The mining sector has been and is one of the main drivers of economic development in Peru, being one of the sectors with the greatest contribution to the Gross Domestic Product (GDP) according to INEI. The objective was to identify which factors in the mining sector have the greatest impact on the country's economic development and influence the national economy. The methodology was non-experimental, quantitative descriptive, through the collection of statistical data, carrying out a detailed analysis of the influence of the mining sector and its repercussions on the axes of poverty reduction, employment generation, tax collection and mining canon. It was concluded that the different investments and the development of mining projects have generated 1.6 million direct and indirect jobs in 2020, it has also promoted growth and development in the different regions, with Ancash and Arequipa being the ones that registered the highest income. between 2011 and 2020 through taxes and royalties. In addition, it contributed to reducing poverty inPeru from 58,7% to 22.2% from 2004 to 2019.

The research design was quantitative with a predictive scope, real information on monthly copper prices since September 2020 was used to August 2022. The models used as time series forecasting methods were moving average forecasting, weighted moving average, simple exponential smoothing, Holt exponential smoothing, and Winters exponential smoothing. The adjustment of the methods to the original model used the coefficient of determination (R2) and the mean absolute percentage error (MAPE) as a measure of precision. The result indicated that the best method is simple exponential smoothing, where the forecast copper price for September 2022 was $3.60/lb, the mean absolute percentage error (MAPE) was 4.4% and the coefficient of determination (R2) was 0.86. Finally, it is concluded that with the time series forecasting methods it is possible to forecast the price of copper.