HSUI Report Final - Naredco

CONTACT:

Director (NBO) & OSD (JNNURM & RAY)Ministry of Housing & Urban Poverty AlleviationGovernment of India210-G Wing, NBO BuildingNirman Bhavan, New Delhi 110108Tel: +91 11 23061602Fax: +91 11 23061542E-Mail: [email protected]

http://www.nbo.nic.in

HSUIHSUI

Trend in newly constructed residential housesduring 2009 -2011 in 27 cities across India

Pilot Housing Start Up Index

National Buildings OrganisationMinistry of Housing and Urban Poverty Alleviation

Government of IndiaNew Delhi

Reserve Bank of IndiaMumbai

A joint initiative by:




PILOT HOUSING START UP INDEXTrend in newly constructed residential houses during 2009-2011

in 27 cities across India


lR;eso t;rslR;eso t;rs

MESSAGE

I am happy to note that the National Buildings Organisation, the integral arm of the Ministry of Housing and Urban Poverty Alleviation, and the Reserve Bank of India, has taken up this important task of developing the Housing Start Up Index (HSUI). Housing starts have strong forward and backward linkages with various ancillary industries and hence making the HSUI, a leading indicator of the National Economy itself.

National Buildings Organization and the Reserve Bank of India, is releasing the results of the Pilot Index, in this publication with the objective of testing the robustness of the methodology of this index, through wider public debate and I applaud them for their efforts. It is indeed a matter of pride that such an index is being developed for the first time in the country.

I express my compliments to Director (NBO) and his team for their pioneering efforts. I also thank the Reserve Bank of India, for their support since the inception of this index and look forward to their continued support, to ensure the stability and sustainability of this index. I would also like to thank the members of the Technical Advisory Group, without whose support, we would not have been able to formulate this index.

I hope this Pilot Index would generate wider public debate on the robustness of the methodology and would prove a useful tool for all stakeholders.

(Dr Girija Vyas)

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Pilot Housing Start Up IndexlR;eso t;rslR;eso t;rs

CONTENTS Page No

Section-1 Introduction 1

Section-2 Technical Advisory Group (TAG) on HSUI 1

2.1 Methodology suggested by TAG for compilation of HSUI 2

2.2 Action taken for implementing recommendations of TAG on HSUI

4

Section-3 Data Coverage, House Starts and Pilot HSUI 4

3.1 NBO’s contribution in executing the project for compilation of Pilot HSUI

4

3.2 Permit data of 27 Cities 5

3.3 Sample adequacy and Survey of sample permit data for 27 Cities for the years 2009 and 2010

6

3.4 Housing Start rate coefficient matrix for SHU and MHU 6

3.5 House Starts for 27 cites 7

3.6 Region / Centre-wise house starts 7

3.7 Pilot HSUI based on 27 cities for 12 quarters for a period2009- 2011

7

Section-4 Limitations and Scope for further work 8

Table-1 Data receipt position of 27 cities 10

Table-2 City-wise quarterly total permits issued (MHU and SHU) 11

Table-3 Percentage share of permits issued for MHU in the total permits issued

13

Table-4 City wise quarterly house starts 15

Table-5 Region / Centre-wisehouse starts 16

Table-6 House starts of 27 cities and quarterly Pilot HSUI 17

National Buildings OrganisationlR;eso t;rslR;eso t;rs

Annex-1 List of 66 permit issuing authorities in 27 cities in 15 states 19

Annex-II Methodology for calculating sampling error and minimum sam-ple size

22

Annex-IIIA Sampling error and minimum sample size required for survey

data of 2009 at 95% confidence interval

24

Annex-IIIB Sampling error and minimum sample size required for survey

data of 2010 at 95% confidence interval

26

Annex-IV Methodology for computation of coefficient matrix, house starts

and Pilot HSUI

27

Annex-V Housing Start rate coefficient matrix for SHU: 2009 & 2010

Combined

30

Annex-VI Housing Start rate coefficient matrix for MHU: 2009 & 2010

Combined

35

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Section- 1: Introduction

1.1. Housing Starts (i.e., new dwelling units for which construction has begun in a given period) is considered as leadingindicator of economic activity, given its forward and backward linkages with other sectors of economy. An increase in the number of houses beginning construction, measured through Housing Starts Up Index (HSUI) would be indicative of an increase in investment, business and consumer optimism and vice versa. Progress in housing starts reflect the demand for houses and hence positive signal for the construction industry. Sustained rise in housing starts has spillovers to other sectors due to the multiplier effect, augmenting economic growth. On the other hand, its moderation indicates lower levels of activity, and has adverse spillover costs on the economy.

1.2. Increase in housing starts generally impacts home sale, both through credit market conditions and through wealth effect, whereas its slowdown generally reflects moderation in demand conditions with financial and household sectors reacting differently. Housing starts can also reflect persistence of macro-economic policy shocks such as, terms of finance for investors leading to property market imbalances and their consequential impact on other segments of asset markets. As such it contains useful information for different economic agents such as, home-buyers, material suppliers, bankers, investors and macr-oeconomic analysts. Further the input prices and wages in this sector are very sensitive to industry trends.

Section-2: Technical Advisory Group (TAG) on HSUI

Recognizing the significant multiplier effect of the housing sector, RBI initiated the task for development of Housing Start Up Index (HSUI) for India by constituting a Technical Advisory Group (TAG) on HSUI under the Chairmanship of Prof. Amitabh Kundu, Jawaharlal Nehru University (JNU), New Delhi. Other members were from Central Statistical Organization (CSO),National Sample Survey Organization (NSSO),National Housing Bank (NHB),National Buildings Organization (NBO), Housing and Urban Development Corporation (HUDCO), State Bank of India (SBI), Directorate of Economics and Statistics (DES) of four states and Prof. Abhay Pethe, Mumbai University. The TAG was entrusted with the responsibility of providing the approach to generate a data base and suggest a feasible methodological framework for development of HSUI for the Indian economy and institutional arrangement for regular compilation of HSUI. The TAG submitted its report to Dr. Rakesh Mohan, the then Deputy

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Governor, Reserve Bank of India in the presence of Ms. Kiran Dhingra, Secretary, Ministry of Housing and Urban Poverty Alleviation on March 3, 2009. The Report was placed on the websites of RBI and NBO and also published as a supplement to the June 2009 issue of the Reserve Bank of India Bulletin for wider dissemination.

2.1 Methodology suggested by TAG for compilation of HSUI

2.1.1 In order to initiate the process of compilation of Housing Start-Up Index for India, the TAG deliberated on international practices. It noted that countries like Canada, United States, Japan, France, Australia, and New Zealand are compiling data related to building permits/housing starts on a regular basis and most of these countries use housing permits data, collected either through census or sampling method, to compile housing starts.

2.1.2 TAG also deliberated on various issues regarding the development of a sound and reliable HSUI. Since considerable information on house construction is available from permit issuing authorities in India, TAG proposed that permit data may be used for HSUI compilation. The permit issuing authorities in India vary depending on the nature of settlement. They mainly include Municipal Corporations, Town Planning Authorities, Tahsildaars(Nagar Parishad / Palika) and Gram Panchayats.

2.1.3 In its report, TAG made the following proposals for compilation of HSUI for India:

i. The objective of HSUI compilation is to measure the change in the level of activities in the housing sector and to identify the growth/recessionary tendencies in this sector and related sectors of the economy.

ii. The scope of HSUI would be limited to new private and public built residential units in India, whose construction is authorized through issuance of building permits.

iii. HSUI may be compiled on a quarterly basis.

iv. After reviewing the international practices on compilation of Housing starts based on the sample/census survey on quarterly/monthly basis in most of the countries, TAG felt that in the Indian context, conducting quarterly sample survey of permits issued in major cities representing all India level new residential construction activities is a massive job. Hence it may not be easy to compile quarterly HSUI a in timely manner and loses its relevance as a leading indicator. TAG, therefore, recommended the compilation

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of HSUI based on Housing start coefficient1 matrices. The field survey can be conducted once in three years to estimate the starts coefficient matrices for each of the centers.

v. TAG observed that NBO has already has a system under which permit data are collected on annual basis from all the Class I and II towns and 10 per cent of the Class III to VI towns are selected at random and it is therefore recommended that the present system of data collection, as reported by NBO along with its formats should be fine-tuned to obtain the requisite data on building permits on a quarterly basis. This would constitute the basic information for HSUI compilation.

vi. The field survey for estimating the start coefficient matrices may be done in two phases. In the first phase, the complete data base on building permits may be collected in the selected centers. The reference year for this survey would have to be three to four years before the date of conducting the sample survey on the Housing Starts. The sample survey is to be conducted in the second phase to determine the percentage distribution of the housing starts over the eight quarters (after the issuance of the permit, including the quarter of issuing) and thereafter and build start rate matrices in each of the centers. These start rate (coefficient) matrices can be used to obtain the housing starts for the selected Metros and Class I towns for which the regular data on building permits can be obtained without any difficulty on quarterly basis. The number of houses started in a particular center for a particular quarter can be obtained by multiplying the start rates coefficients with the corresponding number of permits issued in that quarter and preceding quarters. The field survey can be conducted once in three years to estimate the starts coefficient matrices for each of the centers.

vii. NBO, Ministry of Housing & Urban Poverty Alleviation, Government of India, will collect the data on building permits issued for the new residential buildings in various centers (metros and class I cities at the first stage) across the country on a quarterly basis under the overall guidance of the Standing Advisory Committee(SAC) to be constituted by NBO.

