Energy Vulnerability in the Grain of the City: Toward Neighborhood Typologies of Material Deprivation

Figures & data

Figure 1. Map indicating the locations of case study cities and areas. BUA = Budapest; BUB = Kispest; GDA = Wrzeszcz; GDB = Przymorze; PRA = Hloubětín; PRB = Holešovice; SKA = Debar Maalo and Bunjakovec; SKB = Chair, Skopje Sever, and Gazi Baba.

Table 1. List of indicators that were used in analyses

Indicator category	Name and description	Coding
Expenditure-related indicators	ENER_COSTS: Average monthly share of energy costs (electricity, gas, and heating bills, etc.) in total household income	1 = Less than 10%
		2 = 10–20%
		…
		6 = More than 50%
	ENERbin20: Household spending 20% or more of income on energy costs	1 = Yes
		0 = No
	DH_DISC: Household has been disconnected from the district heating network	1 = Yes
		0 = No
	ELEC_DISC: Household has been disconnected from electricity or gas network	1 = Yes
		0 = No
	ARREARS: Household not able to pay energy bills on time	1 = Yes
		0 = No
	AFFORD: Household cannot afford to keep home adequately warm	1 = Yes
		0 = No
	FOOD: Household has cut back on food	1 = Yes
	WATER: Household has cut back on water heating	0 = No
	LIGHT: Household has cut back on lighting
	APPL: Household has cut back on appliance use
	MEDIC: Household has cut back on other basic expenses (e.g., medicine, clothes)
Self-reported objective housing indicator	COND: Condensation on windows and walls during winter	1 = Yes
		0 = No
	DAMP: Dampness on the walls or floors	1 = Yes
		0 = No
	MOLD: Mold in home	1 = Yes
		0 = No
	LEAK: Home has a leaking roof	1 = Yes
		0 = No
Self-reported subjective energy indicators	WARM: Dwelling not comfortably warm during winter	1 = Yes
		0 = No
	COOL: Dwelling not comfortably cool during summer	1 = Yes
		0 = No
	DAY: Home is generally not heated throughout the day when it is cold outside	1 = Yes
		0 = No
Other relevant housing and sociodemographic indicators	OWNER: Own home	1 = Yes
	RENTER: Rent home	0 = No
	MOVE: When household moved in	1 = During the last 5 years
		2 = 5–10 years ago
		3 = 10–20 years ago
		4 = More than 20 years ago
	SQM: Dwelling area of home in square meters
	ROOMS: Number of rooms in home (excluding bathrooms)
	SIZE: Number of people in household
	AGE: Age of respondent in years
	DHeating: Household uses district heating as main heating method	1 = Yes
		0 = No
	EEINDEX: Index of energy efficiency that counts the number of measures installed in the home from the following list: new windows; new heating system; additional insulation; solar thermal panels; energy-efficient appliances.	Possible answers range from 0 (no measures installed) through to 5 (all measures installed)
	EDUC3: Three-level education variable	1 = Primary
		2 = Secondary
		3 = Tertiary
	FTWORK: At least one full-time worker in the household	1 = Yes
		0 = No
	INC: Net monthly household income	Income bands vary by country according to income trends
	INCbin: Household has above median income	1 = Yes
		0 = No
	CHILDHH: Household contains children	1 = Yes
	PENSonly: Pensioner-only household	0 = No
	UNDEROCCUPY: Underoccupancy, measured using standard methodology, where underoccupancy is defined as occurring when rooms = > number of people	1 = Yes
		0 = No

Table 2. Principal features of the case study areas as established by the authors' household survey

