The Experts below are selected from a list of 170901 Experts worldwide ranked by ideXlab platform
Toby E Stuart - One of the best experts on this subject based on the ideXlab platform.
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syndication networks and the spatial distribution of venture capital Investments
American Journal of Sociology, 2001Co-Authors: Olav Sorenson, Toby E StuartAbstract:Sociological investigations of economic exchange reveal how institutions and social structures shape transaction patterns among economic actors. This article explores how interfirm networks in the U.S. venture capital (VC) market affect spatial patterns of exchange. Evidence suggests that information about Potential Investment opportunities generally circulates within geographic and industry spaces. In turn, the circumscribed flow of information within these spaces contributes to the geographic‐ and industry‐localization of VC Investments. Empirical analyses demonstrate that the social networks in the VC community—built up through the industry’s extensive use of syndicated investing—diffuse information across boundaries and therefore expand the spatial radius of exchange. Venture capitalists that build axial positions in the industry’s coInvestment network invest more frequently in spatially distant companies. Thus, variation in actors’ positioning within the structure of the market appears to differentia...
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syndication networks and the spatial distribution of venture capital Investments
Social Science Research Network, 1999Co-Authors: Olav Sorenson, Toby E StuartAbstract:Sociological investigations of economic exchange pay particular attention to the manner in which institutions and social structures shape transactions among economic actors. Extending this line of inquiry, we explore how interfirm networks in the US venture capital (VC) market from 1986 to 1998 affect the spatial patterns of exchange. We present evidence suggesting that geographic and industry spaces represent natural boundaries that contain the transmission of information about Potential Investment opportunities. In turn, the highly circumscribed flow of information within these spaces contributes to the geographic- and industry-localization of venture capital Investments. After establishing this finding, the majority of our empirical analyses document that the social networks in the venture capital community ? built up through the industry's extensive use of syndicated investing ? facilitate the diffusion of information across geographic and industry boundaries and therefore expand the spatial radius of exchange. We show that VCs that build axial positions in the industry's co-Investment network can obtain information from distant sources and hence expand the scope of their Investments over time. Consistent with the sociologist's general view of markets, variation across actors in their positioning within the structure of a market appears to differentiate market participants in their ability to overcome boundaries that otherwise would curtail exchange.
Paul Oyer - One of the best experts on this subject based on the ideXlab platform.
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the making of an Investment banker macroeconomic shocks career choice and lifetime income
National Bureau of Economic Research, 2006Co-Authors: Paul OyerAbstract:New graduates of elite MBA programs flock to Wall Street during bull markets and start their careers elsewhere when the stock market is weak. Given the transferability of MBA skills, it seems likely that any effect of stock returns on MBA placement would be short-lived. In this paper, I use a survey of Stanford MBAs from the classes of 1960 through 1997 to analyze the relationship between the state of the stock market at graduation, initial job placement, and long-term labor market outcomes. Using stock market conditions at graduation as an instrument for first job, I show that there is a strong causal effect of initial placement in Investment banking on the likelihood of working on Wall Street anywhere from three to twenty years later. I then measure the Investment banking compensation premium relative to other jobs and estimate the additional income generated by an MBA cohort where a higher fraction starts in higher-paid jobs relative to a cohort that starts in lower-paid areas. The results lead to several conclusions. First, random factors play a large role in determining the industries and incomes of members of this high-skill group. Second, there is a deep pool of Potential Investment bankers in any given Stanford MBA class. During the time these people are in school, factors beyond their control sort them into or out of banking upon graduation. Finally, industry-specific or task-specific human capital appears to be important for young Investment bankers.
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the making of an Investment banker macroeconomic shocks career choice and lifetime income
Social Science Research Network, 2006Co-Authors: Paul OyerAbstract:New graduates of elite MBA programs flock to Wall Street during bull markets and start their careers elsewhere when the stock market is weak. Given the transferability of MBA skills, it seems likely that any effect of stock returns on MBA placement would be short-lived. In this paper, I use a survey of Stanford MBAs from the classes of 1960 through 1997 to analyze the relationship between the state of financial market at graduation, initial job placement, and longterm labor market outcomes. Using stock market conditions at graduation as an instrument for first job, I show that there is a strong causal effect of initial placement in Investment banking on the likelihood of working on Wall Street anywhere from three to twenty years later. I then measure the Investment banking compensation premium relative to other jobs and estimate the additional income generated by an MBA cohort where a higher fraction starts in higher-paid jobs relative to a cohort that starts in lower-paid areas. The results lead to several conclusions. First, random factors play an important role in determining the industries and incomes of members of this high-skill group. Second, there is a deep pool of Potential Investment bankers in any given Stanford MBA class. During the time these people are in school, factors beyond their control sort them into or out of banking upon graduation. Finally, industry-specifi co r task-specific human capital appears to be important for young Investment bankers.
