• This fact, however, considerably underestimates the longer term costs of the current policies related to the preservation of non-transparency in financing and be distorted incentives of sector players.
• Such inertial policies seem fully affordable to the population, and they do, for example, a reduction in the eligibility threshold for housing allowances).
• The sensitivity of these results is high relative to the modest changes in the level of residential tariffs (e.g., all other factors being the same, the transition from 90 to percent in cost recovery could increase the number of recipients of housing allowances by 30 percent.
• The sensitivity of the results is low relative to the variation in rates of economic growth: in our scenarios with lower economic growth (columns 1-6), we assumed a lower level of domestic energy prices and housing costs, but this effect is largely compensated by lower household incomes in these scenarios.
Table 3.19: Results of Simulations for the Third Year of Reforms: Status Quo Scenarios -- Slow Reforms in Housing and Utility Tariffs, No Elimination of lgoty Low growth High growth Maximum household spending on housing 15% 22% 15% 22% 100% + 100% + 100% + 100% + Cost recovery in tariffs Capital Capital Capital Capital 90% 100% Repair 90% 100% Repair 90% 100% Repair 90% 100% Repair Total housing costs, % of GDP 6.5 6. 1 2 3 4 5 6 7 8 9 10 11 Budget spending on allowances 0.13 0.18 0.32 0.05 0.07 0.14 0.13 0.18 0.31 0.05 0.07 0.Budget subsidies on tariffs 0.54 0 0 0.54 0 0 0.54 0 0 0.54 0 Budget compensation for lgoty 0.66 0.74 0.89 0.66 0.74 0.89 0.63 0.71 0.85 0.63 0.71 0.Budget spending on capital repair 1.09 1.09 0 1.09 1.09 0 1.04 1.04 0 1.04 1.04 Total budget costs 2.42 2.01 1.21 2.34 1.9 1.03 2.34 1.93 1.16 2.26 1.82 0. as % of total housing costs 37.2% 30.9% 18.6% 36.0% 29.2% 15.8% 37.7% 31.1% 18.7% 36.5% 29.4% 15.8% Max number of hhs that are recipients of allowances, mn 4,207 5,206 7,202 1,683 2,209 3,416 4,284 5,294 7,304 1,721 2,257 3, as % of population 9.0 11.1 15.4 3.6 4.7 7.3 9.1 11.3 15.6 3.7 4.8 7.Number of regions with the share of recipients > 25% 3 5 13 0 0 1 3 5 13 0 0 Share of population that resides in these regions, % 3.7 5.0 10.3 0 0 0.3 3.7 5.0 10.3 0 0 0. Scenarios for the acceleration of housing and utility reforms 3.107 Table 3.20 presents the results for simulations of the group of scenarios that provide for a significant acceleration of tariff reforms in the housing and energy sectors, including the elimination of cross-subsidization and a much more aggressive pace of adjustment in domestic energy prices. However, these scenarios do not assume an elimination of the housing lgoty (privileges).
3.108 We again use as a base case the scenario reflected in Column 10, which assumes that the key current parameters of housing policy remain unchanged: an eligibility threshold for allowances of 22 percent and a 90 percent cost recovery in tariffs. This simulation suggests that the overall costs of the housing sector’s operations would increase to 9 percent of GDP (i.e., a growth of almost 90 percent relative to 2002). However, these are the full costs that assume the full elimination of quasi-fiscal financing.
3.109 In this scenario, the budget would be responsible for 37 percent of the total costs (3.percent of GDP), while households would have to pay the remaining 5.7 percent of GDP, which is an increase of 130 percent relative to 2002. This would bring the share of housing spending in household budgets to 16 percent. About 9 percent of households would become recipients of housing allowances. In only 1 out of 88 regions the share of allowance recipients would exceed 25 percent.
3.110 In this scenario the total costs of housing lgoty, which grow in line with growth in unit housing costs, would reach 0.9 percent of GDP. This would amount to 30 percent of total budget spending in the sector.
3.111 A further shift of the housing cost burden to the population (as reflected in Column 11) seems to be fully affordable as well. Under the 100 percent cost recovery, the share of the government in total housing financing declines to 30 percent (2.7 percent of GDP, namely, 0.percent more than in 2002). The share of allowance recipients reaches 11 percent, which does not sound as prohibitively high.
