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The ECB’s Outright Monetary Transactions (OMT) program, launched in summer 2012, indirectly recapitalized periphery country banks through its positive impact on the value of sovereign bonds. However, the regained stability of the European banking sector has not fully transferred into economic growth. We show that zombie lending behavior of banks that still remained undercapitalized after the OMT announcement is an important reason for this development. As a result, there was no positive impact on real economic activity like employment or investment. Instead, firms mainly used the newly acquired funds to build up cash reserves. Finally, we document that creditworthy firms in industries with a high prevalence of zombie firms suffered significantly from the credit misallocation, which slowed down the economic recovery.
SAFE Newsletter : 2016, Q3
(2016)
SAFE Newsletter : 2016, Q4
(2016)
Amid increasing regulation, structural changes of the market and Quantitative Easing as well as extremely low yields, concerns about the market liquidity of the Eurozone sovereign debt markets have been raised. We aim to quantify illiquidity risks, especially such related to liquidity dry-ups, and illiquidity spillover across maturities by examining the reaction to illiquidity shocks at high frequencies in two ways:
a) the regular response to shocks using a variance decomposition and,
b) the response to shocks in the extremes by detecting illiquidity shocks and modeling those as ultivariate Hawkes processes.
We find that:
a) market liquidity is more fragile and less predictable when an asset is very illiquid and,
b) the response to shocks in the extremes is structurally different from the regular response.
In 2015 long-term bonds are less liquid and the medium-term bonds are liquid, although we observe that in the extremes the medium-term bonds are increasingly driven by illiquidity spillover from the long-term titles.
This paper is the outcome of a related broader project, exploring the explanatory power of the Legal Theory of Finance, which proposes a new institution-based analytical framework for the analysis of phenomena of financial markets. One of its most important theoretical assumptions, the legal construction of financial markets, is highlighted by the example of the private creation of money by structured finance products in this paper. Further implications can then be shown referring to pari passu clauses and collective action clauses, which are both exhibit a differential application of these legal rules according to the hierarchical status of the respective market participant, and can therefore endanger sovereign debt restructurings. Legal instruments to avoid this are briefly explored. An example of another key role of the law in crisis that is the task to resolve the tension between market discipline and financial stability is exemplified by the regulation of the OTC derivatives market and proposals of effective loss-sharing among CCPs. Related questions about the significance of legal rules to ensure financial stability are raised in the analysis of minimum capital requirements under Basel III.
Using two datasets containing demographically representative samples of the Dutch population, I study how lifetime experiences of aggregate labor market conditions affect personality. Three sets of findings are reported. First, experienced aggregate unemployment is negatively correlated with the levels of all Big Five personality traits, except for conscientiousness (no significant correlation). Second, in panel data models with individual fixed effects I find that changes in experienced aggregate unemployment cause changes in emotional stability and agreeableness for men, and conscientiousness for women. The correlation is positive, and effects are economically large. Thirdly, I report suggestive evidence that the main driver is experienced aggregate unemployment, instead of other macroeconomic variables as experienced GDP, stock market returns or inflation. Taken together, these findings suggest that changes in Big Five personality traits are systematically related to experienced aggregate labor market conditions.
The global financial crisis and the ensuing criticism of macroeconomics have inspired researchers to explore new modeling approaches. There are many new models that deliver improved estimates of the transmission of macroeconomic policies and aim to better integrate the financial sector in business cycle analysis. Policy making institutions need to compare available models of policy transmission and evaluate the impact and interaction of policy instruments in order to design effective policy strategies. This paper reviews the literature on model comparison and presents a new approach for comparative analysis. Its computational implementation enables individual researchers to conduct systematic model comparisons and policy evaluations easily and at low cost. This approach also contributes to improving reproducibility of computational research in macroeconomic modeling. Several applications serve to illustrate the usefulness of model comparison and the new tools in the area of monetary and fiscal policy. They include an analysis of the impact of parameter shifts on the effects of fiscal policy, a comparison of monetary policy transmission across model generations and a cross-country comparison of the impact of changes in central bank rates in the United States and the euro area. Furthermore, the paper includes a large-scale comparison of the dynamics and policy implications of different macro-financial models. The models considered account for financial accelerator effects in investment financing, credit and house price booms and a role for bank capital. A final exercise illustrates how these models can be used to assess the benefits of leaning against credit growth in monetary policy.
“Institutional Overburdening” to a large extent was a consequence of the “Great Moderation”. This term indicates that it was a period in which inflation had come down from rather high levels. Growth and employment were at least satisfying and variability of output had substantially declined. It was almost unavoidable that as a consequence expectations on future actions of central banks and their ability to control the economy reached an unprecedented peak which was hardly sustainable. Institutional overburdening has two dimensions. One is coming from exaggerated expectations on what central banks can achieve (“expectational overburdening”). The other dimension is “operational overburdening” i.e. overloading the central bank with more and more responsibilities and competences.
Microeconomic modeling of investors behavior in financial markets and its results crucially depends on assumptions about the mathematical shape of the underlying preference functions as well as their parameterizations. With the purpose to shed some light on the question, which preferences towards risky financial outcomes prevail in stock markets, we adopted and applied a maximum likelihood approach from the field of experimental economics on a randomly selected dataset of 656 private investors of a large German discount brokerage firm. According to our analysis we find evidence that the majority of these clients follow trading pattern in accordance with Prospect Theory (Kahneman and Tversky (1979)). We also find that observable sociodemographic and personal characteristics such as gender or age don't seem to correlate with specific preference types. With respect to the overall impact of preferences on trading behavior, we find a moderate impact of preferences on trading decisions of individual investors. A classification of investors according to various utility types reveals that the strength of the impact of preferences on an investors' rading behavior is not connected to most personal characteristics, but seems to be related to round-trip length.
This paper addresses whether and to what extent econometric methods used in experimental studies can be adapted and applied to financial data to detect the best-fitting preference model. To address the research question, we implement a frequently used nonlinear probit model in the style of Hey and Orme (1994) and base our analysis on a simulation stud. In detail, we simulate trading sequences for a set of utility models and try to identify the underlying utility model and its parameterization used to generate these sequences by maximum likelihood. We find that for a very broad classification of utility models, this method provides acceptable outcomes. Yet, a closer look at the preference parameters reveals several caveats that come along with typical issues attached to financial data, and that some of these issues seems to drive our results. In particular, deviations are attributable to effects stemming from multicollinearity and coherent under-identification problems, where some of these detrimental effects can be captured up to a certain degree by adjusting the error term specification. Furthermore, additional uncertainty stemming from changing market parameter estimates affects the precision of our estimates for risk preferences and cannot be simply remedied by using a higher standard deviation of the error term or a different assumption regarding its stochastic process. Particularly, if the variance of the error term becomes large, we detect a tendency to identify SPT as utility model providing the best fit to simulated trading sequences. We also find that a frequent issue, namely serial correlation of the residuals, does not seem to be significant. However, we detected a tendency to prefer nesting models over nested utility models, which is particularly prevalent if RDU and EXPO utility models are estimated along with EUT and CRRA utility models.