The European Union is the world's largest economic entity, yet its ability to design and implement effective economic policies is not commensurate with its size. It is lagging, for example, in terms of effective policies promoting productivity, growth, scientific research or technological innovation. The Eurozone debt crisis has provided a sharp and painful reminder that the European Union must adopt a new approach to designing its economic policies and coordinating them with the policies of its Member States.

At the same time, while the field of economics in Europe has seen impressive growth in terms of global impact, and in the number of researchers and funding, Europe still lags behind the US in terms of research productivity, and European research remains fragmented across its Member States. According to recent research, the share of articles in the top economics journals published by European researchers represents 34 per cent of the total production of articles in the world, while the US amounts to 53.5 per cent.1 The contrast is even sharper when the citation impact of these publications is taken into account. In terms of share of citations, the US represents 70.8 per cent while the EU share is 28.4 per cent, which illustrates the considerably higher impact of US research in economics.

Developing a competitive and open European research area is essential for growth and to the progress of European integration, because research is a key factor of growth, and competition among researchers provide them with incentives for cooperating across borders. However, different languages, a diversity of academic traditions and a variety of informal barriers often inhibit the free flow of research funding, the mobility of academic talent and, as a result, the efficient allocation of research and development funding. In times of financial restraint the latter becomes particularly important. In this context, research grants, especially if they are allocated across national borders (e.g., by the European Research Council, ERC), can provide valuable tools to circumvent limits to integration and consequently to enhance the exchange of ideas. In fact, the relationship between openness and successful research funding is reciprocal and internationalization can benefit national and regional funding, by, for example, permitting the inflow of foreign resources.

Abstract

This chapter provides an overview of a growing literature on the emergence of dual labour markets and their persistence in some EU countries, as well as the impact that dualism has on a large range of labour market dimensions including, among others, job and worker flows, (overall and youth) unemployment, wage setting, training, labour mobility, household formation, and technology adoption. A distinctive feature of the chapter is that it places the accumulated evidence on these issues in a general equilibrium framework, which helps understand why dual labour markets have performed so poorly since 2008, and also to identify promising avenues of research for the near future. The chapter also evaluates recent reforms and reform proposals (single and unified labour contracts) to eliminate the undesirable consequences of excessive dualism in the labour market.

Introduction

This COEURE Survey deals with the consequences of dual labour markets, namely labour markets where workers are entitled to different employment protection depending on the contract they hold, and where these differences are large. The effect of dualism on several labour-market dimensions has been widely analysed in the literature but many of these issues have strongly reemerged during the recent crisis due to the poor performance of countries subject to strong dualism. In this survey we review the main lessons drawn from past experience with these labour market regimes, where they originate from, why they are so difficult to change, why they have failed during the Great Recession and the subsequent sovereign crisis, what reform proposals have been posed and which ones are more likely to work. In addition to reviewing the accumulated stock of knowledge on these issues, we place them in a general equilibrium framework to understand which ones constitute the most promising avenues of research for the near future. The rest of the survey is organized as follows. Section 2.2 deals with the historical origins of dual labour markets. Section 2.3 considers conditions under which labour contracts become too different, leading to optimal versus nonoptimal arrangements of stability and flexibility in the labour market. Section 2.4 looks at the performance of dual labour markets since the onset of the Great Recession. Section 2.5 documents the case of Spain, as an epitome of a dual labour market.

Abstract

The Big Data Era creates a lot of exciting opportunities for new developments in economics and econometrics. At the same time, however, the analysis of large datasets poses difficultmethodological problems that should be addressed appropriately and are the subject of the present chapter.

Introduction

‘Big Data’ has become a buzzword both in academic and in business and policy circles. It is used to cover a variety of data-driven phenomena that have very different implications for empirical methods. This chapter discusses some of these methodological challenges.

In the simplest case, ‘Big Data’ means a large dataset that otherwise has a standard structure. For example, Chapter 13 describes how researchers are gaining increasing access to administrative datasets or business records covering entire populations rather than population samples. The size of these datasets allows for better controls and more precise estimates and is a bonus for researchers. This may raise challenges for data storage and handling, but does not raise any distinct methodological issues.

However, ‘Big Data’ often means much more than just large versions of standard datasets. First, large numbers of units of observation often come with large numbers of variables, that is, large numbers of possible covariates. To illustrate with the same example, the possibility to link different administrative datasets increases the number of variables attached to each statistical unit. Likewise, business records typically contain all consumer interactions with the business. This can create a tension in the estimation between the objective of ‘letting the data speak’ and obtaining accurate (in a way to be specified later) coefficient estimates. Second, Big Data sets often have a very different structure from those we are used to in economics. This includes web search queries, real-time geolocational data or social media, to name a few. This type of data raises questions about how to structure and possibly re-aggregate them.

The chapter starts with a description of the ‘curse of dimensionality’, which arises from the fact that both the number of units of observation and the number of variables associated with each unit are large. This feature is present in many of the Big Data applications of interest to economists. One extreme example of this problem occurs when there are more parameters to estimate than observations.

