7. Reconciling Housing and the Environment
The nexus between the residential sector and environmental quality is reciprocal and complex. The residential sector generates environmental impacts via land and materials use, energy consumption and the transport activity it engenders. Environmentally motivated policies on land-use, construction and energy efficiency, and transport seek to alleviate these impacts by incorporating the cost of environmental externalities into house prices. As a result, such policies often have negative impacts on affordability. Housing policies can also have environmental implications insofar as they affect the environmental footprint of residential development. The impacts of environmental policies on housing markets, and vice versa, depend on policy and the characteristics of the urban areas where they are implemented. Sustainability in the housing market can be promoted according to social welfare approach that accounts for housing affordability, as well as the environmental and economic impacts of policies.
The residential sector has a sizeable environmental footprint. It generates environmental externalities directly, through the use of materials in construction and demolition. It also impacts the environment indirectly, through the energy consumed during construction and use of residential buildings. The housing sector is also related to transport-related environmental externalities, as spatial development patterns determine the extent to which urban mobility depends on car use.
Environmental policies in the residential sector aim to correct these externalities by better aligning the private and the social costs of housing. The net environmental impacts of common land-use policies depend on how these policies internalise the external costs from land-use, energy consumption, materials use into property prices and rents.
Although evaluating the housing-related impacts of environmental policies in specific contexts involves the use of cost-benefit analysis on a case-by-case basis, certain policy interventions tend to have consistent impacts on housing supply, demand and affordability. For example, because environmentally related policies tend to increase the cost of housing, it is important to consider possible trade-offs between environmental sustainability and affordability objectives. In contrast, some environmental policies, such as densification, can mitigate the environmental footprint of the residential sector while also ameliorating housing affordability. Such policies that achieve net improvements in environmental quality and in housing affordability could be identified and prioritised in housing policy reform packages.
There is scope for better accounting for the impacts that environmental policies can have on housing markets, and vice versa. These impacts can be anticipated via ex-ante approaches that estimate the cross-sectoral implications of policies based on the characteristics of the housing market, urban form, transport systems and consumer preferences in specific contexts. Ex-post approaches that evaluate the impacts of housing and environmental policies on the housing markets and the environment, respectively, are also important in better understanding the trade-offs between the two and of the role of contextual factors therein.
A residential structure generates various pecuniary and negative externalities across its life cycle. First, it implies the use of land, which in many cases is relatively scarce and may have other productive uses. Its construction requires materials and energy that generate greenhouse gas emissions and other environmental pollutants. Globally, urban land area is projected to rise nearly five-fold, to almost 3 million km2 by 2050 (Angel et al., 2011[1]), and 70% of the world population is expected to live in these areas. To meet the increasing housing demand globally, the construction sector is expected to more than double between 2017 and 2060, along with its use of materials. This expansion is set to lead to almost 84 Gt of construction materials use per year in 2060 (OECD, 2019[2]).
Once a structure is built, it continues to have environmental impacts through energy and water consumption on the one hand, and waste and sewerage creation on the other. Many countries have improved housing-related energy efficiency, as evidenced by declining residential energy consumption per capita (Figure 7.1 , Panel A). Exceptions are most Eastern European countries as well as Brazil, Italy, Spain and Finland. Countries that achieved small reductions in energy intensity however saw overall energy consumption increase on the back of rising population, a trend that is set to continue on unchanged housing and energy policies. The bulk of the energy consumption of the residential sector originates comes from heating, which explains why countries exposed to cooler temperatures usually exhibit higher per capita energy consumption. Still, there are large discrepancies in terms of how heating degree days, an indicator for the intensity and duration of cold temperatures, translate into residential energy consumption per capita (Figure 7.1 , Panel B). In some countries that consume a lot of energy relative to what the number of heating degree days would suggest, the use of air conditioning explains a good chunk of energy consumption (United States, Australia, Canada). Another key determinant of high energy consumption seems to be the size of dwellings. Indeed, the United States leads the country ranking in terms of floor area per capita followed by Canada and Denmark, all countries that exhibit a residential energy intensity above the average for a given number of heating degree days.
Note: The residential sector’s energy consumption includes space heating and cooling, water heating, cooking and appliances.
