Club-convergence analysis provides a more realistic and detailed picture about regional income growth than traditional convergence analysis. This paper presents a spatial econometric framework for club-convergence testing that relates the concept of club-convergence to the notion of spatial heterogeneity. The study provides evidence for the club-convergence hypothesis in cross-regional growth dynamics from a pan-European perspective. The conclusions are threefold. First, we reject the standard Barro-style regression model which underlies most empirical work on regional income convergence in favour of a two regime [club] alternative in which different regional economies obey different linear regressions when grouped by means of Getis and Ord's local clustering technique. Second, the results point to a heterogeneous pattern in the pan-European convergence process. Heterogeneity appears in both the convergence rate and the steady-state level. But, third, the study also reveals that spatial error dependence introduces an important bias in our perception of the club-convergence and shows that neglect of this bias would give rise to misleading conclusions.

This paper presents a theoretical growth model that accounts for technological interdependence among regions in a Mankiw-Romer-Weil world. The reasoning behind the theoretical work is that technological ideas cannot be fully appropriated by investors and these ideas may diffuse and increase the productivity of other firms. We link the diffusion of ideas to spatial proximity and allow for ideas to flow to nearby regional economies. Through the magic of solving for the reduced form of the theoretical model and the magic of spatial autoregressive processes, the simple dependence on a small number of neighbouring regions leads to a reduced form theoretical model and an associated empirical model where changes in a single region can potentially impact all other regions. This implies that conventional regression interpretations of the parameter estimates would be wrong. The proper way to interpret the model has to rely on matrices of partial derivatives of the dependent variable with respect to changes in the Mankiw-Romer-Weil variables, using scalar summary measures for reporting the estimates of the marginal impacts from the model. The summary impact measure estimates indicate that technological interdependence among European regions works through physical rather than human capital externalities.

The focus of this dissertation is local government expenditure, where growth, quality, and equality is in the center of attention Essay 1: Sports and Local Growth in Sweden: Is a Sports Team Good for Local Economic Growth? The purpose of Essay 1 is to analyzethe effect of professional sports on the municipality’s tax base. I find no indications of a positive effect on the growth rate of per capita income from having a team in the top series. Essay 2: Equality of Quality of Day Activity Service Programs in Sweden. In this Essay we investigates the equality of the day activity service programs for people with intellectual disabilities provided by local governments in Sweden. The findings are that despite the Act concerning Support and Service for Persons with Certain Functional Impairments intended to secure equality in living conditions, the quality of day activity service programs seems to be dependent on the local government’s tax base as well as the political preferences. In Essay 3: Analysis of Cost and Quality Indicators of Day Activity Service Programs in Sweden, we analyze the distribution of observable quality indicators for daily activity service programs. We find that municipalities that conduct regular user surveys find reasons to spend more per user on average. Additionally, the probability for transitions to employment at a regular workplace is higher in municipalities where as a routine a review is made of whether each participant can be offered an internship or work. The objective of Essay 4: The Composition of Local Government Expenditure and Growth: Empirical Evidence from Sweden, is to analyze whether there is a possibility of enhancing the average income growth rate at the local level by redistributing expenditure between main functional areas of local governments, while keeping the budget restriction fixed. We find that devoting large shares of expenditure on areas that increase labor supply, such as child care are positively related to growth in income. Additionally we find that spending areas previously categorized as productive can have a non-linier relationship with growth.