Olav Sorenson - One of the best experts on this subject based on the ideXlab platform.
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syndication networks and the spatial distribution of venture capital Investments
American Journal of Sociology, 2001Co-Authors: Olav Sorenson, Toby E StuartAbstract:Sociological investigations of economic exchange reveal how institutions and social structures shape transaction patterns among economic actors. This article explores how interfirm networks in the U.S. venture capital (VC) market affect spatial patterns of exchange. Evidence suggests that information about Potential Investment opportunities generally circulates within geographic and industry spaces. In turn, the circumscribed flow of information within these spaces contributes to the geographic‐ and industry‐localization of VC Investments. Empirical analyses demonstrate that the social networks in the VC community—built up through the industry’s extensive use of syndicated investing—diffuse information across boundaries and therefore expand the spatial radius of exchange. Venture capitalists that build axial positions in the industry’s coInvestment network invest more frequently in spatially distant companies. Thus, variation in actors’ positioning within the structure of the market appears to differentia...
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syndication networks and the spatial distribution of venture capital Investments
Social Science Research Network, 1999Co-Authors: Olav Sorenson, Toby E StuartAbstract:Sociological investigations of economic exchange pay particular attention to the manner in which institutions and social structures shape transactions among economic actors. Extending this line of inquiry, we explore how interfirm networks in the US venture capital (VC) market from 1986 to 1998 affect the spatial patterns of exchange. We present evidence suggesting that geographic and industry spaces represent natural boundaries that contain the transmission of information about Potential Investment opportunities. In turn, the highly circumscribed flow of information within these spaces contributes to the geographic- and industry-localization of venture capital Investments. After establishing this finding, the majority of our empirical analyses document that the social networks in the venture capital community ? built up through the industry's extensive use of syndicated investing ? facilitate the diffusion of information across geographic and industry boundaries and therefore expand the spatial radius of exchange. We show that VCs that build axial positions in the industry's co-Investment network can obtain information from distant sources and hence expand the scope of their Investments over time. Consistent with the sociologist's general view of markets, variation across actors in their positioning within the structure of a market appears to differentiate market participants in their ability to overcome boundaries that otherwise would curtail exchange.
Mariliis Lehtveer - One of the best experts on this subject based on the ideXlab platform.
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bioenergy with carbon capture and storage beccs global Potential Investment preferences and deployment barriers
Energy research and social science, 2018Co-Authors: Mathias Fridahl, Mariliis LehtveerAbstract:Keeping global warming well below 2 °C entails radically transforming global energy production and use. However, one important mitigation option, the use of bioenergy with carbon capture and storag ...
Joan L Walker - One of the best experts on this subject based on the ideXlab platform.
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a discrete choice framework for modeling and forecasting the adoption and diffusion of new transportation services
Transportation Research Part C-emerging Technologies, 2017Co-Authors: Feras El Zarwi, Akshay Vij, Joan L WalkerAbstract:Abstract Major technological and infrastructural changes over the next decades, such as the introduction of autonomous vehicles, implementation of mileage-based fees, carsharing and ridesharing are expected to have a profound impact on lifestyles and travel behavior. Current travel demand models are unable to predict long-range trends in travel behavior as they do not entail a mechanism that projects membership and market share of new modes of transport (Uber, Lyft, etc.). We propose integrating discrete choice and technology adoption models to address the aforementioned issue. In order to do so, we build on the formulation of discrete mixture models and specifically Latent Class Choice Models (LCCMs), which were integrated with a network effect model. The network effect model quantifies the impact of the spatial/network effect of the new technology on the utility of adoption. We adopted a confirmatory approach to estimating our dynamic LCCM based on findings from the technology diffusion literature that focus on defining two distinct types of adopters: innovator/early adopters and imitators. LCCMs allow for heterogeneity in the utility of adoption for the various market segments i.e. innovators/early adopters, imitators and non-adopters. We make use of revealed preference (RP) time series data from a one-way carsharing system in a major city in the United States to estimate model parameters. The data entails a complete set of member enrollment for the carsharing service for a time period of 2.5 years after being launched. Consistent with the technology diffusion literature, our model identifies three latent classes whose utility of adoption have a well-defined set of preferences that are significant and behaviorally consistent. The technology adoption model predicts the probability that a certain individual will adopt the service at a certain time period, and is explained by social influences, network effect, socio-demographics and level-of-service attributes. Finally, the model was calibrated and then used to forecast adoption of the carsharing system for Potential Investment strategy scenarios. A couple of takeaways from the adoption forecasts were: (1) placing a new station/pod for the carsharing system outside a major technology firm induces the highest expected increase in the monthly number of adopters; and (2) no significant difference in the expected number of monthly adopters for the downtown region will exist between having a station or on-street parking.