Panel B: Heating degree days are defined as the number of degrees that a day's average temperature is below the country’s base temperature, that is, the temperature below which residents typically turn on the heating system. The green (red) area signifies energy consumption smaller (greater) than expected given the number of heating degree days. Shaded areas around the regression line denote confidence intervals
Including the indirect emissions from power generation are considered, buildings are responsible for nearly 30% of global energy-related CO2 emissions. In absolute terms, buildings-related CO2 emissions rose to an all-time high of 9.6 GtCO2 in 2019 (IEA, 2020[3]). While the residential sector's carbon intensity strongly correlates with energy intensity (Figure 7.2), differences in the energy mix explain a significant part of cross-country differences in the carbon footprint per capita. Countries with a high share of low-carbon energies (i.e. nuclear and renewables) achieve a much lower per capita carbon footprint for the same per capita energy consumption. Countries that stand out in this respect are France with a high share of primary energy from nuclear (37% in 2019), Sweden with both a high percentage from nuclear (27%) and renewables (42%) and Brazil that displays the highest share from renewables (45%) mainly from hydroelectric power (28%).
Note: Green (red) area signifies a carbon intensity smaller (greater) than expected given the level of energy intensity. Shaded areas around the regression line denote confidence intervals. All data refers to 2019.
1. Residential activities are also responsible for 44% of fine particulate matter (PM2.5) emissions on average across OECD countries (Figure 7.3).1 Housing is a critical source of PM2.5, especially in Central and Eastern European countries, due to the relatively high proportion of solid fuels, notably wood and coal, in residential heating (Karagulian et al., 2015[4]). PM2.5 is the air pollutant that poses the greatest risk to health globally, and critical exposure to these particles considerably increases the risk of respiratory and cardiovascular diseases. Exposure to PM2.5 concentration is positively correlated with the density of urban areas (Borck and Schrauth, 2021[5]). Mean exposure to PM2.5 emissions is decreasing in most OECD countries (Figure 7.4) – due to optimised combustion processes (in industry and in residential heating), a decrease of coal in the energy mix, and lower emissions from transport and agriculture – but still remains high and above the 10 μg/m3 recommended by WHO (OECD, 2020[6]).
Note: The “Housing” category includes the sub-categories: Housing, water, electricity, gas and other fuels, and Housing-other. The “Industry” category includes all ISIC rev.4 classification activities from A to U except for H, which is merged together with the Households-Transport subcategory into “Transport”.
Source: Air emission accounts, OECD Environment Database.
Note: Mean annual outdoor PM2.5 concentration weighted by population living in the relevant area, that is, the concentration level, expressed in microgram/m3, to which a typical resident is exposed throughout a year. 2019.
Source: Enviromental risks and health, OECD Environement Database.
2. The housing sector also generates environmental impacts related to the transport activity that it engenders. In general, a less accessible location implies greater reliance on private cars and a larger environmental footprint. The relationship between environmental quality and the housing sector is bidirectional, as the former also has implications for the latter. Proximity to environmental amenities is an important determinant of housing demand, and the elasticity of property values with respect to the quality of environmental amenities is generally greater than one (Kuethe and Keeney, 2012[7]; Wang et al., 2015[8]). Finally, urban growth is often characterised by a scattered, low-density development pattern known as urban sprawl, which is associated with multiple environmental externalities, social inefficiencies and car dependence (OECD, 2018[9]). The loss of biodiversity is among the most pressing global environmental challenges related to urbanisation. Figure 7.5 illustrates the percentage of tree cover, grassland, wetland, shrubland and sparse vegetation converted to cropland or artificial surfaces from 1992 to 2015 in functional urban areas. The results suggest large discrepancies across countries.
Note: The indicator shows the percentage of tree cover, grassland, wetland, shrub land and sparse vegetation converted to any other land cover type (cropland or artificial surface).
Source: OECD.Stat: Land Cover in Functional Urban Ares (http://dotstat.oecd.org/Index.aspx?DataSetCode=LAND_COVER_FUA).
The general aim of environmental policies in urban areas is to reduce the environmental externalities of urban development, such as greenhouse gas emissions and other pollutants generated by buildings and transport. Other interventions aim at limiting land-use change, preserving open space and protecting biodiversity. Such policies can affect the functioning of housing markets through their impacts on supply and demand for housing, and therefore on housing prices and affordability. The impact of environmentally-related policies on housing supply is twofold. In the long term they may induce more gradual changes in urban form and other factors that affect supply and housing prices.
