unaffordable housing if their actual residual (non-housing) expenditures are lower than the monetary resources needed to achieve a minimum standard of living based on non-housing needs.

**_Obtaining the non-housing consumption aggregate_** . The REM estimates the non-housing expenditure aggregate in a direct manner by summing reported expenditures on non-housing items. Housing-related expenditures, which are excluded from the aggregate, include rental payments (actual and imputed) as well as electricity, water, maintenance, fuel and waste collection.

**_Estimating the minimum standard for non-housing expenditures_** . The CBN methodology, which the Government of Pakistan used to establish the national poverty line for 2013-14, is followed. As a first step, the food poverty line is estimated. This is the minimum expenditure required to fulfill basic food requirements for a particular reference group. This reflects the cost of a basic food basket that meets the minimum daily caloric requirement, using food items, quantities, and prices faced by the reference group (see below). In the case of Pakistan, the minimum daily standard has been set at 2350 calories per adult equivalent. Second, the total non-housing basic needs are estimated by scaling up the food poverty line. This is indirectly accomplished by estimating the food share of the total non-housing budget for households whose food expenditure is close to the food poverty line. This share, or scaling factor, is used to inflate the food poverty line to obtain the basic minimum threshold of total (food and non-food) non-housing expenditures.

Application of the REM in Urban Pakistan revealed that 25.2 percent of households cannot meet their basic needs _and_ pay for housing, and that housing poverty is concentrated among the bottom 40 percent of the income distribution where more than half of households cannot meet basic needs _and_ pay for housing (Table 1). Nearly all (93.7 percent) of those in the bottom quintile are housing poor, and the housing unaffordability rate decreases as household income rises. Using the conventional EIR approach, and adopting 30 percent as the threshold; however, housing is unaffordable for a larger share of households (43.9 percent), and higher-income groups have more affordability challenges. This highlights one of the main shortcomings of the ratio method: it fails to account for the fact that the well-off can afford to spend a larger proportion of their overall expenditure on housing, even after paying for basic needs. Conversely, people at the bottom end of the expenditure spectrum struggle with meeting their basic needs, even if they spend less than 30 percent of their expenditure on housing.

**Table 1. Share of Urban Households in Unaffordable Housing as Measured by REM and EIR**

|**Urban Welfare Quintiles**|**Housing Poverty - REM (%)**|**Unaffordability - EIR (%)**|
|---|---|---|
|All Pakistan|25.2|43.9|
|Q1 (lowest)|93.7|28.1|
|Q2|29.3|35.6|
|Q3|2.6|44.3|
|Q4|0.6|52.0|
|Q5 (highest)|0|59.6|

Note: Sample restricted to urban areas only. Source: Authors’ calculations based HIES 2018-19 microdata.

The REM applied in Pakistan is adapted from the traditional RIM in two ways: (i) expenditure data is used instead of income, and (ii) a non-housing expenditure threshold was derived from HIES data instead of 16