Economics has emerged as a major discipline today of interest to all because of its impact on our day-to-day life. What has been achieved so far has been truly impressive, although the discipline is not as successful as one would expect. Notwithstanding what mainstream economics does or strives for, it does not really meet the criteria to be called a natural science yet. This book is an attempt to steer it in that direction.

Although natural sciences, such as physics, chemistry, biology, or geology employ logic and mathematics (as a condensed form of logic), it is never the sole ingredient. Stepwise observations are organized in a logical fashion, often with the help of tentative or approximate hypotheses, and both the existing observations and predicted outcomes are carefully compared. The understanding of the next level or of similar but different systems grows progressively, based on the successful ideas or an understanding developed earlier. Naturally, there is interdependence in natural sciences as a consequence of this kind of development. In general, precise knowledge, successful ideas, or techniques developed in one area of the natural sciences become easily translated into another.

This interdependent structure of research in the natural sciences also gets reflected in the graduate level course structure for students in their respective disciplines. Students of one major discipline of the natural sciences have to learn the basic and established concepts in other disciplines: Physics majors learn concepts of chemistry, biology, or geology; biology majors learn basic concepts of physics and chemistry, along with others. This practice is somehow not there yet for the social sciences; the graduate students here do learn mathematics and statistics but not the basic concepts of physics, chemistry, or biology. Personal interests are, of course, exceptions and are not counted here!

To many, this is the main reason why economics, which also started becoming formalized much later compared with most other branches of the natural sciences, could not boast of the spectacular successes achieved by other disciplines. Among others, econophysicists believe in the need for a similar mutation of ideas from economics and physics, for the healthy evolutionary growth in both.

Abstract

This chapter shows how the Schumpeterian growth paradigm can be used both to shed light on various aspects of the growth process which cannot be easily understood using alternative paradigms, and also to think about policies to foster innovation-led growth in a developed economy. In particular it will: (i) look at the relationship between growth and competition; (ii) shed light on how growth relates to firm dynamics and the size distribution of firms; (iii) revisit the debate on how growth relates to income inequality and social mobility; and (iv) discuss the role of the state in fostering innovation-led growth, and question the design and limits of R&D subsidies, or the desirable scope for patent protection, or whether the government should provide sectoral state aids or instead limit itself to pure horizontal targeting.

Introduction

There is a broad consensus among most European leaders and in Brussels on the importance of structural reforms to foster innovation-based growth in Europe. However, this consensus has not reached the European public at large. One recent example is France, where the timid reforms proposed by the Economy Minister have met opposition from all political parties. So often do we hear that structural reforms amount to austerity, and therefore are detrimental to growth and employment. Similarly, a commonly held view is that going for supply side policies (structural reforms or fiscal devaluations aimed at fostering such reforms) necessarily means that we have decided to ignore the demand side. We also hear that a fiscal system conducive to innovation and entrepreneurship would necessarily aggravate inequality and reduce social mobility. The purpose of this chapter is twofold: first, to bring the reader up to speed with recent research in the Economics of Innovation and Growth; second, to provide the reader with the theoretical and empirical background to think about growth policy design in EU countries.

We should emphasize right away that this chapter is opinionated in the sense that it reflects our own biases and uses the lenses of our own work. However, the reader should feel free (and is welcome) to disagree and take issue with the models, analyses and statements outlaid in the next sections.

Abstract

This chapter surveys the fundamental forces that drive the formation and size of cities. We discuss the different types of agglomeration economies generated by a dense web of activities, with special emphasis on the benefits associated with the clustering of highly skilled workers. The distribution of activities within cities results from the trade-off between commuting and housing costs. We show that in this trade-off commuting costs are the cause and land rent is the consequence. The land rent capitalizes the advantages associated with proximity to particular urban locations such as employment centres. We identify the main sources of inefficiency in various urban policies implemented in Europe. Special attention is paid to the regulation of the land market and the pricing of urban transport.

Introduction

The main distinctive feature of a city is the very high density of activities and population, which allows agents to be close to one another. Households and firms seek spatial proximity because they need to interact for a variety of economic and social reasons on a daily basis. For example, individuals want to be close to each other because they like to meet other people, learn from others, and have a broader range of opportunities. Hence, the main reason for the existence of cities is to connect people. This need is gravitational in nature in that its intensity increases with the number of agents set up nearby, and decreases with the distance between them. Contrary to an opinion widespread in themedia, and despite the Internet and other new communication devices, face-to-face contact remains important, at least for a certain number of human and economic activities. To understand why this is so, one has to remember that information transferred through modern communication tools must be structured according to clearly defined schemes and codes known to all. Only formal and precise information can be transmitted this way. In contrast, information that is difficult to codify can often be conveyed only through face-to-face contact.

In the industrial era, cities have enabled transport costs between large and connected production plants to decrease substantially. Today, cities are the cradles of new ideas that benefit firms of very different sizes. But this is not new; cities are – and have been for centuries – the source of productivity gains as well as technological and cultural innovations (Hohenberg and Lees, 1985; Bairoch, 1985).