Factors affecting property prices in National Capital Region
working
The real estate sector of India is witnessing rapid growth. Not only does it provide housing and commercial spaces to people, but it is also accepted as a source of income for many. There are multiple ways in which a buyer chooses to utilise real estate. For instance, they could hold the purchased property to resell it at a higher price or rent out the real estate for additional income. Another means of gain is of converting the available real estate into a homestay or hotel. Although each has its own benefits, a buyer seeks to make the optimal choice to maximise the returns on his investment.
There are many factors which affect the prices and trends in real estate for a dynamic market like NCR (National Capital Region). Preliminary analysis shows us that there are three main categories of factors: demographic, socioeconomic, and infrastructure. The goals of this study are to identify them and establish the linkage between the factors and the prices of property. This purpose of this study is to help property buyers foresee trends in real estate and make optimal investment decisions.
To identify the factors affecting property prices in Delhi NCR
Aim: The first goal is to carry out a literature review to identify the factors affecting property prices in Delhi-NCR. Delhi-NCR, being a sprawling metropolitan area, exhibits a dynamic real estate market influenced by a multitude of variables. These factors can be broadly categorized into socioeconomic, infrastructural, environmental, and demographic aspects. By meticulously identifying and analyzing these factors, the study aims to provide a detailed understanding of the diverse and interconnected elements that drive property prices in the region. This foundational knowledge is crucial for stakeholders such as investors, policymakers, and urban planners to make informed decisions and strategize effectively in the real estate market.
Methodology: It involves a systematic review of at least 50 empirical studies conducted in the past showing:
- author name (year)
- aim of the study
- methodology adopted
- findings
To contribute and publish select a pending milestone.
Completed
There are no completed milestones.
Pending
Real estate market of NCR
Purpose: The purpose of this milestone is to review the present status of the real estate market in the NCR region. This involves an in-depth analysis of the current market trends, key players, property types, pricing patterns, and market dynamics. The goal is to provide a comprehensive overview that sets the foundation for understanding the factors affecting property prices.
Methodology: Use recent reports and news articles to:
- Study the market overview (current real estate market size, key segments within the market (residential, commercial, industrial, retail), recent trends in property transactions and price movements)
- Identify key players and Stakeholders
- Identify the role of governments
- Review property types and prices (for example hotspots with more market appreciation)
Structure: To achieve this milestone, write a 1500 words article following the below structure.
- Introduction
- Market overview of real estate in NCR
- Key players and stakeholders
- Role of governments in real estate of NCR
- Property types and prices
- Conclusion/Summary
- References
Factors affecting real estate market of NCR
Purpose: The purpose of this milestone is to conduct a thorough review of the various factors influencing the real estate market in Delhi-NCR. This includes demographic, socioeconomic, infrastructure, and environmental factors. The aim is to understand how each of these elements impacts property prices and market dynamics.
Methodology: Perform a systematic review of 45-50 studies showing the effect of the variables given in the attachment. Select studies with the following criteria:
- Specific to Indian real estate market
- Published after 2010
- Published in recognised journals
- Having empirical research
Structure: To achieve this milestone, write a 1500 words article following the below structure.
- Introduction: Start the article by explaining the factors affecting real estate market in India:
- Demographic
- Socioeconomic
- Infrastructure
- Environmental
- Methodology:
- Introduce your chosen methodology, i.e., systematic review of literature. Explain the elements you will focus on, i.e., identifying the driving forces of digital systems in retail stores.
- Studies selection process: Clearly articulate the criteria used for selecting studies such as keywords used, and sources or libraries used.
- Inclusion and exclusion criteria: explain the criteria employed to include or exclude studies, like year of publication, language, format, publication credibility, etc.
- Analysis: This is the main section presenting the systematic review. It will have a table showing the following columns. Summarise each of the 30 studies in this format.
- Author (year)
- Aim of the study
- Findings (explain the driving forces of digitalization this author found)
- Variables identified
- Discussion: Summarize and synthesize the findings from the selected studies.
