In this thesis, I propose that bike courier delivery is not merely a convenient service for clients but an important function in the operation of successful economies. By allowing the regions to function at higher speeds, same-day courier networks seem to play an active role in generating positive economic outcomes. The availability of courier networks is found to be as uneven as economic vitality itself. Cities like New York and Toronto have large, dense courier networks, capable of delivering items within an hour while smaller cites, do not support same-day courier service at all. They do this, in part, by allowing for couriers to cope with the precariousness of their work, and in part by providing supportive sub-cultures. These findings point to the role of service workers, and wider eco-systems in fostering regional advantage.

In this thesis, I propose that bike courier delivery is not merely a convenient service for clients but an important function in the operation of successful economies. By allowing the regions to function at higher speeds, same-day courier networks seem to play an active role in generating positive economic outcomes. The availability of courier networks is found to be as uneven as economic vitality itself. Cities like New York and Toronto have large, dense courier networks, capable of delivering items within an hour while smaller cites, do not support same-day courier service at all. They do this, in part, by allowing for couriers to cope with the precariousness of their work, and in part by providing supportive sub-cultures. These findings point to the role of service workers, and wider eco-systems in fostering regional advantage.

Knowledge, learning, and innovation are vital elements in facilitating economic development and growth. Technological change, which is a synonym for generating knowledge, the diffusion thereof, and subsequent application in the marketplace in the form of novel products and processes, i.e. innovations, has a strong effect on the collective wealth of regions and nations. Knowledge spillovers, which are unintended knowledge flows that take place among spatial (geography) and sectoral (industry) units of observation, provide a rationale for diverging growth rates among spatial units, well beyond what might be explained by variations in jurisdictional factor endowments, and thus are of particular interest in this context. Measuring and quantifying the creation and diffusion of knowledge has proven to be a challenging endeavor. One way to capture technical and economically valuable knowledge is by means of patent and patent citation analysis. Following this approach, and utilizing a novel patent database that has been specifically developed for this purpose, the present dissertation investigates the spatio-sectoral patterns of knowledge spillovers in the Canadian economy over the time period 1983 to 2007. The employed research methodology addresses existing limitations in this stream of research, and contributes to the continuing debate regarding the significance of sectoral specialization versus diversity, and local versus non-local knowledge spillovers as the main driver of knowledge formation processes leading to innovation at the sub-regional scale. The findings indicate that knowledge spillovers are localized, and furthermore, that this localization effect has increased over time for both spillovers within a particular industry, as well as between industry sectors. The analysis of micro-geographic industry specific spatio-sectoral knowledge formation processes, and the inquiry into local sectoral knowledge spillover patterns, outlines how regional evolutionary technology trajectories potentially shape the rate and direction of technological change, and consequently influence economic growth, at a particular place.

Identifying the emergence and development of new technologies has become an essential ability for firms competing in dynamic environments. Nonetheless, current technology intelligence practices are unstructured and vaguely defined. Moreover, the existing literature in future technology studies lacks strong, systematic explanations of what technologies are, where technologies come from, and how new technologies emerge and evolve. The present study builds on Structuration Theory, and proposes the structurational model of emerging technologies (SMET). The SMET suggests not only an ongoing view of technologies as social objects, but also a process for thinking through scientifically the complex, multidimensional and emergent dynamic of social and technological change. The SMET proposes that the emergence and development of a new technology can be tracked by examining systematically and collectively the extent of development of its technology-related social structure – its degree of structuration. The degree of structuration of a technology is an ongoing process instantiated in social practices, and can be observed through visible patterns or specific social outcomes of systemic activity organized in three analytical dimensions: structures of meaning, power, and legitimacy. The SMET assumes that the conceptual initiation of a new technology triggers new patterns of social activity or a signal of technological change; thus, the variation in the slope or trajectory of the degree of structuration of a technology may indicate an early signal of technological change. The SMET sets a foundation for identifying early signals of technological change when it is used on a systematic basis. Empirically, the study conducted an exploratory case study in the Internet industry. The study employed a sequential transformative mixed method procedure, and relied on 77 Internet experts to create retrospectively a systematic and collective interpretation of the Internet industry in the last ten (10) years. The test of hypotheses was based on only seven (7) Internet technologies due to time and instrumental constraints. The results confirm the fundamental relationships among constructs in the model, and support, thus, the SMET. The degree of structuration of a technology is revealed as a process independent of individuals’ participation in the enactment of a technology. Technological outcomes are explained by the extent of development of structures of meaning, power, and legitimacy (i.e., the degree of structuration of a technology). Moreover, influential technological outcomes shape individuals’ perspectives over time – i.e., the structurational effect. Hence, the study not only provides evidence that supports this novel theoretical framework, but also illustrates methodologically how to identify the emergence and development of new technologies. Likewise, the study discusses the implications of these results for technology management practices (e.g., product and technology development, innovation policies, and technology transfer activities). Lastly, the study recognizes limitations and suggests further research avenues.

