Industrialisation and trade are two major contributors to growth and development. Historical experience has clearly demonstrated the importance of industrialisation and manufactured exports in the transformation from a backward country to an advanced country. Moreover, industrialisation is not only an efficient way to increase productivity and welfare, but also an effective way to promote social and cultural changes. Over the recent decades, two trends in developing countries' industrialisation and trade have been well documented in the literature. First, manufactures have taken increasingly important share in many developing countries' export basket. Second, the fast-growing trade between developing countries, say, South-South trade, has been highlighted. Given the importance of industrialisation and trade in development process, this PhD thesis aims at contributing to knowledge on the evidence, mechanism, and determinants of developing countries' trade and industrialisation, centring on South-South trade, export upgrading, export directionality, and terms of trade over the recent two decades from 1995 to 2014. Each of the four topics is addressed in one of the following four chapters from Chapter 2 to Chapter 5. Chapter 2 criticises the existing approach towards the definition of the Global South and South-South trade, and clarifies that the delightful picture of South-South trade highlighted in the literature is actually an "illusion". Including de facto developed countries (e.g., the Asian Tigers) and emerging countries in the group of developing countries strongly inflates the size and growth of South-South trade. If these countries are excluded, then the relative size of South-South trade becomes quite small. In particular, this chapter demonstrates that including these de facto developed and emerging countries in South-South trade statistics heavily overstates technological and manufacturing capabilities of the so-called "Global South". Moreover, this chapter also explores the composition of developing countries' exports to different trade partners and their trade potential with the rest of the world. It reveals great differences in the composition between developing countries' different export directions and significant asymmetries in mutual trade potential between developing countries and the rest of the world. Chapter 3 examines the determinants of developing countries' export upgrading with a particular interest in the role of China and productive investment. Amongst general factors, access to sea, human capital, productive investment, and trade openness are found to be major contributors to developing countries' export upgrading. The robust effect of productive investment reflects the importance of political and social agents' motivations of industrialisation and, perhaps more importantly, endemic political-economic embeddedness that determines the motivations. This echoes the centrality of strong and developmentally-oriented elites in the developmentalist model of industrialisation and development. Developing countries' absolute gains from trade with China, as reflected by the significant improvement in their income terms of trade vis-à-vis China, promote their export upgrading. Importantly, mediation analysis shows that this export-upgrading effect operates, to a large extent, through the enhancing effect of trade with China on developing countries' productive investment. This export-upgrading effect of absolute gains from trade with China is stronger and more robust in the period of 2002-2014 than 1995-2014, which is consistent with the growing role of China in the global economy since the early 2000s, reflecting on China's commodity boom and its strong performance in manufactured exports. That is to say, trade with China serves as a source of investment for developing countries' export upgrading. This finding provides a new and indirect channel to understand the influence of China on developing countries' industrialisation, going beyond the conventional perspectives of the "crowding-out" effect and the "re-primarisation" effect. It suggests that, for developing countries, China serves more as a stimulator of capital accumulation than a competitor in manufacturing market or a predator of natural resources. Therefore, the priority for developing countries is the appropriate use of gains from trade for productive purpose. Chapter 4 provides the latest evidence to the discussion in the 1980s on developing countries' export directionality, and explores the determinants of this directionality. Between 1995 and 2014, more than half of developing countries tended to have more sophisticated Southbound exports than Northbound exports, while the opposite is true for the rest. Productive capabilities are found to be a major and robust determinant of this directionality of export sophistication. Productively more advanced developing countries are more likely to have more sophisticated Northbound exports than Southbound exports, which is likely to be due to their ability to access the more competitive markets of developed and emerging countries and/or the downstream value chains with their relatively sophisticated products. In contrast, productively less advanced developing countries have to access developed and emerging countries' markets and/or the downstream value chains with their less sophisticated products, due to the lack of competitiveness in more sophisticated products. This finding suggests that the conventional argument that South-South trade is more beneficial to developing countries than North-South trade should be interpreted conditionally, because, for those productively more advanced developing countries, Northbound exports are likely to be more sophisticated. Another important contributor to the directionality of export sophistication is geographical distance. Larger distance to other developing countries reduces a developing country's Southbound export sophistication or increases its Northbound export sophistication, which is consistent with the argument of the