BA7032 Final Research Proposal – Feedback front sheet
Attach this form to your Research Proposal, which should be stapled with a single staple. Do not put it in a plastic sleeve or folder. TO BE COMPLETED BY THE STUDENT | Student ID:K1359443 | Student’s name:Romil Tulshan | Degree:MSc in Accounting and Finance | Supervisor’s name:Dr Jia Miao | Working title of proposed study:Qualitative and Quantitative investigation of property prices in Tier 2 and 3 cities of India | TO BE COMPLETED BY THE MARKER(To provide feedback, please tick attributes in any column that apply) | Learning outcome and weighting* | Fail | Pass | Commendation | Distinction | Clarity of research problem and scope(10%) | UnclearUnfocused | Some attempt at clarity and focus of the aims and objectives | Clear and focused aims and objectives and are ‘doable’ within the timeframe | Clear and sharply focused aims and objectives and are ‘doable’ within the timeframeRelated to student’s masters degree | Critical evaluation of the main literature(40%) | Eclectic, disorganised, irrelevant or out of dateNo research questionsNot linked to research questions | Some attempt to identify relevant literature and link with the main theory (ies) of the research topicSome attempt to link to research questions | Critical evaluation of main literature and link with the main theory (ies) of the research topicLinked to clear research questions | Excellent review of main literature and clear link with the main theory (ies) of the research topicRelated to academic debate and linked to clear research questions | Proposed methodology and data deriving from the literature(40%) | UnclearUnfocusedUnjustified Unclear data source | Some attempt at clarity and focus with justificationValid sources of data | Clear and focused with clear justification | Clear and sharply focusedRelated to academic debate | Presentation and referencing(10%) | Inappropriate writing stylePoor referencing | Some attempt at appropriate writing styleSome weaknesses in referencing | Writing style follows academic conventionsAppropriately referenced | Clear and accessible writing style that follows academic conventionsAppropriately referenced | Additional feedback (continue overleaf as necessary) | Mark: | Marker’s signature: | Date: |
* Indicative

Qualitative and Quantitative investigation of property prices in Tier 2 and Tier 3 cities of India.

Abstract:
The research proposal is carried out to make a dissertation on real estate. It mainly states, reviews and analyses the various articles and cases on changes in property prices, investors view and motive of the tier 1, 2 and 3 cities of India. The objective was to learn the present scenario of the real estate in the country to further carry out business and expand myself into this field. The data collected are from reliable sources and hence would be used in dissertation to carry out various ratios, findings and conclusion. The result of this proposal indicate that tier 2 and 3 cities are better in terms of investment point of view as it got better returns in the last few years and same can be assumed for future period.
Declaration:
I declare that all materials in this dissertation that are not my own work have been acknowledged and that no materials from my previous degree(s) have been included.
I have kept all materials used in this research, including samples, research data, preliminary analysis, notes and drafts, and I can produce them on request.

Contents 1.0 Introduction: 5 1.1 Definition of terms: 5 1.2 Aims and Objectives: 5 1.3 Rationale: 5 2.0 Literature Review: 6 2.1 Factors Affecting Growth 7 2.2 Real Estate Companies 8 3.0 Research Methodology: 8 4.0 Data Collection Method & Analysis: 9 5.0 Data Analytical Tool: 10 6.0 Conclusion: 10 7.0 Proposed Timetable: 11 8.0 References 12

1.0 Introduction:
India is considered and analysed as one of the most emerging economies of the world. Various industries and businesses are flourishing in this developing country; and real estate is one such business which has done well in the past and has great potential in coming years. It is 2nd most highly populated country in the world, with statistics showing 1.2 billion in 2012 and is world’s largest democracy (Worldbank, 2014). It has a total area of 12.6 lakh sq. miles (Infoplease, 2014). The research proposal is presented for the dissertation on real estate for understanding the changes in property prices of different cities and the factors affecting the price fluctuations in those areas. It describes the methodologies used and the data collected which contributed immensely to arrive to a conclusion.
1.1 Definition of terms:
Real Estate can be defined as a piece of land and the properties on it (Thefreedictionary.com, 2014). The real estate includes construction of commercial buildings, industrial zones, residential projects and trading in vacant properties.
1.2 Aims and Objectives:
Identify the growth in property prices of tier 2 and 3 cities as compared with tier 1 city. Review the various literatures on changes in prices of properties and analyse the factors related to it. Obtain data showing the changes in prices of different cities and compare the growth rate of tier 1 cities on one side and Tier 2 and 3 cities on other.
1.3 Rationale:
Considering my future business and liking in the field of real estate; it is necessary for me to understand the present development in this field. I need to invest in properties in India depending upon the growth; availability of land and most importantly the city should have growing rates and must be in my budget. The analysis would help me to come to a conclusion which would be used at the time of actual investments in properties back in India.

