A carregar...
Publicação
Accessing the impact of COVID-19 on the Portuguese unemployment rate
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 1.94 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
We analyze the possibility of Vector Autoregressive models being good estimators for the
unemployment rate in Portugal, by studying their ability to understand the impact the COVID-19
pandemic had on the unemployment rate. We make use of Bayesen Stochastic Search Variable
Selection and bootstrapping techniques for forecasting, comparing the results of these models
with two benchmark techniques, ARIMA and Artificial Neural Networks. The model performance
is tested through the RMSE, MSE and MAE of the estimations, and we compare the forecasting
quality through a Diebold-Mariano test. We conclude that the VAR methodology can provide
better forecasts than the benchmark models when combined with the Bayesian approach, both
for shorter and longer forecasting horizons. We also conclude that COVID-19 did not provide the
expected shock to the Portuguese unemployment rate.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
Palavras-chave
COVID-19 unemployment vector autoregressive models forecasting