Thesis
Essays in macroeconomic interdependence, business cycles and nowcasting in a multi-country context
- Creator
- Rights statement
- Awarding institution
- University of Strathclyde
- Date of award
- 2024
- Thesis identifier
- T16821
- Person Identifier (Local)
- 201984442
- Qualification Level
- Qualification Name
- Department, School or Faculty
- Abstract
- This thesis employs a multi-country approach and builds upon the existing literature on the Bayesian Panel Vector Autoregressions (PVARs) as its foundationfor analysing empirical macroeconomic interdependence, business cycles synchronisation and economic forecasting. The contribution is provided in three essays.The first essay (Chapter 2) examines macroeconomic interdependency of mainmacroeconomic variables in terms of dynamic, static, and cross-sectional homogeneity features by using a PVAR model. In order to accurately measure thesefeatures, a stochastic search specification selection (S4) prior algorithm is employed to investigate their interdependencies within the G-7 countries. The results indicate that while cross-sectional homogeneity is of little significance amongthe G-7, dynamic and static interdependencies are of great importance. In brief,the S4 algorithm is beneficial for classifying each type of the panel structure ofmacro-financial interlinkages. This essay also compares the inflation forecasting performance of the S4 algorithm with the original factor shrinkage prior ofCanova and Ciccarelli (2009) and finds that the PVARs with the S4 algorithmgive a better point forecasting performance, particularly in the short-term forecasthorizons. Regarding the density forecasts, the PVARs with the S4 prior outperform the PVARs with the factor shrinkage prior for all the G-7 in the short-termhorizons, whereas in the long-term horizons, although the PVARs with the factorshrinkage prior give an improved performance, they still only forecast better fortwo of the seven countries, namely Canada and Japan.The second essay (Chapter 3) investigates the economic interdependencies between the ASEAN+3 and the US as well as between the ASEAN+3 membersthemselves through the lens of business cycle synchronisation, by using a Bayesianpanel Markov-switching VAR approach (The PMS-VAR model). The main reasonfor investigating this phenomenon is that the increasing level of regional economicintegration of the ASEAN+3 has led to a discussion over the past decade aboutwhether or not the ASEAN+3 is decoupling from the US economy. The resultsprovide evidence that the business cycles of the ASEAN+3 economies are muchmore synchronised with each other than any of them are with the US economy,especially for real economic variables. However, for financial variables, the results indicate that after the US subprime crisis of 2008 the synchronisations ofthe ASEAN+3 and the US have become more substantial, particularly of theirstock price indices and exchange rates.The third essay (Chapter 4) studies recent literature on nowcasting. Upon study,there is a substantial gap to be found regarding investigation into whether or notmulti-country nowcasting models can give predictive gains, no doubt due to thehistorical issue of over-parameterisation, and this thesis meets the challenge offilling that gap. These models are helpful when considering the role of interdependence among a particular group of economies and have potential to help in theassessment of nowcasts of several different GDPs. Therefore, this chapter focusesmainly on comparing nowcasting performance between multi-country models -large Bayesian VARs, Panel VARs and a multi-country dynamic factor model,and individual-country models - MF-BVARs, MF-DFM, with mixed-frequencyapproaches, applied to the four largest European economies during both normal periods and the Covid-19 pandemic. The results show that country-specificmodels outperform the other models when it comes to nowcasts for almost allcountries, especially the pandemic period.
- Advisor / supervisor
- Koop, Gary
- Darby, Julia
- Resource Type
- DOI
- Funder
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PDF of thesis T16821 | 2024-03-07 | Público | Descargar |