Say VAT? ..... And Other Concepts

So, I’ve talked about India’s broad GDP trends (aggregate and sectoral) in the last couple of posts. Before we really begin to talk numbers though, I want to talk about how the new series of National Accounts (2011-12 as base year) released by the CSO in Jan 2015, differs from the previous series (2004-05 as base year). And no – the differences don’t just lie in the base year. 

To appreciate the key differences between the series, it’s important to understand some basic concepts first. These concepts are from the SNA, 2008 (latest edition). The United Nation’s SNA or “System of National Accounts” is an international standard system of national accounts, followed by most countries (including India) to the extent that they can, to prepare and present the accounts of their nation. 

Basic Concepts (from the SNA, 2008)

VAT 

VAT is a tax on products collected in stages by enterprises. Producers are required to charge certain % rates of VAT on the goods/services they sell. VAT is shown separately on the sellers’ invoices so that purchasers know the amounts they have paid. Producers however, are not required to pay to the government the full amounts of the VAT invoiced to their customers because they're usually permitted to deduct the VAT that they themselves have paid on goods/services purchased for their own intermediate consumption, resale or gross fixed capital formation. Producers are thus obliged to pay only the difference between the VAT on their sales and the VAT on their purchases for intermediate consumption or capital formation. Hence the expression “value added tax”.

• Invoiced VAT is the VAT payable on the sales of a producer; it is shown separately on the invoice that the producer presents to the purchaser.

• Deductible VAT is the VAT payable on purchases of goods/services intended for intermediate consumption, gross fixed capital formation or for resale that a producer is permitted to deduct from his own VAT liability to the government in respect of VAT invoiced to his customers.

• Non-deductible VAT is VAT payable by a purchaser that is not deductible from his own VAT liability, if any.

Lets take the example of producer “A”. Let's assume that the VAT that A invoices to customers is = X, and the VAT that A pays on his own purchases for intermediate consumption, GFCF or resale = Y. In this case, Y is the deductible VAT. Hence, A’s final VAT liability to the government is = X-Y.

On the other hand, the VAT paid by households for purposes of final consumption or fixed capital formation in dwellings is not deductible. This entire amount goes to the government. 

Taxes on Products vs. taxes on Production

• Taxes on products (or product taxes) are payable per unit of the product. The tax may be a flat amount per unit or a percentage of the value at which the product is sold. Examples include Excise Tax, Sales tax, Service tax and Import/Export duties. Similarly, Product subsidies are receivable per unit of the product. In the Indian context, these include food, petroleum and fertilizer subsidies, interest subsidies given to farmers/households through banks, and subsidies for providing insurance to households at lower rates. 

• Taxes on production (or production taxes) are paid with relation to production and are independent of the volume of actual production. Examples include land revenues, stamp fees, registration fees and tax on profession. Production subsidies, which follow the same principle, include subsidies to railways, input subsidies to farmers, subsidies to village and small industries, administrative subsidies to corporations or cooperatives etc.

Armed with this knowledge, we’re now going to talk about the various “prices” used in the SNA.

Types of Prices used in the SNA

The SNA uses two types of prices to measure output: Basic prices and Producers’ prices.

1. Basic price 

Basic price is the amount receivable by a producer from the purchaser (per unit of good/service) minus any product taxes payable, and plus any product subsidy receivable by the producer. It does include taxes on production and exclude subsidies on production. It excludes any transport charges invoiced separately by the producer. 

Basic price = Price received by producer1 – product taxes + product subsidies 

2. Producer’s price

Producer’s price is the amount receivable by the producer from the purchaser (per unit of good/service) minus any VAT2 invoiced to the purchaser. Unlike the Basic price, Producer’s price does include taxes on products (other than VAT) and exclude subsidies on products. It excludes any transport charges invoiced separately by the producer. 

In a nutshell, the Producer’s price is the price, excluding VAT, that the producer invoices to the purchaser. 

Producer’s price = Price received by producer1 – invoiced VAT2 

                               = Basic price + product taxes – product subsides – invoiced VAT 

1 Excluding any transport charges invoiced separately by the producer. 
2 VAT refers to VAT or any other similar type of deductible tax collected in stages 

Basic price preferred over Producer’s price for valuing Output of producers 

As I explained above, Producer’s price excludes invoiced VAT, but includes all other taxes on products. The Basic price on the other hand, does not include any product taxes (VAT or others). It is thus, a much clearer concept to grasp and the preferred method for valuing the output of producers. 