In this dissertation, I investigate how different aspects of the procurement process and evaluation affect bidding behavior. In essay 1, we attempt to map public procurements in Sweden by gathering a representative sample of procurements. We find that framework agreements and multiple-contract procurements represent a very large share of total government spending. The total value procured by government authorities, municipalities and counties accounts to 215 BSEK yearly, which we believe is an underestimate due to data issues. Essay 2 suggests a simple method for of estimating bidding costs in public procurement, and are empirically estimated to be approximately 2 percent of the procurement value using a comprehensive dataset and approximately 0.5 percent for a more homogeneous road re-pavement dataset. Our method provides reasonable estimates with, compared to other methods, relatively low data requirements. Essay 3 investigates the effect of quality evaluation on small and medium-sized enterprises (SMEs). Contrary to common belief, SMEs’ participation does not increase when evaluating quality, and their probability to win procurements decreases compared with that of large firms. In essay 4, the bidders’ decision to apply for a procurement review “appeal” is investigated. Contrary to procurers’ beliefs, evaluating quality is found not to have any statistically significant effect on the probability of appeals. Instead, I empirically confirm theoretical prediction of the 1st runner-up’s decision to claim the evaluation to be redone, as well as free-riding in appealing. In essay 5, we test whether spatial econometrics can be used to test for collusion in procurement data. We apply this method on a known cartel and test during and after the period the cartel was active. Our estimates support the proposition that spatial econometrics can be used to test for collusive behavior.

Various adaptation and mitigation strategies have been explored to cope with changes in the climate. Estimating these strategies impacts on the local economy is one of the growing and pressing issues for the management of natural resources. This thesis consists of three parts and aims to contribute to regional economic studies by analyzing: (1) the economic impact of solar energy facilities, (2) the level of virtual water flow and the effectiveness of scenarios to mitigate water resource shortage, and (3) the impact of climate change on agriculture through a Ricardian approach weighted by stream flow connectivity. As an increasingly adopted renewable energy resource, solar power has a high potential for carbon emission reduction and economic development. In the first essay the impacts on jobs, income, and economic output of a new solar power plant are calculated in an input-output framework. The contribution is twofold. First, we compare the multipliers generated by the construction and operation/maintenance of a plant located in California with those that would pertain had it been built in Arizona. Second, we point out the differences in the results obtained with the popular IMPLAN software from those obtained with the solar photovoltaic model of JEDI. The second essay focuses on water use in Arizona. As much as 73% of the state's scarce water is used by a single sector: crop production. Because 79% of Arizona's crop production is consumed outside the state, this means that, 67% of the water available in the state is being exported to the rest of the country and abroad. This should be of major concern for a state expected to see its population grow and its climate get drier. Using input-output techniques we explore three scenarios aimed at saving 19% of the water available. This figure is based on the results of the first of the scenarios that explores how much can be saved through improving the efficiency of the current irrigation system. The second scenario shows that equivalent water savings could be reached by a twenty-seven-fold increase in the price of water. The third scenario shows that a 19.5% reduction in crop exports could conserve an equal amount of water. The model results suggest that the least costly solution is a more efficient irrigation system, while export reduction is the second best choice. The third and final essay offers an extension of the well-known Ricardian model of agrarian economic rent. In spite of its popularity among studies of the impact of climate change on agriculture, there has been few attempts to examine the role of interregional spillovers in this framework. We remedy this gap by focusing on the spatial externalities of surface water flow used for irrigation purposes and demonstrate that farmland value—the usual dependent variable used in the Ricardian framework—is a function of the climate variables experienced locally and in upstream locations. This novel approach is tested empirically on a spatial panel model estimated across the counties of the Southwest USA for every five-year period from 1997 to 2012. This region is one of the driest in the country, hence its agriculture relies heavily on irrigation with the preponderance of the sources being surface water transported over long distances. The results highlight the significant role of irrigation spillovers and indicate that the actual impact of climate change on agriculture and subsequent adaptation policies can no longer overlook the streamflow network.

