The EMU in Europe was created for a variety of political and economic reasons. From an economic perspective, the EMU was conceived as a complement and component of the EU single market. Exchange rate risks and transaction costs that were associated with different national currencies, constituted barriers to ‘intra-EU’ trade, which the single market programme was designed to eliminate. The removal of physical, technical and monetary barriers was expected to boost trade and financial integration amongst the member states (European Commission 1990).
The countries or regions choosing to participate in a currency arrangement define the borders of a specific OCA. The EMU, which is ‘purported’ to be an OCA, has been galvanised by anticipated macroeconomic benefits. However, most economists agree that there is difficulty in quantifying the costs and benefits of a currency union. Thus, Chapter 2 features the broad range of research that has attempted to investigate these costs and benefits at the macroeconomic level – with particular emphasis on financial integration, OCA qualification and international trade implications. Most importantly, what is evident is that the microeconomic impact has been largely ignored – specifically the impact on industries and firms.
Section 2.1 provides a brief historical summary of the motivation to launch the euro. The significant stages of EMU implementation are outlined, which highlights the unprecedented social, political and financial structure of the single currency. One of the most important objectives of the EMU was to enhance competition across the EU, which commenced with the SMP. This was to be accomplished by the removal barriers to trade and eventually currency transaction costs; where the costs savings are re-invested by the member states – stimulating economic activity and increasing competition. In addition, and quite importantly, the Lisbon agenda [launched in March 2000] was a comprehensive 10-year strategy covering product, labour and capital market reforms; aimed at transforming the EU into the most competitive and dynamic knowledge-based economy in the world (see European Commission 2005).
Section 2.2 outlines the theory of OCAs, which is motivated by macroeconomic benefits – consequently driving microeconomic value through enhanced competition in an economy. OCA theorem continues to remain the implicit reference framework to assess the real consequences of monetary integration, which was initiated by Robert Mundell in 1961. The theory of OCAs asserts that a single currency zone must have symmetry across shocks and structures. In terms of OCA
properties, optimality is explored with respect to mobility of factors of production and labour, including price and wage flexibility; trade openness (see McKinnon 1963); industrial diversification in production and consumption (see Kenen 1969); fiscal transfer management structures; homogeneity of preferences; and solidarity of monetary management (i.e. a shared vision) between member states. There is still much debate about whether member states of the EMU qualify under the OCA criteria.
Section 2.3 discusses the extensive body of work on international trade and its impact on currency unions. Andrew K. Rose is the most prominent economist who has shone a light on this area of research. The overwhelming majority of the empirical analysis infers that the effect that the EMU in Europe has had on trade is significant and economically important. Section 2.5 focuses on the IO empirical literature, which is concerned with the microeconomic implications of competition. The SCP paradigm surmises that market performance is the success of a market in producing benefits for consumers. Market structure consists of those factors that determine the competitiveness of a market, which ultimately affects market performance through the conduct (i.e. behaviour) of firms.
The SCP paradigm is the premise for which competition (specifically the existence of a market power) is assessed across markets, countries and regions. Competition which is typically measured through market concentration (structure), can foster collusion (conduct); and as a result monopoly pricing (performance). Interestingly, the comprehensive body of work that exists precludes a specific focus of the impact of the euro on competition.
Chapter 3 explores competition and the impact on market structure. Section 3.1 briefly highlights four key market structures: perfect competition, monopolistic competition, monopoly and oligopoly; that are used extensively in microeconomics to explain the theory of a firm and corresponding role in the competitive process. Section 3.2 encapsulates the Cournot oligopoly model to identify the equilibrium number of firms. An important feature of market structure is industry concentration, where the number and size distribution of firms within a specified market indicates the depth of concentration. The microeconomic model defined in Section 3.2 is expressed in context to the EU in Section 3.3. In essence, the price transparency introduced as a result of the EMU is believed to enhance competition [and reduce market concentration] across the member states.
All concentration measures vary in sophistication, seeking to translate the information on the number and size distribution of firms (presented by a concentration curve) into a single value.
Section 3.4 discusses in detail the HHI, which is the most commonly used indicator of market concentration. Market participants are assumed to be indicative of competitive conditions when represented by extraneous (low) values when calculating concentration indices. Generally, concentration indices would be larger the fewer the number of firms and the more unequal the distribution of market shares among them. Hence, market concentration makes reference to the structural characteristics of the business sector and is the degree to which production in an industry or economy is dominated by a few large firms. Traditionally, market concentration was assumed to be a symptom of market failure. However in today’s context, it is mostly seen as an indicator of superior economic performance.
