Does the European Union create the foundations of an information society for all? Bruges European Economic Policy (BEEP) Briefing 11/2005

In order to increase the use of information and communication technologies (ICT) in the European Union Member States, the European Commission, on the initiative of Commissioner E. Liikannen, launched in December 1999 a bold programme called “eEurope”. Soon after its creation, the eEurope programme was integrated into the so- called Lisbon agenda for Europe to become the “most advanced knowledge based economy” in the world. We try to assess if the programme is successful in achieving its stated objective of promoting a knowledge based economy through the development of an “information society for all”. First, we conclude that eEurope, due to its origins and its procedures, has intrinsic limits both as regards its scope and effectiveness. Second, we show how Member States have adopted different trajectories towards the “knowledge based society”. To identify these heterogeneous paths of growth, we have selected a set of variables that, combined together, represent the institutional arrangements specific to a country or a group of countries. We found sharp differences between two advanced models that we label, respectively, as Scandinavian and Anglo-Saxon. Without asserting the superiority of a model, we propose policy orientations to help Europe overcome those gaps hindering the move towards knowledge economies where information society technologies are widely diffused.

The Valuation of Agricultural Land and the Influence of Government Payments. Factor Markets Working Paper No. 10, December 2011

This study gives an overview of the theoretical foundations, empirical procedures and derived results of the literature identifying determinants of land prices. Special attention is given to the effects of different government support policies on land prices. Since almost all empirical studies on the determination of land prices refer either to the net present value method or the hedonic pricing approach as a theoretical basis, a short review of these models is provided. While the two approaches have different theoretical bases, their empirical implementation converges. Empirical studies use a broad range of variables to explain land values and we systematise those into six categories. In order to investigate the influence of different measures of government support on land prices, a meta-regression analysis is carried out. Our results reveal a significantly higher rate of capitalisation for decoupled direct payments and a significantly lower rate of capitalisation for agri-environmental payments, as compared to the rest of government support. Furthermore, the results show that taking theoretically consistent land rents (returns to land) and including non-agricultural variables like urban pressure in the regression implies lower elasticities of capitalisation. In addition, we find a significant influence of the land type, the data type and estimation techniques on the capitalisation rate.

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%.

Developing an underlying inflation gauge for China. Bruegel Working Paper 2014/11, 9 October 2014

This paper develops a new underlying inflation gauge (UIG) for China which differentiates between trend and noise, is available daily and uses a broad set of variables that potentially influence inflation. Its construction follows the works at other major central banks, adopts the methodology of a dynamic factor model that extracts the lower frequency components as developed by Forni et al (2000) and draws on the experience of the People’s Bank of China in modelling inflation.