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    <title>EconStor Community: Christian-Albrechts-Universität Kiel (CAU)</title>
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  <item rdf:about="http://hdl.handle.net/10419/73651">
    <title>Sticky information models in Dynare</title>
    <link>http://hdl.handle.net/10419/73651</link>
    <description>Title: Sticky information models in Dynare
&lt;br/&gt;
&lt;br/&gt;Authors: Verona, Fabio; Wolters, Maik H.
&lt;br/&gt;
&lt;br/&gt;Abstract: Macroeconomic models with sticky information include an infinite number of lagged expectations. Several authors have developed specialized solutions algorithms to solve these models under rational expectations. We demonstrate that it is also possible to implement this class of models in Dynare - a widely used software package for solving dynamic stochastic general equilibrium (DSGE) models. Using the Dynare macro language one can easily construct and change the required large number of lagged expectation terms. We assess the accuracy of simulations run with different truncation points for the lagged expectations terms and find that the solution is reasonably precise even for moderate truncation points.</description>
  </item>
  <item rdf:about="http://hdl.handle.net/10419/73651">
    <title>Sticky information models in Dynare</title>
    <link>http://hdl.handle.net/10419/73651</link>
    <description>Title: Sticky information models in Dynare
&lt;br/&gt;
&lt;br/&gt;Authors: Verona, Fabio; Wolters, Maik H.
&lt;br/&gt;
&lt;br/&gt;Abstract: Macroeconomic models with sticky information include an infinite number of lagged expectations. Several authors have developed specialized solutions algorithms to solve these models under rational expectations. We demonstrate that it is also possible to implement this class of models in Dynare - a widely used software package for solving dynamic stochastic general equilibrium (DSGE) models. Using the Dynare macro language one can easily construct and change the required large number of lagged expectation terms. We assess the accuracy of simulations run with different truncation points for the lagged expectations terms and find that the solution is reasonably precise even for moderate truncation points.</description>
  </item>
  <item rdf:about="http://hdl.handle.net/10419/68592">
    <title>Hostile Parent Firms and Child Firm Performance</title>
    <link>http://hdl.handle.net/10419/68592</link>
    <description>Title: Hostile Parent Firms and Child Firm Performance
&lt;br/&gt;
&lt;br/&gt;Authors: Walter, Sascha; Heinrichs, Simon; Walter, Achim 131877801
&lt;br/&gt;
&lt;br/&gt;Abstract: We investigated how and when parent hostility (degree to which a parent firm disapproves the spawning of an own spin-out) affects spin-out performance and how spin-outs can effectively react to it. Analyses of 144 technology spin-outs support our arguments that spin-outs suffer from hostility. Hostility consequences are, however, less severe if market turbulence is high or if the spin-out pursues effective network development.</description>
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  <item rdf:about="http://hdl.handle.net/10419/68591">
    <title>Don’t Step Into Your Parent’s Shoes – How Exploitation and Exploration Affect Spin-out Growth</title>
    <link>http://hdl.handle.net/10419/68591</link>
    <description>Title: Don’t Step Into Your Parent’s Shoes – How Exploitation and Exploration Affect Spin-out Growth
&lt;br/&gt;
&lt;br/&gt;Authors: Heinrichs, Simon; Walter, Sascha
&lt;br/&gt;
&lt;br/&gt;Abstract: This study examines how different organizational learning strategies (i.e., exploration or exploitation) impact the sales growth of technology spin-outs, and the role of the parent firm in this context. Using knowledge-based and learning views of the firm, we propose that spin-out performance benefits from exploration, but suffers from exploitation. Results based on a sample of 134 spin-outs support these arguments. Additionally, parent goodwill reinforced the positive effect of exploration, whereas high market similarity to the parent firm increased the negative effect of exploitation.</description>
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