Purpose of Explaining Data Exclusion
This page explains the logic by which certain residential segments are excluded or omitted from the listing-based dataset used for Addis Ababa. The objective is to clarify that absence from the dataset is a structural outcome of data construction rather than a statement about residential reality.
Exclusion and omission are treated here as inherent properties of observability, not as errors or deficiencies to be corrected.
Structural Sources of Exclusion
Residential listing datasets are constructed from properties that become visible through specific platforms at a given point in time. Any residential segment that does not pass through these publication channels is structurally excluded.
This includes housing that is not actively marketed, exchanged through informal networks, occupied without turnover, or represented outside digital or intermediary systems.
Omission as a Function of Dataset Design
Omission arises not only from lack of listing activity, but also from dataset design choices that define scope and eligibility. Geographic boundaries, residential definitions, and platform selection all shape which properties can appear.
As a result, omission should be understood as a predictable outcome of how the dataset is constructed, rather than as missing data that could be inferred or approximated.
Interpretive Implications
Excluded residential segments cannot be indirectly reconstructed, estimated, or inferred from the visible data. Their absence places firm limits on aggregation, generalization, and extrapolation.
This logic establishes a clear boundary: listing-based data describes only what is visible within its defined scope and remains silent on all structurally omitted residential contexts.