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Commit a3d5beca authored by Ingram Jaccard's avatar Ingram Jaccard
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iso2,iso3,quint,eu_q_rank,total_adult_eq,total_households,pop_estimate_per_quintile
AT,AUT,1,6,847506.5687880205,763180,1303488.2950612388
AT,AUT,2,7,918270.3423103484,763180.0000000001,1412324.9152099492
AT,AUT,3,8,1081852.591006424,763180,1663918.8901806187
AT,AUT,4,8,1291552.7687296416,763180,1986443.5020256557
AT,AUT,5,9,1480157.9275472744,763180,2276523.397522538
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BE,BEL,2,6,1156465.2146188256,939860,1857796.6617649938
BE,BEL,3,7,1345366.5798724124,939859.9999999999,2161256.1358025544
BE,BEL,4,8,1596301.0002782969,939860,2564368.242123575
BE,BEL,5,9,1892640.682281059,939860,3040421.36072489
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BG,BGR,3,1,885298.1911033463,587960,1423523.840614015
BG,BGR,4,1,976847.4461194862,587960,1570731.3560202157
BG,BGR,5,2,1137482.0585474095,587959.9999999999,1829025.3440989142
CY,CYP,1,3,70204.59704880817,59500,164950.58557782482
CY,CYP,2,5,84451.85231383311,59500,198425.5031421086
CY,CYP,3,7,98292.58061255432,59499.999999999985,230945.2573130556
CY,CYP,4,8,113481.09179627936,59500,266631.72115058743
CY,CYP,5,10,127696.55149368444,59500,300031.9328164237
CZ,CZE,1,1,962059.7512015832,928840,1458464.8936532796
CZ,CZE,2,2,1178549.58032491,928840.0000000002,1786659.4940562344
CZ,CZE,3,2,1397826.4728033473,928840,2119079.231260452
CZ,CZE,4,3,1605885.4920604737,928840,2434492.878921582
CZ,CZE,5,3,456655.148506932,234049.24026114304,692280.8087247723
CZ,CZE,5,4,1355611.2260496058,694790.7596876039,2055081.6933836788
DE,DEU,1,3,8585780.584588131,8051560,12551665.689935965
DE,DEU,2,5,9526619.796315368,8051560,13927090.92206699
DE,DEU,3,7,10810021.98619632,8051560.000000001,15803313.482661366
DE,DEU,4,8,12624234.586238762,8051560,18455534.771320656
DE,DEU,5,10,14329856.656081911,8051559.999999998,20949006.134015024
DK,DNK,1,6,492674.9535667608,474620.00000000006,832558.7718256488
DK,DNK,2,8,572588.8328643782,474620.00000000006,967603.1874554192
DK,DNK,3,9,634264.0837796481,474620,1071826.6126210701
DK,DNK,4,10,766003.3840095247,474620,1294449.4782782625
DK,DNK,5,10,897726.4734982332,474620,1517044.949819599
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EE,EST,2,1,149570.4082876295,114320.00000000001,229789.27043150694
EE,EST,3,2,176796.73313432836,114320,271617.8473183401
EE,EST,4,3,195512.99471915507,114320.00000000001,300372.17208097613
EE,EST,5,5,213675.10885442025,114320,328275.1443628371
EL,GRC,1,3,1145435.0845930525,875220,1762867.0885130719
EL,GRC,2,3,1228569.6894409938,875220,1890814.3294997078
EL,GRC,3,4,1378978.855297916,875220.0000000001,2122299.615629279
EL,GRC,4,5,1571819.0678785534,875220,2419087.8567726407
EL,GRC,5,8,1706140.8805784553,875220,2625814.109585301
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ES,ESP,1,3,185383.7691024067,136053.9184232916,294941.46306189755
ES,ESP,2,4,5321708.987800857,3675200,8466720.913331877
ES,ESP,3,5,5642672.147724775,3675200,8977366.17874687
ES,ESP,4,6,6228544.078144078,3675200,9909475.419817016
ES,ESP,5,8,2765422.237246014,1453593.2004521461,4399725.41601894
ES,ESP,5,9,4226547.595180143,2221606.799495291,6724343.438796728
FI,FIN,1,4,538717.9028894847,524500,808277.1952084983
FI,FIN,2,5,585334.6963585125,524500,878219.7214781132
FI,FIN,3,7,698073.5049019607,524500,1047369.8601163309
FI,FIN,4,8,836179.8464491363,524500,1254580.732054177
FI,FIN,5,10,993809.2725409836,524500,1491083.4911428809
FR,FRA,1,4,6538329.955240006,5792280,10295777.794893894
FR,FRA,2,5,7321421.96382429,5792280,11528897.16460074
