dollar on account of the inherent weakness in the US economy caused by its structural weakness as reflected in the sub-prime crisis; The repeated softening of the interest rates in the US that has the potency to kill the US dollar; and How the fall in the US dollar suits the US corporate sector, especially its omnipotent financial sector. Naturally, since the past few years, the US financial sector has begun to turn its attention from currency and stock markets to commodity markets. According to The Economist, about $260 billion has been invested into the commodity market -- up nearly 20 times from what it was in 2003. Coinciding with a weak dollar and this speculative interest of the US financial sector, prices of commodities have soared globally. And most of these investments are bets placed by hedge and pension funds, always on the lookout for risky but high-yielding investments. What is indeed interesting to note here is that unlike margin requirements for stocks which are as high as 50 per cent in many markets, the margin requirements for commodities is a mere 5-7 per cent. This implies that with an outlay of a mere $260 billion these speculators would be able to take positions of approximately $5 trillion -- yes, $5 trillion! -- in the futures markets. It is estimated that half of these are bets placed on oil. Readers may note that oil is internationally traded in New York and London and denominated in US dollar only. Naturally, it has been opined by experts that since the advent of oil futures, oil prices are no longer controlled by OPEC (Organization of Petroleum Exporting Countries). Rather, it is now done by Wall Street. This tectonic shift in the determination of international oil prices from the hands of producers to the hands of speculators is crucial to understanding the oil price rise. Today's oil prices are believed to be determined by the four Anglo-American financial companies-turned-oil traders, viz., Goldman Sachs, Citigroup, J P Morgan Chase, and Morgan Stanley. It is only they who have any idea about who is entering into oil futures or derivative contracts. It is also they who are placing bets on oil prices and in the process ensuring that the prices of oil futures go up by the day. But how does the increase in the price of this oil in the futures market determine the prices of oil in the spot markets? Crucially, does speculation in oil influence and determine the prices of oil in the spot markets? Answering these questions as to whether speculation has supercharged the demand for oil The Economist, in its recent issue, states: 'But that is plain wrong. Such speculators do not own real oil. Every barrel they buy in the futures markets they sell back again before the contract ends. That may raise the price of 'paper barrels,' but not of the black stuff refiners turn into petrol. It is true that high futures prices could lead someone to hoard oil today in the hope of a higher price tomorrow. But inventories are not especially full just now and there are few signs of hoarding.' On both counts -- that speculation in oil is not pushing up oil prices, as well as on the issue of the build-up of inventories -- the venerable Economist is wrong. The finding of US Senate Committee in 2006 In June 2006, when the oil price in the futures markets was about $60 a barrel, a Senate Committee in the US probed the role of market speculation in oil and gas prices. The report points out that large purchase of crude oil futures contracts by speculators has, in effect, created additional demand for oil and in the process driven up the future prices of oil. The report further stated that it was 'difficult to quantify the effect of speculation on prices,' but concluded that 'there is substantial evidence that the large amount of speculation in the current market has significantly increased prices.' The report further estimated that speculative purchases of oil futures had added as much as $20-25 per barrel to the then prevailing price of $60 per barrel. In today's prices of approximately $130 per barrel, this means that approximately $100 per barrel could be attributed to speculation! But the report found a serious loophole in the US regulation of oil derivatives trading, which according to experts could allow even a 'herd of elephants to walk to through it.' The report pointed out that US energy futures were traded on regulated exchanges within the US and subjected to extensive oversight by the Commodities Future Trading Commission (CFTC) -- the US