A Comparative Methodological Framework for Evaluating Distributional and Nutritional Effects of Food Carbon Pricing
Ghassan Al-Masbhi, Cathal O’Donoghue, Zeynep Gizem Can, Anna Diop-Christensen, Ana Montes, Emily Paradowska, Martina Pezer, Denisa Sologon
University of Galway; BiOrbic SFI Research Centre, Galway, Ireland; University College of Northern Denmark, Hjørring, Denmark; Luxembourg Institute of Socio-Economic Research, Esch-sur-Alzette, Luxembourg; Institute of Public Finance, Zagreb, Croatia
Cite as: G. Al-Masbhi, C. O’Donoghue, Z. Can, A. Diop-Christensen, A. Montes, E. Paradowska, M. Pezer, D. Sologon; 2026; A Comparative Methodological Framework for Evaluating Distributional and Nutritional Effects of Food Carbon Pricing; International Journal of Microsimulation; 19(2); 1–21. doi: 10.34196/ijm.00336
Abstract
Food systems contribute significantly to greenhouse gas emissions, but carbon pricing in this sector remains limited and its distributional implications are not well understood. This paper develops a cross-country microsimulation framework that links Life Cycle Assessment (LCA) emissions intensities with Household Budget Survey (HBS) microdata to assess a food carbon tax in seven EU Member States and Türkiye. The model applies a uniform carbon tax to emissions embodied in food purchases, assumes full pass through to consumer prices and holds household quantities fixed. It produces household level outcomes on food expenditure, diet related emissions, caloric cost per kilojoule and the tax burden as a share of income. Results point to small but consistent regressive effects: post tax Gini coefficients increase slightly in all countries, Reynolds–Smolensky indices are negative and Kakwani values indicate a higher relative burden on lower income groups. A sensitivity analysis using alternative EU and global LCA datasets shows that, despite variation in some emission factors, the relative ordering of foods and the distributional patterns remain broadly similar. The framework can be further extended to incorporate behavioural responses, alternative tax designs and broader food system policies.
This article contains 5 figures and 2 tables.
Figures
Figure 1. Price per 1000 kJ of Food Energy by Category and Country (€/1000kJ)Figure 2. Price per unit of Energy by Food Group per Country (€/1000 kj per GDP per Capita)Figure 3. Composition of Food Expenditure by Category Across Income Deciles and CountriesFigure 4. Energy-Based Carbon Intensity of Food Consumption Across Income Deciles in Eight European Countries (Relative to National Mean)Figure 5. Carbon Tax Burden on Food as a Share of Income Across Income Deciles in Eight Countries
Tables
Table 1. Distributional Indicators of the Food Carbon Tax Across Countries
Country
Gini (Pre-Tax)
Gini (Post-Tax)
Reynolds–Smolensky Index
Kakwani Index
Average tax rate
IE
0.301
0.304
–0.0026
–0.2496
0.0103
FR
0.306
0.308
–0.0022
–0.1651
0.0122
DK
0.305
0.307
–0.0024
–0.1351
0.0163
UK
0.303
0.305
–0.0020
–0.2021
0.0098
TR
0.394
0.396
–0.0019
–0.3386
0.0055
LU
0.296
0.298
–0.0019
–0.1961
0.0096
PL
0.277
0.279
–0.0023
–0.2174
0.0105
ES
0.285
0.287
–0.0037
–0.1642
0.0129
Table A1. Sensitivity analysis of food emission factors across EU countries
HBSVar
ci_low
ci_high
ci_low_t
ci_high_t
mean_other
Rice
3.585959
4.766041
3.340309
5.011692
4.27
Flours and other cereals
1.414113
1.857887
1.321735
1.950265
1.72
Bread
1.360303
1.639697
1.302143
1.697857
1.55
Other bakery products
1.766372
3.201628
1.467605
3.500395
2.78
Pizza and quiche
1.719267
2.932733
1.466668
3.185332
2.5825
Pasta products and couscous
1.770238
2.693762
1.577994
2.886006
2.465
Breakfast cereals
1.335546
2.396454
1.114703
2.617297
2.0075
Other cereal products
2.1078
8.556199
.7654805
9.89852
6.34
Beef and veal
50.19272
67.63927
46.56099
71.27101
62.945
Pork
4.759902
6.768098
4.341869
7.186131
5.38
Lamb and goat
27.81898
46.29702
23.97253
50.14347
40.2225
Poultry
1.821446
4.742554
1.213379
5.350621
2.5775
Other meats
3.205559
5.598442
2.707448
6.096552
3.8275
Edible offal
7.107489
20.13251
4.396157
22.84384
10.3
Dried, salted or smoked meat
5.832946
6.887054
5.613519
7.106481
6.275
Other meat preparations
1.9457
5.1023
1.288611
5.759388
2.73
Fresh or chilled fish
2.145666
3.406334
1.883241
3.668759
2.47
Frozen fish
2.226454
3.465546
1.96852
3.72348
2.5575
Fresh or chilled seafood
3.93944
4.47256
3.828464
4.583536
4.2575
Frozen seafood
4.910359
10.28564
3.791423
11.40458
8.4975
Dried, smoked or salted fish and seafood
2.226108
5.133892
1.620814
5.739186
2.95
Other preserved or processed fish and seafood-based preparations
2.347288
6.180712
1.54931
6.97869
3.68
Milk, whole, fresh
-.0587203
2.35472
-.5611099
2.85711
.535
Milk, low fat, fresh
.1770255
2.490974
-.3046537
2.972654
.7675
Milk, preserved
.1464105
2.44159
-.3313615
2.919362
.7175
Yoghurt
.1569365
2.431064
-.3164532
2.904453
.7175
Cheese and curd
4.039816
6.724184
3.48103
7.28297
5.8275
Other milk products
.9050175
2.870983
.4957758
3.280224
1.46
Eggs
.4451219
3.118878
-.1114559
3.675456
1.1025
Butter
2.729667
3.402333
2.589643
3.542357
3.1325
Margarine and other vegetable fats
1.852835
4.647165
1.271158
5.228842
2.5375
Olive oil
5.791921
5.896079
5.77024
5.91776
5.83
Other edible oils
2.977505
4.842494
2.589283
5.230717
3.4375
Other edible animal fats
2.806462
5.373538
2.272091
5.907909
3.4375
Fresh or chilled fruit
.5109639
.7370361
.463904
.7840961
.605
Frozen fruit
.4104033
.6775967
.3547835
.7332165
.505
Dried fruit and nuts
4.800905
15.11909
2.653037
17.26696
12.275
Preserved fruit and fruit-based products
.8582021
1.185798
.7900087
1.253991
1.0775
Fresh or chilled vegetables other than potatoes and other tubers
.2552969
.4527031
.2142042
.4937958
.3175
Frozen vegetables other than potatoes and other tubers
.4497801
.6822199
.4013946
.7306053
.5825
Dried vegetables, other preserved or processed vegetables