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IZA Discussion Papers

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Die IZA Discussion Papers (ISSN: 2365-9793) gilt mit ihren über 17.000 Titeln als die wichtigste Schriftenreihe dieser Art in der Arbeitsökonomie. Mitglieder des IZA-Netzwerks stellen hier ihre aktuellen Forschungsresultate vorab zur Diskussion, bevor sie Eingang in Fachzeitschriften finden. Das IZA leistet damit einen wichtigen Beitrag zur wissenschaftlichen Qualitätssicherung.

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7 IZA Discussion Papers
IZA Discussion Paper No. 15921
Recovering Income Distribution in the Presence of Interval-Censored Data
Gustavo J. Canavire Bacarreza, Fernando Rios-Avila, Flavia Sacco-Capurro
published in: Journal of Economic Inequality, 2024, 22, 1039 - 1060
IZA Discussion Paper No. 8251
How Diverse Can Spatial Measures of Cultural Diversity Be? Results from Monte Carlo Simulations of an Agent-Based Model
Daniel Arribas-Bel, Peter Nijkamp, Jacques Poot
published in: Environment and Planning A, 2016, 48(10), 2046-2066
IZA Discussion Paper No. 6583
Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Data Models
Kazuhiko Hayakawa, M. Hashem Pesaran
published as 'Robust standard errors in transformed likelihood estimation of dynamic panel data models with cross-sectional heteroskedasticity' in: Journal of Econometrics, 2015, 188 (1), 111-134
IZA Discussion Paper No. 4794
Estimation of Heterogeneous Treatment Effects on Hazard Rates
Simen Gaure, Knut Røed, Gerard J. van den Berg, Tao Zhang
IZA Discussion Paper No. 3745
The Italian Job: Match Rigging, Career Concerns and Media Concentration in Serie A
Tito Boeri, Battista Severgnini
published as "Match rigging and the career concerns of referees" in: Labour Economics, 2011, 18(3), 349-359
IZA Discussion Paper No. 3095
Bandwidth Selection and the Estimation of Treatment Effects with Unbalanced Data
Jose C. Galdo, Jeffrey A. Smith, Dan A. Black
published in: Annales d'Economie et Statistique, 2008, 91-92, 189-216
IZA Discussion Paper No. 996
Bayesian Inference for Duration Data with Unobserved and Unknown Heterogeneity: Monte Carlo Evidence and an Application
M. Daniele Paserman
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