Chapter 6: Local cost of decent housing for a living wage
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Chapter 6 is concerned with estimating the cost of acceptable housing. It describes how to do a local housing market survey to obtain the cost of rent (and utilities) for decent housing that meets the local housing standard discussed in Chapter 5. It includes tips on how to conduct an efficient local housing market survey, and provides an example of a housing survey questionnaire form. The chapter discusses how to analyze and present the results of a local housing market survey. Chapter 6 also discusses how to estimate housing costs when the rental market for decent housing is not well developed, and so there are very few rental units available that meet the local housing standard for decency.

Chapter 5 was concerned with how to establish a standard for acceptable housing for a location. The current chapter is concerned with how to estimate the cost of local housing that meets the local standard.

Estimating the cost of acceptable housing focuses on rent, because it is much easier to collect rental prices than to estimate the cost of home ownership. Many national statistical offices (including the United States) use rent rather than the cost of owner-occupied housing to estimate housing cost when they estimate CPI. Section 6.1 describes how to carry out a local rental cost survey. Section 6.2 indicates how to analyze this information. Section 6.3 discusses the possibility of asking workers about how much they think it would cost to rent acceptable housing in the study location. Sections 6.4–6.5 discuss how to estimate utility costs, fees and routine maintenance and repair costs. In locations where almost all housing is owned rather than rented, finding representative rental costs is difficult. In this case, the user cost of owner-occupied housing is estimated and used as a proxy for rental cost (Section 6.6).

## 6.1.1  Locations to visit

Collection of information on rents should focus on areas where workers typically live. To help locate suitable areas to visit, it is very useful to have a map of the study area that indicates where factories or farms are concentrated as well as where workers typically live. One could start with a published map, or a map downloaded from the web, or a freehand drawn map. Based on discussions with knowledgeable persons, locations of interest such as farms and factories should be marked on the map along with notable roads, towns, landmarks, and markets. In urban areas, key characteristics of neighborhoods should be indicated such as whether they are expensive or unsafe or a slum since slums and unsafe neighborhoods are not acceptable for decent housing and housing in expensive neighborhoods is too costly.1 It is also best to avoid neighborhoods that are far away from workplaces and so require an inordinately long commute. Figure 6.1 provides an example of a map of areas in Shenzhen, China that was used for a living wage study that focused on electronics factories in Shenzhen. Notice that factories and the areas where workers live were concentrated in the outskirts of Shenzhen where costs were lower than in the center of the city.

Notes: Stars indicate areas with a concentration of electronics factories. Star 1 represents an area with small electronics factories. Star 2 represents Guanlan Science and Technology Park (in Guanlan town). Star 3 represents Longhua Science and Technology Park (in Longhua Town). Star 4 represents LED lighting and electronic application factories located in Shangrong Science and Technology Industrial Park in Longgang District.

Source: Wang et al. (2016), base map from Wikimedia Commons (https://commons.wikimedia.org/wiki/File:Administrative_Divisions_of_Shenzhen_City.svg).

Figure 6.1  Districts, industrial bases, and study sites, Shenzhen, China

Maps showing the locations of factories sometimes already exist. For example, an interactive map indicating the number of registered and unregistered garment factories in many areas in the greater Dhaka area of Bangladesh is available from the Stern School of Business (Labowitz and Bauman-Pauly, 2015). This map was used to help select areas to collect information on food prices and housing costs for a living wage study that focused on garment factories in Dhaka.

The map used to select locations does not need to be sophisticated. For the Lake Naivasha area of Kenya where a living wage study focused on fresh cut flower farms, we used a hand-drawn map that indicated the main flower farms and the main communities where workers live (Figure 6.2). In other countries, we have asked local key informants to indicate locations with the highest concentrations of workers on a road map that we purchased. For agricultural products/industries, we have used a map downloaded from the web of areas in a country where the product of focus is grown that we overlaid with locations of farms to help identify and choose representative study locations.

