Genetic algorithms: a tool for optimization in econometrics - basic concept and an example for empirical applications

This paper discusses a tool for optimization of econometric models based on genetic algorithms. First, we briefly describe the concept of this optimization technique. Then, we explain the design of a specifically developed algorithm and apply it to a difficult econometric problem, the semiparametric estimation of a censored regression model. We carry out some Monte Carlo simulations and compare the genetic algorithm with another technique, the iterative linear programming algorithm, to run the censored least absolute deviation estimator. It turns out that both algorithms lead to similar results in this case, but that the proposed method is computationally more stable than its competitor. --Genetic Algorithm,Semiparametrics,Monte Carlo Simulation

Inventor mobility index : a method to disambiguate inventor careers

Usually patent data does not contain any unique identifiers for the patenting assignees or the inventors, as the main tasks of patent authorities is the examination of applications and the administration of the patent documents as public contracts and not the support of the empirical analysis of their data. An inventor in a patent document is identified by his or her name. Depending on the patent authority the full address or parts of it may be included to further identify this inventor. The goal is to define an inventor mobility index that traces the career of an inventor as an individual with all the job switches and relocations approximated by the patents as potential milestones. The inventor name is the main criteria for this identifier. The inventor address information on the other hand is only of limited use for the definition of a mobility index. The name alone can work for exotic name variants, but for more common names the problem of namesakes gets in the way of identifying individuals. The solution discussed here consists in the construction of a relationship network between inventors with the same name. This network will be created by using all the other information available in the patent data. These could be simple connections like the same applicant or just the same home address, up to more complex connections that are created by the overlapping of colleagues and co-inventors, similar technology fields or shared citations. Traversal of these heuristically weighted networks by using methods of the graph theory leads to clusters representing a person. The applied methodology will give uncommon names a higher degree of freedom regarding the heuristic limitations than the more common names will get

Genetic Algorithms: A Tool for Optimization in Econometrics – Basic Concept and an Example for Empirical Applications

This paper discusses a tool for optimization of econometric models based on genetic algorithms. First, we briefly describe the concept of this optimization technique. Then, we explain the design of a specifically developed algorithm and apply it to a difficult econometric problem, the semiparametric estimation of a censored regression model. We carry out some Monte Carlo simulations and compare the genetic algorithm with another technique, the iterative linear programming algorithm, to run the censored least absolute deviation estimator. It turns out that both algorithms lead to similar results in this case, but that the proposed method is computationally more stable than its competitor

Disambiguation of Researcher Careers: Shifting the Perspective from Documents to Authors

The thesis describes an algorithm that disambiguates the namespaces of inventors and researchers, spawned by their patents and publications, into career paths. A probabilistic theory to assess the risk of erroneously linking documents of namesakes, different individuals with a mutual name, into one career bypasses the need for training datasets, thereby avoiding a namesake bias caused by the inherent underestimation of namesakes in training/benchmark data. The economic relevance of identified careers is illustrated by two applications. The first one outlines the impact of inter-regional inventor mobility in Italy on the total factor productivity of the sending and receiving regions. We show that an inflow of high skilled labor has a significant positive effect on TFP, while outflow decreases it. We further separate mobility in firm-internal relocation and job switches to find a more pronounced effect for the latter mobility. The second application observes the reaction of German university researchers to an exogenous change in federal law pertaining the property rights of their inventions equivalent to the Bayh Dole Act. Being able to trace their careers along with the careers of an unaffected control group allows us to evaluate the efficacy of technology transfer offices replacing the former informal activities of the university professors in regard of academic entrepreneurship. We find that an overall decrease of university patenting neutralizes any institutionalized efforts of spurring entrepreneurship at the expense of informal faculty-firm networks as channels for knowledge transfer

