MBFM Project

8/2/2019 MBFM Project

1/7

Money Banking & Financial Markets

Assignment

Group number 9

2009B3A4616P NITISH BHARGAVA

2009B3TS871P PRAKHAR BHARGAVA

2009B3A7560P PRAKASH YADAV

2009B3A4537P SUHAS KARANTH

2009B3A3587P SAUMYA VIJ


2/7

Factors

Money:

Money here is taken to be narrow money since time deposits do not affect the other two factors.

It includes money with the public, Other deposits with RBI and Demand deposits and is often

represented as M1. The data for Narrow Money was obtained from Table 45: Average Monetary

Aggregates provided by annual publication by RBI. The data spans annual values from 1960-61

to 2010-11.

Price Level

The Wholesale Price Index (WPI) is the price of a representative basket of wholesale goods and

therefore is considered a good measure for the price level of the economy. The data for WPI was

taken from Table 39: Wholesale Price Index - Annual Average (All commodities) from annual

publication by RBI and entirely converted to base year 2004-05. The data spans annual valuesfrom 1960-61 to 2010-11.

DATA

Year

Money Supply (in

Crores) WPI1960 2720 4.15

1961 2869 4.25

1962 3049 4.4

1963 3317 4.561964 3752 5.03

1965 4080 5.45

1966 4529 6.1

1967 4951 7.01

1968 5350 6.98

1969 5779 7.13

1970 6536 7.57

1971 7374 7.95

1972 8323 8.65

1973 9700 10.071974 11200 12.94

1975 11975 13.45

1976 13325 13.18

1977 16024 14.18

1978 14388 14.15

1979 17292 15.8

1980 20000 18.97


3/7

1981 23424 21.29

1982 24937 21.81

1983 28535 23.53

1984 33398 25.16

1985 39915 26.33

1986 44095 27.791987 51516 29.73

1988 58555 32.32

1989 66786 34.51

1990 81060 37.62

1991 92892 42.7

1992 114406 47.77

1993 124066 51.34

1994 150778 56.75

1995 192257 62.05

1996 214835 64.831997 240615 67.77

1998 267844 71.75

1999 309068 74.22

2000 341796 79.09

2001 379450 82.9

2002 422843 84.99

2003 473581 89.6

2004 578716 95.49

2005 649790 100

2006 826415 104.742007 967955 109.77

2008 1155837 119.3

2009 1259707 121.82

2010 1489301 133.22

Code for regression analysis

CALENDAR 1960 1 1

ALLOCATE 2010:1

OPEN DATA D:/wpi.dat

DATA(FORMAT=free,ORG=OBS) / A

OPEN DATA D:/money.dat


4/7

DATA(FORMAT=free,ORG=OBS) / B

graph(header='WPI',vlabel='Wholesale price index',hlabel='year') 2

# A

# constant

graph(header='Money Supply',vlabel='Money Supply in Crores',hlabel='year') 2

# B

# constant

scatterplot(header='Money Supply vs WPI',vlabel='WPI',hlabel='Money supply in crores') 1

# B A

linreg A

#constant B

linreg B

#constant A

Output

Graph 1


5/7

Graph 2

Graph 3

Linear Regression - Estimation by Least Squares

Dependent Variable B

Annual Data From 1960:01 To 2010:01

Usable Observations 51 Degrees of Freedom 49


6/7

Centered R**2 0.827145 R Bar **2 0.823617

Uncentered R**2 0.873937 T x R**2 44.571

Mean of Dependent Variable 213351.09804

Std Error of Dependent Variable 353672.72093

Standard Error of Estimate 148535.25039

Sum of Squared Residuals 1.08107e+12

Regression F(1,49) 234.4745

Significance Level of F 0.00000000

Durbin-Watson Statistic 0.069019

Variable Coeff Std Error T-Stat Signif

******************************************************************************

*

1. Constant -141702.7692 31148.7380 -4.54923 0.00003559

2. A 8492.6775 554.6216 15.31256 0.00000000

Regression Analysis:

Degrees of Freedom = 49 (512) as we have 51 observations and 2 parameters for eachregression.

For linear regression between WPI and Money supply

R Bar **2 = 0.823617 which means that shows that the change in WPI is significant to an extentof 82.36% due to a corresponding change in money supply.

Durbin-Watson Statistic: 0.069019 which is less than 0.2. So, WPI and money supply are not

auto correlated.

Equation of regression:WPI = -141702.7692 + 8492.6775 (Money supply)


7/7

Analysis:

Money supply is regulated by RBI in India which is the central bank of India. It has various

instruments like CRR, repo & reverse repo etc. Its decision on these rates determines inflation,

growth and GDP. Through our graphs, weve seen that money supply and WPI has positive

relationship with time. That is, both have increased with time. Inflation rates and GDP figures

have a direct impact on the money supply since their increase and decrease determines the level

of circulating money in the system as and when required by the Central Bank.

As the graph 3 shows, as money supply increase, even inflation rate increases. Its been

consistent for 50 years. The regression analysis depicts the same.

Through our regression analysis we have come to conclude that money supply have a significant

impact on the changes in Inflation rate observed over a period of 50 years in this project work.

The regression values are highly significant in explaining the relationship between the dependent

and independent variables.

MBFM Project

Documents

Transcript of MBFM Project