Below is a table from the paper on four river basins. From their regression analysis, you can see that the individual river coefficients are all negative and indicative of a higher electricity price when river levels fall. The bottom line of their research - - electricity prices are significantly affected by both falling river levels and higher river temperatures (which is a combination of decreased thermal efficiency, an increasing heat rate, and environmental regulatory constraints on water withdrawal rates).
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Elbe
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Main
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Neckar
|
Rhine
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Dep. Var. = Price (€/MWH)
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||||
COEFFICIENTS
|
||||
Base Volume
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8.099
|
8.256
|
8.081
|
8.277
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Predetermined
Variables
|
||||
1.1 Base Price
|
0.644
|
0.633
|
0.623
|
0.620
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1.7 Base Price
|
0.158
|
0.153
|
0.168
|
0.140
|
1.1 Base Volume
|
-3.738
|
-3.757
|
-3.672
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-3.7949
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1.7 Base Volume
|
-2.230
|
-2.330
|
-2.271
|
-2.284
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River Levels (cm)
|
||||
Single Series
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-0.130
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-0.372
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-0.511
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-0.217
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River Temperature (⁰C)
|
||||
DRiv25
(1-River Temp > 25⁰C)
|
-0.0246
|
0.00289
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0.00373
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-0.0683
|
River Temp,
if>25⁰C
|
0.208
|
0.222
|
0.227
|
0.210
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Brent (90-day MA)
|
0.131
|
0.113
|
0.0755
|
0.137
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TESTS (p-values)
|
||||
Endogeneity test
|
0.0000
|
0.0000
|
0.0000
|
0.0000
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Instrumental variable test
|
0.0000
|
0.0000
|
0.0000
|
0.0000
|
Overidentifying restrictions test
|
0.0716
|
0.0555
|
0.0613
|
0.0731
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Joint significance tests
|
|
|
|
|
Month Dummies
|
0.0000
|
0.0000
|
0.0000
|
0.0000
|
Year Dummies
|
0.0000
|
0.0000
|
0.0000
|
0.0000
|
N
|
2915
|
2915
|
2915
|
2915
|
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