Analysis of Affordability of Cost Recovery:
Communal and Network Energy Services
September 30, 1998
By
Clare T. Romanik
The Urban Institute
under contract to
The World Bank
EXECUTIVE SUMMARY
The following analysis compares the housing-utility burden of Russian households
under the current (1996) subsidized rate scheme with the burden they would experience
under a rate scheme that would cover the full cost of providing the same services. Special
attention is given to the relative impact of the new scheme on households in different
expenditure categories and on households living in urban and rural areas. In this analysis,
households are grouped into quintiles based on total expenditures, which serve as a proxy
for income. The analysis uses a sample of households that is 68 percent urban, 6 percent
PGT (poselok gorodskogo typa), and 26 percent rural (using GOSKOMSTAT settlement
type definitions). Rural households comprise a disproportionate share (33 percent) of the
households in the lowest quintile. In addition, households in the lowest quintile are much
more likely to be one-to-two member households, to be composed of pensioners without
working age adults, and to occupy more space per capita than households in the higher
expenditure quintiles.
By Western standards, housing and utility charges in Russia are very low—
households in the highest expenditure quintile on average spend more money on alcohol
and tobacco than on all housing-related costs. The mean combined housing-utility charge
for the sample is 97 thousand rubles (19 US dollars at an exchange rate of 5000 rubles to
$1); at full-cost recovery levels, the mean charge is 285 thousand rubles ($57). “Standard”
units in the sample (with district heat and hot water, gas stove, central water and sewerage
and telephone connections), were on average 49 square meters—one square meter larger
than the overall sample mean; their higher mean charge of 371 thousand rubles ($74)
reflects greater amenities.
The analysis defines the housing-utility cost burden to be housing and utility charges
as a share of total expenditures, and then uses this measure to illustrate how burdens
increase with the introduction of full-cost recovery measures. A household paying out 20
to 29 percent of its expenditures on housing and utility services has a moderate burden;
one paying 30 percent or more has a high burden. With full-cost recovery tariffs and no
income growth, nearly all (97 percent) of the households in the lowest expenditure quintile
have moderate or high burdens while only a few (8 percent) of the households in the
highest expenditure quintile fall into this category. The share of the overall population with
moderate or high burdens increases from 12 to 54 percent when tariffs increase to full-cost
recovery levels. We can put the latter figures into perspective by comparing them with
figures for the United States: according to the American Housing Survey for the United
States in 1995, 54 percent of U.S. households had moderate or high burdens. However,
the figures for Russia are not directly comparable because they overstate the housing-utility
burden. The Russian sample comprises owners occupying their own unit and public
renters paying below-market rent, and the market value of their housing is not counted as
income.
To assist households facing a moderate or high housing-utility burden, municipalities
will have to set aside funds for housing allowances, distributed on a means-tested basis.
i
Despite the higher costs associated with operating a housing allowance program, raising
tariffs to full-cost recovery levels will help municipalities balance their budgets. At 1996
tariffs, a municipality must provide an average annual effective subsidy of 2.6 million rubles
($513) per household because of low tariffs, housing benefits and housing allowances, and
non-collection (arrears). If tariffs increase to full-cost recovery levels with zero income
growth and the same levels of energy consumption, a municipality will still have to provide
an average annual subsidy of 1.1 million rubles ($225) per household because of increased
participation in the housing allowance program and continuing non-collection. However,
this means that a municipality will be subsidizing only one-third of housing-utility costs
(referred to as the subsidy burden of the municipality), as opposed to subsidizing threequarters of the costs under the current rate scheme. For a municipality with 50,000
households, the savings from lower subsidies annually amounts to 72.2 billion rubles ($14.4
million).
Sensitivity analysis was performed to see how assumptions about income growth
and energy conservation affect the housing-utility burdens faced by households and
municipal subsidies. With 3 percent annual growth in real income from 1996 to 2003, the
share of households with moderate or high burdens drops from 54 to 44 percent and the
municipality’s subsidy burden drops from 33 to 28 percent. Assuming a modest decline in
energy demand due to low-cost investments in energy conservation measures causes the
share of households with moderate or high burdens to fall from 54 to 49 percent and the
municipality’s subsidy burden to decrease from 33 to 30 percent of costs.
Access to utility services is weakly correlated with expenditures, but strongly
correlated with settlement type. Services like district heat, centrally-supplied hot water, and
sewerage are available to most urban households; few rural households have this access
to these services. The majority of rural households have to use coal for heating, bottled
gas and coal for hot water, and bottled gas for cooking. At current tariffs, coal is the most
expensive form of heating; however, cost recovery levels of coal are currently twice those
for district heat and gas boiler heating on average.
Reliance on fuels that already have higher cost recovery levels, helps explain why
rural households experience smaller payment increases under a full-cost recovery
scenario—both in terms of absolute and percentage increases. If rates are brought up to
full-cost recovery levels, the average total housing-utility charge for rural households
increases from 95 to 214 thousand rubles; the average total charge for urban households
increases from 100 to 316 thousand rubles. Compared to households in the highest
quintile, households in the lowest quintile experience similar smaller increases in total
charges when housing-utility charges are brought up to full-cost recovery levels. The
average charge for households in the lowest quintile increases from 69 to 195 thousand
rubles; the average charge for households in the highest quintile increases from 128 to 397
thousand rubles. Households in higher quintiles will tend to have a greater increase
because they typically occupy larger units and have more family members (both factors
affecting housing and utility charges).
ii
Thirty percent of households in the sample reported that they had arrears in housing
or utility bills. Since the incidence of arrears varies little by income, it indicates a serious
problem of enforcement as opposed to a problem of households not having the ability to
pay. Although the incidence of arrears does not vary much by settlement type, it can vary a
lot for individual oblasts, krais, and cities. For example, default rates range from 8 percent
in Moscow City to 71 percent in Kurgan, indicating real differences in the efforts or ability to
control this problem. The average cumulative household arrearage (among those
households in arrears) also varies by individual oblasts, krais, and cities, ranging from 15
to 450 thousand rubles ($3-90). Cumulative arrears are particularly high in PGT (about 400
thousand rubles per household on average), and are lowest in rural areas (about 186
thousand rubles per household on average).
iii
DESCRIPTION OF THE SAMPLE
This analysis uses data from Round 7 of the RLMS (Russian Longitudinal Monitoring
Survey), which was conducted in the last quarter of 1996.1 The original Round 7 sample
had 3562 household records. After cleaning the data for this analysis, 2990 records
remained. The original RLMS sample was designed to be representative of the population
of the Russian Federation. The resulting sample after cleaning should also be
representative of this population, except for the exclusion of households renting their units
at market value.2 Using GOSKOMSTAT settlement type definitions, the resulting sample is
68% urban, 6% PGT (poselok gorodskogo typa), and 26% rural. The reader should
carefully interpret statistics presented for PGT because of the relatively small number of
cases in the PGT category. Household size does not vary by settlement type, having a
median value of three persons for all settlement types.
This is not a poverty study. Specialists in poverty studies measure current
consumption because they are trying to assess the household’s welfare. Knowing that
income will vary over a lifetime, the household saves. When current resources fall, the
household may rely on savings to continue its habitual level of consumption. This is known
as consumption smoothing. A poverty study would not consider money invested or put in
savings because the household is, in effect, setting aside the money for future
consumption.
1
In Round 7 of the RLMS, 77 percent of the interviews were held in October, 23 percent in
November, and less than one percent in December 1996. See Poverty in Russia: Public Policy and Private
Responses, (ed. Jeni Klugman), Washington, DC, The World Bank for a detailed description of the RLMS.
2
Annex 1 includes a detailed description of the process of cleaning the data and imputing unit
characteristics. Cases were removed if they did not have pertinent information on expenditures, utility
connections, or unit type, and this information could not be imputed. Also, all households renting on the
secondary market (as opposed to renting from municipalities and enterprises) were excluded. Households that
split were not included, because it could not be determined whether the new households resided in separate
units or in the same housing unit.
1
This study measures income (including from past savings) because it is the current
resources of the household that determine its ability to pay for housing and utility services.
Household expenditures are used as a proxy for household income because of the problem
of underreported income in surveys.3 For the sample as a whole, the average reported
total expenditures is 50 percent more than the average reported total income. The
variance between reported expenditures and income grows with wealth: average reported
total expenditures for the highest expenditure quintile is twice the reported income; in the
lowest expenditure quintile there is little difference between the reported figures. Questions
on both income and expenditures were quite thorough in the RLMS.4 This together with the
anonymity of the survey may have encouraged some households to reveal more income
than they would to the government. The mean monthly income reported in the RLMS
(1,192 thousand rubles) is 34 percent higher than the official mean monthly income (892
thousand rubles) for September 1997, nearly a year later.
In addition to reported expenditures, total household expenditures include an
imputed value for food produced and either consumed or given away by the household
(imputed by the Carolina Population Center of the University of North Carolina, responsible
for designing the RLMS) as well as an imputed value for housing and utility charges
(imputed as part of this report). Households reported what they had paid in the past 30
days for housing and communal services; however, in this time they might have paid none
of what they owed for that month, some of what they owed, exactly what they owed, or
what they owed for that month plus past arrears. Thirty percent of the households reported
that they were in arrears. In addition to arrears, many households were eligible for housing
benefits because they were veterans, disabled or had an occupation designated as special.
Other households were also participants in the new housing allowances program which
targets subsidies to low-income households whose housing-utility burden is more than a
certain percent of total income. Finally, some households might be paying up past arrears
or building a stock of coal or firewood for the whole winter. Thus the reported value often
does not correspond to the family’s usual housing-related liabilities.
Table 1 compares imputed monthly housing and utility charges with those reported
in the RLMS.5 Since most households spend a relatively small share of their budget on
3
For a discussion of problems encountered in measuring income with households surveys in
Russia, see Poverty in Russia: Public Policy and Private Responses. One serious problem with measuring
income in Russia is the common delay of salary payments.
4
Although the RLMS was quite thorough in its questions, it is very difficult to obtain the monetary
value of many in-kind benefits that employees receive. For example, respondents were asked if they had
received goods and services from their place of work. However, it is unlikely that respondents would cite
benefits such as free lunches, subsidized food in schools and kindergartens managed by enterprises, and
subsidized vacations.
5
The reported charges had three components: (1) a question on all charges for housing and
communal services; (2) a question on purchases of coal, firewood, peat, kerosene; and (3) a question on
purchases of bottled gas. The households were to report expenditures within the past 30 days. However, the
2
housing and utility charges, the imputation process does not greatly affect total
expenditures. Annex 2 provides more information on the imputation process and a
comparison of total expenditures based on the imputed and reported charges.
Table 1
Comparison of Reported and Imputed Monthly Housing and Utility Charges, per Household
(1996 Thousand Rubles)
Methods for Estimating Housing
and Utility Charges
Reported total rent and utility
expenditures
Reported total rent and utility
expenditures with 0 values
excluded
Imputed total rent and utility
expenditures
Minimum
Value
Median
Value
Mean Value
Maximum
Value
0.0
47.5
71.1
1,170.0
0.8
75.0
97.8
1,170.0
15.1
88.2
97.2
377.9
Table 2 shows that the mean monthly total expenditure level of the sample is 1,797
thousand rubles (1996 rubles). At an exchange rate of 5000 rubles to one US dollar this is
$359. The median for the sample 1,152 thousand rubles, or $230. The mean expenditure
level for rural households is below the sample average because they are overrepresented
in the lowest quintile and underrepresented in the highest quintile. Although rural
households make up 26 percent of the sample, they represent 33 percent of the
households in the lowest expenditure quintile and only 17 percent of the households in the
highest expenditure quintile. The opposite is true of urban households which are
overrepresented in the highest quintile and underrepresented in the lowest quintile. The
expenditure disparity among all households is high: the mean expenditure level of the
lowest quintile (331 thousand rubles) is only 7 percent of the mean expenditure level of the
highest quintile (4,912 thousand rubles).
