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The role of economic and political factors in budget forecasting errors: evidence from Turkey’s metropolitan municipalities for the period 2011-2022
Berat Kara* 
Article | Year: 2025 | Pages: 273 - 307 | Volume: 49 | Issue: 2 Received: June 14, 2024 | Accepted: September 25, 2024 | Published online: June 7, 2025
|
FULL ARTICLE
FIGURES & DATA
REFERENCES
CROSSMARK POLICY
METRICS
LICENCING
PDF
|
Variable
|
Explanation
|
Acronym
|
|
Revenue forecasting error
|
Annual budget revenue forecasting absolute error
rate
|
REV
|
|
Expenditure forecasting error
|
Annual budget expenditure forecasting absolute error
rate
|
EXP
|
|
Inflation
|
Annual local inflation rate
|
INF
|
|
Unemployment
|
Annual local unemployment rate
|
UNP
|
|
Per capita GDP
|
Annual local per capita GDP
|
GDP
|
|
Export-to-import ratio
|
Local Export-to-import ratio: (Export / Import)
|
EIR
|
|
Population growth rate
|
Annual local population growth rate
|
PGR
|
|
Mayor’s political party
|
“1” if mayor’s political party is right-wing, “0”
otherwise
|
RLP
|
|
Mayor’s re-candidacy
|
“1” if mayor re-candidate for the next election, “0”
otherwise
|
REL
|
|
Municipality election periods
|
“1” if municipality elections were held that year, “0”
otherwise
|
ELC
|
|
Budget surplus
|
“1” if budget surplus, “0” otherwise
|
BDM
|
|
Variable
|
Mean
|
Std. dev.
|
Min.
|
Max.
|
Obs.
|
|
EXP
|
overall
|
0.1887
|
0.1870
|
0.0001
|
1.1190
|
N
|
180
|
|
between
|
|
0.0693
|
0.0699
|
0.3068
|
n
|
15
|
|
within
|
|
0.1745
|
-0.0971
|
1.0452
|
T
|
12
|
|
REV
|
overall
|
0.1707
|
0.1325
|
0.0021
|
0.7005
|
N
|
180
|
|
between
|
|
0.0673
|
0.0729
|
0.3074
|
n
|
15
|
|
within
|
|
0.1154
|
-0.0332
|
0.6644
|
T
|
12
|
|
BDM
|
overall
|
0.3555
|
0.4800
|
0
|
1
|
N
|
180
|
|
between
|
|
0.2076
|
0
|
0.75
|
n
|
15
|
|
within
|
|
0.4358
|
-0.3944
|
1.1888
|
T
|
12
|
|
INF
|
overall
|
18.4078
|
18.4690
|
5.43
|
73.3
|
N
|
180
|
|
between
|
|
0.4282
|
17.6466
|
19
|
n
|
15
|
|
within
|
|
18.4643
|
4.8787
|
73.1670
|
T
|
12
|
|
UNP
|
overall
|
10.3150
|
3.3335
|
3.6
|
23.4
|
N
|
180
|
|
between
|
|
2.8017
|
6.575
|
15.6083
|
n
|
15
|
|
within
|
|
1.9351
|
1.6066
|
18.1066
|
T
|
12
|
|
GDP
|
overall
|
10,464.98
|
4,376.786
|
3,043
|
20,883
|
N
|
180
|
|
between
|
|
4,301.055
|
3,901.333
|
17,653.08
|
n
|
15
|
|
within
|
|
1,339.401
|
5,983.394
|
13,952.64
|
T
|
12
|
|
EIR
|
overall
|
1.4758
|
1.6461
|
0.3546
|
10.4561
|
N
|
180
|
|
between
|
|
1.1814
|
0.6403
|
5.3017
|
n
|
15
|
|
within
|
|
1.1831
|
-2.6785
|
8.0300
|
T
|
12
|
|
PGR
|
overall
|
14.7243
|
11.1765
|
-23.24
|
39.09
|
N
|
180
|
|
between
|
|
8.6468
|
-2.1208
|
29.8908
|
n
|
15
|
|
within
|
|
7.3986
|
-13.464
|
48.866
|
T
|
12
|
|
RLP
|
overall
|
0.7444
|
0.4373
|
0
|
1
|
N
|
180
|
|
between
|
|
0.3542
|
0
|
1
|
n
|
15
|
|
within
|
|
0.2712
|
-0.0055
|
1.3277
|
T
|
12
|
|
REL
|
overall
|
0.5888
|
0.4934
|
0
|
1
|
N
|
180
|
|
between
|
|
0.3556
|
0
|
1
|
n
|
15
|
|
within
|
|
0.3532
|
-0.3277
|
1.3388
|
T
|
12
|
|
ELC
|
overall
|
0.1666
|
0.3737
|
0
|
1
|
N
|
180
|
|
between
|
|
0
|
0.1666
|
0.1666
|
n
|
15
|
|
within
|
|
0.37375
|
0
|
1
|
T
|
12
|
Note: For all variables: N=180, n=15, T=12. Source: Author’s calculations.