3.112 In the most advanced scenario (column 12), which assumes the full incorporation of capital repair charges in tariffs, the share of the government would fall to 18 percent of total financing (1.65 percent of GDP, namely, 30 percent below the 2002 level). Households would face out-of-pocket housing expenditures of 7.35 percent of GDP (an increase of almost percent relative to 2002). More than 15 percent of the population would become recipients of allowances, while in 10 regions the share of recipients would exceed 25 percent. The average share of total housing spending in household budgets would be close to 20 percent. This is 2.times higher than the 2002 level, but still somewhat below the levels currently common in CEE countries.
3.113 Thus, in the most advanced scenario, the households’ out-of-pocket expenditures on HUS would be by almost five percent of GDP above its 2002 level. This is a very large increase indeed. How affordable is such a burden In the view of the authors of this report, it could be broadly affordable, assuming the latest trends of high real income growth are sustained. As discussed in Chapter 4, it is expected that in the medium term the real average wage growth in Russia will remain above the rate of GDP growth. This in part will be driven, as shown in Chapter 2, by the reforms in civil sector employment that should result in a considerable increase in public sector wages. Annual budget spending on (non-military) wages may increase by 1 percent of GDP under the advanced reform scenarios. Overall, preliminary estimates suggest that about 60 percent of the future out-of-pocket housing spending could be funded through a parallel growth in real household incomes. More accurate estimates could be obtained when the full information for 2003-04 is available. Those were the years, during which real housing costs have been increasing at a relatively high for Russia pace, but this was mitigated by a high and broad-based income growth.
3.114 Our further interpretation of these results is that a practical policy option for the government for the next two to three years would be some combination of scenarios reflected in columns 11 and 12 of Table 3.20. That is, regions with higher incomes should follow scenario 12 (with the incorporation of capital repairs charges in tariffs), while those with lower incomes may follow scenario 11 (100 percent cost recovery, but no household responsibility for capital repairs). Such a combination of policies would keep the government spending in the sector at roughly its current level of about 2.2 percent of GDP. On average, households would be spending about 18-19 percent of their budget on HUS.
3.115 An important conclusion from our analysis is that the acceleration of energy and housing reforms in the current macroeconomic conditions should not bring any incremental costs to the consolidated government budget. In the worst case, the reforms should be budget neutral in the medium term, and they should bring considerable savings in the long term.
3.116 At the same time, it is worth noting that in the analyzed scenarios while the total budget outlays on the sector would decline, their structure of budget spending would remain rather inefficient. This is because, without the elimination of lgoty, their costs would expand drastically in line with progress on the tariff reforms. In scenario 12, the costs of lgoty would amount to 1.2 percent of GDP, and they amount to three-fourths of the total budget spending in the sector. This means that phasing out lgoty is critical for any significant improvement in the efficiency of budgetary spending in the sector.
3.117 The low income regions, where the population cannot afford capital repair charges as yet, should be partially supported by the federal government. It is recommended that the federal government should develop a separate program for investment grants to support the rehabilitation of the housing stock in such regions on a co-financing basis. Funding for such a program could be obtained by phasing out the existing non-transparent programs of housing sector financing as described above.
3.118 The analysis identified two groups of regions that are likely to be most affected by the proposed cost increases in the HUS, as follows:
• Regions located in the south of Eastern Siberia and in the Far East. These are the regions with high unit housing costs due to their remoteness and climate conditions.
At the same time, these are relatively poor regions, which are significantly dependent upon federal budget transfers.
• Autonomous (internal national) republics in various parts of the country. These are predominantly the rural, least developed regions with a relatively low share of urban housing that has full access to subsidized and expensive network utilities. Thus, these regions spend relatively little on housing, but their policy in the sector has been traditionally the least reformed and they have had among the lowest levels of cost recovery in tariffs. As a result, the future costs of residual adjustment to reach full cost recovery in these regions could be quite high. Moreover, these regions are the most transfer-dependent entities in Russia, and this reduces their fiscal room for adjustment to additional policy and price shocks.
