|
Parameters |
Year 2009 |
Year 2018 |
Increase over Year 2009 |
|
Sales (in units ) |
2,17,253 |
2,78,989 |
1.28 times |
|
Sales Value |
1,31,495 |
2,05,792 |
1.56 times |
|
Inventory ( in units) |
2,83,060 |
13,19,793 |
4.66 times |
|
Inventory Value |
1,64,338 |
9,38,109 |
5.71 times |
|
Months Inventory |
16 |
41 |
2.56 times |
|
Total debt on sector (INR trillion) |
1.2 |
4 |
3.33 times |
Source: LIASAS FORAS
Sales and Unsold Inventory trends in units (Top – 8 cities)
|
Year |
Annual Sales in Unit |
Unsold Housing in Units |
Months Unsold stock of Housing |
|
2009 |
2,17,253 |
2,83,060 |
16 |
|
2010 |
2,14,743 |
3,78,577 |
21 |
|
2011 |
2,10,109 |
4,38,416 |
25 |
|
2012 |
2,28,472 |
4,99,949 |
26 |
|
2013 |
2,11,646 |
5,84,734 |
33 |
|
2014 |
2,22,149 |
6,74,888 |
36 |
|
2015 |
2,24,869 |
8,54,668 |
46 |
|
2016 |
2,37,185 |
9,53,977 |
48 |
|
2017 |
2,56,248 |
9,18,773 |
43 |
|
2018 |
2,78,989 |
9,43,680 |
41 |
|
Source www.liasasforas.com |
|||
Sales and Unsold Housing flats trends in Value (Top -8 cities)
|
Year |
Value of sold stock in Crores |
Value of unsold inventory/ stock in Crore |
|||
|
2009 |
1,31,495 |
1,64,338 |
|||
|
2010 |
1,25,331 |
2,23,536 |
|||
|
2011 |
1,18,569 |
2,86,620 |
|||
|
2012 |
1,37,974 |
3,78,885 |
|||
|
2013 |
1,43,211 |
4,85,062 |
|||
|
2014 |
1,60,024 |
5,89,404 |
|||
|
2015 |
1,78,396 |
7,32,893 |
|||
|
2016 |
1,81,389 |
8,25,260 |
|||
|
2017 |
1,96,660 |
7,79,121 |
|||
|
2018 |
2,05,792 |
7,77,183 |
|||
|
Source : |
www.liasasforas.com |
||||
Valuation of Unsold Housing Flats (Stock/Inventories) in India
|
Project segment |
Segment range (Rs) |
Unsold units |
Value of unsold units ( Rs in Cr) |
Average Ticket size (Rs in Cr) |
|
Priority sector |
1-30 Lakh |
3,92,364 |
83,217 |
0.21 |
|
Priority-affordable |
30-45 Lakh |
3,06,437 |
1,16,801 |
0.38 |
|
Affordable segment |
45-60 Lakh |
2,17,791 |
1,16,041 |
0.53 |
|
Affordable Mid segment |
60 lakh -1 Crore |
2,15,032 |
1,70,216 |
0.79 |
|
Mid segment |
1-2 Crore |
1,28,827 |
1,79,010 |
1.39 |
|
Upper Mid Segment |
2-3 Crore |
29,361 |
71,315 |
2.43 |
|
Luxury |
3-8 Crore |
24,216 |
1,10,282 |
4.55 |
|
Ultra Luxury |
>8 Crore |
5,765 |
91,227 |
15.82 |
|
Total |
13,19,793 |
9,38,109 |
0.71 |
Source: www.liasasforas.com
The Top 8 cities are Mumbai, Kolkata, New Delhi, Ahmedabad, Pune, Chennai, Hyderabad, and Bengaluru.
It is observed that maximum unsold housing Units(3.92 Lakh flats) exists in the affordable housing category which basically caters to low income category flats. The average flat size of this category is Rs 21 Lakh.
Out of the Total Unsold Housing flats, 85 % of the flats comes under the category of Affordable Housing segment.
