https://hdl.handle.net/10419/191984 Research Department, Statistics Norway, Oslo 2026-10-24T19:49:54Z https://hdl.handle.net/10419/336505 Title: A practical framework for behavioral microsimulation using external evidence Authors: Jia, Zhiyang; Skagseth, Snorre; Thoresen, Thor Olav; Vattø, Trine Engh Abstract: When structural labor supply models are unavailable or impractical, the paper proposes a practical method for incorporating behavioral responses into static taxbenefit microsimulation models. Using elasticity estimates from the literature, the proposed external evidence procedure offers a flexible and transparent tool for incorporating behavioral effects into microsimulation. We distinguish between responses in income both at the intensive and extensive margins. The framework is implemented within the Norwegian LOTTE microsimulation system and illustrated through two policy reforms: (i) a five percentage-point increase in the two top brackets of the labor income tax and (ii) the introduction of a work-related income deduction. Empirical results show that behavioral adjustments substantially offset mechanical revenue effects for high-income tax increases, while the work deduction generates positive participation responses but amplifies revenue losses due to phase-out effects. 2026-01-01T00:00:00Z https://hdl.handle.net/10419/336497 Title: A cost-benefit assessment of covid-19 strategies: The case of Norway Authors: Bjertnæs, Geir H. M.; Holmøy, Erling; Hammersland, Roger Abstract: This study evaluates the costs and benefits of alternative COVID-19 strategies for Norway, drawing on ex-post evidence from countries that pursued markedly different approaches. We argue that an elimination strategy-combining strict infection control with stringent border measures until a vaccine becomes available-delivers the greatest net benefits when a successful vaccine is expected within a short timeframe. Under vaccine uncertainty, both elimination and mitigation, the latter allowing gradual community spread, remain viable options. Norway adopted a suppression approach based on extensive TTIQ measures. Our findings suggest that this strategy was inferior compared to both elimination and mitigation. Finally, we compare ex-post assessments of costs and benefits with those emphasized in ex-ante evaluations, highlighting key discrepancies. 2026-01-01T00:00:00Z https://hdl.handle.net/10419/336503 Title: Does tax transparency influence wage setting? Evidence on gender gaps Authors: Carvalho, Cristiano Costa; Vattø, Trine Engh Abstract: This paper examines how an often-overlooked source of pay transparency-the public disclosure of tax information-affects gender wage gaps. We exploit a 2001 change in Norway that made individual tax returns searchable online. Using matched employer-employee data and a differencein-differences design, we find that within-firm gender wage gaps fell by 2.2 percentage points (8.7 percent), driven by rising female wages. Effects are strongest in private-sector firms, industries with initially larger gaps, and municipalities that previously lacked easy access to printed tax lists. Wage gains are concentrated among job-changing women, suggesting that broad-based transparency mainly operates through improved information for job search. 2026-01-01T00:00:00Z https://hdl.handle.net/10419/310446 Title: Innovation outcomes of public R&D support: A new approach to identifying output additionality Authors: Iversen, Eric; Raknerud, Arvid; Klemetsen, Marit; Bye, Brita Abstract: What difference does government support of business R&D make to the rate of innovation? Addressing this important question has deep theoretical roots and broadening practical applications in OECD countries. The analysis of output additionality has been hampered by incomplete data combined with adaption of problematic methodologies. In this light, we contribute to the formative literature in three main ways: we analyze comprehensive panel data of Norwegian enterprises over a 20-year period; we include trademarks and industrial designs as well as patents to broaden measures of innovation output; and we apply machine learning methods to estimate treatment effect functions, thereby addressing the problem of a practically unlimited number of potential confounding factors. Our findings support and elaborate earlier work that fiscal stimulus tends to have greatest impact on previously non-innovative firms. The impact of support measures, alone or in combination, is on the extensive rather than intensive margin. For previously R&D-active firms, our results indicate that public support has low additionality and even risks crowding-out private financing of R&D. 2025-01-01T00:00:00Z