Figure 6.2  Flower farms and townships surrounding Lake Naivasha, Kenya

## 6.1.2  Number of neighborhoods to visit

There is no golden rule as to the number of neighborhoods to visit. This depends partly on time available, heterogeneity of living costs across neighborhoods where workers live, and size of the area covered. For estimating living wages in larger cities, at least three or four different areas should be covered with food and housing costs collected from at least two neighborhoods within each area.

## 6.1.3  Finding rental units to visit that meet the local living wage housing standard

It is often difficult to find basic acceptable rental units to visit, especially when prevailing wages are far below a living wage. In many locations in developing countries, workers’ housing tends to be substandard because this is all that most workers can afford at present. At the same time, there is usually also a market for housing catering to higher income families that is well above the basic but decent housing standard for a living wage. The market for basic rental units that just meets a living wage housing standard is often relatively small when relatively few workers earn a living wage. This means that efficiency in identifying acceptable rental units to visit is required. Otherwise, an inordinate amount of time would be spent visiting housing below (and often well below) the local living wage housing standard.

We have found that the following approaches increase efficiency:

## 6.1.4  Usefulness of visiting range of housing above and below local housing standard

Although we are interested in the cost of renting an acceptable house for a family, it is important to visit a range of dwellings that includes dwellings above and below the local housing standard. This provides a check on the estimated rental cost of acceptable housing, since rent for better and worse housing units bracket rent for acceptable housing units. This is also useful information for explaining to readers the type and the quality of housing workers currently live in.

## 6.1.5  Rural-urban differences

There are usually large differences between rural and urban housing markets and costs. There is often a far greater choice of rentals in urban areas than in rural areas. Indeed, often there is not much of a rental market in rural areas. In addition, acceptable housing standards often differ between rural and urban areas in part because of the higher population density in urban areas.

## 6.1.6  Data collection form for rental units

Table 6.1 is an example of a data collection form that can be used to collect local housing information. Data collected are used in several ways: (1) to determine whether or not a dwelling visited meets the local housing standard; (2) to estimate the cost of acceptable housing; and (3) to estimate the cost of utilities such as electricity, water, and cooking fuel, as well as other costs associated with renting a dwelling such as fees and taxes. As with all forms provided in this manual, this form should be adapted to local conditions.

Table 6.1  Example of data collection form for rental units

 Neighborhood Town/city/place Approximate distance and time from workplace Travel method and cost of one-way transport to workplace Is neighborhood a slum? Safety of neighborhood? (very safe, somewhat safe, unsafe?) Indicate environmental problems (e.g. street lights, drainage, sewage, garbage, etc.) Name of person/family (optional) Address Indicate if OWNED, RENTED or PROVIDED FREE Type of dwelling: flat, independent house, single room, etc. Total number of residents in dwelling Number of adults Number of children Material of dwelling Walls Roof Floor Condition of walls, floor roof, foundation (e.g. roof leaks, mold, etc.) Condition of walls Condition of roof Condition of floor Indicate if height of ceiling is less than 2 meters # Windows in dwelling Ventilation quality of dwelling (poor, fair, good, very good) Size of dwelling Total approximate number of square meters of living space Total # rooms # separate bedrooms # separate living/dining rooms If separate kitchen room inside? (yes or no) If proper ventilation of smoke from cooking? (yes or no) Is cooking done outside house? (yes or no) Amenities Electricity? (hours per day) Source of water Separate source of drinking water? If so specify Piped indoor water? (yes or no) If no indoor water: distance to water Number days per week water available How water stored (e.g. open or closed vessel, tank, jerry can, etc.) Toilet: pit, flush, or _____? (indicate) Toilet: inside or outside? (indicate) Condition of toilet (very good, good, fair, poor) If toilet fair or poor: Explain e.g. smell, drainage, building condition, etc. General condition of dwelling (very good, good, fair, poor) If condition fair or poor: Explain Consumer durables (yes or no) Refrigerator Motorbike Cost per month (indicate total cost of dwelling even if cost is shared with others) Rent per month Electricity cost per month (0 if included in rent) Water cost per month (0 if included in rent) Cooking fuel cost per month (0 if included in rent) Heating fuel: Number of months needed (0 if included in rent) (When used) Cost of heating fuel per month Other costs per month including fees and taxes (indicate type & amount) Investigator’s opinion: Does house meet acceptable standards for location? (yes or no) If no: Indicate reasons why not acceptable