3. The interactions between environmentally related policies and housing markets are complex (Figure 7.6). Land-use and transport policies may impact either housing demand or housing supply, or both, whereas construction regulations mainly influence housing supply. Policies surrounding construction practices and energy efficiency mainly influence housing supply. Non-environmentally related policies can also have impacts on environmental quality through their impacts on housing markets. In turn, environmentally related policies that impact housing supply and demand will also impact housing prices and affordability.
Policies also interact with fundamental drivers of housing supply, including the cost of land, renovation/site improvement, labour and materials, as well as finance, administration and marketing. In addition to the cost of these inputs, the price of the existing stock of dwellings, and the technologies used in construction also impact housing supply. Insofar as the housing supply is elastic to the availability of land and other factors, any policy affecting these factors will have an impact on the housing market via changes in housing supply. The extent to which environmentally related policies will impact housing supply in specific areas depends on local conditions that determine how supply responds to changes in these factors.
Environmentally related policies can impact housing demand by affecting accessibility of jobs, economic centres, and environmental and other amenities. For instance, policies that make an area more accessible to public transport and soft mobility, as well as less exposed to traffic congestion will render it more attractive as a residential location and will consequently serve to raise housing and land prices in that area. In addition, other powerful factors drive housing demand, such as demographics (e.g. population growth, family size and age composition, net migration), income, the user cost of capital, the availability of credit, consumer and investor preferences, and the prices of substitutes and complements to housing. The analysis of the impacts that follows considers these factors as fixed, thus the reported impacts should be interpreted as assuming that all else remains equal.
Land-use policies must be carefully designed to achieve their environmental objectives without inducing substantial welfare losses in the housing market. Land-use policies play an important role in shaping urban form, which has direct as well as indirect environmental implications. Environmentally related land-use policies seek to mitigate the negative externalities of the residential sector via several approaches, including managing growth, reducing the environmental impacts of existing development, and preserving open space (Table 7.1 and Table 7.2). In addition to reducing the negative environmental externalities of urban areas, land-use policies also aim to foster social cohesion and security, protect public health and safety, secure property rights and improve the functioning of housing markets, capture the value accruing from public sector investments and raise revenues to finance continued infrastructure provision (UNECE, 2008[10]; Silva and Acheampong, 2015[11]).
Despite their generally positive environmental impacts, land-use policies have substantial distortionary impacts on the functioning of the housing market in urban areas. For instance, the economic benefits of greenbelts include the higher amenity value of protected land and fiscal savings from more efficient provision of public services and infrastructure. However, greenbelts can also give rise to economic side-effects such as rising housing costs and social pressure if housing supply within the area is not able to accommodate growing demand (see Box 7.1; Glaeser and Kahn, 2008). Furthermore, although they often result in improvements in local environmental quality, the net environmental impacts of these types of measures are not always positive. Net environmental impacts can in fact be negative in cases where the urban area located within the containment zone is not able to accommodate additional development. This may occur, for example, when an urban growth boundary coexists with stringent maximum building height restrictions. For instance, leapfrog development may create a scattered development pattern (Vyn, 2012[36]) that increases the social cost of public service provision. Car dependency and increased CO2 emissions are among the most important consequences of such development (Matteucci and Morello, 2009[37]).
Therefore, environmentally motivated land-use policies must be carefully designed to achieve their environmental objectives without inducing substantial welfare losses in the housing market. Ensuring an adequate amount of developable area within an urban perimeter and periodically reevaluating the boundaries defined by urban containment measures, for example, can prevent housing supply from becoming inelastic and mitigate the negative impacts of containment policies on house prices (Silva and Acheampong, 2015[11]; Ball et al., 2014[13]; Bengston and Youn, 2006[16]; Blöchliger et al., 2017[38]). Similarly, the net environmental impacts of zoning regulations are unclear, as considerable diversity exists regarding specific zoning mechanisms and the contexts in which they are implemented.