This is a serious concern especially in view of the Government of India mission of “Housing for All” by 2022, providing housing to every household in the country. Its impact on the society is huge, any delay in the projects restricts employability, living and existence of the family.
|
Cities |
New Units Launched in FY 2019-20 |
Sold units |
Unsold Housing Units |
|
NCR* |
5,790 |
9,830 |
1,77,900 |
|
MMR* |
14,040 |
17,180 |
2,20,870 |
|
Bengaluru |
9,370 |
10500 |
63,540 |
|
Pune |
8,320 |
8,550 |
92,560 |
|
Hyderabad |
2,050 |
3,280 |
23,890 |
|
Chennai |
2,530 |
2,620 |
31,380 |
|
Kolkata |
3,130 |
3,120 |
45,570 |
|
37,742 |
55,080 |
6,55,710 |
Status of Unsold Inventory -07 major Indian Cities as on September 2019
Source: www.anarock.com
- MMR –Mumbai Metropolitan Region
- NCR – National Capital Region of Delhi
RERA Projects in Maharashtra
Status as on September 2019
|
Parameters |
Figures in Actual |
|
Total RERA Projects Registered |
21,812 |
|
Registered but not completed |
16,946 (78%) |
|
Registered and Completed |
4,698 (21 %) |
|
Yet to be Registered |
168 (1 %) |
|
Source:www.mahareraonline |
Only 21 % of the Projects registered under RERA in Maharashtra are completed.
Contemporary debates &Interests;:
Analysis of the Housing trends and progress from the reports of the National Housing Bankreveals that Indian housing underwent transformative change beginning post year 2004.
The rise in Population growth, increasing urbanisation, increase in disposable income, easy accessibility and availability of Institutional finance, Tax sops attached to housing, resulted in housing becoming an increasingly a viable investment option for the investors and general Public.
After Year 2016, external policy interventions due to RERA and Demonetisation and GST have resulted in the drastically restricting the usage of cash as a means of purchasing the Housing Flats. Strict RERA guidelines have restricted the multiple launch of Housing projects. Importance is now given to Compliance and timely completion of the existing projects.
It has direct impact on reducing the number of the Developers/Builders/ Standalone Builders who were not having the net worth, credibility and commitment to customer delivery of the completed projects.
According to report of Insolvency & Bankruptcy Board of India, Insolvencies of property firms have more than doubled in year presently 500.
Recently Government of India announced a Alternative Fund with an Initial corpus of Rs 25000 Crore to revive up to 4.6 Lakh housing units in 1600 Projects.
The Fund is sponsored by Government of India, State Bank of India and LIC. Only those projects will be considered for funding where the unit’s price is less than Rs 2 Crore in case of Mumbai and Rs.1 Crore in other cities. To get funding from Alternative Investment Fund, the project has to be registered under Real estate (Regulation and Development) Act and it should be net – worth Positive.
Cross functional –Inter disciplinary aspects
The Real estate economy is the fourth largest contributorcontributing 6.86 % of the India’s GDP.
A Study on “Impact of investments in the housing sector on GDP and Employment in the Indian Economy” was conducted by National Council of Applied Economic Research (NCAER) in 2014 based on the inter-industry linkages of housing investment.
The key ?ndings of the report are as follows:
- The residential construction i.e. housing sector accounts for 1% of GDP and 6.86% of the employment.
- Housing sector is fourth largest employment generating sector.
- 99.4% of the jobs in housing sector are informal jobs.
- Its labour to output ratio i.e. number of persons employed to produce a lakh units of output, is 2.34 which is the highest among all the sectors.
- For every lakh invested in the housing sector, 2.69 new jobs are created in the economy. With inducedeffect (i.e. resultant increase in demand for output on account of increased income), the number of jobs created would be 4.06 (3.95 informal and 0.11 formal).
- Every additional rupee invested in the housing sector will add ?1.54 to the GDP and with household expenditure considered, this is going to add ? 2.84.
- For every rupee invested in creation of housing, ?0.12 gets collected as indirect taxes.
Ref: National Housing Bank report – Trends and Progress report – 2018
Policy based motivation for the research as a trigger
The Indian Real Estate economy is expected to contribute to 5 Trillion $ economy by Year 2023. Introduction of Goods and Services Tax (GST)and Real Estate Regulation Act 2016 is giving the real estate market the necessary institutional support.