Also, unlike Producer’s price, Basic price measures the amount actually retained by the producer for covering factor costs and paying taxes on production to the government. It is therefore, much more relevant to the producer’s decision making (note: product taxes are usually paid by purchasers and not producers themselves, so don’t directly impact producers’ production decisions). 

3. Factor cost 

Factor cost is a concept usually not used on a per unit basis, but here’s what it implies – it is the amount receivable by a producer from the purchaser minus all product and production taxes payable, and plus all product and production subsidies receivable by the producer. It excludes any transport charges invoiced separately by the producer. 

Factor cost = Price received by producer1 – product taxes – production taxes + product subsidies + production subsidies 

which means, 

Factor cost = Basic price - production taxes + production subsidies 

The equation above makes clear why this concept isn’t normally used on a per-unit basis. It’s because production taxes and subsidies aren’t charged on a per unit basis and not reported on sale invoices. Their "implied" per unit values have to be derived from the accounts of the producer. 

Factor cost not explicitly used in SNA, 2008; relegated to background in new Indian series of National Accounts 

Factor cost is not a concept that is explicitly used in the SNA, 2008. It can however be derived from the measure of Output at Basic prices by subtracting production taxes and adding production subsidies (as we show in the equation above). 

The reason that we've still defined the concept is here, is because GDP at Factor Cost was an important measure of value added for the Indian economy thus far – till the new series of national accounts was released by the CSO in January 2015. In the new series, GDP at Factor cost has been relegated to the background, in-line with SNA recommendations. We’ll talk more about this in our next post. 

4. Purchaser’s price

The purchaser’s price is the amount paid by the purchaser, excluding any deductible VAT (i.e. any VAT that is deductible for the purchaser), in order to take delivery of the good/service at the time and place required by the purchaser. Purchaser’s price includes any transport charges paid separately by the purchaser to take delivery at the required time and place. 

GDP at Purchaser’s price is what we’ve hitherto referred to as GDP at Market price in the Indian context. 

Ciao for now. 

India's Sectoral GDP Trends

In this post, I’m going to talk about India’s GDP from a sectoral perspective. While I touched upon this in my previous post, I will highlight different trends here.

To begin with, lets take a quick look at the sectoral composition of India’s GDP vs. key developed and emerging nations.

Table 1: Sectoral Composition of India’s GDP vs. Other Nations
* See the note on data sources for this table at the end of the post.

To be able to draw any valid conclusions from this table, its important to understand the history of sectoral GDP transitions in the developed and developing world first.

1. Historically, for the leading developed nations (US, UK), there was an extended period of strong industrial sector growth (in terms of GDP share), its reaching of a peak (40%+ of GDP for the US), and then a fall off in its GDP share over the decades, all while services continued to gain share and finally came to dominate the GDP. (See chart below)

    Chart 1: US Sectoral GDP (as a % of total GDP)
    * See note for this chart at the end of the post.

I’ve picked up the chart provided above from the article “History lessons: Understanding the decline in manufacturing”, authored by Louis Johnson and published in the MinnPost in Feb 2012. Here’s the link to the full article: https://www.minnpost.com/macro-micro-minnesota/2012/02/history-lessons-understanding-decline-manufacturing. The trend that I have mentioned above is clearly visible in this chart. 

The share of agriculture in US GDP has been falling since the 1840s. The industry sector showed an extended period of growth (in GDP share) from 1840 till about 1910 when industry share peaked at ~43%, following which its share in GDP has shown a declining trend except for the short period during/after WWII. 

The US services sector has continued to gain share (as % of GDP) since 1850. It has always had a higher share in GDP vs. the industry sector (since 1850) except for the period between 1895-1905. Since then, while the share of services in GDP has continued to rise, that of the industry sector has been falling.

With this background in mind, lets look at Table 1 again. The share of industry in India’s GDP is 17%, same as that in the US. The share of the services sector in India is 65% vs. 82% in the US. The share of agriculture of course is much higher at 18% vs. 1% in the US.