Table 2
Total Monthly Household Expenditures By Settlement Type (1996 Thousand Rubles)
latter two categories are generally ‘lumpy’ purchases (purchased less frequently than on a monthly basis) so
some households would report an amount much larger than that needed for one month, while others would
report zero spending. These values were adjusted to a third of the reported amount to compensate.
3
All
Households
N = 2990
Urban
N = 2024
PGT
N = 188
Rural
N = 778
All Households
mean
median
1,796.6
1,152.4
1,948.5
1,227.1
1,605.1
1,090.7
1,447.8
974.1
By Expenditure Quintile (mean)
Lowest
2
3
4
Highest
331.0
727.2
1,161.9
1,851.2
4,912.0
335.4
725.9
1,167.3
1,870.2
5,041.7
336.2
737.6
1,180.3
1,823.6
4,238.6
321.8
728.0
1,142.5
1,809.2
4,573.9
Households in different expenditure quintiles tend to have different demographic
characteristics. (See Table 3.) About 28 percent of all households in the sample could be
called “pensioner” households. A pensioner household is defined here as a household with
no working age adults (in a few cases, these households might include children under 18
years of age). Pensioner households make up 59 percent of the households in the lowest
quintile and only 7 percent of the households in the highest quintile. Another difference
concerns household size. Households in the lowest quintile on average have fewer than
two household members, while the higher quintiles on average have more than three
household members. This is to be expected, since a household’s income and expenditures
should increase as it includes more working age adults.
Table 3
Pensioner Households and Average Household Size by Expenditure Quintile
Pensioner Households as
a Percentage of all
Households
Average Household
Size
All Households
28
2.8
By Expenditure Quintile
Lowest
2
3
4
Highest
59
32
25
17
7
1.9
2.5
2.9
3.3
3.5
Although households in the higher quintiles tend to have larger apartments, they
tend to have less space per capita than households in the lower quintiles. (See Table 4.)
The latter is true even for households that occupy only part of an apartment or house (the
living space of these households, however, varies little by expenditure quintile).6 Table 3
6
The 10 percent of dwellings that were part of a house or apartment were much smaller on average
4
largely explains this counterintuitive result. Households in the lowest quintile tend to have
fewer members and are more likely to be pensioners. Pensioners may reside in a unit that
used to be occupied by themselves and their children who have since then moved into their
own unit. This finding is counter to the approach of a poverty study which would rate these
pensioners as not poor because their per capita consumption of housing, at least, is
relatively high. From the perspective of housing reform, however, this finding is important
because pensioners with relatively large apartments and relatively low income are facing a
very real problem with respect to space-based fees that should be understood by policy
makers.
Table 4
Total Space and Space Per Capita by Expenditure Quintile and by Type of Space (Square
Meters)
Separate Apartment or
House (Total Space)
N = 2696
Part of Apartment or House (Living
Space Occupied by Household)
N = 294
Per Capita
Total
Total
Per Capita
All Households
50
22
32
14
By Expenditure Quintile
Lowest
2
3
4
Highest
43
48
51
54
55
29
24
21
19
18
26
33
32
35
33
16
15
12
14
11
Table 5 describes the sample in terms of ownership and housing type. The sample
contains 62 percent privatized, private, or cooperative housing units and 38 percent
publicly-owned units. A large share (71 percent) of the units in the rural areas are private
single-family houses. In urban areas, the housing units are overwhelmingly (88 percent)
apartments, but are almost equally split between private (52 percent) and publicly-owned
(48 percent) dwellings.
Table 5
Distribution of Ownership and Unit Type of Housing Units, By Settlement Type
All
Households
N = 2990
Privatized, Private or
61.8
Urban
N = 2024
PGT
N = 188
52.4
(32 square meters) than separate houses and apartments (50 square meters).
5
68.6
Rural
N = 778
84.4
Table 5
Distribution of Ownership and Unit Type of Housing Units, By Settlement Type
All
Households
N = 2990
Urban
N = 2024
PGT
N = 188
Rural
N = 778
Cooperative
Apartments
Single Family Houses
33.0
28.8
41.1
11.4
26.1
42.6
13.6
70.8
Publicly-Owned
38.2
47.6
31.4
15.6
36.4 1.9
47.1
0.5
29.3
2.1
10.2
5.4
Apartments
Single Family Houses
UTILITY SERVICES AND CHARGES
This analysis focuses on the utility component of housing-related costs. Table 6
shows that utility connections vary heavily by settlement type: for example, only 10 percent
of rural households enjoy utility-supplied hot water, while 75 percent of urban households
have this service. Central (district) heating is supplied to most (89 percent) urban
households, but only to 21 percent of rural households. Because of these differences in
utility connections, households from different settlement types are likely to be affected
differently by a rise in utility tariffs.
Table 6
Percent of Households with Utility Connections By Settlement Type
Utility Service
All Households
N = 2990
Urban
N = 2024
PGT
N = 188
Rural
N = 778
Central Heating
70
89
66
21
Network Gas
63
73
92
27
Hot Water
57
75
52
10
Central Water
76
90
81
39
Sewerage
66
87
47
17
Telephone
44
51
53
24
Table 7 shows that, in most cases, households in the highest quintile are more likely
to have a utility connection than households in the lowest quintile. However, the
relationship between wealth and utility connections is not as strong as the relationship
between settlement type and utility connections. Network gas is the one utility service that
does not appear to be related to income. This is because many households in the higher
6
quintiles have units equipped with electric stoves and thus have no need for gas
connections. The weak correlation between income and access to utilities results from the
past practice of administrative allocation of housing and the persistence of underdeveloped
housing markets.
Table 7
Percent of Households with Utility Connections, By Settlement Type and Expenditure Quintile
Utility Service and
Expenditure Quintile
All Households
N = 2990
Urban
N = 2024
PGT
N = 188
Rural
N = 778
Central Heating
Lowest
2
3
4
Highest
61
69
67
70
81
82
90
87
90
93
54
62
56
74
89
23
19
18
21
27
Network Gas
Lowest
2
3
4
Highest
62
63
66
63
60
76
77
76
76
64
92
92
95
94
86
29
22
31
24
30
Hot Water
Lowest
2
3
4
Highest
44
53
55
59
72
65
73
70
79
84
31
41
63
65
64
8
7
11
8
20
Central Water
Lowest
2
3
4
Highest
64
76
77
77
87
80
91
91
92
95
62
77
93
81
92
34
36
36
41
51
Sewerage
Lowest
2
3
4
Highest
56
65
65
68
77
79
89
85
88
92
31
38
51
58
61
19
14
15
18
19
Telephone Connection
Lowest
2
3
32
43
43
39
50
49
33
44
63
19
26
23
7
Table 7
Percent of Households with Utility Connections, By Settlement Type and Expenditure Quintile
Utility Service and
Expenditure Quintile
4
Highest
All Households
N = 2990
46
58
Urban
N = 2024
52
64
PGT
N = 188
71
56
Rural
N = 778
25
33
To highlight the potential impact of reforms, it is useful to compare how much
households relying on a particular fuel were expected to pay based on 1996 charges, with
how much they would be paying if they were charged at full-cost recovery levels.7 (See
Table 8.) The utility charges in Table 8 are broken down by fuel type to show how
households are obtaining heating, cooking, and hot water services. The lowest cost
recovery levels, and thus the greatest jump in charges, are for gas space heat and services
typically supplied by the municipality: district heating, hot water connections, central water,
and sewerage.
Under the 1996 rate scheme, the combined average charges for district heat and hot
water are the same as the combined average charges for heat and hot water fueled by
network gas—46 thousand rubles, or 9 US dollars. When rates are raised to cover the full
cost of providing these services, however, the combined average district heat and hot water
charges become greater—159 thousand rubles ($32), as opposed to 144 thousand rubles
($29). Households without network gas and district heat must use coal, bottled gas or
some other means for obtaining heat and hot water.8 Households using coal for heating
and bottled gas for hot water begin by paying the most at 69 thousand rubles ($14), but end
up paying the least at full-cost recovery levels, roughly 107 thousand rubles ($22). No
matter which fuel type, heating charges are a household’s largest payment both under 1996
charges and at full-cost recovery levels.9
7
As with estimating the current housing and utility costs, the estimates for full cost recovery
depended on the type of service, fuel and unit type. Data on cost recovery levels for communal services were
taken from Form 22 of the Department of Housing and Communal Services. Cost recovery levels for gas and
coal were calculated using 1996 prices and unsubsidized prices. Full information is provided in Annex 3.
8
The RLMS did not explicitly ask households what fuel they used for heating; however, it did ask
households if they had a connection to the district heating network or the natural gas network. It also asked if
the household had purchase firewood, coal, peat, or kerosene (and in a separate question, bottled gas) within
the past 30 days. Combining this information, we categorized households accordingly using “coal-heating” as
a catch-all for households without district heat or network gas.
9
Annex 4 has more information on the breakdown of the housing-utility bill by type of unit and
ownership of unit. Again, regardless of the breakdown, heating charges represent the largest share of a
household’s housing-utility bill.
8
Table 8
Imputed Monthly Utility Charges by Fuel and Utility Connection (1996 Rubles)
Mean Value of Imputed
Charge
(1996 Rubles)
Utility Connection and Fuel Type
At Full Cost
Recovery
Levels
1996
Charges
Ratio of
Average 1996
Charge to
Average Full
Cost Recovery
Charge (%)
Percent of
Households
With
Connection
Heat
27,134.9
41,826.0
60,541.3
91,782.2
131,501.6
96,436.9
30
32
63
69.8
8.6
21.6
3,155.4
7,766.4
10,008.4
7,507.8
9,708.0
22,388.7
42
80
45
60.8
21.5
17.7
18,751.9
4,545.8
8,400.9
(accounted
for in heat)
66,911.6
12,086.3
10,501.1
(accounted
for in heat)
28
38
80
--
56.6
19.1
20.2
4.1
Central Water/Sewerage
Central Water & Sewerage
Only Central Water
Only Sewerage
Neither
13,519.6
7,521.5
2,891.3
0.0
46,627.1
23,262.6
13,068.6
0.0
29
32
22
--
65.6
10.5
0.7
23.2
Telephone
With Connection
No Connection
15,752.1
0.0
26,253.5
0.0
60
--
44.3
55.7
Electricity (Except for Cooking)
14,445.7
33,209.4
44
100.0
Central (District) Heating
Gas Boiler Heating
Coal Heating
Cooking
Network Gas
Bottled Gas
Electric Stove
Hot Water
Hot Water Connection
Gas Boiler (Network Gas)
Gas Boiler (Bottled Gas)
Coal or Other
In 1996, property taxes and payments for capital repair were practically non-existent.
(See Table 9.) Tenants of publicly-owned apartments made one kvarplata payment which
included a nominal rent component. Since 1997, many jurisdictions have instituted
separate capital repair and rent payments, in addition to a maintenance fee. Here, we
assume that rent for tenants of publicly-owned apartments will be equal to the property tax
instituted for owners.10 Thus, future rent and property tax are presented as one category
10
This assumption reflects the principles of the current housing policy by the Government of Russia.
9
here. Also, the average future maintenance fee was calculated for all apartment units,
without regard to tenure.
Table 9
Imputed Monthly Housing Charges by Ownership and Unit Type (1996 Rubles)a
Mean Value of Imputed Charge
(1996 Rubles)
Ownership - Unit Type Category
Maintenance
Publicly-Owned Apartment (APT)
Privatized or Cooperative APT
Single Family Housing (SFH)
1996 Charges
At Full Cost
Recovery
Levels
Percent of
Households
in Each
Category
(included in kvarplata)
15,604.9
0
53,146.1
53,146.1
0
36.4
33.0
30.6
18,308.2
4,542.9
0
0
0
0
36.4
1.9
61.7
0
0
0
0
5,073.4
7,480.5
9,653.7
11,426.0
27.9
18.2
40.7
13.2
0
0
0
0
6,595.4
12,155.9
15,445.9
18,281.6
27.9
18.2
40.7
13.2
Kvarplata
Publicly-Owned APT
Publicly-Owned SFH
Private Housing
Property Tax or Rent
SFH without network gas or without district
heat
APT without network gas or without district
heat
Housing with network gas and district heat
Housing with network gas and district heat in a
large city
Capital Repair
SFH without network gas or without district
heat
APT without network gas or without district
heat
Housing with network gas and district heat
Housing with network gas and district heat in a
large city
Notes:
a
In the future, the kvarplata paid by renters of state-owned units will be divided into a rent payment and a
maintenance payment. The rent payment should be comparable to the property tax charged to owners of
privatized units. Maintenance payments should be the same regardless of ownership of the unit. Having both
network gas and central heating connections is used as a proxy for housing with modern amenities.
