Topics in Local Economic Development

This thesis contributes to the current debate in literature about local economic development by considering two different topics: quality of institutions, and the role of clusters in innovation and productivity growth. The research is built upon three papers. The first paper deals with the analysis of the effect of administrative continuity on administrative efficiency. The analysis underlines the importance of different typologies of social capital. Findings reveal a positive impact on administrative efficiency (AE) by administrative continuity (AC) when it is coupled by bridging and linking social capital. On the contrary, bonding social capital influences negatively the effect by AC on AE. The second paper investigates the spatial interaction in levels of quality of government (QoG) among European regions. Notwithstanding the largely recognised role by institutions in the design of regional policies, no study has been conducted about the mechanisms of interaction and diffusion of QoG at regional level. This research wants to overcome this knowledge gap in literature. Findings reveal a heterogeneity in spatial interaction among groups of regions, i.e. ‘leader regions’ (Northern regions) and ‘lagging regions’ (Southern regions), when considering different mechanisms of interaction (learning / imitating competition and pure competition). Moreover, the effect of wealth on the levels of QoG is nonlinear. Finally, the third paper analyses the relation among specialization and productivity within the agricultural sector. In literature, the study of clusters dynamics has long neglected agriculture. The analysis describes the changes in sectorial specialization for eight main crop groups in Italian regions (NUTS 3), assessing the existence of spatial autocorrelations by using an exploratory data analysis. Furthermore, the effect of specialization on productivity is analysed within the main crop groups using a spatial panel data model. Findings reveal a marked tendency to specialization in the Italian agriculture, and a heterogeneous effect by specialization on productivity.

Deglaciation records of 17O-excess in East Antarctica: reliable reconstruction of oceanic relative humidity from coastal sites

We measured δ17O and δ18O in two Antarctic ice cores at EPICA Dome C (EDC) and TALDICE (TD), respectively and computed 17O-excess with respect to VSMOW. The comparison of our 17O-excess data with the previous record obtained at Vostok (Landais et al., 2008) revealed differences up to 35 ppm in 17O-excess mean level and evolution for the three sites. Our data showed that the large increase depicted at Vostok (20 ppm) during the last deglaciation, is a regional and not a general pattern in the temporal distribution of 17O-excess in East Antarctica. The EDC data display an increase of 13 ppm, whereas the TD data show no significant variation from the Last Glacial Maximum (LGM) to the Early Holocene (EH). Lagrangian moisture source diagnostic revealed very different source regions for Vostok and EDC compared to TD. These findings combined with the results of a sensitivity analysis, using a Rayleigh-type isotopic model, suggest that relative humidity (RH) at the oceanic source region (OSR) are a determining factor for the spatial differences of 17O-excess in East Antarctica. However, 17O-excess in remote sites of continental Antarctica (e.g. Vostok) may be highly sensitive to local effects. Hence, we consider 17O-excess in coastal East Antarctic ice cores (TD) to be more reliable as a proxy for RH at the OSR.

Early ship-based upper-air data and comparison with the Twentieth Century

Extension of 3-D atmospheric data products back into the past is desirable for a wide range of applications. Historical upper-air data are important in this endeavour, particularly in the maritime regions of the tropics and the southern hemisphere, where observations are extremely sparse. Here we present newly digitized and re-evaluated early ship-based upper-air data from two cruises: (1) kite and registering balloon profiles from onboard the ship SMS Planet on a cruise from Europe around South Africa and across the Indian Ocean to the western Pacific in 1906/1907, and (2) ship-based radiosonde data from onboard the MS Schwabenland on a cruise from Europe across the Atlantic to Antarctica and back in 1938/1939. We describe the data and provide estimations of the errors. We compare the data with a recent reanalysis (the Twentieth Century Reanalysis Project, 20CR, Compo et al., 2011) that provides global 3-D data back to the 19th century based on an assimilation of surface pressure data only (plus monthly mean sea-surface temperatures). In cruise (1), the agreement is generally good, but large temperature differences appear during a period with a strong inversion. In cruise (2), after a subset of the data are corrected, close agreement between observations and 20CR is found for geopotential height (GPH) and temperature notwithstanding a likely cold bias of 20CR at the tropopause level. Results are considerably worse for relative humidity, which was reportedly inaccurately measured. Note that comparing 20CR, which has limited skill in the tropical regions, with measurements from ships in remote regions made under sometimes difficult conditions can be considered a worst case assessment. In view of that fact, the anomaly correlations for temperature of 0.3–0.6 in the lower troposphere in cruise (1) and of 0.5–0.7 for tropospheric temperature and GPH in cruise (2) are considered as promising results. Moreover, they are consistent with the error estimations. The results suggest room for further improvement of data products in remote regions.

