facets of indian consumers 3

8/14/2019 Facets of Indian Consumers 3

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Is there a clear relationship between credit growth and market growth?

The fastest growing cities out of 112

Growth rates(CAGR)

Market Size

GrowthRate

DepositGrowth Rate

Credit GrowthRate

Silvassa 23 14 71

Gandhinagar 22 10 54

Bokaro 19 7 -4

Surat 17 11 18

Thiruvallur 17 11 28

Agartala 16 13 32

Chandigarh 16 13 7

Thanjavur 16 5 20

Kohima 15 9 26

Noida 15 28 43

The slowest growing cities out of 112

Growth rates

(CAGR)

Market Size

Growth

Rate

Deposit

Growth Rate

Credit Growth

Rate

Guntur 8 7 16

Gwalior 8 6 9

Jabalpur 8 3 0

Nellore 8 7 22

Varanasi 8 6 13

Kanpur 7 7 13

Kavaratti 7

Vijayawada 7 7 24

Dhanbad 6 12 15

Kancheepuram 2 16 22

With the exception of Bokaro, and to a certain extent Chandigarh, the 10 fastest growing cities grew

on the back of high credit growth. However, this is not a general rule as a look at the slower growing

cities reveal. Cities such as Vijaywada, Kancheepuram, Nellore and Guntur did not display a robust

growth in spite of high credit growth. Deposit growth, on the other hand is an effect of market growth

and in general grows in the wake of market growth. This is generally borne out by the facts, though a

few notable exceptions exist Thanjavur, Kohima, Bokaro (among the fast growing cities) and

Dhanbad and Kancheepuram (slow growing cities)


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Insights into the Financial landscape of the country

Indian Financial Scape provides insights into the financial landscape of the country. It

presents nearly 250 different variables at district level. The product helps enhance a

professionals understanding of the markets. A few samples of unusual insights are

presented below. There are many more interesting ones available in the product.

Fastest growing districts in terms of Personal Loans (Personal loans, as defined byRBI includes all loans taken by individuals secured and unsecured)Unit %

Year

2001-02 to2007-08

Personal loans- growth rate ofSCB`s credit

State District

Karnataka Bangalore Rural 77

Meghalaya West Garo Hills 74

Arunachal Pradesh Changlang 72Arunachal Pradesh East Siang 72

Arunachal Pradesh Papum Pare 72

Arunachal Pradesh West Kameng 72

Bihar Katihar 72

Uttar Pradesh Sant Kabir Nagar 71

Haryana Jhajjar 70

Assam Hailakandi 69

Gujarat Narmada 69

Haryana Panipat 68

Haryana Rohtak 67

Haryana Sonipat 67

Haryana Faridabad 62

Jammu & Kashmir Pulwama 62

Mizoram Champhai 60

Bihar Araria 57

Chhattisgarh Rajnandgaon 57

Uttar Pradesh Baghpat 56

Arunachal Pradesh is an unusual place. Not much is known about it and it has a small

base. Yet, on a sustained basis, over a 6 year period, four of its districts have figured

among the top 6 districts in India in terms of growth in personal credit. Haryana is

another place which has seen a boom with four of its districts figuring in the top 15.

Fastest growing districts in terms of Professional and other Services credit

Unit % %

Year

2001-02 to2007-08

2001-02 to2007-08

Professional &other Services -growth rate ofSCB`s credit

Personalloans -

growth rate ofSCB`s credit

State District

Gujarat Rajkot 51 26

Chhattisgarh Korba 47 34Punjab Bathinda 47 50


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Andhra Pradesh Krishna 46 18

Rajasthan Ajmer 46 31

Rajasthan Kota 44 25

Madhya Pradesh Katni 44 12

Chhattisgarh Kanker 44 34

Rajasthan Ganganagar 43 31

Sikkim South Sikkim 42 26

Sikkim North Sikkim 42 53

Arunachal Pradesh Lohit 42 -16

Rajasthan Jodhpur 42 36

West Bengal Haora 42 17

Sikkim East Sikkim 42 16

Rajasthan Sikar 41 51

Orissa Sambalpur 41 34

Haryana Rewari 40 -11

Andhra Pradesh Nalgonda 40 21

Haryana Mahendragarh 40 33

The growth in credit in this category has been much lower than in the personal credit

category. The districts that have grown fastest are those that are not in the top pecking

order, yet they are not very small either. Lohit, in Arunachal Pradesh is unusual

because it shows a negative growth in personal credit. Its possible that personal credit

were routed through Professional credit in reality. Rewari is another standout high

growth in Professional combining with a negative growth in personal credit.

