Electronic Data Delivery System of The Central Bank of the Republic of Turkey. In econometric applications
below, we use the real variables which we obtain by deflating our variables by the GNP deflator. Our data is given
in Table 1 below.
Table 1: Income Tax Revenue and Taxable Income: 1975-2005, in million YTL
|
years |
Income Tax Revenue ( T ) |
Nominal GNP ( Y )______ |
Taxable Income(TI) |
|
1975 |
43.50______________________ |
690.9008________________ |
647.3917____________ |
|
1976 |
59.30______________________ |
868.0658________________ |
805.9202____________ |
|
1977 |
87.70______________________ |
1108.2707_______________ |
1031.7467___________ |
|
1978 |
139.40_____________________ |
1645.9685_______________ |
1527.1844___________ |
|
1979 |
233.10____________________ |
2876.5229_______________ |
2690.0576___________ |
|
1980 |
463.80____________________ |
5303.0102_______________ |
4965.6312___________ |
|
1981 |
745.80____________________ |
8022.7453_______________ |
7442.9227___________ |
|
1982 |
804.90____________________ |
10611.8592______________ |
9886.9590___________ |
|
1983 |
1109.87____________________ |
13933.0081______________ |
12843.8519__________ |
|
1984 |
1341.00____________________ |
22167.7399_____________ |
20785.9830_________ |
|
1985 |
1771.76____________________ |
35350.3184_____________ |
32384.8482__________ |
|
1986 |
3052.87___________________ |
51184.7593______________ |
46316.3705__________ |
|
1987 |
4424.40___________________ |
75019.3880_____________ |
67945.9444_________ |
|
1988 |
6918.50___________________ |
129175.1037_____________ |
118219.1656_________ |
|
1989 |
13468.50__________________ |
230369.9371_____________ |
211369.0890________ |
|
1990 |
23245.90__________________ |
397177.5474____________ |
365731.4159________ |
|
1991 |
40419.50__________________ |
634392.8411_____________ |
583794.7753_________ |
|
1992 |
70133.70__________________ |
1103604.9090____________ |
1009425.5400________ |
|
1993 |
125793.00________________ |
1997322.5974____________ |
1848801.7668________ |
|
1994 |
246578.60________________ |
3887902.9165___________ |
3633779.7261________ |
|
1995 |
436000.00________________ |
7854887.1670___________ |
7337185.5632_______ |
|
1996 |
865909.00________________ |
14978067.2830__________ |
14090439.2427 |
|
1997 |
1897693.00_______________ |
29393262.1470__________ |
26601657.9519 |
|
1998 |
4231794.70_______________ |
53518331.5800__________ |
50873904.4317 |
|
1999 |
6537502.00_______________ |
78282966.8090__________ |
73941964.6117 |
|
2000 |
10503414.60______________ |
125596128.7550_________ |
119662278.5856 |
|
2001 |
15647885.00______________ |
176483953.0210_________ |
176446798.1920 |
|
2002 |
19343401.00______________ |
275032365.9528_________ |
262196553.8044 |
|
2003 |
25716174.00_____________ |
356680888.2222_________ |
324693990.8191 |
|
2004 |
29307924.00_____________ |
428932343.0257_________ |
374787394.4870 |
|
2005 |
34219410.00_____________ |
480922786.9____________ |
404019328.9________ |
Source: SPO and CB of Turkey
A time series is said to be nonstationary if its mean and variance are not constant over time and the value of the
covariance between two time periods depend on the actual time at which the covariance is computed. Regressions
involving nonstationary time series data include the possibility of obtaining spurious regressions. The results of
such regressions seem artificially good but they do not reflect the true relation. So the stationarity of a time series
must be tested by a unit root test. In our study, we use Augmented Dickey Fuller Unit Root test (ADF) and KPSS
unit root test (Kwiatkowski, Phillips, Schmidt, Shin, 1992), to test the time-series properties of our variables.
ADF unit root test sets the null hypothesis that the series has a unit root (not stationary). In other words, this test
use unit autoregressive (AR) roots as null hypothesis. But KPSS unit root test sets stationarity as the null
hypothesis. The asymptotic distributions of two tests are different. It is much more confident that if two tests’
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