gravity model in a broad sense. Chapter 5 examines the recent trends of developing countries' terms of trade under the trichotomous global economic hierarchy consisting of developed, emerging, and developing countries. Time-series analysis shows that developing countries, especially those specialising in fuels or minerals, have experienced an improvement in their net barter terms of trade vis-à-vis developed countries over the recent two decades. In contrast, developing countries' net barter terms of trade vis-à-vis China and other emerging countries tends to show negative or trendless behaviour, except those specialising in mineral fuels. In summary, on a global scale, developing countries specialising in fuels or minerals have tended to hold a favourable position, whereas those specialising in agricultural products or manufactures have experienced a less favourable or even unfavourable situation. On the other hand, income terms of trade of all groups of developing countries vis-à-vis the rest of the world, regardless of developed countries, China or other emerging countries, has significantly improved. This indicates developing countries' absolute gains from trade with the rest of the world. However, the rest of the world has comparable improvement in their income terms of trade vis-à-vis developing countries. Therefore, despite the favourable income terms of trade facing developing countries, the condition for global (North-South) convergence does not hold. As a consequence, developing countries have to mobilise more resources to maintain the favourable income terms of trade, which impedes their domestic consumption and investment, and the unequal global exchange has remained. Particularly, this global inequality is magnified by the persistent North-South gap in productivity and technology and by developing countries' high population growth. The global inequality is rooted in the competitive nature of the markets for primary commodities and simple manufactures and the oligopolistic nature of the markets for sophisticated manufactures. In this sense, the findings are in line with the Prebisch-Singer hypothesis.

For most low developed economies in Sub-Sahara Africa (SSA), agriculture has been the main source of livelihood contributing 34% to Gross Domestic Product (GDP) and 64% to employment, either directly or indirectly. Dependence on agricultural commodities for exports has been accompanied by a high degree of price risk in terms of both volatile and declining prices, a phenomenon which has not only affected the way households allocate their resources but also affected their welfare in terms of consumption and poverty. In this thesis, three interrelated issues on market intermediation, diversification and poverty are studied at both household and community level in order to broaden our understanding on how risk affects household resource allocation decisions and subsequently, welfare. In the first part of the thesis, I study the impact of marketing strategies on household coffee incomes in a post- liberalised environment while the second part studies cover both the determinants of household diversification and link between poverty and diversification. Lastly I study the impact of diversification on the conduct of agricultural commodity markets. Though placed in a wider context of development economics, the contribution to the state of the art is that the studies in this thesis combine aspects from agricultural economics, rural development and behavioural/experimental economics to generate results and policy recommendations on poverty policy from the broader point of view.

This dissertation is about public research and development (R&D) subsidies to support private firms doing innovative activities and quantitative impact evaluation of the policy on total factor productivity (TFP) change and additional R&D effort. Public R&D subsidization as a public R&D policy, beside different types of public interventions, has been widely used by governments to stimulate private R&D. These policies aim to fill the gap between the private and social rates of returns by encouraging business enterprises to spend on additional R&D, produce more innovation output and inventions, or change their innovative behavior. These changes can be carried out either individually or in collaboration with other entities. One ultimate goal of R&D policy is increasing the total factor productivity and relative performance both at firm and aggregate levels. This study deals with direct place-based public R&D subsidies and empirically measures the effects of this type of public incentives on productivity growth and R&D input additionality. In order to evaluate the policy effect, a quasi-experimental counterfactual setting for subsidized (treated) and non-subsidized (non-treated) firms can be framed thank to the characteristics and mechanism of the local R&D program in the Province of Trento in Italy. The average treatment effect of the policy on target variables is measured for subsidized units (Average treatment effect on treated: ATET) and for the whole population of the firms (Average treatment effect: ATE), using techniques capable of tackling the problems of endogeneity and selection bias which arise in empirical evaluation studies. Propensity score matching (PSM) and structural modeling methodologies are used to measure the effects of the R&D subsidies on target variables, TFP change and additional R&D expenditure, respectively. The former approach is non-parametric and does not assume a functional form for the effect of policy on R&D and productivity change, while the latter models the optimizing behavior of the firm (agent) and the public agency, searching for an equilibrium in a pre-determined game theoretical framework. Although the PSM method takes advantage of no pre-defined structure assumption, however and in contrary, the structural model with simultaneous equations, takes into account the effect of unobservables on subsidized firms’ selection procedure, beside R&D spillovers effect. In order to design