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.

Thesis (M.A.)--Carleton University, 2003. / Includes bibliographical references (p. 119-123). Also available in electronic format on the Internet.

Moore’s law is the main driving factor behind the rapid evolution of computers that has been observed in the past 50 years. Though the law is soon ending due to heat- and sizing-related issues. One solution to continuing the evolution is utilizing alternative computer hardware, where parallel hardware is especially interesting. The Field Programmable Gate Array (FPGA) is one such piece of hardware. This study compares the runtime of two linear-algebra benchmarks executed on a traditional CPU-based platform and an FPGA-based platform respectively. The benchmarks are called cholesky and durbin respectively. The cholesky benchmark performs Cholesky decomposition and the durbin benchmark computes the solution to a Yule-Walker equation. The CPU implementations of the benchmarks were provided in the C programming language and the FPGA implementations of the benchmarks were written using OpenCL, which is a High-Level-Synthesis framework. The results highlighted a clear advantage for the CPU implementations, which had a shorter runtime than the FPGA implementations in both benchmarks for every test case. This was caused by both benchmarks containing data dependencies, which required them to be executed sequentially. Since the CPU operates at a clock frequency more than ten times higher than the FPGA’s clock frequency, it executed sequential instructions faster than the FPGA. / Moores lag är den främsta orsaken till den snabba datorutveckling som skett de senaste 50 åren. På grund av svårigheter med värme och dimensionering närmar sig dock lagen sin applicerbara gräns. En lösning för att bibehålla utvecklingen är att nyttja alternativ hårdvara och särskilt intressant är parallell hårdvara. En Field Programmable Gate Array (FPGA) är ett exempel på sådan hårdvara. Denna studie jämför körtiden mellan två prestandatest för linjär-algebra-algoritmer som utvärderades på en traditionell CPU-baserad plattform och en FPGA-baserad plattform. Prestandatesterna kallas cholesky respektive durbin. Testet cholesky utför Choleskydekomposition och testet durbin löser en Yule-Walker-ekvation. CPU-implementationerna av testen tillhandahölls i programmeringsspråket C och FPGA-implementationerna av testen skrevs i OpenCL, som är ett ramverk för högnivåsyntes. Resultaten visade en tydlig fördel för CPU-implementationerna, som har en kortare körtid än FPGA-implementationerna för alla testfall i båda prestandatest. Detta orsakades av databeroenden som existerar i båda algoritmerna, vilket påtvingade en sekventiell exekvering. Då CPU:n når en närmare tio gånger högre klockfrekvens än FPGA:n exekverar den sålunda sekventiella instruktioner snabbare än FPGA:n.

Denna studie är en kvantitativ undersökning av Swedbanks, SEB:s och Nordeas ersättningssystem och finansiella prestationer. Vi har utgått från följande syfte: Vårt syfte med studien är att undersöka om det finns något samband mellan ledningens ersättning och finansiella prestationer. För att kunna besvara vår problemställning och vårt syfte har vi använt oss av ersättningssystem, agentteorin, intressentteorin och finansiella prestationsmått. Vi har valt prestationsmått vilka visar ett företags operativa resultat (EBIT, ROA, ROE, kassaflöde/totala tillgångar) och multipelvärdering (P/E-tal och P/S-tal). I vårt fall med enbart en oberoende variabel testas om det finns något samband på den beroende variabeln ur resultaten från enkel regressionsanalys. Vi har använt Durbin-Watson:s värdet i samtliga fall för att undersöka om det finns någon eventuell autokorrelation. Vi har även använt konfidensintervallberäkningar för att se om bankernas utbetalda ersättningar ligger inom konfidensintervallgränserna. Vi har inte kunnat visa på något samband i vår undersökning mellan ersättning och finansiella prestationsmått. För samtliga värden gällande Swedbank föreligger positiv autokorrelation.

This paper studies the use of Monte Carlo simulation techniques in the field of econometrics, specifically statistical inference. First, I examine several estimators by deriving properties explicitly and generate their distributions through simulations. Here, simulations are used to illustrate and support the analytical results. Then, I look at test statistics where derivations are costly because of the sensitivity of their critical values to the data generating processes. Simulations here establish significance and necessity for drawing statistical inference. Overall, the paper examines when and how simulations are needed in studying econometric theories.

Three different algorithms for the generation of stationary Gaussian time series with given autocorrelation function are presented in this paper. The algorithms have already been suggested in the literature but are not well known and have never been compared before. Interrelations between the different methods, advantages and disadvantages with respect to speed and memory requirements and the range of autocorrelation functions for which the different methods are stable are discussed. The time-complexity of the algorithms and the comparisons of their implementations show that the method twice using the Fourier transform is by far the most efficient if time series of moderate or large length are generated. A tested C-code of the latter algorithm is included as this method is tricky to implement and very difficult to find in the literature. (We know only one reference, that gives a correct algorithm, but there the description is very short and no proof is included.) (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

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)

Investing in public real estate stocks can diversify a stock portfolio due to the nature of these companies. The industry is generally less sensitive to economic downturns and spikes in inflation are offset by increased real estate property and rent prices. Nevertheless, measures of the wider economy could be used as predictors of the real estate stock market.  This thesis attempts to model the Swedish real estate stock market with the index SX35PI (Stockholm Real Estate PI) using the fundamental economic factors and repo rate. Data was collected and formatted to a monthly interval for the period February 2012 to December 2021. This resulted in an exponential multiple regression model that used all the regressors that explained 95.7% of the variation in SX35PI, and an alternative autoregressive forecasting model that explained 82.3% of the variation in SX35PI. / Investeringar i fastighetsbolag kan diversifiera en aktieportfölj tack vare dessa bolags karaktär. Denna industri är nämligen mindre känslig för ekonomiska nedgångar och minskad efterfråga samt plötsliga ökningar i inflationen som vägs upp av ökningar i fastighetspriser och hyror. Aktiemarknaden för fastighetsaktier kan modelleras med makroekonomiska mått. Denna rapport försöker modellera aktiemarknaden för svenska fastighetsbolag med fundamentala ekonomiska mått samt reporäntan. Data samlades och transformerades för att få datapunkter varje månad under februari 2012 till december 2021. Resultatet blev en exponentiell multipel regressionsmodell som använde alla förklarande variabler vilka förklarade 95.7% av variationen i SX35PI, och en alternativ autoregressiv modell som förklarade 82.3% av variationen i SX35PI.

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)