City	Budapest		Gdańsk		Prague		Skopje
District	VIII	XIX	Wrzeszcz	Przymorze	7	14	Bunjakovec/Debar Maalo	Chair, Skopje Sever, Zhelezara
Code used in text	BUA	BUB	GDA	GDB	PRA	PRB	SKA	SKB
Sample size	293	228	298	300	317	303	300	300
Sampling ratio (nth term)	148	91	175	159	142	152	128	134
Response rate (%)	21.3	28.5	40.0	40.0	10.5	8.9	54.2	50.8
Average size of dwelling (m^2)	59.5	69.1	52.8	56.0	79.6 (82.9)	79.6 (91.1)	78.3	104.5
Average number of rooms per dwelling	2.3	3.6	2.9	2.9	3.1 (3.1)	3.5 (3.8)	3.5	3.3
Average household size	2.6	2.6	2.5	2.6	2.4 (2.7)	2.6 (3.0)	3.1	4.3
Owner occupancy rate (%)	60.4	82.0	37.7	50.7	45.4 (58.7)	52.8 (64.7)	90.3	95.0
Residency ≤ 20 years (%)	71.7	49.1	50.7	53.3	33.1 (47.1)	43.2 (52.6)	45.4	29.4
Residency ≥ 20 years (%)	27.3	50.9	48.3	45.0	66.9 (52.9)	56.4 (47.1)	54.3	69.6
Residents with a tertiary education (%)	45.7	43.9	24.6	36.0	51.1 (54.6)	42.3 (49.5)	70.2	40.8
Share of households with at least one resident in full-time employment (%)	58.7	62.7	67.0	64.3	59.0 (79.2)	63.0 (80.6)	71.2	58.9
Heating degree days	2,856		4,004		3,431		2,646
Cooling degree days	260		12		67		346

Note: Figures in brackets for Prague refer to post hoc weighted results. BUA = Budapest; BUB = Kispest; GDA = Wrzeszcz; GDB = Przymorze; PRA = Hloubětín; PRB = Holešovice; SKA = Debar Maalo and Bunjakovec; SKB = Chair, Skopje Sever, and Gazi Baba. Source for heating and cooling degree data: Boerman and Petersdorf (2007).

Table 3. Final logistic regression model: Energy burdens (Method: Backward likelihood ratio)

	BUA		BUB		GDA		GDB		PRA		PRB		SKA		SKB
Variable	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
Age of respondent	1.028^*	1.005, 1.051	0.989	0.965, 1.013	1.006	0.982, 1.030	1.002	0.997, 1.006	1.041^*	1.009, 1.075			1.018	0.995, 1.042	1.024	0.996, 1.053
Energy efficiency index	0.837	0.621, 1.127	0.970	0.737, 1.277	0.904	0.678, 1.206	0.676^**	0.505, 0.906	0.966	0.677, 1.378	1.086	0.785, 1.503	1.009	0.794, 1.282	1.324^*	1.029, 1.705
Number of rooms	1.231	0.781, 1.941	0.981	0.711, 1.354	0.782	0.572, 1.069	1.512^*	1.001, 2.286	0.796	0.452, 1.404	0.624^**	0.460, 0.845	1.332	0.934, 1.898	1.229	0.881, 1.713
Household size	1.114	0.781, 1.587	1.001	0.663, 1.510	1.118	0.747, 1.673	0.826	0.552, 1.234	1.376	0.760, 2.490	1.168	0.807, 1.690	1.068	0.701, 1.628	0.896	0.687, 1.168
Below median income	4.768^***	2.494, 9.113	3.115^**	1.499, 6.473	1.306	0.683, 2.497	2.074^*	1.122, 3.834	1.089	0.353, 3.364	1.929	0.604, 6.164	2.617^*	1.176, 5.821	0.318^***	0.161, 0.628
Households with children	0.733	0.331, 1.623	1.470	0.564, 3.833	0.605	0.263, 1.396	1.109	0.501, 2.453	1.330	0.460, 3.850	0.377	0.139, 1.026	0.976	0.471, 2.022	0.589	0.290, 1.198
Pensioner-only households	0.330^*	0.120, 0.909	1.730	0.660, 4.536	0.365^*	0.146, 0.913	1.365	0.704, 2.645	1.713	0.444, 6.607	0.533	0.151, 1.889	0.809	0.291, 2.249	1.025	0.254, 4.146
Rented dwelling	0.749	0.093, 6.058	0.552	0.088, 3.480	0.136^***	0.063, 0.294	0.307	0.070, 1.349			0.122	0.012, 1.247	0.590	0.078, 4.471	1.194	0.205, 6.953
Owner of dwelling	0.660	0.084, 5.192	0.993	0.207, 4.757			1.075	0.288, 4.006			0.242	0.025, 2.313	0.303	0.049, 1.869
District heating user	0.843	0.281, 2.530	0.791	0.404, 1.549	0.994	0.553, 1.786	0.626	0.196, 2.004	0.912	0.332, 2.504	0.196^***	0.090, 0.424	0.525^*	0.297, 0.927	3.024^*	1.154, 7.927
Underoccupying home	0.608	0.228, 1.618	0.697	0.235, 2.066	1.495	0.611, 3.656	0.791	0.328, 1.908	1.047	0.283, 3.873			0.579	0.231, 1.449	0.645	0.184, 2.257
Constant	0.167		1.330		1.509		0.634		0.015		9.123		0.351		0.322
Nagelkerke R^2	0.211		0.121		0.234		0.156		0.109		0.210		0.108		0.272
Hosmer and Lemeshow Test Sig.	0.486		0.141		0.138		0.497		0.397		0.387		0.604		0.057

