TSI Concluding Conference – March 17-18, 2025, Berlin
TSI Concluding Conference 17-18 March 2025 in Berlin The TSI Concluding Conference , held in Berlin on March 17–18, 2025 , brought together key stakeholders from across the TSI…
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11th Annual Conference in Luxembourg
11th Annual Conference in Luxembourg 14.-15. September 2022 in Luxembourg This year CompNet celebrated its 11th Annual Conference, together with EIB and ENRI as co-hosts, which…
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CompNet-EBRD Workshop
Localization and Productivity CompNet-EBRD Workshop, October 8-9, 2018, European Bank for Reconstruction and Development, London, United Kingdom The workshop of The…
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CompNet Data Provider Forum & TSI Workshop
7th CompNet Data Provider Forum & 4th TSI Workshop The upcoming CompNet Data Providers Forum and TSI Workshop, taking place in Amsterdam on November 18-19, 2024, promises to be a…
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Advances in Using Vector Autoregressions to Estimate Structural Magnitudes
Christiane Baumeister, James D. Hamilton
Econometric Theory,
No. 3,
2024
Abstract
This paper surveys recent advances in drawing structural conclusions from vector autoregressions (VARs), providing a unified perspective on the role of prior knowledge. We describe the traditional approach to identification as a claim to have exact prior information about the structural model and propose Bayesian inference as a way to acknowledge that prior information is imperfect or subject to error. We raise concerns from both a frequentist and a Bayesian perspective about the way that results are typically reported for VARs that are set-identified using sign and other restrictions. We call attention to a common but previously unrecognized error in estimating structural elasticities and show how to correctly estimate elasticities even in the case when one only knows the effects of a single structural shock.
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Application Barriers and the Socioeconomic Gap in Child Care Enrollment
Henning Hermes, Philipp Lergetporer, Frauke Peter, Simon Wiederhold
Abstract
Why are children with lower socioeconomic status (SES) substantially less likely to be enrolled in child care? We study whether barriers in the application process work against lower-SES children — the group known to benefit strongest from child care enrollment. In an RCT in Germany with highly subsidized child care (N = 607), we offer treated families information and personal assistance for applications. We find substantial, equity-enhancing effects of the treatment, closing half of the large SES gap in child care enrollment. Increased enrollment for lower-SES families is likely driven by altered application knowledge and behavior. We discuss scalability of our intervention and derive policy implications for the design of universal child care programs.
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IWH FDI Micro Database
IWH FDI Micro Database The IWH FDI Micro Database (FDI = Foreign Direct Investment) comprises a total population of affiliates of multinational enterprises (MNEs) in selected…
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EVA-KULT
EVA-KULT Establishing Evidence-based Evaluation Methods for Subsidy Programmes in Germany The project aims at expanding the Centre for Evidence-based Policy Advice at the Halle…
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ENTRANCES
ENTRANCES aims at examining the effects of the coal phase-out in Europe. How does the phase-out transform society – and what can politics do about it? The EU-funded,…
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Behaviour
The maths behind gut decisions First carefully weigh up the costs and benefits and then make a rational decision. This may be the way we want it to be. But in reality, invisible…
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