
More than half of Germany's medium-sized companies expect an economic downturn next year, according to a survey by the BVMW business association.
Christoph Ahlhaus, the association's chief executive, said on Saturday that "superficial reforms are no longer enough to get Germany back on track."
He said businesses expect the federal government to finally deliver on long-promised structural reforms and concrete relief measures in areas such as bureaucracy, the labour market, taxation and energy costs.
According to the survey, 54% of companies expect an economic slowdown, while only 22% anticipate an upswing. In addition, 42% of respondents said they plan to scale back investment in 2026, the association said.
Medium-sized companies, known as the Mittelstand, form the backbone of Germany's economy and account for a large share of employment and investment.
The German economy contracted in 2023 and 2024, while growth is forecast to be minimal this year and no meaningful recovery is expected in 2026.
The BVMW surveyed more than 1,000 Mittelstand companies in an online poll conducted between December 18 and 23.
LATEST POSTS
- 1
8 Espresso Bean Starting points All over the Planet - 2
‘Wu-Tang Forever: The Final Chamber’ tour — How to get tickets, presale times, concert dates and more - 3
Vote In favor of Your #1 sort of film - 4
Was This Driver Simply Having A great time Or Behaving Like An Ass? - 5
The 15 Most Compelling Books in History
Journalist reported killed in the Gaza Strip
A hunger for new experiences Narratives: Motivating Travel and Experience
Instructions to Upgrade the Proficiency of Your Sunlight powered chargers
Jesse Jackson hospitalized, under observation for a neurodegenerative condition
Figurine of a woman and a goose offers peek at prehistoric beliefs
NASA funds new tech for upcoming 'Super Hubble' to search for alien life: 'We intend to move with urgency'
'A perfect storm': Airlines cut flights and increase airfares as jet fuel price spikes
Vote in favor of your Favored kind of pasta
We analyzed Philly street scenes and identified signs of gentrification using machine learning trained on longtime residents’ observations













