Search Results (6)

This study investigates how bank mergers and acquisitions (M&As) reshape the monitoring architecture of syndicated loans and, by extension, borrowers’ financing conditions. Using a global panel of 20,299 syndicated loan contracts, originating in 43 countries between 1982 and 2020, we link LPC DealScan data to Securities Data Company M&A records to trace each loan’s lead arrangers before and after consolidation events. Fixed-effects regressions, enriched with borrower- and loan-level controls, reveal three key patterns. First, post-merger loans exhibit significantly more concentrated syndicates: the Herfindahl–Hirschman Index rises by roughly 130 points and lead arrangers retain an additional 0.8–1.1 percentage points of the loan, consistent with heightened monitoring incentives. Second, these effects are amplified when information asymmetry is acute, i.e., for opaque or unrated firms, supporting moral hazard theory predictions that lenders internalize greater risk by holding larger stakes. Third, relational capital tempers the impact of consolidation: borrowers with repeated pre-merger relationships face smaller increases in syndicate concentration, while switchers experience the most significant jumps. Robustness checks using lead arranger market share, alternative spread measures, and lag structures confirm the findings. Overall, the results suggest that bank consolidation strengthens lead arrangers’ incentives to monitor but simultaneously reduces risk-sharing among participant lenders. For borrowers, the net effect is a trade-off between potentially tighter oversight and reduced syndicate diversification, with the balance hinging on transparency and prior ties to the lender. These insights refine our understanding of how structural shifts in the banking sector cascade into corporate credit markets and should inform both antitrust assessments and borrower funding strategies. Full article

Economic stability in emerging market economies is increasingly shaped by the interplay between global financial integration, domestic monetary dynamics, and asset price fluctuations. Yet, early detection of financial market disruptions remains a persistent challenge. This study constructs a Financial Stress Index (FSI) for Pakistan, utilizing monthly data from 2005 to 2024, to capture systemic stress in a globalized context. Using Principal Component Analysis (PCA), the FSI consolidates diverse indicators, including banking sector fragility, exchange market pressure, stock market volatility, money market spread, external debt exposure, and trade finance conditions, into a single, interpretable measure of financial instability. The index is externally validated through comparisons with the U.S. STLFSI4, the Global Economic Policy Uncertainty (EPU) Index, the Geopolitical Risk (GPR) Index, and the OECD Composite Leading Indicator (CLI). The results confirm that Pakistan’s FSI responds meaningfully to both global and domestic shocks. It successfully captures major stress episodes, including the 2008 global financial crisis, the COVID-19 pandemic, and politically driven local disruptions. A key understanding is the index’s ability to distinguish between sudden global contagion and gradually emerging domestic vulnerabilities. Empirical results show that banking sector risk, followed by trade finance constraints and exchange rate volatility, are the leading contributors to systemic stress. Granger causality analysis reveals that financial stress has a significant impact on macroeconomic performance, particularly in terms of GDP growth and trade flows. These findings emphasize the importance of monitoring sector-specific vulnerabilities in an open economy like Pakistan. The FSI offers strong potential as an early warning system to support policy design and strengthen economic resilience. Future modifications may include incorporating real-time market-based metrics indicators to better align the index with global stress patterns. Full article

Foreign direct investment (FDI) is essential for enhancing economic resilience and promoting sustainable development. However, inefficiencies in financial connectivity and capital allocation have hindered the facilitation of FDI. Bank linkages between countries in the global sectors of multinational enterprises (MNEs) offer potential solutions to these challenges. In this paper, we focus on whether sustainable FDI can benefit from consolidating bank linkages, which are measured for each pair of countries in each year as the number of bank pairs in both countries that are connected through cross-border syndicated lending. Using the gravity model, we provide empirical evidence based on cross-border data to support the following conclusions: (1) Bank linkages can sustainably enhance the host country’s attractiveness to FDI through information, external financing, and international financial services channels. (2) This positive effect is pronounced in host countries with lower financial development, weaker institution quality, and higher investment risk while remaining insignificant for OECD countries. (3) Bank linkages exhibit a lagged impact on FDI, but newly established bank linkages are more conducive to inward FDI than those established earlier. In this paper, we offer some policy implications for emerging economies and suggest that emerging economies should continue to deepen their financial openness and strengthen international bank links through various means to attract more inward FDI. Full article