Since rural households often do not have access to district heat, network gas, and
centrally-supplied hot water, they more heavily rely on coal for heating, bottled gas for
cooking, and bottled gas or coal for hot water. The high costs of coal heating relative to
10
district heating (at 1996 rates) help drive up the housing and utility charges of rural
households.11 It is not surprising then, that rural households are expected to pay almost as
much as urban households for housing and utility services (see Table 10). It is important to
note that while expected to pay nearly as much as urban households, rural households
generally do not have access to many important services, such as centrally-supplied hot
water and sewerage.
Table 10
Imputed Monthly Utility Charges and their Distribution by Settlement Type: At 1996 Rates
(Mean Value in 1996 Thousand Rubles or Percent Distribution)
All Households
N = 2990
Housing or Utility
Service
Urban
N = 2024
PGT
N = 188
Rural
N = 778
Charge
Share
(%)
Charge
Share
(%)
Charge
Share
(%)
Charge
Share
(%)
Heat
Cooking
Hot Water
Water/ Sewerage
Telephone
Electricity
Rent /Maintenance
35.6
5.4
13.2
9.7
7.0
14.4
11.9
37
6
13
9
7
17
11
29.9
5.0
15.3
11.8
8.2
14.1
15.3
31
5
14
11
8
16
14
28.3
2.8
10.4
8.7
6.7
16.2
8.9
36
4
11
9
8
23
9
52.3
6.9
8.3
4.5
3.8
15.0
3.8
53
8
9
4
3
19
4
Total
97.2
100
99.5
100
82.1
100
94.6
100
A rural household’s relatively high housing and utility costs at the 1996 rates, even in
the absence of many services, partly reflects the relatively high cost recovery levels of the
main fuels on which they rely: coal and bottled gas. This means that when charges are
brought up to full-cost recovery levels the average rural household is now in a better
situation than its urban counterpart. Table 11 shows that the mean housing-utility charge of
rural households (215 thousand rubles) at full cost recovery rates is only about two-thirds
that of urban households (316 thousand rubles).
11
Other explanations for why heating is such a large share of a rural household’s housing costs
include: (1) Many rural households do not have access to and thus, do not pay for sewerage or even central
water; (2) There are more houses than apartments in rural areas which means no maintenance costs as well
as more total space to heat; (3) Under the calculation method used here, the costs of providing hot water with
coal was included in heating charges. (Eleven percent of the rural households were assumed to be using coal
for heating water. See Annex 5 for a complete breakdown of utility services by fuel and settlement type.)
11
Table 11
Imputed Monthly Utility Charges and their Distribution by Settlement Type: At Full Cost
Recovery (Mean Value in 1996 Thousand Rubles or Percent Distribution) a
All Households
N = 2990
Housing or Utility
Service
Heat
Cooking
Hot Water
Water/ Sewerage
Telephone
Electricity
Maintenance
Rent / Property Tax
Capital Repair
Total
Urban
N = 2024
PGT
N = 188
Rural
N = 778
Charge
Share
(%)
Charge
Share
(%)
Charge
Share
(%)
Charge
Share
(%)
96.2
10.6
42.3
33.1
11.6
33.2
36.8
8.2
12.8
37
4
12
10
4
14
11
3
5
93.9
10.6
53.2
40.9
13.7
32.8
14.2
47.8
9.0
31
4
15
12
4
12
5
14
3
79.7
8.1
31.6
27.1
11.1
34.0
13.2
26.0
8.5
36
4
12
10
5
16
6
9
4
106.2
11.2
16.6
14.5
6.4
34.0
8.8
10.9
6.2
51
6
7
5
3
18
4
4
3
284.9
100
316.1
100
239.3
100
214.7
100
Notes:
a
The average unit in the sample has 48 square meters, 2.8 occupants, and an average cost per square meter
of 6,190 rubles. In the entire sample, 70% has central heat, 61% gas stove, 57% hot water connection, 66%
both central water and sewerage and 44% telephone. “Standard” units in the sample, having all of the
abovementioned amenities, make up 24% of the sample. On average, they have 49 square meters, 2.8
occupants and an average cost per square meter of 7,807 rubles. The mean charge for standard units in the
sample is 371,226 rubles, which is 30 percent more than the mean charge of the average unit in the sample.
ARREARS
Before considering raising tariffs, it is also important to analyze why there are arrears
in housing and utility bills. From Table 12, it appears that poor enforcement is a major
cause of high arrears. Thirty percent of households reported that they had arrears in
housing or utility bills.12 The incidence of arrears among households in the highest
expenditure quintile, who clearly have the means to pay, is only slightly lower (27 percent)
than that of all households. The region with the lowest rate of reported arrears is Moscow
City with 8 percent. The city of Kurgan has the highest rate of reported arrears at an
astounding 71 percent. The fact that in Kurgan the cost of housing and utility services is
high in relation to income level may help explain the city’s high arrears rate.
12
The terminology in the RLMS was, “Do you have unpaid housing bills?” which was preceded by the
question, “Have you paid for housing and communal services in the past 30 days?” A third question asked
12
The incidence of arrears is lowest in rural areas, although still high at around 25
percent of the households in each expenditure category. It may be difficult, however, to
define arrears in rural areas. Although 25 percent of rural households reported that they
housing bills that they had not paid, 51 percent of rural households reported they had not
paid a regular housing and communal services bill in the prior thirty days. Even when the
purchase of coal, peat, kerosene, firewood, or bottled gas is taken into account, 32 percent
of the rural households reported no housing related expenditures in the previous thirty
days. Rural households may not report housing-related expenditures if they receive the
goods and services through a barter arrangement between their employer and the utility
company. For example, an agricultural employee may receive very little cash, but their
employer might arrange for their utility payments to be paid through a barter arrangement
with the utility service provider.
Table 12
Monthly Incidence of Arrears and Cumulative Arrearage in Housing and Utility Bills
(Percent of Households in Each Expenditure Quintile, 1996 Thousand Rubles)
All
Households
N = 2990
Urban
N = 2024
PGT
N = 188
Rural
N = 778
Incidence for All Households
30
31
42
25
Incidence by Expenditure Quintile
Lowest
2
3
4
Highest
33
32
31
29
27
35
34
32
30
26
49
56
42
32
25
26
20
25
26
28
250.2
247.6
393.9
185.7
Average cumulative arrearage
(among households in arrears)
It is important to know not only the incidence of arrears, but the amount of arrears. If
a household reported that it had unpaid housing or utility bills, the RLMS asked how much
the family owed. The mean cumulative arrearage of households is 250 thousand rubles,
while the median is 128 thousand rubles. The mean cumulative arrearage in PGT is
particularly high, at close to 400 thousand rubles. As with the incidence of arrears,
cumulative arrearage varies widely for different oblasts, krais, and cities. The place with
the lowest average arrearage, 15 thousand rubles, is the settlement of Betlutsa in
respondents how much they owed. Judging from the rather high amounts reported in response to the third
question, it is most likely that households interpreted this as cumulative arrears.
13
Kalushskaya oblast. In contrast, the city Surgut in Khanty Mansiiskiy AO, Tiumenskaya
oblast, and the settlement Zalokokuazhe in Kabardino-Balkariia have the highest
cumulative arrearage, averaging nearly 450 thousand rubles for the households reporting to
be in arrears. The latter also had the second highest incidence of arrears at 59 percent.
The areas with the highest average cumulative arrearage are not the poorest. The
average total expenditures for Kabardino-Balkariia (2,530 rubles) is well above the sample
mean, and the average for Khanty Mansiiskiy (6,842 rubles) is the highest in the sample.
In both of these locations the cost of housing and utility services in relation to income level
is lower than it is in Betlutsa, which has the lowest cumulative arrears in the sample.
ANALYSIS OF HOUSING-UTILITY BURDEN
In most countries, food and housing dominate a household’s expenditures. In Russia,
food is clearly a household’s most significant expenditure; housing-related costs do not
represent a significant expenditure, except for households in the lowest quintile. Table 13
shows that for households in each of the three highest expenditure quintiles, the average
housing- utility burden (combined housing and utility charges as share of total
expenditures) is less than 10 percent. Households in the second lowest expenditure
quintile on average have a housing-utility burden of 12 percent, while the lowest quintile
has an average housing-utility burden of 25 percent.13
Having to spend little on housing, the wealthier households devote a small portion of
their income to investment and a large portion to other items, including the purchase of
durables. Note that when a household devotes income to investment and purchase of
durables, they are not fully consuming their income today, but are setting aside income for
future consumption. For the poorer households, investment is practically non-existent.
This may reflect in part different demographic characteristics of the quintiles. Younger
wealthier families are establishing their households and saving for retirement. Pensioners
may have less need for durables or savings. However, it also signifies a continuing trend of
income disparity.
13
Note that the imputed housing and utility charges and the resulting housing-utility burdens do not
reflect the fact that many households pay little or none of the prescribed charge because they are recipients of
housing benefits or housing allowances or they simply do not pay and are in arrears. Thus, actual housingutility burdens will be considerably lower and even zero for many households. By calculating what the
housing-utility burden would be without these programs and arrears, we can compare the relative change in
housing-utility burden as a result of policy changes. Later on, we will take into account these programs as well
as arrears in determining the impact of these policy changes on municipal budgets.
14
The very low share of expenditures spent on housing by wealthier households reflects
the low dispersion of housing and utility charges even as income disparity has grown
immensely. Under market pricing, it is normal for wealthier households to have lower
housing-utility burdens than poorer households; however, the particularly low burdens of
Russian households in the highest expenditure quintile is an artifact of universallysubsidized rent and utility services.
Table 13
Average Share of Monthly Household Budget By Category and Expenditure Quintile
(Mean Percent Value)
Expenditure Quintile
All Households
N = 2990
Urban
N = 2024
PGT
N = 188
Rural
N = 778
Food a
All Quintiles
Lowest
2
3
4
Highest
60.0
61.4
67.2
65.8
60.5
45.1
59.0
63.0
66.4
65.5
59.8
42.8
59.4
63.8
67.7
65.7
50.7
45.8
62.8
57.9
68.9
66.7
64.0
55.1
Housing & Utility Charges b
All Quintiles
Lowest
2
3
4
Highest
10.8
24.8
11.8
8.3
6.0
3.3
10.1
23.2
11.8
8.2
6.0
3.4
9.6
22.2
8.7
7.8
5.0
3.2
13.2
28.3
12.8
8.6
6.0
3.2
Alcohol and Tobacco c
All Quintiles
Lowest
2
3
4
Highest
3.5
2.8
3.6
3.7
3.6
3.7
3.7
3.1
3.9
3.8
3.7
3.9
2.8
1.7
2.2
2.6
4.4
3.5
3.0
2.2
3.2
3.5
3.4
2.8
Investment d
All Quintiles
Lowest
2
3
4
Highest
2.9
0.9
1.4
1.8
4.0
6.7
3.2
0.8
1.5
2.1
4.0
6.7
2.8
0.9
2.0
1.5
0.8
8.9
2.4
0.9
1.1
1.1
4.4
5.8
Other Items e
All Quintiles
22.7
24.1
25.4
18.6
15
Table 13
Average Share of Monthly Household Budget By Category and Expenditure Quintile
(Mean Percent Value)
Expenditure Quintile
Lowest
2
3
4
Highest
All Households
N = 2990
10.2
16.0
20.4
26.0
41.1
Urban
N = 2024
9.9
16.5
20.3
26.5
43.1
PGT
N = 188
11.3
19.3
22.5
39.2
38.5
Rural
N = 778
10.6
14.0
20.1
22.2
33.1
Notes:
a
Food includes food produced and either consumed or given away by the family.
b
Housing and utility charges were imputed based on local tariffs, norms and household and dwelling
characteristics. The imputation includes the purchase of coal or bottled gas.
c
Alcohol and tobacco expenditures are probably underestimated because of the difficulty of separating them
from food purchases.
d
Investment expenditures include cash savings, deposits, investments in securities, and loans to others.
e
Other items include, among others, the purchase of durables in the last three months, adjusted to obtain a
monthly figure.
