Background
Home > Kenya > Nairobi > Definition of Residential Data Scope for Nairobi

Definition of Residential Data Scope for Nairobi

Clarifying inclusion, exclusion, and interpretive limits of listing-based residential data

Last updated: 2026-01

Purpose of Data Scope Definition

This page defines the scope of residential data used to observe Nairobi’s residential landscape. The objective is to establish clear boundaries around what the dataset represents and, equally important, what it does not represent.

Defining data scope is a methodological requirement. It prevents implicit assumptions about completeness, representativeness, or coverage that listing-based observation cannot support.

Included Observation Layer

The dataset includes residential units that are publicly visible through active listings. Inclusion is determined by publication, not by existence, occupancy, or transaction status.

Only what is observable at the point of publication enters the dataset. Visibility is therefore conditional, episodic, and dependent on listing behavior.

Excluded Residential Segments

Large portions of Nairobi’s residential system are structurally excluded from listing-based observation. These include stable owner-occupied housing, long-term rental arrangements, informally transacted units, and residential areas where public listing is uncommon.

Exclusion does not imply inactivity or insignificance. It reflects the methodological boundary of relying on publication as the sole inclusion criterion.

Non-Representation of Stock and Occupancy

The dataset does not represent total housing stock, unit availability, or occupancy conditions. It also does not track ownership structures or tenure stability.

Observable listings should therefore not be interpreted as a subset of total residential supply. They form a separate visibility layer with its own logic.

Spatial and Temporal Constraints

Spatial coverage is shaped by where listing publication is prevalent. Temporal coverage is shaped by when listings appear, rotate, or are withdrawn.

As a result, both spatial and temporal gaps are inherent features of the dataset rather than data deficiencies.

Interpretive Boundary

This scope definition establishes a boundary between observation and inference. The dataset supports structural description of visibility patterns but does not support conclusions about residential conditions.

All subsequent analysis must be read within this defined scope to avoid overextension of what listing-based data can meaningfully represent.

Frequently Asked Questions

01Does the dataset represent all residential units in Nairobi?

02Are non-listed areas considered inactive or irrelevant?

03Can listing data be treated as a proxy for housing supply?

Related Articles

Comparable markets in East Africa