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All about Preston Curve

5th June, 2024 Economy

All about Preston Curve

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Context

  • When a poor country grows, its per capita income rises and causes an increase in life expectancy.
  • Preston Club was in news.

Preston Curve

  • The Preston curve delineates an empirical cross-sectional correlation between life expectancy and real per capita income.
  • Named after Samuel H. Preston, who introduced it in 1975, based on his analysis spanning the 1900s, 1930s, and the 1960s.

The Relationship Dynamics:

  • Rich-Poor Disparity: Individuals born in wealthier nations generally exhibit longer life expectancies compared to those born in impoverished countries.
  • Diminishing Returns: The link between income and life expectancy showcases a flattening effect. At lower income levels, incremental income growth is associated with substantial increases in life expectancy. However, at higher income levels, the impact of further income growth on life expectancy diminishes.

Interpreting the Dynamics:

  • Causal Interpretation: If interpreted causally, the Preston curve suggests diminishing returns to income concerning life expectancy.
  • Implications: Beyond a certain income threshold, additional income increments yield diminishing marginal benefits to life expectancy, highlighting the complexity of the relationship between income and life span.

Contemporary Relevance:

  • Updated Research: Recent studies have further explored and refined the Preston curve, providing contemporary insights into the dynamics of life expectancy and income correlation.
  • Policy Considerations: Understanding the nuances of this relationship informs policy interventions aimed at addressing disparities in life expectancy and promoting equitable socio-economic development.

Preston Curve

  • The Preston Curve, proposed by American sociologist Samuel H. Preston in 1975, illustrates a significant empirical relationship between a nation's life expectancy and its per capita income.
  • This relationship is foundational in understanding the dynamics of socio-economic development within countries.

Trends in Life Expectancy and Per Capita Income:

  • Historically, as per capita income rises within a country, there is a noticeable increase in life expectancy among its populace. This phenomenon is observable across various nations and over different periods.
  • For instance, in the case of India, from the year 1947 to 2011, there has been a remarkable increase in both average per capita income and average life expectancy.
  • This suggests a correlation between economic growth and improvements in life expectancy, owing to factors such as better access to healthcare, education, sanitation, and nutrition facilitated by increased wealth.

Limitations of the Curve:

  • While the initial stages of economic growth often result in significant gains in life expectancy, the positive correlation between per capita income and life expectancy tends to flatten out beyond a certain point.
  • This implies that the incremental increase in life expectancy diminishes as a country's income level rises further.
  • Such diminishing returns underscore the complexity of the relationship between economic development and health outcomes.

Debate Surrounding Causal Relationship:

  • There exists a robust debate among scholars regarding the causal relationship between economic growth and human development indicators.
  • Some economists advocate for policies aimed at fostering economic growth as a means to improve overall development outcomes.
  • They point to examples like India and China, where rapid economic growth has coincided with notable enhancements in life expectancy and other socio-economic indicators.
  • However, others contend that improvements in life expectancy are not solely driven by increases in per capita income.
  • Instead, they attribute these improvements to public investments in healthcare, education, and technological advancements.
  • Critics of the singular focus on economic growth argue that technological progress and access to life-saving interventions can be achieved even in the absence of significant wealth.

Conclusion:

  • In conclusion, while the Preston Curve provides valuable insights into the relationship between economic development and life expectancy, it also highlights the nuanced nature of this association.
  • Achieving sustainable improvements in life expectancy and other development indicators requires a comprehensive approach that combines economic growth with targeted investments in healthcare, education, and technology.
  • By addressing these multifaceted aspects, nations can strive towards fostering inclusive and sustainable development for all segments of society.

PRACTICE QUESTION

Q. Which of the following best describes the concept of the Preston curve?

a) A theoretical framework for predicting economic growth based on life expectancy.

b) An empirical correlation between population growth and real per capita income.

c) A cross-sectional relationship between life expectancy and real per capita income.

d) A statistical model predicting the impact of inflation on life expectancy.

Correct answer: c) A cross-sectional relationship between life expectancy and real per capita income.