|
REV
|
EXP
|
BDM
|
INF
|
UNP
|
GDP
|
EIR
|
PGR
|
RLP
|
REL
|
ELC
|
|
REV
|
1
|
|
|
|
|
|
|
|
|
|
|
|
EXP
|
0.4953
|
1
|
|
|
|
|
|
|
|
|
|
|
BDM
|
-0.1505
|
0.0248
|
1
|
|
|
|
|
|
|
|
|
|
INF
|
0.1057
|
0.4426
|
0.0511
|
1
|
|
|
|
|
|
|
|
|
UNP
|
-0.2229
|
-0.0935
|
0.232
|
0.0323
|
1
|
|
|
|
|
|
|
|
GDP
|
0.0362
|
0.3941
|
0.1327
|
0.8105
|
0.0975
|
1
|
|
|
|
|
|
|
EIR
|
0.0329
|
0.0457
|
-0.1073
|
0.0038
|
-0.1091
|
-0.1018
|
1
|
|
|
|
|
|
PGR
|
0.0476
|
-0.0175
|
0.2151
|
-0.1706
|
0.134
|
-0.0091
|
-0.133
|
1
|
|
|
|
|
RLP
|
-0.0326
|
-0.1492
|
-0.0171
|
-0.1224
|
-0.1905
|
-0.3044
|
-0.1116
|
-0.1572
|
1
|
|
|
|
REL
|
0.0497
|
-0.0384
|
-0.0398
|
-0.0607
|
-0.0893
|
0.0539
|
-0.187
|
0.1035
|
-0.1789
|
1
|
|
|
ELC
|
0.1203
|
0.1016
|
0.0415
|
-0.2056
|
0.1235
|
-0.1068
|
0.0026
|
0.0228
|
-0.0114
|
-0.0808
|
1
|
|
Municipality
|
Category
|
MPE
|
MAPE
|
NoNEP
|
NoPEP
|
|
Istanbul
|
Revenue
|
11.17
|
14.42
|
4
|
8
|
|
Expenditure
|
5.78
|
13.21
|
6
|
6
|
|
Ankara
|
Revenue
|
-4.66
|
12.62
|
8
|
4
|
|
Expenditure
|
-1.97
|
16.88
|
11
|
1
|
|
Izmir
|
Revenue
|
-1.62
|
7.29
|
8
|
4
|
|
Expenditure
|
-7.92
|
11.92
|
11
|
1
|
|
Kocaeli
|
Revenue
|
-3.09
|
13.26
|
7
|
5
|
|
Expenditure
|
-6.72
|
20.91
|
9
|
3
|
|
Bursa
|
Revenue
|
-4.10
|
10.82
|
9
|
3
|
|
Expenditure
|
3.34
|
15.68
|
7
|
5
|
|
Antalya
|
Revenue
|
-12.89
|
30.74
|
9
|
3
|
|
Expenditure
|
-20.06
|
24.61
|
10
|
2
|
|
Konya
|
Revenue
|
-24.40
|
26.35
|
11
|
1
|
|
Expenditure
|
-12.54
|
29.20
|
11
|
1
|
|
Adana
|
Revenue
|
-21.00
|
23.72
|
11
|
1
|
|
Expenditure
|
-18.51
|
18.51
|
12
|
0
|
|
Tekirdag
|
Revenue
|
-7.030
|
20.03
|
7
|
5
|
|
Expenditure
|
-24.99
|
30.68
|
11
|
1
|
|
Gaziantep
|
Revenue
|
-9.11
|
14.14
|
9
|
3
|
|
Expenditure
|
-10.38
|
10.38
|
12
|
0
|
|
Kayseri
|
Revenue
|
2.30
|
20.68
|
8
|
4
|
|
Expenditure
|
-4.95
|
26.25
|
10
|
2
|
|
Sanliurfa
|
Revenue
|
-7.79
|
11.99
|
9
|
3
|
|
Expenditure
|
-15.87
|
15.87
|
12
|
0
|
|
Samsun
|
Revenue
|
-4.95
|
9.74
|
9
|
3
|
|
Expenditure
|
1.17
|
6.99
|
7
|
5
|
|
Ordu
|
Revenue
|
-9.86
|
17.60
|
11
|
1
|
|
Expenditure
|
3.23
|
18.91
|
7
|
5
|
|
Erzurum
|
Revenue
|
-20.52
|
22.64
|
10
|
2
|
|
Expenditure
|
-0.75
|
23.11
|
10
|
2
|
Note: NoNEP: number of negative error periods; NoPEP: number of positive error periods. Source: Author’s calculations based on the Ministry of Treasury and Finance data.
