The recent crisis has shown yet again how the world economies are globally interlinked, via a complex net of transmission channels. When it comes, however, to build econometric frameworks aimed at analysing such linkages, modellers are faced with what is called the "curse of dimensionality": there far too many parameters to be estimated with respect to the available observations. The GVAR, a VAR based model of the global economy, offers a solution to this problem. The basic model is composed of a large number of country specific models, comprising domestic, foreign and purely global variables. The foreign variables, however, are treated as weakly exogenous. This assumption, which is typically held when empirically tested for virtually all economies - with the notable exception of the US which is treated differently - allows to estimate first the individual country models separately. Only in a second stage country-specific models are simultaneously solved, thus allowing global interactions.This volume presents - for a first time in a compact and rather easy to read format - principles and structure of the basic GVAR model and a number of its many applications and extensions developed in the last few years by a growing literature. Its main objective is to show how powerful the model can be as a tool for forecasting and scenario analysis. The clear modelling structure of the GVAR appeals to policy makers and practitioners as shown by its growing use among major institutions, as well as by econometricians, as shown by the main extensions and applications.

We study how firm innovativeness is related to individual cooperation events and the structure and dynamics of firms’ ego-networks employing a unique panel dataset for the full population of 233 German laser source manufactures between 1990 and 2010. Firm innovativeness is measured by yearly patent applications as well as patent grants with a two year time-lag. Network measures are calculated on the basis of 570 knowledge-related publicly funded R&D alliances. Estimation results from a panel data count model with fixed effects are suggestive of direct innovation effects due to individual cooperation events, but only as long as structural ego-network characteristics are neglected. Innovativeness is robustly related to ego-network size and ego-network brokerage whereas ego-network density reveals some surprising results.

This paper conducts an empirical study of the factors that affect the spatial distribution of foreign direct investment (FDI) across regions in Russia; in particular, this paper is concerned with those regions that are endowed with natural resources and market-related benefits. Our analysis employs data on Russian firms with a foreign investor during the 2000-2009 period and linked regional statistics in the conditional logit model. The main findings are threefold. First, we conclude that one theory alone is not able to explain the geographical pattern of foreign investments in Russia. A combination of determinants is at work; market-related factors and the availability of natural resources are important factors in attracting FDI. The relative importance of natural resources seems to grow over time, despite shocks associated with events such as the Yukos trial. Second, existing agglomeration economies encourage foreign investors by means of forces generated simultaneously by sector-specific and inter-sectoral externalities. Third, the findings imply that service-oriented FDI co-locates with extraction industries in resource-endowed regions. The results are robust when Moscow is excluded and for subsamples including only Greenfield investments or both Greenfield investments and mergers and acquisitions (M&A).

We seek to quantify the impact on euro area GDP of the European Economic Recovery Plan (EERP) enacted in response to the financial crisis of 2008–2009. To do so, we estimate an extended version of the ECB's New Area-Wide Model with a richly specified fiscal sector. The estimation results point to the existence of important complementarities between private and government consumption and, to a lesser extent, between private and public capital. We first examine the implied present-value multipliers for seven distinct fiscal instruments and show that the estimated complementarities result in fiscal multipliers larger than one for government consumption and investment. We highlight the importance of monetary accommodation for these findings. We then show that the EERP, if implemented as initially enacted, had a sizeable, although short-lived impact on euro area GDP. Since the EERP comprised both revenue and expenditure-based fiscal stimulus measures, the total multiplier is below unity.

This paper analyses the impact of vertical grants on local public sector efficiency. First, we develop a theoretical model in which the bureaucrat sets the tax price while voters choose the quantity of public services. In this model, grants reduce efficiency if voters do not misinterpret the amount of vertical grants the local bureaucrats receive. If voters suffer from fiscal illusion, i.e. overestimate the amount of grants, our model yields an ambiguous effect of grants on efficiency. Second, we use the model to launch a note of caution concerning the inference that can be drawn from the existing cross-sectional studies in this field: Taking into account vertical financial equalization systems that reduce differences in fiscal capacity, empirical studies based on cross-sectional data may yield a positive relationship between grants and efficiency even when the underlying causal effect is negative. Third, we perform an empirical analysis for the German state of Saxony-Anhalt, which has implemented such a fiscal equalization system. We find a positive relationship between grants and efficiency. Our analysis shows that a careful reassessment of existing empirical evidence with regard to this issue seems necessary.

This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown et al. (J R Stat Soc B 37:149–163, 1975) and Zeileis (Stat Pap 45(1):123–131, 2004), Nyblom (J Am Stat Assoc 84(405):223–230, 1989) and Hansen (J Policy Model 14(4):517–533, 1992), and Andrews et al. (J Econ 70(1):9–38, 1996). Power and size properties are derived using Monte Carlo simulations. We find that the Nyblom test is on par with the commonly used F type tests in a small sample in terms of power. While the Nyblom test’s power decreases if the structural break occurs close to the margin of the sample, it proves far more robust to nonnormal distributions of the error term that are found to matter strongly in small samples although being irrelevant asymptotically for all tests that are analyzed in this paper.

Due to the recent financial crisis, the interest in econometric models that allow to incorporate binary variables (such as the occurrence of a crisis) experienced a huge surge. This paper evaluates the performance of the Qual VAR, i.e. a VAR model including a latent variable that governs the behavior of an observable binary variable. While we find that the Qual VAR performs reasonably well in forecasting (outperforming a probit benchmark), there are substantial identification problems. Therefore, when the economic interpretation of the dynamic behavior of the latent variable and the chain of causality matter, the Qual VAR is inadvisable.

Many economic decisions implicitly or explicitly rely on a projection of the medium- or long-term economic development of a country or region. In this paper, we provide a federal long-run projection model for Germany and the German states. The model fea-tures a top-down approach and, as major contribution, uses error correction models to estimate the regional economic development dependent on the national projection. For the medium- and long-term projection of economic activity, we apply a production function approach. We provide a detailed robustness analysis by systematically varying assumptions of the model. Additionally, we explore the effects of different demographic trends on economic development.

This article focuses on the impact of agglomeration and labour market factors on the location choice of MNEs in post-transition economies. We compare data from 33 regions in East Germany, the Czech Republic and Poland using a mixed logit model on a sample of 4,343 subsidiaries for the time period between 2000 and 2010. The results show that agglomeration advantages, such as sectoral specialization as well as a region’s economic and technological performance prove to be some of the most important pull factors for FDI in post-transition regions.