regulator for commodity futures market. In recent years, the report however pointed out to the tremendous growth in the trading of contracts which were traded on unregulated OTC (over-the-counter) electronic markets. Interestingly, the report pointed out that the trading of energy commodities by large firms on OTC electronic exchanges was exempted from CFTC oversight by a provision inserted at the behest of Enron into the Commodity Futures Modernization Act in 2000. The report concludes that consequential impact on account of lack of market oversight has been 'substantial.' NYMEX (New York Mercantile Exchange) traders are required to keep records of all trades and report large trades to the CFTC enabling it to gauge the extent of speculation in the markets and to detect, prevent, and prosecute price manipulation. In contrast, however, traders on unregulated OTC electronic exchanges are not required to keep records or file any information with the CFTC as these trades are exempt from its oversight. Consequently, as there is no monitoring of such trading by the oversight body, the committee believes that it allows speculators to indulge in price manipulation. Finally, the report concludes that to a certain extent, whether or not any level of speculation is 'excessive' lies entirely in the eye of the beholder. In the absence of data, however, it is impossible to begin the analysis or engage in an informed debate over whether our energy markets are functioning properly or are in the midst of a speculative bubble. That was two years back. And much water has flown in the Mississippi since then. The link to the spot markets Now to answer the second leg of the question: how speculators are able to translate the future prices into spot prices. The answer to this question is fairly simple. After all, oil price is highly inelastic -- i.e. even a substantial increase in price does not alter the consumption pattern. No wonder, a mere 3-4 per cent annual global growth has translated into more than a 40 per cent annual increase in prices for the past three or four years. But there is more to it. One may note that the world supply and demand is evenly matched at about 85 million barrels every day. Only if supplies exceed demand by a substantial margin can any downward pressure on oil prices be created. In contrast, if someone with deep pockets picks up even a small quantity of oil, it dramatically alters the delicate global demand-supply gap, creating enormous upward pressure on prices. What is interesting to note is that the US strategic oil reserves were at approximately 350 million barrels for a decade till 2006. However, for the past year and a half these reserves have doubled to more than 700 million barrels. Naturally, this build-up of strategic oil reserves by the US (of 350 million barrels) is adding enormous pressure on the oil demand and consequently its prices. Do the oil speculators know of this reserves build-up by the US and are indulging in rampant speculation? Are they acting in tandem with the US government? Worse still, are they bordering on recklessness knowing fully well that if the oil prices fall the US government will be forced to a 'Bears Stearns' on them and bail them out? One is not sure. But who foots bill at such high prices? At an average price of even $100 per barrel, the entire cost for the purchase of this additional 350 million barrels by the US works out to a mere $35 billion. Needless to emphasise, this can be funded by the US by allowing it currency printing presses to work overtime. After all, it has a currency that is acceptable globally and people worldwide are willing to exchange it for precious oil. No wonder Goldman Sachs predicts that oil will touch $200 to a barrel shortly, knowing fully well that the US government will back its prediction. And, in the past three years alone the world has paid an estimated additional $3 trillion for its oil purchases. Oil speculators (and not oil producers) are the biggest beneficiaries of this price increase. In the process, the US has been able to keep the value of the US dollar afloat -- perhaps at an extra cost of a mere $35 billion to its exchequer! The global crude oil price rise is complex, sinister and beyond innocent economic theories of demand and supply. It is speculation, geopolitics and much more. Obviously, there is a symbiotic link between the US, the US dollar and the oil prices. And unless this truth is understood and the link broken, oil prices cannot be controlled.