|
Coef.
|
Std. err
|
z
|
P > z
|
[95% Conf. Interval]
|
|
BDM
|
-0.0405
|
0.0198
|
-2.04
|
0.042**
|
-0.0794
|
-0.0015
|
|
INF
|
0.0021
|
0.0010
|
2.08
|
0.037**
|
0.0001
|
0.0040
|
|
UNP
|
-0.0100
|
0.0038
|
-2.62
|
0.009***
|
-0.0176
|
-0.0025
|
|
GDP
|
-0.0004
|
0.0004
|
-0.99
|
0.324
|
-0.0012
|
0.0004
|
|
EIR
|
0.0014
|
0.0068
|
0.21
|
0.831
|
-0.0119
|
0.0148
|
|
PGR
|
0.0018
|
0.0010
|
1.72
|
0.085*
|
-0.0002
|
0.0039
|
|
RLP
|
-0.0265
|
0.0294
|
-0.90
|
0.367
|
-0.0842
|
0.0311
|
|
REL
|
-0.0265
|
0.0228
|
-1.16
|
0.245
|
-0.0713
|
0.0182
|
|
ELC
|
0.0671
|
0.0241
|
2.78
|
0.006***
|
0.0197
|
0.1145
|
|
_cons
|
0.2659
|
0.0614
|
4.32
|
0.000
|
0.1453
|
0.3864
|
|
R-sq
|
within
|
0.1345
|
|
Obs. per group
|
min
|
12
|
|
between
|
0.0939
|
|
avg
|
12
|
|
overall
|
0.1179
|
|
max
|
12
|
|
Number of obs
|
180
|
|
Number of groups
|
15
|
|
Wald chi2(9)
|
25.14
|
|
Prob > chi2
|
0.0028
|
|
sigma_u
|
0.0594
|
|
sigma_e
|
0.1147
|
|
rho
|
0.2114
|
|
Coef.
|
Std. err
|
z
|
P > z
|
[95% Conf. Interval]
|
|
BDM
|
-0.0023
|
0.0269
|
-0.09
|
0.929
|
-0.0551
|
0.0503
|
|
INF
|
0.0046
|
0.0012
|
3.62
|
0.000***
|
0.0021
|
0.0071
|
|
UNP
|
-0.0089
|
0.0043
|
-2.05
|
0.040**
|
-0.0173
|
-0.0004
|
|
GDP
|
0.0001
|
0.0005
|
0.22
|
0.830
|
-0.0008
|
0.0011
|
|
EIR
|
0.0017
|
0.0084
|
0.20
|
0.839
|
-0.0147
|
0.0181
|
|
PGR
|
0.0008
|
0.0012
|
0.70
|
0.482
|
-0.0015
|
0.0033
|
|
RLP
|
-0.0489
|
0.0346
|
-1.41
|
0.158
|
-0.1167
|
0.0189
|
|
REL
|
-0.0221
|
0.0280
|
-0.79
|
0.429
|
-0.0770
|
0.0327
|
|
ELC
|
0.1060
|
0.0334
|
3.17
|
0.002***
|
0.0405
|
0.1715
|
|
_cons
|
0.2063
|
0.0717
|
2.88
|
0.004
|
0.0657
|
0.3469
|
|
R-sq
|
within
|
0.2848
|
|
Obs. per group
|
min
|
12
|
|
between
|
0.1755
|
|
avg
|
12
|
|
overall
|
0.2706
|
|
max
|
12
|
|
Number of obs.
|
180
|
|
Number of groups
|
15
|
|
Wald chi2(9)
|
64.53
|
|
Prob > chi2
|
0.0000
|
|
sigma_u
|
0.0332
|
|
sigma_e
|
0.1569
|
|
rho
|
0.0429
|
|
No
|
Hypothesis
|
Status
|
|
Revenue
|
Expenditure
|
|
1
|
Budgets
are forecasted with a high degree of inaccuracy.
