A STUDY ON IMPACT OF CONSUMER INDICES ON HOUSING PRICE INDEX AMONG BRICS NATIONS

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1 International Journal of Civil Engineering and Technology (IJCIET) Volume 9, Issue 5, May 2018, pp , Article ID: IJCIET_09_05_130 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed A STUDY ON IMPACT OF CONSUMER INDICES ON HOUSING PRICE INDEX AMONG BRICS NATIONS Dr. R. Krishnaraj Associate Professor, School of Management, K. Sankara Moorthy Assistant Professor, School of Management, G. Kumar Assistant Professor, School of Management, Dr. I Francis Gnanasekar Associate Professor, Department of Commerce, St. Joseph's College (Autonomous), Tiruchirappalli, Tamilnadu ABSTRACT Status of Real Estate Sector in a country becomes an important measure of the economic situation in a nation. It becomes significant to understand the consumer behavior towards the choice of housing and a cross country analysis would throw lights on a global viewpoint of the Housing trends. This study tries to find the relation between the consumer Indices like consumer confidence Index, Consumer spending Index and Consumer price index and their relation along with the Housing Index Keywords: Housing Index, Consumer Index, Volatility Cite this Article: Dr. R. Krishnaraj, K. Sankara Moorthy, G. Kumar and Dr. I Francis Gnanasekar, A Study on Impact of Consumer Indices on Housing Price Index Among Brics Nations, International Journal of Civil Engineering and Technology, 9(5), 2018, pp INTRODUCTION Housing forms one of the basic amenities of mankind and has become an investment avenue in the present era. Realty sector has undergone major fluctuations due to various factors like inflation, increase in prices of raw materials and government policies. Analysis of consumer editor@iaeme.com

2 A Study on Impact of Consumer Indices on Housing Price Index Among Brics Nations indices alongside realty indices gives us a clear understanding of the impact of consumer parameters. Analysis of consortium of countries from diverse forms of government gives us a global viewpoint of the various realty parameters. BRICS nations comprising oof Brazil, Russia, India, China and South Africa has a diverse profile. Analyzing the BRICS nations gives a global perspective for the builders and investment analysts for making informed decisions in the realty sector. 2. LITERATURE REVIEW Housing market recovery from a downturn has been considered as a vital indicator for the performance in an economy(housing Europe, 2017). Awareness about the financial products relating to the ownership of houses may cause an enormous change in the market among the consumers. In an adverse market, there is a potential for investment that may result at a greater return in a long run(watson, 2010). Land use and planning regulations by the respective country policies has a significant impact on the housing demand and supply. As policies vary among geography, for an international real estate dealer it becomes important to diversify the assets to be successful(caldera & Johansson, 2013). Natural calamities like Flood, Cyclones etc. in a particular geographic location impacts the price of the housing to greater extent. Predicting the proneness to the natural calamity and understanding the history of location for any such experiences becomes mandatory before the investment in made(lamond, Proverbs, & Hammond, 2010). Dwelling age and depreciation of housing form the sensitive factors in determining the price of the housing for further sale(goodman & Thibodeau, 1995). Amenities in a particular location also affect the pricing of the housing. Crime Rates in an area is a more sensitive factor that impacts housing development(kiel & Zabel, 2008). Hedonic imputation model for housing price estimation is found to be accurate and robust in determining the same(goh, Costello, & Schwann, 2012). Hedonic imputation model for housing price estimation is found to be accurate and robust in determining the same(goh, Costello, & Schwann, 2012). Hedonic imputation model for housing price estimation is found to be accurate and robust in determining the same(goh, Costello, & Schwann, 2012). Classic theory suggests that the real estate market cycle reflects the consequences of an inherent self-correcting pattern(tsai, 2013). In volatile markets, the booms in the prices are short lived and the price elasticity might be in unpredictable trends. Migrating of the richer neighborhoods to the poorer neighborhoods has a greater impact on the price level fluctuations in a given market(guerrieri, Hartley, & Hurst, 2013). Migrating of the richer neighborhoods to the poorer neighborhoods has a greater impact on the price level fluctuations in a given market(guerrieri, Hartley, & Hurst, 2013) Research Methodology Data on the BRICS nations has been extracted from trading economics dataset and analyzed using SPSS and MS Excel. Karl Pearson coefficient of correlation has been employed to study the impact of the consumer indices over the realty index. Data Analysis and Interpretation: 3. HOUSING INDEX Housing index is constructed by the changes in the housing prices in particular market where the transaction on Housing is carried out editor@iaeme.com

