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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
Change F Change df1 df2 Sig. F Change
1 .999a .999 .995 715.680 .999 286.455 3 1 .043
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 4.3%
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CORRELATIONS
Price Inflation Unemployment Interest
Pearson Correlation Price 1.000 .987 .319 -.652
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
Unemployment .301 .231 . .032
Interest .116 .067 .032 .
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 32% correlation between Unemployment and Real Estate Prices.
And there exist 65% correlation between Interest and Real Estate Prices.
Level of significance:
Inflation has 0.01% level of significance.
Unemployment has 30.1% level of significance.
Interest has 11.6% 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) -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.
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.,
0.490(49.0%) and 0.209(20.9%) for Unemployment and Interest respectively. For Inflation it is only
0.36(3.6%).
DELHI
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 .997 353.596 .999 490.670 3 1 .033
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 3.3%
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CORRELATIONS
Price Inflation Unemployment Interest
Pearson Correlation Price 1.000 .998 .386 -.731
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
Unemployment .261 .231 . .032
Interest .080 .067 .032 .
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 39% 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 26.1% 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) 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.
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.,
0.480(48.0%) and 0.907(90.7%) for Unemployment and Interest respectively. For Inflation it is only
0.33(3.3%).
HYDERABAD
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 1.000 .998 153.655 1.000 880.551 3 1 .025
a. Predictors: (Constant), Interest, Inflation, Unemployment
R Square = 1 (100%).
The independent variables explain 100% of dependent variable (Real Estate Prices).
Significance level is 2.5%
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CORRELATIONS
Price Inflation Unemployment Interest
Pearson Correlation Price 1.000 .999 .461 -.783
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
Unemployment .217 .231 . .032
Interest .059 .067 .032 .
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 46% correlation between Unemployment and Real Estate Prices.
And there exist 78% correlation between Interest and Real Estate Prices.
Level of significance:
Inflation has 0% level of significance.
Unemployment has 21.7% level of significance.
Interest has 5.9% 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) -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
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.
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.,
0.983(98.3%) and 0.601(60.1%) for Unemployment and Interest respectively. For Inflation it is only
0.026(2.6%).
BANGLORE
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 1.000 .999 226.262 1.000 1034.573 3 1 .02
a. Predictors: (Constant), Interest, Inflation, Unemployment
R Square = 1 (100%).
The independent variables explain 100% of dependent variable (Real Estate Prices).
Significance level is 2.3%
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CORRELATIONS
Price Inflation Unemployment Interest
Pearson Correlation Price 1.000 .998 .388 -.722
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
Unemployment .260 .231 . .032
Interest .084 .067 .032 .
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 39% correlation between Unemployment and Real Estate Prices.
And there exist 72% correlation between Interest and Real Estate Prices.
Level of significance:
Inflation has 0% level of significance.
Unemployment has 26% level of significance.
Interest has 8.4% 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) -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
a. Dependent Variable: Price
The above table explains that there is positive association between Inflation, Unemployment and Interest 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.,
0.859(85.9%) and 0.337(33.7%) for Unemployment and Interest respectively. For Inflation it is only
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.
The real estate prices will increase from 21083/sf in 2010 to 40830/sf in the 5 years.
The real estate prices show an increase of 93% 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.
The real estate prices show an increase of 79% in 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.
The real estate prices show an increase of 104% in 5 years.
Mumbai:
The real estate prices in Mumbai will increase significantly in 5 years.
The real estate prices will increase from 43994/sf in 2010 to 77079/sf in the 5 years.
The real estate prices show an increase of 75% 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
Year % change in rate of Inflation
% 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:
Year % Change in Per CapitaIncome
% 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:
Year % change in rate of Inflation
% 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
increase in inflation.
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
percentage increase in the GDP.
Per Capita Income VS Price in Hyderabad:
Year % Change in Per CapitaIncome
% 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:
Year % change in rate of Inflation
% 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
increase in inflation.
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
percentage increase in the GDP.
Per Capita Income VS Price in Delhi:
Year % Change in Per CapitaIncome
% 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:
Year % change in rate of Inflation
% 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
percentage increase in the GDP.
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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.
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