# 1. Introduction

Private property price levels and their movement over time have critical implications for the economy of most countries, but they also play a fundamental role in household (HH) wealth. Buying property is undoubtedly the most significant investment for many families around the world and reliable information on private property prices and their determinants are essential decision-making factors for HHs. The relationship between property prices and HHs’ disposable incomes determines what type of property HHs can afford. Therefore, from a policy standpoint, reliable property price data are key to understanding the scale of affordability issues and identifying market failures leading to supply-demand mismatches in the housing sector.

House price data also bear key insights on countries’ financial and macroeconomic stability. Disproportionally rising private property prices, or high price-to-income ratios, can be an early indication of imbalances and risks in the financial system (e.g., Anundsen et al. 2016; Drehmann & Juselius 2014). Decreasing house prices, in turn, may be associated with a decrease in HH wealth and a decline in consumption (e.g., Campbell & Coco 2007; Mian et al. 2017). If monitored over time, property prices can function as an early warning system of systemic banking stress or economic downturn. In addition, urban planners, private developers, economists, and policy makers depend on reliable property price data to update zoning regulations, formulate housing policies, and decide how to efficiently allocate scarce resources to support housing solutions where they are needed most.

Despite the importance of property price data for various stakeholders, comprehensive house price data are scarce in developed economies and virtually non-existent for emerging markets and developing economies (EMDEs). If available at all, residential property prices are mostly presented and published in indexed format, allowing to track changes over time; however, indices are not informative to understanding distributional aspects of prices, affordability issues, or the degree of price segments underserved in a market. When housing markets mature, properties' characteristics and attributes may be more stable over time. Hence, changes captured by price indices reflect price movements over a relatively constant set of properties in the market. However, in many EMDEs, there are dynamic changes to the type of properties being built by formal developers. Due to the nascency of markets, formal developers and builders in EMDEs are evolving to expand their portfolio to also cater to housing solutions to HHs with lower or even informal incomes. In such circumstances, aggregate price indices may not be fit for purpose and may suffer from biases due to rapidly changing underlying property types.

The wide gap of publicly available property price data in EMDEs is a key impediment to extending the understanding of housing markets widely available from developed economies to these markets. Insights on the determinants of property prices and their drivers over time are heavily researched subjects, but exclusively rely on studying this dynamic in developed economies. If comparable property price data were available in EMDEs, they could provide crucial insights on potential inefficiencies along the housing value chain. Analyzing property price data in emerging economies can also help, for instance, to point towards constraints in developers’ ability to access finance, prohibitively high construction costs, or regulatory bottlenecks in land acquisition and titling. In addition, property price data in EMDEs can also help point towards affordability issues and potential ramifications on HH consumption and spending. The width of these challenges is often difficult to grasp as the housing value chain is very interconnected and complex, 2