FR,FRA,3,6,6310976.555919539,4332039.946868278,9937768.930804474
FR,FRA,3,7,2127298.1906729415,1460240.0530630788,3349814.038842654
FR,FRA,4,7,9403513.873241574,5732924.261110954,14807525.773841646
FR,FRA,4,8,97359.1291468069,59355.73882808106,153309.4791578328
FR,FRA,5,9,7846776.783016149,4344132.234302799,12356162.921897244
FR,FRA,5,10,2615779.551111851,1448147.7656418395,4119015.8959615137
HR,HRV,1,1,364900.3569436698,297360,588750.8589884269
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HR,HRV,4,2,591413.3376309428,297360,954219.7038770819
HR,HRV,5,4,674565.9141842033,297360,1088382.770427303
HU,HUN,1,1,939019.3767390096,830320.0000000002,1495229.7632223081
HU,HUN,2,1,1030680.601116359,830320.0000000001,1641184.7820616092
HU,HUN,3,1,1204309.5156923695,830320,1917659.5037352087
HU,HUN,4,2,1379150.8730019324,830320.0000000001,2196064.835688338
HU,HUN,5,3,1628360.5241700644,830320.0000000001,2592889.1152925356
IE,IRL,1,4,427687.7770056366,346100,699661.1454991506
IE,IRL,2,6,516970.68432933354,346100,845720.45457959
IE,IRL,3,7,563085.9842277755,346100,921161.1973052245
IE,IRL,4,9,641225.4891304348,346100,1048990.8395075328
IE,IRL,5,10,725235.0284414106,346100,1186423.363108502
LT,LTU,1,1,296845.35974973935,266300,453469.6310961922
LT,LTU,2,3,330121.5716151502,266300,504303.34307204484
LT,LTU,3,3,368832.34409853554,266300,563439.048384362
LT,LTU,4,4,423830.5093167702,266300,647455.849972591
LT,LTU,5,6,481950.8170036937,266300,736242.12747481
LV,LVA,1,1,182289.19339885036,166540,283808.75933954684
LV,LVA,2,1,217955.50864267495,166539.99999999997,339338.17658489663
LV,LVA,3,2,256737.2466257669,166540.00000000003,399718.0418791062
LV,LVA,4,3,283406.8767320127,166540,441240.38608048216
LV,LVA,5,5,329768.59536997584,166540,513421.63611596805
MT,MLT,1,2,41011.04646330313,34540,63581.68998943899
MT,MLT,2,2,49674.76146648259,34540,77013.52577499775
MT,MLT,3,3,56653.23175913561,34540,87832.63362548876
MT,MLT,4,4,65952.34692731153,34540,102249.56537406307
MT,MLT,5,5,73773.79307094037,34540,114375.58523601147
NL,NLD,1,5,1651271.2910618794,1524340,2516419.815479265
NL,NLD,2,6,1876852.86377788,1524340,2860190.0624775514
NL,NLD,3,7,2151819.936607102,1524340,3279220.2935589775
NL,NLD,4,7,2544665.9806903847,1524340,3877889.6794526177
NL,NLD,5,9,2891344.5673199752,1524340,4406203.149031588
NO,NOR,1,8,485312.70728271006,463329.4,766036.4096222686
NO,NOR,2,9,521627.48526109435,463329.4,823357.0643699018
NO,NOR,3,10,623247.5800901967,463329.4,983758.165392408
NO,NOR,4,10,780835.8621076765,463329.4,1232501.6249055946
NO,NOR,5,10,876152.8996448411,463329.4,1382953.7357098276
PL,POL,1,1,3528911,2822000,5705032.108768991
PL,POL,2,1,4100522.522522522,2822000,6629130.815064876
PL,POL,3,2,4758843.76875375,2821999.9999999995,7693409.241931967
PL,POL,4,3,5359775.246636772,2822000,8664908.204782728
PL,POL,5,4,5748864.675101013,2822000,9293931.629451435
PT,PRT,1,2,1022493.0247388677,816540,1615924.2099953631
PT,PRT,2,3,1197537.2491828012,816540,1892560.0336686375
PT,PRT,3,4,1349208.072878092,816540,2132257.078078062
PT,PRT,4,5,1440476.0594474594,816540,2276494.8826661543
PT,PRT,5,7,1544467.0301120149,816540,2440839.7955917837
RO,ROU,1,1,1855835.015636276,1493939.9999999998,3043503.616331723
RO,ROU,2,1,2100008.6821705424,1493940,3443939.770865227
RO,ROU,3,1,2395750.421813799,1493940,3928945.7366546425
RO,ROU,4,2,2681875.6605516695,1493940,4398180.981967612
RO,ROU,5,4,3049484.165361729,1493940,5001045.894180794
SE,SWE,1,5,1073950.664349686,1019960,1438968.2638728165
SE,SWE,2,7,1212707.4260829703,1019959.9999999999,1624886.0933970092
SE,SWE,3,8,1437206.6401006712,1019960,1925688.7791809777
SE,SWE,4,9,1664469.759659558,1019960,2230194.775079771
