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Going global, locally? Decentralized environmental expenditure and air quality
Sean Dougherty*
Andoni Montes Nebreda*
Andoni Montes Nebreda
Affiliation: Ituna Center (UPV/EHU) & ICEI (UCM) - Agirre Lehendakariaren etorbidea, Bilbao, Spain
0000-0002-9150-9974
Article | Year: 2022 | Pages: 489 - 503 | Volume: 46 | Issue: 4 Received: May 24, 2022 | Accepted: June 28, 2022 | Published online: December 7, 2022
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FULL ARTICLE
FIGURES & DATA
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Variables
|
N
|
Mean
|
S.d.
|
Min
|
Max
|
Level
|
Exposure to PM2.5
>10μg/m3 (% pop.)
|
1,953
|
58.07
|
46.77
|
0
|
100
|
Metropolitan
|
GG environmental
expenditure (% GDP)
|
2,306
|
0.887
|
0.27
|
1.00e-10
|
1.7
|
Country
|
SNG environmental
expenditure (% GDP)
|
2,306
|
0.687
|
0.295
|
0.0617
|
1.385
|
Country
|
European Quality
of Government Index (regional EQI)
|
1,562
|
0.244
|
1.069
|
-2.230
|
1.885
|
Region
|
GDP per capita
(PPP)
|
2,016
|
41,067
|
13,087
|
10,714
|
108,069
|
Metropolitan
|
Population density
|
2,299
|
2,213
|
1,603
|
87
|
12,929
|
Metropolitan
|
Tree cover (%
of land)
|
2,343
|
14.61
|
15.13
|
0
|
66.30
|
Metropolitan
|
Transport performance
gap
|
736
|
2.257
|
1.069
|
0.547
|
6.537
|
Metropolitan
|
Note: Main data are consistent with Gilmore and St. Clair (2018) for the United States and Plouin and Allain-Dupré (2018) for remaining OECD member countries, who explained that although more than half of environmental public expenditure is carried out at the subnational level, it does not reach even 1% of total general government expenditure in most cases. Due to data limitations, and particularly lack of disaggregation (OECD, 2019b, 2020), some variables have been considered at higher levels of government, as described in table 1.
Variable
|
Subnational government
|
General government
|
(1)
|
(2)
|
(3)
|
(4)
|
Δ ln(envexp)t-1
|
-21.28***
|
-22.12***
|
-25.82***
|
-20.72
|
(2.293)
|
(6.947)
|
(6.210)
|
(17.33)
|
Δ regionalEQI
|
-26.64**
|
-47.75*
|
-26.13**
|
-46.91*
|
(11.70)
|
(23.77)
|
(11.81)
|
(24.20)
|
ln(envexp) * regionalEQI
|
|
-4.564**
|
|
-7.451***
|
|
(1.699)
|
|
(2.353)
|
Δ GDP per capita
|
-0.00312***
|
-0.00275***
|
-0.00316***
|
-0.00280***
|
(0.000477)
|
(0.000639)
|
(0.000470)
|
(0.000676)
|
Δ Population
density
|
0.00605
|
-0.0109
|
0.000837
|
-0.00212
|
(0.0485)
|
(0.0601)
|
(0.0484)
|
(0.0550)
|
Δ Tree-cover
land share
|
-26.85***
|
-25.61
|
-27.49***
|
-27.42
|
(7.086)
|
(20.97)
|
(7.195)
|
(20.46)
|
Δ Transport perf.
gap.
|
|
-1.214
|
|
-1.296*
|
|
(0.724)
|
|
(0.695)
|
Constant
|
-13.60***
|
-10.68***
|
-13.59***
|
-10.61***
|
(0.738)
|
(2.210)
|
(0.739)
|
(2.074)
|
Observations
|
739
|
230
|
739
|
230
|
R-squared
|
0.066
|
0.091
|
0.060
|
0.086
|
Note: Robust standard errors in parentheses. Significance *** p<0.01, ** p<0.05, * p<0.1.
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December, 2022 IV/2022 |