As farmers rallied in Athens on Tuesday, Prime Minister Kyriakos Mitsotakis was in the Rhodope region, a key agricultural area in northeastern Greece, where he announced a 50 pct increase in the fuel tax rebate cap for farmers.

For immigrant communities from countries with especially high duties, food costs have risen sharply courtesy of President Trump.

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.

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.