the evaluation framework to estimate ATE and ATET on the target variable of interest (TFP change), we have built a firm-level panel dataset (maximum 5 years of information) constructed by combination and merge of datasets related to public (provincial) R&D policy, firms’ characteristics, firms’ R&D activities and TFP change measures. The time span of the dataset allows us to capture the effects in both short-term and long run, consequently tracing the short and long term effects of the R&D program. This helps us to consider the usual longer effect lag an innovation policy entails, specifically on a target variable such as productivity and a treatment such as innovation incentive, which the effects may take time to be realized in comparison with other types of outcomes and investment policies. The dataset represents the outcome of a long process of combining and merging various datasets related to firms’ financial statements and balance sheet (AIDA: Italian company information and business intelligence) and APIAE’s R&D policy information provided by ISPAT. TFP change and its decompositions, technical efficiency change and technological frontier change are realized using Malmquist Data Envelopment Analysis (DEA) method. DEA takes a system approach towards the firm as decision making unit (DMU) and only applies the input(s) and output(s) measures to calculate the relative (in)efficiency of the firms. Malmquist method based on index theory, captures the (in)efficiency change and the technological frontier movement within a time interval. TFP change measures are calculated by CRS output-oriented DEA dual model using a new package introduced in STATA software and merged into the reference dataset described previously. To sum up, after the formation and construction of dataset by combining and merging different datasets, treatment effect analysis is carried out using PSM nearest neighbor and kernel estimators. The balancing property satisfaction on pre-treatment observable factors (age and size in our setting) is primarily investigated and propensity distribution graphs have been also provided. Taking into account the dataset features, R&D subsidies effect is measured for manufacturing and ICT industries (using 4 techniques to measure both ATE and ATET), beside low-medium technology and high-tech industries classifications (Both ATE and ATET). Moreover, the subsidies effect on TFP measures have also been measured for different categories of selection procedures. Results show heterogenous and mixed effect of R&D subsidies based on different settings of evaluation (sectors and selection categories), targeted outcome, PSM method (different PSM algorithms for nearest neighbor and kernel) and time of the effect (short-term or long run). The complete results have been discussed in detail in the related sections in chapter three. To address the effect of unobservable factors, beside spillover effect on R&D subsidies allocation and the effect on outcome, a structural model is estimated using a cross-sectional dataset. The dataset is formed by merging R&D policy-related (linked to Provincial Law LP 6/99 enforced by provincial agency for the promotion of economic activities :APIAE) dataset and firms’ determinants provided by ISPAT (Statistical institute of Province of Trento).This approach complements the drawbacks due to estimation using PSM methodology. However, the pre-defined functional form for equations is a limitation of this approach. The structural model applied includes application decision, selection (subsidies allocation) and R&D investment equations to be turned into econometric equations for empirical estimation. The context and dataset features allow for different empirical modifications with respect to the benchmark model applied. The results determine the effect of firm (project) characteristics on all stages of the subsidization game. Size, age, exporting status, board size and sector are main factors being investigated. The results show not only there is no additional R&D expenditure, but also some crowding out of subsidies occurs. The base model is determined in such a format which makes it possible to evaluate the spillover effect and spillover rate of R&D spending as well. The results show that on average half (50%) of each euro spent on R&D spill overs. The results shed light on the effects and impacts of a place-based R&D policy on TFP change ,R&D additionality and spillovers, while suggesting policy implications to the local public authorities. Furthermore, the design and process of impact evaluation using two different complementary approaches in a new context on a different target variable (TFP change in addition to classical input additionality variable) can be referred and applied in any policy evaluation related studies. In the following, chapter one deals with the theoretical and empirical reasons for the existence of different public R&D policies based on Schumpeterian growth theory, spillovers effect and tackling market failure. It further provides a review of R&D and innovative activity indices at different levels of analysis (regional, national and international) and reviews the literature of empirical innovation policy evaluation studies related to the effect of R&D policy on additionality. The review concerns both micro and macro perspectives in approaching public R&D policy and the impact of the policy on additionalities and TFP growth. Studies in R&D policy usually concern either the macro growth accounting approach and measure the effect of R&D policies on aggregate growth indices regardless of pointing out to micro foundation effects leading to the aggregate level changes or they only focus on the micro-econometric firm-level evaluation without addressing the relationship between firms’ additional R&D activities and the economic growth. Moreover, the R&D activities expenditure and growth indices at international, EU, national (Italy) and regional (Trento Province) have also been briefly pointed out and tracked over time, to realize the practical importance