This has resulted in bringing to fore the problems of real estate market especially the problems of building residential projects getting stuck due to non-availability of project funding. It is resulting in rise of Unsold Housing Units which are primarily under construction flats.
As per the estimates of the 12th Five Year Plan of Government of India, the shortage of housing in urban segment of society stood at 18.78 million as per the 2011 census.
Government of India is focussed on making “Housing for all” as a mission to provide every family a House by 2022. Towards this, Housing made affordable and accessible through government interventions is put in place in reducing the demand supply gap of the unsold Housing inventories.
The Government of India attempts to focus on reducing the gap of Housing shortage through various policy initiatives and measures as under since 1951 till date:
|
Sr. no |
Housing Policy/Programme |
Year |
|
1 |
National Housing Policy |
1988 |
|
2 |
National Housing and Habitat Policy |
1998 |
|
3 |
Jawaharlal Nehru National Urban Renewal Mission |
2005 |
|
4 |
National Urban Housing and Habitat Policy |
2007 |
|
5 |
. Interest Subsidy Scheme for Housing the Urban Poor (Rajiv Rinn Yojana) |
2008 |
|
6 |
Affordable Housing in Partnership |
2013 |
|
7 |
Pradhan Mantri Awas Yojana :Housing for all by 2022 |
2015 |
Source: Ministry of Urban Housing and Alleviation
Real estate market was driven through investors and not primary buyers. This asset class was the investors preferred choice during the period 2006 to 2012 and transaction through cash in asset investment thrived the housing economy.
Demonetisationtransformed the operations of the investors driven Housing economy and with RERA implementation and stricter guidelines for projects launch and completion, funding crunch affected the developer’sprojects.
On the Policy making front, GOI intends to achieve 5$ trillion economy by 2023.
Real estate presently contributes 6.86 % of Indian GDP. Its contribution to GDP is much less as compared to other global economies of the World.
On Entrepreneurs front- the slowdown of the economy will affect the services sector restricting the entrepreneurs for Stand up India /Start up Initiative.
On the academic front, to study the causes of the Unsold Housing flats and its impact on affordable housing in the Indian Real Estate market
On the Individual level, the unsold inventory affects the customer’s behaviour towards investment in real estate.
Overall at the Society level,the resultant slump in the housing market affects every aspects of the economy as the existence of human beings centres around ROTI, (Food) KAPDA (Clothing) and MAKAAN (house).
The slump in the economy impacts the purchasing power of individual and hence restricts the decision making ability to invest in housing in an uncertain market wherein the employment continuance becomes uncertain.
Benefits of the Study
The study of the Unsold Housing Flats stock will help understand the reasons for the clog down of the Housing market, understands the ways and means to revive the housing real estate market, means to funding the developers,Bank’s Policy, GOI policy initiative in reviving the Housing real estate market.
The data will be collected from National Housing Bank RESIDEX FROM THE YEAR 2013 TILL 2019.
Potential Contribution of study to Knowledge, Practise, Policy Making, Academia.
The emergent problem of unsold housing flats in residential building projects is new phenomena in the Indian Real Estate. It is related to affordability (Pricing), Accessibility (location of the project iePlace), Product (Size of the Unsold Housing Unit/Flat) and Promotion (Incentives offered by GOI /Builders).
Research Studies undertaken in the field of Unsold Housing Units/Flats Inventory islimited. In the Indian Context, study of the unsold housing stock and its impact is not muchavailable.
Arnott (1989) elucidated that empty houses serve as a socially desirable function in that they expand the width of the selection to households entering the market.His study was however based on mathematical models and not empirical analyses.
Many research studies have been undertaken in the field of Housing Market.
