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This study measures changes in total factor productivity of agriculture for 25 European Union (EU) member states in 2004–2016 using the Färe-Primont index. It also attempts to answer the question whether in the analysed period the levels of total factor productivity in this sector were convergent between member states. To this end, panel unit root tests were used. The study indicates that in new EU member states the level of total factor productivity (TFP) was relatively lower than in most EU-15 states. It was also found that convergence occurred in agricultural productivity almost in all EU member states (except Belgium and the United Kingdom). The research shows that in new EU member states the process of making up differences in the productivity of agriculture was stronger than in old EU member states.

This paper studies club convergence in relation to labour productivity in the agriculture industry of 28 European Union countries for the period 2005 to 2018. The countries were divided into three groups which were homogeneous in terms of level of development in the agricultural sector. The presence of convergence in the groups of countries was verified by using a panel-data model of conditional β-convergence. Then, convergence processes were investigated within clubs of countries. Convergence processes took place in the groups of countries with low and medium levels of labour productivity. In the club of countries where labour productivity was high, opposite processes (i.e. divergence) were observed.

Research background: Given the pivotal role of innovations and technological progress in shaping the economic development of regions and the crucial significance of spatial dimension of innovation processes at the regional level, the assessment of technological convergence in the regional scope becomes an essential research problem. Technological convergence could be identified on the basis of the analysis of total factor productivity (TFP). The significance of the technological convergence analysis results from the fact that income convergence can be both accelerated or impeded, depending on whether the initial differences in the level of technology (TFP) decrease or increase over time. Purpose of the article: The aim of the paper is twofold. Firstly, we attempt to develop a theoretical framework for the analysis of the technological convergence. Secondly, we investigate the technological convergence (on the basis of the TFP analysis) across European regions. Methods: During the first stage of the research, we employ the multiplicatively-complete Färe-Primont index to calculate TFP. The second stage of the study includes estimation of spatial panel models applied to assess the level of technological convergence across European regions. The research sample consists of 273 NUTS 2 European Union (EU) regions over the period 2010– 2016. Findings & Value added: The results of the study confirm a clear division of Europe into the Western European regions with high TFP values and the Eastern European regions with low TFP level. The research also shows that in the Eastern European regions the process of reducing the differences in the productivity levels is faster than in Western European regions. Since the issue of technological convergence is still not sufficiently explored in the relevant literature our paper attempts to fill a cognitive and methodological gap in the investigation of the technological convergence in the European regional space.

The article deals with the issue of knowledge spillovers in the European regions. For this purpose, a standard Knowledge Production Function (KPF) approach was extended by the application of spatial econometrics methods. Our analysis started from the construction of the alternative structures of the spatial weight matrices. These matrices were based on technological and institutional proximities, which represent compelling alternatives to geographic proximity regarded as a kind of all-encompassing connectivity measure. The next step in our analysis was the modeling of regional knowledge generation processes. We treated R&D expenditures and human resources in science and technology as the input measures and patent applications to the European Patent Office as the output measure in our basic and extended models. The results show that the scope and direction of knowledge spillovers are sensitive to the type of knowledge (tacit vs. codified) and proximity dimension engaged. These findings contribute to the current debate in the geography of innovation and economics of knowledge literature.