Disambiguation by namesake risk assessment

Most bibliometric databases only provide names as the handle to their careers leading to the issue of namesakes. We introduce a universal method to assess the risk of linking documents of different individuals sharing the same name with the goal of collecting the documents into personalized clusters. A theoretical setup for the probability of drawing a namesake depending on the number of namesakes in the population and the size of the observed unit replaces the need for training datasets, thereby avoiding a namesake bias caused by the inherent underestimation of namesakes in training/benchmark data. A Poisson model based on a master sample of unambiguously identified individuals estimates the main component, the number of namesakes for any given name. To implement the algorithm, we reduce the complexity in the data by resolving similarity in properties. At the core of the implementation is a mechanism returning the unit size of the intersected mutual properties linking two documents. Because of the high computational demands of this mechanism, it is a necessity to discuss means to optimize the procedure

The SearchEngine: A holistic approach to matching

The SearchEngine is an open source project providing an integrated framework for diverse matching activities, especially the linkage of large scale firm data by fuzzy criteria like company names and addresses. At its core, it utilizes an efficient candidate retrieval mechanism implementing a word respectively token driven heuristic. Every record in one table becomes a search term to retrieve similar candidate records in the base table according to a search strategy replacing blocking strategies of conventional matching efforts. Because similarity is inherently established by the candidate selection, it is only required to filter false positives by using the meta data export file derived from the matching heuristic to implement a machine learning approach. This paper discusses the general foundation of the heuristic and the algorithm while two detailed walkthroughs of company linkages show practical example

Knowledge creates markets : the influence of entrepreneurial support and patent rights on academic entrepreneurship

We use an exogenous change in German Federal law to examine how entrepreneurial support and the ownership of patent rights influence academic entrepreneurship. In 2002, the German Federal Government enacted a major reform called Knowledge Creates Markets that set up new infrastructure to facilitate university-industry technology transfer and shifted the ownership of patent rights from university researchers to their universities. Based on a novel researcher-level panel database that includes a control group not affected by the policy change, we find no evidence that the new infrastructure resulted in an increase in start-up companies by university researchers. The shift in patent rights may have strengthened the relationship between patents on university-discovered inventions and university start-ups; however, it substantially decreased the volume of patents with the largest decrease taking place in faculty-firm patenting relationships

Policy uncertainty and inventor mobility

We follow the migration patterns of European inventors and find evidence of a novel emigration determinant: policy uncertainty. We find that policy uncertainty raises the rate of inventor emigration by a notable magnitude. With a one standard deviation in the policy uncertainty of the home country, relative to the possible destination countries, the rate of inventor emigration increases by nearly 40%. Migrating inventors are subsequently exposed to lower levels of policy uncertainty in the destination country emphasising that uncertainty motivated the move. We conclude that these effects may have strong welfare implications at the aggregate leve

Mandatory financial information disclosure and credit ratings

When firms are forced to publicly disclose financial information, credit rating agencies are supposed to improve their risk assessments. Theory predicts such an information quality effect but also an adverse reputational concerns effect because credit analysts may become increasingly concerned about alleged rating failures. We empirically examine these predictions using a large scale quasi-natural experiment in Germany, where firms were required to publicly disclose annual financial statements. Consistent with the reputational concern hypothesis, we find an average increase in credit rating downgrades that is entirely driven by changes in the discretionary assessment of the credit analysts rather than changes in firm fundamentals. Analysts tend to give positive private information a lower weight in their risk assessment, while they put a higher weight on negative public information. A last set of results indicate that professional credit providers understand that the resulting downgrades are not warranted, while unsophisticated lenders did indeed reduce the provision of trade credit in response to the rating downgrades

How patent rights affect university science

How do intellectual property rights influence academic science? We investigate the consequences of the introduction of software patents in the U.S. on the publications of university researchers in the field of computer science. Difference-in-difference estimations reveal that software scientists at U.S. universities produced fewer publications (both in terms of quantity and quality) than their European counterparts after patent rights for software inventions were introduced. We then introduce a theoretical model that accounts for substitution and complementarity between patenting and publishing as well as for the direction of research. In line with the model’s prediction, further results show that the decrease in publications is largest for scientists at the bottom of the ability distribution. Further, we evidence a change in the direction of research following the reform towards more applied research