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CHAPTER 4

DATA ANALYSIS &

INTERPRETATION

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Quantitative analysis:

A business or financial analysis technique that seeks to understand behavior by using complex

mathematical and statistical modeling, measurement and research. By assigning a numerical value to variables,

quantitative analysts try to replicate reality mathematically.

Quantitative analysis can be done for a number of reasons such as measurement, performance evaluationor valuation of a financial instrument. It can also be used to predict real world events such as changes in a real

estate price.

Hypothesis:

Null hypothesis: - There is no significant effect of independent variables (Inflation rate, Unemployment rate and

Interest rate) on dependent variable (Real Estate Prices) at 5% level.

Alternative hypothesis: - There is a significant effect of independent variables on dependent variables at 5%

level.

In this analysis the Dependent variable is Real Estate Prices and the Independent variables are Inflation rate,

Unemployment rate and Interest rate.

CHENNAI

MODEL SUMMARY

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

Change Statistics

R Square

Change F Change df1 df2 Sig. F Change

1 1.000a .999 .998 324.828 .999 581.491 3 1 .030

a. Predictors: (Constant), Interest, Inflation, Unemployment

R Square = 0.999 (99.9%).

The independent variables explain 99.9% of dependent variable (Real Estate Prices).

Significance level is 3%

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CORRELATIONS

Price Inflation Unemployment Interest

Pearson Correlation Price 1.000 .998 .558 -.731

Inflation .998 1.000 .604 -.763

Unemployment .558 .604 1.000 -.871

Interest -.731 -.763 -.871 1.000

Sig. (1-tailed) Price . .000 .164 .080

Inflation .000 . .140 .067

Unemployment .164 .140 . .027

Interest .080 .067 .027 .

N Price 5 5 5 5

Inflation 5 5 5 5

Unemployment 5 5 5 5

Interest 5 5 5 5

There is a positive correlation between dependent variable (Real Estate Prices) and independent variables

(Inflation and Unemployment). Negative correlation between Interest rate and Real Estate Prices

There exist 99% correlation between Inflation and Real Estate Prices.

And there exist 56% correlation between Unemployment and Real Estate Prices.

And there exist 73% correlation between Interest and Real Estate Prices.

Level of significance:

Inflation has 0% level of significance.

Unemployment has 16.4% level of significance.

Interest has 8% level of significance.

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COEFFICIENTSa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) 1221.305 4257.627 .287 .822

Inflation 2683.601 96.832 1.046 27.714 .023 .402 2.487

Unemployment -272.850 220.418 -.062 -1.238 .433 .232 4.310

Interest 47.863 205.899 .014 .232 .855 .153 6.555a. Dependent Variable: Price

The above table explains that there is positive association between Inflation and Interest and Real Estate Prices.

There is negative association between Unemployment and Real Estate Prices.

In this analysis, if we take the independent variables (Inflation, Unemployment and Interest) together, the

significance level is below 0.05 (5%). If we take them separately, the significance level is more than 5% i.e.,

0.433(43.3%) and 0.855(85.5%) for Unemployment and Interest respectively. For Inflation it is only

0.023(2.3%).

MUMBAI

MODEL SUMMARY

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

R Square


1 .999a .999 .995 715.680 .999 286.455 3 1 .043


R Square = 0.999 (99.9%).


Significance level is 4.3%

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CORRELATIONS



Inflation .987 1.000 .437 -.763

Unemployment .319 .437 1.000 -.856

Interest -.652 -.763 -.856 1.000

Sig. (1-tailed) Price . .001 .301 .116

Inflation .001 . .231 .067


Interest .116 .067 .032 .

N Price 5 5 5 5

Inflation 5 5 5 5


Interest 5 5 5 5







Inflation has 0.01% level of significance.


Interest has 11.6% level of significance.

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COEFFICIENTSa

Model


Standardized

Coefficients

t Sig.



1 (Constant) -28876.862 13148.145 -2.196 .272

Inflation 4829.536 274.747 1.217 17.578 .036 .242 4.125

Unemployment 597.670 578.831 .089 1.033 .490 .156 6.429

Interest 1835.301 625.559 .353 2.934 .209 .080 12.465a. Dependent Variable: Price

The above table explains that there is positive association between Inflation, Unemployment and Interest and

Real Estate Prices.