of R&D incentives. In order to introduce and spot the areas this research addresses, the traditional market failure and the logic and reasons behind public R&D policies (aimed at increasing positive externalities and R&D spillovers) and subsequently different innovation policy instruments and their interaction with firms’ R&D decision making have been reviewed. This provides a comprehensive perspective over the importance and the forms of R&D policies. Chapter two primarily discusses about the effect of R&D subsidies on TFP change. The discussion addresses the relationship between R&D and total factor productivity (TFP) as a channel which subsidies may affect TFP. In addition, other channels and interactions which can explain the effect of R&D subsidies on TFP change and the components of TFP change, will be investigated and discussed. Afterwards, in line with the review of the previous chapter, the empirical literature of studies dealing with evaluation of the effect of R&D subsidies on TFP (as a different outcome variable from additionality variables discussed in the previous chapter) will be reviewed. This theoretical background helps us to shape the R&D policy evaluation framework to investigate the direct casual impact of R&D subsidization policy on target outcomes including TFP change (Chapter 3) and R&D expenditure (Chapter 4). Finally, taking into account the evaluation framework, we hypothesize the research questions based on the theoretical concepts and literature review discussed through the previous and current chapters. Chapter three measures the effect of the provincial R&D subsidies on technical efficiency and technological frontier change as the decomposing elements of productivity change. It empirically measures the impact of R&D subsidies on productivity change using counterfactual treatment effect analysis. Malmquist Productivity Index (MPI) based on the non-parametric method of Data Envelopment Analysis (CRS output-oriented dual DEA model) is applied to measure the productivity change and the disentangled elements of productivity change. The chapter has contributed to the literature in some different aspects. The main focus of this chapter is measuring the effects of R&D subsidies on decomposing elements of TFP, technical efficiency and technological frontier change. In the whole literature, there is only one other similar work in which the effects of R&D subsidies on TFP decomposed components have been assessed. There are few other papers in which they measure the impact of other type of investment subsidies (mainly capital subsidies) on targeted variables of TFP decompositions. However, they all use a parametric approach to measure the TFP components in contrary to non-parametric Malmquist DEA method applied in our study making no predefined assumption about the production function. The subsidies effect evaluation is implemented using both PSM nearest neighbor and kernel methods (to check the robustness) to measure the average treatment effect of R&D subsidies on subsidized (treated) and all (the population) firms labeled as ATET (average treatment effect on treated) and ATE (Average treatment effect), respectively. The analysis is mainly carried out in manufacturing and ICT sectors as two main sectors in which R&D incentives allocations occur. The elaboration on classification of firms in different main industries based on ATECO 2007 system of firms’ economic activity coding has been carried out. It has also been defined and described in detail how 6-digit industry code is categorized into sectors. Another important feature of this study different with a considerable share of empirical literature, is construction of a panel dataset on subsidies allocation and firms’ characteristics which allows us to capture the effect of the policy both in short term and long run (maximum of 5 years). Moreover, the effect of the evaluation based on two different types of selection and allocation procedures (automatic, evaluative (combined with negotiation method) is implemented. The limitations of this chapter imposed by the methodology used, are excluding the effect of unobservable factors on selection process and not taking into account the spillovers effect. Consequently, Chapter’s four structural modeling puts effort to overcome these restrictions and suggest a complementary approach. Chapter four empirically estimates an equilibrium oriented structural game model to investigate the relationship between firms’ characteristics with application cost (application decision equation), spillover rate (subsidization equation) and R&D investment (investment equation). The chapter reviews, modifies and estimates a structural model describing the mechanism through which the R&D subsidization policy influences R&D activity and the R&D spillover rate. The empirical contribution of this chapter is proposing a simplified model of a reference 4-staged game model with a Nash Bayesian Equilibrium (NBE), based on the contextual setting of the region under study and data availability. The advantage of using this structural model is the ability to assume spillovers effect. This optimization approach relaxes the incapability of evaluation approach used in Chapter three to assume the presence of spillover effect due to the violation of Stable Unit Treatment Value Assumption (SUTVA). Moreover, chapter four takes into account the effect of unobservables on selection procedure and targeted variable, while in chapter three the unobservables are assumed uncorrelated with selection (subsidy) variable and the outcome. Nevertheless, opposed to structural modelling, the method used in chapter three does not assume any parametric form to evaluate the impact. Hence, chapter three and chapter four complement each other in measuring the impact of R&D policy on targeted variables. The empirical evaluations and results of both final chapters are explained and concluded in the related essays. Moreover, the features and contribution of chapters will be restated in the abstract at the beginning of each chapter.