By including per capita expenditures, Table 14 shows that the major difference in the
housing-utility charges of households in the lowest and highest expenditure quintiles is a
result of household size. In other words, unlike in market economies, in Russia there is no
correlation between income and housing-related expenditures. In fact, households in the
lowest quintile on average spend slightly more per capita than their counterparts in the
highest quintile. (This can be explained by the fact that they occupy more space per capita,
shown in Table 4.) Without having to spend more on housing and utility services on a per
capita basis, households in the highest quintile in total still manage to spend more than 7
times the amount spent by households in the lowest quintile on a per capita basis.
To illustrate just how little households in the highest quintile are spending on housing
and utility charges, compare the average amount they spend on housing, 128 thousand
rubles, with the average amount they spend on alcohol and tobacco, 159 thousand rubles.
The average amount households in the highest quintile spend on non-food items (the
categories “alcohol and tobacco” and “other items” from Table 14) is 20 times the average
amount they spend on housing and utility charges.
Table 14
Average Monthly Household Expenditures by Category and Expenditure Quintile
(Mean Value in 1996 Thousand Rubles)
All Households
N = 2990
Expenditure Quintile
Per Capita
Expenditures
Household
Expenditures
16
Urban
N = 2024
PGT
N = 188
Rural
N = 778
Household Expenditures
Table 14
Average Monthly Household Expenditures by Category and Expenditure Quintile
(Mean Value in 1996 Thousand Rubles)
All Households
N = 2990
Expenditure Quintile
Urban
N = 2024
PGT
N = 188
Rural
N = 778
Per Capita
Expenditures
Household
Expenditures
224.1
367.7
494.6
699.2
1,710.4
331.0
727.2
1,161.9
1,851.2
4,912.0
335.4
735.9
1,167.3
1,870.2
5,041.7
336.2
737.6
1,180.3
1,823.6
4,238.6
321.8
728.0
1,142.5
1,809.2
4,573.9
146.9
252.8
330.5
415.1
598.6
211.6
488.7
763.7
1,115.0
1,847.4
218.6
482.2
764.6
1,111.4
1,785.0
226.0
504.0
775.2
922.4
1,764.4
195.7
501.2
757.9
1,160.5
2,151.1
44.9
39.9
37.4
38.0
40.6
69.3
84.7
95.0
108.6
128.1
66.3
84.1
94.8
110.7
133.5
56.8
62.7
89.5
90.3
114.8
77.5
91.3
97.1
106.8
109.2
5.8
12.1
18.0
26.4
56.0
9.4
25.9
42.7
67.9
159.0
11.3
28.2
44.8
69.8
171.0
5.7
13.4
29.8
83.7
138.6
6.4
22.8
40.6
60.1
112.8
Investment
Lowest
2
3
4
Highest
2.8
5.4
11.2
33.1
155.9
3.3
10.5
21.4
74.0
412.1
3.1
10.8
25.2
75.7
406.3
4.2
16.5
16.5
14.4
580.6
3.3
8.2
12.8
81.0
379.4
Other Items
Lowest
2
3
4
23.8
57.5
97.5
186.6
37.4
117.4
239.2
485.7
36.0
120.5
237.9
502.6
43.5
13.9
269.3
712.9
38.8
104.7
234.1
400.8
All Expenditures
Lowest
2
3
4
Highest
Household Expenditures
Food
Lowest
2
3
4
Highest
Housing & Utility
Charges
Lowest
2
3
4
Highest
Alcohol and Tobacco
Lowest
2
3
4
Highest
17
Table 14
Average Monthly Household Expenditures by Category and Expenditure Quintile
(Mean Value in 1996 Thousand Rubles)
All Households
N = 2990
Expenditure Quintile
Highest
Urban
N = 2024
Per Capita
Expenditures
Household
Expenditures
859.4
2,365.3
PGT
N = 188
Rural
N = 778
Household Expenditures
2,545.8
1,640.3
1,821.4
At 1996 tariffs and expenditure levels, housing-utility burdens are not very high for
most households. The mean housing-utility burden for households in the sample is 10.8
percent and the median value is 7.5 percent. Rural households have slightly lower total
charges than urban households (See Table 10), but their mean housing-utility burden is
higher, 13.2 percent compared to 10.1 percent, because of their lower incomes. Nearly 64
percent of the sample has very low housing-utility burdens (defined as less than 10 percent
of their household budgets). Five percent has high housing-utility burdens (defined as
greater than or equal to 30 percent of their household budgets) and another 7 percent has
moderate housing-utility burdens of 20 to 29 percent of their budgets.
By administratively allocating housing and charging low fees for rent and utility
services, the government historically has allowed low-income households to occupy
relatively large units. As shown in Table 4 above, low-income households often have more
space per capita than wealthier households. Since it is the space variable that determines
a household’s largest utility payment—heating—this partially explains the relatively high
housing-utility burden faced by low-income households. (See Table 15.) Low rent and
utility charges do not provide an impetus for a household to find a smaller unit if it becomes
smaller (e.g., children moving out).
Table 15
October 1996 Housing-Utility Burden
Housing-Utility Burden as Percent of Total Expenditures
Very Low
0 - 9%
All Households
Low
10-14%
Low to
Moderate
15-19%
Moderate
20-29%
Total
High
30+%
63.6
16.8
7.7
6.5
5.4
100.0
Lowest
10.9
20.1
18.4
24.2
26.4
100.0
2
41.0
35.6
15.9
6.9
0.7
100.0
3
73.1
21.9
3.8
1.2
--
100.0
Expenditure Quintile
18
Table 15
October 1996 Housing-Utility Burden
Housing-Utility Burden as Percent of Total Expenditures
Total
High
30+%
Moderate
20-29%
--
--
100.0
4
94.0
5.5
Low to
Moderate
15-19%
0.5
Highest
99.2
0.8
--
--
--
100.0
Urban
65.2
17.4
7.6
6.0
3.8
100.0
PGT
71.3
17.6
2.7
4.3
4.3
100.0
Rural
57.7
15.0
9.3
8.1
9.9
100.0
Very Low
0 - 9%
Low
10-14%
Settlement Type
If we hold total expenditures at the same level and allow housing-related costs to rise
to their full-cost recovery levels, the mean housing-utility burden of the sample rises to 31.1
percent, with a median value of 21.9 percent. The median housing-utility burden in the
United States for 1995 was also 22 percent.14 The distributions of housing-utility burden at
full-cost recovery (Table 16) differ dramatically from those computed using 1996 tariffs
(Table 15). Now only 16 percent of the households has a very low burden. Over half of the
sample (54 percent) has moderate or high housing-utility burdens. As expected, the
incidence of moderate or high housing-utility burdens varies heavily by income. Almost all
(97 percent) of the households in the lowest expenditure quintile fall in this category, but
less than 10 percent of the households in the highest quintile do. Burden also varies by
settlement type. The percent of urban households with moderate or high housing-utility
burdens increases by more than 5 times—from 10 percent to 57 percent. The percent of
rural households with moderate or high housing-utility burdens increases less than 3 times:
from 18 percent to 50 percent. This reflects the relatively high current costs that rural
households incur.
Table 16
Housing-Utility Burden at Full Cost Recovery
Housing-Utility Burden, as Percent of 1996 Total Expenditures
14
The source for the US figures is the American Housing Survey for the United States in 1995,
issued April 1997, by the U.S. Department of Commerce and the U.S. Department of Housing and Urban
Development.
19
Low
10-14%
Very Low
0 - 9%
All Households
Low to
Moderate
15-19%
Moderate
20-29%
High
30+%
Total
16.4
15.1
14.3
19.6
34.6
100.0
0
0.8
1.8
10.2
87.1
100.0
2
0.8
4.7
13.0
29.3
52.2
100.0
3
4.5
17.9
23.1
30.3
24.2
100.0
4
20.9
27.3
21.6
21.7
8.5
100.0
Highest
55.5
24.9
12.0
6.5
1.0
100.0
Urban
15.1
14.2
14.3
19.3
37.2
100.0
PGT
15.4
17.6
17.0
23.9
26.1
100.0
Rural
19.9
17.0
13.6
19.4
30.1
100.0
Expenditure Quintile
Lowest
Settlement Type
Table 17 summarizes how the distribution of households across housing-utility burden
categories changes as tariffs increase and compares this with the distribution of housingutility burden in the United States in 1995. The share of households with a very low
housing burden starts out at 64 percent at 1996 rates. It decreases to 26 percent at a 75
percent cost recovery level, and further decreases to 16 percent at full-cost recovery. The
share of households with a high burden begins at a small 5 percent at 1996 rates, and
increases to 22 percent at the 75 percent cost recovery level, and to 35 percent at full-cost
recovery.15 The U.S. distribution is closest to the Russian distribution at full-cost recovery
levels—in both 54 percent of households has moderate or high housing-utility burdens.
Table 17
Comparison of Housing-Utility Burden Levels at 1996 Charges, 75% Cost Recovery and Full
Cost Recovery in Russia, with 1995 Housing-Utility Burden Levels in the United States
Housing-Utility Burden, as Percent of 1996 Total Expenditures
Very
Low
0 - 9%
Low
10-14%
15
Low to
Moderate
15-19%
Moderat
e
20-29%
High
30+%
Total
Note that unit size varies little with burden levels. At 1996 charges, the mean total space occupied
by households with the lowest burden is 49 square meters and the space occupied by those with the highest
burden is 45 square meters; at full-cost recovery, households with the lowest burden occupied 46 square
meters on average and those with the highest burden occupied 48 square meters.
20
Table 17
Comparison of Housing-Utility Burden Levels at 1996 Charges, 75% Cost Recovery and Full
Cost Recovery in Russia, with 1995 Housing-Utility Burden Levels in the United States
Housing-Utility Burden, as Percent of 1996 Total Expenditures
Very
Low
0 - 9%
63.6
Low
10-14%
16.8
Low to
Moderate
15-19%
7.7
Moderat
e
20-29%
6.5
75% Full Cost Recovery
26.4
19.4
13.7
Full Cost Recovery
16.4
15.1
United States
14.7
15.2
1996 Charges
(33% Full Cost Recovery)
High
30+%
Total
5.4
100.0
18.1
22.4
100.0
14.3
19.6
34.6
100.0
15.9
23.2
31.1
100.0
Source for U.S. figures: American Housing Survey for the United States in 1995, issued April 1997 by the U.S.
Department of Commerce and the U.S. Department of Housing and Urban Development. Note that the
distribution excludes 2 percent of the sample which reported zero or negative income as well as 4 percent of
the sample which reported no cash rent. Including these would add to the “very low” and “high” categories.
Housing-utility burden is calculated as monthly housing costs (rent, mortgages, utilities, etc.) as percent of
current income.
Although housing-utility burdens experience great shifts with the imposition of greater
cost recovery, in absolute monetary terms, the increases in charges appear to be less
dramatic. Table 18 compares the 1996 imputed charges and corresponding burden levels
with the charges and burden levels at 75 percent cost recovery and at full-cost recovery
levels. The mean imputed 1996 housing-utility charge for the sample is 97 thousand rubles
($19). At 75 percent cost recovery, the mean charge increases to 214 thousand rubles
($43) and at full cost recovery, the mean charge is 285 thousand rubles ($57).16 With such
a low initial level of charges, it is not surprising to see the average housing-utility burden
double under 75 percent cost recovery and triple under full cost recovery. It is also
important to remember that these burden measures assume that real incomes do not grow
and that no one implements technological or institutional energy conservation measures. In
the following sections on sensitivity analysis, we will see that these factors greatly affect
burden levels.