- Impact of demographic factors on real estate market of India
- Impact of socioeconomic factors on real estate market of India
- Impact of infrastructure factors on real estate market of India
- Impact of environmental factors on real estate market of India
- Conclusion: Summarize the key findings
- References
To determine the linkage between socioeconomic, demographic, infrastructure, and environmental factors and property prices
Aim: The second goal is to collect the data pertaining to the identified factors: socioeconomic, demographic, infrastructure, and environmental in Gurgaon and Faridabad region and statistically establish the linkage using regression.
Methodology: It involves data collection of all identified variables for Gurgaon and Faridabad regions for the years 2020, 2021, 2022, and 2023. The data will involve:
- compilation in MS Excel
- preprocessing & transformation
- trend analysis
- assumption tests
- regression test
- Johansen cointegration test
- VECM
To contribute and publish select a pending milestone.
Completed
There are no completed milestones.
Pending
Aim: In the previous milestone we identified all the factors which affect real estate market in India. This is the first milestone in Goal 2 and involves statistical data collection. Here, you must collect historical statistical data of all the identified variables from various sources. It will help us with analysis of impact of these variables on the property market of Gurgaon.
Methodology: A list of all variables, sub-variables, and the sources are explained in the table inside the attachment. Collect the data of Gurgaon region only. Arrange the data in the form of an Excel file containing separate sheets for each sub-variable. This is because the measurement unit for every variable will be different. Data should be year-wise, from 2013 to 2023.
Submission: Submit an Excel file containing the data.
Real estate data transformation
Aim: This milestone undertakes step 1 of our analysis-ie., cleaning and processing the data. Herein, once you get the data approved from us, the focus would be only declaring the dataseries to be time series and doing the log transformation. In simple terms, it means that the data will be ready for regression testing.
Methodology: Complete steps 2-6 of analysis procedure listed in the attached document. Remember to save all the commands in a do file of STATA and also all the results. The procedure of saving the results and commands is mentioned here. Remember you need to have each milestone log created. Work in same file for the entire project.
Submission: Your submission must include:
- Excel file containing the final dataset used
- STATA files having results and commands
- Article of 500 words showing interpretation of the data
Article structure: Write a 500 words interepretation explaining:
- Introduction to the dataset (variables, time period, etc)
- Results of log transformation
- About the next step in the analysis
Trend analysis of real estate market in Gurugram
Aim: The milestone aims to present the trend analysis of "housing" related sub-variables. Housing is the dependent variable of our study. it has the following sub-variables:
- HPI
- Housing credit
- RESIDEX
- No. of units sold
- Price per square foot
- No. of new units launched
- No. of hotel rooms
- Average rental yield
Methodology: Perform step 7 explained in the attached document on the log transformed variables only. For this milestone, the previous milestone "log transformation" must be completed. Obtain that dataset and log transformation dataset from the Module Handler. Then, draw the line graph to have trend analysis. Once line graph is drawn, the focus is on analyzing the line graph. To analyze the graph there is need of understanding the movement of the variable over the time and then explain what could be the reason for this movement using the external secondary source. Remember, the source you are using need to be cited and it should be authentic i.e. either a paper pubished in scopus or springer journals or the government website based information.
The writing of the trend analysis should be done within 400 words for all the ICT variables. A good example of trend analysis is presented above in the "Aim" section and here.
Submission: Your submission must include:
- STATA files containing results of trend analysis
- Word document having the article of 500 words.
Structure of the article: Follow the below structure to write the article:
- Introduction
- Trend analysis of HPI
- Trend analysis of Housing credit
- Trend analysis of RESIDEX
- Trend analysis of No. of units sold
- Trend analysis of Price per square foot
- Trend analysis of No. of new units launched
- Trend analysis of No. of hotel rooms
- Trend analysis of Average rental yield
- Summary
- List of references
Stationarity test of real estate data of Gurugram
Aim: The milestone aims to present the stationarity test of all sub-variables and variables in our dataset. Find the list of the variables in document 'Milestone 2' attached .