1The house starts in a particular quarter can be estimated from the permits issued in that quarter and the various past quarters by using the rates at which the permits have got converted into starts in the recent past. It would therefore be important to construct a series of start rates (coefficients) for the permits given during the preceding quarters based on the information on actual starts after the issuance of the permits. These coefficients are expected to be different for different quarters due to the seasonality involved in the housing starts. The detailed methodology for compiling start matrix is given in TAG’s Report.

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viii. RBI will coordinate with NSSO and NBO for conducting the sample survey to determine housing starts coefficients every three years, based on which start rate matrices can be constructed for compilation of the HSUI. All technical aspects for conducting survey, compilation of House start matrix and compilation of HSUI may be done under the overall guidance of the Standing Technical Committee (STC) to be constituted by RBI.

2.2 Action taken for implementing recommendations of TAG on HSUI

2.2.1 Standing Advisory Committee (SAC) on HSUI was formed at NBO to guide and oversee the entire process of compilation of housing permit data from concerned local bodies and the DES of State governments, under the chairmanship of Prof. Amitabh Kundu. RBI is also represented in the SAC.

2.2.2 RBI constituted a Standing Technical Committee (STC) under the Chairmanship of Professor Amitabh Kundu and representatives from CSO, NBO, NHB, NSSO, DES-Tamilnadu, Maharashtra, Delhi, West Bengal and Credit Rating Information Services of India (CRISIL) as members.

2.2.3 31 cities (Table-1:col 1 and 2) representing all regions of India were selected for conducting survey and compilation of HSUI by STC. RBI also selected an agency through open tendering for conducting the survey in selected cities. The survey details provide input to construct the House Starts coefficients for compiling HSUI based on the quarterly flow of permit data for all selected cities from NBO.

Section-3:Data Coverage, House Starts and Pilot HSUI

3.1 NBO’s contribution in executing the project for compilation of Pilot HSUI

3.1.1 With the primary responsibility of collecting permit data from all permit issuing authorities in selected cities, NBO has contributed extensively for bringing the project to the present level. NBO initiated various measures which includes i) selection of an outside agency, which is entrusted with the task of a) collection and validation of the permit data from municipal bodies, and b) selection of 10 per cent sample of permit data and conducting the sample survey for generating house start-up coefficients in 27 cities, ii) setting up HSUI cell in 27 cities to deal with the data related problems for generating HSUI, iii) appointment of nodal officers in various States iv) training and capacity building of the concerned

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officials, and iv) preparing a roadmap by setting deadlines for collection of permit data and completion of sample surveys in selected cities.

3.1.2 NBO approached 66 permit issuing authorities in 27 cities in 15 states as listed in Annex-I through outsourced agency and collected permits data for 20 quarters of calendar year 2007 to 2011. All permit data are validated manually with these 66 authorities in the absence of computerized system for issue of permits in each of the authorities.

3.1.3 The sample survey of 10 per cent of total permit data was carried out in 27 cities for 2009 and 2010 by NBO in consultation with RBI following the sampling methodology recommended by the TAG for determining the coefficients of Housing Starts.

3. 2 Permit data of 27 Cities

3.2.1 Permit data of 27 cities was collected by NBO for the period January 2007 to December 2011. Out of these, 21 cities are from the list of 31 cities identified by STC (Table-1).Though Delhi was selected by STC, permit data for same is not available. Hence surrounding cities like Ghaziabad, Agra for which data is available was considered for compilation of pilot HSUI.

3.2.2 Of the total permits issued during 2007 to 2011, it is observed that the majority (about 80 per cent) of the permits issued are for Multiple Housing Units (MHU) for 9 cities viz. Ahmedabad, Chennai, Chandigarh, Faridabad, Guwahati, Kolkata, Pondicherry, Visakhapatnam (Vizag) and Ghaziabad. While for Coimbatore, Sangli, Bangalore, Lucknow, Agra, Kharagpur, Surat, Jodhpur, Bhopal, and Bhilai permits issued are more for Single Housing Units (SHU). For the remaining cities no specific pattern was observed for the period 2007 to 2011.

3.2.3 In Allahabad majority of the permits during 2007 to 2008 was for MHU but after 2008 tendency was changed to SHU and remain same till December 2011.In Hubli, mix scenario was observed for 2007 and 2010 though most of the permit issued was for MHU during 2008 and 2009.

3.2.4 In Mysore no specific pattern was observed for 2007 and 2008 permit data but during 2009 and 2010 most of the permits issued was for MHU and in 2011 majority of the permits issued was SHU.

3.2.5 In Indore most of the permits issued was for SHU during 2007 to 2009, but after 2009

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tendency was changed. During 2010 to 2011 most of the permits issued was for MHU. While in Jamnagar scenario was just opposite of Indore, i.e. during 2007 to 2009 most of the permits issued was for MHU and during 2010 and 2011 most of the permit data was for SHU.

3.2.6 In Jaipur most of the permits issued was MHU during 2007 to 2010 but in 2011 most of the permit issued was for SHU except Q3 of 2011.

3.2.7 City-wise quarterly total permits issued(MHU and SHU) and percentage share for MHU thereof are given in Table-2 and Table-3 respectively.

3.3 Sample adequacy and Survey of sample permit data for 27 Cities for the year 2009 and 2010

The survey data scrutiny, validation and compilation of pilot HSUI for 27 cities has been carried out by RBI and validated by STC. The sample adequacy test was performed on the sample selected and surveyed by NBO and found adequate in most of the cities. The methodology for calculating sampling error and minimum sample size is given in Annex-II. The Sampling error of survey data of 2009 and 2010 at 95% confidence interval is calculated and placed in Annex-IIIA and IIIB respectively. It is observed that sampling error is in the range of 0 to 5 per cent. From the survey results it was observed that for permits issued during each quarter of 2009 and 2010, about 3 and 4 per cent constructions started prior to permits issued in all cities respectively.Insuch cases, for compiling house starts coefficient, the period for house starts in the quarter during which permits were issued was considered.The survey results are used to compile the housing start rate coefficient matrices for SHU and MHU separately in each of the 27 cities.

3.4 Housing Start rate coefficient matrix for SHU and MHU

The Housing Start matrices for 2009 and 2010 were computed based on the survey data as per the methodology given in Annex-IV. The absolute difference between the coefficients of matrices for 2009 and 2010 was calculated for the MHU and SHU for 27 cities separately. The standard errors of these differences derived and the statistical significance in the difference was tested using the asymptotic test of equality of proportions. Given the fact that the coefficients for the two years are not at variance with each other, coefficients are combined by taking weighted average of each coefficient. The number of housing units for which permits are

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issued in the corresponding quarter is used as the weight. The start rate matrices obtained by combining the matrices for 2009 and 2010 for SHU and MHU are given in Annex-V and VIrespectively.

From these matrices it is observed that in most of the cities maximum percentage of permit’s construction starts from the same quarter and previous 4 quarters. However, in few small cities some pattern in realisation of permits in four quarters are observed and example of such cities are given below.

Maximum number of permits starts in Hubli in Q3 and Q4 for SHU and MHU.

No permits start in Q3 in Jaipur for SHU and less for MHU.

Fewer permits start in different quarters in Guwahati for SHU.

In Dehradun most of the coefficients are zero due to less MHU permit issued in the hilly region.

3.5 House Starts for 27 cites

Using these combined Start Rate Matrices for SHU and MHU, quarter wise house starts are estimated for 12 quarters (Q1:2009 to Q4: 2011). City-wise house starts are given in Table-4.It is observed that more construction activities have been happening in Kolkata, Chennai, Vishakhapatnam, Bangalore, Pondicherry, Guwahati, Ahmedabad and Nagpur during Q1:2009 to Q4:2011. Recently construction activities increased robustly in Jaipur, Bhopal and Jamnagar. However construction activities declined in Bangalore, Surat, Bhilai and Mysore in Q4:2011. Since this movement is based on house starts estimated using start rate matrices, it indicates the trend.

3. 6 Region / Centre-wise house starts

House starts in four regions i.e., eastern, western, northern and southern were computed based on house starts of 27 cities (Table-5). The eastern region covers 4 cities, western region 7 cities, northern region 9 cities western region 7 cities and southern region cities (Map-1). It was observed that the housing units started (in %) in southern region was high in 2009 but recently in western region, percentage of housing unit start has grown

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3. 7 Pilot HSUI based on 27 cities for 12 quarters for a period 2009-2011

Pilot HSUI have been compiled for 12 quarters of 2009 to 2012 based on house starts of 27 cites, as per the methodology recommended by TAG. The total house starts and pilot HSUI is given in Table-6.The graphical presentation of same is given in Chart-1. From the movement of pilot HSUI, it is observed that less construction activities were happening during Q1:2009 to Q3:2010, which was in line with low GDP growth during the same period.

Chart 1: Quarterly Housing Start Up index and house starts based on 27 cites permit data

Section-4: Limitations and Scope for further work

4.1 This report has been prepared as a piece of exploratory research with the key objective of generating discussion on the methodology and data base.

4.2 Compilation of housing starts statistics in India is a challenge due to the presence of multiple authorities at various levels following different procedures for issuing housing permits. Unlike advanced economies, prescribing a uniform reporting system for capturing regular census data for the basic housing permits/starts on census basis is not feasible in the current stage of diverse administrative arrangements across different regions / levels. Accordingly, the present approach has been to make a beginning in this area by collecting basic data on permits in select cities and ascertain the distribution of housing starts from permit date, based on surveys. This approach is novel and provides some leads on this critical sector, but the associated caveats are important in this context.

