Initial Conclusions from CURA Survey Data

The Metropolitan Council's new method for determining affordable housing goals is a significant departure from previous practices.  Under the old method (which was determined by the procedures set up in the Livable Communities Act, or LCA), participation by municipalities was voluntary.  Under the new system, the Met Council calculates housing needs for all cities in the core and developing areas of the metropolitan area.  Under the old LCA system, the Met Council and each participating municipality would negotiate goals that were loosely based on the previous track record of that community and others like it.  Thus, the LCA system was not based on a calculation of the need for affordable housing, but rather the imputed capacity of each city to produce affordable housing.  The new system is based on a formula and not on negotiation.  The formula takes need (and other factors ignored in the LCA system) into account very directly.  The formula produces a number for each city which is that city's affordable housing goals for the 2010-2020 period.  (See an explanation of other differences here).

The shift from LCA to the formula has resulted in a significant change in the distribution of affordable housing requirements in the region.  This can be seen by comparing the new goals to what would have been the goals had LCA been extended another 10 years.[1]  An analysis that applied the LCA goals (which expire in 2010) to population growth projections for the 2011-2020 period, and then compared those hypothetical goals to the numbers produced by the new formula system reveals that the new system redistributes affordable housing effort away from the northern and southeastern suburbs of the metro area and toward the western and southwestern suburbs (see figure 1).

In figure 1, communities shaded green and yellow will see a reduction in their affordable housing goals under the formula system, relative to what they would have been had LCA been continued.  Communities shaded orange and red will see a relative increase.  Cities in white did not participate in LCA, or did not have numerical goals under the program, or are not included in the new formula system.  As the map shows, most communities will actually see a relative decline in their affordable housing obligation under the new system.  Despite this, most of the suburban officials we interviewed expressed significant pessimism about their ability to meet the goals.


Officials in 39 cities were interviewed in the spring of 2006, weeks or months after the Met Council announced its new formula system.  The communities chosen for interviews were chosen because of their size and growth rates; they represent the largest and fastest-growing suburban municipalities in the region.  Most (80%) of the officials we spoke with were aware of their new affordable housing need numbers by the time we met with them.  The most striking thing we learned from local officials had to do with the potential impact of the new system.  When we asked them about the goals, most of the respondents expressed reservations.  Three-fourths felt that the formula produced affordable housing goals that were too high for their cities, and the same percentage concluded that the goals were simply not feasible.  In fact, more than half (58%) of the officials we spoke with were unsure whether they would even use the new affordable housing goals as their target in their comprehensive plan updates.[2]  Three officials indicated they would not use the formula number.  Taken as a whole, these responses indicate that the new system and its ability to produce significant affordable housing production in the suburbs may face significant obstacles.

When asked to name the chief obstacles to meeting affordable housing goals, land costs were mentioned by 62% of the respondents, lack of available land for multi-family and low-cost housing was mentioned by 42%, and 36% cited the lack of funding for subsidized housing .  When presented with a specific list of potential obstacles, officials indicated that lot-size requirements and the lack of land zoned for multifamily housing were the most important (see table 1).

Table 1: Obstacles to building affordable housing

Limits affordable housing very much

Limits affordable housing somewhat

Does not limit affordable housing

Lot size requirements

9 (27%)

12 (36%)

12 (36%)

Amount of land zoned for multi-family hsg

7 (21%)

10 (31%)

16 (49%)

Local building materials requirements

3 (9%)

13 (39%)

18 (55%)

Subdivision regulations

2 (6%)

13 (39%)

18 (55%)

Permitting processes and fees

3 (9%)

12 (36%)

18 (55%)

Prohibition on accessory units

2 (6%)

10 (30%)

21 (64%)

Limits on use of manufactured housing

4 (13%)

4 (13%)

23 (74%)

Code enforcement requirements for rehab

3 (10%)

2 (7%)

25 (83%)

Table 1 shows that there was not a great deal of unanimity among the officials we interviewed about the obstacles to affordable housing development.  This suggests that the importance of specific impediments varies from place to place.  A reasonable regional approach to getting affordable housing built, then, must be flexible enough to respond to different challenges in different communities.  The only impediments that seem to operate in most communities are requirements for large lots and a lack of land zoned for multifamily housing.