2. Even though industry has the same share of GDP (17%) in both countries (India and the US), and services has high majority share in both nations as well, it is would be erroneous to assume that India’s path to industrialization has been the same as that of the US. 

The US and UK are now amongst a small set of nations that have built a strong industrial base before moving towards services’ dominance of the GDP. In most developing/emerging nations including India, there has been a movement from agriculture to service oriented economies without a substantive industrial build-up in between. As a result, even though GDP composition in these countries may be similar to that of developed economies, a strong industrial sector and its associated benefits are missing.

The chart below shows India’s sectoral transition post independence. From 10% in 1950, the industrial sector expanded to form ~20% of GDP by 1980. Since then it has hovered around this level, with its share now declining since 2010 (industrial share of 17% in 2013). Bottom-line: No sustained industrial build-up.

Chart 2: India's Sectoral GDP transition post independence - no sustained industry build-up

Source: RBI database on Indian economy. Sectoral GDP shares based on GDP at Factor Cost, at current prices (series with 2004-05 base year). 

3. Why has the industrialization phase been “skipped” as it were in developing nations like India, with services dominating the GDP somewhat prematurely?

There are few reasons for this:

•  First and foremost, many developing nations have not been able to successfully create the conditions required for a sustained industrial build-up. These include attracting the necessary investments in industrial capital and infrastructure, keeping up with technological advances, providing effective governance, ushering in sustainable economic reforms, educating the largely unskilled workforce etc. Not surprisingly, the build-up of a strong industrial base has eluded them. 

• Since the industrial sector (government + private) has been unable to absorb the rapidly growing domestic workforce, the informal services sector is where most non-agricultural workers have been absorbed and create value. Hence, the services sector has ended up dominating developing world GDP in terms of employment generation as well as value added (much like in the developed world), not so much because of its own substantive organic growth over the decades (like in the developed world), but because of industry’s relative lack of robust growth.

• With advances in technology and rising productivity, the share of the manufacturing sector in GDP and employment has been falling worldwide. It’s happening in China too now (I’ll talk about this in the next point). Having benefited from the productivity gains/advances in technology that came before and as they were industrializing, it was never realistic to assume that industrial sectors in developing nations would achieve the kind of GDP share peaks achieved by industry in the US and UK during their path to industrialization decades ago.

• China has been an exception to this developing world phenomenon. Given its communist form of government, unrelenting focus on low-cost manufacturing and infrastructure growth, availability of a large, young, low-cost labour-force as well as a large domestic market, China has become the factory of the world (produces around a quarter of global manufacturing output). While China is losing some of its business to other lower-wage countries mostly in East Asia, it will be hard to replicate China’s model. There cannot be many Chinas on the planet. There simply isn’t that kind of worldwide demand for manufactured goods. Also, China itself is facing the challenge of lower global demand now. Given the industrial scale it has achieved already, growth will have to moderate.

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Note on data sources for Table 1: For USA, UK and Germany, I have sourced the data from the stats.oecd.org website. The industry sector includes energy, while construction is included in the services sector, just as is the case for the Indian data (source: RBI’s database on the Indian economy). For China, I’ve pulled the above data from the Chinese National Bureau of Statistics, while for Brazil I’ve used the figures provided in the CIA world factbook. 

For USA, UK and Germany, the figures are on based on current price estimates of GVA at Basic Prices for 2013 or 2014; for India, they are based on 2013-14 current price estimates of GDP at Factor Cost. For China and Brazil, the figures are based on current price 2013 or 2014 GDP estimates (don’t have more details).

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Note on Chart 1: In chart 1 construction is included in the industry sector, while in table 1, I’ve included construction in the services sector (as is the practice in India). If I adjust for this inconsistency in the table (i.e. add construction which has ~4% share in US GDP to the industry sector after removing it from the services sector), I get US industry share of 21% and services share of 78% of GDP for 2013. This is much closer to 2010 sector shares in chart 1.

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India's GDP Trends

So, I recently downloaded all this GDP and other macro data from the RBI’s database on the Indian economy (http://dbie.rbi.org.in), and I can hardly contain my excitement. My mind is like the inside of a fat water balloon – it is literally “bursting” with ideas for posts!

But since I’m an adult, I’m going to restrain myself and go step by step. I will do a series of posts based on this data. Today, I’m going to present and analyze trends in India’s Gross Domestic Product (GDP) all the way back from the 1960s.