4.3 The movement of house starts and pilot HSUI in the present exercise is indicative as they are estimated using start rate coefficients compiled through survey of permit issued in 2009 and 2010.

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4.3 The aggregate-level pilot HSUI has been compiled for 27 cities presently and for a large and diverse country like ours, more cities (including remaining 10 cities selected by STC) need to be covered for having an all-India representative HSUI.

4.4 A substantial number of residential constructions take place under slum development which is not considered in the present pilot HSUI. Thus besides, Municipal Corporations, Town Planning Authorities etc, Slum Boards in selected cities may be considered for inclusion.

4.5 The pilot HSUI is complied for a period upto quarter ended December 2011 for this exercise. The regular data-flow arrangements need to be put in place for reducing the associated time-lag and ensuring regular compilation of HSUI within a month of every quarter-end with the combined efforts and co-operation of permit authorities, NBO and RBI.

4.6 For this exercise, permit data have been collected and verified manually from Permit-issuing authorities in each city, for compilation of pilot HSUI. The manual system of permit data preservation proves a hurdle for regular and timely flow of permit data collection and its validation. All efforts need to be put to computerize all permit issuing authorities and capacity building with skilled manpower in the concerned organization for this purpose so that regular flow of permit data in electronic form is ensured within the stipulated time-frame.

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Table 1: Data receipt position of 27 cities

21 cities selected by STC where complete data

was received

10 Cities selected by STC, where complete data not received so

far

Other 6 cities not selected by STC but data were ob-

tained

(1) (2) (3)1. Allahabad

2. Kolkata

3. Lucknow

4. Sangli

5. Visakhapatnam

6. Ahmedabad

7. Bangalore

8. Bhopal

9. Chandigarh

10. Chennai

11. Coimbatore

12. Faridabad

13. Hubli

14. Indore

15. Jaipur

16. Jamnagar

17. Jodhpur

18. Kharagpur

19. Guwahati

20. Dehradun

21. Bhilai

1. Amritsar

2. Delhi

3. Jammu

4. Hyderabad

5. Cochin

6. Bhubaneswar

7. Gangtok

8. Patna

9. Raipur

10. Mumbai

1. Agra

2. Ghaziabad

3. Pondicherry

4. Mysore

5. Surat

6. Nagpur

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Table-2: City-wise quarterly total permit issued(MHU and SHU)

Quarter

Kolka

ta

Chen

nai

Ahme

daba

d

Farid

abad

Coim

bator

e

Ghaz

iabad

Hubli

Viza

g

Sang

li

Bang

alore

Luck

now

Allah

abad

Agra

Bhop

al

2007-Q1 611 678 426 725 563 415 278 503 77 2723 241 43 226 902

2007-Q2 804 1440 255 727 646 427 383 751 74 3215 282 21 232 779

2007-Q3 522 1217 144 226 452 378 368 392 85 2869 146 29 197 504

2007-Q4 649 1107 208 205 408 313 292 511 99 3396 139 35 152 747

2008-Q1 872 1321 168 337 571 367 310 613 80 4232 106 67 214 768

2008-Q2 921 1372 239 398 421 472 325 533 80 2204 94 68 173 683

2008-Q3 920 1211 240 348 519 517 276 557 99 2402 107 81 190 595

2008-Q4 720 1302 97 225 452 336 347 643 92 2212 125 104 335 544

2009-Q1 1049 1363 198 279 598 335 240 720 146 2738 162 128 358 936

2009-Q2 836 995 193 252 598 342 401 756 132 2470 458 126 196 849

2009-Q3 1035 861 282 208 491 300 123 526 83 2395 376 146 293 562

2009-Q4 841 880 242 236 362 286 126 756 81 2287 269 155 215 825

2010-Q1 1987 682 222 348 275 224 528 661 190 2933 541 117 318 1355

2010-Q2 1057 1114 443 433 425 385 584 628 208 1758 464 178 338 1083

2010-Q3 903 1358 435 632 531 584 869 735 204 1834 545 178 318 1081

2010-Q4 955 1150 483 807 713 400 921 845 115 1529 534 151 285 939

2011-Q1 851 1204 432 331 334 530 697 754 192 2296 566 147 363 939

2011-Q2 863 814 690 430 403 522 206 547 184 1152 553 151 354 782

2011-Q3 799 895 573 108 2 456 285 659 154 147 355 131 256 788

2011-Q4 682 770 507 313 0 450 583 894 174 95 431 123 314 818

Contd.

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Table-2: City-wise quarterly total permit issued (MHU and SHU)

Quarter

Cha

ndig

arh

Jodh

pur

Kha

ragp

ur

Guw

ahat

i

Deh

radu

n

Bhila

i

Pond

iche

rry

Mys

ore

Nag

pur

Jaip

ur

Sura

t

Jam

naga

r

Indo

re

2007-Q1 5 46 138 175 311 77 525 2 303 27 146 535 743

2007-Q2 18 32 105 405 642 429 451 5 376 16 124 429 531

2007-Q3 42 37 86 298 478 234 474 3 352 15 103 309 496

2007-Q4 37 84 93 392 308 292 406 116 408 19 131 526 587

2008-Q1 67 71 137 353 407 336 396 261 398 23 104 273 659

2008-Q2 52 44 119 554 507 342 610 320 441 18 114 489 527

2008-Q3 76 80 121 566 397 290 540 402 397 21 143 312 590

2008-Q4 67 94 123 508 535 59 470 516 591 8 132 316 610

2009-Q1 65 296 189 629 685 550 257 784 775 12 70 188 761

2009-Q2 106 353 153 585 730 90 594 776 696 15 54 359 579

2009-Q3 129 349 131 561 552 266 523 740 666 13 95 343 721

2009-Q4 137 314 142 540 610 322 422 777 665 14 157 325 298

2010-Q1 127 263 111 545 650 221 458 770 659 23 79 428 1323

2010-Q2 138 248 184 563 593 325 591 1062 1045 33 67 309 1027

2010-Q3 153 380 148 586 559 324 646 991 913 34 102 238 964

2010-Q4 138 275 132 480 565 249 617 900 903 30 123 279 965

2011-Q1 170 419 138 560 612 385 483 1120 1325 22 231 171 374

2011-Q2 178 606 65 389 454 472 540 873 868 37 222 191 923

2011-Q3 185 513 148 320 554 212 468 913 697 33 168 379 1121

2011-Q4 174 349 116 505 580 77 365 917 622 4 178 1288 797

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Table-3: Percentage share of permit issued for MHU in total permits

Quarter

Kol

kata

Che

nnai

Ahm

edab

ad

Fari

daba

d

Coi

mba

tore

Gha

ziab

ad

Hub

li

Viza

g

Sang

li

Bang

alor

e

Luck

now

Alla

haba

d

Agr

a

Bhop

al

2007-Q1 93.29 91.89 82.16 30.76 2.66 80.96 42.45 75.55 10.39 33.90 36.93 83.72 57.52 35.40

2007-Q2 89.80 90.97 90.20 55.30 2.48 87.59 44.13 76.30 12.16 38.01 30.85 95.24 48.71 30.00

2007-Q3 90.04 87.26 89.58 80.53 2.88 87.30 60.05 77.30 15.29 39.04 36.30 75.86 66.50 35.70

2007-Q4 89.21 88.62 94.71 88.29 2.21 85.30 59.93 73.58 15.15 37.60 40.29 77.14 38.82 19.00

2008-Q1 89.68 86.90 61.31 80.71 0.35 92.92 52.26 80.42 11.25 34.00 43.40 59.70 22.43 27.60

2008-Q2 91.31 87.10 72.80 86.18 1.19 96.61 61.23 78.80 11.25 30.81 34.04 57.35 27.75 29.30

2008-Q3 90.11 84.31 74.27 81.61 1.54 93.42 65.58 84.20 23.23 30.35 38.32 50.62 18.42 33.40

2008-Q4 87.64 82.87 65.85 88.00 2.21 89.29 57.06 82.27 14.13 29.93 49.60 39.42 13.13 39.70

2009-Q1 84.08 84.23 93.43 86.74 1.84 81.19 60.83 77.78 22.60 42.51 40.12 36.72 13.69 15.60

2009-Q2 83.49 80.00 91.71 83.33 0.50 83.04 65.09 76.72 17.42 34.70 34.50 30.95 15.82 7.90

2009-Q3 86.28 81.30 91.49 90.87 1.43 84.00 65.04 77.57 25.30 33.24 30.59 33.56 10.58 15.70

2009-Q4 88.47 80.34 89.67 90.25 3.31 88.81 69.05 76.19 27.16 20.11 26.02 29.03 5.12 18.90

2010-Q1 87.12 84.16 92.34 93.97 4.36 83.48 35.80 78.37 23.68 13.98 28.10 32.48 8.18 23.20

2010-Q2 86.57 87.97 76.75 92.15 4.71 88.05 30.65 73.25 25.48 35.32 39.66 41.01 11.83 88.40

2010-Q3 87.04 89.91 69.89 89.08 3.39 77.23 65.25 74.15 35.78 36.91 38.90 37.64 12.89 90.40

2010-Q4 87.54 87.39 76.60 82.78 5.89 86.50 59.93 76.80 30.43 37.15 32.02 37.09 8.42 90.80

2011-Q1 87.31 85.60 89.80 87.01 14.97 86.98 62.27 85.01 33.33 29.22 30.04 39.46 19.83 96.80

2011-Q2 91.77 100.0 82.46 83.95 11.66 87.36 55.83 80.44 29.89 40.28 34.00 39.07 18.08 33.60

2011-Q3 91.24 100.0 84.64 62.04 0.00 86.18 97.54 74.05 35.06 17.69 31.27 29.77 17.19 33.10

2011-Q4 88.56 100.0 79.29 85.62 0.00 83.33 45.11 74.05 29.89 3.16 31.79 44.72 19.75 34.00

Contd.