La littérature économique attribuant des rôles endogènes à l'évolution technologique et à lagéographie pour expliquer la croissance économique suggère que la compréhension des fluxde connaissances dans l'espace et de leurs conséquences sur les activités d'innovation est aucoeur de l'explication des disparités dans la croissance économique. À cet égard, cette thèsemet l'accent sur les réseaux de connaissances comme un mécanisme permettant la circulationdes connaissances dans l'espace et le temps. Parmi les différents types de réseaux deconnaissances, elle étudie les réseaux de collaboration de R&D et explore deux questionsprincipales.Tout d'abord, elle examine l'effet de la géographie sur la formation du réseau pour savoir si lesflux de connaissances par les réseaux de collaboration en R&D sont limités dans l'espace oupas. Elle s'enquiert de cette question à la fois pour le réseau multilatéral entre lesorganisations et le réseau inter-régional entre les régions européennes dans le domaine desbiotechnologies en utilisant les données sur les collaborations de R&D promues par lesProgrammes-Cadres Européens.Deuxièmement, elle explore comment un réseau évolutif de collaborations de R&D entre lesrégions affecte les performances des régions en matière d'innovation. Elle utilise l'économétriespatiale pour quantifier les effets statiques et dynamiques des flux de connaissances desvoisins spatiaux et d'un ensemble évolutif de partenaires de collaboration sur l'activitéinventive des régions dans le domaine des TIC au cours de la période 2003-2009. / The economic literature attributing endogenous roles to technological change and geography inexplaining economie growth suggests that understanding knowledge flows in space and theirconsequences on innovative activities is central to explaining disparities in economie growth. Inthis regard, this PhD thesis focuses on knowledge networks as a mechanism that enablesknowledge flows in space and time. Among different types of knowledge networks, it studiesR&D collaboration networks and addresses two main issues.First, it investigates the effect of geography on network formation to figure out whetherknowledge flows through R&D collaboration networks are constrained in space or not. It inquiresthis question both for multilateral R&D collaboration network among organizations and theresulting inter-regional network among European regions in the field of biotechnology using dataon R&D collaborations promoted via European Framework Programmes.Second, it addresses how an evolving network of R&D collaborations among regions affectsregional innovation performances in time. It employs a spatial econometric approach to quantifythe static and dynamic effects of knowledge flows from spatial neighbors and an evolving set ofcollaboration partners on inventive activity of regions in the field of ICT durin 2003-2009.

<p>Over the last century, developed countries have been successful in enhancing maternal health and reducing Maternal Mortality Ratio (MMR). By 2018, MMR across OECD countries and World Bank Group Regions have converged towards very low levels, averaging more than 5 deaths per 100,000 live births. The United States has become an outlier among the developed countries in maternal deaths and compares unfavorably to a number of poorer countries where the ratio has declined. In 2017, the US ranked worst in MMR among the 39 industrialized nations. United States has experienced almost a 142 percent increase in MMR from 1987-2018. According to the Centers for Disease Control and Prevention (CDC), every year in the US, more than 700 women die due to the pregnancy or childbirth-related complications, with 60 percent of these deaths being preventable. Within the US, MMR varies considerably, leaving large disparities across states as well as between all racial groups. This research study aims to understand the interplay of spatial and racial impacts on the variation of maternal mortality ratios within the US. The paper estimates Ordinary Least Squares (OLS) and Spatial Lag Models for MMR using cross-sectional US state data for 2012-2017, taken from CDC. The results show that the dominant root causes of high maternal mortality differ between black and white women. </p> <p> </p>