Table 18
Comparison of Average Monthly Housing-Utility Charges (1996 Thousand Rubles) and
Average Burden Levels (Percent) Under the 1996 Rate Scheme, 75 Percent Cost Recovery
and Full Cost Recovery, by Expenditure Quintile and by Settlement Type
16
Note that for 24 percent of the sample occupying “standard” units (i.e, receiving the following
services: district heat and hot water, gas stove, central water and sewerage and telephone) the mean charge
is higher at 371 thousand rubles, or $74. The average size of these units was 49 square meters.
21
Housing-Utility Burden
(Percent)
Housing-Utility Charges
(1996 Thousand Rubles)
At 1996
Rates
All
Households
At 75%
Cost
Recovery
At Full
Cost
Recovery
At 1996
Charges
At 75%
Cost
Recovery
Charges
At FullCost
Charges
97.1
213.7
284.9
10.8
23.3
31.1
Lowest
69.3
146.4
195.2
24.8
52.8
70.4
2
84.7
181.2
241.6
11.8
25.3
33.7
3
95.0
205.9
274.6
8.3
17.9
23.9
4
108.6
237.4
316.5
6.0
13.0
17.3
Highest
128.1
297.5
396.7
3.4
7.7
10.3
Urban
99.5
237.1
316.1
10.1
23.9
31.8
PGT
82.1
179.5
239.3
9.6
21.3
28.4
Rural
94.6
161.0
214.7
13.2
22.5
30.0
Expenditure Quintile
Settlement Type
SENSITIVITY ANALYSIS: REAL INCOME GROWTH
Until now, our estimates assumed that there would be no real income growth while
housing and utility charges increased to full-cost recovery levels. The following sensitivity
analysis explores the effect of real income growth on housing-utility burden levels.
Scenario 1 assumes that there will be 3 percent per annum real income growth, which
cumulatively represents a 23 percent increase from 1996 to 2003. Scenario 2 assumes 6
percent per annum real income growth, cumulatively a 50 percent increase over that
period. Under these two scenarios, the mean monthly total expenditure level of the sample
increases from 1.8 million rubles to 2.2 million rubles and 2.7 million (1996) rubles,
respectively.
The housing-burden calculations are quite sensitive to assumptions of income growth.
With no income growth, the mean housing-burden level is 31 percent. With 3 percent per
annum growth, the mean housing-utility burden level drops to 25 percent and with 6 percent
per annum growth, it drops to 21 percent. Table 19 shows that with 6 percent per annum
growth in real income, the share of households facing a high housing-utility burden is cut
roughly in half from 35 to 18 percent. At the same time, the share of households with very
low housing-utility burdens doubles from 16 to 32 percent. There are only small changes in
22
the shares of households with low, low-to-moderate, or moderate housing-utility burdens.
Table 19
Comparison of Housing-Utility Burden Levels at Full Cost Recovery with No Income Growth,
Three Percent Annum Growth and Six Percent Annum Growth From 1996 to 2003
Housing-Utility Burden, as Percent of 1996 Total Expenditures
Very Low
0 - 9%
Low
10-14%
Low to
Moderate
15-19
Moderate
20-29%
High
30+%
Total
No Income
Growth
16.4
15.1
14.3
19.6
34.6
100.0
Three Percent
Annum Growth
23.2
18.1
14.8
18.0
25.9
100.0
Six Percent
Annum Growth
31.5
19.8
14.1
16.4
18.3
100.0
SENSITIVITY ANALYSIS: REDUCTION IN HOUSEHOLD ENERGY CONSUMPTION
There are two potential sources of demand reduction which are likely to mitigate what
households will have to pay in the future for communal and network energy services. The
first is proper billing of consumption; the second is through investment in energy efficient
equipment and measures to reduce energy losses.
Proper Billing. There are two issues here: proper billing of energy produced for
residential use overall, and proper billing of energy consumption by individual households.
To achieve the latter would require metering in individual units, which does not exist at
present, with the exception of electricity consumption. With meters installed and charges
tied to actual usage, overall energy consumption would probably decrease as many
households would downwardly adjust their consumption and save money where they could
not before. Other households would be charged more to reflect their above-average
usage. However, meters may not produce much overall savings in the short-run (i.e., 7
years) because of the high fixed costs involved in installation. We did not include a switch
to billing by metering in our scenarios because of the long payback periods for investments
in meter installation.
In the absence of individual metering systems, distributors of gas, district heat and hot
water will continue to rely on “consumption norms” to charge a household for the services
provided according to the size of the unit or the size of the household. While the norms
cannot match any particular household’s actual usage, they are intended to approximate
overall usage across a population so the distributor can recover his costs. There is some
evidence, however, that these norms overestimate usage overall, and thus, on average,
23
charge households too much for these services at any given rate. For example, gas
consumption norms for cooking range from 7 to 15 cubic meters/person/month. In meter
testing programs in Vladimir and Volgograd, actual consumption was 7 to 8 cubic
meters/person/ month— significantly higher than consumption in France and Germany, but
lower than what many Russian households are charged. Similar situations exist with
consumption norms for gas water heating, gas space heating, district space heat, and
district hot water heating.17
We examined a scenario in which gas consumption norms were adjusted to more
realistically reflect actual consumption (i.e. 8 and 14 cubic meters/person/month for cooking
and water heating, respectively, and 4, 5, and 6 cubic meters/square meter/month for
heating in the south, central, and northern regions, respectively). In addition, consumption
norms for district heat and hot water were reduced by a flat 10 percent to reflect the
possible impact of more accurate recording of usage. The joint effect of improving the
measurement of these services is a 6 percent decrease in imputed full costs on average
from 285 thousand rubles to 268 thousand rubles (1996 rubles).
Energy Conservation Measures. Even with adequate billing arrangements, household
consumption of gas, district heat, and hot water in Russia will be higher than in most
countries with comparable climates because of relatively inefficient energy use. Many
factors have contributed to this inefficiency, including: (a) the structure of the existing
housing stock and networks which have been built under improper pricing signals; (b) lack
of access to new, more efficient technologies; and © lack of sufficient funds to finance
energy efficient investments at either the supply or consumer level.
A potential source of reducing heat costs is improved regulation and increased
competition. At the same time, introducing competition in one area, could have undesired
effects in another area. For example, a combined heat and power producer wanting to
reduce heat charges in face of competition, might increase its electricity tariffs to
compensate. Other results may not produce short-run savings. For instance, if households
are given the opportunity to choose other heat producers, they may shift to building-level
boilers rather than relying on over-extended central heating systems. This might lead to a
cost increase in the early years because of the capital costs involved in such a shift. For
these reasons, the sensitivity analysis does not consider regulation and competition as a
likely source of much savings in the short-run.
Other ways to reduce heat costs include more efficient production technologies and
17
Annex 6 compares the 1996 range of consumption norms for gas, district heat and hot water with
estimated average actual usage, based on meter testing programs or consumption levels in countries with
comparable climates.
24
improved heating efficiency of apartments. A modest degree of cost reduction at the
producer level could be accomplished through high rate-of-return, low-cost investments
(e.g., automated controls, heat meters at the intake from the heat supplier, leak detection
programs, etc.). Demonstrations projects of building retrofits in the former Soviet Union
countries have recorded energy savings of up to 30 percent. Complete retrofits may
decrease the short-run marginal cost of supply, but not the total cost because of high
investment requirements and long payback periods. However, partial retrofits (e.g., window
weather-stripping, heat balancing, building-level heat control, etc.) have achieved energy
savings of up to 20 percent with considerably shorter payback periods.
Given that savings of 5 to 15 percent seem to be achievable for relatively minor levels
of investment on both the residential and producer side, the sensitivity analysis examined
the impact of a 10 percent reduction in energy consumption (over and above the savings
achieved through improved measurement).
The cumulative effect of improved
measurement and low-cost energy conservation measures is an 8 percent decrease from
285 thousand to 262 thousand rubles (1996 rubles).
Table 20 shows that with proper measurement and energy conservation measures,
the share of households facing a high housing-utility burden is reduced from 35 to 30
percent. The share of households with very low housing-utility burdens increases from 16
to 20 percent. Again, there is little change in the share of households with low, low-tomoderate, or moderate housing-utility burdens. Compared to the effect of increasing
incomes, the decrease in burden is less dramatic. The potential impact of these measures,
however, is somewhat constrained because they only affect some of the services provided.
The cost of other services, such as maintenance, telephone, and electricity are not
reduced.
Table 20
Comparison of Housing-Utility Burden Levels at Full Costs: Demand Reductions through
Proper Billing Arrangements and Energy Conservation Measures
Housing-Utility Burden, as Percent of 1996 Total Expenditures
Very
Low
0 - 9%
Low
10-14%
Low to
Moderate
15-19%
Moderate
20-29%
High
>= 30%
Total
Ceteris Paribus
16.4
15.1
14.3
19.6
34.6
100.0
Proper Billing
Arrangements
18.7
15.0
15.6
18.5
32.2
100.0
Energy Conservation
Measures & Proper
Billing Arrangements
19.8
15.8
15.1
19.0
30.4
100.0
These are only a sample of the most important factors that will influence future
25
housing burden. Other related effects include expected growth in availability of telephones
and corresponding costs; additional salary growth in the public sector (e.g., military) which
will happen in response to and simultaneously with elimination of existing housing benefits;
potential growth in a number of market renters (as part of growing labor mobility) which will
face a much higher level of total housing-related costs.
IMPACT ON MUNICIPAL BUDGETS
As the level of government responsible for providing most of the current housingrelated subsidies, municipalities and other local governments stand to benefit the most from
an increase in tariffs to full-cost recovery levels. Every municipality knows, however, that
when it increases tariffs, it will not receive a full payment from every household. Even at
the low 1996 rates, many households did not pay the prescribed tariff because they
received housing benefits or housing allowances, or simply refused to pay and were in
arrears. Thus, the estimated collection has three components:
Collection Estimate =
Amount Billed to Unsubsidized Population + Amount Billed to Subsidized Population - Arrears
Likewise, the difference between the amount collected and the total costs to provide
these services represents a combined direct and indirect subsidy from the municipality to
households. The subsidy burden is the share of total costs borne by the municipality.
Subsidy Burden =
(Total Housing and Utility Costs - Collection Estimate) / Total Housing and Utility Costs
According to estimates by the Institute for Urban Economics (IUE) in Moscow, 30 to
35 percent of households received housing benefits in the end of 1996 and they were
billed, on average, 55 percent of the unsubsidized rate. Distribution of housing benefits is
category based, that is, it depends on the person’s status (e.g., veteran), occupation (e.g.,
teacher or military) or perhaps, physical disability. Depending on their category, recipients
of housing benefits might be liable for only 50 or 70 percent or, in some cases, none of the
prescribed charges for their unit.
Also according to IUE, 6 to 7 percent of households received housing allowances
during this period and they were billed for approximately 75 percent of the unsubsidized
rate. Distribution of payments in the housing-allowance program is means-based. Eligibility
and the size of the subsidy is based on the family’s housing needs and their ability to pay.
In 1996, participation in the housing allowance program was below estimated eligibility for
four reasons: (1) some households had to choose between housing benefits and housing
allowances and chose the former; (2) some housing allowance offices demonstrated poor
performance, including information campaign activities; (3) some eligible households
decided not to pay at all and are in the category of households with arrears; (4) some
26
households with a small expected allowance do not apply.18 In the future, the housing
benefits program will gradually be replaced by the housing allowance program. Many of
the households receiving housing benefits will be eligible for housing allowances.
