A Spatial Analysis of Agricultural Land Prices in Bavaria. Factor Markets Working Document No. 50, June 2013

This paper empirically analyses a dataset of more than 7,300 agricultural land sales transactions from 2001 and 2007 to identify the factors influencing agricultural land prices in Bavaria. We use a general spatial model, which combines a spatial lag and a spatial error model, and in addition account for endogeneity introduced by the spatially lagged dependent variable as well as other explanatory variables. Our findings confirm the strong influence of agricultural factors such as land productivity, of variables describing the regional land market structure, and of non-agricultural factors such as urban pressure on agricultural land prices. Moreover, the involvement of public authorities as a seller or buyer increases sales prices in Bavaria. We find a significant capitalisation of government support payments into agricultural land, where a decrease of direct payments by 1% would decrease land prices in 2007 and 2001 by 0.27% and 0.06%, respectively. In addition, we confirm strong spatial relationships in our dataset. Neglecting this leads to biased estimates, especially if aggregated data is used. We find that the price of a specific plot increases by 0.24% when sales prices in surrounding areas increase by 1%.

Simulation Results of AgriPoliS about Diminishing Capital Subsidies and Restrictions. Factor Markets Working Document No. 55, June 2013

This paper investigates the impacts of high interest rates for borrowed capital and credit restrictions on the structural development of four European regions. The method used is the model AgriPoliS which is a spatial-dynamic agent-based model. It is able to provide aggregated results at the regional level, but very individual results as well by considering farms as independent entities. Farms can choose between different investment options during the simulation. Several scenarios with different interest rates for borrowed capital on the one hand as well as with different levels of credit restrictions on the other hand are tested and compared. Results show that higher interest rates have less impact on declining production branches than on expanding ones. If they have the possibility farms invest in the most profitable production branch which relative profitability might have changed with high interest rates. Credit restrictions lead farms to choose smaller and cheaper investments than expensive and large ones. Results also show that income losses in both cases due to under-investment compared to the reference situation are partially compensated by lower rental prices. The impacts on structural change also differ depending on the region and the initial situation. In summary, credit subsidies or imperfections on credit markets might have indirect impacts on the type of dominant investment and therefore on the whole regional agricultural sector as well.

How mobile is tech talent? A case study of IT professionals based on data from LinkedIn. CEPS Special Report No. 140, July 2016

This study aims to provide independent and in-depth insights into how IT professionals move from one region to another within Europe and beyond. This study was carried out by Mikkel Barslund, Research Fellow, and Matthias Busse, Researcher in the Economic Policy research unit at CEPS. The work was commissioned by the business networking website LinkedIn, whose data analysts kindly provided the data used in this study, aggregated by region and in relative and anonymised terms. The authors are solely responsible for the findings and opinions expressed in this study. CEPS is an independent policy research institute in Brussels, whose mission is to produce sound policy research leading to constructive solutions to the challenges facing Europe today. The views expressed in this study are solely those of the authors and should not be attributed to CEPS or to any other institution with which they are associated or to the business networking website LinkedIn.