The most direct route to market concentration is where the consolidation of production occurs resulting in fewer firms due to M&A. Firm consolidations that strengthen or create a dominant player in the market is central to merger policy theory. Competition policy in the EU primarily aims to prevent negative effects being incurred on welfare. Competition is empirically assessed by government authorities globally through the estimation of market concentration pertaining to a defined economy [i.e. industry sector]. The HHI plays a significant role in EU antitrust legislation – reinforcing its validity as an important indicator if competition as is discussed in Section 3.5. The empirical literature pertaining to competition and the EMU in Europe is scarce. The minimal research that does exist is discussed briefly in Section 3.6. The banking sector has been extensively explored namely due to the financial integration implications of the euro.
Chapter 4 employs the HHI (an indicator of market structure) that is calculated across eight different market definitions to assess the implications of the European OCA on competition. The HHI is a function of firm, industry and country characteristics, and hence the determinants of market concentration are summarised under Section 4.2. This includes the extensive body of research that has been published over the last sixty years relating to the structural variables that influence a firm’s conduct.
Circa 1980, most industrial economists approached market concentration as an important determinant of the manner in which firms establish pricing and other competitive weapons. However, very little regard was given to the fundamental determinants of market concentration itself. Market structure was somehow presumed to be a consequence of a few basic conditions; such as economies of scale (relative to the size of the market) and exogenous consumer preferences. These two assumptions were not thought to be fundamentally important, with the exception of
economics of scale – if found to be relatively large, would most likely result in a few firms existing in the defined market; and as a result, may confer a degree of monopoly power.
In order to assess the impact on competition of the introduction of the euro [on member states], the HHI is calculated in Section 4.3 across eight different market definitions. The mean HHI increased during the euro-era, suggesting that competition has in fact reduced as a result of the EMU. However the concentration curves generated suggest that the cumulative market share [of the top ten firms] has shifted to the right, implying an increase in competition. This is despite the increase in the number of firms across Europe. However, it is important to note that the rate of growth at which this occurred during the euro-era has reduced significantly.
Section 4.3 also proposes a market concentration model that includes the following firm and industry level determinants: initial capital requirements, lagged profitability, lagged industry growth, economies of scale; and country indicators measuring the economic wealth, stability and sustainability. Two dummy variables were also included in order to capture each country’s membership in the EU and EMU.
The market concentration model is constructed in Section 4.5 using six different estimation techniques; in order to ensure that the robustness and sensitivity of the model has been optimised.183 The Breusch-Pagan Lagrange Multiplier test identified that the RE model is a more suitable fit than OLS estimation. The Hausman test confirmed that the coefficients generated under a FE model are more efficient that that of a RE estimation. Hence, the model of best fit is of a FE estimation. Irrespective of which estimation method is applied, the EURO_MEMBER variable is statistically significant across all eight different market definitions. When including instrumental variables to the model in order to remove the endogeneity of the asset-to-sales ratio and MES, the
EURO_MEMBER variable remains statistically significant. However, an extremely long lag
structure is required to meet the requirements of the Arellano-Bond test; using both difference GMM and system GMM. Section 4.6 concludes that the EMU has clearly stimulated competition positively across the European region.
Lastly, Chapter 5 explores the impact on firm profitability resulting from the introduction of the euro. The model for firm profitability is defined in Section 5.2. An extensive body of research is discussed in detail that outline firm, industry and country characteristics that affect firm
183 The estimation techniques include (1) OLS with augmented time dummies, (2) OLS without augmented time dummies, (3) Panel with RE, (4)
profitability. Section 5.3 provides a correlation matrix of the eight different geographic definitions of market concentration and three firm profitability metrics – ROS, ROA and ROE. The findings suggest a mostly positive relationship; with respect to the country-defined HHI.
The concentration-efficiency nexus is further discussed, followed by the mean profitability summarised by geographic sector [and time period]. All three profitability measures have mostly declined across all three zones over the three time periods. The mean profitability [by year] for the euro-zone is further illustrated, which show unsurprisingly that they are closely correlated. The market concentration of each firm [by year] is further classified into three categories: low HHI, medium HHI or high HHI. The corresponding mean profitability for ROS, ROA and ROE is illustrated by time period [specifically for the euro-zone]. This shows that firm profitability is consistently decreasing throughout each time period.
Section 5.4 proposes a firm profitability model that includes the following independent variables (i.e. determinants): GDP per capita, lagged HHI, MES, industry growth and asset-to-sales ratio. Two dummy variables are also included in order to capture each country’s EU and EMU membership.
The profitability model is constructed and the findings are discussed in Section 5.5. The models (OLS, OLS + t, panel with FE and panel with RE) were generated for the three profitability measures: ROS, ROA and ROE. This reason for this was to ensure that the robustness and sensitivity of results had been taken into consideration. Initially, all models highlighted that being a member of the EU and EMU results in an increase in firm profitability. However, when generating the profitability model using GMM estimation, only the EURO_MEMBER variable is statistically significant across all three profitability measures. Also, the ROS variable becomes negative; suggesting that firm profitability has decreased as a result of member states participating in the EMU.