This paper measures the effects of interest rate and gdp on money demand then compares the regression in logs. This dataset starts in 1960 until 1983. The dependent variable (Y) represents money demand. The two independent variables are GDP (X1) and Interest (X2). The second regression uses loggdp and loginterest as X1 and X2.

M1 GDP Interest Y X1 X2 Y: money demand (M1)
1960 141.8 506.5 3.247 X1: GDP
1961 146.5 524.6 2.605 X2: Interest Rate
1962 149.2 565 2.908
1963 154.7 596.7 3.253
1964 161.8 637.7 3.686
1965 169.5 691.1 4.055
1966 173.7 756 5.082
1967 185.1 799.6 4.63
1968 199.4 873.4 5.47
1969 205.8 944 6.853
1970 216.5 992.7 6.562
1971 230.7 1077.6 4.511
1972 251.9 1185.9 4.466
1973 265.8 1326.4 7.178
1974 277.5 1434.2 7.926
1975 291.1 1549.2 6.122
1976 310.4 1718 5.266
1977 335.5 1918.3 5.51
1978 363.2 2163.9 7.572
1979 389 2417.8 10.017
1980 414.1 2631.7 11.374
1981 440.6 2954.1 13.776
1982 478.2 3073 11.084
1983 521.1 3309.5 8.75

The model: Y = a + b1x1 + b2x2 logY= a + logb1x1 + logb2x2
Data: Sample size is 24 observations spanning 24 consecutive years between 1963 and 1984. The data are undated/unstructured.
The theoretical expectation is that an increase in GDP or a decrease in Interest rate will raise money demand.

Dependent Variable: MONEYDEMAND

Method: Least Squares

Date: 03/10/15 Time: 11:33

Sample: 1 24

Included observations: 24

Variable
Coefficient
Std. Error t-Statistic Prob.

C
89.77735
4.103806
21.87661
0.0000
GDP
0.135940
0.003959
34.33303
0.0000
INTEREST
-2.577072
1.189214
-2.167038
0.0419

R-squared
0.995329
Mean dependent var
269.7125
Adjusted R-squared
0.994884
S.D. dependent var
113.6849
S.E. of regression
8.131613
Akaike info criterion
7.145864
Sum squared resid
1388.586
Schwarz criterion
7.293121
Log likelihood
-82.75037
Hannan-Quinn criter.
7.184932
F-statistic
2237.262
Durbin-Watson stat
0.423710
Prob(F-statistic)
0.000000

Y= 89.77 + 0.13gdp – 2.57interest
Interpretation of the estimated results: Holding everything else constant a one unit increase in money demand increases gdp by .13 and decreases interest by 2.57. R-squared is .99 meaning that 99% of variation can be explained by GDP and Interest in the model. The adjusted R-squared says the 99% of variation can be explained by money demand in the model. The prob ( F-Statistic) states that the model is significant because it is lower than 5%. The Durban Watson stat was