0.36(3.6%).

DELHI

MODEL SUMMARY

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

Change Statistics

R Square


1 1.000a .999 .997 353.596 .999 490.670 3 1 .033


R Square = 0.999 (99.9%).



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CORRELATIONS



Inflation .998 1.000 .437 -.763

Unemployment .386 .437 1.000 -.856

Interest -.731 -.763 -.856 1.000

Sig. (1-tailed) Price . .000 .261 .080

Inflation .000 . .231 .067


Interest .080 .067 .032 .

N Price 5 5 5 5

Inflation 5 5 5 5


Interest 5 5 5 5

There is a positive correlation between dependent variable (Real Estate Prices) and independent variables(Inflation and Unemployment). Negative correlation between Interest rate and Real Estate Prices







Interest has 8% level of significance.

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COEFFICIENTSa

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3088.147 6496.098 .475 .717

Inflation 2612.862 135.744 1.019 19.248 .033 .242 4.125

Unemployment -304.950 285.983 -.070 -1.066 .480 .156 6.429

Interest -45.316 309.070 -.013 -.147 .907 .080 12.465

a. Dependent Variable: Price

The above table explains that there is positive association between Inflation and Real Estate Prices

There is negative association between Unemployment, Interest and Real Estate Prices.




0.33(3.3%).

HYDERABAD

MODEL SUMMARY

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

R Square


1 1.000a 1.000 .998 153.655 1.000 880.551 3 1 .025


R Square = 1 (100%).

The independent variables explain 100% of dependent variable (Real Estate Prices).


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CORRELATIONS



Inflation .999 1.000 .437 -.763

Unemployment .461 .437 1.000 -.856

Interest -.783 -.763 -.856 1.000

Sig. (1-tailed) Price . .000 .217 .059

Inflation .000 . .231 .067


Interest .059 .067 .032 .

N Price 5 5 5 5

Inflation 5 5 5 5


Interest 5 5 5 5

There is a positive correlation between dependent variable (Real Estate Prices) and independent variables(Inflation and Unemployment). Negative correlation between Interest rate and Real Estate Prices








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COEFFICIENTSa

Model


Standardized

Coefficients

t Sig.



1 (Constant) -2123.827 2822.880 -.752 .589

Inflation 1436.190 58.988 .962 24.347 .026 .242 4.125

Unemployment -3.386 124.274 -.001 -.027 .983 .156 6.429

Interest -97.386 134.306 -.050 -.725 .601 .080 12.465


The above table explains that there is positive association between Inflation and Real Estate Prices.

There is negative association between Unemployment, Interest and Real Estate Prices.




0.026(2.6%).

BANGLORE

MODEL SUMMARY

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

R Square


1 1.000a 1.000 .999 226.262 1.000 1034.573 3 1 .02


R Square = 1 (100%).

The independent variables explain 100% of dependent variable (Real Estate Prices).


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CORRELATIONS



Inflation .998 1.000 .437 -.763

Unemployment .388 .437 1.000 -.856

Interest -.722 -.763 -.856 1.000

Sig. (1-tailed) Price . .000 .260 .084

Inflation .000 . .231 .067


Interest .084 .067 .032 .

N Price 5 5 5 5

Inflation 5 5 5 5


Interest 5 5 5 5








Unemployment has 26% level of significance.


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COEFFICIENTSa

Model


Standardized

Coefficients

t Sig.