GDP Trends  

I’ve created below a chart of economy-wide y-y GDP growth over the last 50+ years. The growth rates charted here are those of GDP at Factor Cost, at constant prices (04-05 base year). What does that mean?

• “GDP at factor cost” = GDP at market prices – Indirect taxes + Subsidies. It is a measure of GDP that excludes net indirect taxes paid to the government (these are taxes paid on good and services, and not on personal incomes). Since indirect taxes and subsidies are “transfer” payments (i.e. no output is created or economic value added in such transactions), it makes sense to exclude them while measuring GDP growth.

• “GDP at constant prices” is calculated using prices of products/services in a chosen base year (04-05 in this case), as opposed to GDP at current prices, which is calculated using prices of goods/services prevailing in the current year. GDP at constant prices allows us to measure “real” GDP growth i.e. growth due to expansion in output (and not just inflation) since prices are held constant.

Below are the key trends and analyses extracted from this data:

• Annual GDP growth rates of the 2000s three times more stable (less volatile) vs. those of the 1960s. 

The chart above shows that GDP growth was significantly more volatile in the '60s and '70s, than it has been in later years. GDP growth rates have become more stable (less volatile) and predictable over the decades. For the mathematically inclined (nerds like me), I’ve calculated below the arithmetic mean of y-y GDP growth rates in each decade, as well as their Standard Deviation (from the mean).

What is Standard Deviation you ask? Standard Deviation (σ or SD) is simply a measure of how spread out numbers in a population are around the population mean.

Look at the third column in the table above. It shows that in the 1960s, SD/Mean was = 93%, which means that on an average, yearly growth rates lay almost “1 mean distance” away from the population mean of 4%. In the ’90s, this distance was “0.34 mean”, while in the 2000s, it was “0.30 mean”. These numbers clearly indicate that growth has become much more stable. Infact, GDP growth rates in the 2000s were 3x more stable (less volatile) vs. the 1960s [SD/Mean of 2000s (30%) =1/3rd SD/Mean of 1960s (93%)].

• Why has GDP growth become more stable and predictable, you ask? It’s because Agriculture, the sector exhibiting the most volatility in y-y growth, now comprises just 14% of real GDP vs. 48% in 1960. Services, which exhibits the least volatility, now comprises 67% of real GDP vs. 37% in 1960.

There are three key sectors in our economy (any economy really) – Agriculture, Industry and Services. The Indian Agriculture sector has always been the most volatile in terms of GDP growth because it is heavily dependent on the monsoon for irrigation. 

In the table below, I’ve calculated the mean & SD of y-y sectoral GDP growth rates for the period 2000-01 to 2013-14. The SD for the agriculture sector is 1.3x the mean! Kind of defeats the purpose of calculating a mean, huh? Services growth is the most stable (SD = 0.22x mean).

Given that the agriculture sector is now (2013-14 estimates) just 14% of real GDP vs. 48% in 1960, and Services comprises 67% of GDP vs. 37% in 1960, GDP growth today is much more stable and predictable.

• Average y-y GDP growth has been accelerating over the decades (3.2% in the 1960s to 7.2% in the 2000s). The answer lies again in sectoral composition --> in the rising share (67% of GDP today vs. 37% in 1960) of the services sector where growth has been accelerating; and the falling share (14% today vs. 48% in 1960) of the volatile and low (avg.) growth agriculture sector. Industry has exhibited a modest though patchy/inconsistent acceleration in growth (19% of GDP today vs. 14% in 1960). See chart below and pie charts above.

• How does India’s GDP growth compare with other nations? For the period 2006-14, India’s GDP has grown at an average 7.5% y-y vs. just 1-1.5% growth for the major developed nations (USA, UK and Germany) and 3-3.5% for the emerging economies of Russia and Brazil. China has grown at a scorching 9.9%. That said, growth has slowed down in China this year and it faces many challenges as it looks ahead.

India though well positioned for now, has challenges of it’s own (subject for another post). I’m going to talk about Sectoral GDP trends in detail in our next post. Ciao for now!

Time To Narrow The Gender Chasm in National Income Accounting

Want a break from all the money market stuff (Repos, CRR etc.) I’ve been talking about so far? That makes the two of us.