Maximum building height restrictions are among the most common regulatory mechanisms worldwide, with considerable impacts on the housing market and the environment. For instance, maximum building height restrictions are often invoked to protect historical buildings in city centres and to maintain non-market attributes, such as visibility, primarily in suburban areas. As such, they often confer social benefits, which may increase residential satisfaction (Brown, Oueslati and Silva, 2016[39]) and raise land and house prices. Flexible building height restrictions are a particularly effective instrument to prevent population density from reaching levels that are socially detrimental, such as in areas where the spatial concentration of air pollutants is high (Schindler and Caruso, 2014[40]). In spite of this, widespread building height restrictions can have severe adverse effects in the markets of land and housing, as well as on the environment. When deployed without sufficient justification, this type of zoning policy contributes to excessive sprawl, generates additional congestion and emissions whose social cost may well exceed 2% of household income (Bertaud and Brueckner, 2005[41]; Tikoudis, Verhoef and van Ommeren, 2018[42]).
Other measures, while theoretically efficient, are not in widespread use due to practical issues related to their implementation. For example, performance zoning, which requires properties to meet certain standards of environmental performance, allows for flexibility in how developers achieve environmental outcomes. However, this type of zoning is more difficult to administer than more classic approaches based on simpler metrics, such as how a property is used and its physical characteristics (Wilson et al., 2018[43]; Frew, Baker and Donehue, 2016[44]; Baker, Sipe and Gleeson, 2006[19]).
Land-use policies can have substantial environmental repercussions, but they also affect the housing market, often via their interactions with transport policies. That is, these policies have an impact on housing demand and supply, with implications for housing prices. A case study of Auckland, New Zealand, carried out by the OECD examines these interactions. They study compares a reference scenario characterised by zoning regulations that preserve low population density, with five scenarios characterised by alternative densification policies.
The study finds that, apart from contributing to car dependency, existing maximum density restrictions can cause housing prices to rise much faster than they would if such restrictions were relaxed (Figure 7.7). The study also demonstrates how growth in housing prices can have substantial distributional effects. The simulations employed in the study show that widespread densification can limit real house price growth in the period 2018-50 to 58%, as opposed to a total increase of more than 200% predicted in the reference scenario. Rising house prices benefits the segments of the population with a net positive income from rents, to the detriment of tenants with limited access to borrowing mechanisms. These findings demonstrate that the widespread densification is an effective instrument in the long-run policy response to the challenge of housing affordability in Auckland. This type of densification has the potential to prevent housing prices from reaching levels that will lead to welfare losses. Targeted densification packages, which in two cases represent a shift to transit-oriented development, can also slow down house price growth.
Note: TD refers to one of four targeted densification programs; TD1 refers to further densification of already-dense areas lying close to major employment hubs and public transit nodes; TD2 refers to densification of low-density zones surrounding the central business district; TD3 refers to densification of low-density areas in Auckland’s isthmus; TD4 refers to densification of areas in close proximity to employment hubs; WD refers to a widespread densification program.
Source: OECD (2020[45]).
The study demonstrates the various trade-offs policymakers should consider in designing urban policies. These include the desirable effect of densification on housing affordability, the welfare losses it may imply for those that highly value open space and its impacts on accessibility, car dependence and CO2 emissions.
Source: OECD (2020[45]).
Environmentally related construction practices and energy efficiency measures affect construction and maintenance costs
A number of environmentally related policies and measures target construction processes and energy efficiency. Such policies aim to promote or impose durable building design, recycling of construction and demolition waste, energy efficiency standards and the use of renewable energy (Table 7.3 and Table 7.4). In general, environmentally related construction and energy efficiency policies do not have a considerable impact on housing supply, but they affect house prices primarily via their impacts on construction and maintenance costs. Subsidies for energy-efficiency upgrading can ease adverse near-term impacts on affordability but are likely to be neutral over the long term as the value of the improvement gets capitalised in the dwelling price (Taruttis and Weber, 2020[46]). One large-scale example is Italy’s “Superbonus 110” programme, which provides a tax reduction equal to 110% of the expenses made by households to improve the energy efficiency of their homes.2 The COVID-crisis is likely to alter workplace and housing preferences bringing about challenges and opportunities for the environmental policy agenda (Box 7.2).
