IWH Research Seminar

Why Don’t Old Firms Do New Things?

Public events

Wirtschaft als Sicherheitsfrage. Wie verwundbar ist Deutschland?

Die Deutsche Atlantische Gesellschaft und das Leibniz-Institut für Wirtschaftsforschung Halle (IWH) laden Sie herzlich zu einer Podiumsdiskussion am 22. Juni 2026 nach Halle (Saale) ein.

IWH Research Seminar

Green Business Cycles

This paper examines the relationship between green innovation and the business cycle, revealing that while non-green innovation is procyclical, green innovation is countercyclical.

Workshops and conferences

12th IWH-FIN-FIRE Workshop on "Challenges to Financial Stability"

The Halle Institute for Economic Research (IWH) – Member of the Leibniz Association is organizing a workshop on “Challenges to Financial Stability” on August 24th and 25th, 2026, to be held in Halle (Saale). We aim to attract excellent theoretical and empirical papers from a broad range of financial economics and stability topics.

IWH Research Seminar

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Workshops and conferences

21. IWH/IAB Workshop: Transformation pressure in the labour market: heterogeneity, adjustment processes, and lessons for economic policy

The German economy is going through a period of profound transformation. Technological change, decarbonization and demographic developments are fundamentally changing labor markets – albeit not uniformly, but with significant differences between regions, sectors and groups of workers.

IWH Research Seminar

The Wandering Scholars: Understanding the Heterogeneity of University Commercialization

University-based scientific research has long been argued to be a central source of commercial innovation and economic growth.

Workshops and conferences

27th IWH-CIREQ-GW Macroeconometric Workshop: Identifying Macroeconomic Dynamics - Advances in VAR Methods and Applications

This workshop provides a forum for the discussion of recent advances in empirical and applied macroeconometric modelling, with a particular emphasis on vector autoregressive (VAR) models and the identification of causal effects in multiple time series models.