Network Analysis of Business Cycle Synchronisation (available on SSRN)
To investigate the fundamental relationship between business cycle synchronisation (BCS) and trade/finance intensities, we develop the simultaneous equation panel data model that accommodates all the key elements: simultaneity, spatial spillovers, global shocks and parameter heterogeneity. We propose the consistent CCEX-2SLS estimator, and conduct a spatial network analysis to investigate the direct and indirect impacts of trade/finance intensities on the BCS across country-pairs or the selected clusters. We apply the proposed approach to the dataset consisting of the 136 pairs of the 17 OECD countries over 1995Q1-2019Q4, and convincingly unveil: (i) the individual CCEX-2SLS estimation results demonstrate the importance of explicitly taking parameter heterogeneity into account; (ii) almost 90% of the sample belong to cases where the direct and indirect effects of trade/finance intensities on BCS display opposite signs; (iii) we observe the surprisingly negative total effect of trade intensity on BSC and negative spillovers of trade and financial intensities on BCS. This suggests that EU economies promote the policies to facilitate trade/financial intensities for improved BCS.
Systematic Common Components in ESG Ratings across Legal Origins (joint with Prof. Yongcheol Shin, Prof. Kausik Chaudhuri, Dr. Han Jin) – under consideration in the International Review of Financial Analysis (available on SSRN)
We aim to identify and analyse systematic components of ESG ratings using the multilevel factor model. Applying the generalised canonical correlation (GCC) approach to the MSCI and Refinitiv datasets across the four legal origins (English, French, German, Scandinavian), we document the presence of one global factor irrespective of ESG rating or its three E/S/G pillars, confirming ESG globalisation while the number of local factors varies across legal origins and sub-components. We find the dominance of global factors in Refinitiv data but the dominance of local factors in MSCI data in explaining the variance of ESG. Furthermore, we find the mixed evidence on the impacts of legal origin on ESG performance. As the GCC-based approach is data-driven, such different findings point towards the raters' ESG divergence as postulated in the literature. We suggest that the relative importance ratios of the global factor be greatly improved relative to local factors and idiosyncratic components so as to better predict overall ESG performance. Given that the standards of ESG disclosure reporting are currently quite different across civil and common law countries, this goal can be achieved through the enforcement of global mandatory reporting standards.
Network Analysis of ESG and SDG across Legal Origins (joint with Prof. Yongcheol Shin, Prof. Kausik Chaudhuri, Dr. Han Jin)
We explore the relationship between ESG and SDG across legal origins (English, French, German, Scandinavian) using an integrated panel data model with local spillovers, global shocks and parameter heterogeneity. Applying the CCEX-IV approach and GCM network analysis, we find that civil legal origins show higher direct effects of ESG on SDG within each legal origin while common legal origin exhibits stronger spill-in effects, supporting the first- and second-generation legal origin theory. But, network analysis of aggregate ESG and its pillars indicates that English legal origin has the highest direct effects. Furthermore, heterogeneity is observed within civil legal origins, with German legal origin being the most influential shock transmitter, challenging the monolithic view of civil law countries and thereby raising the importance of accommodating sub-categorisation in legal origin theory.
Business Cycle Synchronisation with Simultaneity and Cross-section Dependence
We aim to uncover the implications of bilateral trade and financial intensities on business cycle synchronisation (BCS), using the simultaneous panel data model with interactive effects. To address the joint issue of simultaneity and cross-section dependence that are largely overlooked in the literature, we develop a CCE-2SLS estimation approach to the dataset consisting of the 120 pairs of the 16 OECD countries over 1995Q1-2019Q4. We find a positive effect of trade intensity and a negative effect of financial intensity on BCS. When decomposing trade intensities, the impact of intensity in intermediate inputs is shown to be substantially stronger than that of final goods. Furthermore, we find that the relationship between financial intensity and BCS turns to be positive under the 2008 crisis while it remains negative within tranquil periods.