Methodology: Firstly, you cannot work on this milestone until the previous milestone 'Trend analysis' is completed. Obtain that dataset from your Handler.
Next, perform steps 8-10 of the 'Analysis procedure' document attached on the dataset which your Handler sends to you. Remember stationarity test will be done with log transformed variables. Herein, the criteria of the evaluation is same as listed in the analysis procedure. Now, what you will need is to use the data given to use for evaluation. Herein, state the p-value for each variable and assess it whether the variable is stationary or not. In case the variables are non-stationary how you have removed the non-stationarity from the data.
Submission: Your submission must include:
- STATA files containing results of stationarity test.
- Word document having the article of 500 words.
Structure of the article: Follow the below structure to write the article:
- Introduction
- Findings of the stionarity test (table + interpretation of the values)
- Summary
- List of references
Here is a sample article for reference.
Normality test of real estate data of Gurugram
Aim: The milestone aims to present the normality test of all sub-variables and variables in our dataset. Normality is a part of "assumption testing" of social sciences data. Find the list of the variables in document 'Milestone 2' attached .
Methodology: Firstly, you cannot work on this milestone until the previous milestone 'Trend analysis' is completed. Obtain that dataset from your Handler.
Next, perform steps 11 of the 'Analysis procedure' document attached on the dataset which your Handler sends to you. Herein Shapiro wilk test is used as stated in analysis procedure. For this you will again need to interpret the normality result to decide which variables to be considered for further analysis. Only normal variables will be taken. Non-normal variables are eliminated from the analysis.
Submission: Your submission must include:
- STATA files containing results of normality test.
- Word document having the article of 500 words.
Structure of the article: Follow the below structure to write the article:
- Introduction
- Findings of the test (table + interpretation of the values)
- Summary
- List of references
Here is a sample article for reference.
Autocorrelation test of real estate data of Gurugram
Aim: The milestone aims to present the autocorrelation of all sub-variables and variables in our dataset. Autocorrelation is a part of "assumption testing" of social sciences data. Find the list of the variables in document 'Milestone 2' attached .
Methodology: Firstly, you cannot work on this milestone until the previous milestone 'Trend analysis' is completed. Obtain that dataset from your Handler.
Next, perform steps 12-16 of the 'Analysis procedure' document attached on the dataset which your Handler sends to you. Herein, the Durbin Watson test is used as mentioned in analysis procedure. For interpretation consider that the value should be between 1.5-2.5 for rejection of serial correlation else correlation is present.
Submission: Your submission must include:
- STATA files containing results of autocorrelation test.
- Word document having the article of 500 words.
Structure of the article: Follow the below structure to write the article:
- Introduction
- Findings of the test (table + interpretation of the values)
- Summary
- List of references
Here is a sample article for reference.
Heteroskedasticity of real estate data of Gurugram
Aim: The milestone aims to present the heteroskedasticity of all sub-variables and variables in our dataset. Autocorrelation is a part of "assumption testing" of social sciences data. Find the list of the variables in document 'Milestone 2' attached .
Methodology: Firstly, you cannot work on this milestone until the previous milestone 'Trend analysis' is completed. Obtain that dataset from your Handler.
Next, perform steps 12-16 of the 'Analysis procedure' document attached on the dataset which your Handler sends to you. Herein, Breusch Pagan test must be used. The criteria is to have value more than 0.05 for p to have the non-rejection of the null hypothesis of constant variance showing heteroskedasticity is not present.
Submission: Your submission must include:
- STATA files containing results of heteroskedasticity test.
- Word document having the article of 500 words.
Structure of the article: Follow the below structure to write the article:
- Introduction
- Findings of the test (table + interpretation of the values)
- Summary
- List of references
Here is a sample article for reference.
Multicollinearity of real estate data of Gurugram
Aim: The milestone aims to present the multicollinearity of all sub-variables and variables in our dataset. It is a part of "assumption testing" of social sciences data. Find the list of the variables in document 'Milestone 2' attached .