1 (Constant) -8983.712 4156.789 -2.161 .276

Inflation 2564.331 86.861 1.076 29.522 .022 .242 4.125Unemployment 41.232 182.998 .010 .225 .859 .156 6.429

Interest 337.799 197.771 .108 1.708 .337 .080 12.465


The above table explains that there is positive association between Inflation, Unemployment and Interest and

Real Estate Prices




0.022(2.2%)

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Trend Analysis:

Chennai:

Place 2006 2007 2008 2009 2010Nungabakkam 3200 5800 10440 15660 20358Anna Nagar 3500 6500 8500 11115 14535Besant Nagar 5600 7448 13174 17522 23304

T Nagar 4000 5800 7500 10125 13668Velachery 3200 3840 4608 5529 6635Average 3900 5877.6 8844.4 11990.2 15700

a=9262.44 b=2971.2

Projection of the

prices:

Bangalore:

Place 2006 2007 2008 2009 2010White field 5000 8900 12500 17500 24500Richmond town 7200 11000 15500 21840 30775

Palace orchards 7500 11000 13500 16568 20330Indira nagar 4200 6500 9200 13020 18430Kanamangla 4000 6500 8500 11100 14530Average 5981.2 9181.4 12241.6 16407.4 22115

Trend:

Year Price(y)

Deviation(x) x2 x*y

2006 3900 -2 4 -78002007 5877.

6-1 1

-5877.

6

2008 8844.4 0 0 0

2009 11990.2 1 1

11990.2

2010 15700 2 4 31400

N=546312

.2 0 1029712

.6

year Prices

2010

15204.

96

201118176.

22

201221147.

48

201324118.

74

2014 27090

201530061.

26

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a=13185 b=3949.4

Projection of the prices:

year Prices

201021083

.8

201125033

.2

201228982

.6

2013 32932

201436881

.4

201540830

.8

Delhi:

Place 2006 2007 2008 2009 2010

Shanti Niketan 18000 22500 27000 33750 40500Vasant Vihar 17000 21000 26500 33440 42200Friends Colony 10000 13500 18000 24000 32000Gurgaon 3700 4850 6100 7672.165 9649.527Nodia 3700 4900 6850 9576.02 13386.89

Average 10881.2 13751.4 17291.6 22089.44 27949.28

a=5589.856 b=4247.42

Year Price(y)

Deviation(x) x2 x*y

2006 5981-2 4

-11962

2007 9181 -1 1 -91812008 12241 0 0 02009 16407 1 1 16407

2010 22115 2 4 44230

N=5 65925 0 10 39494

Year Price(y

)

Deviation

(x) x

2

x*y2006 10881.2 -2 4 -7800

2007 13751.4

-1 1

-5877.

62008 17291.

6 0 0 02009 22089.

44 1 111990

.22010 27949.

28 2 4 31400

Average

27949.28 0 10

29712.6

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Hyderabad:

Place 2006 2007 2008 2009 2010Banjara Hills 3000 4800 6500 8800 11920Jublee Hills 3000 4600 7500 12230 19930Himayatnagar 2000 3200 4800 7200 10800West & East

Marredpally2000 2800 4200

6300 9450Secunderabad 2000 3100 4500 6530 9480

Average 2801.2 4101.4 5901.6 8613.8 12718

a=

6827.2 b=

2434.6

year Prices

201026887.

42

201131134.

84

201235382.

26

201339629.

68

201443877.

1

201548124.

52

Year Price(y)

Deviation(x) x2 x*y

2006 2801.2

-2 4

-5602.

4

2007 4101.4

-1 1

-4101.

4

2008 5901.

6 0 0 02009 8613.8 1 1

8613.8

2010 12718 2 4 25436

53413

6 0 10 24346

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Mumbai:

Place 2006 2007 2008 2009 2010Cuffe Parade 25000 35000 42000 50400 60480

Malabar Hill 28000 38000 46000 55684.21 67407.2

Worli 18000 26000 32500 33120 41400Bandra (W) 13500 21500 26500 33125 41406.25

Navi Mumbai 2800 3500 5500 8642.857 13581.63

Average 17460 24800 30500 36194.41 44855.02

Year Price(y)

Deviation(x) x2 x*y

2006 17460 -2 4

-34920

year Prices

201011696

.4

2011 14131

201216565

.6

201319000

.2

201421434

.8

201523869

.4

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2007 24800 -1 1

-24800

2008 30500 0 0 0

2009 36190 1 1 36190

2010 44850 2 4 89700

51538

00 0 10 66170

a= 30760 b= 6617

year Prices

2010 43994

2011 50611

2012 57228

2013 63845

2014 70462

2015 77079

Inference:

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Chennai:

The real estate prices in Chennai will increase significantly in 5 years.