Gist is as under:
|
Researchers |
Main contents |
|
Follain ( 1979) |
Examines whether the demand for the structural component of new housing has exerted an upward influence on the long run price of housing |
|
Arnott (1989) |
Presents a model with rental housing vacancies in equilibrium |
|
Green et al(1996) |
Measures the impact of age structure , education, and Income on the willingness of households to pay for constant quality housing |
|
Blackley ( 1999) |
Investigates the long run elasticity of new housing supply in the United states |
|
Malpezzi et all( 2001) |
Estimates the price elasticity of housing supply from new constructions separately for the United states and UK |
|
Mayers et al(2004) |
Presents an empirical model of housing supply derived from the Urban growth theory |
|
Sing et al( 2006) |
Empirically tests the house price dynamics associated with the mobility of households in the public resale , Private resale and private housing market in Singapore |
|
Glaeser et al(2008) |
Presents a simple model of housing bubbles that predicts that places with more elastic housing supply have fewer and shorter bubbles with small price increases |
|
Oikarinen( 2009) |
Empirically examines if household borrowing data indeed , is of importance in a dynamic housing price model |
|
Sewoong Jang & Lee (2010) |
Relationship between Demand –supply in the Housing Market and Unsold New Housing Stock in south Korea |
|
Younghoon Lee & Kim( 2016) |
Analysis of the Dynamic Relationship between Fluctuations in the Korean Housing market and the Occurrence of the Unsold New Housing Stocks |
|
Journal Review (May 2000) Federal Reserve Bank of New York |
Explaining the gap between New Home sales and Inventories |
|
Journal of Real Estate Practise & Education |
An integrated Property Market Model – a Pedagogic tool by Dominique Achour –Fischer Addis Ababa University |
|
OIKO DOMOS – a virtual campus |
Housing concepts – study of dwelling in contemporary Europe |
|
John F Kain, John M Quigley ( 1975) |
Housing Market and Racial Discrimination: a micro economic Analysis |
|
Jan K Brueckner & Peter F colwell |
A model of Housing Attributes : Theory & evidences |
|
Surabhi Singh (2015) |
A study of the Marketing strategies of Morpheus: Real Estate Company |
|
Shraddhanjali Parida |
Real Estate in Indian Context – Opportunities and Challenges |
|
Vera Li( 2011) |
A methodology to assess the competitiveness of Real estate Developers in China |
|
Vakili-Zad et al ( 2011) |
Unlikely contribution of high vacancy rate and the high price of housing from a welfare state perspective |
|
Couch et al ( 2013) |
Shrinking cities, housing vacancy and policy responses in Liver pool UK – The nature of Housing Policy and effectiveness of Policy responses |
|
Whitetaker et al( 2013) |
Impacts of property tax delinquency, vacancy, and foreclosures on the value of the neighbouring homes. This study shows that an additional property within a certain distance that is vacant or delinquent reduced a home ‘s selling price |
|
Molloy( 2016) |
Presented a simple theoretical framework to illustrate the connection between vacancy and excess supply in the housing market and discussed why data on duration of vacancy could help refine estimates of the excess supply. This study showed that the long term vacancy rate was more strongly correlated with various measures of housing market distress than standard measures of vacancy such as gross vacancy rate or the home owner vacancy rate. |
Review of Literature:
- Origins
Unsold Housing stock(UNHS) are used as a measure of housing inventories or vacant houses.
In Korea, UNHS are defined as houses for which a sales contract has not been entered into after marketing began to attract buyers under the time guideline and procedure.
UNHS have only recently been used as a housing market indicator; therefore, there have been few studies providing at through analysis of their in influence upon the housing market.
Arnott(1989)performed a study on vacant houses using a numerical model. His study verified that vacant houses play a socially desirable function in that they provide potential house purchasers with wider options to choose from, but he did not conduct an empirical analysis.
Mayer and Somervillesuggested an empirical model focusing on housing supply estimation. In the estimation function, housing price was selected as an important variable for housing supply, and vacant houses were referred to but excluded from the set of independent variables.
Kangstated that the cause of UNHSwas housingover-supply, lack ofconsumer purchasingpower, and insufficientgovernment financialsupport. He suggestedpolicy improvement as away to resolve the issue of UNHS. However, he did not review the effect of UNHS on the Housing market.
Jung and Kim performed an empirical study, via time series analysis, of the macroeconomic factors and government policies that affect UNHS. However, they did not mention the time lag between investment decisions on housing and its supply in the market.