Local governments, ‘urban-booster’ commentaries and some academic approaches have increasingly focused on the idea of the ‘fashion city’ as a strategic factor for the economic development, growth and regeneration of major and minor cities across the world. Nowadays, in addition to established fashion’s world cities, there has been a proliferation of new fashion centres that have been termed as ‘second-tier’ cities of fashion. The growing and crucial importance of fashion in urban development strategies, together with the current diversity and variety of fashion centres, has created the need to broaden the knowledge of what constitutes a fashion city. To this day, either in academic or local policy field, little attention has been paid to defining the key elements that form a contemporary fashion centre. In light of these considerations, the aim of the present dissertation is to contribute to furthering the understanding of the actual meaning and significance of this concept and to possibly identifying distinctive models of fashion centres. Furthermore, the research seeks to explore the best suited methodologies to analyse the complexity and heterogeneity of contemporary fashion cities. The research is structured in four chapters, which address three main objectives. The first objective is to systematize the existing body of cross-disciplinary academic literature on the topic into a precise theoretical framework. In this regard, Chapter 1 presents a state of the art of fashion’s relation with cities by adopting a specific ‘creative approach’, which primarily focuses of fashion design as a cultural and creative industry (CCI) and on fashion designers as an example of the wider ‘creative class’. This analysis directs attention to a particular example of fashion centre that has been termed as the ‘creative fashion city’. The second objective is to develop an analytical framework to address the current heterogeneity of contemporary fashion centres. Chapter 2, drawing upon an extensive analysis of fashion’s world cities and ‘second-tier’ cities of fashion, suggests a framework of analysis for thinking about the diverse nature of fashion’s relation with the urban. It identifies multiple models of fashion’s world cities, as well as contrasting patterns in the development of newer fashion centres. Most importantly, through the adoption of Weber’s ideal type approach, it proposes three ideal types of fashion cities (‘manufacturing’, ‘design fashion’ and ‘symbolic’), which function as heuristic device to address the distinctive characteristics of fashion centres and to discuss future development pathways. The final and third objective is to understand how ‘real’ fashion cities can be studied, analysed and plotted on the ideal type model. To meet this objective, Chapter 3 and Chapter 4 present two analyses of London from a ‘supply’- and ‘demand-side’ perspective. The first one is based on the execution of 23 semi-structured interviews with key actors from London’s fashion ecosystem, as well as statistics and policy documents, to analyse the ‘material’ elements that underlie the development, transformation and current nature of this fashion centre. The second one explores the meaning embedded in two samples of around 30,000 tweets, which were collected at different times, to highlight the ‘symbolic’ representation of London as a fashion city on the social media platform Twitter. Both the ‘supply’- and ‘demand-side’ analyses draw a picture of London as a fashion centre that tends towards the ideal type of the ‘symbolic fashion city’. The present dissertation has implications either for the academic and local policy field. It contributes to investigating the importance of different kinds of position that fashion plays in urban economies, drawing attention to fashion’s qualities as rather more than a conventional urban CCI. There emerges a growing emphasis on the symbolic economy as a tool for cementing the reputation of contemporary fashion centres, either specialised in manufacturing, fashion design or image-making activities. Furthermore, the ideal type approach complements and extends the now very familiar division between ‘fashion’s world cities’ and ‘second-tier cities’ and shifts away from the simplistic ‘tool-kit’ approach that has sought to promote new fashion centres as developing versions of ‘models’ set by established fashion’s world cities. In this respect, the accentuated ideal type of the ‘symbolic fashion city’ points to the risks of what can described as a ‘hollowing-out’ of the fashion city, which is detached not only from making and designing clothing but also from urban fashion cultures. Thus, what is important is not about fixed strategies for the development of a fashion centre, but the need for ad-hoc fashion policies specifically adapted to different historical and cultural local contexts.

In this research we analyze the main drivers of the growth of cities, according to their sizes: Mega, Big, Midsize, etc., applying a cross-country analysis that involves about 114 countries in a period of time of forty years (1960-2000). We look for differences in the underlying factors of cities growth particularly among large agglomerations, which are attracting great interest among policy makers. Secondly, we have tried to verify if the growth of cities is linked to urbanization processes that encompass economic structural transformations (performing urbanism), or if their growth is linked to dynamics that disadvantage further economic development (non-performing urbanism). Once considered the relation between the evolution of cities sizes and the shape of the urban structure (using the Zipf’s parameter and other urban variables) we analyze the quality of this structure as a “new†deep determinant of economic growth. This is why, in the last part of the research, we look for possible relations between the quality of the urban structure and economic growth. Our results indicate that growth in very large agglomeration tends to be “non-performing†and that the urban structure which fits better with economic growth is characterized by high urbanization rates but low hierarchical structures.