The real estate prices will increase from 15204/sf in 2010 to 30061/sf in the 5 years.

The real estate prices show an increase of 97% in 5 years.

Banglore:

The real estate prices in Banglore will increase significantly in 5 years.



Delhi:

The real estate prices in Delhi will increase significantly in 5 years.

The real estate prices will increase from 26887.42/sf in 2010 to 48124.52/sf in the 5 years.


Hyderabad:

The real estate prices in Hyderabad will increase significantly in 5 years.

The real estate prices will increase from 11696.4/sf in 2010 to 23869.4/sf in the 5 years.


Mumbai:

The real estate prices in Mumbai will increase significantly in 5 years.



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The real estate prices in Hyderabad has the highest growth rate

The real estate price in Mumbai has the lowest growth rate, the real estate prices in

Mumbai will also be the costliest of the studies.

For the investors in the real estate, the investment made in real estate of Hyderabad will

give higher return.

Percentage Analysis:

Inflation VS Price in Mumbai:

Year % change in rate of Inflation

% change of price inMumbai

2007 26.19 42.038952008 20.75 22.983872009 29.69 18.655742010 31.33 23.92926

Inflation VS Price in Mumbai:

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Inference:

The graph above shows the variation of the real estate prices in Mumbai with the change in the

rate of inflation.

From the graph it is clear that with increase in the rate of inflation results in the increase in the

real estate prices in Mumbai.

Per capita income VS Price in Mumbai:

Year % Change in Per CapitaIncome

% change of price inMumbai

2007 13.1992622.98387

2008 13.2768418.65574

2009 12.6400923.92926

2010 16.8044842.03895

Per capita income VS Price in Mumbai:

Inference:

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The graph above shows the variation of the real estate prices in Mumbai with the change in Per

capita income.

The graph shows that per capita income is increasing at a steady rate and the real estate prices in

Mumbai is also increasing

GDP VS Price in Mumbai:

Year % Increase in GDP % change in price inMumbai

2007 9.6 18.655742008 9 23.929262009 8 42.038952010 7.8 22.98387

GDP VS Price in Mumbai:

Inference:

The graph above shows the variation of the real estate prices in Mumbai with the percentage

increase in GDP.

The graph shows that GDP is increasing at a steady rate and the real estate prices in Mumbai is

also increasing

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Inflation VS Price in Chennai


% change in price inChennai

2007 26.19 50.707692008 20.75 50.476382009 29.69 35.568272010 31.33 30.94027

Inflation VS Price in Chennai:

Inference:

The graph above shows the variation of the real estate prices in Chennai with the change in the

rate of inflation.

From the graph it is clear that real estate prices in Chennai increases at steady rate with the

increase in inflation.

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Per capita income VS Price in Chennai:


% change in price inChennai

2007 13.19926

50.707692008 13.27684

50.476382009 12.64009

35.568272010 16.80448

30.94027

Per capita income VS Price in Chennai:

Inference:

The graph above shows the variation of the real estate prices in Chennai with the change in Per

capita income.

The graph shows that per capita income is increasing at a steady rate and the real estate prices in

Chennai is also increasing

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GDP VS Price in Chennai:

Year % Increase in GDP % change in price inChennai

2007 9.6 50.707692008 9 50.476382009 8 35.568272010 7.8 30.94027

GDP VS Price in Chennai:

Inference:

The graph above shows the variation of the real estate prices in Chennai with the percentage

increase in GDP.

The graph shows that the percentage change prices in Chennai vary with the change in the

percentage increase in the GDP.

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Inflation VS Price in Bangalore:


% change in price inBanglore

2007 26.19 53.502762008 20.75 33.32972009 29.69 34.033172010 31.33 34.79003

Inflation VS Price in Bangalore:

Inference:

The graph above shows the variation of the real estate prices in Bangalore with the change in the

rate of inflation.