The last couple of decades have seen a renewed interest among urban transportation planners in light rail transit (LRT) systems in large cities across the United States (US) as a possible means of addressing negative transportation externalities such as congestion and greenhouse gas emissions while encouraging the use of public transit [1]. LRT infrastructure investments have also gained traction as a means of revitalizing decayed urban centres because transportation infrastructure developments are highly correlated with economic growth in surrounding areas [2]. <div>The primary objective of this dissertation is to examine the externalities associated with LRTs during its the construction and operations phases. In particular, three areas of concern are addressed: (1) The effect that proximity to LRT stations </div><div>have on nearby single family residences (SFRs) throughout the LRT life-cycle; (2) the effect that directional heterogeneity between LRT stations, the central business district (CBD), and the SFR; and (3) the longer term effects on nearby populations due to LRT operations. To answer the first two research objectives, quasi-experimental spatial econometric models are used; to address the last objective, a-spatial fixed effects panel models are developed. The analyses primarily relies on SFR sales data from 2001-2019, publicly available geographical information systems data, as well as demographic data from eight 5-year American Communities Surveys (ACS). Charlotte, NC, a medium-sized US city, is chosen as the site of analysis, both due to the relative novelty factor of its LRT in the region and data availability.</div><div>The results show that SFR values are positively associated with proximity to LRT stations in the announcement and construction phases but negatively associated with proximity to stations once the LRT is operational. Additionally, potential homeowners with prior experience with LRT do not behave any differently than potential homeowners with no prior experience with LRT in terms of willingness to pay to live a certain distance from LRT stations. Further, directional heterogeneity is shown to be a statistically significant source factor in deciding the extent to which house-buyers are willing to pay to be near LRT stations. Lastly, distance from LRT stations are found to have no statistically significant effect on changes in the racial composition of nearby areas but have significant positive effects on educational attainment and average median incomes of residents living in nearby areas over time. </div><div>The contributions of this research are twofold. First, in addition to highlighting the need to use spatial econometric methods when analyzing the effect that LRTs have on surrounding real estate markets, this research provides a framework by which directional heterogeneity can be incorporated into these analyses. Second, this research adds to the existing pool of knowledge on land use externalities of LRT through incorporating the life-cycle of LRT from announcement to operations. Furthermore, this research examines the effects that LRT have on surrounding populations in transit adjacent areas to provide a look at the broader effects of LRT over time. </div><div>A major challenge in the analyses conducted in this dissertation is its reliance on SFR sales data. Urban areas near LRT may contain additional land uses. In order to fully determine LRT’s effects on its surrounding area, one should examine the proximity effects on all land use types. Furthermore, LRT stations and rail lines are assumed exogenous, which may not be the case as public hearings and town halls during the planning phase may influence stations’ locations. Future research should seek to understand how the circumstances surrounding the planning process could indirectly affect the socio-demographic characteristics in transit adjacent areas over time. Finally, additional research is needed to better understand the extent to which LRT affects urban intra- and inter-migration. Knowing the population repulsion and attraction of LRT can help planners design facilities to better serve the public.</div>

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The big-box retail stores such as Wal-Mart and Target have become the focus of many studies researching their impacts on local economic outcomes. This dissertation studies three related topics: (i) the dynamic interrelationship among the presence of the big-box stores, retail wage, and employment, (ii) the impact of the big-box retailers on personal income growth, and (iii) the dynamic interrelationship between the presence of big-box retailers and personal income growth. The research draws important insights with potential implications for regional developers and policy makers. The first essay analyzes the dynamic relationship among the presence of the big-box retailers, retail wage, and employment at the county level for 1986-2005. A vector autoregression model is applied on panel data. Impulse response functions and variance decompositions are also presented. Results suggest that the presence of big-box stores decreases retail wages and increases retail employment. Retail employment has a higher impact on the retailers’ location decision than retail wage. The results also show that the presence of Wal-Mart drives the above-mentioned effects, while the presence of Target is insignificant. The second essay investigates the impact from the presence of big-box retailers on personal income growth in U.S. counties between 2000 and 2005 - based on neoclassical growth models of cross-country income convergence. Results suggest that counties having both Wal-Mart and Target stores experienced slower growth in personal income. After controlling for spatial autocorrelation, similar to the first essay, the effect of Wal-Mart’s presence on personal income growth is dominant in terms of statistical significance relative to Target’s. The third essay expands the second essay and investigates the dynamic interaction between the presence of big-box retailers and personal income growth over time at the county level for the period 1987-2005, using a panel vector autoregression model. For this analysis, the earning shares of natural resources and manufacturing sectors are included - assuming that all the variables are endogenous to one another. The findings indicate that big-box retailers negatively affect personal income growth, which is consistent with the second essay. However, personal income growth has an insignificant effect on the big-box retailers’ location decision.