Even though the social phenomenon of UNHS is regarded as a serious problem, few studies have examined its influence on the housing market. The main reason for this is the lack of sufficient time series data due to the difficulty of measuring UNHS. Nevertheless, UNHS should be counted as an intermediate factor that can influence the rationale of developers’ investment decisions and the attitudes of homebuyers. Therefore, it is appropriate to develop a method to analyse UNHStoexploreitsroleinthedynamichousingmarketratherthanrelegateittoavariableinanequation.
2. Theoretical framework of the problem
Hendry (1986) presents an empirical econometric model for the levels of starts and completions and the stock of work in progress for new private dwellings in the. UK. He illustrates both the theoretical issues and a sub-stantive econometric model to aid understanding of how housing construction markets operate. In his housing construction model the stock-flow relationships play an important role. The housing starts and housing completions series are the flow variables, and housing units under construction is the stock variable. It is interesting to note that the stock variable is obtained by accumulating the difference of the two flow variables. The stock of housing units under construction is the accumulated sum of uncompleted starts.
A similar relationship for the inventory model is studied by Granger and Lee (1989, 1990) and Lee (1990) using the concept of multico-integration. The production and sales series are the flow variables, and the level of inventory is the stock variable. The level of inventory is the accumulated sum of production minus sales
3. The context of the identified Researchproblem
In the Indian Real Estate review of work on the study of Unsold Housing stock inventory is restricted to independent research consultants. It is yet to find a place in the national Housing Policy domain. The current focus is on affordable housing to reduce the gap of the Housing shortage at Urban India level.
It has not given due attention to the rise of stock of the Unsold Housing Inventory.
The context is to explore the causes of the unsold Housing flats in residential building projects and suggest strategies to reduce the stock of Unsold Housing units. The study is to also to understand the impact of Unsold Housing units on affordability housing in Indian Real Estate market.
4. The solutions that have been attempted to date - what has worked, what has not worked, why
Efforts taken by Government of India to reduce the pricing at the consumer level is done by reducing GST from general 12 % to 5 % (for properties above Rs 45 Lakh) and to 1 % (for properties up to Rs 45 Lakh).
5. Policy initiatives by Government of India-
- Real estate and Regulation Act (2016)
- Goods and Services Tax
- Benami Transactions act
- Atal Mission for Rejuvenation & Urban Transformation (AMRUT)
- Smart Cities Mission
- Real Estate Investment Trust (REIT)
- Easing of FDI Norms
- Alternative Investment Fund (AIF) of Rs 25000 Crore to stalled projects
All these transformative efforts have helped in giving the real Estate industry a support to free itself gradually from being speculative/Investor driven industry.
However, it continues to be ailed in not able to ensure and control the rise of unsold inventory of housing stock.
6.Relevance& urgency of the problem
The value of the Housing inventory lying unsold as on September 2019 stands at 9.38 Lakh crore. This value amounts to 5 % of the India’s unsold housing inventories.
The Unsold Inventory includes flats those which are completed but not sold (Ready to Move in Houses) and those flats which are still under construction.
7. Research Gaps identified – Study of the causes of the Unsold Housing Flats in the Residential Building Projects and its impact on the affordable Housing in the Indian Real Estate Market.
Research Methodology:
Research Problem - The Unsold Residential housing inventory that exists in the urban Real Estate market.
Research Question–what are the causes of Unsold Housing flats /units/Inventories existing in Residential building Projects in spiteAffordable Housing in Indian Real Estate Market.