## 6.2.1  Table with local rental cost data

The easiest and most effective way to analyze and present data collected in a local housing survey is to create a table with each housing unit listed in a separate row in ascending order of their rent (see Table 6.2). Variables to describe each housing unit include: (i) whether visited; (ii) whether acceptable and meets or exceeds the local housing standard; (iii) rent per month; (iv) utility costs, fees, and other costs per month; (v) key characteristics such as walls, floor and roof; (vi) size in square meters and number and types of rooms; and (vii) comments. The comments column should indicate reasons why the dwelling was found to be unacceptable or acceptable and what the housing unit was like. Why rent may have been unusually high or unusually low might also be indicated (e.g. landlord was a relative, or rent had not changed in a long time). In this way, the type of housing available at different rents is clearly displayed and it is possible to see what rents are for dwellings below the housing standard, similar to the housing standard, and above the standard.

## 6.2.2  Photos of local housing

We have found it very effective and informative to include photos of local housing in living wage reports – photos of both unacceptable housing and basic acceptable housing. Photos provide a visual perspective and are easy to understand and especially useful for international readers who have little or no familiarity with local conditions. Photos can be especially effective in communicating when many workers currently live in poor housing and the basic nature of the local housing standard.

## 6.2.3  Example: Table presenting local rental costs for rural Dominican Republic

Table 6.2 lists rent from 14 rental units we visited in rural Dominican Republic. We concluded that acceptable housing rented for around RD$2,000 per month (although one of the lessons we learned from this pilot study is that we should have included more time for fieldwork). Although two acceptable units rented for RD$1,500, each of these had a reason for exceptionally low rent (one was rented from a relative; rent for the other was expected to increase soon). Otherwise, we did not find other acceptable units except ones that were much more expensive. Based on this information, we concluded that rent for acceptable housing was above RD$1,500. At the same time, it was clear that RD$3,000 per month was too high, since dwellings well above the local housing standard rented for this amount. In this case, we decided to set rent for basic acceptable housing at a conservative RD$2,000 per month. This was on the lower side between the RD$1,500 which was known to be too low, and the RD$3,000 which was known to be too high. This rent was cross-checked with information from banana plantations on the cost of building and maintaining basic acceptable housing for families. It was noted in our living wage report that RD$2,000 per month was approximately two to three times the rent for one small room.

Table 6.2  Cost of rented housing units visited, rural Dominican Republic

Notes: LR indicates living room. BR indicates bedroom. K indicates kitchen.

## 6.2.4  Estimating rent for an acceptable dwelling using rent per square meter

Since rent is related to dwelling size, it is possible to estimate rent for an acceptable dwelling from the rent of dwellings of various sizes using observed rent per square meter. Regressing rent (dependent variable) on number of square meters of floor space (independent variable) will indicate whether this relationship is linear or non-linear (such as log linear or quadratic).

Our experience is that the relationship between rent and amount of living space is more or less linear (i.e. cost per square meter is similar regardless of size of dwelling, and so twice as much space costs twice as much money) in places where workers rent one bare room without indoor amenities such as piped water, toilet, or kitchen with chimney (see Kenya example below), and non-linear (i.e. cost per square meter falls with size) when even small dwelling units include such amenities because the cost of these amenities is in a sense defrayed over a larger floor space (see Vietnam example below).

This method can provide useful information especially in locations where there are not many rental properties that just meet the local housing standard, but there are many rental properties with required amenities that are too small or too large. Regression results should not be used as a substitute for reported rents in locations where rental properties that are similar to the local housing standard can be found.

6.2.4.1 Example: Using rent per square meter in rental cost estimate for a second tier city in Vietnam Figure 6.3 provides an example of a non-linear relationship between rent per square meter and house size for houses in a second tier city in Vietnam where most housing has basic amenities of piped water, toilet, and separate kitchen. A log function reasonably represents the relationship between monthly rent (y axis) and size of housing unit in square meters (x axis), with rent per square meter decreasing with house size. Based on this relationship, rent for a housing unit with 36 square meters would cost VND939,637 (VND26,101 per square meter derived from regression multiplied by 36 square meters). Note that if one were interested in rent for units with 50 square meters, there would be no need for regression analysis, because a number of units with 50 square meters were observed.

