Reproduction Package for The Bioeconomy—A New Life Cycle Phase For Swedish Forestry

This repository contains the reproduction package for: Kreutzer, P.J. (2026). "The Bioeconomy — A New Life Cycle Phase For Swedish Forestry: Evidence from 50 Years of Significant Innovation Output." This study is included as a chapter in the PhD dissertation, Trees Like Cabbages – Innovation Towards a Forest-Based Bioeconomy, Lund University, 2026. Contents The package includes all code and data needed to reproduce the figures, tables, and inline statistics reported in the paper. The analysis pipeline is implemented in Python and the manuscript is authored in Quarto. The repository contains: - The manuscript source files (paper.qmd, _code-setup.qmd, _tbl-bioeconomy-query.tex) - The Python analysis package (swinno_bioeconomy_ilc/) and analysis scripts (scripts/), which compute all figures and regression results - Classification data derived from the SWINNO database (Swedish innovations, 1970–2021), including manually coded bioeconomy innovations - External reference data to aggregate organizations and create price controls - Pre-built logit estimation results and prediction figures (see Restricted Data below) How to Reproduce The package uses https://pixi.sh to manage all dependencies, including Python, Quarto, and a TeX Live distribution. To reproduce: pixi install -e repro pixi run -e repro reproduce This executes four tasks in sequence: generating industry life cycle and bioeconomy composition figures from raw innovation data, computing the capture mechanism analysis, and rendering the final PDF via Quarto and LuaLaTeX. The package has been tested on macOS (ARM). Dependencies are solved for macOS, Linux, and Windows. On Windows, I recommend running inside WSL (Windows Subsystem for Linux) for full compatibility. Restricted Data The file funding_data.dta (innovation-level public funding status, compiled by Fink 2024) cannot be redistributed. The data pipeline and logit estimation tasks that depend on this file are not part of the automated reproduction pipeline, but their scripts are included for inspection. Pre-built outputs from these tasks — including the estimation dataset, fitted logit model, and prediction figures — are shipped as artifacts. See RESTRICTED_DATA.md for details on how to obtain the original data. Data Sources Innovation data are drawn from the SWINNO database, a literature-based innovation output database covering significant innovations commercialized in Sweden. The bioeconomy classifications were coded manually by the author. Firm-level collaboration data are derived from SWINNO's producer and collaborator records.