Note: BUA = Budapest; BUB = Kispest; GDA = Wrzeszcz; GDB = Przymorze; PRA = Hloubětín; PRB = Holešovice; SKA = Debar Maalo and Bunjakovec; SKB = Chair, Skopje Sever, and Gazi Baba; OR = odds ratio; CI = confidence interval. Values shown in bold indicate statistical significance at the p ≤ 0.05 level.

* p < 0.05.

** p < 0.01.

*** p < 0.001.

Table 4. Final logistic regression model: Dwelling not comfortably warm during winter (Method: Backward likelihood ratio)

	BUA		BUB		GDA		GDB		PRA		PRB		SKA		SKB
Variable	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
Age of respondent	0.985	0.963, 1.008	0.985	0.956, 1.015	0.988	0.965, 1.013	1.000	0.996, 1.004	0.992	0.968, 1.018	1.027	0.993, 1.061	0.989	0.966, 1.013	0.986	0.955, 1.017
Energy efficiency index	0.714^*	0.521, 0.978	0.679^*	0.470, 0.981	0.280^***	0.175, 0.449	0.732	0.463, 1.157	0.616^**	0.425, 0.891	0.813	0.520, 1.270	0.873	0.674, 1.131	0.397^***	0.289, 0.546
Number of rooms	0.784	0.498, 1.235	1.069	0.721, 1.583	1.394^*	1.072, 1.812	1.802	0.967, 3.357	0.419^**	0.225, 0.780	0.885	0.591, 1.325	1.286	0.905, 1.827	0.669^*	0.457, 0.980
Household size	1.369	0.966, 1.939	0.835	0.519, 1.342	1.483^*	1.050, 2.094	1.262	0.736, 2.165	3.113^***	1.633, 5.935	1.380	0.687, 2.770	0.954	0.611, 1.491	1.427^*	1.045, 1.948
Below median income	1.655	0.881, 3.108	0.731	0.291, 1.835	1.722	0.870, 3.410	2.628^*	1.137, 6.075	2.551	0.996, 6.536	1.264	0.334, 4.785	2.110	0.959, 4.644	2.276^*	1.072, 4.833
Households with children	0.888	0.392, 2.011	1.090	0.354, 3.359			0.730	0.232, 2.295	0.279^*	0.105, 0.747	0.237	0.037, 1.526	0.662	0.304, 1.441	0.476	0.204, 1.110
Pensioner-only households	2.540	0.898, 7.185	1.630	0.474, 5.604	4.054^**	1.445, 11.376	2.601	0.873, 7.744	0.748	0.185, 3.017	0.981	0.221, 4.359	1.443	0.502, 4.146	0.630	0.130, 3.064
Rented dwelling	0.809	0.120, 5.451	0.768	0.059, 9.941	0.328^**	0.156, 0.687	1.699	0.306, 9.423			0.762	0.044, 13.095	1.219	0.165, 9.032	0.422	0.049, 3.637
Owner of dwelling	0.513	0.077, 3.402	1.621	0.175, 14.977			0.123^*	0.024, 0.637			0.328	0.019, 5.585	0.898	0.149, 5.410
District heating user	0.925	0.271, 3.153	1.867	0.827, 4.219	0.473^*	0.250, 0.895	4.546	0.505, 40.936	0.572	0.182, 1.797	0.701	0.272, 1.808	0.855	0.472, 1.550	0.082^***	0.023, 0.292
Underoccupying home	1.248	0.469, 3.322	0.396	0.108, 1.458			0.245^*	0.062, 0.972	8.340^***	2.439, 28.513	2.454	0.595, 10.118	0.844	0.327, 2.177	1.644	0.376, 7.182
Constant	1.045		1.210		0.338		0.016		0.166		0.040		0.481		8.117
Nagelkerke R^2	0.113		0.083		0.311		0.382		0.205		0.108		0.061		0.470
Hosmer and Lemeshow test sig.	0.178		0.793		0.493		0.491		0.612		0.340		0.147		0.078