I have just what the doctor ordered - some mid-day comic relief from one of my favorite webcomics.

This also happens to be a great segue to the relatively serious stuff I’m going to be talking about in this post, which as you may have guessed, has something to do with “gender chasms” and something to do with “national income accounting”.

Follow the link below to read my full article “Time To Narrow The Gender Chasm in National Income Accounting”, published by Point blank 7 in May 2014.

Time to narrow the Gender Chasm in National Income Accounting

Point Blank 7 is an upcoming, independent news website focused on presenting a wide range of news and opinions (sometimes ignored by mainstream media) to its readers.

In this article, I’ve talked about the non-inclusion of unpaid domestic services (in developing countries, 90% of these services are provided by women) in the United Nation’s globally followed “System of National Accounts” and its devastating consequences for women. It’s a simple, quick and unpretentious read – great for gaining a speedy grip on this important issue.

MY PROMISE TO YOU:
If you’re a woman (or man) who’s feeling under-appreciated for all the mind-numbing yet life-sustaining chores you do everyday for your loving yet slightly ungrateful family (its OK to say that out loud, even if its grammatically incorrect), this will strike a special chord in your heart.

Note: Incase you were wondering (I know you weren't, but I'm going to tell you anyway) where grammatical liberty was exercised above - it was in the phrase "slightly ungrateful". It's like saying "I'm slightly dead".

With love,

- The grammar Nazi

Calculating NDTL & CRR – in Practice

So in my last post titled “CRR: How to calculate Net Demand and Time Liabilities (NDTL) – the Theory”, I covered all the theory behind the NDTL calculation for CRR purposes. In this post, we’ll do a real-life numerical illustration in true Nerdverve “Ishstyle”.

Provided below is the same table that we included in the previous post - table number 4, “Scheduled Commercial Banks – Business in India” from the RBI’s WSS published on Sep 18th 2015. We’ll use the information in this table to calculate NDTL for SCBs (for CRR) outstanding as on September 4th.

From the table above (as on Sep 4^th):

Liabilities to Others = Rs. 97,341.5 Bn  (90, 280.5 + 2,380.2 + 4,680.8)

Liabilities to the Banking system = Rs. 1,806 Bn  (1,267.5 + 470.4 + 68.1)

Assets with the Banking system = Rs. 2583 Bn (1,772.1 + 207.7 + 232.8 + 370.4)

Since Liabilities to the Banking system are < Assets with the Banking system, NDTL = Liabilities to Others = Rs 97,341.5 Bn.  

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Remember (from our previous post), NDTL for the banking system is =

Liabilities to Others in India (#2 in table above) + Liabilities to the Banking system (#1 in table above) – Assets with the Banking system (#5 in table above), when “Liabilities to the Banking system” – “Assets with the Banking system”> 0.

If “Liabilities to the Banking system” – “Assets with the Banking system” < 0, then NDTL = Liabilities to Others in India.

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Now, from this NDTL figure obtained above, we need to subtract the following items that are exempted from CRR maintenance. (Please read my previous post for detailed explanations on all these exempted items)

1.    While calculating the “Net inter-bank liabilities” (“Liabilities to the Banking system” – “Assets with the Banking system”), SCBs should not include inter-bank term deposits / term borrowing liabilities of original maturities of 15 days and above and up to one year in “Liabilities to the Banking system”. Similarly, banks should exclude their inter-bank assets of term deposits and term lending of original maturity of 15 days and above and up to one year in “Assets with the Banking System”.

2.    Credit balances in Asian Clearing Union (US$) Accounts.

3.    Demand and Time Liabilities of banks’ Offshore Banking Units (OBU)

4.  The eligible amount of incremental FCNR (B) and NRE deposits of maturities of three years and above from the base date of July 26, 2013, and outstanding as on March 7, 2014, till their maturities/ pre-mature withdrawals.

5.  Minimum of Eligible Credit (EC) and outstanding Long Term Bonds (LB) to finance infrastructure loans and affordable housing loans, as per the circular DBOD.BP.BC.No.25/08.12.014 /2014-15 dated July 15, 2014.

Detailed data that would allow us to exclude the exempted items above from our NDTL calculation is not provided in the RBI’s WSS and other public releases. Banks however obviously possess all this information for their own operations. They subtract the exempted items from the NDTL calculated in the formula above, to get the precise NDTL for CRR maintenance purposes.