Fastest growing districts in terms of Trade Credit

Unit %

Year

2001-02 to2007-08

Trade Credit -growth rate ofSCB`s credit

State District

Tamil nadu Nagapattinam 49

Chhattisgarh Rajnandgaon 47

Meghalaya Jaintia Hills 44

Haryana Jhajjar 40

Karnataka Bangalore Rural 40Uttar Pradesh Mahoba 40

Gujarat Kheda 39

Orissa Ganjam 39

Haryana Gurgaon 38

Himachal Pradesh Kinnaur 38

Uttar PradeshGautam BuddhaNagar 38

Sikkim East Sikkim 37

Jammu & Kashmir Leh (Ladakh) 37

Bihar Madhubani 37

Arunachal Pradesh West Kameng 36

Uttaranchal Rudraprayag 35

West Bengal Medinipur 35


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Most of the major centres are ranked within the top 30%. However, there are widedifferences. The Western region (Mumbai, Ahmadabad, etc.) are clearly the safest. Kolkatastands out with a very poor ranking.


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Demand for HousingThe Housing Skyline of India estimates the demand for housing units in the top 30 cities togrow by 6.36 million units during the next 7 years leading up to 2015. The current stock ofhousing units in these 30 cities is estimated to be 25 million units, which implies a growth inhousing stock of over 25% within 7 years.Demand between 2008 and 2015

Total Demandfor Housing

Demand forPlinth Area Lessthan 500 Sq ft

Demand forPlinth Area

Between 500-1000 Sq ft

Demand forPlinth Area Morethan 1000 Sq ft

Top 10 cities(alpha) 3,548,000 1,212,000

1,151,000

1,186,000

Next 20 cities(beta) 2,815,000 930,000

921,000

965,000

Top 30 cities(alpha + beta) 6,363,000 2,142,000

2,072,000

2,151,000

Current Stock

Current HousingStock

Current Housing

Stock - PlinthArea Less than500 Sq ft

Current Housing

Stock - PlinthArea Between500-1000 Sq ft

Current Housing

Stock - PlinthArea More than1000 Sq ft

Top 10 14,624,000 5,829,0004,337,00

04,458,0

00

Next 20 10,413,000 4,179,0003,145,00

03,089,0

00

Top 30 25,037,000 10,008,000 7,482,000 7,547,000

Whereas most of the attention of the building industry is on the upper segment, it is middleand lower middle India which is driving demand -

The demand for housing of size less than 1000 sq ft is 4.2 million units over 7 years,

which is 2/3rd of the demand

The anticipated growth in percentage terms in the lower segments (24% combined)

is only marginally lower than the upper segment (28.5%)

The pattern is similar for the alpha (top 10) and beta (the next 20) cities, implying a

uniform demand for affordable housing.The above pattern indicates that a renewed focus on affordable housing is in order. There isplenty of demand out there; supply is more likely to be the constraint.Alpha cities are - Hyderabad, Delhi, Ahmadabad, Surat, Bangalore, Mumbai, Pune, Chennai,Coimbatore, KolkataBeta cities are Asansol, Bhopal, Faridabad, Indore, Jaipur, Jamshedpur, Kancheepuram,Kanniyakumari, Kanpur, Kochi, Lucknow, Ludhiana, Madurai, Nagpur, Patna, Salem,Thiruvallur, Urban Areas in North 24 Parganas, Urban Areas in Thane, Vadodara

The estimation process involved the following steps: Demographic parameters such as population across age-groups, change in

household sizes, and family structures were estimated using data from census andvarious large scale data surveys.

This data was used with large scale survey data on housing conditions (NSSO 49 th

and 58th rounds) to establish the relationship between housing demand anddemographic parameters.

Independently the relationship between ownership and income was established.

Estimates of current income and growth from The Market Skyline of India were usedto estimate households across income levels for the two time periods.

One of the major drivers of housing demand is the current and future rental markets.

This in turn is driven by growth in economy, employment and migration trends.Estimates of GDP, employment growth and migration were used from The DistrictLevel GDP 2006-07 to define the relationship with housing demand.


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Another relationship established was the ease and extent of availability of finance and

housing demand. Data from RBI on housing loans for the last ten years were used todetermine the function.

All these aspects were then combined to estimate the net demand in housing during

the period 2008-15. They were also used to determine the demand for housingacross various segments including income categories, plinth area, room size, etc.

The entire exercise was validated at various stages using a primary survey ofhouseholds on income, demography, financial habits and housing conditionsconducted in July 2008. Secondary data such as housing stock estimates from NHB,proposed construction data from various housing boards, etc. were also used to crosscheck estimates at various intermediate steps.