Nowadays, entrepreneurship has received a large amount of attention in such studies as economics, sociology, finance, and public policy. Furthermore, The European Union and national government have implemented several policy interventions aimed to encourage new firm formation. Entrepreneurial education is now reinforced in schools, colleges, and universities. Nevertheless, entrepreneurship remains to be a black box. Making everyday decisions on firm organization and management is a complex process, which depends on how entrepreneurs perceive the environment and their own entrepreneurial abilities. These perceptions influence firm behavior that can be represented by combination of different actions. The main goal of this doctoral thesis is to examine how entrepreneurial perceptions and learning influence entrepreneur preferences for certain actions and thus, how they affect firm performance. The first essay aims to understand whether the effectiveness of the policy is altered by the behavioral assumption that entrepreneurs are overconfident about their entrepreneurial abilities and tend to be overoptimistic in the evaluation of future prospects. The essay applies the agent-based model that is a modified version of the financial fragility model of Delli Gatti et al. (2005). The simulation results suggest that the presence of misperceptions of entrepreneurial abilities influence the policy outcomes. The main purpose of the second essay is to reveal how entrepreneurial perceptions of competitive environment influence their preferences for competitive strategies. Competitive advantages of firms are defined on the basis of Porter’s (1980) model of generic strategies — differentiation and cost leadership. The results of the analysis suggest that perceived threat of competition pushes firms to take actions. The preferences for actions are explained by available resources such as human capital. The third essay aims to evaluate the impact of capital grants given to microenterprises operating in the Province of Trento, Italy in 2009 and 2010. The last essay empirically illustrates how lack of restrictions imposed on the amount of possible subsidy requests and fixed eligibility criteria has invoked subsidy-seeking behavior of firms. The results from econometric analysis suggest that subsidies have not been able to improve firm performance or to increase firm size in 2011. However, a positive effect of subsidies on the propensity to invest in training and in marketing and advertising in 2012 has been detected.

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Coesione e competitività sono i principali obiettivi della politica regionale Europea. È però possibile che investimenti in competitività possano beneficiare maggiormente le regioni più sviluppate, a discapito della coesione. Si tratta di una contraddizione? In questo lavoro si risponde a questa domanda approfondendo tre argomenti. Il primo riguarda le determinanti della crescita regionale. Il secondo interessa il ruolo degli spillover di conoscenza per l’innovazione regionale. Il terzo è relativo al contributo delle infrastrutture di conoscenza all’attività innovativa regionale. I principali risultati possono essere sintetizzati in questa maniera. Una più alta crescita nella regioni meno sviluppate è importante ma non sufficiente a garantire convergenza. La crescita, nel lungo periodo, è determinata dagli investimenti in conoscenza, che producono rendimenti crescenti. La mancanza di sviluppo nelle regioni più arretrate può essere attribuita a questi divari di conoscenza, non sempre facili da colmare. Le esternalità alla base dei rendimenti crescenti sono estremamente localizzate e non si diffondono facilmente nelle economie. D’altra parte la conoscenza non si produce solamente con investimenti in ricerca. La promozione della ristrutturazione economica regionale verso modelli basati sulla conoscenza dovrebbe dedicare particolare attenzione alle fonti esterne di conoscenza, quali, accanto alle università, i servizi ad alto contenuto di conoscenza. / Cohesion and competitiveness are the two main objectives of the EU regional policy. It seems however that improving competitiveness will benefit developed regions more, implying a less cohesive Europe. Is that a contradiction? This work answers this question by studying three related topics. The first concerns the determinants of regional growth in Europe. The second is about the importance of interregional knowledge spillovers for the regional innovative activity. The third is related to the way knowledge infrastructures can shape regional innovative activity. The main results can be summarized as follows. The higher growth in least developed region is important but not sufficient to catch-up. Growth, in the long-run, is determined by investments in knowledge, which produce increasing returns. The lack of development of lagging regions could be accordingly ascribed to the existence of knowledge gaps which are not as easy to be filled. Knowledge externalities, the essence of the more than proportional returns, are extremely localized and do not necessarily spread across the economies. However knowledge is not only produced through R&D. The promotion of economic restructuring of lagging regions toward a knowledge-based economy should deserve special attention to external knowledge sources like, alongside universities, Knowledge Intensive Business Services.

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