Additional sensitivity analysis 3.119 Additional analysis was undertaken to check the sensitivity of the above results to changes in what are seen as the most important parameters in the model: i) the dynamic of household incomes, and ii) the level of housing costs.
3.120 Sensitivity to changes in incomes. A set of simulations was undertaken with significantly lower rates of real income growth, which would result in 2006 household incomes being 20 percent below the level assumed in the base case scenario above. The simulation showed rather high sensitivity: in the scenario with 100 percent cost recovery (column 11) a 20 percent decline in incomes increases the number of recipients on housing allowances by about 80 percent (to 20 percent of the population). The total budget spending on housing allowances would increase by 140 percent (to 0.57 percent of GDP). In such an environment an aggressive policy of tariff adjustments may be much more difficult to implement.
3.121 The high sensitivity of the results to income dynamics suggests that the government should establish an efficient monitoring system to track the affordability of tariff increases for the population in general and for specific household groups. While within the current favorable macroeconomic environment the government should make a strong push toward the necessary adjustments in domestic energy prices, the elimination of cross-subsidization, and the achievement of full cost recovery in tariffs, this policy may be modified in cases where the economy faces a major slowdown in household income growth. Some low income regions could be allowed to move with the reforms at a slower pace than the rest of the country.
3.122 If, in the environment with high growth in household incomes, the advancement of housing reforms could be easily made budget neutral, this is not case when income growth slows down. The latter may generate incremental budget costs of 0.4-0.5 percent of GDP per annum in the medium term, which would be mostly related to the additional financing of housing allowances.
3.123 Sensitivity to changes in housing costs. Additional simulations assumed are approximately 20 percent higher level of housing costs. These simulations revealed a relatively high sensitivity (although lower than in the case of household incomes) - the number of recipients of housing allowances increases by 27-31 percent depending on the level of cost recovery.
Table 3.20: Results of Simulations for the Third Year of Reforms: Scenarios with Advanced Reforms in Housing and Utility Tariffs, but without Elimination of lgoty (as % of GDP) Low growth High growth Maximum household spending on housing 15% 22% 15% 22% 100% + 100% + 100% + 100% + Cost recovery in tariffs Capital Capital Capital Capital 90% 100% Repair 90% 100% Repair 90% 100% Repair 90% 100% Repair Total housing costs, % of GDP 9.1 9. 1 2 3 4 5 6 7 8 9 10 11 Budget spending on allowances 0.35 0.48 0.79 0.15 0.22 0.39 0.39 0.52 0.85 0.17 0.24 0.Budget subsidies on tariffs 0.76 0 0 0.76 0 0 0.75 0 0 0.75 0 Budget compensation for lgoty 0.92 1.02 1.23 0.92 1.02 1.23 0.91 1.02 1.22 0.91 1.02 1.Budget spending on capital repair 1.51 1.51 0 1.51 1.51 0 1.50 1.50 0 1.50 1.50 Total budget costs 3.54 3.01 2.02 3.34 2.75 1.62 3.55 3.04 2.07 3.33 2.76 1. as % of total housing costs 38.9% 33.1% 22.2% 36.7% 30.2% 17.8% 39.0% 33.4% 22.7% 36.6% 30.3% 18.1% Max number of hhs that are recipients of allowances, mn 7,758 9,096 11,609 3,790 4,730 6,640 8,296 9,678 12,209 4,161 5,154 7, as % of population 16.6 19.4 24.8 8.1 10.1 14.2 17.7 20.6 26.0 8.9 11.0 15.Number of regions with the share of recipients > 25% 15 23 46 2 4 12 13 20 42 1 3 Share of population that resides in these regions, % 11.7 18.7 46 1.8 3.9 9.1 10.3 16.3 41.5 0.3 3.7 8. J. SIMULATIONS FOR PHASING OUT HOUSING PRIVILEGES (LGOTY) Incidence of lgoty 3.124 Various non-cash housing privileges (lgoty) represent one of the major deficiencies of Russia’s housing policy. Lgoty provide their beneficiaries with considerable discounts (usually 50 percent) against their housing and utility bills. Lgoty are category-based benefits, and as such they are an inefficient policy instrument of social assistance that tends to channel most support to middle-income and high-income groups (World Bank, 2004c).
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