Refine
Year of publication
Document Type
- Working Paper (1498)
- Part of Periodical (578)
- Article (206)
- Report (141)
- Book (100)
- Doctoral Thesis (70)
- Contribution to a Periodical (44)
- Conference Proceeding (21)
- Part of a Book (13)
- Periodical (12)
Is part of the Bibliography
- no (2712)
Keywords
- Deutschland (98)
- Financial Institutions (92)
- Capital Markets Union (67)
- ECB (67)
- Financial Markets (59)
- Banking Regulation (53)
- Banking Union (50)
- Household Finance (47)
- Monetary Policy (41)
- Banking Supervision (40)
Institute
- Wirtschaftswissenschaften (2712) (remove)
This paper examines the relationship between oil movements and systemic risk of financial institution in major petroleum-based economies. We estimate ΔCoVaR for those institutions and observe the presence of elevated increases in its levels corresponding to the subprime and global financial crises. The results provide evidence in favor of risk measurement improvements by accounting for oil returns in the risk functions. The spread between the standard CoVaR and the CoVaR that includes oil absorbs in a time range longer than the duration of the oil shock. This indicates that the drop in the oil price has a longer effect on risk and requires more time to be discounted by the financial institutions. To support the analysis, we consider also the other major market-based systemic risk measures.
This paper presents a comprehensive extension of pricing two-dimensional derivatives depending on two barrier constraints. We assume randomness on the covariance matrix as a way of generalizing. We analyse common barrier derivatives, enabling us to study parameter uncertainty and the risk related to the estimation procedure (estimation risk). In particular, we use the distribution of empirical parameters from IBM and EURO STOXX50. The evidence suggests that estimation risk should not be neglected in the context of multidimensional barrier derivatives, as it could cause price differences of up to 70%.
We consider a class of panel tests of the null hypothesis of no cointegration and cointegration. All tests under investigation rely on single-equations estimated by least squares, and they may be residual-based or not. We focus on test statistics computed from regressions with intercept only (i.e., without detrending) and with at least one of the regressors (integrated of order 1) being dominated by a linear time trend. In such a setting, often encountered in practice, the limiting distributions and critical values provided for and applied with the situation “with intercept only” are not correct. It is demonstrated that their usage results in size distortions growing with the panel size N. Moreover, we show which are the appropriate distributions, and how correct critical values can be obtained from the literature.
Two alternative hypotheses – referred to as opportunity- and stigma-based behavior – suggest that the magnitude of the link between unemployment and crime also depends on preexisting local crime levels. In order to analyze conjectured nonlinearities between both variables, we use quantile regressions applied to German district panel data. While both conventional OLS and quantile regressions confirm the positive link between unemployment and crime for property crimes, results for assault differ with respect to the method of estimation. Whereas conventional mean regressions do not show any significant effect (which would confirm the usual result found for violent crimes in the literature), quantile regression reveals that size and importance of the relationship are conditional on the crime rate. The partial effect is significantly positive for moderately low and median quantiles of local assault rates.
We analyze and compare the social, cultural and historical determinants that influence the international competitiveness of China and India. Starting with the discussion why pure economic determinants cannot solely explain a country's competitiveness, we will analyze previous qualitative research and evaluate quantitative data to assess which country has more favorable socio-economic factors influencing its economic performance in the long run.
For some time now, structural macroeconomic models used at central banks have been predominantly New Keynesian DSGE models featuring nominal rigidities and forwardlooking decision-making. While these features are widely deemed crucial for policy evaluation exercises, most central banks have added more detailed characterizations of the financial sector to these models following the Great Recession in order to improve their fit to the data and their forecasting performance. We employ a comparative approach to investigate the characteristics of this new generation of New Keynesian DSGE models and document an elevated degree of model uncertainty relative to earlier model generations. Policy transmission is highly heterogeneous across types of financial frictions and monetary policy causes larger effects, on average. The New Keynesian DSGE models we analyze suggest that a simple policy rule robust to model uncertainty involves a weaker response to inflation and the output gap in the presence of financial frictions as compared to earlier generations of such models. Leaning-against-the-wind policies in models of this class estimated for the Euro Area do not lead to substantial gains. With regard to forecasting performance, the inclusion of financial frictions can generate improvements, if conditioned on appropriate data. Looking forward, we argue that model-averaging and embracing alternative modelling paradigms is likely to yield a more robust framework for the conduct of monetary policy.
We study the general equilibrium implications of different fiscal policies on macroeconomic quantities, asset prices, and welfare by utilizing two endogenous growth models. The expanding variety model features only homogeneous innovations by entrants. The Schumpeterian growth model features heterogeneous innovations: "incremental" innovations by incumbents and "radical" innovations by entrants. The government levies taxes on labor income and corporate profits and supplies subsidies to consumption, capital investment, and investments in research and development by entrants and, if applicable, incumbents. With these models at hand, we provide new insights on the interplay of innovation dynamics and fiscal policy.
Exploiting NASDAQ order book data and difference-in-differences methodology, we identify the distinct effects of trading pause mechanisms introduced on U.S. stock exchanges after May 2010. We show that the mere existence of such a regulation constitutes a safeguard which makes market participants behave differently in anticipation of a pause. Pauses tend to break local price trends, make liquidity suppliers revise positions, and enhance price discovery. In contrast, pauses do not have a “cool off” effect on markets, but rather accelerate volatility and bid-ask spreads. This implies a regulatory trade-off between the protective role of trading pauses and their adverse effects on market quality.