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Table-3: Percentage share of permit issued for MHU in total permits

Quarter

Cha

ndig

arh

Jodh

pur

Kha

ragp

ur

Guw

ahat

i

Deh

radu

n

Bhila

i

Pond

iche

rry

Mys

ore

Nag

pur

Jaip

ur

Sura

t

Jam

naga

r

Indo

re

2007-Q1 80.00 50.00 26.09 88.00 0.00 42.86 69.14 100.00 29.37 100.00 53.42 63.36 11.71

2007-Q2 100.00 34.38 26.67 79.51 0.31 32.63 66.96 40.00 27.93 62.50 19.35 57.81 14.50

2007-Q3 95.24 43.24 12.79 79.87 0.21 38.03 71.94 0.00 26.70 80.00 16.50 48.54 16.13

2007-Q4 100.00 51.19 27.96 79.08 0.32 36.30 78.82 50.86 19.85 84.21 32.06 63.69 16.18

2008-Q1 92.54 59.15 35.04 75.07 0.00 31.85 85.10 61.69 20.85 86.96 22.12 65.20 15.17

2008-Q2 90.38 47.73 39.50 82.31 0.00 42.11 73.11 57.19 17.91 72.22 38.60 76.89 16.51

2008-Q3 86.84 57.50 36.36 82.69 0.25 35.86 73.15 55.22 15.62 71.43 38.46 77.88 23.90

2008-Q4 80.60 40.43 52.85 81.30 0.00 38.98 75.74 44.38 11.68 100.00 50.00 81.33 22.46

2009-Q1 87.69 22.97 53.44 82.67 0.15 32.36 60.31 52.04 11.23 50.00 12.86 76.60 25.10

2009-Q2 85.85 16.71 43.79 83.25 0.27 35.56 75.42 61.21 14.37 93.33 14.81 61.84 26.77

2009-Q3 93.02 20.92 36.64 83.96 0.00 30.08 84.89 55.14 13.06 92.31 18.95 81.92 26.63

2009-Q4 94.89 13.38 34.51 82.78 0.00 31.99 75.36 57.27 13.83 71.43 32.48 74.15 43.29

2010-Q1 98.43 7.98 29.73 82.94 0.62 44.34 83.19 62.73 24.58 47.83 46.84 6.07 89.72

2010-Q2 95.65 3.23 26.09 80.99 0.67 48.62 67.85 50.38 21.15 54.55 73.13 2.27 89.68

2010-Q3 96.08 5.53 35.81 81.74 0.18 47.53 73.53 50.66 19.28 70.59 47.06 5.04 89.00

2010-Q4 98.55 4.36 35.61 82.29 0.35 48.59 71.96 54.67 21.71 60.00 33.33 13.98 85.60

2011-Q1 99.41 4.77 12.32 85.71 0.16 24.42 85.71 42.50 20.83 45.45 31.60 0.58 85.29

2011-Q2 96.63 5.78 60.00 80.21 0.22 21.19 54.44 33.56 20.39 45.95 32.88 1.57 87.22

2011-Q3 96.76 7.21 76.35 85.31 0.54 34.91 91.45 30.23 13.92 90.91 28.57 1.06 81.80

2011-Q4 99.43 9.46 77.59 82.57 0.17 29.87 95.34 39.37 6.43 25.00 46.63 0.08 85.70

Note: City wise quarterly Single Housing Unit (SHU) permit issued (in %) = 100 - City wise quarterly MHU permit issued (in %)

15


Table-4: City-wise quarterly estimated house starts

Cities Q1-

2009

Q2-

2009

Q3-

2009

Q4-

2009

Q1-

2010

Q2-

2010

Q3-

2010

Q4-

2010

Q1-

2011

Q2-

2011

Q3-

2011

Q4-

2011

Kolkata 3623 3457 3096 4088 6205 7760 4947 4453 6736 4265 4490 4857

Chennai 3732 3180 2807 3091 4278 3123 3134 3496 4515 3635 2758 2946

Ahmedabad 969 2253 1671 3246 6872 7337 7015 7848 7654 13414 12232 12831

Faridabad 381 540 403 382 391 717 835 1147 1091 801 591 346

Coimbatore 518 555 633 554 533 606 815 864 798 1406 551 273

Ghaziabad 658 514 572 900 2134 633 699 900 998 1242 926 1614

Hubli 141 212 618 523 127 269 1311 1818 389 532 1046 1096

Vizag 1765 2072 2464 1838 1754 1881 1762 2043 3417 3001 2781 2883

Sangli 172 194 131 130 231 348 556 364 264 458 571 454

Bangalore 3076 3461 3810 6889 5421 4454 4647 9215 4407 6101 3501 1160

Lucknow 156 205 310 478 451 390 383 825 654 457 406 676

Allahabad 76 133 110 167 169 238 156 177 333 266 166 157

Agra 228 207 202 228 187 221 251 286 303 331 582 503

Chandigarh 121 129 172 323 231 213 238 391 284 269 291 488

Jaipur 623 467 740 1461 859 932 173 999 389 1363 1008 1202

Jodhpur 94 243 263 296 256 236 250 261 259 346 377 381

Kharagpur 203 181 203 207 218 137 223 244 230 125 217 240

Bhopal 686 642 857 1200 852 1424 1806 2206 1589 2892 2657 4488

Indore 430 951 1182 778 539 2287 2855 1805 784 2584 3575 3428

Jamnagar 364 477 1246 1177 718 469 613 987 219 174 381 1390

Pondicherry 2197 623 878 969 788 935 1106 1329 1004 1312 1079 1359

Surat 748 1490 923 3267 4740 6948 7754 2423 2571 3055 7208 2782

Dehradun 382 534 469 648 537 552 468 667 597 514 426 654

Bhilai 329 286 363 456 478 384 548 520 796 528 688 393

Guwahati 2489 1632 1356 1874 3304 1725 1448 1808 5379 2473 1758 2509

Mysore 299 508 2012 1227 603 818 2062 1481 740 982 1908 1320

Nagpur 1074 1646 795 1239 1530 1723 1957 5146 2855 3200 1590 2342Total Housing Unit Starts 25703 26853 28305 37638 44406 46759 48013 53706 49244 55725 53765 52768

16


Table 5: Region / Centre-wise house starts

Quarter House starts-

Northern region

House starts-

Southern region

House starts-

Eastern region

House starts-

Western region

House starts-

Northern region

(%)

House starts-

Southern region

(%)

House starts-

Eastern region

(%)

House –starts

Western region

(%)

Q1-2009 2719 11728 6644 4442 11 46 26 17

Q2-2009 2973 10609 5556 7653 11 40 21 29

Q3-2009 3242 13222 5019 6805 11 47 18 24

Q4-2009 4883 15090 6624 11038 13 40 18 29

Q1-2010 5215 13505 10206 15483 12 30 23 35

Q2-2010 4132 12087 10005 20535 9 26 21 44

Q3-2010 3454 14837 7167 22556 7 31 15 47

Q4-2010 5654 20246 7026 20780 11 38 13 39

Q1-2011 4909 15269 13141 15936 10 31 27 32

Q2-2011 5588 16971 7391 25776 10 30 13 46

Q3-2011 4774 13622 7154 28214 9 25 13 52

Q4-2011 6020 11036 7999 27714 11 21 15 53

17


Table 6: House starts of 27 cities and quarterly Pilot HSUI

Quarter

Total number of housing unit started

in 27 citiesPilot HSUI-Based on

27 cities

2009-Q1 25533 1002009-Q2 26791 1132009-Q3 28288 1082009-Q4 37636 1422010-Q1 44409 1392010-Q2 46758 1302010-Q3 48013 1322010-Q4 53706 1812011-Q1 49255 1622011-Q2 55726 1892011-Q3 53765 1572011-Q4 52768 169

18


Map1: Region / Centre-wise house starts

19


Annex-I: List of 66 permit issuing authorities in 27 cities in 15 states

Sr. No

Name of the State

Name of the City

Name of Department

1 Andhra Pradesh

1 Visakhapat-nam 1

Greater Visakhapatnam Municipal Corpora-tion

2 Assam 2 Guwahati 2 Guwahati Municipal Corporation

3Guwahati Metropolitan Development Author-ity

4 North Guwahati town development committee3 Chandigarh 3 Chandigarh 5 Chandigarh Municipal Corporation

6 Local Self Government7 Housing Board

4 Chhattisgarh 4 Bhilai 8 Bhilai Municipal Corporation9 Dept. of Town Planning (BSP)

5 Gujarat 5 Ahmedabad 10 Ahmedabad Municipal Corporation11 Ahmedabad Urban Development Authority12 Ahmedabad: Gujarat Housing Board