Figure 6.3  Rent per square meter as function of number of square meters for housing that meets all other characteristics of acceptable housing, tier two city in Vietnam

## 6.2.5  Example: Estimate of rental cost in non-metropolitan urban Kenya

Table 6.3 includes results from our living wage local housing market survey for Lake Naivasha supplemented by a recent survey of available housing done by the workers’ welfare committee from a large flower farm. Housing units for most workers consisted of one bare room without kitchen facilities, indoor water, or indoor toilet that was rented by a migrant worker living without his or her family. It was clear that the cost of acceptable housing was more than KSh4,000 per month, since none of the housing units visited with a rent below KSh4,000 were acceptable. At the same time, housing units visited with rent of KSh8,000 or above were more than acceptable. Therefore, rent for basic acceptable housing appeared to be between KSh4,000 and KSh8,000 per month.

To help determine where in the KSh4,000–8,000 range the cost of acceptable basic housing might be, we estimated that rent for the minimum 30–36 square meters required for decency in this location for a family to be around KSh5,400 by extrapolation. KSh5,400 was roughly three times the rent for a 10 feet by 10 feet room (i.e. 3 × KSh1,800) and around 1.5 times rent for two rooms with around 20 square meters of living space (i.e. 1.5 × KSh3,000–4,000). KSh5,400 was felt to be a very conservative estimate of rent for acceptable housing, since while this amount would be enough to rent housing with sufficient space, this space would not include a separate kitchen area with a chimney.

## 6.3  Asking Workers How Much They Think Rent is for Housing Similar to the Local Housing Standard

Statistical offices and researchers sometimes ask people how much they think it would cost to rent housing with particular characteristics. This includes asking home owners how much their house would rent for if it were rented out. In our case, people could be asked how much rent would be for housing that meets the local housing standard. This is a controversial approach to estimating rental costs, because the extent to which people provide reasonable answers varies greatly by country and location, and how questions are asked. Our experience in a number of countries is that this is not a good approach in locations where there is a small rental market for housing that just meets the local living wage housing standard. We have been struck by how variable and often inaccurate people’s perceptions of rental costs are in different countries. Statistics South Africa (2008), also found that persons owning a dwelling had ‘difficulty’ in providing ‘a reliable estimate of the market value of their property.’ On the other hand, recent living wage studies for cities in Brazil and China, where rental markets are well developed found it useful to ask workers about likely rent for basic acceptable housing (Barbosa et al., 2016, Wang et al., 2016). In short, while this approach can be used, this should be done cautiously and in any case restricted to locations with a well-developed housing market for basic acceptable housing.

Table 6.3  Cost of rented housing units visited, Lake Naivasha Kenya

Notes:

a  Unless otherwise indicated, dwellings: (i) were located in urban townships near large flower farms; (ii) did not have indoor water; (iii) water needed to be boiled for drinking; (iv) cooking was done indoors without a chimney using small charcoal stove; and (v) shared pit toilet with concrete slab was of acceptable quality outside house.

b  WWC indicates Workers’ Welfare Committee of a large farm that looked at available housing in the area in the previous year for management.

## 6.4  Utility and Other Housing Costs

Utility costs and other housing costs such as taxes and user fees are an important part of housing costs. Utility costs include water, electricity, cooking fuel, heat, and lighting.

## 6.4.1  Collecting data on utility costs in local housing survey

To calculate utility costs, it is best to collect information on these costs from several sources in addition to the information collected on a local housing survey, since a local housing survey usually covers a relatively small number of houses. In this way, it is possible to estimate utility costs by triangulating between estimates from several sources.