To estimate how much a municipality might collect if it increased tariffs to full cost
recovery levels, we first had to estimate how many households would qualify for a housing
allowance (assuming that housing benefits programs no longer exist). The eligibility rules
for housing allowance programs vary throughout the country, but for our analysis, we
assumed that a household would be eligible for an allowance if its housing and utility
charges totaled more than 20 percent of its household income.19 That is, the household
would pay the portion of the bill that is equal to 20 percent of its income; the municipality
would not bill them for the remaining portion. In this sense, the municipality is billing the
household for services at some rate below full cost recovery. Under the 75 percent cost
recovery rate scheme and expenditure levels the same as in late 1996, we estimate that 41
percent of the households would be eligible for housing allowances. With the full cost
recovery rate scheme and expenditure levels again held constant, we estimated that 54
percent of the households would be eligible for housing allowances. These estimates were
used to calculate a weighted average of the charges to be billed to the population. (See
Table 21.)
Table 21
Share of Households Receiving Subsidies and Estimated Charges
Population Category
Mean Charge per
Population
Category
(Rubles)
Population share
(%)
Weighted
Charge (Billed)
per Population
Category
At October 1996 Tariffs
Unsubsidized Population a
Housing Allowance Recipients
64
97.2
62.2
6
72.9
4.4
18
A thorough description of early experience with the housing allowance program in Russia can be
found in the article, “Monitoring Russia’s Experience with Housing Allowances,” by Raymond J. Struyk,
Alexander S. Puzanov, and Lisa A. Lee, in Urban Studies, Vol. 34, No. 11, 1789-1818, 1997.
19
According to the Federal Concept for Housing and Communal Reform, the federal standard for
housing allowance eligibility under full-cost recovery (to be achieved by the year 2003) is 25 percent. Thus,
the 20 percent rule used throughout this paper should overestimate the subsidy burden of a municipality.
27
Housing Benefits Recipients
30
Total
53.4
100
16.0
82.6
At 75 Percent Cost Recovery Tariffs
Unsubsidized Population
59
213.7
127.1
Housing Allowance Recipients b
41
139.0
56.3
Total
100
183.4
At Full Cost Recovery Tariffs
Unsubsidized Population
46
284.9
131.1
Housing Allowance Recipients b
54
169.3
91.4
Total
100
222.5
Notes:
a
This is really a misnomer because the 1996 tariffs represent large subsidies in themselves since they are
much below cost. For the sake of consistency, we use the term “unsubsidized” for the households who are not
receiving special housing benefits or housing allowances.
b
The assumption is that the housing benefits program is phased out. Many of the households currently
receiving housing benefits would be eligible for housing allowances, particularly if housing and utility rates
were increased.
The reader should be aware that the figures in Table 21 represent an upper limit of
housing allowance eligibility. The estimates in Table 21 assumed that the municipality
would pay the difference between actual costs and the share paid by the household (set at
20 percent of the household’s income). In practice, each local government operating a
housing allowance program sets a “maximum social rent” according to family size. The
municipality is responsible for the difference between the maximum social rent and the
share paid by household. (When actual costs are below the maximum social rent, the
housing allowance is based on actual costs.) The degree to which the figures above
overstate housing allowance eligibility depends on actual maximum social rents employed
by local governments. These can vary a lot. If we assume a maximum social rent based
on 20 square meters per household member, then under the 75 percent cost recovery rate
scheme the share of households eligible for housing allowances falls from 41 to 36 percent.
Under the full-cost recovery rate scheme, the share falls from 54 to 49 percent. In addition
to reducing the number of households eligible for housing allowances, the use of a
maximum social rent also reduces the municipality’s subsidy to households that are still
eligible. The combined effect is that perhaps one quarter of all households will experience
moderate or high burdens, even though they are recipients of housing allowances. Out of
their own pockets, fifteen percent of all households will pay 21 to 29 percent, 5 percent will
pay 30 to 39 percent, and another 5 percent of the households will pay more than 40
percent of their total expenditures on housing-related costs (according to estimates based
28
on the rule of 20 square meters per capita). The other option facing these households is to
relocate.
It was also necessary to calculate current arrears to have an assumption for future
arrears. Table 22 shows how we estimated monthly (as opposed to cumulative) arrears to
be 14 percent of the amount billed to households. Monthly arrears are defined as the
difference between the average amount billed and the average amount collected (that is,
the amount that households reported paying in the RLMS). As was illustrated in Table 21,
the average amount billed depends on the share of households receiving housing benefits
and allowances and the average amount billed to these households.
Table 22
Calculation of Arrears Estimate
Value (1996 Thousand Rubles or Percent)
Total Billed in 1996 (weighted average of
charges from the table above)
82.6
Mean Housing-Utility Payments, as reported
in the RLMS survey
71.1
Arrears Estimate (weighted per household
charge)
11.5
Arrears as Percent of Total Billed
14%
Returning to the assumptions behind the estimates laid out in Table 21, we estimated
the net impact of an increase in tariffs on a municipality, given the fact that it will collect
more fees from some households, but have to provide greater subsidies to other
households. Table 23 shows the subsidy level per 100,000 households, the subsidy
burden (as percent of total housing and utility costs), and the savings to a municipality
under a variety of scenarios. The share of households eligible for housing allowances
changes with each scenario depending on the number of households facing a moderate or
high housing-utility burden, and the severity of their burden.20 In all scenarios (including
the 1996 rate scheme), the arrears are assumed to be 14 percent of the total amount billed
to households.21
At 1996 tariffs, a municipality of 100,000 households annually collects approximately
20
We assume here that 100 percent of the eligible households will participate in the housing
allowance program, even though experience shows that the number of participants is always smaller than the
eligible population.
21
With higher charges, there will be more incentive for households not to pay their housing and utility
bills. We assume that the household’s incentive not to pay, however, will be counteracted by the municipality’s
greater efforts at enforcement, thus maintaining monthly arrears at approximately 14 percent.
29
85.3 billion rubles ($17.1 million), which means that it must subsidize 75 percent of all
housing-related costs—257 billion rubles ($51.3 million)— through low rates, program
benefits and non-collection (arrears). When unsubsidized households are charged rates
corresponding to 75 percent of cost recovery levels, the same municipality might expect to
provide housing allowances to 41 percent of the households and, including the cost of
arrears, subsidize 45 percent of the full cost of the services provided. However, it would
save 104 billion rubles ($20.8 million) compared to the 1996 rate scheme.
When unsubsidized households are charged the full cost of providing the services, the
municipality would provide housing allowances to 54 percent of the households, but
subsidize only 33 percent of all housing-related costs. All together, it would annually collect
approximately 230 billion rubles ($45.9 million), and provide a subsidy of 112 billion rubles
($22.5 million) through housing allowance program benefits and non-collection (arrears).
The difference in subsidy from the 1996 rate scheme annually amounts to 144 billion rubles
($28.9 million).
The municipality’s subsidy burden and its savings compared to the 1996 rate scheme
would improve even more if there were either income growth or reduced household
consumption of energy.
If there was 3 percent annum income growth, then the
municipality could expect that its subsidy burden would decrease, perhaps to 28 percent of
total housing-related costs. If households reduce their energy consumption, even if there is
no income growth, then total costs of providing the services would fall while households
would pick up more of the tab. The municipality would subsidize 30 percent of total
housing-related costs, and save 163 billion rubles ($32.6 million) compared to what it must
pay out under the 1996 rate scheme.
Table 23
Housing-Utility Subsidy Burden of a Municipality with 100,000 Households, By Scenario
(Million US Dollars: 5000 Rubles = $1)
Annual
Subsidy, per
100,000
Households
Subsidy as %
of Total
Housing-Utility
Costs
Savings to
Municipality,
Compared to the
1996 Rate Scheme
1996 Rate Scheme
51.3
75%
----
75 Percent Cost Recovery
30.5
45%
20.8
Full-Cost Recovery
22.5
33%
28.9
Scenario
Income Growth Scenarios (With Full-Cost Recovery Tariffs)
Three Percent Annum Growth
19.2
28%
32.1
Six Percent Annum Growth
16.4
24%
35.0
Reduced Household Consumption Scenarios (With No Income Growth)
30
Table 23
Housing-Utility Subsidy Burden of a Municipality with 100,000 Households, By Scenario
(Million US Dollars: 5000 Rubles = $1)
Annual
Subsidy, per
100,000
Households
Subsidy as %
of Total
Housing-Utility
Costs
Savings to
Municipality,
Compared to the
1996 Rate Scheme
Proper Billing
20.1
31%
31.2
Energy Conservation Measures
& Proper Billing
18.7
30%
32.6
Scenario
This analysis is not intended to be predictive, i.e., it does not try to predict what the
world will look like in a future point in time. Instead, it provides an estimate of the upper
limit of a municipality’s subsidy burden under a variety of scenarios. Actual costs to the
municipality will depend on 1) housing allowance participation rates; 2) the program’s
administrative costs; and, 3) the municipality’s success in enforcing collection and reducing
arrears. We have no way of knowing what actual housing allowance participation rates will
be under different rate schemes; we can only estimate eligibility. Actual participation will be
influenced by the local administration’s outreach efforts, the degree of difficulty in applying
for assistance, the expected benefit level, and cultural factors such as attitude towards
receiving government assistance and even fear of government intrusion. The greater the
increase in burden, the more likely that a household will participate.
For the above-mentioned reasons it is not possible to extrapolate participation rates
from experience in other countries, except to say that the number of participants is always
smaller than the eligible population. Under the full cost recovery rate scheme, we estimate
that 54 percent of households would be eligible to receive a housing allowance. Even with
participation rates much below eligibility rates this would represent a significant increase
from the 6 percent participation rate in 1996. During the process of German reintegration,
East German households experienced great increases in their rent. By the end of 1992, 2
million East German households—30 percent of all East German households— participated
in a housing allowance program. (The housing allowance program existed in West
Germany since 1955; during the same period, 6 percent of West German households, 1.8
million, were also participating in the program.) This share of East German participants
dropped to 1.4 million households (or about 20 percent) by the end of 1993 as real income
increased.22 Analysis of housing allowance participation rates and the accompanying
22
Material taken from Wohngeld and Mietenbericht, 1993, Bundesministerium fur Raumordnung
Bauwesen und Stadtebau, 1994 and personal conversation with Dr. Dick and Dr. Volker, as reported in
31
administrative costs in Russia is beyond the scope of this analysis.
Housing Allowance Design: An Evaluation for Slovakia, by M. Mikelsons, et.al, The Urban Institute, 1996. The
reader is referred to the Urban Institute report’s annex, “Other Country Experience with a Consumer-Based
Housing Subsidy,” for a summary of experience throughout the world.
32
ANNEX 1
FURTHER DESCRIPTION OF THE SAMPLE
Table 1 - Annex 1
Process Followed in Excluding Records from the Sample
Number of
Records
Excluded
Percent of All
Records in
Original Sample
Market Renters
181
5.18
Dormitory Occupants
151
4.24
20
0.56
Zero Value on Total Household Expenditures
4
0.11
Zero Value on Number of Household Members
1
0.03
Missing Value on Hot Water
18
0.51
Missing Value on Network Gas
36
1.01
Missing Value on Both Living Space and Total
Space
47
1.32
2
0.06
112
3.14
Total Cases Remaining
2990
83.94
Original RLMS Sample
3562
100.00
Reason for Exclusion
Missing Values on Housing Type (own
residence, market rent or dormitory)
Missing Value on Unit Type (Separate Apartment
or House or Part of Apartment or House)
Split Households
33
Table 2 - Annex 1
Process Followed in Imputing Housing Characteristics
Variable with Imputed Values
Imputation Method
Total Space
1,2
Living Space
1,2
Connection to Central Heating
1
Connection to Central Water Supply
1
Connection to Central Sewerage
1
Telephone Connection
1,3
Unit is Private or Privatized
1,3
Unit is Separate or Part of Larger Unit
1
Ownership of Building
1
•
Imputation method (1) involved replacing missing values from Round 7 of the RLMS
with Round 6 values.
•
Imputation method (2) was used after imputation method (1) for computing total or
living space for cases that still had missing information for one, but not both types of
space information. For cases in which only one space value was missing, the missing
value was imputed based on the existing value times the median total space / living
space ratio for that unit type (separate apartment, part of an apartment, separate
house, part of house).
