Knowledge is a necessary and critically important factor in generating growth and increased prosperity. The extent to which such effects are materialized depends however on its diffusion and how it transcends into innovation, entrepreneurship and growing firms. This doctoral thesis consists of four papers that examine how labor mobility and innovation strategies influence the performance at the firm level with respect to new ventures, firm level growth and innovativeness.   The first paper provides empirical support of the validity of the knowledge-based spillover theory of entrepreneurship by employing a detailed database. The results indicate that both inter-regional labor inflows and intra-regional labor mobility exert a strong positive effect on entrepreneurship, while inter-regional outflows negatively affect entrepreneurial entry.   The second paper examines the influence of the labor mobility of knowledge workers on innovation at the firm level. New evidence are provided that reveals a positive and significant impact of labor mobility on firms’ innovations measured as patent applications.   In the third paper the influence of labor mobility between multinational enterprises (MNEs) and other firms on innovation is investigated. Looking at firms having different owner structures, empirical evidence are provided that particularly domestically owned MNEs generate strong knowledge spillovers to non-MNEs that translates into innovations.   The fourth paper examines the relationship between innovation and firm growth. We implement a classification of innovations based on whether they are explorative or exploitative. The more radical explorative innovations are shown to have a persistent growth effect in the long term, while exploitative innovation increases the labor demand predominantly in the short term. / <p>QC 20160401</p>

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<p> </p><p>The purpose of this paper is to examine whether foreign direct investment, FDI, has any impact on economic growth in Mexico. In order to find a possible connection I use a multiple regression analysis with GDP per capita as dependent variable. Furthermore, I critically examine previous studies of FDI and its effect on GDP per capita in Mexico as well as other studies with several developed and developing countries. The difference between this paper and previous studies is that the data is more up-to-date here. My results, like most of the previous studies, do not indicate on any statistical significance that FDI has a positive effect on economic growth. FDI do however seem to produce positive spillover effects on the domestic economy, mainly through knowledge and technological spillovers.</p><p> </p><p> </p>

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Master of Science / Department of Agricultural Economics / Ted C. Schroeder / In recent years, the agricultural markets have been subject to increased prices and unusual levels of elevated volatility. One likely driver of this is the mandated ethanol expansion in the Energy Policy Act of 2005. Previous research has identified relationships in market prices and variability between the energy and grain markets, but little has been done to evaluate volatility spillover across a broader spectrum of agricultural commodities. Additionally, few studies have assessed causal linkages across market implied volatilities. This research examines implied volatility spillover in futures markets across major agricultural commodities and energies. The analysis also determines the time path and magnitude of volatility translation across the markets and compares the causal relationships between pre-ethanol boom and post-ethanol boom time periods. Granger causality tests are conducted using multivariate and bivariate vector autoregressive modeling techniques, and impulse response functions are employed to obtain time paths of the reactions. Overall, results indicate that strong implied volatility spillover relationships exist between the grain markets and between the live cattle and feeder cattle markets. The analysis also finds that the agricultural markets have evolved from lean hogs being the primary volatility leader in the pre-ethanol boom era to corn being the primary volatility leader in the post-ethanol boom era. Despite a high correlation between crude oil and corn volatilities in the post-ethanol boom time period, the causal linkage between the two commodities’ volatilities may not be as definite as other literature suggests.

In this study, I examine the transmissions of volatility spillovers during the subprime crisis in the U.S between Vietnam and other Asian financial markets (Japan, Korea, China, Hong Kong, and Taiwan). I attempt to explore the level and magnitude of volatility spillover effects of other Asian markets on the Vietnam stock market by applying a multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) model. It is found that the level of the volatility effect of the selected financial markets on the Vietnamese stock market’s return from 2006 to August - 2009 increases over time. Particularly, the level of volatility transmissions and spillover effect of two developed markets, Hong Kong and Japan onto the Vietnamese market are relatively higher and more consistent than other markets during the 2006-2009 period. Also, the Vietnamese financial market seems to perform better than other markets during my 2006-2009 sample, including the financial crisis period in 2007.