NDTL as on Sep 4th used to calculate CRR funds requirement for fortnight of Sep 19th – Oct 2nd 

Per RBI regulations, every alternate Friday, banks have to release certain data on their assets, liabilities, operations etc. These alternate Fridays are called “Reporting Fridays”. The period starting from the Saturday immediately following a Reporting Friday, all the way to the next reporting Friday is called “Reporting fortnight”. Let’s clarify with a real life example. The month of Sep 2015 had two reporting Fridays (see the calendar snapshot provided below) – the 4th and the 18th. The two reporting fortnights in the month were 5th -18th Sep and 19th Sep – 2nd Oct (this one included the first couple of days of October).

CRR maintenance happens with a fortnight’s lag. This means that CRR is maintained on the NDTL of the reporting Friday of the second preceding fortnight. For instance, for the reporting fortnight 19th Sep – 2nd Oct, CRR is maintained on the NDTL as on 4th Sep – the reporting Friday of the 2nd preceding fortnight (22nd Aug – 4th Sep).

This is why we are going to use the NDTL as on Sep 4th to calculate the funds requirement for CRR maintenance for the fortnight of 19th Sep -2nd Oct. 

Funds required for CRR maintenance during fortnight of 19th Sep -2nd Oct?

The NDTL we calculated above (Rs 97,341.5 Bn as on Sep 4th) is not adjusted for CRR exemptions. Lets use it however, to do a rough calculation of the CRR funds requirement for the fortnight of 19th Sep – 2nd Oct. CRR was 4%, hence the funds required for CRR maintenance were = 4% * 97,341.5 = Rs. 3,894 Bn. 

Note: The precise CRR funds requirement for a reporting fortnight is provided in the WSS released on the Friday following that fortnight. This supplement also includes the actual cash balances maintained by banks (with the RBI) during the fortnight. For instance, the CRR requirement for the fortnight of 19th Sep – 2nd Oct was provided in table no. 3 of the WSS released by the RBI on Oct 9nd (please see exhibit below). It was = Rs. 3,682.5 Bn. 

Our rough estimate of the cash reserve requirement was ~6% higher than the actual figure. Not bad I say! (given that we worked with incomplete data) 

We can work backward and calculate the actual NDTL figure (for CRR purposes) as on Sep 4th by dividing 3,682.5 by 4%, which gives us Rs. 92,062.5 Bn. 

How CRR is maintained in practice

We know from the data above that the daily CRR funds requirement for the fortnight of Sep 19th – Oct 2nd was Rs 3,682.5 Bn. This means that for the entire 14 day period, banks had to maintain total funds (adding up cash reserve reserves maintained on each of the 14 days) of Rs 3,682.5 Bn * 14 = Rs. 51,555 Bn. 

Per current guidelines, all banks are required to maintain a minimum CRR balance of 95% of the average daily reserves required for the fortnight, on all days of the fortnight. This means that banks were required to maintain at least Rs. 3,498.4 Bn (95% of 3,682.5) in cash reserves with the RBI every day of the fortnight in question, in addition to fulfilling the total funds requirement of Rs. 51,555 Bn for the fortnight. 

Lets assume that banks maintained the minimum balance of Rs. 3,498.4 Bn (95% of requirement) on the first 13 days of the fortnight. This means that on the last day of the fortnight, they would have to maintain a cash balance of (51,555 – 3,498.4 * 13) = Rs 6,076.1 Bn. 

In the table above, you can see that the total cash balances maintained with the RBI during the fortnight (adding all 14 days) were = Rs 52,605.4 Bn. This was Rs 1,050 Bn more than what was required for CRR maintenance over the 14 days.

This was the case because the banking system was in an excess liquidity situation. This fact is underscored by the tables provided below from the RBI's Weekly supplements (table no. 8 “Liquidity Operations of by the RBI) – they show the net absorption of liquidity by the RBI from the banking system through its Reverse Repo and Open Market Operations during the fortnight in question. Including the 19th of Sep (not shown in the tables below), the RBI absorbed a total of Rs. 224 Bn from the banking system during the fortnight.

In a tight liquidity situation, the cash balances maintained with the RBI would normally not have been in excess of the CRR requirement.