Some utility costs such as water and cooking fuel, increase with family size. To estimate cost per family for water based on data from a local housing survey, it is best to calculate cost per person and multiply this by the reference family size for a living wage. Cost of other utilities, such as heat, electricity, and lighting, which are not as dependent on family size, should be used as reported for the family. Note that when using data on utility costs from a local housing survey, it is necessary to consider the possibility that utility costs indicated by a local housing survey are too low for decency. For example, low wage workers in poor countries might be able to afford only one or two light bulbs and few if any electrical items and for this reason spend very little for electricity; or their landlord might restrict their use of electrical items such as irons that consume a lot of electricity. In these situations, electricity consumption will be below what it would be if a living wage was earned.

## 6.4.2  Secondary data on household expenditure for utilities

Secondary data on the share of household expenditure for utilities from a recent household expenditure survey (or CPI expenditure weights) is a useful source of information. The ratio of the share of household expenditures for utilities to the share of household expenditures for food can be used to estimate utility costs for a living wage by multiplying this ratio by the cost of a living wage model diet. The advantage of these data is that they are based on a large number of households.

## 6.4.4  Drawing together different information on utility costs

Estimates of utility costs from secondary data, a local housing survey, and other sources should be compared. Differences should be examined with reasons for differences considered as the basis for estimating utility costs.

## 6.5  Maintenance and Routine Repair Costs

Every dwelling has expenses for routine maintenance and repairs. How large this cost is for renters depends on responsibilities of renters and landlords for repairs and maintenance, condition of the dwelling, and climate. The cost of improvements should be excluded. Generally, we include nothing or a small amount for renters for repairs and maintenance.

## 6.6  User Cost of Owner-occupied Housing as a Proxy for Rental Cost in Locations, such as Rural Areas, Where There is Little or No Rental Market

Rent for acceptable local housing should be used to estimate housing costs whenever possible based on a local housing survey. This approach is followed because it is difficult and controversial to estimate the cost of housing to home owners and indeed for this reason many national statistical offices use rent to estimate housing costs when estimating CPI.

Unfortunately, this approach may not make sense in locations where not many dwellings are rented. This situation is common in rural areas in developing countries. In such situations, housing cost should be estimated, using what is called the user cost approach.

## 6.6.1  How to estimate user cost per month for local housing

Three approaches (user cost, payment outlays, and acquisition cost) are used by national statistical offices to estimate the cost of owner-occupied housing for estimating CPI (ILO et al., 2004). We use the user cost approach to estimate the rental equivalent value of acceptable owner-occupied housing when there is little or no rental market, as does the International Comparison Program (ICP) of the World Bank to determine parity purchasing parity values (PPP) for countries that lack rental market surveys (Heston, 2013).

The following information is needed to estimate the user cost of owner-occupied housing. It is best to obtain this information from several sources as a way of cross-checking the information.

##### ●  Annual taxes, levies, fees, and house insurance.

The following equation is used to calculate the approximate annual user cost of an acceptable owner-occupied dwelling:2

Annual user cost of owner-occupied dwelling = Construction cost of new house excluding land cost ÷ Expected service life of house3

+ Annual cost for routine maintenance and repairs4

+ Annual taxes, fees, levies, and house insurance5

It is important to note that the above equation does not include the opportunity cost of money tied up in a house (that could earn income through investments elsewhere) or the capital gains from appreciation of housing prices that are often included in the user cost approach (ILO et al., 2004). This is a controversial aspect of the user cost approach (ILO et al., 2004) and is often excluded in practice (Australian Bureau of Statistics, 2010). There are several reasons why we do not include opportunity cost and capital appreciation of owner-occupied housing to estimate the user cost of owner-occupied housing. First, in locations with little or no rental market (the situation in many rural areas in developing countries), where there are ‘limited opportunities for substitution between owner-occupation and renting, it might be argued that the consumption element [of home ownership] dominates’ (ILO et al., 2004, p. 184). Second, the opportunity cost of money tied up in a house and capital gain in the value of a house are counterbalancing (ILO et al., 2004). Third, houses in rural areas in developing countries are often built with considerable free family labor and the value of this labor cannot be easily put into alternative investments. Fourth, including opportunity cost and capital appreciation in an estimate of user cost would mean that this estimate would be very sensitive to uncertain assumptions (especially in areas without well-functioning housing and capital markets) about interest rates and capital appreciation rates, and this is not a good attribute of an estimation method (ILO et al., 2004).

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