Inflação de alimentos, transporte e habitação: uma análise dinâmica de 2000 à 2023

Abstract

This thesis work is an analysis of the time series of price variations in Food, Transportation, and Housing, spanning from 2000 to 2023. The main objective is to comprehend the peaks and fluctuations observed in these indicators over the years. To achieve this, a methodology was followed, including an exploratory analysis of the main series. A graph was plotted to understand the series behavior, followed by a stationarity test and decomposition via SEATS to identify seasonalities. Additionally, modeling was performed using a SARIMA (Seasonal AutoRegressive Integrated Moving Average) model. Furthermore, the quality of the SARIMA model residuals was assessed to ensure they adhered to statistical assumptions. The study also incorporated exogenous variables such as exchange rate, wheat quotation, oil quotation, meat quotation, and total public debt to explore their influence on the variation in prices of Food, Transportation, and Housing. However, comparative analysis indicated that the SARIMA model outperformed the Temporal Linear Regression model in capturing the peaks and troughs of the series, suggesting that the series itself is more effective in explaining the fluctuations than the external factors used in the analysis. Overall, the work provides interesting insights into the dynamics of these indicators over the years, offering an analysis of the underlying trends and patterns that shaped the price variations in Food, Transportation, and Housing during the study period.