Research Objective:
- To explore the causes of the Unsold Housing Units in the Residential Building Projects
- To Suggest strategies to reduce Unsold Housing Units in the Residential Building Projects
- To study existing promotional strategies adopted by builders to market the Unsold Housing Units in the Residential Building Projects
- To study the impact of the Government of India Policies resulting in rise of Unsold Housing Units in the Residential Building Projects
- To study the impact of the Unsold Housing Units in the Residential Building Projects on the Affordable Housing
- To study the access of Public amenities infrastructure and its impact on the rise on unsold Housing Units in the Residential Building Projects
- To study the impact of Affordability (Pricing), Location (Place), Housing Dwelling units(Product) and access to retail credit(process), facilities available (physical evidence), Classes (People) andthe Promotion on the rise of of Unsold Housing Units in the Residential Building Projects
Hypotheses:
- Timely possession of flats to buyers will reduce Unsold Housing Units
- GOI Policies is directly responsible for Unsold Housing Inventory
- Larger sized flats results in greater Unsold Housing Units
- Residential Housing Projects financed by Financial Institutions reduces the Unsold Housing Units
- Public amenities having access to Residential to Residential Housing Projects will reduce Unsold Housing Units
Scope of the Study
Conceptual Scope:
The scope of the study is aroused from the fact that there exist huge Inventory of Unsold Housing flats/Units in the residential Housing Projects across the major metropolitan cities. The value of the Unsold Housing Inventory amounts to 5 % of India’s GDP and more than 85% of the Unsold Housing Inventory comes under the category of Affordable Housing.
This is a drag on the Housing market and overall Indian Economy. The Purpose of the study is therefore to understand the causes of the rise of the Unsold Housing Units/flats/Inventories and understand its impact on affordable housing in the Indian Real Estate market.
The existing research work in this area is mostly attempted towards understanding the impact of Housing Policies on Housing Market and on Affordable Housing.
However, in the Indian context, there is hardly any research study undertaken to study and highlight the causes of the rise of the Unsold Housing Units/flats/Inventories in the Real Estate Market. In order to fill the above research gap, the study is undertaken.
Geographical Scope:
The selected area is the Pune City, Pimpri Chindwad Municipal Corporation. This area is the most expanding city for Housing Real estate. According to RERA site of Government of Maharashtra more than 4000 Real Estate Housing projects are presently registered under RERA in Pune City and Pune Chinchwad MunicipalCorporation. More than 92000 Vacant Unsold Housing flats/Units/Inventories exist in the Pune city and Pimpri Chindwad Municipal Corporation.
Research Philosophy / paradigm – It is belief about the about the ways in which the data about a phenomenon is collected, analysed and used.
|
Feature |
Outcome |
|
Philosophy |
Positivism, Interpretivism |
|
Approach |
Deduction, Inductive |
|
Methodological Choice |
Multimethod –Quantitative& Qualitative |
|
Strategy |
Survey, In Focus Group Discussion, In-depth Interview. |
|
Time Horizon |
Cross sectional (different Population group) |
|
Techniques & Procedures |
Data collection & Procedures |
|
Research Paradigm |
Objectivist |
|
Research Method |
Quantitative, Descriptive , and Exploratory, and Qualitative |
Research Design– Since the research question is to explore the causes of the Unsold Housing Units /Flats/Inventories, The methodology adopted will be as under
|
Parameters |
Inputs |
|
Research method |
Quantitative, Descriptive, Qualitative |
|
Nature of data |
Primary , and Secondary |
|
Source of Primary Data |
People (Customers who have booked the flats ) Builders/Developers having Projects with Unsold Housing Inventory, Real Estate Brokers, Bankers, Architects, Registered Valuers , Direct Sales Agents (DSAs) |
|
Source of Secondary data |
RERA, Government Statistics, Real Estate data analytic companies, Banks, SLBC, Registrar Offices, Published Reports, Magazines, Newspapers, Websites, Real Estate Journals |
Sampling Design:
a) Population — 4000 Housing Residential Projects under Pune City and Pimpri Chindwad Municipal Corporation and customers booked the flats in Under Construction housing projects.
b) Sample –
1) Atleast 600 customers (People) who have booked housing flats in under- construction Projects and Projects which are completed but not sold with special focus on Pune City Pimpri Chindwad Municipal Corporation
2) 50 Builders/Developers associated with atleast 100 such housing projects where in the Unsold Inventory of Housing flats/Units exists.