Measures that rely on voluntary engagement, such as some benchmarking efforts and information campaigns to encourage behaviour change also have a role to play. Benchmarking measures, for example, have been found to yield 2-14% energy savings across 8 studies in the United States (Karatasou, Laskari and Santamouris, 2014[58]; Mims et al., 2017[51]). The programmes that yielded these reductions relied on providing owners with information on how the emissions from their buildings compare with similar ones and also on concrete measures that can be taken to reduce emissions.
The COVID19 crisis has sparked a global economic downturn and has contributed to widening inequalities. Addressing these challenges deserves concerted policy responses in a range of areas. The OECD has issued a number of environmental policy recommendations in response to the COVID19 crisis. These include:
Maintaining existing environmental standards as part of recovery plans;
Continuing to develop and implement comprehensive strategies to achieve air quality objectives via a better integration of land-use planning, transport and environmental policies;
Implementing economic instruments to address pollution from mobile and stationary sources, and improving data collection and quality across monitoring networks.
As is evident by these recommendations, the crisis should not fundamentally alter the key aims of the environmental policy agenda in the long term. Because environmental policies essentially seek to reconcile housing market prices with their social costs, complementary measures to maintain affordability will be even more important in the aftermath of this crisis. For example, efforts to increase the share of soft modes in urban transport via financial incentives and infrastructure improvements. All else equal, this can be expected to lead to increased housing prices in the urban areas with improved accessibility. As a result, simultaneous efforts should be made to ensure the availability of affordable housing in the areas served by enhanced infrastructure.
A number of policy responses to COVID-19 in other areas can be expected to have environmental implications. Policies that facilitate teleworking will have two opposing environmental effects: a short-term positive effect, as the total number of commuting trips with widespread teleworking decreases; and a mid-term rebound effect, as less total commuting time decreases time valuations and induces household relocation further away from working locations. In a scenario in which the pandemic persists beyond the short run, promoting teleworking will increase the value of suburban and exurban properties and will have the opposite effects in more central and accessible urban locations. Preliminary evidence suggests that the crisis has generally led to increased property values and more stringent loan eligibility criteria (Carrns, 2020[59]).
Persistent risk aversion could also mean that housing markets may also need to contend with a shift in demand towards less-dense areas following the crisis, as has occurred in the vicinity of New York City (Hughes, 2020[60]).The extent of these changes, as well as the corresponding effects on property tax bases are currently unknown and require further research. Despite this, the pandemic should not reduce the appeal of increasing density as a strategy for improving the environmental footprint of urban areas. Density is far from the determining factor in virus transmission rates (Barr and Tassier, 2020[61]), as illustrated by the fact that many high density cities such as Singapore, as well as those in South Korea, Taiwan, Japan have been more successful than less dense urban areas in controlling the spread of the virus.
Source: OECD (2020[62]), OECD (2020[63]), Kholodilin (2020[64]), Barr and Tassier (2020[61]), Hughes (2020[60]), Carrns (2020[59]).
Environmentally related transport policies affect both demand and supply of housing
Transport policies can have a long-term impact on housing markets to the extent that they alter the desirability of different residential locations, primarily through their impact on travel time and costs. Transport policies may also affect local levels of air pollution, noise and traffic accidents. While transport policies can significantly affect the demand for housing and property prices across space, they can also impact housing supply insofar as they shape the investment decisions of residential developers.
Several environmentally related transport policies that regulate traffic-related externalities have an impact on urban form and house prices (OECD, 2018). These include a series of market-based instruments: pricing of road use, either with a flat kilometre tax or with charging schemes based on a cordon surrounding the central business district; pricing of on-street parking and public transport services; and motor fuel taxes. Regulatory mechanisms include various forms of urban vehicle access regulations, such as low emission zones, i.e. areas in which entry of vehicles is regulated based on their emission profile. Finally, the provision of infrastructure for public transport, walking and cycling also have clear implications for the environment and a simultaneous impact on demand for housing (Table 7.5 and Table 7.6).
