Use this URL to cite or link to this record in EThOS:
Title: Empirical studies on the social structure of knowledge
Author: Mohnen, M. M.
ISNI:       0000 0004 8498 9564
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2017
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
This thesis applies micro-econometric techniques to examine the effect of social structure on knowledge. Chapter 2 investigates the role of mass migration in the passage of compulsory schooling laws. It provides qualitative and quantitative evidence that compulsory schooling laws were used as a nation-building tool to homogenise the civic values held by the culturally diverse migrants who moved to America during the "Age of Mass Migration". Our central finding is that the adoption of compulsory schooling by American-born median voters occurs significantly earlier in time in states that host many migrants who had lower exposure to civic values in their home countries and had lower demand for common schooling when in the US. Chapter 3 explores whether, and to what extent, the position in the coauthorship network of medical scientists matters for the productivity of a researcher. I use sudden and unexpected deaths of star scientists as exogenous shocks to the network thus providing a causal identification of the loss of a star on the productivity of a scientist. I characterise the heterogeneity in the impact of the death by exploiting the position of the deceased scientists. Following the death of a star, coauthors suffer on average a 8% decrease in annual publications and this effect can differ by up to 31% depending on the network position. Chapter 4 examines knowledge spillovers by measuring the relative intensity of patent citations in two technological fields for which clean and dirty inventions can be clearly distinguished: energy production (renewables vs. fossil fuel energy generation) and automobiles (electric cars vs. internal combustion engines). We develop a new methodology based on Google's PageRank algorithm to measure the social benefit of knowledge spillover. We find that clean technologies generate 40% higher spillovers than their dirty counterparts.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available