Business Cycles in India

This paper describes business and growth rate cycles with special reference to the Indian economy. It uses the classical NBER approach to determine the timing of recessions and expansions in the Indian economy, as well as the chronology of growth rate cycles, viz., the timing of speedups and slowdowns in economic growth. The reference chronology for business as well as growth rate cycles is determined on the basis of the consensus of key coincident indicators of the Indian economy, along with a composite coincident index comprised of those indicators, which tracks fluctuations in current economic activity. Finally, it describes the performance of the leading index – a composite index of leading economic indicators, designed to anticipate business cycle and growth rate cycle upturns and downturns. Business Cycles, Growth Cycles, Growth Rate Cycles Economic cycles are characteristic features of market-oriented economies – whether in the form of the alternating expansions and contractions that characterise a classical business cycle, or the alternating speedups and slowdowns that mark cycles in growth. With the progress of the liberalisation process in India, which has transformed it into more of a market-driven economy, such cycles are destined to become prominent features of the economic landscape. The National Bureau of Economic Research (NBER), founded in New York in 1920, pioneered research into understanding the repetitive sequences that underlie business cycles. Wesley C. Mitchell, one of its founders, first established a working definition of the business cycle that he, along with Arthur F. Burns (1946), later characterised as follows: “Business cycles are a type of fluctuation found in the aggregate economic activity of nations that organize their work mainly in business enterprises: a cycle consists of expansions occurring at about the same time in many economic activities, followed by similarly general recessions, contractions and revivals which merge into the expansion phase of the next cycle; this sequence of changes is recurrent but not periodic; in duration business cycles vary from more than one year to ten or twelve years; they are not divisible into shorter cycles of similar character with amplitudes approximating their own.” This definition of the business cycle does not make explicit the notion of ‘aggregate economic activity’, leading some to argue in recent years that a satisfactory proxy for this concept is a country’s GDP, which is, after all, about as aggregate a measure of output as possible. On this narrow, output-based view, if one had available a monthly estimate of GDP, then its peaks and troughs would be all that would be needed to determine the peak and trough dates for the business cycle. But Geoffrey H. Moore, who worked closely with Mitchell and Burns at the NBER, noted (1982) that “No single measure of aggregate economic activity is called for in the definition because several such measures appear relevant to the problem, including output, employment, income and [wholesale and retail] trade… Virtually all economic statistics are subject to error, and hence are often revised. Use of several measures necessitates an effort to determine what is the consensus among them, but it avoids some of the arbitrariness of deciding upon a single measure that perforce could be used only for a limited time with results that would be subject to revision every time the measure was revised.” Basically, both on the basis of the meaning of aggregate economic activity and issues of revision and measurement error, he advocated the determination of business cycle dates based on multiple measures. This approach is, in fact, the basis of the determination of the official U.S. business cycle dates by the NBER, and of international business cycle dates by the Economic Cycle Research Institute (ECRI), founded by Moore.

What is a recession? In this context, it is important to understand something of the mechanism that drives a business cycle. A recession occurs when a decline – however initiated or instigated – occurs in some measure of aggregate economic activity and causes cascading declines in the other key measures of activity. Thus, when a dip in sales causes a drop in production, triggering declines in employment and income, which in turn feed back into a further fall in sales, a vicious cycle results and a recession ensues. This domino effect of the transmission of economic weakness from sales to output to employment to income, feeding back into further weakness in all of these measures in turn, is what characterizes a recessionary downturn.

At some point, the vicious cycle is broken and an analogous self-reinforcing virtuous cycle begins, with increases in output, employment, income and sales feeding into each other. That is the hallmark of a business cycle recovery. The transition points between the vicious and virtuous cycles mark the start and end dates of recessions.

Under the circumstances, it is logical to base the choice of recession start and end dates not on output or employment in isolation, but on the consensus of the dates when output, income, employment and sales reach their respective turning points. To do any less is to do scant justice to the complexity of the phenomenon known as the business cycle (Layton and Banerji, 2004). That is also why a decline in GDP alone, when it does not trigger the characteristic vicious cycle of falling employment, income and sales, does not constitute a recession. Similarly, that is why a transient rise in GDP that does not ignite a selfreinforcing recovery in employment, income and sales may be part of a “double-dip recession”, but does not qualify as a new expansion. However, because of its simplicity, two consecutive quarterly declines in GDP has become perhaps the most popular rule for determining the onset of recession. Yet, the use of such a rule may produce quite a nonsensical set of business cycle dates. One could well imagine a period of depressed economic activity associated with falling output and employment and with unemployment climbing, but with two clear quarterly declines in GDP happening to have a modestly positive intervening quarter.