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Financial Asset Penetration

On an average, only 16% of Indian households have taken loans from institutional agencies.On the other hand, 22% of the households have taken loans from non institutional agencies.There are two clear indications here a) the bulk of the population is financially underservedand rely on informal lending and b) the non institutional agencies have together achieved a

much higher penetration than the institutional agencies.If we look at another indicator of financial inclusion, namely percentage of households whohold stocks and debentures, we find that the penetration is just 5%.There is no doubt that financial inclusion is extremely poor and financial institutions need tofocus more on expanding the market rather than flog the existing markets.

Here are the top districts in terms of penetration of institutional loans. These districts havepenetrations ranging from 37% to 68%. As many as 14 of these 20 are from Kerala. Thedistricts are Kottayam, Kannur, Idukki, Ernakulam, Pathanamthitta, Kasaragod, Wayanad,Palakkad, Kollam, Thrissur, Kozhikode, Malappuram, Alappuzha and Thiruvananthapuramfrom Kerala and Mahe, Udupi, Satara, Kolhapur, Wardha, Shajapur (MP).

The bottom twenty districts (all less than 1% penetration) are mainly from the hill districts(Arunachal Pradesh, Manipur, Mehghalaya and J&K - Changlang, East Kameng, Lohit, LowerSubansiri, Tirap, Dhubri, Kupwara, Bishnupur, Chandel, Churachandpur, Senapati,Tamenglong, Thoubal, Ukhrul, East Garo Hills, Jaintia Hills, Ri Bhoi, South Garo Hills, WestGaro Hills

The picture changes substantially when one looks at the penetration of non institutionalloans. The top 24 districts have penetration ranging from 50-53%. These are - Tiruchirappalli,Nagapattinam, Thiruvarur, Thanjavur, Karur, Pudukkottai and Perambalur from Tamil Nadu,Mahe, Karaikal, Pondicherry, Yanam from Pondicherry, and Prakasam, Srikakulam, WestGodavari, Krishna, Nellore, Guntur, Visakhapatnam, Vizianagaram, East Godavari, Chittoor,Cuddapah, Anantapur and Kurnool from Andhra Pradesh indicating a clear geographicpattern.

The bottom districts are again from the hill states. In fact of the bottom 64 (up to 7%penetration) - 2 are from Andaman and Nicobar, 13 are from Arunachal, 14 are from J&K, 7from Meghalaya, 8 from Mizoram, 4 from Sikkim, 13 from Uttaranchal, and 3 from WestBengal.

At a broader level there is a clear need for enhanced services in the hill states. However,even among the relatively well off districts, it is interesting to note that TN and Andhra seemto have a very high penetration of non institutional loans as compared to institutional loans clearly an area for capturing the low hanging fruits for the formal sector.


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Housing Stock and DemandThe Housing Skyline of India estimates the demand for housing units in the top 112 cities tobe 10.5 million units during the next 7 years leading up to 2015. The current stock of housingunits in these cities is estimated to be 41.8 million units, which implies a growth in housingstock of over 25% within 7 years

Of these 112, the top 30 cities will account for 60% of the demand and are expected to add6.36 million units during the next 7. The current stock of housing units in these 30 cities isestimated to be 25 million units.

The top 112 Cities

Figures in

millionsHouseholds with Plinth Area Less than 500 Sq ft 17.0

Households with Plinth Area Between 500-1000 Sq ft 12.5

Households with Plinth Area More than 1000 Sq ft 12.3

Demand for units (2008-2015) for Plinth Area Less than 500 Sq ft 3.5

Demand for units (2008-2015) for Plinth Area Between 500-1000Sq ft 3.4

Demand for units (2008-2015) for Plinth Area More than 1000 Sq ft 3.7

The top 30 CitiesFigures inmillions

Households with Plinth Area Less than 500 Sq ft 10.01

Households with Plinth Area Between 500-1000 Sq ft 7.48Households with Plinth Area More than 1000 Sq ft 7.55

Current stock of houseswith plinth area > 1000 sqfeet (figures in 000s)


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Demand for units (2008-2015) for Plinth Area Less than 500 Sq ft 2.14

Demand for units (2008-2015) for Plinth Area Between 500-1000Sq ft 2.07

Demand for units (2008-2015) for Plinth Area More than 1000 Sq ft 2.15

Whereas most of the attention of the building industry is on the upper segment, it is middle

and lower middle India which is driving demand -

The demand for housing of size less than 1000 sq ft is 6.2 million units over 7 years,

which is 2/3rd of the demand

The anticipated growth in percentage terms in the lower segments (23% combined)

is lower than the upper segment (30%), but on a base which is nearly two and a halftimes.

The pattern is similar for the alpha (top 10) and beta (the next 20) cities, implying a

uniform demand for affordable housing.The above pattern indicates that a renewed focus on affordable housing is in order. There isplenty of demand out there; supply is more likely to be the constraint.