Note: BUA = Budapest; BUB = Kispest; GDA = Wrzeszcz; GDB = Przymorze; PRA = Hloubětín; PRB = Holešovice; SKA = Debar Maalo and Bunjakovec; SKB = Chair, Skopje Sever, and Gazi Baba; OR = odds ratio; CI = confidence interval. Values shown in bold indicate statistical significance at the p ≤ 0.05 level.

* p < 0.05.

** p < 0.01.

*** p < 0.001.

Figure 2. Distribution of energy burdens by income in Budapest (authors' own data). The overall height of each column indicates the proportion of households within the given income band.

Figure 3. Distribution of energy burdens by income in Gdańsk (authors' own data). The overall height of each column indicates the proportion of households within the given income band. GDA = Wrzeszcz; GDB = Przymorze.

Figure 4. Distribution of energy burdens by income in Prague (authors' own data). The overall height of each column indicates the proportion of households within the given income band. PRA = Hloubětín; PRB = Holešovice.

Figure 5. Distribution of energy burdens by income in Skopje (authors' own data). The overall height of each column indicates the proportion of households within the given income band. SKA = Debar Maalo and Bunjakovec; SKB = Chair, Skopje Sever, and Gazi Baba.

Figure 6. Shares of households that stated that they were unable to keep the home warm versus those with disproportionately high energy burdens (i.e., more than 20 percent of income). Data point diameters are proportional to the share of households with incomes lower than two thirds of the national mean (corresponding figures are indicated in parentheses next to the case study area codes). Source: Based on authors' own data and World Bank databases. BUA = Budapest; BUB = Kispest; GDA = Wrzeszcz; GDB = Przymorze; PRB = Holešovice; SKA = Debar Maalo and Bunjakovec; SKB = Chair, Skopje Sever, and Gazi Baba.

Figure 7. Selected energy poverty–related housing symptoms in the eight study areas, expressed as a percentage of all households in the given area (authors' own data). BUA = Budapest; BUB = Kispest; GDA = Wrzeszcz; GDB = Przymorze; PRA = Hloubětín; PRB = Holešovice; SKA = Debar Maalo and Bunjakovec; SKB = Chair, Skopje Sever, and Gazi Baba.

Figure 8. Selected energy vulnerability–related household strategies in the eight study areas, expressed as a percentage of households that stated that they could not afford to keep their home adequately warm in the given area (authors' own data). BUA = Budapest; BUB = Kispest; GDA = Wrzeszcz; GDB = Przymorze; PRA = Hloubětín; PRB = Holešovice; SKA = Debar Maalo and Bunjakovec; SKB = Chair, Skopje Sever, and Gazi Baba.

Boermans, T., and C. Petersdorf. 2007. U-values for better energy performance of buildings. Cologne: Ecofys.

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