2.0 Literature Review:
The first article says that growing affordability and sturdy demand among the people will continue the rate of land in tier 2 and tier 3 cities. The boom seen in tier 1 cities and metropolitan cities is carried to smaller cities as there is a willingness to buy a home by the people of the country. As per Census 2001, India comprises of 401 class 2 cities and 1151 class 3 cities. As per the ministry of urban development, class 2 cities have population in the range of 50,000 – 1, 00,000 and class 3 cities have a population in the range of 20,000 to 50,000 people.
According to Macquarie Research Equities, affordability to own house has increased due to lower mortgage rates and tax breaks. According to Reserve Bank of India, the number of loan accounts for housing in metropolitan cities surged to 3.05 m in ‘05 from 1.87 m in ’00; performing a growth of 63 per cent in 5 years (Real estate boom spills to non-metro cities now, 2006).
Adding further, notorious big players have invested millions of money in and around tier 2 and tier 3 cities to earn huge profits in the future. Companies like Unitech and Mahindra Gesco also got its stock growth by 31 % and 10 % respectively, owing to huge investments in the country. Another reason for the growth in tier 2 cities was retail revolution. A steep increase in demand for commercial zones leads to the growth of land prices in small cities. According to Knight Frank, one of the property agents, year ’06 will also see a steady growth in property market owing to foreign investors’ demand in the coming days (Real estate boom spills to non-metro cities now, 2006).
Another important article states that the saturation level in metro cities have led to the deviation of builders and end dwellers to tier 2 and tier 3 cities in the past decade, which has a very good potential for economic growth and construction opportunities. Ahmadabad, Kanpur, Chandigarh, Patna, Dehradun, Pondicherry, Pune etc. are tier 2 cities having population around 1 million, while other small cities like Nasik, Baroda, Trichy, etc. have population less than 1 million comes under tier 3 cities. Some basic advantages these cities have are skilled labour, ample of land, availability of basic amenities and connectivity to near- by metro cities (Tier 2 and 3 cities, 2013).
Real estate firms and IT firms are shifting to tier 2 and 3 cities considering cheap real estate and manpower. Many other factors that are lucrative and driving growth to tier 2 and 3 cities remain as quality lifestyle, emergence of IT companies, walk-to-work concept, etc. This led to other sectors’ like FM radio, banks, hotels; electronic companies like Lenovo, Sony India are planning to expand in these cities to mark their foothold and thus increase their profits. In cities like Mysore and Mangalore, where the cost of rent is very reasonable with good infra developed, pre-schools have been growing at the rate of 120%. Some cities of Gujarat state like Vadodara, Surat and Ahmedabad have made huge progress industrially.
2.1 Factors Affecting Growth * A number of factors co-exist that affects the growth of tier 2 and 3 cities. As per a study of Top 10 emerging business destinations in India by Cushman &Wakefield, global real estate solution providers, it is the increasing disposable money of people that led to the growth of Tier 2 and 3 cities in India. * Other factors that attract the investors here is the supportive state and local government policies, availability of skilled labour at cheap prices and real estate at reasonable prices. * Another important factor is the availability of skilled manufacturing industries in sectors like automotive, IT, pharmaceuticals, and engineering flagging the way for rapid industrialization (Tier 2 and 3 cities, 2013). * Ahmedabad, Bhubaneswar, Chandigarh, Coimbatore, Jaipur, Kochi, Indore, Nagpur, Vadodara and Visakhapatnam are the top 10 emerging cities which had to bear lesser day to day cost, less salary expectations and reduced price fluctuations to new ventures which are scheduling to start their businesses in these cities. * The improvement in connectivity has made these cities more preferable for investors; with international airports being a part of them, NRI’s also prefer to travel and invest in these cities. * One of the most positive factors for investors is the increment of property prices in these cities, which is gradual unlike a steep growth in metro cities (Tier 2 and 3 cities, 2013).
2.2 Real Estate Companies
Leading real estate companies and builders like Tata Housing, Lodha Builders, Raheja, Ansal Housing and DLF have initiated schemes in these smaller cities. Sahara Infrastructure and Housing have recently launched multiple integrated townships spread across 900 acres in Tier 2 and 3 cities like Pune, Solapur, Aurangabad, Bareilly, Jodhpur, Gwalior and Kashipur. Seven already under construction projects are going on in cities like Nagpur, Jaipur, Ahmedabad, Indore, Lucknow, Satna and Coimbatore. Tata Housing Development Company Ltd has entered into long term plans with tier 2 and 3 cities. Rajeeb Dash, Head- Marketing of the firm confirms that Tata is planning over long time to sustain growth in these cities which are growing faster and have better returns as compare to tier 1 cities (Tier 2 and 3 cities, 2013). Another major real estate company, Ansal has its hi-tech residential township in Lucknow which is spread over 3500 acres by the name Sushant Golf City. One more real estate company, Sattva Group has forayed into tier 2 cities and looked very positive for it.
As per moneycontrol.com, the future of real estate is not only in metros but also in tier 2 and tier 3 cities; India has highest rate of urbanization among BRIC countries which clearly shows the development and growth in India that took place and is calculated to be continued unless it becomes one of the strongest economy of the world.
All these reviews, factors investment propositions are co related and tell us about how the prices have affected in the past few years.
3.0 Research Methodology:
Both qualitative and quantitative methods are to be used to determine the solutions of the above mentioned problems. In case of qualitative method, the reviews of journal articles and cases would be done to understand the responses and reactions of investors and depending factors. On the other hand, in quantitative method, inferential statistics would be used to reach to a more concrete solution about the changes in prices for respective cities at a given period of time.

