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  <title>EconStor Collection:</title>
  <link rel="alternate" href="https://hdl.handle.net/10419/84" />
  <subtitle />
  <id>https://hdl.handle.net/10419/84</id>
  <updated>2026-04-29T12:28:42Z</updated>
  <dc:date>2026-04-29T12:28:42Z</dc:date>
  <entry>
    <title>Lack of identification of parameters in a simple behavioral macroeconomic model</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/300523" />
    <author>
      <name>Lux, Thomas</name>
    </author>
    <id>https://hdl.handle.net/10419/300523</id>
    <updated>2024-07-20T11:48:36Z</updated>
    <published>2024-01-01T00:00:00Z</published>
    <summary type="text">Title: Lack of identification of parameters in a simple behavioral macroeconomic model
Authors: Lux, Thomas
Abstract: Identifiability of the parameters is an important precondition for consistent estimation of models designed to describe empirical phenomena. Nevertheless, many estimation exercises proceed without a preliminary investigation into the identifiability of its models. As a consequence, the estimates could be essentially meaningless if convergence to the 'true' parameters is not guaranteed in the pertinent problem. We provide some evidence here that such a lack of identification is responsible for the inconclusive results reported in recent literature on parameter estimates for a certain class of nonlinear behavioral New Keynesian models. We also show that identifiability depends on the subtle details of the model structure. Hence, a careful investigation of identifiability should preceed any attempt at estimation of such models.</summary>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Socioeconomic inequality in life expectancy: Perception and policy demand</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/300522" />
    <author>
      <name>Jessen, Lasse J.</name>
    </author>
    <author>
      <name>Köhne, Sebastian</name>
    </author>
    <author>
      <name>Nüß, Patrick</name>
    </author>
    <author>
      <name>Ruhose, Jens</name>
    </author>
    <id>https://hdl.handle.net/10419/300522</id>
    <updated>2024-07-20T01:18:14Z</updated>
    <published>2024-01-01T00:00:00Z</published>
    <summary type="text">Title: Socioeconomic inequality in life expectancy: Perception and policy demand
Authors: Jessen, Lasse J.; Köhne, Sebastian; Nüß, Patrick; Ruhose, Jens
Abstract: Using survey experiments in the United States and Germany with 12,000 participants, we examine perceptions of life expectancy inequality between rich and poor people. The life expectancy of the poor is underestimated more than that of the rich, leading to exaggerated perceptions of inequality in both countries. Receiving accurate information narrows concerns about this inequality. However, the impact of information on policy demand is limited because support for policies addressing life expectancy for the poor is consistently high, regardless of varying perceptions of inequality. We conclude that there is strong and unconditional public support for health equity policies.</summary>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Inflation: Thruway of ECB's monetary policy</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/269213" />
    <author>
      <name>Seidl, Christian</name>
    </author>
    <id>https://hdl.handle.net/10419/269213</id>
    <updated>2023-12-22T02:49:27Z</updated>
    <published>2023-01-01T00:00:00Z</published>
    <summary type="text">Title: Inflation: Thruway of ECB's monetary policy
Authors: Seidl, Christian
Abstract: Part of the present inflation is caused by the breakdown of globalization, in particular supply chains, part is caused by the Corona Pandemic, in particular lockdowns, part is caused by the Ukrainian War, part is caused by European sanctions, and part - and not the smallest one - is caused by the European Central Bank's printing money by hook or by crook in the past and in the presence. This paper attributes inflation decisively to the overwhelming money creation by the European Central Bank.</summary>
    <dc:date>2023-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Forecasting the Variability of Stock Index Returns with the Multifractal Random Walk Model for Realized Volatilities</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/247272" />
    <author>
      <name>Sattarhoff, Cristina</name>
    </author>
    <author>
      <name>Lux, Thomas</name>
    </author>
    <id>https://hdl.handle.net/10419/247272</id>
    <updated>2023-11-22T02:27:00Z</updated>
    <published>2021-01-01T00:00:00Z</published>
    <summary type="text">Title: Forecasting the Variability of Stock Index Returns with the Multifractal Random Walk Model for Realized Volatilities
Authors: Sattarhoff, Cristina; Lux, Thomas
Abstract: We adapt the multifractal random walk model by Bacry et al. (2001) to realized volatilities (denoted RV-MRW) and take stock of recent theoretical insights on this model in Duchon et al. (2012) to derive forecasts of financial volatility. Moreover, we propose a new extension of the binomial Markov-switching multifractal (BMSM) model by Calvet and Fisher (2001) to the RV framework. We compare the predictive ability of the two against seven classical and multifractal volatility models. Forecasting performance is evaluated out-of-sample based on the empirical MSE and MAE as well as using model confidence sets following the methodology of Hansen et al. (2011). Overall, our empirical study for 14 international stock market indices has a clear message: The RV-MRW is throughout the best model for all forecast horizons under the MAE criterium as well as for large forecast horizons h=50 and 100 days under the MSE criterion. Moreover, the RV-MRW provides most accurate 20-day ahead forecasts in terms of MSE for the great majority of indices, followed by RV-ARFIMA, the latter dominating the competition at the 5-day-horizon. These results are very promising if we consider that this is the first empirical application of the RV-MRW. Moreover, whereas RV-ARFIMA forecasts are often a time consuming task, the RV-MRW stands out due to its fast execution and straightforward implementation. The new RV-BMSM appears to be specialized in short term forecasting, the model providing most accurate one-day ahead forecasts in terms of MSE for the same number of cases as RV-ARFIMA.</summary>
    <dc:date>2021-01-01T00:00:00Z</dc:date>
  </entry>
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