This dissertation consists of three essays in applied microeconomics. These essays investigate different aspects of the impact of technology on labor market outcomes and firm strategy. The first essay, co-authored with Ronald L. Oaxaca, is in the area of labor economics and it investigates the relation between non-neutral technological change and the gender gap in wages. This essay is the first to address the issue of the recent narrowing of the gender wage gap in the context of technological change by using a novel approach to separately estimate the effects of technological change and discrimination on the gender wage gap. Using a constant elasticity of substitution production function and Current Population Survey data on employment and wages by industry and occupation, the results show that changes in non-neutral technological change explain between 5% and 9% of the narrowing of the wage gap between 1979 and 2001. The latter two essays span topics across applied industrial organization, firm strategy and labor economics. The second component of my dissertation investigates the relation between technological knowledge diffusion through the labor mobility of scientists and the organization of R&D activities by innovative firms. Using a labor mobility measure from the Current Population Survey March Supplements as a measure for inter-firm technology spillovers and a panel of R&D alliance data for 18 U.S. industries between 1989 and 1999, a Poisson estimation shows that firms facing a 10% increase in the labor mobility of scientists have a 5% increase in the annual number of R&D collaborations. The third essay is an empirical analysis of the impact of knowledge dissemination generated by the labor mobility of scientists and engineers on a measure of the pace of innovation. Using an unbalanced panel of firms containing patent data matched with firm data across eight innovative industries, from 1989 to 1998, along with a measure of the labor mobility of scientists and engineers, this essay provides evidence that firms in industries exposed to levels of labor mobility of scientists and engineers that differ by 1%, have an expected time lag between sequential generations of technologies that differs by 0.56 years.

Identifying the emergence and development of new technologies has become an essential ability for firms competing in dynamic environments. Nonetheless, current technology intelligence practices are unstructured and vaguely defined. Moreover, the existing literature in future technology studies lacks strong, systematic explanations of what technologies are, where technologies come from, and how new technologies emerge and evolve. The present study builds on Structuration Theory, and proposes the structurational model of emerging technologies (SMET). The SMET suggests not only an ongoing view of technologies as social objects, but also a process for thinking through scientifically the complex, multidimensional and emergent dynamic of social and technological change. The SMET proposes that the emergence and development of a new technology can be tracked by examining systematically and collectively the extent of development of its technology-related social structure – its degree of structuration. The degree of structuration of a technology is an ongoing process instantiated in social practices, and can be observed through visible patterns or specific social outcomes of systemic activity organized in three analytical dimensions: structures of meaning, power, and legitimacy. The SMET assumes that the conceptual initiation of a new technology triggers new patterns of social activity or a signal of technological change; thus, the variation in the slope or trajectory of the degree of structuration of a technology may indicate an early signal of technological change. The SMET sets a foundation for identifying early signals of technological change when it is used on a systematic basis. Empirically, the study conducted an exploratory case study in the Internet industry. The study employed a sequential transformative mixed method procedure, and relied on 77 Internet experts to create retrospectively a systematic and collective interpretation of the Internet industry in the last ten (10) years. The test of hypotheses was based on only seven (7) Internet technologies due to time and instrumental constraints. The results confirm the fundamental relationships among constructs in the model, and support, thus, the SMET. The degree of structuration of a technology is revealed as a process independent of individuals’ participation in the enactment of a technology. Technological outcomes are explained by the extent of development of structures of meaning, power, and legitimacy (i.e., the degree of structuration of a technology). Moreover, influential technological outcomes shape individuals’ perspectives over time – i.e., the structurational effect. Hence, the study not only provides evidence that supports this novel theoretical framework, but also illustrates methodologically how to identify the emergence and development of new technologies. Likewise, the study discusses the implications of these results for technology management practices (e.g., product and technology development, innovation policies, and technology transfer activities). Lastly, the study recognizes limitations and suggests further research avenues.