Similarly, to automatically conclude that a country was in recession simply because of two minutely negative quarterly growth rates in GDP – particularly if they occurred simply because they followed on from one or two quarters of unusually strong quarterly growth – seems just as misguided. In the Indian case, quarterly GDP data were not available until the late 1990s, so it would be difficult in any case to base the historical business cycle dates on such a rule. The above discussion describes classical business cycles that measure the ups and downs of the economy in terms of the absolute levels of the coincident indicators, i.e. indicators that gauge current economic activity. However, in the decades that followed the end of World War II, many economies like Japan and Germany saw long periods of rapid revival from wartime devastation, so that classical business cycle recessions seemed to have lost their relevance. Rather, what was considered increasingly germane was a second NBER definition of fluctuations in economic activity, termed a growth cycle. A growth cycle traces the ups and downs through deviations of the actual growth rate of the economy from its long-run trend rate of growth. In other words, a growth cycle upturn (downturn) is marked by growth higher (lower) than the long-run trend rate. Economic slowdowns begin with reduced but still positive growth rates and can eventually develop into recessions. The high-growth phase typically coincides with the business cycle recovery, while the low-growth phase may correspond to the later stages leading to recession. Some slowdowns, however, continue to exhibit positive growth rates and are followed by renewed upturns in growth, not recessions. As a result, all classical business cycles associate with growth cycles, but not all growth cycles associate with classical cycles. Of course, growth cycles, measured in terms of deviations from trend, necessitated the determination of the trend of the time series being analysed. However, while growth cycles are not hard to identify in a historical time series, they are difficult to measure accurately on a real-time basis (Boschan and Banerji, 1990). This is because any measure of the most recent trend is necessarily an estimate and subject to revisions, so it is difficult to come to a precise determination of growth cycle dates, at least in real time. This difficulty makes growth cycle analysis less than ideal as a tool for monitoring and forecasting economic cycles in real time, even though it may be useful for the purposes of historical analysis. This is one reason that by the late 1980s, Moore had started moving towards the use of growth rate cycles for the measurement of series which manifested few actual cyclical declines, but did show cyclical slowdowns. Growth rate cycles are simply the cyclical upswings and downswings in the growth rate of economic activity. The growth rate used is the "six-month smoothed growth rate" concept, initiated by Moore to eliminate the need for the sort of extrapolation of the past trend needed in growth cycle analysis. This smoothed growth rate is based on the ratio of the latest month's figure to its average over the preceding twelve months (and therefore centred about six months before the latest month). Unlike the more commonly used 12-month change, it is not very sensitive to any idiosyncratic occurrences 12 months earlier. A number of such advantages make the six-month smoothed growth rate a useful concept in cyclical analysis. Cyclical turns in this growth rate define the growth rate cycle.

At ECRI, growth rate cycles rather than growth cycles are used along with business cycles as the primary tool to monitor international economies in real time. The growth rate cycle is, in effect, a second way to monitor slowdowns in contrast to contractions. Because of the difference in definition, growth rate cycles are different from growth cycles. Thus, what has emerged in recent years is the recognition that business cycles, growth cycles and growth rate cycles all need to be monitored in a complementary fashion. However, of the three, business cycles and growth rate cycles are more suitable for real-time monitoring and forecasting, while growth cycles are suited primarily for historical analysis. Dating of Business Cycles and Growth Rate Cycles in the Indian Economy For India, Chitre (1982) had initially determined a set of growth cycle dates. Following the classical NBER procedure, Dua and Banerji (1999) later determined business cycle and growth rate cycle dates for the Indian economy. These dates were further revised and reported in Dua and Banerji (2004a)1. Coincident Index and Reference Chronology The timing of recessions and expansions of Indian business cycles is determined on the basis of a careful consideration of the consensus of cyclical co-movements in the broad measures of output, income, employment and domestic trade that define the cycle. A summary combination of these coincident indicators, viz., variables that move in tandem with aggregate economic activity, is called the Coincident Index, whose cyclical upswings and downswings generally correspond to periods of expansion and recession respectively. Table 1 reports the business cycle chronology for the Indian economy since the 1960s and gives the dating of peaks and troughs as well as the duration of recessions and expansions. This shows that during the 1990s, the Indian economy experienced two short recessions – the first from March 1991 to September 1991 and the second from May 1996 to November 1996. Prior to these recessions, it experienced a very long expansion from March 1980 to March 1991. Likewise, the reference cycle, derived from the central tendency of the individual turning points in the growth rates of the coincident indicators that comprise the 1 The latest updates to the chronologies are available at http://www.businesscycle.com/internationalcycledates.php coincident index, gives the highs and lows of the growth rate cycle. This dates the slowdowns and speedups in economic activity. Table 2 gives the reference chronology of the growth rate cycle along with the duration of slowdowns and speedups in the Indian economy since the 1960s. While the economy experienced only two short recessions in the 1990s, it exhibited four slowdowns – March 1990 to September 1991, April 1992 to April 1993, April 1995 to November 1996, and September 1997 to October 1998. Thus, the growth rate cycle peaks led their comparable business cycle peaks, highlighting the distinction between a slowdown and a full-fledged recession. The historical chronology of business and growth rate cycles helps to design a system for the prediction of recessions and recoveries as well as slowdowns and pick ups. In fact, the reference chronology provides a test of the performance of leading indicators in anticipating turning points of the cycles.