3) 50 – Bankers, Architects, Registered Valuers, Real Estate Brokers, Direct Sales Agents , Housing Channel Partners
c) Sampling Methods– Probability sampling, Convenience Sampling
d) Sample Size/Respondent– 700
Data Collection Methods–Questionnaire, Mails, Personal visit.
a) Investigative Techniques – Interview, mails.
b) Data Collection Instrument – Primary data collection -structured Questionnaire,Builders website, RERA, Registry Office, National Housing Bank, Government Statistics.
c) Field work – Visits will conducted to the Projects which are under construction or are ready to Move but not sold. Visits to Government offices, Registrar offices, banks, Consultancies will be undertaken to collect the data.
Data Analysis Plan– Towards analysis of data and testing of hypotheses statistical tools like Mean Standard deviation, median, Z Test, Factor analysis ANOVAs, Correlation statistic using SPSS and M S Excel shall be used or any other Tests as required.
Tables, Pie charts, Bar and Pie Diagram as applicable will used for Data presentation.
Testing of Reliability and Validity of the Questionnaire:
Reliability means that the measuring instrument gives consistent results.
Test for Reliability of the questionnaire will be carried out using by test-retest method.
Validity:
means the instrument used for measurement really measures what it is intended to measure, meaning are we collecting necessary information and only the necessary information.
For checking validity, a pilot study of atleast 50 questionnaires will be made anda dummy report shall be prepared to check if all the questions are covered and no data remains unused.
Ethical considerations:Due care to be taken to ensure that no information obtained affects the interests – financial /reputational or otherwise of the participants/Projects whose data is obtained for study.
Findings:
- The Value of Unsold Housing Inventory lying Unsold/Vacant as on September 2019 stands at 9.38 Lakh Crore.It amounts to 5 % of the India’s GDP.
- More than 13 Lakh flats remain Unsold across India
- Out of the Total Unsold Housing Inventory (13.98 Lakh Units) , 85 % of the flats falls under Affordable Housing
- Unsold Inventory has increased 4.66 times during the period year 2009 – Year 2018
- Housing Real Estate was primarily Investor driven and focussed on High End Flats.
- With the New regulations like RERA, GST and also due to Demonetisation, the role of the Cash economy in the Real Estate has taken a retreat.
- Institutional funding to Real Estate is restricted due to Prompt Corrective action (PCA) initiated by RBI resulting in slower completion of the existing projects.
- Earlier, Builders/Developers used to launch multiple projects with no commitment to delivery of the Projects.
- With implementation of RERA, all existing incomplete projects have to be mandatorily registered under RERA and with a commitment for completion of the Projects. This has resulted in builders focussing on completion of existing projects.
- 78 % of the RERA registered projects are yet to be completed in Maharashtra.
Originality of the Research Study: There is no research study undertaken to study and highlight the causes of the rise of the Unsold Housing Units/flats/Inventories in the Real Estate Market in India. In order to fill the above research gap, the study is undertaken.
Conclusion:
- The research study on the unsold housing stock will help tounderstand the causes of the rise of Unsold Inventory and its impact on affordable Housing.
- The asset value of the properties locked for wants of sale is a drag, hampering the growth on the economy.
- It will help in the creation of employment, MSME sector, bringing the much needed confidence towards investment back into real estate.
- It will bring help in achieving the Government of India (GOI) mission of “Housing for all” by year 2023.
- It will help in stabilising the real estate and strengthen the overall economy.
Limitation of the Study:
- The Housing Market is a dynamic market. It gets impacted with time and Government of India Policies.
- The Survey is restricted to Pune, Pimpri Chindwad Municipal Corporation
- The research is based on, Quantitative descriptive- causal design where data collected is a snapshot for cross-sectional studies and not the longitudinal Study.
- The research period considered for the study is only 03 years.
References:
Min-ji K woun, Sang-Hyo Lee, Ju-Hyung Kim, and Jae –Jun Kim (2011).Dynamic cycles of unsold new housing stocks, investment in housing and housing supply – demand. Mathematical and Computer Modelling 57(2013) pp.2094-2105
Goro Takahashi (2015). Two main Conditions for Collapse of the Bubble Economy of China- large Number of unsold Houses and Deregulation of Deposit Interest rates. Journal of Financial Risk Management (2015) 4, 40-55doi:10.4236/jfrm.2015.41005
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