Officials also mentioned a smattering of other specific obstacles, such as design guidelines, minimum square-footages built into some zoning ordinances, and taxes/red tape that all drive up the cost of housing.

Local Actions

Only one-quarter of the cities we contacted keep a database tracking the supply of low- and moderate-income housing in their communities. Others either rely on the County or other agencies to monitor the availability of affordable housing, or they do not concern themselves with it.  Such a lack of monitoring, of course, makes it difficult to know whether local goals are being met.

A range of public policy approaches are being used by the cities we contacted.  The most common means by which these communities attempt to provide affordable housing is the use of Planned Unit Developments (PUDs) that incorporate smaller lots or density bonuses for developers (79% of respondents indicated they did this).  Other commonly used techniques are Tax Increment Financing (70%), adjustments in lot sizes (50%), allowing manufactured homes (44%), the use of the Low Income Housing Tax Credit (LIHTC) program (41%), and various zoning techniques such as density bonuses and variances.

Officials felt that the LIHTC program was the most effective in producing affordable units, perhaps because it provides direct funding for development.  In fact, half of the respondents felt that their communities could reach the affordable housing goals set for them by the Met Council if there were greater funding available for low- and moderate-income housing.

Another mechanism that was identified as very effective by a large percentage of officials who had used it, was a 'set-aside' for low-mod housing (i.e., an inclusionary zoning program).  However, only a very small percentage of communities actually have any experience with such an approach - 12%. 

The respondents did not indicate that they would be expanding their toolbox for building affordable housing very much in the future.  For example, 15 respondents reported having used density bonuses in the past, but only 14 indicate that they are likely to do so in the future.   While 15 have used the LIHTC program in the past, 14 said they will in the future.  Twenty-seven have used TIF in the past, but only 16 said they will in the future. This pattern is repeated for every one of the specific tools we inquired about.


The survey results give some cause for concern about whether the regional system of planning for affordable housing will have a significant impact.  A significant percentage of the suburban officials we spoke with felt the new goals were too high, and in fact unrealistic.  Most indicated to us that they would either not be using the goals in their comprehensive plans or that they were unsure whether the new numbers would be used.

Officials recognize a range of impediments to the production of affordable housing.  None of the obstacles was prevalent enough to suggest that a one-size-fits-all approach to getting affordable housing built would be effective in the region.  The salience of different impediment varies from community to community, suggesting that an extensive menu of policy approaches and resources will be necessary to produce a widespread increase in affordable housing production.

[1]  We simply applied the LCA goals - which are expressed as a percentage of new development - to the growth projections for each community.  To take a hypothetical example, if a community was projected to grow by 600 households between 2011 and 2020, we multiplied 600 by the community's LCA owner/rental goals (for the sake of this example let us establish these goals as 75% ownership and 25% rental).  This produced the projected number of units in each tenure category (600*.75=450 new ownership units and 600*.25=150 new rental units).  We then multiplied these numbers by the affordability goals for each category of housing.  Again, for the sake of the example let us say that the community had an ownership affordability goal of 78 (under LCA this meant that 78% of new units would be affordable) and a rental affordability goal of 42.  This produced the actual unit goals that would have applied had LCA been extended for another 10 years.  In our hypothetical case it was 450*.78=351 new affordable owner units, and 150*.42=64 new affordable rental units.  The total affordability goal is the sum of the two, 351+64=415.  This number was then compared to the affordability goals produced by the formula.  Figure 1 shows how the numbers compare for each community.  Cities in red have higher goals as a result of the formula than would have been the case had LCA been continued, and cities in green have lower goals than LCA would have produced.

[2]  It should be noted that this is the very purpose of the new formula and the goals that it calculates for each community.


Edward G. Goetz & Audrey Vesota, 2007
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