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Data · dataset · 2025

G²LM|LIC - Female Wage Labor and Fertility - Evidence from the Cut-Flower Industry in Kenya

Listed in IDSC Dataverse

This study examines how the emergence and expansion of the cut-flower export industry in Kenya—particularly rose-growing greenhouses employing predominantly low-skilled women—affects female labour market participation and fertility outcomes.

Description

The project constructs a new geospatial database documenting the timing, location, and growth of flower-processing plants from 1999–2022 using historic satellite imagery, phone verification, and customs records.

These data are linked to multiple rounds of household surveys, DHS birth histories, and population censuses to estimate how new wage opportunities for women shape employment patterns and fertility decisions. The empirical strategy follows a staggered difference-in-differences design comparing treated villages to geographically suitable control locations. The resulting database provides the first systematic mapping of Kenya’s rose-greenhouse expansion and supports research on structural transformation, gender, and demographic change in sub-Saharan Africa.

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Data Description The dataset contains a time series documenting the expansion of the Kenyan cut-flower industry at the county level. For each year from 1999 to 2022, it records the number of identifiable greenhouses and total greenhouse area based on satellite imagery and auxiliary sources. The dataset captures greenhouse-based export production, predominantly roses.

Open-field production (e.g. summer flowers) is not systematically measurable from satellite imagery and is therefore outside the main scope. Scope

Note

This dataset records the expansion of greenhouse-based rose farms only. Summer-flower production or non-greenhouse fields cannot be reliably detected and are not included. The time series begins in 1999 because earlier satellite images are of insufficient quality to identify structures consistently.

Variables county — county name year — calendar year gh_numn_greenhouses — number of flower growing greenhouses gh_area — total greenhouse area

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Where it is published

Catalogue records · 1

Topics

Stated by source
Social Sciences
Inferred from text
Image 65% · Satellite remote sensing 65%
Provenance · 1 source records, 12 field assertions
SourceKeyLast seenRaw
IDSC Dataversedoi:10.15185/glmlic.815.15 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:field:440302mapping · dataverse iza orgvocabulary-mapper@1.0.0keywords['Fertility']
concepts[field].dataverse_subject:social-sciencessource · dataverse iza orgconnector:dataverse_iza_org@1.0.0/subjects
concepts[field].local:field:engineeringmapping · dataverse iza orgconnector:dataverse_iza_org@1.0.0/subjects
concepts[field].local:field:social-sciencemapping · dataverse iza orgconnector:dataverse_iza_org@1.0.0/subjects
concepts[modality].local:modality:imageenrichment · dataverse iza orgkeyword-concept-rules@1.0.0title+description (65%)
concepts[modality].local:modality:remote-sensingenrichment · dataverse iza orgkeyword-concept-rules@1.0.0title+description (65%)
created_datesource · dataverse iza orgconnector:dataverse_iza_org@1.0.0
descriptionsource · dataverse iza orgconnector:dataverse_iza_org@1.0.0/description
publication_datesource · dataverse iza orgconnector:dataverse_iza_org@1.0.0
titlesource · dataverse iza orgconnector:dataverse_iza_org@1.0.0/name
updated_datesource · dataverse iza orgconnector:dataverse_iza_org@1.0.0
version_labelsource · dataverse iza orgconnector:dataverse_iza_org@1.0.0