Following extensive reading of research on the affordable housing sector in emerging markets and the availability of mortgage financing in the region – despite the chronic need for quality affordable housing in the region, the research to date is scarce… let alone a scalable, suitable and effective initiative. This is a complex area for research in bringing together policy, private sector funding, real estate market dynamics, town planning and suitable financing, and as a backdrop, developing the suitable legal framework from a capital markets, property rights and infrastructure perspective to facilitate the necessary investment.
Acknowledging the depth and multidisciplinary nature of addressing the affordable housing sector in Central America – a basic analysis on the feasibility of commercial mortgage financing is undertaken with reference to commercially available financing and income distribution.
“Cities are built the way they are financed” — B. Renaud
Access to credit and issues around the notion of financial inclusion in emerging markets are often cited as impediments to development among bottom of the pyramid populations. Despite the sheer number of this population, the formal financial sector has been unable to adequately make an impact in addressing this customer segment through suitable product design and associated education.
As discussed in an earlier post, bankarisation rates in Central America are low – 36.7% in Guatemala, 45.2% in Honduras and 40.4% in El Salvador (Financial Access Survey, IMF – 2013). In this post – the relationship between bankarisation and insurance was analysed, and per the findings of Badev, Beck, Vado and Walley (2014) there is a strong correlation between the development of insurance and equities markets and mortgage market development, as opposed to a strong relationship with government subsidies.
Looking at the feasibility of existing mortgage funding on a purely statistical basis given the income distribution by quintile also reveals some interesting affordability (rather, lack thereof) analysis. Data has been sourced from the World Bank World Development Indicators database on income distribution and population metrics, with monetary amounts denominated in USD across all countries. In deriving the per capita monetary amounts, an adjustment on the denominator (population) has been made to only include the population aged between 15-64 years, assuming 100% of the population in this age bracket rather than adjusting again for employment and participation rates. To get a sense of a per day income, the data is then provided on a ‘per day’ basis.
The disparity between first and fifth quintiles is huge – the top 20% earns a whopping 23.5x more than the bottom 20% in Honduras, 14.8x in Guatemala and 8.8x in El Salvador.
However, income inequality is not the focus of this post albeit worthy of future analysis. It does, however, dictate affordability of many things including mortgage financing (and access thereto).
In determining the ability of each quintile to fund a mortgage, data on lending rates has been collected from the IMF database in the case of Honduras and Guatemala, and the Central Bank of El Salvador in the case of El Salvador. Note that El Salvador is a dollarized monetary system and accordingly imputes USD monetary policy – Honduran and Guatemalan lending rates reflect local currency denominated lending. In the region, mortgages are typically granted for a period of 15 years. Whilst these data points were fairly straightforward to collect – data on average house prices was difficult, particularly sourcing specific affordable housing prices; furthermore regional pricing would further undermine relevance of any ‘average pricing’ used in the analysis. Noting that whilst construction and labour costs in the region are relatively low, land prices vary significantly between regions and the added cost of servicing land (water, utilities) is elevated in remote areas, which is typically imputed into housing prices. With this in mind, a ‘guesstimate’ figure of USD10,000 for an ‘affordable house’ has been used in the analysis on mortgage affordability across the income quintiles.
Across all three countries, the average house price of USD10,000 has been used, with an LTV of 80% and therefore a mortgage amount of USD8,000; typically, ‘safe lending’ policies focus on mortgage repayments not exceeding 40% of gross income. Based on a 15 year mortgage with monthly payments, the analysis is as follows – with red indicating that mortgage funding costs exceed this 40% ‘safe lending’ range:
Accordingly – without regard to regional differences, subsidies, household formation, bankarization and other distortions in the funding and residential real estate markets, on a purely mathematical basis, a large proportion of the population in the region is not positioned to access mortgage funding to acquire their own residence, and are therefore subject to fluctuations in the rental market and potentially substandard accommodation given landlord reluctance to invest in upgrades. Whilst these conditions persist mortgage penetration will remain low as only the top percentage of the population will be able to access financing – current mortgage penetration in Guatemala and El Salvador is estimated at only 1.3% and 2.4% respectively.
In developed mortgage markets, typically longer duration mortgages improve affordability. However as noted in of Badev, Beck, Vado and Walley (2014), in emerging markets, given elevated funding costs, longer duration does not have a meaningful impact on reducing repayments and thus improving affordability.
The more pronounced the income inequality, the more pronounced the inequality of opportunity – this is particularly pronounced in access to financial services and even more so in housing which is targeted towards lower income populations, yet still out of reach. With the development of capital markets comes an improved access to financial services to support consumption, albeit in the region this is of course yet to be initiated in a meaningful way on a meaningful scale…
Postscript – this research has been inspired by the paper : Housing Finance Across Countries: New data and analysis, January 2014, World Bank Policy Research Working Paper 6756