As policymakers refocus on growth, the ability to take a firm-level view is key to disentangling the various factors at the root of competitiveness, and thus to designing appropriate policies. Firm-level data provides critical information for the design of appropriate competitiveness measures that complement traditional macro analysis. More work remains to be done assembling firm-level information, but the variance of the distribution of firm characteristics already conveys important information in addition to standard averages. New indicators should be developed to translate the distribution of firm characteristics into indicators of competitiveness designed to capture not only average performance but also the heterogeneity of firm performance. This Policy Contribution builds on ongoing research within EFIGE (www.efige.org), a project to help identify the internal policies needed to improve the external competitiveness of the European Union.

This article analyses how regional employment growth in Germany is affected by related variety, unrelated variety and the functions a region performs in the production process. Following the related variety literature, we argue that regions benefit from the existence of related activities that facilitate economic development. However, we argue that the sole reliance of related variety on standard industrial classifications remains debatable. Hence, we offer estimations for establishing that conceptual progress can indeed be made when a focus for analysis goes beyond solely considering industries. We develop an industry-function based approach of related and unrelated variety. Our findings suggest that related variety only in combination with a high functional specialization of the region facilitates regional growth in Germany. Additionally, also unrelated variety per se fails to wield influences affecting development of regions. It is rather unrelated, but functionally proximate variety in the groups “White Collar” and “Blue Collar Workers” positively affects regional employment growth.

The U.S. share of world merchandise exports has declined sharply over the last decade. Using data at the level of detailed industries, this paper analyzes the decline in U.S. share against the backdrop of alternative measures of the competitiveness of the U.S. economy. We document the following facts: (i) only a few industries contributed to the decline in any meaningful way, (ii) a large part of the drop was driven by the changing size of U.S. export industries and not the size of U.S. sales within those industries, (iii) in a gravity framework, the majority of the decline in the U.S. export share within industries was due to the declining U.S. share of world income, and (iv) in a computed structural measure of firm productivity, average U.S. export productivity has generally maintained its high level versus other countries over time. Overall, our analysis suggests that the dismal performance of the U.S. market share is not a sufficient statistic for competitiveness.

Local economic development policies worldwide perceive business incubation as an effective measure to promote regional growth through the support of young and innovative ventures. The common assumption is that incubation promotes firm growth, in particular after these firms graduated from their incubator organizations. This article investigates the long-term performance of 324 graduate firms from five German business incubators (incubated between 1990 and 2006) after they have (successfully) completed their incubation. The present study does not suffer from a survivor bias, meaning that performance data of non-surviving firms is also included. Using employment and sales measures as performance indicators, this study contributes to our knowledge with regard to long-term incubator firm performance after graduation. While in the first years after graduation there is significant growth of formerly incubated firms, further results do not support the presumption of continuous firm growth beyond incubation. A minority of graduate firms exhibits a strong increase in performance, but the majority of firms do not experience considerable growth.

The present paper compares expected inflation to (econometric) inflation forecasts based on a number of forecasting techniques from the literature using a panel of ten industrialized countries during the period of 1988 to 2007. To capture expected inflation, we develop a recursive filtering algorithm which extracts unexpected inflation from real interest rate data, even in the presence of diverse risks and a potential Mundell-Tobin-effect.

The extracted unexpected inflation is compared to the forecasting errors of ten

econometric forecasts. Beside the standard AR(p) and ARMA(1,1) models, which

are known to perform best on average, we also employ several Phillips curve based approaches, VAR, dynamic factor models and two simple model avering approaches.

Combining forecasts, we analyse the role of information flow in computing short-term forecasts up to one quarter ahead for the euro area GDP and its main components. A dataset of 114 monthly indicators is set up and simple bridge equations are estimated. The individual forecasts are then pooled, using different weighting schemes. To take into consideration the release calendar of each indicator, six forecasts are compiled successively during the quarter. We found that the sequencing of information determines the weight allocated to each block of indicators, especially when the first month of hard data becomes available. This conclusion extends the findings of the recent literature. Moreover, when combining forecasts, two weighting schemes are found to outperform the equal weighting scheme in almost all cases. Compared to an AR forecast, these improve by more than 40% the forecast performance for GDP in the current and next quarter.

Assessing the impacts of bank mergers on small firms requires separating borrowers with single versus multiple banking relationships and distinguishing the three alternatives of “staying,” “dropping,” and “switching” of relationships. Single-relationship borrowers who “switch” to another bank following a merger will be less harmed than those whose relationship is “dropped” and not replaced. Using Belgian data, we find that single-relationship borrowers of target banks are more likely than other borrowers to be dropped. We track postmerger performance and show that many dropped target-bank borrowers are harmed by the merger. Multiple-relationship borrowers are less harmed, as they can better hedge against relationship discontinuations.

The development of ‘standards’ for the application of matching algorithms in empirical evaluation studies is still an outstanding goal. The first step of the matching procedure is the choice of an appropriate distance function. In empirical evaluation situations often the sample sizes are small. Moreover, they consist of variables with different scale levels which have to be considered explicitly in the matching process. A simulation is performed which is directed towards these empirical challenges and supplements former studies in this respect. The choice of the analysed distance functions is determined by the results of former theoretical studies and recommendations in the empirical literature. Thus, two balancing scores (the propensity score and the index score) and the Mahalanobis distance are considered. Additionally, aggregated statistical distance functions not yet used for empirical evaluation are included. The matching outcomes are compared using non-parametric scale-specific tests for identical distributions of the characteristics in the treatment and the control groups. The simulation results show that, in small samples, aggregated statistical distance functions are the better choice for summarising similarities in differently scaled variables compared to the commonly used measures.