Abstract
AbstractThis paper discusses the use of the OECD’s framework to identify early warning indicators for building a Composite Leading Indicator (CLI) and the use of the Vector Autoregressive Model (VAR) for constructing a short-term forecasting model of economic growth of Hong Kong. With the onset of the COVID-19 pandemic, this paper further evaluates the performance of the CLI and forecasting model which were built based on pre-COVID-19 parameters and identify further adjustments to enhance the model performance.
Publisher
Springer Science and Business Media LLC
Reference27 articles.
1. Aldasoro, I., Borio, C., & Drehmann, M. (2018). Early warning indicators of banking crises: Expanding the family. Bank for International Settlements Quarterly Review (March), 29–45.
2. Angelini, E., Camba-Mendez, G., Giannone, D., Reichlin, L., & Rustler, G. (2008). Short-term forecasts of euro area GDP growth. European Central Bank Working Paper 949, 1–31.
3. Bobeica, E., & Hartwig, B. (2021). The COVID-19 shock and challenges for time series models. European Central Bank Working Paper 2558, 1–41.
4. Bry, G., & Boschan, C. (1971). Cyclical analysis of time series: Selected procedures and compute programs. NBER.
5. Cerqueira, V., Torgo, L., & Mozetič, I. (2020). Evaluating time series forecasting models: An empirical study on performance estimation methods. Machine Learning, 109, 1997–2028.