6 Jamnagar 13 Jamnagar Development Authority14 Jamnagar Municipal Corporation15 Jamnagar: Gujarat Housing Board

7 Surat 16 Surat Development Authority17 Surat Urban Development Authority18 Surat: Gujarat Housing Board

6 Haryana 8 Faridabad 19 Municipal Corporation of Faridabad20 Haryana Urban Development Authority21 Housing Board Haryana

20


7 Karnataka 9 Bangalore 22 Bruhat Bangalore Municipal Corporation23 Bangalore Development Authority

24Bangalore metropolitan regional development authority

25 Bangalore: Karnataka police housing board

26Bangalore: Karnataka state industrial develop-ment corporation

10 Hubli 27 Hubli-Dharwad Municipal Corporation28 Hubli Dharwad urban development Authority29 HD: Karnataka State police housing board

30HD: Karnataka State industrial development corporation

11 Mysore 31 Mysore City Corporation32 Mysore Urban Development Authority33 Mysore: Karnataka state police housing board

34Mysore: Karnataka state industrial develop-ment corporation

8 Madhya Pradesh

12 Bhopal 35 Bhopal Municipal Corporation13 Indore 36 Indore Municipal Corporation

9 Maharashtra 14 Nagpur 37 Nagpur Municipal Corporation38 Nagpur improvement trust

15 Sangli 39 Sangli-Miraj-Kupwad Municipal Corporation10 Pondicherry 16 Pondicherry 40 Pondicherry Municipal Corporation11 Rajasthan 17 Jaipur 41 Jaipur Development Authority

42 Jaipur Municipal Corporation43 Jaipur: Rajasthan Housing Board

18 Jodhpur 44 Jodhpur Development Authority45 Jodhpur Nagar Nigam46 Jodhpur: Rajasthan Housing Board

12 Tamilnadu 19 Coimbatore 47 Coimbatore Municipal Corporation20 Chennai 48 Corporation of Chennai

13 Uttaranchal 21 Dehradun 49 Mussoorie Dehradun Development Authority

21


14 Uttar Pradesh 22 Agra 50 Agra Development Authority

51Agra: UP Housing & Development Board (Av-asVikasParishad)

52Agra: Uttar Pradesh State Industrial Develop-ment Corporation

23 Allahabad 53 Allahabad Development Authority

54Allahabad: UP Housing & Development Board (AvasVikasParishad)

55Allahabad: Uttar Pradesh State Industrial De-velopment Corporation

24 Lucknow 56 Lucknow Development Authority

57Lucknow: UP Housing & Development Board (AvasVikasParishad)

58Lucknow: Uttar Pradesh State Industrial Devel-opment Corporation

25 Ghaziabad 59 Ghaziabad Development Authority

60Ghaziabad: UP Housing & Development Board (AvasVikasParishad)

61Ghaziabad: Uttar Pradesh State Industrial De-velopment Corporation

15 West Bengal 26 Kharagpur 62 Kharagpur Municipal Corporation63 PWD: Kharagpur

27 Kolkata 64 Kolkata Municipal Corporation65 Kolkata metropolitan development authority66 Howrah municipal corporation

22


Annex-II

Methodology for calculating sampling error and minimum sample size:

To determine sampling error and minimum sample size required for each city is calculated by the following methodology. In the methodology, the estimate which is calculated from the sample for each city separately, where p equals proportion of housing unit starts and (1-p) equal’s proportion of housing unit not started. Assuming n is large enough, a confidence interval for the true proportion p is given by

The interval has

Width=

This is twice the margin of error. The above expression involves which is unknown until the study is finished. Now, suppose that we want the margin of error to be no more than m. Now the minimum sample size required can be determine for fix margin of error and. We therefore want

This implies

Where

Solving this equation we get,

The equation still depends upon the eventual, which is unknown when one is planning the survey. However, we can see what sample size will be appropriate for a city for which is calculated from survey data allowing m=.025.Though if we draw a graphs ) versus , we will see that ) takes its biggest value when p =1/2. Thus, the “worst case” occurs when we use p =1/2 in the above equation as it leads to the biggest value of n.

23


Example:

In survey data of 2009 of Bangalore, number of housing unit started is 1943 and not started 130.So, from these observations

If we fix an interval no wider than w=.05(since 5%=5/100=.05), or m=0.025

Where

Minimum sample size require for p=.94, q=.06 and m=.025 is 354. But 2073 housing unit was surveyed in Bangalore. So, the sample is adequate sample for p=.94 and m=.025

24


Annex III (A): Sampling error and minimum sample size required for survey data of 2009 at 95% confidence interval

Citi

es se

lect

ed b

y ST

C

Tota

l hou

sing

uni

t(N

)

Tota

l hou

sing

uni

t in

surv

ey d

ata(

n)

Num

ber o

f hou

sing

unit

star

ted

in

surv

ey d

ata

Num

ber o

f hou

sing

unit

not s

tart

ed

in su

rvey

dat

a

Prop

ortio

n of

hou

sing

unit

star

ted

Sam

plin

g er

ror (

%)

Min

imum

sam

ple s

ize r

equi

red

Diff

eren

ce b

etw

een

actu

al a

nd m

ini-

mum

sam

ple s

ize

Ahmedabad 9436 771 760 11 0.99 0.80 86 685Allahabad 812 195 159 36 0.82 4.75 432 -237Bangalore 17434 2073 1943 130 0.94 0.98 354 1719Bhopal 3750 426 376 50 0.88 2.88 544 -118Chandigarh 895 137 135 2 0.99 1.85 80 57Chennai 12111 1387 1321 66 0.95 1.05 272 1115Coimbatore 2284 467 437 30 0.94 1.98 318 149Faridabad 1867 259 237 22 0.92 3.15 380 -121Hubli 1464 328 306 22 0.93 2.38 305 23Indore 4151 732 680 52 0.93 1.69 370 362Jaipur 4682 4442 3971 471 0.89 0.20 518 3924Jamnagar

3202 771 771 0 1.00 0.00 0 771

Jodhpur1664 221 144 77 0.65 5.85 759 -538

Kharagpur924 129 115 14 0.89 4.98 362 -233

Kolkata 16440 1762 1651 111 0.94 1.07 355 1407Lucknow 1919 282 161 121 0.57 5.34 844 -562

25


Sangli 693 192 184 8 0.96 2.40 181 11Visakhapat-nam

8603 1768 1715 53 0.97 0.71 175 1593

Bhilai 1683 203 183 20 0.90 3.84 412 -209Dehradun 2674 369 297 72 0.80 3.75 709 -340Guwahati 9867 1166 1033 133 0.89 1.71 584 582Pondicherry 4857 335 282 53 0.84 3.77 701 -366Agra 1186 182 134 48 0.74 5.89 595 -413Ghaziabad 2808 300 250 50 0.83 3.99 655 -355Surat 9768 5845 5015 830 0.86 0.57 696 5149Nagpur 5970 536 491 45 0.92 2.24 438 98Mysore 5229 585 502 83 0.86 2.66 655 -70

26


Annex III(B):Sampling error and minimum sample size required for survey data of 2010 at 95% confidence interval

Cities selected by STC

Total Housing Unit(N)

Total Hous-

ing unit in survey data(n)

Hous-ing unit

start-ed in

survey data

Hous-ing unit not

start-ed in

survey data

Propor-tion of hous-

ing unit started

Sam-pling error (%)

Mini-mum

sample size re-quired

Difference between

actual and minimum

sample size

Ahmedabad 33552 3747 3663 84 0.98 0.45 134 3613Allahabad 1115 204 162 42 0.79 5.02 529 -325Bangalore 22339 4767 4572 195 0.96 0.50 239 4528Bhopal 10327 1289 1051 238 0.82 1.98 849 440Chandigarh 1155 146 138 8 0.95 3.45 250 -104Chennai 13909 1664 1538 126 0.92 1.19 417 1247Coimbatore 2823 814 790 24 0.97 0.98 166 648Faridabad 4503 576 503 73 0.87 2.54 591 -15Hubli 4437 327 294 33 0.90 3.14 495 -168Indore 9575 1094 803 291 0.73 2.46 1066 28Jaipur 46693 3261 2020 1241 0.62 1.61 1405 1856Jamnagar 2205 596 592 4 0.99 0.56 40 556Jodhpur 1318 219 173 46 0.79 4.93 575 -356Kharagpur 817 163 146 17 0.90 4.20 337 -174Kolkata 26794 5563 4830 733 0.87 0.79 678 4885Lucknow 3075 334 211 123 0.63 4.88 976 -642Sangli 1603 425 418 7 0.98 1.04 94 331Visakhapatnam 8047 1330 1275 55 0.96 0.98 237 1093Bhilai 1727 213 200 13 0.94 3.01 289 -76Dehradun 2762 485 418 67 0.86 2.79 584 -99Guwahati 8981 1476 1323 153 0.90 1.42 521 955Pondicherry 4607 634 357 277 0.56 3.59 1138 -504Agra 1398 211 135 76 0.64 5.97 704 -493Ghaziabad 4402 358 287 71 0.80 3.96 800 -442Surat 20643 8383 8173 210 0.97 0.26 149 8234Nagpur 12308 824 705 119 0.86 2.32 698 126Mysore 6048 818 750 68 0.92 1.76 421 397

27


Annex-IV: Methodology for computation of coefficient matrix, house starts and HSUI

(i) Housing Start Rates (coefficients)

Housing Start Rates (coefficients) are computed from the survey data 0f the year 2009 and 2010 for 27 cities. The sample permits for four quarter in each of the 2009 and 2010 were taken as the starting observations for the survey. It tried to estimate the number of house constructions started in all the succeeding quarters, staring from the quarter in which the permits were issued till the latest period. Following international practice, all the house constructions started after the lapse of two years of issue of permits till two years further were added together. The last coefficient would indicate the house starts taking place over a period of another two years after the lapse of two years. This may be taken to reflect the coefficient of startups in a quarter out of all two year old permits till two years further. All houses started beyond 4 years of permit issued were assumed as not started. Based on this data corresponding to different quarters of the years, 9 start-up rates (1 for the quarter in which permits were issued, 7 for the 7 succeeding quarters and 1 for all the starts after 2 years till two years further) were computed. This produces a 4x9 matrix of start rates (coefficients) (see (1) and (2)). This matrix (HSRM) is used for estimating the number of housing starts in each quarter, using the methodology described below.