Methodology: Firstly, you cannot work on this milestone until the previous milestone 'Trend analysis' is completed. Obtain that dataset from your Handler.
Next, perform steps 12-16 of the 'Analysis procedure' document attached on the dataset which your Handler sends to you. Herein, VIF test will be used and the criteria was to have value less than 10 for all the models. The VIF of less than 10 ensures no multicollinearity. Based on this, the results of each variable will be evaluated.
Submission: Your submission must include:
- STATA files containing results of multicollinearity test.
- Word document having the article of 500 words.
Structure of the article: Follow the below structure to write the article:
- Introduction
- Findings of the test (table + interpretation of the values)
- Summary
- List of references
Here is a sample article for reference.
Impact of socioeconomic, demographic, infrastructure, and environmental factors on real estate market of Gurgaon
Aim: So far in this goal, we prepared the dataset for this study and processed it with assumption tests so that it is ready for regression test. The aim of this milestone is to perform the regression test for the following hypotheses:
- Socioeconomic factors have a relationship with real estate market in Gurgaon
- Demographic factors have a relationship with real estate market in Gurgaon
- Infrastructure factors have a relationship with real estate market in Gurgaon
- Environmental factors have a relationship with real estate market in Gurgaon
A detailed list of all the variables chosen in this study is attached.
For every category of factor, we are checking the impact on the following aspects of 'real estate market':
- Price/ sq. foot
- No. of units sold
- No. of new units launched
- HPI
- Housing credit
- RESIDEX
- No. of hotel rooms
- Average rental yield
Method: Follow steps 12-16 of the 'Analysis plan' document attached. Present the values of adjusted R square, F-value, significance value and coefficient and interpret them after performing hypothesis testing at 5% level of signficiance. The sample of interpreting regression results is given here. Remember the sample is for your understanding of each value but for writing the work will be in paragraph.
Structure of the article: The writing will be in 1000 words for all the models. You need to add some secondary studies, the published paper within past 10 years for supporting your findings. Add the in-text citation for it. The structure of writing would be in this form:
1st model – interpret adjusted R square and F-value, p-value assessment for hypothesis testing, coefficient value examination
Following it the 2nd model and so on
Finally supporting the finding i.e. factors impact the real estate sector of India published with past 10 years.
Long term effect of factors affecting real estate market in Gurgaon
Aim: In the previous milestone, the relationship between socioeconomic, demographic, infrastructure, and environmental factors and real estate market of Gurgaon was established. The aim of this milestone is to affirm the relationship in the long-term by applying the Johansen Cointegration test in STATA.
Methodology: Firstly, you cannot work on this milestone until the previous milestone 'Trend analysis' is completed. Obtain that dataset from your Handler. Next, perform step 17 of the 'Analysis procedure' document attached on the dataset which your Handler sends to you. Herein, you need complete the analysis and interpret the results as given in video given at the end of that document.
Submission: Your submission must include:
- STATA files of the Johansen cointegration test
- 500- words article explaining the results of the Johansen cointegration test
Structure of the article:
- Introduction
- Results of the test
- Summary
- References
Short-Term and Long-Term Influences on Property Prices in Gurgaon
Aim: This is the last step towards establishing the relationship between socioeconomic, demographic, infrastrucutre, and environmental factors and real estate market of Gurgaon. In previous milestone we established the long term relationship with Johansen cointegration test. in this milestone we will check the long term as well as short term effect with VECM test.
Methodology: Firstly, you cannot work on this milestone until the previous milestone 'Trend analysis' is completed. Obtain that dataset from your Handler. Next, perform step 18 of the 'Analysis procedure' document attached on the dataset which your Handler sends to you. Herein, you need complete the analysis and interpret the results as given in video given at the end of that document.
Submission: Your submission must include:
- STATA files of the VECM test
- 500- words article explaining the results of the Johansen cointegration test
Structure of the article:
- Introduction
- Results of the test
- Summary
- References