World Economic and Demographic Data

The "World Economic and Demographic Data" database is a comprehensive, integrated data repository designed to gather data from economics, public health, demography, and social sciences. The database consolidates three major categories of country-level data – economic indicators, demographic statistics, and health metrics – spanning multiple years and countries worldwide. It consists of four interrelated tables that maintain the original data structure while enforcing referential integrity through foreign key constraints.

The "World Economic and Demographic Data" database consists of four interrelated tables. The World Country Data table serves as the master reference, storing country codes, country names, and regional grouping information, with a self-referential foreign key to track historical changes in country codes or group affiliations. The Economic table captures annual economic indicators for each country, including GDP, GDP per capita, GDP growth, GNI, trade (imports and exports as percentages of GDP), government debt, and related metrics, with each record uniquely identified by the combination of country code and year. The Demographic Data table provides annual population statistics, such as total, male, and female populations (in thousands), population density, sex ratio, median age, rate of natural change, population change, and population growth rate, also keyed by country code and year. The Health Data table contains annual public health indicators, including fertility rate, life expectancy at birth, crude death and birth rates, net migration, current health expenditure as a percentage of GDP, hospital beds per 1,000 people, DPT immunization coverage, and HIV incidence, again uniquely identified by country code and year. Together, these four tables are linked through foreign key constraints on country code, ensuring referential integrity and enabling integrated cross-domain analysis across economics, demography, and public health.

This database design enables researchers to conduct complex cross-sectional and longitudinal analyses, such as examining the relationship between GDP growth and life expectancy, analyzing how population density correlates with healthcare expenditure, or investigating the impact of trade policies on demographic transitions. The structured relational model ensures data integrity, eliminates redundancy, and supports efficient querying across all three data domains.