|
Accept
|
Accept
|
|
2
|
Forecasting
errors are mostly in the negative direction.
|
Accept
|
Accept
|
|
3
|
A
budget surplus affects budget forecasting errors.
|
Accept
|
Reject
|
|
4
|
An
increase in inflation affects the forecasting error in a positive direction.
|
Accept
|
Accept
|
|
5
|
An
increase in the unemployment rate affects revenue forecasting errors negatively
and expenditure forecasting errors positively.
|
Accept
|
Accept
|
|
6
|
An
increase in per capita GDP increases errors in a positive direction.
|
Reject
|
Reject
|
|
7
|
As
the export-to-import ratio increases, forecasting errors also increase in a
positive direction.
|
Reject
|
Reject
|
|
8
|
As
the population growth rate increases, forecasting errors also increase in a
positive direction.
|
Accept
|
Reject
|
|
9
|
Mayor’s
political party affiliations affect the forecasting error.
|
Reject
|
Reject
|
|
10
|
Mayor’s
candidacy in the next elections affects revenue forecasting errors negatively
and expenditure forecasting errors positively.
|
Reject
|
Reject
|
|
11
|
Election
periods affect revenue forecasting errors negatively and expenditure
forecasting errors positively.
|
Accept
|
Accept
|
|
(b)
|
(B)
|
(b-B)
|
sqrt(diag(V_b-V_B))
|
|
Fixed
|
Random
|
Difference
|
S.E.
|
|
BDM
|
-0.0426
|
-0.0405
|
-0.0021
|
0.0046
|
|
INF
|
0.0021
|
0.0021
|
0.0000
|
0.0004
|
|
UNP
|
-0.0107
|
-0.0100
|
-0.0006
|
0.0028
|
|
GDP
|
-0.0004
|
-0.0004
|
-0.0000
|
0.0002
|
|
EIR
|
0.0029
|
0.0014
|
0.0015
|
0.0034
|
|
PGR
|
0.0018
|
0.0018
|
-0.0000
|
0.0006
|
|
RLP
|
-0.0316
|
-0.0265
|
-0.0051
|
0.0177
|
|
REL
|
-0.0484
|
-0.0265
|
-0.0218
|
0.0112
|
|
ELC
|
0.0652
|
0.0671
|
-0.0018
|
0.0037
|
|
chi2(8)
|
7.8000
|
|
Prob>chi2
|
0.4531
|
|
(b)
|
(B)
|
(b-B)
|
sqrt(diag(V_b-V_B))
|
|
Fixed
|
Random
|
Difference
|
S.E.
|
|
BDM
|
-0.0184
|
-0.0023
|
-0.0161
|
0.0091
|
|
INF
|
0.0050
|
0.0046
|
0.0003
|
0.0008
|
|
UNP
|
-0.0062
|
-0.0089
|
0.0026
|
0.0050
|
|
GDP
|
-0.0001
|
0.0001
|
-0.0002
|
0.0004
|
|
EIR
|
-0.0010
|
0.0017
|
-0.0027
|
0.0066
|
|
PGR
|
-0.0002
|
0.0008
|
-0.0011
|
0.0011
|
|
RLP
|
-0.0625
|
-0.0489
|
-0.0135
|
0.0330
|
|
REL
|
-0.0621
|
-0.0221
|
-0.0400
|
0.0218
|
|
ELC
|
0.1001
|
0.1060
|
-0.0058
|
0.0067
|
|
chi2(8)
|
13.5000
|
|
Prob>chi2
|
0.0957
|
|
Models
|
|
Revenue
|
Expenditure
|
|
Var
|
sd = sqrt(Var)
|
|
Var
|
sd = sqrt(Var)
|
|
REV
|
0.0175
|
0.1325
|
EXP
|
0.0349
|
0.1870
|
|
e
|
0.0131
|
0.1147
|
e
|
0.0246
|
0.1569
|
|
u
|
0.0035
|
0.0594
|
u
|
0.0011
|
0.0332
|
|
chibar2(01)
|
18.8800
|
chibar2(01)
|
3.2800
|
|
Prob > chibar2
|
0.0000
|
Prob > chibar2
|
0.0352
|
|
Models
|
|
Revenue
|
Expenditure
|
|
F (1, 14)
|
0.463
|
2.032
|
|
Prob > F
|
0.507
|
0.176
|
|
Models
|
|
Revenue
|
Expenditure
|
|
Pr
|
0.177
|
0.112
|
|
Average absolute value of the off-diagonal elements
|
0.306
|
0.418
|
|
|
June, 2025
II/2025
|