•
Imputation method (3) was used after imputation method (1) for cases that still had
missing information. Two cases with missing information on telephone connection
were assumed to not have telephone service. Two cases (apartment dwellers) were
assumed to have non-privatized units. Two cases (in separate houses) were
assumed to have private units.
34
ANNEX 2
JUSTIFICATION FOR IMPUTING HOUSING AND UTILITY CHARGES
In one question of the RLMS survey, respondents were asked how much they had
paid for all housing and communal services (maintenance and utilities) in the past 30 days.
For several reasons the reported value may not correspond to the family’s usual housingrelated liabilities. Most significantly, these include arrears: 30 percent of the households
reported that they had unpaid housing and utility bills. In addition to arrears, many
households were eligible for housing benefits because they were veterans, disabled or had
an occupation designated as special. Finally, some households were also participants in
the new housing allowances program which targets subsidies to low-income households
whose housing-utility burden is more than a certain percent of total income. It is not
possible to tell from responses to the RLMS questionnaire whether a household received
benefits or allowances or both.
In the past 30 days, a household might have paid none of what they owed for that
month, some of what they owed, exactly what they owed, or what they owed for that month
plus past arrears. Thus, the payment often will not correspond to the housing and utility
services consumed by the household. To create a variable that reflects the value of the
housing and utility services enjoyed by a household (whether or not they are actually
paying for these services), required using unit and household characteristics reported in the
RLMS. The following table presents the algorithms for imputing housing and utility
charges.
Table 1 - Annex 2
Algorithms for Calculating Housing and Utility Charges
Service
Unit Characteristics
Calculation Approach
Rent -
Non-privatized apartment
Kvarplata tariff * unit size
Maintenance
Non-privatized single family dwelling
100 Rubles * unit size
Privatized apartment
Maintenance tariff * unit size
Privatized single family dwelling
0
If central heating connection
Heat tariff * unit size
If no central heating connection, but have
gas connection
Gas price per m3 * norm usage
of m3 per month per m2 of space
* unit size
If no central heating connection and no
gas connection, assumed coal heating
Coal price per ton (minimum
150,000 R) * norm usage of
tons per month * unit size
Heating
35
Table 1 - Annex 2
Algorithms for Calculating Housing and Utility Charges
Service
Cooking
Hot Water
Water Sewerage
Telephone
Electricity
Unit Characteristics
If network gas connection
Calculation Approach
Gas tariff * household size
If no gas connection, but household uses
gas stove
Bottled gas price per liter * .09
liters per person * household
size (maximum 4)
If household uses electric stove
Electricity tariff per kWt * 40 kWt
* household size (maximum 3)
If hot water connection
Hot water tariff * household size
If no hot water connection, but have gas
connection
Gas price per m3 * norm usage
of m3 per month per person *
household size
If no hot water connection, no network gas
connection, but use bottled gas for
cooking
Bottled gas price per liter * .09
liters per person * household
size
If neither hot water nor gas connection
0 (Costs assumed to be
accounted for under heating)
If both cold water and sewerage
connection
Water-sewerage tariff *
household size
If only cold water connection
3/5 * Water-sewerage tariff *
household size
If only sewerage connection
2/5 * Water-sewerage tariff *
household size
If neither connection
0
If telephone connection
Local service flat fee
If no telephone connection
0
All households assumed to have electricity
service
Electricity tariff per kWt * 200
kWt if household has 5 or more
members; else tariff per kWt *
(100 + 25 * (household size - 1))
Notes:
1) Unit size is defined as total space for households that live in separate apartments or houses and as living
space for households that live in parts of apartments or houses.
2) All tariffs and prices used for imputing charges were regionally-based. In most cases this meant at the city
or oblast level. The norm usage levels for gas also vary by region.
36
Note that the imputed charges still do not correspond to the full value of these
services, since in 1996 they were still provided at subsidized rates for all households. Even
when utility and maintenance services are increased to full cost recovery levels, rent for
state-owned housing will still probably lag behind market levels. This means that those
households will continue to consume much more housing than will be reflected in their
expenditures.
The low share of the household budget spent on housing and utility services means
that altering the estimate for these charges does not greatly affect the distribution of
households by total expenditures. In the following table, records with the same column and
row number are households that did not shift expenditure deciles after the imputation of
housing and utility charges. These represent 84 percent of the sample. Another 15
percent of the households in the sample shifted one decile, either higher or lower, because
of the imputed charges. Less than one percent of the households shifted more than one
decile as a result of the imputation. In all of the latter cases, households that were in a
higher expenditure decile based on reported payments, were recategorized in a lower
decile based on imputed charges. A household might report a housing-utility payment
much higher than its regular monthly housing-utility bill if it is paying up arrears and/or
building a stock of coal or firewood for the whole winter.
Table 2 - Annex 2
Shift of Households Among Expenditures Deciles after Imputation of Housing-Utility Charges
(Count of Records)
Expenditure Decile with Imputed Housing-Utility Charges
1
(Lowest)
2
1
272
27
2
27
230
42
3
40
223
36
4
2
29
226
42
5
4
34
232
29
6
1
3
24
250
21
1
19
254
25
1
23
259
16
1
15
279
Expenditure
Decile with
Reported
Charges
3
4
5
7
8
9
37
6
7
8
9
10
(High
-est)
4
10
4
295
Note: The reported charges had three components: 1) a question on all charges for housing and communal
services; 2) a question on purchase of coal, firewood, peat, kerosene; 3) a question on purchase of bottled
gas. The households were to report expenditures within the past 30 days. However, the latter two categories
are generally ‘lumpy’ purchases (purchased less frequently than on a monthly basis) so households would
report an amount much larger than that needed for one month. These values were adjusted to a third of the
reported amount to compensate.
38
ANNEX 3
CALCULATION OF FUTURE HOUSING AND UTILITY CHARGES
As with estimating the current housing and utility costs, the estimates for full cost
recovery depended on the type of service, fuel and unit type. Data on cost recovery for
communal services (maintenance, central heat, hot water, central water and sewerage)
were provided by the Form 22 of the Department of Housing and Communal Services. In
the regions in the sample, the cost recovery levels for communal services ranged from 17
to 40 percent (as of August 1997). Over half of the regions in the sample had cost recovery
levels between 25 and 35 percent for communal services. Electric cost recovery levels
were taken from information provided by individual Energos (electric power plants). These
ranged from 19 to 61 percent.
Cost recovery levels for delivery of natural gas were calculated using the November
1996 subsidized price for residential users and the price for unsubsidized (industrial) users.
In the sample, gas cost recovery levels ranged from 15 to 100 percent, with a relatively
even and wide dispersion. Likewise, cost recovery levels for coal were calculated based on
the 1996 price and an estimate of the full price. (The estimated full price was 200 thousand
rubles per ton in coal-producing regions and 350 thousand rubles in all other regions.
The telephone cost recovery level was assumed to be 60 percent and the bottled gas
cost recovery level 80 percent.
Table 1 - Annex 3
Algorithms for Calculating Housing and Utility Charges
Service
Unit Characteristics
Calculation Approach
Rent Property Tax
Single family dwelling without gas or central
heating
100 Rubles* unit size
Apartment without gas or central heating
160 Rubles * unit size
Single family dwelling with both gas and central
heating
200 Rubles * unit size
Apartment with both gas and central heating
250 Rubles * unit size
Apartment
(1996 maintenance tariff / cost
recovery level for communal
services ) * unit size
House
0
Single family dwelling without gas or central
heating
130 * unit size
Maintenance
Capital
Repair
39
Table 1 - Annex 3
Algorithms for Calculating Housing and Utility Charges
Service
Heating
Cooking
Hot Water
Water Sewerage
Unit Characteristics
Calculation Approach
Apartment without gas or central heating
260 * unit size
Single family dwelling with both gas and central
heating
320 * unit size
Apartment with both gas and central heating
400 * unit size
If central heating connection
1996 charge / cost recovery level
for communal services
If no central heating connection, but have gas
connection
1996 charge / gas cost recovery
level
If no central heating connection and no gas
connection, assumed coal heating
Coal price at full cost recovery per
ton * norm usage of tons per
month * unit size
If network gas connection
1996 charge / gas cost recovery
level
If no gas connection, but household uses gas
stove
1996 bottled gas charge / 0.80
If household uses electric stove
1996 electricity for stove charge /
electricity cost recovery level
If hot water connection
1996 hot water charge / cost
recovery level for communal
services
If no hot water connection, but have gas
connection
1996 charge / gas cost recovery
level
If no hot water connection, no network gas
connection, but use bottled gas for cooking
1996 bottled gas charge / 0.80
If neither hot water nor gas connection
0 (Costs assumed to be accounted
for under heating)
If both cold water and sewerage connection
1996 water-sewerage charge /
cost recovery level for communal
services
If only cold water connection
1996 water charge / cost recovery
level for communal services
If only sewerage connection
1996 sewerage charge / cost
recovery level for communal
services
If neither connection
0
40
Table 1 - Annex 3
Algorithms for Calculating Housing and Utility Charges
Service
Unit Characteristics
Calculation Approach
Telephone
If telephone connection
1996 telephone charge / 0.60
If no telephone connection
0
All households assumed to have electricity
service
1996 electricity charge / electricity
cost recovery level
Electricity
41
ANNEX 4
DISTRIBUTION OF HOUSING AND UTILITY CHARGES
BY TYPE AND OWNERSHIP OF UNIT
For households in single-family houses, heat and electricity represent nearly threequarters of their monthly housing and utility charges. For apartment dwellers, heat still
sticks out as a high cost, but there are also other important components such as hot water,
cold water and maintenance charges. Similar patterns occur between private and publiclyowned dwelling because the large majority of single-family houses are privately owned.
Table 1 - Annex 4
Distribution of (Full-Cost Recovery) Housing and Utility Charges By Type and Ownership of
Unit
Type of Unit
House
Housing or Utility Service
Heat
Cooking
Hot Water
Cold Water/Sewerage
Telephone
Electricity
Maintenance
Rent / Property Tax
Capital Repair
Total
Ownership of Unit
Apartment
Privatized or
Cooperative
54
6
6
4
3
19
0
3
4
29
3
15
12
5
12
16
3
5
41
4
11
8
4
15
9
3
5
29
4
15
13
4
13
15
3
5
100
100
100
100
42
PubliclyOwned
ANNEX 5
DISTRIBUTION OF FUEL TYPES USED
BY UTILITY SERVICE AND SETTLEMENT TYPE
Not having access to district heat, centrally-supplied hot water, or network gas, the
majority of rural households have to use coal (or furnace oil or firewood) for heating, bottled
gas and coal for hot water, and bottled gas for cooking. The following table shows the
breakdown of fuel types used by utility service and settlement type. The fuel type used was
determined by the algorithms found in Table 1 - Annex 2.
Table 1 - Annex 5
Distribution of Fuel Types Used by Utility Service and Settlement Type
Rural
N = 778
PGT
N = 188
All
Households
N = 2990
Urban
N = 2024
70
9
22
89
5
6
66
29
5
21
13
66
Cooking
Network Gas
Bottled Gas
Electric Stove
61
22
18
71
8
21
92
4
4
27
61
12
Hot Water
Hot Water Connection
Gas Boiler (Network Gas)
Gas Boiler (Bottled Gas)
Coal or Other
57
19
20
4
75
17
7
1
52
40
4
4
10
20
59
11
Central Water/Sewerage
Central Water & Sewerage
Only Central Water
Only Sewerage
Neither
66
11
1
23
86
4
1
9
47
34
0
19
17
22
<1
61
Telephone
With Connection
No Connection
44
56
51
49
53
47
24
76
100
100
100
100
Expenditure Decile
Heat
Central (District) Heating
Gas Boiler Heating
Coal Heating
Electricity
43
ANNEX 6
COMPARISON OF 1996 CONSUMPTION NORMS WITH ESTIMATED AVERAGE
ACTUAL USAGE
At present, only a few households have meters to record actual energy consumption,
with the exception of electricity consumption, which is generally metered. In most
households, consumption of gas, district heat, and hot water is estimated based on
“consumption norms”. Given that the norms are adjusted to ensure that system losses fall
within allowed parameters, many households are paying for significantly more energy than
they are actually consuming.