The Effects of Interstate Speed Limit Increases: Fatality Rates and Traffic Diversion Versus Speed Spillover

This thesis examines two panel data sets of 48 states from 1981 to 2009 and utilizes ordinary least squares (OLS) and fixed effects models to explore the relationship between rural Interstate speed limits and fatality rates and whether rural Interstate speed limits affect non-Interstate safety. Models provide evidence that rural Interstate speed limits higher than 55 MPH lead to higher fatality rates on rural Interstates though this effect is somewhat tempered by reductions in fatality rates for roads other than rural Interstates. These results provide some but not unanimous support for the traffic diversion hypothesis that rural Interstate speed limit increases lead to decreases in fatality rates of other roads. To the author’s knowledge, this paper is the first econometric study to differentiate between the effects of 70 MPH speed limits and speed limits above 70 MPH on fatality rates using a multi-state data set. Considering both rural Interstates and other roads, rural Interstate speed limit increases above 55 MPH are responsible for 39,700 net fatalities, 4.1 percent of total fatalities from 1987, the year limits were first raised, to 2009.

The Returns to Migration: The Influence of Education and Migration Type

We show the impact of migration type on real wages over time. We create a migration and earnings history from the National Longitudinal Survey of Youth over the period 1979-2002. We estimate the effects of primary, onward, and two types of return migration on real wages using a panel data model with individual, location, and time fixed effects. Panel data are well suited for the study of the returns to U.S. internal migration because the influence of migration on wages has been found to occur years after the event. We differentiate return migration into two types: return to a location with ties that form a geographical anchor (home) and return to a prior place of work. We find that real wage growth varies by migration type. Education attainment is a significant factor in real wage growth. Our results show that onward migration is an important channel by which the monetary rewards to a college education are manifested.

Species Richness-Environment Relationships of European Arthropods at Two Spatial Grains: Habitats and Countries

We study how species richness of arthropods relates to theories concerning net primary productivity, ambient energy, water-energy dynamics and spatial environmental heterogeneity. We use two datasets of arthropod richness with similar spatial extents (Scandinavia to Mediterranean), but contrasting spatial grain (local habitat and country). Samples of ground-dwelling spiders, beetles, bugs and ants were collected from 32 paired habitats at 16 locations across Europe. Species richness of these taxonomic groups was also determined for 25 European countries based on the Fauna Europaea database. We tested effects of net primary productivity (NPP), annual mean temperature (T), annual rainfall (R) and potential evapotranspiration of the coldest month (PETmin) on species richness and turnover. Spatial environmental heterogeneity within countries was considered by including the ranges of NPP, T, R and PETmin. At the local habitat grain, relationships between species richness and environmental variables differed strongly between taxa and trophic groups. However, species turnover across locations was strongly correlated with differences in T. At the country grain, species richness was significantly correlated with environmental variables from all four theories. In particular, species richness within countries increased strongly with spatial heterogeneity in T. The importance of spatial heterogeneity in T for both species turnover across locations and for species richness within countries suggests that the temperature niche is an important determinant of arthropod diversity. We suggest that, unless climatic heterogeneity is constant across sampling units, coarse-grained studies should always account for environmental heterogeneity as a predictor of arthropod species richness, just as studies with variable area of sampling units routinely consider area.

Deglaciation records of 17O-excess in East Antarctica: reliable reconstruction of oceanic normalized relative humidity from coastal sites

We measured δ17O and δ18O in two Antarctic ice cores at EPICA Dome C (EDC) and TALDICE (TD), respectively, and computed 17O-excess with respect to VSMOW. The comparison of our 17O-excess data with the previous record obtained at Vostok (Landais et al., 2008a) revealed differences up to 35 ppm in 17O-excess mean level and evolution for the three sites. Our data show that the large increase depicted at Vostok (20 ppm) during the last deglaciation is a regional and not a general pattern in the temporal distribution of 17O-excess in East Antarctica. The EDC data display an increase of 12 ppm, whereas the TD data show no significant variation from the Last Glacial Maximum (LGM) to the Early Holocene (EH). A Lagrangian moisture source diagnostic revealed very different source regions for Vostok and EDC compared to TD. These findings combined with the results of a sensitivity analysis, using a Rayleigh-type isotopic model, suggest that normalized relative humidity (RHn) at the oceanic source region (OSR) is a determining factor for the spatial differences of 17O-excess in East Antarctica. However, 17O-excess in remote sites of continental Antarctica (e.g. Vostok) may be highly sensitive to local effects. Hence, we consider 17O-excess in coastal East Antarctic ice cores (TD) to be more reliable as a proxy for RHn at the OSR.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Practical Large-Scale Spatio-Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of PM10 for the full time period and PM2.5 for a subset of the period. For the earlier part of the period, 1988-1998, few PM2.5 monitors were operating, so we develop a simple extension to the model that represents PM2.5 conditionally on PM10 model predictions. In the epidemiological analysis, model predictions of PM10 are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space-time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.

