YSS1
Thursday, August 28, 2025 |
11:00 - 13:00 |
G1 |
Details
Chair & Discussant: Daniel Felsenstein
Speaker
Ms Eleanor Johansson
Ph.D. Student
Swedish University Of Agricultural Sciences
Spatial Spillovers in Functional Crop Diversification and implications for productivity - (EPAINOS Paper)
Author(s) - Presenters are indicated with (p)
Eleanor Johansson (p)
Discussant for this paper
Daniel Felsenstein
Abstract
This study examines the spatial spillover effects of functional crop diversification on farm-level total factor productivity (TFP) in Sweden. Functional crop diversification is the practice of cultivating crop groups with distinct ecological functions (de Bello et al., 2010). It has been shown to enhance ecosystem services such as nutrient cycling, biological pest control, and soil health (Bommarco et al., 2013). While research has established the direct benefits of crop diversification for yield stability and ecosystem services (Isbell et al., 2017; Watson et al., 2017), its diffusion through spatial networks and impact on economic performance is less explored. This study investigates whether there is a particular type of knowledge associated with functional crop diversification that spreads across farms and how these spatial spillovers affect farm-level total factor productivity.
The empirical analysis is based on a panel dataset of roughly 30,000 Swedish crop farms from 2009 to 2021. The dataset integrates farm level crop information from the Swedish Land Parcel Identification System (LPIS), farm financial data from Statistics Sweden (SCB), and geospatial coordinates to define spatial relationships. First, TFP is estimated using a standard production function approach, incorporating land, capital, labour, and intermediate inputs (Rovigatti and Mollisi, 2018). Second, the estimated TFP values serve as the dependent variable in a spatial Durbin model. This allows for the identification of both direct effects from a farm’s own crop diversification, and indirect effects from the diversification of neighbouring farms on productivity (Vroege et al., 2020). Following Nilsson et al. (2022), functional crop diversity is quantified using a decomposition of the Shannon diversity index where crops are categorized into nine ecological functional groups. The spatial structure is modelled using inverse distance weighting, where the impact of neighbouring farms decreases with distance.
This research contributes to the understanding of agricultural knowledge spillovers by providing empirical evidence on how diversification strategies adopted by one farm influence the productivity of its neighbours. By explicitly modelling spatial externalities, the findings have important implications for policy. If there are positive spillover effects, place-based interventions such as subsidies for functional diversification or knowledge-sharing initiatives could not only enhance individual farm performance but also generate positive regional spillovers (Altieri et al., 2015; Bowles et al., 2020). By bridging ecological and economic perspectives, this study offers new insights into how diversification spreads within agricultural communities and its broader impact on economic resilience.
The empirical analysis is based on a panel dataset of roughly 30,000 Swedish crop farms from 2009 to 2021. The dataset integrates farm level crop information from the Swedish Land Parcel Identification System (LPIS), farm financial data from Statistics Sweden (SCB), and geospatial coordinates to define spatial relationships. First, TFP is estimated using a standard production function approach, incorporating land, capital, labour, and intermediate inputs (Rovigatti and Mollisi, 2018). Second, the estimated TFP values serve as the dependent variable in a spatial Durbin model. This allows for the identification of both direct effects from a farm’s own crop diversification, and indirect effects from the diversification of neighbouring farms on productivity (Vroege et al., 2020). Following Nilsson et al. (2022), functional crop diversity is quantified using a decomposition of the Shannon diversity index where crops are categorized into nine ecological functional groups. The spatial structure is modelled using inverse distance weighting, where the impact of neighbouring farms decreases with distance.
This research contributes to the understanding of agricultural knowledge spillovers by providing empirical evidence on how diversification strategies adopted by one farm influence the productivity of its neighbours. By explicitly modelling spatial externalities, the findings have important implications for policy. If there are positive spillover effects, place-based interventions such as subsidies for functional diversification or knowledge-sharing initiatives could not only enhance individual farm performance but also generate positive regional spillovers (Altieri et al., 2015; Bowles et al., 2020). By bridging ecological and economic perspectives, this study offers new insights into how diversification spreads within agricultural communities and its broader impact on economic resilience.
Mr Daniel Ruiz Palomo
Ph.D. Student
Universitat Autònoma de Barcelona (UAB)
Assessing the Impact of High-speed Rail on Population Growth: the Case of Spain - (EPAINOS Paper)
Author(s) - Presenters are indicated with (p)
Daniel Ruiz Palomo (p)
Discussant for this paper
Daniel Felsenstein
Abstract
Over the past three decades, Spain has built the second largest high-speed rail network in the world, massively reducing travel times across the country. Did the construction of the high-speed rail network contribute to the concentration of population in the main metropolitan areas, or did it contribute to the relocation of residents to outlying regions This paper proposes an empirical methodology to answer this question. To address the endogeneity between growth and route allocation, the paper uses an inconsequential unit approach based on a hypothetical minimum construction cost network. Preliminary results suggest that more exposed regions experienced greater population growth.
Dr. Harm-Jan Rouwendal
Post-Doc Researcher
University Of Groningen
New skill adoption and cities
Author(s) - Presenters are indicated with (p)
Harm-Jan Rouwendal (p), Anet Weterings, Sierdjan Koster
Discussant for this paper
Daniel Felsenstein
Abstract
This paper studies the relationship between new technology adoption and agglomeration economies. We asses to what extent the adoption of new technologies differs across space by studying differences in the demand for new digital skills in the Netherlands. The use of online job vacancy data allows us to study the implementation of new technologies on the skill level in the workplace and empirically analyse the spatial variation in new digital skill adoption within occupations. Results show that employers in urban areas demand new digital skills for open jobs more frequently and more intensively than elsewhere, especially when it comes to skills for emerging technologies like Deep learning and Blockchain. This indicates new technology adoption is higher in cities, which helps explain the productivity premium of urban areas.