Gas consumption levels and, therefore, gas norms, vary by type of use and between
regions. Gas consumption norms for cooking range from 7 to 15 cubic
meters/person/month. In meter testing programs in Vladimir and Volgograd, actual
consumption has been found to be on the order of 7 to 8 cubic meters/person/month—
lower than the consumption norms in many regions. Gas consumption norms for water
heating range from 12 to 25 cubic meters/person/month. Actual consumption in France
and Germany is around 14 cubic meters/person/month. Allowing for the relatively low
efficiency of water heaters, the actual consumption on average is probably relatively close
to the billing norms. However, in some areas, where the norms are particularly high, there
appears to be significant overbilling. Consumption norms for gas heating also appear high
relative to expected actual consumption. Based on conservative estimates of energy
consumption and conversion efficiency, (25 Mcal/square meter/month and 60% conversion
efficiency), gas consumption for space heating should be on the order of 5 cubic
meters/square meter/month. This could vary by plus or minus 25 percent in the northern
and southern regions, respectively. While the consumption norms in the major centers are
close to these levels, in outlying regions the norms range from 7 to 14 cubic meters/square
meter/month.
With respect to district heating and hot water supply, only limited information has been
collected on actual heat consumption and hence on the error level incorporated into the
consumption norms. Early indications are, however, that overbilling is less significant for
heat/hot water than for gas supply, and that part of the overbilling for heat may be offset by
under-billing for hot water.
We examined a scenario in which gas consumption was adjusted to more realistically
reflect actual consumption (i.e. 8 and 14 cubic meters/person/month for cooking and water
heating, respectively, and 4, 5, and 6 cubic meters/square meter/month for heating in the
south, central, and northern regions, respectively). In addition, consumption norms for
district heat and hot water were reduced by a flat 10 percent to reflect the possible impact
of more accurate recording of usage.
44
ANNEX 7
ANOTHER VIEW OF HOUSING-UTILITY BURDEN
In our analysis, estimates of housing-utility burden have used total expenditures as a
proxy for income. While this is useful for understanding the relative impact of a policy
change, this approach overestimates the impact on the population as a whole. The reason
is that the total expenditures includes an imputed value for housing and utility charges at
their subsidized rates. This underestimates a household’s income in the sense of their
well-being because the value of the services they are consuming is much greater than
represented by the subsidized rates. What would happen to the current and full-cost
housing burdens if the monthly market rent value of the dwelling was included as part of the
household’s income?23
To illustrate the effect of including the market rent value of the household’s dwelling,
we will use an example from Moscow. Table 1 shows the mean 1996 and full-cost housingutility charges for Moscow as well as the mean total expenditures, market rent unit value,
and an income estimate including this market rental unit value. The mean market rent
value for a Moscow housing unit was calculated from Wave 4 of the Moscow Longitudinal
Housing Survey which was conducted in December 1995 (roughly one year before the
RLMS). In the MLHS twelve households reported paying market rent for their unit, with
rents ranging from $200 to $400.
Table 1 - Annex 7
Income Estimate That Includes Market Rent Value of Housing Unit:
Illustrative Example of Moscow City (Mean Values)
Input into Housing Burden Calculation
Ruble Value (1996
Thousand Rubles)
Dollar Value
(Rubles / 5000)
1996 Charges
113.2
$22.6
Full-Cost Charges
563.4
$112.7
Total Expenditures
2,956.3
$591.3
Market Rental Value of Dwelling (1995)
1,237.5
$247.5
23
It is common practice in expenditure surveys to impute a rental value for owners occupying their
own units. In essence, the owners are paying rent to themselves. To understand the potential income
represented by the unit, consider the case when the owner rents out his property and moves in with family
members for free.
45
Income Proxy (Total Expenditures + Imputed
Market Rent Value of Dwelling)
4193.8
$838.8
Note:
Both household incomes (expenditures) and market rents are higher in Moscow than in most of Russia.
The housing burden drops considerably when the household’s income is upwardly
revised to reflect their unit’s market value. Instead of a 1996 housing burden of 6 percent,
the households have a burden of 4 percent. Under the full-cost recovery scenario, the
median burden of Moscow households decreases from 32 to 17 percent. This simple
example illustrates that the true income of Russian households includes the value of their
housing for which they either pay nominal rent or receive free because they have privatized
the unit.
Table 2 - Annex 7
Revised Estimates of Housing-Utility Burden Taking Into Account the Market Value of
Dwelling Consumed by Household: Illustrative Example of Moscow City
(Median Values of Percents)
Level of Housing-Utility Charges
Based on Total
Expenditures
Based on Income
Estimate with Market
Value of Dwelling
Housing-Utility Burden Based on Current
Charges and Total Expenditures
6
4
Housing-Utility Burden Based on Full-Cost
Charges and Total Expenditures
32
17
46
References
Klugman, Jeni, ed. Poverty in Russia: Public Policy and Private Responses, Washington,
DC, The World Bank.
Martinot, Eric. Investments to Improve the Energy Efficiency of Existing Residential
Buildings in Countries of the Former Soviet Union. The World Bank, 1997.
Mikelsons, Maris, et. al. Housing Allowance Design: An Evaluation for Slovakia, The Urban
Institute, 1996.
Struyk, R., A. Puzanov, and L. Lee. “Monitoring Russia’s Experience with Housing
Allowances,” in Urban Studies, Vol. 34, No. 11, 1789-1818, 1997.
U.S. Department of Commerce and the U.S. Department of Housing and Urban
Development. American Housing Survey for the United States in 1995. Issued April 1997.
48
ANNEX 8
TARIFF INFORMATION USED FOR IMPUTING HOUSING AND UTILITY CHARGES
Oblast or City
St Petersburg
Moscow City
Moscow Oblast
Syktyvkar
Leningrad Oblast
Smolensk
Rzhev
Tula
Kaluga
Nizhniy Novgorod
Cheboksary
Penza
Lipetsk
Tambov
Kazan
Saratov
Saratov
Volgograd
Nalchik
Rostov-na-Donu
Krasnodar
Stavropol
Chelyabinsk
Kurgan
Izhevsk
Orsk
Perm
Miass
Tomsk
Surgut
Biusk
Krasnoyarsk
Vladivostok
Blagoveschensk
1996 District
1996 Hot
1996 Central
Heat Tariff /sq Water Tariff / Water-Sewerage 1996 Kvarplata
m
person
Tariff / person
Tariff / sq m
335
3,012
9,860
400
492
9,138
6,968
310
650
7,579
7,776
404
777
14,625
5,175
542
600
8,000
5,000
373
304
5,390
1,296
141
432
3,240
2,380
160
291
4,254
2,768
139
350
4,000
3,000
150
480
5,064
3,496
543
350
4,500
400
77
450
2,079
1,594
103
276
6,905
5,263
369
300
3,500
2,000
168
300
1,200
2,084
990
305
3,185
2,934
45
305
3,185
2,934
45
300
4,000
1,500
197
200
4,000
1,900
166
450
6,500
6,000
202
550
9,075
6,090
300
500
5,000
6,000
276
810
10,875
2,844
668
1,166
5,618
5,864
175
420
4,000
1,120
366
763
4,881
6,337
420
397
4,500
3,044
252
831
10,983
10,085
322
700
4,320
5,050
300
865
5,760
14,870
1,490
840
9,820
3,400
214
644
8,366
3,636
555
1,576
10,508
2,736
385
1,000
11,000
6,000
450
46
1996
Maintenance
Tariff / sq m
368
310
404
375
373
129
160
139
107
543
77
100
336
96
900
45
45
176
166
200
300
276
625
158
366
400
156
315
154
1,200
214
555
385
450
Cost Recovery
Level for
Communal
1996 Coal
1996 Bottled
Services
Price / ton Gas Price / liter
35%
150,000
40,000
17%
166,300
.
35%
166,300
21,000
25%
266,000
12,495
30%
150,000
40,000
25%
150,000
32,000
30%
150,000
20,000
20%
150,000
15,225
30%
150,000
31,500
25%
350,000
30,000
30%
180,400
27,300
25%
150,000
29,400
40%
348,300
26,000
25%
584,500
48,300
40%
162,000
25,200
25%
250,000
21,000
25%
250,000
21,000
30%
585,000
21,000
30%
150,000
20,000
40%
150,000
22,000
30%
150,000
20,000
40%
345,000
20,000
30%
150,000
50,000
35%
161,300
25,000
30%
250,000
43,800
40%
150,000
25,000
30%
150,000
6,300
30%
150,000
50,000
30%
203,600
40,000
35%
240,100
40,000
30%
162,800
40,000
40%
150,000
44,100
35%
150,000
46,200
35%
242,400
72,000
ANNEX 8
TARIFF INFORMATION USED FOR IMPUTING HOUSING AND UTILITY CHARGES
Oblast or City
St Petersburg
Moscow City
Moscow Oblast
Syktyvkar
Leningrad Oblast
Smolensk
Rzhev
Tula
Kaluga
Nizhniy Novgorod
Cheboksary
Penza
Lipetsk
Tambov
Kazan
Saratov
Saratov
Volgograd
Nalchik
Rostov-na-Donu
Krasnodar
Stavropol
Chelyabinsk
Kurgan
Izhevsk
Orsk
Perm
Miass
Tomsk
Surgut
Biusk
Krasnoyarsk
Vladivostok
Blagoveschensk
1996 Flat
Telephone
Tariff
28,000
12,000
10,500
24,000
20,000
14,000
12,000
10,000
12,000
18,000
12,544
13,500
10,000
10,000
15,000
14,000
14,000
11,000
10,000
12,000
12,500
8,000
10,000
20,000
15,000
20,000
20,000
22,000
18,000
28,000
16,000
24,000
20,000
30,000
1996 Network
Gas Tariff /
person (for
stove use)
1,000
470
325
953
1,545
1,100
1,200
1,350
2,033
1,350
900
800
2,475
1,200
1,000
891
891
940
850
1,440
960
640
1,827
1,400
592
1,280
1,920
1,827
1,200
1,200
2,200
2,000
2,000
2,000
Consumption
Norm for Gas
Hot Water
(cubic meter /
12.9
12.5
13.1
18.8
10.0
12.0
12.0
13.0
19.8
15.0
20.0
10.0
15.0
13.0
12.5
15.0
15.0
12.0
15.0
16.0
25.0
25.0
14.7
13.0
15.8
15.0
15.0
14.7
12.5
13.0
14.0
25.0
25.0
25.0
Consumption
Norm for Gas
1996
Heat (cubic
1996 Gas Tariff
Gas Cost
Electricity Electricity Cost
meter / sq m)
/cubic meter
Recovery Level Tariff /kWh Recovery Level
4.1
145
55%
10,000
43%
7.6
57
21%
13,000
49%
4.5
41
15%
13,000
49%
12.0
75
31%
18,400
61%
4.5
150
56%
10,000
43%
7.0
110
41%
8,000
34%
7.0
150
56%
6,000
30%
7.5
193
73%
5,000
27%
6.3
231
87%
10,000
35%
4.3
169
65%
8,000
49%
8.0
90
34%
7,000
56%
7.5
80
31%
9,000
50%
7.0
309
100%
3,700
19%
14.0
120
45%
6,000
30%
8.5
83
32%
12,000
38%
7.0
59
23%
9,000
38%
7.0
59
23%
9,000
38%
7.0
118
44%
9,000
45%
55%
12.0
85
31%
15,000
6.2
111
41%
8,000
50%
13.0
74
27%
12,000
50%
13.0
49
18%
10,000
45%
5.5
174
68%
8,000
32%
8.0
200
78%
12,000
43%
8.3
74
29%
8,500
43%
7.0
128
53%
8,000
41%
7.0
192
75%
10,000
38%
5.5
174
68%
8,000
32%
10.1
145
56%
10,000
43%
7.3
171
77%
8,000
43%
8.6
220
83%
7,500
37%
13.0
154
69%
8,400
54%
13.0
154
64%
15,000
50%
13.0
154
60%
15,000
50%
47