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Demography Age profile of the top 112 cities of India

The age profile of the top 112 cities (which account for a population of 200 million) does notshow too much variation. 69% are between the age of 18 and 60 and the proportions do notvary much across different cities. The proportion of the aged in the larger cities is higher butonly marginally.

In sheer numbers, about 36 million people in the top 112 cities are above 60 years of age andthe alpha cities account for 35% of them. The under 18 population is significantly smaller atabout 26 million

under 18years 18-35 years 35-60 years > 60 years

Alpha (top 10) 12.4% 34.3% 34.7% 18.6%

Beta (11th to 30th) 13.0% 34.7% 34.2% 18.1%

Gamma (31st to50th) 14.1% 35.9% 32.7% 17.3%

Delta (51st to 112th) 14.3% 36.7% 31.6% 17.3%

Total (112 cities) 13.3% 35.3% 33.5% 17.9%

under 18years 18-35 years 35-60 years > 60 years

Alpha (top 10)8,306,88

823,052,69

823,318,89

012,456,12

8

Beta (11th to 30th)6,714,66

117,926,72

317,642,44

89,352,40

0

Gamma (31st to50th)

4,390,776

11,161,258

10,161,636

5,388,436

Delta (51st to 112th)7,211,06

218,473,93

615,894,69

08,708,91

7

Total (112 cities)26,623,38

770,614,61

567,017,66

435,905,88

1

8,306,888 6,714,661 4,390,7767,211,062

23,052,698

17,926,723

11,161,258

18,473,936

23,318,890

17,642,448

10,161,636

15,894,690

12,456,128

9,352,400

5,388,436

8,708,917

Alpha (top 10) Beta (11th to 30th) Gamma (31st to 50th) Delta (51st to 112th)

under 18 years 18-35 years 35-60 years > 60 years


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12.4% 13.0% 14.1% 14.3%

34.3% 34.7%35.9% 36.7%

34.7% 34.2%32.7% 31.6%

18.6% 18.1% 17.3% 17.3%

Alpha (top 10) Beta (11th to 30th) Gamma (31st to 50th) Delta (51st to 112th)

under 18 years 18-35 years 35-60 years > 60 years


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Income and Savings in Urban India

The top 112 cities account for about 200 million Indians which is more than 60% of urban India. Thesecities constitute a market of consumers whose combined annual incomes are Rs 13.26 billion. Theircombined savings are Rs 3.5 billion which is about 26.5% of income. However there is considerableheterogeneity in the income and savings pattern across these cities.If we look at four classes of cities (by size), we get the following picture:

Total Income (Rsbillions)

Total Savings(Rs billions)

Savings/Income Ratio

Alpha (Top 10) 5,912 1,296 21.9%

Beta (11th to 30th) 2,887 931 32.2%

Gamma (31st to 50th) 1,774 519 29.3%

Delta (The balance 62) 2,688 771 28.7%

Top 112 cities 13,261 3,516 26.5%

The large cities have a significantly lower savings rate. The top 10 cities have a savings rate of under22%, whereas the gamma and delta cities (82 in number) have savings rate around 29%. Clearly theEMI culture hasnt percolated down to too many cities in India. An interesting piece of statistics is thatthe 2nd rung of cities are the biggest savers the beta cities save as much as 32% of their income andreinforce the old adage that savings and investment are the route to growth.

If we look at the same set of data through the regional prism, we get the following picture:




East 2,011 522 25.9%

West 5,167 1,191 23.0%

North 2,849 797 28.0%

South 3,233 1,007 31.1%

The Southerners are by far the largest savers with a savings rate of over 31%. The West (it includesRajasthan and MP) has the lowest savings rate of just 23%. Within West, Gujarat is a high saver with27% savings rate whereas Maharashtra saves only 18%. Madhya Pradesh is a very high saver withsavings rate of 38%.Contrary to popular wisdom, the North is not exactly spendthrift, they are second only to the South insavings rate.

What do the figures look like for some of the major cities?




Mumbai 1,608 216 13.4%

Delhi 1,264 289 22.8%

Bangalore 602 192 31.9%

Urban Areas in Thane 569 132 23.2%

Pune 446 111 24.9%

Ahmadabad 429 109 25.3%

Chennai 393 88 22.2%

Kolkata 350 68 19.3%

Surat 318 82 25.8%

Hyderabad 295 87 29.3%

Mumbai has the lowest savings rate. Delhi, Kolkata and Mumbais neighbours are also low savers.Bangalore and Hyderabad are high savers, much higher than average.The heterogeneity of India is well reflected in the savings patterns. There are no clear regional patterns.However, it is evident that the economically vibrant cities are lower in savings rate as compared to theirregional brethrens which reinforces the theory that consumerism is one of the key pivots of the recentsurge in economic growth and erosion in consumer confidence will impact economic growth negatively.

facets of indian consumers 3

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