People often make social-related trips to perform activities with their friends. An individual's group of friends can be characterized by his or her social network. While traditional social network data collection is time-consuming and dependent on memory recollection, new online social networking sites may address these shortcomings. This research focuses on the use of tie-strength, the strength of an individual's relationships in his or her social network, to characterize friendships and how this influences an individual's air travel behavior. Four candidate weighting schemes were developed using data collected from a web-based survey which included demographic information, an air travel diary, and friendship information retrieved from Facebook.com. The candidate weight matrices were then tested in a spatial Durbin count model (social model). The results of this study are threefold. First, candidate weighting schemes which consider mutual friendship (i.e. the number of mutual friends two people have in common) exclusively produced higher log-likelihoods than weighting schemes which also consider whether individuals are direct friends (i.e. whether the two individuals are friends themselves). Second, the results of the social model were compared with those of a non-social model. These results suggest that there exist major flaws in using a non-social model to represent variables which may be socially dependent and correlated. Finally, results suggest that individuals tend to have friends who, on average, make more trips than they do. With a growing number of people using online social networks, exploring and understanding friendship influences on travel behavior will help the transportation industry better recognize future travel needs.

This paper focuses on Austrian outbound foreign direct investment (FDI, measured by sales of Austrian affiliates abroad) in Europe over the period 2009-2013, using a spatial Durbin panel data model specification with fixed effects, and a spatial weight matrix based on the first-order contiguity relationship of the countries and normalised by its largest eigenvalue. Third-country effects essentially enter the empirical analysis in two major ways: first, by the endogenous spatial lag on FDI (measured by FDI into markets nearby the host country), and, second, by including an exogenous market potential variable that measures the size of markets nearby the FDI host country in terms of gross domestic product. The question whether the empirical result is compatible with horizontal, vertical, export-platform or complex vertical FDI then depends on the sign and significance levels of both the coefficient of the spatial lag on FDI and the direct impact estimate of the market potential variable. The paper yields robust results that provide significant empirical evidence for horizontal FDI as the main driver of Austrian outbound FDI in Europe. This result is strengthened by the indirect impact estimate of the market potential variable indicating that spatial spillovers do not matter. (authors' abstract) / Series: Working Papers in Regional Science

This paper focuses on Austrian outbound foreign direct investment (FDI, measured by sales of Austrian affiliates abroad) in Europe over the period 2009-2013, using a spatial Durbin panel data model specification with fixed effects, and a spatial weight matrix based on the first-order contiguity relationship of the countries and normalised by its largest eigenvalue. Third-country effects essentially enter the empirical analysis in two major ways: first, by the endogenous spatial lag on FDI (measured by FDI into markets nearby the host country), and, second, by including an exogenous market potential variable that measures the size of markets nearby the FDI host country in terms of gross domestic product. The question whether the empirical result is compatible with horizontal, vertical, export-platform or complex vertical FDI then depends on the sign and significance levels of both the coefficient of the spatial lag on FDI and the direct impact estimate of the market potential variable. The paper yields robust results that provide significant empirical evidence for horizontal FDI as the main driver of Austrian outbound FDI in Europe. This result is strengthened by the indirect impact estimate of the mark et potential variable indicating that spatial spillovers do not matter. (authors' abstract)

This paper presents a theoretical growth model that extends the Mankiw-Romer-Weil [MRW] model by accounting for technological interdependence among regional economies. Interdependence is assumed to work through spatial externalities caused by disembodied knowledge diffusion. The transition from theory to econometrics leads to a reduced-form empirical spatial Durbin model specification that explains the variation in regional levels of per worker output at steady state. A system of 198 regions across 22 European countries over the period from 1995 to 2004 is used to empirically test the model. Testing is performed by assessing the importance of cross-region technological interdependence, and measuring direct and indirect (spillover) effects of the MRW determinants on regional output. (author's abstract)

This paper explores the contribution of knowledge capital to total factor productivity differences among regions within a regression framework. The dependent variable is total factor productivity, defined as output (in terms of gross value added) per unit of labour and physical capital combined, while the explanatory variable is a patent stock measure of regional knowledge endowments. We provide an econometric derivation of the relationship, which in the presence of unobservable knowledge capital leads to a spatial regression model relationship. This model form is extended to account for technological dependence between regions, which allows us to quantify disembodied knowledge spillover impacts arising from both spatial and technological proximity. A six-year panel of 198 NUTS-2 regions spanning the period from 1997 to 2002 was used to empirically test the model, to measure both direct and indirect effects of knowledge capital on regional total factor productivity, and to assess the relative importance of knowledge spillovers from spatial versus technological proximity. (authors' abstract)

This paper presents a theoretical growth model that extends the Mankiw-Romer-Weil [MRW] model by accounting for technological interdependence among regional economies. Interdependence is assumed to work through spatial externalities caused by disembodied knowledge diffusion. The transition from theory to econometrics leads to a reduced-form empirical spatial Durbin model specification that explains the variation in regional levels of per worker output at steady state. A system of 198 regions across 22 European countries over the period from 1995 to 2004 is used to empirically test the model. Testing is performed by assessing the importance of cross-region technological interdependence, and measuring direct and indirect (spillover) effects of the MRW determinants on regional output. (author's abstract)

This paper explores the contribution of knowledge capital to total factor productivity differences among regions within a regression framework. We provide an econometric derivation of the relationship and show that the presence of latent/unobservable regional knowledge capital leads to a model relationship that includes both spatial and technological dependence. This model specification accounts for both spatial and technological dependence between regions, which allows us to quantify spillover impacts arising from both types of interaction. Sample data on 198 NUTS-2 regions spanning the period from 1997 to 2002 was used to empirically test the model, to measure both direct and indirect effects of knowledge capital on regional total factor productivity, and to assess the relative importance of knowledge spillovers from spatial versus technological proximity. (authors' abstract)

This paper employs a spatial Durbin model for analyzing the impact of human capital on regional productivity using for 198 NUTS-2 European regions for the sample period from 1995 to 2004. The study provides evidence for the existence of spatial externalities and interactions of the sort as emphasized by new growth theory. To interpret results meaningfully, we calculate summary measures that account for the simultaneous feedback nature of the underlying model. By sampling from the parameter distribution we present measures of dispersion, revealing that it is relative regional advantages in human capital that matter most for productivity growth. (authors' abstract)

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