Modelos econométricos de predicción macroeconómica: caso Ecuador período 1980 - 2015

Abstract

Abstract:The GDP is an indicator of the health of the economy that serves as a basis to establish and planning economic development, it is therefore essential to examine the impact it has on a country; this is achieved thanks to the analysis of forecasts obtained with time series modeling techniques. This work focuses on the analysis of the prediction of economic growth for the years 2016 and 2017 in Ecuador, obtained from the historical data of the period 1980 - 2015, for which two time series methodologies were used: integrated autoregressive model of moving averages (ARIMA) and autoregressive vectors (VAR). The final objective is to determine which of the two proposed models presents the best predictive performance, obtaining in this way empirical evidence that can be used to make economic policy decisions.