Economic Variables

Economic forecasting using big data analytics, the goal is to predict the future performance of an economy by leveraging large-scale datasets and advanced analytical methods. Key variables used to represent the economy in this research include Gross Domestic Product (GDP), GDP Growth Rate, and Price Inflation Rate. These indicators provide a holistic view of the economic health, enabling more accurate forecasting models.

GDP serves as the broadest measure of a country’s economic activity, reflecting the total market value of goods and services produced within a country. GDP growth rate represents the change in GDP over a given period, indicating the pace of economic expansion or contraction. Price inflation rate is crucial for measuring the increase in general price levels over time, which impacts consumer purchasing power and overall economic stability.

The dataset used for such research typically comprises large, longitudinal data that includes historical records of the selected economic indicators. It would include:

GDP Data: Time series data representing the total value of goods and services produced in a country or region over multiple years.
GDP Growth Rate Data: Annual or quarterly changes in GDP, allowing analysis of how quickly the economy is growing or shrinking over time.
Price Inflation Rate Data: Data on the percentage increase in the average price level of goods and services over time, often derived from consumer price indexes (CPI).
The dataset may also include supplementary factors such as interest rates, unemployment rates, trade balances, and government spending, which can further enhance the model’s predictive capabilities. The data is typically gathered from reliable sources like national statistics agencies, the World Bank, IMF, or OECD.