4.0 Data Collection Method & Analysis:
All the data that will be collected would be secondary data which is available online. Data related to change in prices of land per sq. ft. of specific cities would be collected from sites like magicbrick.com. It gives a detailed description of changes in price quarter on quarter (q-o-q) and year on year (y-o-y) for the cities about which analysis is to be done. It shows the upper price range, average price range and lower price range for residential plots, residential house and multi storey apartments. Also, the Office of National Statistics of India aids in deriving Net City Domestic product in real estate y-o-y. It helps in determining the change in the overall prices of property, housing and commercial zones of a city.
By comparing the increase in prices of tier 1 cities on one side and comparing it with the increment in prices of tier 2 and tier 3 cities. This would help in analysing the percentage return on investment (ROI) that an investor would earn if it has to invest in India. Hence, it would be interesting and useful for me to understand the real estate business in more depth and forecast the coming years of this industry as a whole.
The comparison of prices in residential, commercial and industrial zones would be done for the last 10 years of tier 1, 2 and 3 cities using magicbricks.com price which are government approved and checked by land revenue department. This would help in judging the growth in prices in the last decade in respective areas and assuming the same growth in the coming days considering the factors mentioned above.

5.0 Data Analytical Tool:
Apart from Inferential Statistics, Time series vs. cross-sectional data analysis would be used to understand the price variations after uniform time intervals. It would help in observing a trend in property prices and assuming short term future trends.
Another method that could be use of market trends that gives a snapshot of previous month’s house sales, sale prices and foreclosure fillings of mortgage performance data in a datasheet which can be used to analysed the rates.
Any other related method which seemed to be useful for data analysis would be used to get the best price of different sectors and zones of the country.

6.0 Conclusion:
After going through the various articles of journals and the data collected, it can be analyzed that tier 2 and Tier 3 cities of India are growing rapidly in the last few years owing to the availability of required factors like land at reasonable yet growing rates, job opportunities for working class, mainly in the IT and real estate sector. Also, the presence of quality schools and colleges keep the new generation stick to those cities and also give them the opportunities to fulfill their dreams in those areas.
It also can be concluded that tier 1 cities though are more developed as compare to Tier 2 and Tier 3 cities, the sky scrapers and their sky touching rates makes it very grim to buy property in those areas. A saturation level is observed in the metro cities which states that the return on investment would be better and hence it is adequate to invest in smaller and growing cities.

7.0 Proposed Timetable:
Research proposal made as per this timetable Working Durations | Questions | Descriptions of the topic covered | Week 1:12 – 19 September | Confirming On Topic | Confirmation to continue the proposal and hence dissertation on real estate. Data Collection started | Week 2:20-26 September | Analyzing Journals | Various resources like i-cat and online case studies were studied to get information and data related to real estate. | Week 3:27-02 September | Literature review and selection of methodology | Various data were shortlisted and finally the appropriate ones were used in literature review | Week 4:03-09 October | Data Analysis and Results | The data analysis using statistical method, ratios and comparison to come to a conclusion. |

Word Count : 2312

8.0 References

Corelogic.com, (2014). [online] Available at: http://www.corelogic.com/solutions/real-estate-analytics-solutions.aspx [Accessed 20 Jun. 2014].
Infoplease, (2014). [online] Available at: http://www.infoplease.com/ipa/A0004379.html [Accessed 18 Jun. 2014].
Mooneycontrol, (n.d.). [online] Available at: http://www.moneycontrol.com/master_your_money/stocks_news_consumption.php?autono=692245 [Accessed 19 Jun. 2014].
Siliconindia.com, (2014). [online] Available at: http://www.siliconindia.com/realestate/news/6-Key-Factors-That-Influence-Property-Valuation-in-India-nid-140833.html [Accessed 19 Jun. 2014].
Thefreedictionary.com, (2014). [online] Available at: http://financial-dictionary.thefreedictionary.com/real+estate [Accessed 19 Jun. 2014].
Worldbank, (2014). [online] Available at: http://www.worldbank.org/en/country/india [Accessed 18 Jun. 2014].
Real estate boom spills to non-metro cities now. (2006). [online] Available at: http://ezproxy.kingston.ac.uk/docview/459697839?accountid=14557 [Accessed 7 Oct. 2014].
Tier 2 and 3 cities. (2013). NBM & CW. [online] Available at: http://ezproxy.kingston.ac.uk/docview/1412210232?accountid=14557 [Accessed 9 Oct. 2014].