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Wie der Iran-Krieg einen Aufschwung bremsen könnteOliver HoltemöllerTagesschau.de, 12. März 2026
This paper investigates a perception in the political debates as to what extent poor countries are affected by price movements in the global commodity markets. To test this perception, we use the case of India to establish in a standard SVAR model that global food prices influence aggregate prices and food prices in India. To further analyze these empirical results, we specify a small open economy New-Keynesian model including oil and food prices and estimate it using observed data over the period 1996Q2 to 2013Q2 by applying Bayesian estimation techniques. The results suggest that a big part of the variation in inflation in India is due to cost-push shocks and, mainly during the years 2008 and 2010, also to global food price shocks, after having controlled for exogenous rainfall shocks. We conclude that the inflationary supply shocks (cost-push, oil price, domestic food price and global food price shocks) are important contributors to inflation in India. Since the monetary authority responds to these supply shocks with a higher interest rate which tends to slow growth, this raises concerns about how such output losses can be prevented by reducing exposure to commodity price shocks.
We study the impact of the interaction between fiscal and monetary policy on the low-frequency relationship between the fiscal stance and inflation using cross-country data from 1965 to 1999. In a first step, we contrast the monetary–fiscal narrative for Germany, the U.S., and Italy with evidence obtained from simple regression models and a time-varying VAR. We find that the low-frequency relationship between the fiscal stance and inflation is low during periods of an independent central bank and responsible fiscal policy and more pronounced in times of non-responsible fiscal policy and accommodative monetary authorities. In a second step, we use an estimated DSGE model to interpret the low-frequency measure structurally and to illustrate the mechanisms through which fiscal actions affect inflation in the long run. The findings from the DSGE model suggest that switches in the monetary–fiscal policy interaction and accompanying variations in the propagation of structural shocks can well account for changes in the low-frequency relationship between the fiscal stance and inflation.
The current situation regarding the migration of refugees can only be handled efficiently through closer international cooperation in the field of asylum policy. From an economic point of view, it would be reasonable to distribute incoming refugees among all EU countries according to a distribution key that reflects differences in the costs of integration in the individual countries. An efficient distribution would even out the marginal costs of integrating refugees. In order to reach a political agreement, the key for distributing refugees should be complemented by compensation payments that distribute the costs of integration among countries. The key for distributing refugees presented by the EU Commission takes account of appropriate factors in principle, but it is unclear in terms of detail. The compensation payments for countries that should take relatively high numbers of refugees for cost efficiency reasons should be financed by reallocating resources within the EU budget.
In this article, we examine the effect of estimation biases – introduced by model misspecification – on the impulse responses analysis for dynamic stochastic general equilibrium (DSGE) models. Thereby, we use full and limited information estimators to estimate a misspecified DSGE model and calculate impulse response functions (IRFs) based on the estimated structural parameters. It turns out that IRFs based on full information techniques can be unreliable under misspecification.
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, originally proposed by Dueker (2005). The Qual VAR is a VAR model including a latent variable that governs the behavior of an observable binary variable. While we find that the Qual VAR performs reasonable well in forecasting (outperforming a probit benchmark), there are substantial identification problems even in a simple VAR specification. Typically, identification in economic applications is far more difficult than in our simple benchmark. Therefore, when the economic interpretation of the dynamic behavior of the latent variable and the chain of causality matter, use of the Qual VAR is inadvisable.
In this paper we analyze the small sample properties of full information and limited information estimators in a potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including price and wage rigidities. We then study the effects of omitted variable problems on the structural parameter estimates of the model. We find that FIML performs superior when the model is correctly specified. In cases where some of the model characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and significance tests are mostly reliable.
We estimate the low-frequency relationship between fiscal deficits and inflation and pay special attention to its potential time variation by estimating a time-varying vector autoregression model for US data from 1900 to 2011. We find the strongest relationship neither in times of crisis nor in times of high public deficits, but from the mid 1960s up to 1980. Employing a structural decomposition of the low-frequency relationship and further narrative evidence, we interpret our results such that the low-frequency relationship between fiscal deficits and inflation is strongly related to the conduct of monetary policy and its interaction with fiscal policy after World War II.
Uncertainty about the appropriate choice among nested models is a concern for optimal policy when policy prescriptions from those models differ. The standard procedure is to specify a prior over the parameter space, ignoring the special status of submodels (e.g., those resulting from zero restrictions). Following Sims (2008, Journal of Economic Dynamics and Control 32, 2460–2475), we treat nested submodels as probability models, and we formalize a procedure that ensures that submodels are not discarded too easily and do matter for optimal policy. For the United States, we find that optimal policy based on our procedure leads to substantial welfare gains compared to the standard procedure.
Designers of MMOs such as Diablo 3 face economic problems much like policy makers in the real world, e.g. inflation and distributional issues. Solving economic problems through regular updates (patches) became as important to those games as traditional gameplay issues. In this paper we provide an agent framework inspired by the economic features of Diablo 3 and analyze the effect of monetary policy in the game. Our model reproduces a number of features known from the Diablo 3 economy such as a heterogeneous price development, driven almost exclusively by goods of high quality, a highly unequal wealth distribution and strongly decreasing economic mobility. The basic framework presented in this paper is meant as a stepping stone to further research, where our evidence is used to deepen our understanding of the real-world counterparts of such problems. The advantage of our model is that it combines simplicity that is inherent to model economies with a similarly simple observable counterpart (namely the game environment where real agents interact). By matching the dynamics of the game economy we can thus easily verify that our behavioral assumptions are good approximations to reality.
The European debt crisis has revealed severe imbalances within the Euro area, sparking a debate about the magnitude of those imbalances, in particular concerning real effective exchange rate misalignments. We use synthetic matching to construct a counterfactual economy for each member state in order to identify the degree of these misalignments. We find that crisis countries are best described as a combination of advanced and emerging economies. Comparing the actual real effective exchange rate with those of the counterfactuals gives evidence of misalignments before the outbreak of the crisis: all peripheral countries appear strongly and significantly overvalued.