Leading Index: The Indian Experience Leading indicators are designed to anticipate the timing of the ups and downs in the business cycle. They are related to the drivers of business cycles in market economies, which include swings in investment in inventory and fixed capital that both determine and are determined by movements in final demand. They also include the supply of money or credit, government spending and tax policies, and relations among prices, costs and profits. An understanding of these drivers can help identify the predictors of the downturns and upturns. Remarkably, decades of experience of the researchers at ECRI have shown that in a wide variety of market economies, both developed and developing, similar leading indicators consistently anticipate business cycles, underscoring the fundamental similarity of market economies. Such robust leading indicators can be used as the foundation for reliable cyclical forecasts. A composite of the leading indicators yields the Leading Index, peaks and troughs in which anticipate or “lead” peaks and troughs in the business cycle. Also, peaks and troughs in the leading index growth rate anticipate peaks and troughs in the growth rate cycle, i.e. slowdowns and speedups in economic growth respectively. The Leading Index for the Indian economy is described in Dua and Banerji (2004a). The performance of the Leading Index for the Indian economy vis-à-vis the business cycle reference chronology is shown in Chart 1 while the performance of the Leading Index growth rate is shown in Chart 2. Leads are shown with a negative sign. Both charts show that the emergence of fairly consistent leads (especially with respect to troughs) started only in the post-liberalisation period that began in earnest in 1991. Before that, the government long dominated the “commanding heights of the economy” and the assumption of a free-market economy was questionable. For the first four decades after India’s independence, the government owned roughly half of the economy’s productive capacity. Even the private sector was hemmed in by myriad regulations and rampant distortions of the free market, such as controls on prices and interest rates and extensive licensing procedures for the establishment of new factories or expansion of existing capacity. Generally, there were major barriers to entry and exit in most industries, including the difficulty of laying off any part of the labour force regardless of the profitability. Under such circumstances, endogenous cyclical forces do not necessarily drive business cycles. It is thus understandable that the leading indicators that typically anticipate business cycles in market economies did not lead in a systematic manner. In fact, Indian recessions before the 1990s were mainly triggered by bad monsoons, which cannot be predicted by leading indicators. In a sense, the emergence of the leads since the early 1990s is evidence that the free market is starting to dominate the economy. Another aspect of the liberalisation of India’s economy is the growing importance of exports, which have become increasingly important to its overall growth prospects. Like domestic growth, export growth is also cyclical, but is driven by business cycles in the main export markets. Thus, in order to predict the timing of peaks and troughs in exports growth, it is logical to combine ECRI’s leading indexes for those foreign economies with a real effective exchange rate, which determines the price competitiveness of Indian exports, to arrive at a leading index for India’s exports (Dua and Banerji, 2004b), which leads turning points in Indian exports growth by an average of nine months. This leading exports index complements the leading index for the Indian economy, to provide the means to monitor cycles in domestic cycles and well as exports cycles. Source - http://www.cdedse.org/pdf/work146.pdf