The global financial crisis (2008–2009) represents a notable example of a generally unpredicted crisis in economic history. Nevertheless, it presented features comparable to almost any previous (monetarily related) crisis episode. For instance, it was characterized by a “vicious cycle” made by over-issued money and/or over-granted loans nourishing private and public indebtedness and—eventually—affecting asset prices with stable consumer price indexes. While the post-COVID-19 inflation presents different characteristics because of being a crisis “exogenous” to the economic system, the present Communication claims that future crises (if endogenous to the economic system) are likely to follow usual patterns. The approach used to analyse the transmission channels contributing to economic and financial crises is theoretical. Nevertheless, the present Communication still contains statistical evidence in support of the predictability of such crises as soon as their usual dynamics is understood. The statistical analysis carried out is rather descriptive than causal in nature. Finally, this Communication reminds that “typical” economic and financial crises in advanced economies behave along some consolidated patterns. At their origins, there are mostly over-issued money and/or over-granted loans by central and/or commercial banks financing private and public debt. This phenomenon exacerbates risks in the economy and—while it incentivises money issuers and credit granters in good times to over-issue money and over-grant credits to earn extra-profits—it over-exposes economic agents to the risk of (even greater) economic losses in negative times. As soon as the bubble to be defined as over-proportionally grown prices of specific assets due to over-issued money and over-granted credits pops and funds are rapidly divested, prices collapse and drive the economy into a severe crisis. Full article

This paper addresses the problem of modeling credit risk for multi-product and global loan portfolios. The authors presented an improved version of the Basel Committee’s one-factor model for capital requirements calculation. They examined whether latent market factors corresponding to distinct portfolios are always highly correlated within the global portfolio and how this correlation impacts total losses distribution function. Historical losses of top-tier banks (JPMorgan Chace, Bank of America, Citigroup, Wells Fargo, US Bancorp) were analyzed. Furthermore, the estimation of the correlations between latent market factors was conducted, and its impact on the total loss distribution function was assessed. The research was performed based on consolidated financial statements for holding companies - FR Y-9C reports provided by the Federal Reserve Bank of Chicago. To verify the improved model, the authors analyzed two distinct loan portfolios for each bank, i.e., credit cards and commercial and industrial loans. They showed that the correlation between latent market factors could be significantly lower than one and disregarding this conclusion may lead to overestimating total unexpected losses. Hence, capital requirements calculated according to the IRB (Internal Ratings Based Approach) formula as a sum of individual VaR999 estimates may be biased. According to this finding, the enhanced one-factor model seems to be more accurate while calculating unexpected total loss for global portfolios. The authors proved that the active credit risk management process aiming to lower market factors’ correlation results in less volatile total losses. Therefore, financial institutions could be more resistant to macroeconomic downturns. Full article

Accurate maps of surface water extent are of paramount importance for water management, satellite data processing and climate modeling. Several maps of water bodies based on remote sensing data have been released during the last decade. Nonetheless, none has a truly (90 ${}^{\circ }$ N/90 ${}^{\circ }$ S) global coverage while being thoroughly validated. This paper describes a global, spatially-complete (void-free) and accurate mask of inland/ocean water for the 2000–2012 period, built in the framework of the European Space Agency (ESA) Climate Change Initiative (CCI). This map results from the synergistic combination of multiple individual SAR and optical water body and auxiliary datasets. A key aspect of this work is the original and rigorous stratified random sampling designed for the quality assessment of binary classifications where one class is marginally distributed. Input and consolidated products were assessed qualitatively and quantitatively against a reference validation database of 2110 samples spread throughout the globe. Using all samples, overall accuracy was always very high among all products, between $98\%$ and $100\%$ . The CCI global map of open water bodies provided the best water class representation (F-score of $89\%$ ) compared to its constitutive inputs. When focusing on the challenging areas for water bodies’ mapping, such as shorelines, lakes and river banks, all products yielded substantially lower accuracy figures with overall accuracies ranging between $74\%$ and $89\%$ . The inland water area of the CCI global map of open water bodies was estimated to be 3.17 million km ${}^2$ ± 0.24 million km ${}^2$ . The dataset is freely available through the ESA CCI Land Cover viewer. Full article