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Financial literacy affects wealth accumulation, and pension planning plays a key role in this relationship. In a large field experiment, we employ a digital pension aggregation tool to confront a treatment group with a simplified overview of their current pension claims across all pillars of the pension system. We combine survey and administrative bank data to measure the effects on actual saving behavior. Access to the tool decreases pension uncertainty for treated individuals. Average savings increase - especially for the financially less literate. We conclude that simplification of pension information can potentially reduce disparities in pension planning and savings behavior.
The paper presents an empirical analysis of the alledged transformation of the financial systems in the three major European economies, France, Germany and the UK. Based on a unified data set developed on the basis of national accounts statistics, and employing a new and consistent method of measurement, the following questions are addressed: Is there a common pattern of structural change; do banks lose importance in the process of change; and are the three financial systems becoming more similar? We find that there is neither a general trend towards disintermediation, nor towards a transformation from bank-based to capital market-based financial systems, nor for a loss of importance of banks. Only in the case of France strong signs of transformation as well as signs of a general decline in the role of banks could be found. Thus the three financial systems also do not seem to become more similar. However, there is also a common pattern of change: the intermediation chains are lengthening in all three countries. Nonbank financial intermediaries are taking over a more important role as mobilizers of capital from the non-financial sectors. In combination with the trend towards securitization of bank liabilites, this change increases the funding costs of banks and may put banks under pressure. In the case of France, this change is so pronounced that it might even threaten the stability of the financial system.
We evaluate the importance of the precautionary saving motive by relying on a direct question about precautionary wealth from the 1995 and 1998 waves of the Survey of Consumer Finances. In this survey, a new question has been designed to elicit the amount of desired precautionary wealth. This allows us to assess the amount of precautionary accumulation and to overcome many of the problems of previous works on this topic. We find that a precautionary saving motive exists and affects virtually every type of household. However, precautionary savings account for only 8 percent of total wealth holdings. Even though this motive does not give rise to large amounts of wealth, particularly for young and middle-age households, it is particularly important for two groups: older households and business owners. Overall, we provide strong evidence that we need to take the precautionary saving motive into account when modeling saving behavior. Klassifizierung: D91, E21, C21
Ignoring the existence of the zero lower bound on nominal interest rates one considerably understates the value of monetary commitment in New Keynesian models. A stochastic forward-looking model with lower bound, calibrated to the U.S. economy, suggests that low values for the natural rate of interest lead to sizeable output losses and deflation under discretionary monetary policy. The fall in output and deflation are much larger than in the case with policy commitment and do not show up at all if the model abstracts from the existence of the lower bound. The welfare losses of discretionary policy increase even further when inflation is partly determined by lagged inflation in the Phillips curve. These results emerge because private sector expectations and the discretionary policy response to these expectations reinforce each other and cause the lower bound to be reached much earlier than under commitment. JEL Klassifikation: E31, E52
The capital requirements of Solvency II allow insurers to make discretionary choices. Besides extensive possibilities regarding the choice of a risk model (ranging between a regulatory prescribed standard formula to a full self-developed internal model), insurers can make use of transitional measures and adjustments, which can have a substantial impact on their reported solvency level. The aim of this article is to study the effect of these long-term guarantee measures and to identify drivers of the discretionary decisions. For this purpose, we first assess the risk profile of 49 European insurers by estimating the sensitivities of their stock returns to movements in market risk drivers, such as interest rates and credit spreads. In a second step, we analyze to what extent insurers’ risk profiles influence their discretionary decisions in the capital requirement calculation. We gather information on discretionary decisions based on hand-collected Solvency II data for the years 2016 to 2020. We find that insurers optimize their reported solvency situation by making discretionary decisions in such a way that capital requirements for material risk drivers are clearly reduced. For instance, we find that the usage of the volatility adjustment is positively related to the interest rate risk as perceived by financial markets, even when controlling for the portion of life insurance in technical provisions. Similarly, the matching adjustment is linked to significantly higher credit risk sensitivities. Our results point out that due to discretionary decisions Solvency II figures can substantially deviate from a market-oriented, risk-based view on insurance companies’ risk situation.
European insurers are allowed to make discretionary decisions in the calculation of Solvency II capital requirements. These choices include the design of risk models (ranging from a standard formula to a full internal model) and the use of long-term guarantees measures. This article examines the impact and the drivers of discretionary decisions with respect to capital requirements for market risks. In a first step of our analysis, we assess the risk profiles of 49 stock insurers using daily market data. In a second step, we exploit hand-collected Solvency II data for the years 2016 to 2020. We find that long-term guarantees measures substantially influence the reported solvency ratios. The measures are chosen particularly by less solvent insurers and firms with high interest rate and credit spread sensitivities. Internal models are used more frequently by large insurers and especially for risks for which the firms have already found adequate immunization strategies.
This paper examines how the transmission of government portfolio risk arising from maturity operations depends on the stance of monetary/fiscal policy. Accounting for risk premia in the fiscal theory allows the government portfolio to affect the expected inflation, even in a frictionless economy. The effects of maturity rebalancing on expected inflation in the fiscal theory directly depend on the conditional nominal term premium, giving rise to an optimal debt maturity policy that is state dependent. In a calibrated macro-finance model, we demonstrate that maturity operations have sizable effects on expected inflation and output through our novel risk transmission mechanism.
The aim of this paper is to examine what has been the role of information provision to the market throughout the crisis. We consider two main sources of information to the market, financial statements and information provided by credit rating agencies. We examine how these sources of information work and the effectiveness of their disclosure process during the crisis. Contrary to the commonly held view, fair value accounting did not have a major impact on the crisis development and severity. However, the structure and lack of accountability of credit rating agencies had a profound impact on their incentives, which may have jeopardized the accuracy of the whole rating process. We claim that the crisis experience has changed the way we think about information as well as market discipline and discuss policy implications and proposals for regulation. JEL Classification: G01, G24, G28, M41, M48