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  <title>EconStor Collection:</title>
  <link rel="alternate" href="https://hdl.handle.net/10419/55212" />
  <subtitle />
  <id>https://hdl.handle.net/10419/55212</id>
  <updated>2026-05-02T15:43:26Z</updated>
  <dc:date>2026-05-02T15:43:26Z</dc:date>
  <entry>
    <title>An econometric analysis of the demand surge effect</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/70911" />
    <author>
      <name>Döhrmann, David</name>
    </author>
    <author>
      <name>Gürtler, Marc</name>
    </author>
    <author>
      <name>Hibbeln, Martin</name>
    </author>
    <id>https://hdl.handle.net/10419/70911</id>
    <updated>2023-11-08T02:20:17Z</updated>
    <published>2013-01-01T00:00:00Z</published>
    <summary type="text">Title: An econometric analysis of the demand surge effect
Authors: Döhrmann, David; Gürtler, Marc; Hibbeln, Martin
Abstract: In case of a natural catastrophe there is an increased demand for skilled labor and materials which in turn leads to significant price increases that should be taken into account in the forecast of catastrophe losses. Such price effects are referred to as Demand Surge effects. The paper at hand presents an extensive econometric analysis and modeling of the Demand Surge effect. We find that Demand Surge is positively influenced by the total amount of repair work, by alternative catastrophes in the same region in close temporal proximity, and by a higher amount of insurance claims per event. Furthermore, the Demand Surge effect is more pronounced if the construction sector is in a growth stage. In contrast, a higher capacity of the construction sector has a restraining effect on Demand Surge. In addition, if we restrict the data to very severe catastrophes, we observe a saturation effect according to which a wage increase for building services before a catastrophe reduces the Demand Surge effect.</summary>
    <dc:date>2013-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Empirical studies in a multivariate non-stationary, nonparametric regression model for financial returns</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/67961" />
    <author>
      <name>Gürtler, Marc</name>
    </author>
    <author>
      <name>Rauh, Ronald</name>
    </author>
    <id>https://hdl.handle.net/10419/67961</id>
    <updated>2023-11-26T02:26:32Z</updated>
    <published>2013-01-01T00:00:00Z</published>
    <summary type="text">Title: Empirical studies in a multivariate non-stationary, nonparametric regression model for financial returns
Authors: Gürtler, Marc; Rauh, Ronald
Abstract: In this paper we analyze a multivariate non-stationary regression model empirically. With the knowledge about unconditional heteroscedasticty of financial returns, based on univariate studies and a congruent paradigm in Gürtler and Rauh (2009), we test for a time-varying covariance structure firstly. Based on these results, a central component of our non-stationary model is a kernel regression for pairwise covariances and the covariance matrix. Residual terms are fitted with an asymmetric Pearson type VII distribution. In an extensive study we estimate the linear dependence of a broad portfolio of equities and fixed income securities (including credit and currency risks) and fit the whole approach to provide distributional forecasts. Our evaluations verify a reasonable approximation and a satisfactory forecasting quality with an out performance against a traditional risk model.</summary>
    <dc:date>2013-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Insured loss inflation: How natural catastrophes affect reconstruction costs</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/97788" />
    <author>
      <name>Döhrmann, David</name>
    </author>
    <author>
      <name>Gürtler, Marc</name>
    </author>
    <author>
      <name>Hibbeln, Martin</name>
    </author>
    <id>https://hdl.handle.net/10419/97788</id>
    <updated>2023-11-24T10:05:37Z</updated>
    <published>2013-01-01T00:00:00Z</published>
    <summary type="text">Title: Insured loss inflation: How natural catastrophes affect reconstruction costs
Authors: Döhrmann, David; Gürtler, Marc; Hibbeln, Martin
Abstract: In the aftermath of a natural catastrophe, there is increased demand for skilled reconstruction labor, which leads to significant increases in reconstruction labor wages and hence insured losses. Such inflation effects are known as 'Demand Surge' effects. It is important for insurance companies to properly account for these effects when calculating insurance premiums and determining economic capital. We propose an approach to quantifying the Demand Surge effect and present an econometric model for the effect that is based on 191 catastrophe events in the United States. Our model explains more than 75% of the variance of the Demand Surge effect and is thus able to identify the key drivers of the phenomenon.</summary>
    <dc:date>2013-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>The optimality of heterogeneous tournaments</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/67962" />
    <author>
      <name>Gürtler, Marc</name>
    </author>
    <author>
      <name>Gürtler, Oliver</name>
    </author>
    <id>https://hdl.handle.net/10419/67962</id>
    <updated>2023-11-03T02:11:48Z</updated>
    <published>2013-01-01T00:00:00Z</published>
    <summary type="text">Title: The optimality of heterogeneous tournaments
Authors: Gürtler, Marc; Gürtler, Oliver
Abstract: We investigate the effect of employee heterogeneity on the incentive to put forth effort in a market-based tournament. Employers use the tournament's outcome to estimate employees' abilities and accordingly condition their wage offers. Employees put forth effort, because by doing so they increase the probability of outperforming the rival, thereby increasing their ability assessment and thus the wage offer. We demonstrate that the tournament outcome provides more information about employees' abilities in case they are heterogeneous. Thus, employees get a higher incentive to affect the tournament outcome, and employers find it optimal to hire heterogeneous contestants.</summary>
    <dc:date>2013-01-01T00:00:00Z</dc:date>
  </entry>
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