This thesis is an investigation of econometric crop yield models divided into two essays. In the first essay, I propose estimating a single heteroscedasticity coefficient for all counties within a crop-reporting district by pooling county-level crop yield data in a two-stage estimation process. In the context of crop insurance---where heteroscedaticity has significant economic implications---I demonstrate the pooling approach provides economically and statistically significant improvements in rating crop insurance contracts over contemporary methods. In the second essay, I propose a new method for measuring the rate of technological change in crop yields. To date the agricultural economics literature has measured technological change exclusively at the mean; in contrast, the proposed model can measure the rate of technological change in endogenously-defined yield subpopulations. I find evidence of different rates of technological change in yield subpopulations, which leads to interesting questions about the effect of technological change on agricultural production. / Ontario Ministry of Agriculture and Food

During the first two thirds of the 20th century, electricity, running water, and a host of new consumer durables diffused into most American homes. These new household technologies revolutionized domestic life by freeing up time from basic housework. In this dissertation, I study the consequences of household technological change on families, focusing on fertility, child health, marriage, and female labour force participation. Chapter 1 provides a short history of household modernization. I then present an econometric framework for evaluating the effects of household technological change, and discuss the main estimation challenges. To address these issues, I introduce an estimation strategy based on a newly-assembled dataset that captures the rollout of the U.S. power grid during the mid-20th century. In chapter 2, I study the impact of household technological change on fertility and child health, exploiting substantial cross-county and cross-state variation in the timing of when households acquired new consumer durables. Modern household technologies led families to make a child quantity-quality tradeoff favouring quality: household modernization is associated with decreases in infant mortality and decreases in fertility. The declines in infant mortality were particularly large in states where households had relied heavily on coal for heating and cooking, where the potential to improve indoor air quality was greatest. Health improvements were also larger in states that had previously invested heavily in maternal education, suggesting that household modernization led parents to provide better infant care. Overall, household technological change can account for between 25% and 30% of the total decline in infant mortality between 1930 and 1960. In chapter 3, I examine the relationship between household modernization, investment in children, and female employment. I present a conceptual framework in which household technological change has little immediate impact on female employment, but generates increased investment in daughters' human capital, ultimately causing a rise in employment for subsequent cohorts of women. I find empirical support for these predictions. Further, the results suggest that the diffusion of modern technology into the home during the first half of the 20th century can account for a significant fraction of the rise in female employment after 1950.

This paper examines a dynamic stochastic model of a competitive industry with heterogeneous firms that allows for entry, exit and mergers of firms in equilibrium. The model we build is an extension of a modified version of Jovanovic and Rousseau's (2002) model that introduces financial frictions, describes the market for corporate control and endogenizes its equilibrium price, and develops a stationary equilibrium à la Hopenhayn (1992). It provides a theoretical framework within which to study factors affecting variables such as entry, exit and investment through direct unbundled capital good purchase and mergers. This work contributes to the literature by suggesting another explanation to many empirical regularities and describing one more mechanism through which aggregate liquidity shocks may affect merger activity. The results suggest that due to asymmetric information about entrepreneur's survival probabilities aggregate liquidity shocks may contribute to codetermine the turnover rate of firms and investment levels through mergers.

This dissertation addresses the crucial problem of how environmental policy uncertainty influences investments in energy technological change. The rising level of carbon emissions due to increasing global energy consumption calls for policy shift. In order to stem the negative consequences on the climate, policymakers are concerned with carving an optimal regulation that will encourage technology investments. However, decision makers are facing uncertainties surrounding future environmental policy. The first part considers the treatment of technological change in theoretical models. This part has two purposes: (1) to show-through illustrative examples-that technological change can lead to quite different, and surprising, impacts on the marginal costs of pollution abatement. We demonstrate an intriguing and uncommon result that technological change can increase the marginal costs of pollution abatement over some range of abatement; (2) to show the impact, on policy, of this uncommon observation. We find that under the assumption of technical change that can increase the marginal cost of pollution abatement over some range, the ranking of policy instruments is affected. The second part builds on the first by considering the impact of uncertainty in the carbon tax on investments in a portfolio of technologies. We determine the response of energy R&D investments as the carbon tax increases both in terms of overall and technology-specific investments. We determine the impact of risk in the carbon tax on the portfolio. We find that the response of the optimal investment in a portfolio of technologies to an increasing carbon tax depends on the relative costs of the programs and the elasticity of substitution between fossil and non-fossil energy inputs. In the third part, we zoom-in on the portfolio model above to consider how uncertainty in the magnitude and timing of a carbon tax influences investments. Under a two-stage continuous-time optimal control model, we consider the impact of these uncertainties on R&D spending that aims to lower the cost of non-fossil energy technology. We find that our results tally with the classical results because it discourages near-term investment. However, timing uncertainty increases near-term investment.