A machine learning approach to real time identification of turning points in monetary aggregates M1 and M3

11/11/2025 European Central Bank Central banks

Monetary aggregates provide valuable information about the monetary policy transmission and the business cycle. This paper applies machine learning methods, namely Learning Vector Quantisation (LVQ) and its distinction-sensitive extension (DSLVQ), to identify turning points in euro area M1 and M3. We benchmark performance against the Bry–Boschan algorithm and standard classifiers. Our results show that LVQ detects M1 turning points with only a three-month delay, halving the six-month confirmation lag of Bry–Boschan dating.

Joining forces: why banks syndicate credit

11/11/2025 European Central Bank Central banks

Banks can grant loans to firms bilaterally or in syndicates. We study this choice by combining bilateral loan data with syndicated loan data. We show that loan size alone does not adequately explain syndication. Instead, banks’ ability to manage risks and firm riskiness drive the choice to syndicate. Banks are more likely to syndicate loans if their risk-bearing capacity is low and if screening and monitoring come at a high cost. Syndicated loans are more expensive and more sensitive to loan risk than bilateral loans.

A machine learning approach to real time identification of turning points in monetary aggregates M1 and M3

11/11/2025 European Central Bank Central banks

Monetary aggregates provide valuable information about the monetary policy transmission and the business cycle. This paper applies machine learning methods, namely Learning Vector Quantisation (LVQ) and its distinction-sensitive extension (DSLVQ), to identify turning points in euro area M1 and M3. We benchmark performance against the Bry–Boschan algorithm and standard classifiers. Our results show that LVQ detects M1 turning points with only a three-month delay, halving the six-month confirmation lag of Bry–Boschan dating.

Joining forces: why banks syndicate credit

11/11/2025 European Central Bank Central banks

Banks can grant loans to firms bilaterally or in syndicates. We study this choice by combining bilateral loan data with syndicated loan data. We show that loan size alone does not adequately explain syndication. Instead, banks’ ability to manage risks and firm riskiness drive the choice to syndicate. Banks are more likely to syndicate loans if their risk-bearing capacity is low and if screening and monitoring come at a high cost. Syndicated loans are more expensive and more sensitive to loan risk than bilateral loans.

China’s growing trade surplus: why exports are surging as imports stall

11/11/2025 European Central Bank Central banks

Debate over China’s growing trade surplus has resurfaced amid US-China trade tensions, geoeconomic shifts and global imbalances. This box shows that the surplus reflects two distinct dynamics: persistently weak imports and surging exports. On the import side, structural policies promoting domestic substitution, trade restrictions and sluggish demand have curbed demand for foreign goods. On the export side, subdued domestic demand has led firms to redirect excess production capacity abroad, consistent with the “vent-for-surplus” mechanism.

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