(11,1) (12,1) (13,1) (14,1) (21,1) (22,1) (23,1) (24,1) (..,1)

(1) (1) (1) (1) (1) (1) (1) (1) (1)

(12,2) (13,2) (14,2) (21,2) (22,2) (23,2) (24,2) (31,2) (..,2)

(2) (2) (2) (2) (2) (2) (2) (2) (2)

(

s s s s s s s s sp p p p p p p p ps s s s s s s s sp p p p p p p p ps 13,3) (14,3) (21,3) (22,3) (23,3) (24,3) (31,3) (32,3) (..,3)

(3) (3) (3) (3) (3) (3) (3) (3) (3)

(14,4) (21,4) (22,4) (23,4) (24,4) (31,4) (32,4) (33,4) (..,4)

(4) (4) (4) (4) (4) (4) (4) (4) (4)

s s s s s s s sp p p p p p p p ps s s s s s s s sp p p p p p p p p

HSRM = .…(1)

a) The number of housing starts during the jthquarter of the ith year, for which permits are issued in the kth quarter of the calendar year is denoted by ( ). The sample number of housing units authorized by building permits in the kth quarter of the calendar year is ( ).Now represents the corresponding housing start coefficient. represents the ratio of number of house constructions started after 8 quarters (including the quarter in which permit is issued) till two years further out of the total number of permits issued in kthquarter of the calendar year to the sample number of housing units authorized by building permits in the kth quarter of the calendar year.

28


b) The first start rate coefficient that is to be applied for estimating the housing starts in a quarter is computed by dividing the number of constructions started in that quarter for which permits are issued in that quarter itself. Understandably, many more house constructions would start during this quarter for which permissions have been obtained in previous quarters. But the coefficients in the first row of the matrix HSRM show how the permits given in the first quarter got converted into housing start in the subsequent quarters. The second row gives the corresponding coefficients for the second quarter. To estimate the number of starts in a quarter, therefore the matrix HSRM is to be transformed. The transformed matrix HSRMtransformed is obtained by rearranging HSRM.

HSRMtransformed=

(11,1) (21,4) (21,3) (21,2) (21,1) (31,4) (31,3) (31,2) (..,1)

(1) (4) (3) (2) (1) (4) (3) (2) (1)

(12,2) (12,1) (22,4) (22,3) (22,2) (22,2) (32,4) (32,3) (..,2)

(2) (1) (4) (3) (2) (1) (4) (3) (2)

(

s s s s s s s s sp p p p p p p p ps s s s s s s s sp p p p p p p p ps 13,3) (13,2) (13,1) (23,4) (23,3) (23,2) (23,1) (33,4) (..,3)

(3) (2) (1) (4) (3) (2) (1) (4) (3)

(14,4) (14,3) (14,2) (14,1) (24,4) (24,3) (24,2) (24,1) (..,4)

(4) (3) (2) (1) (4) (3) (2) (1) (4)

s s s s s s s sp p p p p p p p ps s s s s s s s sp p p p p p p p p

…(2)

c) This matrix HSRMtransformed is to be used for estimating the housing start figure for a particular quarter. The first row of HSRMtransformed gives the coefficients of housing start for the first quarter of the calendar year, based on which permissions given in previous quarters. Similarly the second, third and fourth rows correspond to the second, third and fourth quarters of the calendar year respectively.

(ii) Compilation of Housing Starts

a) The number of SHU or MHU house constructions started in a particular center during a particular quarter can be obtained by multiplying the start rates (coefficients) in the HSRMtransformed matrix with the corresponding total number of housing permits issued (in the current as also the preceding quarters). The choice of the row or the set of start rates depends on the quarter for which the housing starts are to be estimated. For example, if we are interested in estimating the number of housing starts in the third quarter of the calendar year then the third row of the HSRMtransformed matrix should be used along with the corresponding figures for housing permits.

29


b) This procedure is represented in mathematical form as follows. Let vectortP is a 9x1 vector of

which the first eight elements are the number of housing permits issued in the tth, ( t-1)th,( t-2)th…( t-7)th quarter. The ninth element is the sum total number of the number of housing permits issued in the ( t-8)th to ( t-15)th quarters.

'1 2 3 4 5 6 7 ( 8) ( 15)[ ]vector

t t t t t t t t t t tP P P P P P P P P P ……… (3)

Let Q be a 1x4 vector of seasonal dummies.

……………….. (4)

Where qi = 1 if t corresponds to ithquarter

= 0 otherwise for i = 1, 2, 3, 4

The number of housing starts in the quarter t which is a scalar is given by

……………… (5)

(iii) Compilation of Housing Start-Up Index

As the number of urban centers in India large, compiling housing starts for each and every center and thereby obtaining an All India figure on a quarterly basis is difficult. As an alternative, 27 cities have been chosen and an index is developed at All India level using the information obtained from these 27 selected cities.

The HSUI is estimated using the formulae given below,

………. (6)

Where n is the number of cities,Aitis the average plinth area in the tth quarter in ithcentre; Aiois the average plinth area in the ithcentre in the base period Q1 of 2009 ;Sitis the number of housing starts in the tth quarter in ithcentre; Si0is the number of housing starts in the base period in ithcentre. It is mentioned that all plinth area used in this method is calculated from actual permit data during 2009 to 2011.

30


Annex V: Housing Start rate coefficient matrix for SHU: 2009 & 2010 Combined

Kolkata

Q1 0.18 0.38 0.10 0.12 0.02 0.00 0.03 0.00 0.04Q2 0.21 0.24 0.17 0.13 0.06 0.08 0.03 0.00 0.06Q3 0.16 0.26 0.22 0.00 0.03 0.00 0.02 0.00 0.00Q4 0.21 0.35 0.15 0.06 0.07 0.03 0.03 0.00 0.00

Chennai

Q1 0.14 0.41 0.06 0.09 0.11 0.00 0.03 0.00 0.03Q2 0.31 0.29 0.18 0.06 0.06 0.09 0.00 0.03 0.03Q3 0.39 0.23 0.20 0.00 0.00 0.06 0.06 0.00 0.00Q4 0.21 0.42 0.14 0.09 0.12 0.00 0.06 0.00 0.00

Ahmedabad

Q1 0.14 0.68 0.04 0.00 0.00 0.00 0.00 0.00 0.05Q2 0.36 0.76 0.12 0.04 0.00 0.00 0.00 0.00 0.00Q3 0.27 0.50 0.05 0.00 0.04 0.00 0.00 0.00 0.00Q4 0.12 0.50 0.09 0.00 0.00 0.04 0.00 0.00 0.00

Faridabad

Q1 0.15 0.54 0.10 0.00 0.00 0.00 0.00 0.00 0.00Q2 0.25 0.70 0.04 0.00 0.00 0.00 0.00 0.05 0.00Q3 0.14 0.55 0.00 0.04 0.05 0.00 0.00 0.00 0.00Q4 0.08 0.52 0.05 0.00 0.00 0.05 0.00 0.00 0.00

Coimbatore

Q1 0.08 0.32 0.18 0.04 0.10 0.01 0.03 0.06 0.06Q2 0.19 0.21 0.10 0.06 0.03 0.06 0.02 0.01 0.09Q3 0.17 0.34 0.17 0.09 0.10 0.03 0.03 0.01 0.06Q4 0.23 0.26 0.10 0.10 0.11 0.06 0.04 0.04 0.02

Ghaziabad

Q1 0.36 0.55 0.13 0.05 0.00 0.00 0.00 0.00 0.05Q2 0.41 0.36 0.00 0.00 0.00 0.05 0.00 0.00 0.00Q3 0.17 0.45 0.09 0.00 0.04 0.05 0.00 0.00 0.04Q4 0.23 0.21 0.00 0.05 0.00 0.08 0.00 0.00 0.00

31


Hubli

Q1 0.00 0.12 0.05 0.04 0.00 0.00 0.00 0.00 0.00Q2 0.04 0.25 0.07 0.07 0.06 0.02 0.02 0.02 0.00Q3 0.36 0.38 0.50 0.05 0.07 0.02 0.06 0.00 0.00Q4 0.64 0.31 0.40 0.06 0.02 0.00 0.00 0.00 0.00

Visakhapatnam

Q1 0.00 0.76 0.06 0.03 0.00 0.00 0.00 0.00 0.00Q2 0.00 0.97 0.03 0.00 0.09 0.00 0.00 0.00 0.00Q3 0.00 0.80 0.03 0.03 0.00 0.03 0.00 0.00 0.00Q4 0.16 0.88 0.03 0.00 0.00 0.00 0.03 0.00 0.00