3 Dr. R. Krishnaraj, K. Sankara Moorthy, G. Kumar and Dr. I Francis Gnanasekar Brazil China India Russia South Africa Based on the above table we could infer that South Africa has a higher price in the housing market while Russia has the least performance in the realty segment. India has got an average fluctuation over the years Consumer Confidence Index Consumer confidence index gives an idea about the consumer perception towards purchase on high value Products and towards critical purchase decisions. Brazil China India Russia South Africa Based on the above table we could infer that china has a higher consumer confidence index with Points, while Russia has the least consumer confidence index with lease value of -8. India has never had a negative value for the consumer confidence index, which is a positive aspect for the business investors making India an attractive investment arena Consumer Spending Consumer spending index gives an idea about the consumption of final goods in the country in which the measurement in taken. Brazil China India Russia South Africa Based on the above table we could infer that South Africa has the highest value in consumer spending with , while Russia has the least consumer spending index value with India has reached the lowest value of 4470 in the past, while the present value shows a steady improvement from the previous value Consumer Price Index Consumer price index is a measure of inflation over the variety of goods and services in a particular economy which gives an idea about the price profile of goods based on various decisions and changes in a country. Brazil China India Russia South Africa From the above table we could infer that Brazil has the highest consumer price index value of while china has the lowest Consumer price index of Highly populated countries like India and China have a steady Consumer price index without much deviation in their value editor@iaeme.com

4 A Study on Impact of Consumer Indices on Housing Price Index Among Brics Nations 4. IMPACT OF CONSUMER CONFIDENCE ON HOUSING INDEX housing consumer confidence Pearson Correlation housing Sig. (2-tailed).643 Pearson Correlation Consumer confidence Sig. (2-tailed).643 Consumer confidence and Housing index There is weak negative relationship between Consumer confidence and Housing Index. 5. IMPACT OF CONSUMER SPENDING ON HOUSING INDEX housing Consumer spending housing Consumer spending Pearson Correlation Sig. (2-tailed).051 Pearson Correlation Sig. (2-tailed).051 Consumer spending and Housing index.876. There is strong positive relationship between Consumer spending and Housing Index. 6. IMPACT OF CONSUMER PRICE INDEX ON HOUSING INDEX housing Consumer price index housing Consumer price index Pearson Correlation Sig. (2-tailed).839 Pearson Correlation Sig. (2-tailed).839 Consumer price index and Housing index There is weak negative relationship between Consumer spending and Housing Index. 7. CONCLUSION Consumer Spending Index has a positive correlation with housing index. Consumer spending may be considered as a predictor variable in making decisions regarding Housing investment and policy decisions. Since there is a higher employment generation happens in the real estate sector, it becomes important to preserve the sector from any crisis. Unemployment might also lead to higher crime rate in a particular country. Consumer price index has a negative correlation. Consumer realizes the importance of savings in an adverse market editor@iaeme.com

5 REFERENCES Dr. R. Krishnaraj, K. Sankara Moorthy, G. Kumar and Dr. I Francis Gnanasekar [1] Caldera, A., & Johansson, Å. (2013). The price responsiveness of housing supply in OECD countries. Journal of Housing Economics. [2] Englund, P., & Ioannides, Y. M. (1997). House Price Dynamics: An International Empirical Perspective. Journal of Housing Economics. [3] Glaeser, E. L., Gyourko, J., & Saiz, A. (2008). Housing supply and housing bubbles. Journal of Urban Economics. [4] Goh, Y. M., Costello, G., & Schwann, G. (2012). Accuracy and Robustness of House Price Index Methods. Housing Studies. [5] Goodman, A. C., & Thibodeau, T. G. (1995). Age-related heteroskedasticity in hedonic house price. Journal of Housing Research. [6] Guerrieri, V., Hartley, D., & Hurst, E. (2013). Endogenous gentrification and housing price dynamics. Journal of Public Economics. [7] Housing Europe. (2017). The State of Housing in the EU The state of housing in the EU [8] Kiel, K. A., & Zabel, J. E. (2008). Location, location, location: The 3L Approach to house price determination. Journal of Housing Economics. [9] Kim, K. H., & Renaud, B. (2009). The global house price boom and its unwinding: An analysis and a commentary. Housing Studies. [10] Lamond, J., Proverbs, D., & Hammond, F. (2010). The impact of flooding on the price of residential property: A transactional analysis of the UK market. Housing Studies. [11] Levin, E. J., & Pryce, G. B. J. (2009). What determines the price elasticity of house supply? Real interest rate effects and cyclical asymmetries. Housing Studies. [12] Miller, N., & Peng, L. (2006). Exploring metropolitan housing price volatility. Journal of Real Estate Finance and Economics. [13] Tsai, I. C. (2013). Housing affordability, self-occupancy housing demand and housing price dynamics. Habitat International. [14] Watson, M. (2010). House price Keynesianism and the contradictions of the modern investor subject. Housing Studies. [15] Dr. Jay Desai and Dr. Nisarg A Joshi. Relation between Open Interest and Volatility in Futures Markets. Journal of Management, 5(1), 2018, pp [16] Dr. G.S. David Sam Jayakumar and L. Vijayalakshmi. Modeling the Stock Volatility of top Industrial Returns Listed in BSE. International Journal of Management, 7(2), 2016, pp [17] Dr. M. A. Shakila Banu and K. Saranya. A Study on Comparitive Analysis of Volatility of Equity Share Prices for Selected Steel Companies in India. International Journal of Management, 7(2), 2016, pp [18] Dr. Hemant J. Katole, A Study of Contract Labour at A Real Estate and Construction Company editor@iaeme.com