<p><strong>Purpose</strong>- Previous literatures focus on  the  technology spillover from multinational companies to local companies. However, the great threats generated from spillover to subsidiaries were omitted. The purpose of this paper is to explore the variables which can help subsidiaries control the technology spillover.</p><p><strong>Methodology</strong>-  First a conceptual model is developed, which will then be used to map out how subsidiaries can control their technology spillover. An Adidas' local representative in China is used during the case study.</p><p><strong>Findings</strong>-  Findings indicate  that there is a possibility to  control  the technology spillover by adopting certain variables. There  are  however,  no omnipotent variables to  stop  the technology spillover. Thus the selection of variables employed needs to consider that products have different attributes.</p><p><strong>Value</strong>- This paper stresses the importance and the very necessity of controlling technology spillovers. Furthermore, it maps influencing variables and tests, whether these variables work in real case.</p>

The purpose of this paper is to examine whether foreign direct investment, FDI, has any impact on economic growth in Mexico. In order to find a possible connection I use a multiple regression analysis with GDP per capita as dependent variable. Furthermore, I critically examine previous studies of FDI and its effect on GDP per capita in Mexico as well as other studies with several developed and developing countries. The difference between this paper and previous studies is that the data is more up-to-date here. My results, like most of the previous studies, do not indicate on any statistical significance that FDI has a positive effect on economic growth. FDI do however seem to produce positive spillover effects on the domestic economy, mainly through knowledge and technological spillovers.

Purpose- Previous literatures focus on  the  technology spillover from multinational companies to local companies. However, the great threats generated from spillover to subsidiaries were omitted. The purpose of this paper is to explore the variables which can help subsidiaries control the technology spillover. Methodology-  First a conceptual model is developed, which will then be used to map out how subsidiaries can control their technology spillover. An Adidas' local representative in China is used during the case study. Findings-  Findings indicate  that there is a possibility to  control  the technology spillover by adopting certain variables. There  are  however,  no omnipotent variables to  stop  the technology spillover. Thus the selection of variables employed needs to consider that products have different attributes. Value- This paper stresses the importance and the very necessity of controlling technology spillovers. Furthermore, it maps influencing variables and tests, whether these variables work in real case.

Many communities around the country had already been dealing with the problems of increasing and concentrated foreclosures for several years. Thus, the evidence of the social costs of foreclosures will guide policy makers in deciding what policies should be put in many communities that foreclosures have plagued. The objective of this research is to quantify the price-depressing foreclosure effects on existing home sale prices as one of the major social costs for communities. The first methodological goal is to simultaneously quantify the magnitude of the direct and the spillover effects of foreclosures on existing home prices. The second methodological goal is to provide usefulness concerning spatial econometric models in measuring the impact of foreclosures on housing prices. This study was estimated with traditional hedonic and spatial hedonic models specified during two different housing cycles in Phoenix, Arizona, during a strong housing market when prices were up (2005) and a down housing market with falling prices (2008). It has been shown that foreclosures have negative effects on existing home prices in the neighborhood, depending on housing types and cycles. However, the OLS models do not correct for spatial autocorrelation problems and endogeneity that exist in a cross section of house prices and would overestimate absolute values of the coefficients. As alternatives, the maximum likelihood spatial lag or error model controls for spatial autocorrelation but still causes computation obstacles for large data sets and problems of heteroskedasticity in error terms. Thus, the preferred specification is a generalized method of moments (GMM) approach which requires weaker assumptions than the maximum likelihood application and has flexible form to large datasets. As a joint analysis, the most appropriate specification is the general spatial two-stage least-squares (GMM_2SLS) method with HAC (the spatial heteroskedasticity and autocorrelation consistent) variance estimator. These findings provide further evidence that OLS estimates of a coefficient on a foreclosure indicator tend to overstate the direct or indirect foreclosure discount, ignoring spatial effects such as spatial dependence and endogeneity. With regard to the spillover effect of nearby foreclosures on home prices, both foreclosures of single family homes and condos are statistically significant and negatively impact each type of home sale prices. However, the cumulative effects of neighborhood foreclosures are much greater with nonlinear effects in a housing bust year than a housing boom year. Therefore, this study on price-depressing effects of foreclosures emphasizes the importance of the pre-foreclosure step as the beginning of following foreclosure processes, depending on housing types and housing market cycles.