Sangli

Q1 0.55 0.33 0.03 0.00 0.03 0.00 0.00 0.00 0.00Q2 0.61 0.26 0.05 0.03 0.06 0.00 0.00 0.00 0.00Q3 0.52 0.18 0.05 0.05 0.00 0.00 0.00 0.00 0.00Q4 0.48 0.28 0.09 0.03 0.05 0.03 0.00 0.00 0.00

Bangalore

Q1 0.12 0.27 0.13 0.13 0.05 0.03 0.00 0.01 0.03Q2 0.07 0.31 0.08 0.06 0.07 0.06 0.01 0.01 0.01Q3 0.20 0.25 0.18 0.08 0.05 0.08 0.02 0.00 0.00Q4 0.41 0.39 0.24 0.10 0.01 0.03 0.02 0.01 0.00

Lucknow

Q1 0.17 0.38 0.12 0.12 0.02 0.00 0.03 0.00 0.04Q2 0.16 0.19 0.09 0.03 0.04 0.06 0.00 0.02 0.02Q3 0.08 0.21 0.10 0.00 0.02 0.04 0.02 0.00 0.02Q4 0.23 0.39 0.23 0.13 0.05 0.02 0.00 0.02 0.00

Allahabad

Q1 0.15 0.19 0.19 0.00 0.05 0.00 0.05 0.00 0.00Q2 0.10 0.20 0.14 0.10 0.05 0.10 0.00 0.00 0.00Q3 0.19 0.25 0.15 0.00 0.05 0.05 0.00 0.00 0.00Q4 0.24 0.10 0.00 0.05 0.10 0.05 0.05 0.00 0.00

32


Agra

Q1 0.12 0.39 0.10 0.02 0.02 0.00 0.00 0.04 0.02Q2 0.14 0.44 0.04 0.02 0.00 0.02 0.02 0.00 0.02Q3 0.16 0.40 0.03 0.04 0.02 0.00 0.00 0.00 0.00Q4 0.37 0.29 0.06 0.06 0.00 0.03 0.00 0.00 0.00

Bhopal

Q1 0.01 0.31 0.18 0.21 0.09 0.04 0.00 0.00 0.03Q2 0.02 0.13 0.15 0.15 0.08 0.02 0.00 0.02 0.05Q3 0.00 0.07 0.25 0.09 0.08 0.12 0.02 0.00 0.10Q4 0.27 0.30 0.23 0.36 0.03 0.07 0.05 0.02 0.01

Chandigarh

Q1 0.25 0.22 0.10 0.00 0.00 0.00 0.00 0.00 0.14Q2 0.55 0.36 0.07 0.00 0.00 0.00 0.00 0.00 0.00Q3 0.63 0.23 0.00 0.00 0.00 0.00 0.00 0.00 0.05Q4 0.63 0.21 0.08 0.00 0.00 0.00 0.05 0.00 0.07

Jodhpur

Q1 0.06 0.31 0.21 0.07 0.06 0.00 0.00 0.00 0.02Q2 0.12 0.38 0.15 0.03 0.02 0.02 0.02 0.00 0.02Q3 0.15 0.31 0.14 0.02 0.06 0.02 0.02 0.00 0.00Q4 0.16 0.21 0.22 0.02 0.02 0.03 0.00 0.02 0.00

Kharagpur

Q1 0.05 0.40 0.19 0.10 0.05 0.00 0.00 0.03 0.05Q2 0.10 0.27 0.23 0.19 0.07 0.05 0.03 0.00 0.00Q3 0.15 0.33 0.32 0.03 0.00 0.03 0.05 0.00 0.00Q4 0.10 0.27 0.23 0.05 0.03 0.04 0.00 0.00 0.00

Guwahati

Q1 0.05 0.24 0.17 0.17 0.20 0.12 0.09 0.13 0.00Q2 0.13 0.10 0.04 0.13 0.08 0.00 0.00 0.00 0.00Q3 0.26 0.00 0.05 0.00 0.00 0.00 0.00 0.04 0.00Q4 0.32 0.04 0.21 0.15 0.04 0.09 0.08 0.05 0.04

33


Dehradun

Q1 0.16 0.23 0.15 0.06 0.08 0.02 0.02 0.01 0.04Q2 0.24 0.30 0.13 0.03 0.07 0.03 0.01 0.02 0.01Q3 0.23 0.28 0.07 0.05 0.04 0.04 0.02 0.00 0.01Q4 0.35 0.28 0.14 0.09 0.07 0.03 0.02 0.04 0.02

Bhilai

Q1 0.17 0.42 0.10 0.03 0.12 0.02 0.02 0.00 0.05Q2 0.14 0.18 0.09 0.05 0.03 0.08 0.00 0.00 0.07Q3 0.22 0.28 0.13 0.07 0.10 0.03 0.05 0.00 0.02Q4 0.30 0.29 0.17 0.07 0.00 0.10 0.00 0.03 0.00

Pondicherry

Q1 0.13 0.28 0.14 0.08 0.09 0.00 0.00 0.00 0.22Q2 0.19 0.17 0.16 0.03 0.03 0.04 0.00 0.00 0.22Q3 0.10 0.25 0.13 0.06 0.00 0.08 0.00 0.16 0.31Q4 0.22 0.38 0.11 0.17 0.06 0.03 0.03 0.04 0.06

Mysore

Q1 0.04 0.21 0.14 0.15 0.16 0.00 0.00 0.01 0.02Q2 0.06 0.04 0.16 0.08 0.17 0.08 0.00 0.01 0.00Q3 0.34 0.28 0.33 0.07 0.08 0.02 0.04 0.00 0.01Q4 0.44 0.13 0.17 0.14 0.00 0.01 0.00 0.03 0.00

Nagpur

Q1 0.19 0.19 0.11 0.06 0.10 0.03 0.01 0.01 0.03Q2 0.33 0.11 0.12 0.05 0.04 0.06 0.00 0.01 0.02Q3 0.36 0.19 0.12 0.03 0.02 0.04 0.05 0.00 0.02Q4 0.43 0.20 0.13 0.24 0.04 0.08 0.02 0.02 0.01

Jaipur

Q1 0.00 0.10 0.29 0.00 0.33 0.00 0.00 0.00 0.00Q2 0.00 0.00 0.30 0.00 0.17 0.17 0.00 0.00 0.00Q3 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Q4 0.10 0.29 0.17 0.25 0.10 0.00 0.00 0.08 0.00

34


Surat

Q1 0.14 0.52 0.00 0.00 0.00 0.04 0.00 0.00 0.05Q2 0.35 0.55 0.00 0.00 0.00 0.00 0.04 0.00 0.00Q3 0.20 0.40 0.05 0.00 0.00 0.10 0.00 0.00 0.00Q4 0.26 0.55 0.00 0.09 0.04 0.05 0.00 0.00 0.00

Jamnagar

Q1 0.16 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.02Q2 0.33 0.49 0.00 0.06 0.00 0.00 0.00 0.00 0.00Q3 0.64 0.45 0.24 0.00 0.00 0.00 0.00 0.00 0.00Q4 0.87 0.30 0.14 0.10 0.00 0.00 0.00 0.00 0.00

Indore

Q1 0.08 0.25 0.09 0.06 0.03 0.00 0.00 0.02 0.04Q2 0.14 0.32 0.11 0.04 0.02 0.03 0.02 0.01 0.00Q3 0.22 0.45 0.01 0.00 0.03 0.03 0.03 0.00 0.01Q4 0.38 0.33 0.05 0.05 0.00 0.00 0.00 0.00 0.00

35


Annex VI: Housing Start rate coefficient matrix for MHU: 2009 & 2010 Combined

Kolkata

Q1 0.20 0.32 0.16 0.13 0.08 0.01 0.02 0.02 0.03Q2 0.23 0.29 0.14 0.10 0.04 0.03 0.00 0.03 0.01Q3 0.24 0.29 0.14 0.04 0.02 0.03 0.04 0.01 0.00Q4 0.30 0.26 0.10 0.09 0.06 0.07 0.03 0.02 0.01

Chennai

Q1 0.15 0.38 0.18 0.08 0.06 0.02 0.02 0.02 0.04Q2 0.25 0.32 0.12 0.03 0.06 0.04 0.00 0.01 0.04Q3 0.28 0.26 0.15 0.03 0.07 0.03 0.04 0.00 0.01Q4 0.36 0.30 0.20 0.07 0.02 0.05 0.02 0.03 0.00

Ahmedabad

Q1 0.10 0.50 0.19 0.02 0.00 0.00 0.00 0.00 0.00Q2 0.17 0.77 0.28 0.00 0.00 0.02 0.00 0.00 0.00Q3 0.13 0.62 0.09 0.00 0.03 0.00 0.00 0.00 0.00Q4 0.17 0.65 0.15 0.00 0.02 0.00 0.00 0.00 0.00

Faridabad

Q1 0.15 0.55 0.10 0.00 0.00 0.00 0.00 0.00 0.00Q2 0.22 0.63 0.09 0.02 0.04 0.03 0.00 0.00 0.00Q3 0.16 0.58 0.07 0.01 0.00 0.01 0.00 0.00 0.01Q4 0.18 0.58 0.03 0.01 0.07 0.00 0.01 0.01 0.00

Coimbatore

Q1 0.19 0.46 0.09 0.00 0.00 0.00 0.00 0.00 0.00Q2 0.18 0.37 0.08 0.18 0.08 0.03 0.00 0.00 0.00Q3 0.12 0.40 0.13 0.00 0.00 0.00 0.00 0.00 0.00Q4 0.31 0.53 0.26 0.16 0.07 0.09 0.00 0.00 0.00