Evidence on the impact of transport policies on housing markets is well documented. For instance, simulations for cities with relatively monocentric structures find that common pricing schemes substantially increase property prices and rents closer to central business district areas, while property values and rents in remote areas generally decrease (Verhoef, 2005[87]; Tikoudis, Verhoef and van Ommeren, 2015[88]). To some extent, these findings also apply to polycentric cities with multiple business districts. For instance, pricing traffic with a cordon toll surrounding the inner core of a polycentric city can result in housing costs changing from -4% to +12% (Tikoudis and Oueslati, 2020[89]). These changes largely correlate with house and land prices prior to policy implementation, implying that larger capital gains are expected in the most expensive areas, while smaller or negative capital gains are anticipated in less expensive ones. These results suggest that the distributional impacts of road pricing that materialise through the housing market are substantial and need to be carefully considered in policy design. However, despite their substantial effects on housing costs, urban road pricing generates aggregate welfare gains. Once road charges are aligned with the volume of traffic externalities and streamlined to account for interactions with the rest of the fiscal system, these welfare gains can be considerable.
Fuel taxes also affect house prices. As in the case of a flat kilometre tax, the price effect of the two instruments are at first identical, since in the short run the fuel consumption of private vehicles is fixed. Consequently, fuel tax increases in the short run generally have the effect of inflating property prices in locations of high accessibility since the tax makes travelling more expensive. In general, road pricing and fuel taxes encourage compact urban forms (Creutzig et al., 2015[90]). However, the disincentive created by a fuel tax will gradually subside over time as increasingly fuel-efficient vehicles become used.
Soft mobility and public transport infrastructure have a positive effect on property values. Opinion surveys show a substantial willingness-to-pay for walking and biking infrastructure, as this type of infrastructure can increase accessibility to public transport (Yang et al., 2018[91]). Making public transport more accessible, especially by promoting transit-oriented development, has been empirically found to have a positive effect on house prices (Bartholomew and Ewing, 2011[92]). As a result, investments in public transport and soft mobility can result in higher local property values.
Many policies targeting land-use and housing markets have an impact on the environment. Given that these impacts can be considerable, they need to be taken into account in the design of housing refom packages (Table 7.7 and Table 7.8).
Property taxes can induce urban sprawl with negative consequences on the environment, but also be leveraged to reduce the environmental impact of development
Ad-valorem (based on market value) property taxes have two important environmentally related functions (Chapter 8). First, they increase the overall cost of housing and thus may reduce the demand for residential floor space. In this sense, ad-valorem taxes could foster compact development, given country-specific context and circumstances. More compact development implies economies of density and saves resources by shortening travel distances and reducing transport-related externalities. Second, ad-valorem taxes impose a burden per unit of surface that is higher for dwellings located in areas where land is more expensive. Therefore, they could have a long run centrifugal impact on development patterns, redirecting development to peripheral areas. The environmental impact of the latter can be positive only to the extent that this redirection does not increase car use and exacerbate congestion. This could be the case in polycentric urban environments, where remote areas with relatively low property values may lie close to local job hubs that can provide an employment alternative to the central business district.
Property taxation can also be leveraged to reduce the environmental impacts of development. “Green” property taxes seek to incorporate the full cost of externalities arising from development, and environmentally oriented preferential property taxes can encourage property owners to preserve environmental amenities (Brandt, 2014[32]). Split-rate property taxes are characterised by higher tax rates on the value of land than on the value of buildings and other property improvements (OECD, 2021[94]). By encouraging the development of underdeveloped land, split-rate taxes reduce development pressure at the rural-urban fringe (Banzhaf and Lavery, 2010[93]) and provide further incentive to redevelop urban brownfields. Land taxes also serve to encourage homebuilding where it is most needed if land-use rules are compatible with such development (Chapter 8). They could however also induce construction in areas of high environmental value, for instance those close to ecologically sensitive areas. For this reason, they can be used in conjunction with other regulatory or market-based instruments designed to discourage development in environmentally sensitive areas (OECD, 2018[9]). Location-efficient mortgages constitute another class of instruments with important environmental implications. They can target direct spatially varying environmental externalities, since they can incentivise home purchase in areas where population density lies below socially optimal levels. Location-based mortgages possess plenty of theoretical appeal, but have little precedent demonstrating their effectiveness due to shortcomings in implementation and design (Chatman and Voorhoeve, 2010[95]; Kaza et al., 2016[96]).