From the graph it is clear that real estate prices in Bangalore increases at steady rate with the


Per Capita Income VS Price in Bangalore:

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Bangalore2007 9.6 53.502762008 9 33.32972009 8 34.033172010 7.8 34.79003

GDP VS Price in Bangalore:

Inference:

The graph above shows the variation of the real estate prices in Bangalore with the percentage

increase in GDP.

The graph shows that the percentage change prices in Bangalore vary with the change in the


Per Capita Income VS Price in Hyderabad:


% change in price inHyderabad

2007 13.1992646.41582

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2008 13.2768443.89233

2009 12.6400945.95703

2010 16.8044847.6468

Per Capita Income VS Price in Hyderabad:

Inference:

The graph above shows the variation of the real estate prices in Hyderabad with the change in

Per capita income.

The graph shows that the real estate prices in Hyderabad increases steadily with increase in the

per capita income

Inflation VS Price in Hyderabad:


% change in price inHyderabad

2007 26.19 46.415822008 20.75 43.892332009 29.69 45.957032010 31.33 47.6468

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Inflation VS Price in Hyderabad:

Inference:

The graph above shows the variation of the real estate prices in Hyderabad with the change in the

rate of inflation.

From the graph it is clear that real estate prices in Hyderabad increases at steady rate with the


GDP VS Price in Hyderabad:

Year % Increase in GDP % change in price inHyderabad

2007 9.6 46.415822008 9 43.892332009 8 45.957032010 7.8 47.6468

GDP VS Price in Hyderabad:

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Inference:

The graph above shows the variation of the real estate prices in Hyderabad with the percentage

increase in GDP.

The graph shows that the percentage change prices in Hyderabad vary with the change in the


Per Capita Income VS Price in Delhi:


% change in price inDelhi

2007 28 26.377612008 47 25.744292009 66 27.746652010 81 26.52779

Per Capita Income VS Price in Delhi:

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Inference:

The graph above shows the variation of the real estate prices in Delhi with the change in Per

capita income.

The graph shows that the real estate prices in Delhi increases steadily with increase in the per capita

income

Inflation VS Price in Delhi:


% change in price inDelhi

2007 26.19 26.377612008 20.75 25.744292009 29.69 27.746652010 31.33 26.52779

Inflation VS Price in Delhi:

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Inference:

The graph above shows the variation of the real estate prices in Delhi with the change in the rate

of inflation.

From the graph it is clear that real estate prices in Delhi increases at steady rate with the increase

in inflation.

GDP VS Price in Delhi:

Year % Increase in GDP % change in price of Delhi

2007 9.6 26.377612008 9 25.744292009 8 27.746652010 7.8 26.52779

GDP VS Price in Delhi:

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Inference:

The graph above shows the variation of the real estate prices in Delhi with the percentage

increase in GDP.

The graph shows that the percentage change prices in Delhi vary with the change in the


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CHAPTER 5

CONCLUSION

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Conclusion

It is clear that Real Estate Prices in major cities are always highly deviated. The reason for the deviation is

certainly affected by the 3 major economic factors. The inflation is fully correlated with the Real Estate Prices.

It means the changes in Real Estate Prices is always depends upon inflation. Interest Rate is negatively

correlated with the Real Estate Prices. The reason is if the bank lending rate increases then the demand for loan

decreases. People are not tending to invest in real estate when the bank lending rate is high.

Unemployment rate is always reflecting its value in the commercial and office real estate prices. If any

reduction in unemployment rate means more jobs are created or more companies started their business. So it

increases the demand for office buildings and commercial places. It obviously increases the prices for Real

Estate.

The above points are proved quantitatively by analyzing the last 5 year data. It is clearly showed in the

correlation table of all cities that, the negative correlation between Interest rate and Real Estate Prices. Another

important point is the changes in unemployment rate are also reflected in the co-efficient table. It alwaysbelieved that economic factors are not having significant effect on real estate prices. From this analysis it is

clear that economic factors definitely having significant level of effect on the real estate prices.

Limitations of the study:

This study is confined only to Indian Real Estate Industry.

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Only five major cities have been focused upon.

Calculations are made only for a period of 5 years.

Only 3 major factors have been considered for projections.

Documents

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