Ghaziabad

Q1 0.22 0.34 0.12 0.02 0.10 0.00 0.00 0.02 0.04Q2 0.36 0.28 0.06 0.00 0.00 0.00 0.01 0.00 0.02Q3 0.23 0.46 0.18 0.00 0.00 0.00 0.00 0.00 0.00Q4 0.47 0.40 0.09 0.08 0.00 0.00 0.00 0.00 0.00

36


Hubli

Q1 0.02 0.12 0.04 0.00 0.08 0.02 0.00 0.02 0.02Q2 0.02 0.24 0.06 0.06 0.02 0.02 0.02 0.00 0.00Q3 0.44 0.46 0.45 0.05 0.00 0.02 0.02 0.00 0.00Q4 0.63 0.35 0.36 0.08 0.03 0.03 0.00 0.00 0.02

Visakhapatnam

Q1 0.00 0.89 0.04 0.01 0.00 0.02 0.00 0.00 0.00Q2 0.04 0.93 0.04 0.01 0.00 0.00 0.00 0.00 0.00Q3 0.01 0.88 0.04 0.00 0.00 0.00 0.00 0.00 0.00Q4 0.01 0.89 0.05 0.00 0.00 0.01 0.00 0.00 0.00

Sangli

Q1 0.42 0.18 0.02 0.04 0.00 0.00 0.00 0.00 0.00Q2 0.56 0.36 0.00 0.00 0.04 0.00 0.00 0.00 0.00Q3 0.64 0.37 0.16 0.12 0.00 0.00 0.03 0.00 0.00Q4 0.68 0.30 0.00 0.00 0.00 0.00 0.00 0.00 0.02

Bangalore

Q1 0.16 0.28 0.10 0.05 0.06 0.02 0.02 0.01 0.02Q2 0.08 0.34 0.10 0.05 0.04 0.06 0.01 0.00 0.01Q3 0.14 0.36 0.15 0.05 0.04 0.04 0.03 0.00 0.00Q4 0.40 0.45 0.29 0.09 0.01 0.04 0.03 0.01 0.01

Lucknow

Q1 0.04 0.35 0.06 0.13 0.04 0.00 0.00 0.00 0.12Q2 0.06 0.27 0.11 0.03 0.01 0.15 0.00 0.00 0.00Q3 0.18 0.21 0.08 0.00 0.03 0.00 0.08 0.00 0.03Q4 0.30 0.44 0.24 0.04 0.04 0.03 0.04 0.00 0.00

Allahabad

Q1 0.05 0.22 0.10 0.03 0.02 0.08 0.05 0.00 0.02Q2 0.19 0.56 0.08 0.05 0.06 0.08 0.00 0.00 0.00Q3 0.19 0.32 0.00 0.04 0.05 0.00 0.02 0.00 0.00Q4 0.28 0.38 0.03 0.00 0.02 0.00 0.00 0.00 0.00

37


Agra

Q1 0.04 0.32 0.05 0.05 0.04 0.05 0.00 0.00 0.00Q2 0.05 0.17 0.05 0.00 0.00 0.00 0.00 0.00 0.00Q3 0.10 0.48 0.30 0.05 0.00 0.00 0.00 0.00 0.00Q4 0.32 0.38 0.19 0.00 0.00 0.00 0.00 0.00 0.00

Bhopal

Q1 0.02 0.23 0.20 0.12 0.10 0.01 0.02 0.01 0.02Q2 0.08 0.17 0.22 0.09 0.11 0.08 0.02 0.02 0.00Q3 0.17 0.15 0.27 0.06 0.09 0.06 0.04 0.00 0.01Q4 0.17 0.23 0.22 0.27 0.08 0.04 0.06 0.02 0.01

Chandigarh

Q1 0.19 0.35 0.19 0.08 0.12 0.00 0.00 0.00 0.00Q2 0.24 0.43 0.03 0.06 0.00 0.00 0.00 0.00 0.00Q3 0.19 0.51 0.08 0.00 0.03 0.00 0.00 0.00 0.00Q4 0.52 0.45 0.17 0.19 0.03 0.00 0.00 0.00 0.00

Jodhpur

Q1 0.12 0.12 0.14 0.00 0.00 0.08 0.11 0.00 0.00Q2 0.19 0.41 0.17 0.00 0.08 0.00 0.00 0.11 0.00Q3 0.04 0.44 0.06 0.04 0.00 0.00 0.04 0.00 0.00Q4 0.18 0.20 0.06 0.06 0.08 0.10 0.00 0.00 0.04

Kharagpur

Q1 0.18 0.49 0.10 0.26 0.05 0.00 0.00 0.00 0.05Q2 0.05 0.41 0.00 0.10 0.00 0.00 0.00 0.05 0.00Q3 0.05 0.54 0.05 0.00 0.00 0.00 0.00 0.00 0.10Q4 0.20 0.50 0.10 0.18 0.04 0.05 0.00 0.05 0.04

Guwahati

Q1 0.21 0.31 0.22 0.10 0.16 0.09 0.05 0.07 0.12Q2 0.21 0.13 0.10 0.10 0.04 0.05 0.06 0.01 0.01Q3 0.19 0.19 0.02 0.03 0.04 0.01 0.04 0.02 0.01Q4 0.17 0.15 0.16 0.15 0.07 0.07 0.01 0.03 0.00

38


Dehradun

Q1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Q2 0.00 0.40 0.00 0.00 0.00 0.00 0.00 0.00 0.00Q3 0.00 0.50 0.20 0.00 0.00 0.00 0.00 0.00 0.00Q4 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Bhilai

Q1 0.06 0.33 0.30 0.12 0.10 0.04 0.00 0.04 0.06Q2 0.16 0.22 0.04 0.07 0.04 0.06 0.00 0.00 0.04Q3 0.28 0.23 0.09 0.07 0.13 0.07 0.06 0.00 0.07Q4 0.44 0.16 0.23 0.18 0.00 0.00 0.04 0.06 0.04

Pondicherry

Q1 0.05 0.17 0.15 0.06 0.04 0.00 0.00 0.00 0.03Q2 0.08 0.21 0.14 0.09 0.07 0.00 0.00 0.01 0.03Q3 0.17 0.29 0.08 0.05 0.05 0.07 0.04 0.03 0.00Q4 0.36 0.22 0.18 0.19 0.00 0.04 0.00 0.02 0.02

Mysore

Q1 0.01 0.14 0.06 0.08 0.07 0.02 0.00 0.01 0.00Q2 0.18 0.11 0.05 0.09 0.04 0.07 0.02 0.03 0.02Q3 0.47 0.39 0.48 0.02 0.06 0.05 0.05 0.00 0.00Q4 0.61 0.14 0.13 0.09 0.00 0.00 0.00 0.02 0.01

Nagpur

Q1 0.28 0.29 0.16 0.09 0.07 0.00 0.04 0.00 0.05Q2 0.45 0.18 0.06 0.03 0.06 0.05 0.00 0.00 0.00Q3 0.33 0.14 0.09 0.00 0.03 0.00 0.00 0.00 0.00Q4 0.40 0.28 0.12 0.25 0.08 0.04 0.03 0.00 0.00

Jaipur

Q1 0.00 0.31 0.03 0.30 0.00 0.00 0.08 0.00 0.06Q2 0.00 0.06 0.21 0.25 0.17 0.12 0.00 0.08 0.00Q3 0.04 0.00 0.06 0.13 0.10 0.07 0.06 0.00 0.00Q4 0.07 0.21 0.22 0.11 0.00 0.00 0.00 0.00 0.00

39


Surat

Q1 0.28 0.47 0.00 0.00 0.00 0.00 0.00 0.00 0.01Q2 0.34 0.60 0.00 0.00 0.00 0.00 0.00 0.00 0.08Q3 0.64 0.53 0.01 0.07 0.00 0.00 0.00 0.00 0.00Q4 0.28 0.31 0.00 0.00 0.00 0.02 0.00 0.00 0.00

Jamnagar

Q1 0.10 0.25 0.13 0.03 0.06 0.00 0.00 0.00 0.03Q2 0.42 0.47 0.03 0.00 0.00 0.00 0.02 0.00 0.00Q3 0.52 0.34 0.27 0.00 0.00 0.00 0.00 0.00 0.00Q4 0.70 0.35 0.21 0.06 0.00 0.00 0.00 0.00 0.00

Indore

Q1 0.07 0.14 0.04 0.02 0.01 0.01 0.00 0.00 0.01Q2 0.35 0.46 0.05 0.06 0.02 0.01 0.00 0.00 0.01Q3 0.51 0.41 0.28 0.03 0.01 0.02 0.01 0.00 0.00Q4 0.56 0.23 0.03 0.02 0.01 0.01 0.01 0.00 0.00

CONTACT:

Director (NBO) & OSD (JNNURM & RAY)Ministry of Housing & Urban Poverty AlleviationGovernment of India210-G Wing, NBO BuildingNirman Bhavan, New Delhi 110108Tel: +91 11 23061602Fax: +91 11 23061542E-Mail: [email protected]

http://www.nbo.nic.in

HSUIHSUI

Trend in newly constructed residential housesduring 2009 -2011 in 27 cities across India

Pilot Housing Start Up Index





Documents

HSUI Report Final - Naredco