Other policies that have a bearing on housing markets can also have an impact on the environment. Policies that seek to increase home ownership and revitalise declining rural areas (e.g. the French “one house for 1000 euros” initiative) can reduce house prices but also contribute to scattered development and urban sprawl. Housing finance regulations could also have an environmental impact in addition to the efficiency considerations discussed in Chapters 3 and 4. For instance, the gradual relaxation of regulations governing low collateral mortgages (sub-prime) played a substantial role in the Great Financial Crisis, and it also affected the spatial distribution of dwellings acquired with sub-prime loans, which were located typically in low-income and predominantly minority neighbourhoods (Rosenblatt and Sacco, 2018[97]; Gerardi and Willen, 2008[98]). The extent to which the sub-prime boom contributed in urban sprawl has not yet been examined empirically.
Coordination between the different levels of government is necessary to reconcile the objectives of housing affordability and environment preservation
Housing and environmentally related policies are often administered by different levels of government and jurisdictions, and therefore they need to be coordinated appropriately to achieve their intended objectives. Without coordination, different jurisdictions face incentives to implement taxes and charges above socially optimal levels, especially when they can use the generated revenue to the benefit of local residents (Phillips, 2020[99]). For example, jurisdictional differences in urban containment policies can create incentives for leapfrog development and spatially scattered development. Similarly, differences in property taxes across municipalities can be harmful for the environment and lead to negative distributional outcomes (Banzhaf and Walsh, 2008[100]).
Environmental policies often have diverging impacts on the environment and housing markets. While many environmental policies improve environmental quality in targeted areas, they can involve trade-offs in the residential sector, notably with respect to housing affordability. The opposite can also be true, as several instruments that appear ineffective have plenty of positive by-products. Also, policies can be both beneficial and detrimental in all its objectives, depending on the stringency of the corresponding policy instruments.
Use cost-benefit analysis
Reliable evaluations of alternative policy instruments requires welfare calculations that monetise their various costs and benefits across sectors. A cost-benefit approach can help policymakers to rank competing policies whose primary objectives are the same but whose mechanisms and implications may differ. Such an endeavour is to a large extent context specific and resource intensive, and as such goes beyond the scope of this chapter.
Re-evaluate the stringency of land-use policies
In spite of variation in policy measures and their impacts, a series of general insights can nevertheless be drawn from the evidence gathered. The first is that the net environmental impacts of many environmentally motivated land-use policies are in fact indeterminate, due in part to variations in their stringency and the diverse secondary effects they can entail in terms of development, energy use and transport activity. Similarly, some housing market policies can have negative impacts on affordability insofar as they raise housing costs without yielding substantial additional social value. Thus, in many cases governments should re-evaluate the stringency of some housing policies in light of the negative secondary effects they may create.
Invest in public transport and soft mobility
In contrast to regulatory land-use interventions, investments in public transport and soft mobility increase the social value of land and housing, rather than simply raising housing costs. Although such policies can render housing more expensive, the higher property values they generate reflect local benefits (e.g. increased accessibility) and the fact that certain local externalities are internalised. As long as investment costs are reasonable and willingness-to-pay for the advantages they afford is substantial, the social benefit of investments in public transport and soft mobility infrastructure should be expected to be positive.
Consider tailored compensation mechanisms in case of hard trade-offs
A number of environmentally related market-based mechanisms that attempt to correct for the externalities of urban development can impact house prices. Once these externalities are incorporated into market prices via such mechanisms, the resulting adjustments in property prices will reflect improvements in accessibility or environmental quality. Policy makers should evaluate this type of strategy against policy-driven cuts in housing supply, which can have a similar negative impact on housing costs without necessarily increasing the social value of the existing housing stock. For this reason, housing price adjustments should not be the primary concern in policy reforms that attempt to mitigate the considerable social cost of some types of externalities. There are certain exceptions to this rule, the most important being the case in which environmental taxation causes house price adjustments with large distributional effects. In these cases, tailored compensation mechanisms can support social objectives such as poverty reduction, inclusive growth, and reduced inequalities.
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Notes
← 1. Similarly, Karagulian F. et al., (2017[219]) find that the residential sector (heating/cooling of buildings and equipment/lighting of buildings and waste treatment) accounts for 37% of PM2.5 emissions globally.
← 2. The programme covers expenses incurred between 1 July 2020 and 30 June 2022 (cf. https://www.efficienzaenergetica.enea.it/detrazioni-fiscali/superbonus.html) .