This paper presents a method to conduct early estimates of GDP growth in Germany. We employ MIDAS regressions to circumvent the mixed frequency problem and use pooling techniques to summarize efficiently the information content of the various indicators. More specifically, we investigate whether it is better to disaggregate GDP (either via total value added of each sector or by the expenditure side) or whether a direct approach is more appropriate when it comes to forecasting GDP growth. Our approach combines a large set of monthly and quarterly coincident and leading indicators and takes into account the respective publication delay.

Distortionary effects of inflation on relative prices are the main argument for inflation stabilization in macro models with sticky prices. Under indexation of non-optimized prices, those models imply a nonlinear and dynamic impact of inflation on the cross-sectional price dispersion (relative price or inflation variability, RPV). Using US sectoral price data, we estimate such a relationship between inflation and RPV, also taking into account the endogeneity of inflation by using two- and three-stage least-squares and GMM techniques, which turns out to be relevant. We find an effect of (expected) inflation on RPV, and our results indicate that average (“trend”) inflation is important for the RPV-inflation relationship. Lagged inflation matters for indexation in the CPI data, but is not important empirically in the PPI data.

Im Herbst 2012 stellen sich Lage und Aussichten für die deutsche Konjunktur deutlich schlechter dar als vor einem halben Jahr. Hauptgrund dafür sind die immer neuen Schübe der Schulden- und Vertrauenskrise im Euroraum. Auch die Weltkonjunktur hat generell an Kraft verloren.

Die Produktion hat in Deutschland in der ersten Jahreshälfte weiter zugelegt. Auch im dritten Quartal 2012 dürfte sie zunehmen, und zwar um 0,4%. Für das Winterhalbjahr 2012/ 2013 deutet sich dann allerdings eine Verlangsamung des konjunkturellen Fahrtempos an.

Alles in allem wird das reale Bruttoinlandsprodukt 2012 voraussichtlich um 0,9% und 2013 um 0,8% zulegen. Das 66%-Prognoseintervall liegt für das Jahr 2012 zwischen 0,7% und 1,1%; im Jahr 2013 reicht es von –0,2% bis 1,8%.

The paper accounts for the determinants of inward foreign direct investment in business services across the EU-27 regions. Together with the traditional variables considered in the literature (market size, market quality, agglomeration economies, labour cost, technology, human capital), we focus on the role of forward linkages with manufacturing sectors and other service sectors as

attractors of business services FDI at the regional level. This hypothesis is based on the evidence that the growth of business services is mostly due to increasing intermediate demand by other services industries and by manufacturing industries and on the importance of geographical proximity for forward linkages in services.

To our knowledge, there are no studies investigating the role of forward linkages for the location of FDI. This paper aims therefore to fill this gap and add to the FDI literature by providing a picture of the specificities of the determinants of FDI in business services at the regional level. The empirical analysis draws upon the database fDi Markets, from which we selected projects having as a destination NUTS 2 European regions in the sectors of Business services over the period 2003-2008. Data on FDI have been matched with data drawn from the Eurostat Regio

database. Forward linkages have been constructed using the OECD Input/Output database. By estimating a negative binomial model, we find that regions specialised in those (manufacturing) sectors that are high potential users of business services attract more FDI than other regions. This confirms the role of forward linkages for the localisation of business service FDI, particularly in the case of manufacturing.

We propose a new approach to measuring the effect of unobservable private information on volatility. Using intraday data, we estimate the effect of a well-identified shock on the volatility of stock returns of European banks as a function of the quality of public information available about the banks. We hypothesize that as publicly available information becomes stale, volatility effects and its persistence increase, as private information of investors becomes more important. We find strong support for this idea in the data. We further show that stock volatility is higher just before important announcements if information is stale.

This study investigates the effect of temporary agency work on the user firm’s productivity. We hypothesise that using temporary agency work to enhance numerical flexibility and to screen job candidates may increase productivity, whereas temporary workers’ lower firm-specific human capital and spillover effects on the user’s permanent employees may adversely affect productivity. Other than the sparse existing literature on this issue, we exploit a large panel data set and control for time-invariant and time-varying unobserved heterogeneity by using the system GMM estimator. We find a robust hump-shaped effect of the extent of temporary agency work on the user firm’s productivity.

Governments purchase everything from airplanes to zucchini. This paper investigates whether the technological intensity of government demand affects corporate R&D activities. In a quality-ladder model of endogenous growth, we show that an increase in the share of government purchases in high-tech industries increases the rewards for innovation, and stimulates private-sector R&D at the aggregate level. We test this prediction using administrative data on federal procurement performed in US states. Both panel fixed effects and instrumental variable estimations provide results in line with the model. Our findings bring public procurement within the realm of the innovation policy debate.

We seek to understand the relationship between network change determinants, network change processes at the micro level and structural consequences at the overall network level. Our conceptual framework considers three groups of determinants – organizational, relational and contextual. Selected factors within these groups are assumed to cause network change processes at the micro level – tie formations and tie terminations – and to shape the structural network configuration at the overall network level. We apply a unique longitudinal event history dataset based on the full population of 233 German laser source manufacturers and 570 publicly-funded cooperation projects to answer the following research question: What kind of exogenous or endogenous determinants affect a firm’s propensity and timing to cooperate and enter the network? Estimation results from a non-parametric event history model indicate that young micro firms enter the network later than small-sized and large firms. An in-depth analysis of the size effects for medium-sized firms provides some unexpected yet quite interesting findings. The choice of cooperation type makes no significant difference for the firms’ timing to enter the network. Finally, the analysis of contextual determinants shows that cluster membership can, but do not necessarily, affect a firm’s timing to cooperate.

Fiscal spending multiplier calculations have attracted considerable attention in the aftermath of the global financial crisis. Much of the current literature is based on VAR estimation methods and DSGE models. In line with the Keynesian literature we argue that many of these models probably underestimate the fiscal spending multiplier in recessions. The income-expenditure model of the fiscal spending multiplier can be seen as a good approximation under these circumstances. In its conventional form this model suffers from an underestimation of the multiplier due to an overestimation of the import intake of domestic absorption. In this article we apply input-output calculus to solve this problem. Multipliers thus derived are comparably high, ranging between 1.4 and 1.8 for many member states of the European Union. GDP drops due to budget consolidation might therefore be substantial in times of crisis.

We analyze the decline in the U.S. share of world merchandise exports against the backdrop of a model-based measure of competitiveness. We preliminarily use constant market share analysis and gravity estimations to show that the majority of the decline in export shares can be associated with a declining share of world income, suggesting that the dismal performance of the U.S. market share is not a sufficient statistic for competitiveness. We then derive a computable measure of country-sector specific real marginal costs (i.e. competitiveness) which, insofar it is inferred from actual trade ows, is referred to as 'revealed'. Brought to the data, this measure reveals that most U.S. manufacturing industries are losing momentum relative to their main competitors, as we find U.S. revealed marginal costs to grow by more than 38% on average. At the sectoral level, the "Machinery" industry is the most critical.