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From Wikipedia, the free encyclopedia

Gridded GDP Density of the World 1990 and 2025

GDP density is a measure of economic activity by area. It is expressed as gross domestic product per square kilometer and can be calculated by multiplying GDP per capita of an area by the population density of that area. Amongst other uses it demonstrates the effects of geography on economy.[1]

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GDP Density

What is GDP density

GDP density refers to the distribution or intensity of Gross Domestic Product (GDP) within a particular area or population. GDP density could be interpreted as a measure of economic activity or output relative to the size of a region or population, often expressed as GDP per capita or GDP per unit of area.

GDP per capita

The GDP per capita is a commonly utilized indicator to assess a nation's economic performance. It is calculated by dividing the total value of products and services produced in a nation during a given time period by the average population of that nation.[2] This measure, which is frequently used to compare the economic success of various countries, sheds light on the average economic output per person in a specific nation. GDP per capita typically denotes a higher standard of life because it shows that the nation's citizens have more resources and GDP density

GDP per unit area

GDP per unit area refers to the geographical distribution of Gross Domestic Product within a country. It analyzes how economic output is spread across different regions, provinces, states, or territories within a nation. Understanding GDP geographic distribution is essential for policymakers, businesses, and researchers as it provides insights into regional disparities in economic development and helps identify areas that may require targeted interventions or investment. Policymakers can identify economically underperforming regions and may need to implement tailored policies to promote growth and development by analyzing the geographic distribution of GDP. By identifying the areas of concentrated economic activity, it also assists firms in making well-informed decisions regarding the allocation of resources and market prospects. Additionally, trends of urbanization, economic resiliency, and regional growth are studied by scholars using geographic GDP density data.

Fluctuations in GDP density

Academic discussions have highlighted two significant reasons why typical households might not benefit proportionally from economic growth. These reasons revolve around discrepancies between GDP per capita and median household income, shedding light on challenges in accurately measuring and interpreting economic indicators.[2] The first reason centers on differences in measurement between GDP per capita, derived from national accounts, and median household income, based on household surveys. Despite efforts by organizations like the OECD and EU to align income measures with national accounts concepts, disparities persist due to methodological variations and mismeasurement. Empirical studies reveal substantial disparities between mean per capita income from national accounts and household surveys across various countries. The second reason gaining attention is the widening income inequality, where a significant portion of national income growth concentrates at the top of the income distribution. This trend results in minimal increases in the median income. Empirical studies, primarily focused on countries like the USA and the UK, underscore the impact of income inequality on household income dynamics.

Effect on poverty levels

Geographical detectors have been used, especially in rural poverty contexts, to systematically measure the individual and interacting influences of numerous factors on changes in GDP density. This investigation has found the ideal qualities of important variables that support GDP density growth.[3] Furthermore, a better comprehension of the GDP density differentiation mechanism in rural poverty has been gained. Sufficient reasons for changes in GDP density in rural poverty have been established, based on variables like elevation, average yearly temperature, land use, normalized differential vegetation index (NDVI), and distance to main roadways. Crucially, it has been noted that these impact factors have interactive impacts on GDP density, with synergistic effects frequently producing nonlinear consequences and mutual enhancement.

References

  1. ^ "Gallup J. L., Sachs J. D., and Mellinger A. D. (1999): GEOGRAPHY AND ECONOMIC DEVELOPMENT" (PDF). Archived from the original (PDF) on 2007-06-09. Retrieved 2007-04-13.
  2. ^ a b Nolan, Brian; Roser, Max; Thewissen, Stefan (September 2019). "GDP Per Capita Versus Median Household Income: What Gives Rise to the Divergence Over Time and how does this Vary Across OECD Countries?". Review of Income and Wealth. 65 (3): 465–494. doi:10.1111/roiw.12362. ISSN 0034-6586 – via Business Source Ultimate.
  3. ^ Wang, Guangjie; Peng, Wenfu (March 2021). "Detecting influences of factors on GDP density differentiation of rural poverty changes". Structural Change and Economic Dynamics. 56: 141–151. doi:10.1016/j.strueco.2020.10.004.


This page was last edited on 25 April 2024, at 07:09
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