Unit 4 - Essays - DTM Flashcards
(1 cards)
With the aid of examples, assess the extent to which the demographic transition model (DTM) is useful in predicting population growth in LICs/MICs
Paragraph 1 – DTM is useful for general pattern recognition (e.g., India)
The DTM helps predict broad trends—e.g., high growth in Stages 2/3, slower growth in Stage 4
India: classic Stage 3–4 transition, with growth slowing due to urbanisation, education, and family planning
Fertility fell to ~2.0; growth dropped from 2.3% (1970s) to 0.8% (2020s)
Useful for planning: housing, food, healthcare, and infrastructure
Paragraph 2 – DTM has comparative value but assumes linear, Eurocentric path
DTM assumes all countries pass through stages similarly, based on Western industrialisation
LICs like Sudan and South Sudan do not follow this path—conflict, aid reliance, and displacement dominate trends
South Sudan: over 5.0 fertility rate, war, and humanitarian crisis keep it stuck between Stages 2/3
Paragraph 3 – External factors and policy not included in the model
DTM does not account for war, famine, refugee movements, or global aid flows
South Sudan: spikes in mortality, displacement disrupt standard progression
Government policies (e.g. India’s family planning) can rapidly alter birth rates, not shown in the model
Urban slums: high fertility persists despite urbanisation
Paragraph 4 – Spatial and social variation weakens DTM’s predictive value
Within countries, DTM stages vary: India’s Kerala (Stage 4) vs. Bihar (Stage 2/3)
Urban–rural splits: urban areas may show falling fertility while rural areas remain high
DTM oversimplifies complex demographic diversity across LICs/MICs
Conclusion – Judgement
The DTM is a useful starting point for understanding and predicting broad trends in LICs/MICs, especially MICs like India.
However, its predictive power is limited in LICs due to non-linear development, conflict, migration, and policy interventions.
Therefore, it should be used with caution, and always alongside context-specific data.