SE,SWE,5,9,1925129.315091074,1019960,2579448.0884694257
SI,SVN,1,2,205617.5276908768,176540,289077.6412020105
SI,SVN,2,3,250762.92607802871,176540,352547.5477972447
SI,SVN,3,3,288417.2959082823,176540,405485.8188372617
SI,SVN,4,3,338223.72629843367,176540,475508.6693965914
SI,SVN,5,5,384743.86474465457,176540,540911.3227668914
SK,SVK,1,2,464924.4233507356,369380,765388.786802516
SK,SVK,2,3,590906.7573265865,369380,972789.088695418
SK,SVK,3,3,672965.6100104275,369380,1107879.7024546147
SK,SVK,4,4,741474.0824372759,369380,1220662.8000139399
SK,SVK,5,5,824339.1287128713,369380,1357080.622033511
TR,TUR,1,1,6927880.4113648245,4326720,13585525.556542655
TR,TUR,2,1,3279231.92812372,1830590.4759567378,6430551.1238723695
TR,TUR,2,2,4471446.639376767,2496129.5239874385,8768475.924370412
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UK,GBR,1,4,4775835.5618862845,4047936.045271069,7130724.511623151
UK,GBR,1,5,1895007.817251003,1606183.9546441725,2829406.1881084004
UK,GBR,2,6,7756453.016574586,5654120,11581037.272291804
UK,GBR,3,8,8809951.103810776,5654120,13153998.597332934
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UK,GBR,5,10,10681240.155608008,5654120,15947990.672033325
analysis/figures/unnamed-chunk-1-1.png

33.2 KiB

......@@ -599,6 +599,36 @@ flextable(eemrio_bp) %>%
Here we aggregated the data of 28 European countries with 5 income groups each into 10 European expenditure groups, to decompose the total European household energy and carbon footprint by European expenditure decile, ranking each national income group according to their mean consumption expenditure in PPS euros. We call these European expenditure deciles, although only countries with EUROSTAT HBS data from 2005 to 2015 are included, which excludes Italy and Luxembourg, but includes the UK, Norway and Turkey.
## Unit of analysis
```{r }
### ae vs. per capita
data_population_households = read_csv(here("analysis","data","raw","data_population_households_ingram.csv")) %>%
rename(total_population = pop_estimate_per_quintile)
data_population_households %>%
group_by(eu_q_rank) %>%
select(-total_households) %>%
summarise(total_adult_eq = sum(total_adult_eq),
total_population = sum(total_population)) %>%
pivot_longer(cols = -eu_q_rank, names_to = "indicator", values_to="value") %>%
ggplot(aes(x=factor(eu_q_rank), y=value)) +
geom_col() +
facet_wrap(~indicator, scales="free_y") +
theme_ipsum()
#eu_ntile_name = pdat_country_summary_by_eu_ntile %>%
# ungroup() %>%
# select(eu_q_rank, eu_ntile_name) %>%
# unique() %>%
# arrange(eu_q_rank)
```
## Alternative method
Our methodology used for the main paper, and explained in the sections above, keeps the production sector shares of EE-MRIO household final demand expenditure (and subsequently the footprint) the same as they are found in the original EE-MRIO household final demand expenditure when not decomposed by income quantile. The alternative method is to keep the consumption category shares of total HBS expenditure the same as they are found in the HBS. This means taking the total sum of household final demand expenditure from the EE-MRIO and decomposing it first based on the share of each income quantile's consumption expenditure of the total consumption expenditure as found in the HBS, before decomposing into sectors as well using the HBS 'parts per mille' per sector. This leads to a different total footprint than the original EE-MRIO footprint (when not decomposed by income quantile), because a different amount of final demand expenditure in each sector is now multiplied by the same total intensities per sector that are originally calculated in the EE-MRIO.
......
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