Clindamycin is neuroprotective in experimental Streptococcus pneumoniae meningitis compared with ceftriaxone

In animal models of Streptococcus pneumoniae meningitis, rifampin is neuroprotective in comparison to ceftriaxone. So far it is not clear whether this can be generalized for other protein synthesis-inhibiting antimicrobial agents. We examined the effects of the bactericidal protein synthesis-inhibiting clindamycin (n = 12) on the release of proinflammatory bacterial components, the formation of neurotoxic compounds and neuronal injury compared with the standard therapy with ceftriaxone (n = 12) in a rabbit model of pneumococcal meningitis. Analysis of the CSF and histological evaluation were combined with microdialysis from the hippocampal formation and the neocortex. Compared with ceftriaxone, clindamycin reduced the release of lipoteichoic acids from the bacteria (p = 0.004) into the CSF and the CSF leucocyte count (p = 0.011). This led to lower extracellular concentrations of hydroxyl radicals (p = 0.034) and glutamate (p = 0.016) in the hippocampal formation and a subsequent reduction of extracellular glycerol levels (p = 0.018) and neuronal apoptosis in the dentate gyrus (p = 0.008). The present data document beneficial effects of clindamycin compared with ceftriaxone on various parameters linked with the pathophysiology of pneumococcal meningitis and development of neuronal injury. This study suggests neuroprotection to be a group effect of bactericidal protein synthesis-inhibiting antimicrobial agents compared with the standard therapy with beta-lactam antibiotics in meningitis.

Modeling of transfer kinetics at the serum-cerebrospinal fluid barrier in rabbits with experimental meningitis: application to grepafloxacin

The goals of the present study were to model the population kinetics of in vivo influx and efflux processes of grepafloxacin at the serum-cerebrospinal fluid (CSF) barrier and to propose a simulation-based approach to optimize the design of dose-finding trials in the meningitis rabbit model. Twenty-nine rabbits with pneumococcal meningitis receiving grepafloxacin at 15 mg/kg of body weight (intravenous administration at 0 h), 30 mg/kg (at 0 h), or 50 mg/kg twice (at 0 and 4 h) were studied. A three-compartment population pharmacokinetic model was fit to the data with the program NONMEM (Nonlinear Mixed Effects Modeling). Passive diffusion clearance (CL(diff)) and active efflux clearance (CL(active)) are transfer kinetic modeling parameters. Influx clearance is assumed to be equal to CL(diff), and efflux clearance is the sum of CL(diff), CL(active), and bulk flow clearance (CL(bulk)). The average influx clearance for the population was 0.0055 ml/min (interindividual variability, 17%). Passive diffusion clearance was greater in rabbits receiving grepafloxacin at 15 mg/kg than in those treated with higher doses (0.0088 versus 0.0034 ml/min). Assuming a CL(bulk) of 0.01 ml/min, CL(active) was estimated to be 0.017 ml/min (11%), and clearance by total efflux was estimated to be 0.032 ml/min. The population kinetic model allows not only to quantify in vivo efflux and influx mechanisms at the serum-CSF barrier but also to analyze the effects of different dose regimens on transfer kinetic parameters in the rabbit meningitis model. The modeling-based approach also provides a tool for the simulation and prediction of various outcomes in which researchers might be interested, which is of great potential in designing dose-finding trials.

Analysis of in-cylinder pressure transducer data quality utilizing a SIDI turbocharged engine

In-cylinder pressure transducers have been used for decades to record combustion pressure inside a running engine. However, due to the extreme operating environment, transducer design and installation must be considered in order to minimize measurement error. One such error is caused by thermal shock, where the pressure transducer experiences a high heat flux that can distort the pressure transducer diaphragm and also change the crystal sensitivity. This research focused on investigating the effects of thermal shock on in-cylinder pressure transducer data quality using a 2.0L, four-cylinder, spark-ignited, direct-injected, turbo-charged GM engine. Cylinder four was modified with five ports to accommodate pressure transducers of different manufacturers. They included an AVL GH14D, an AVL GH15D, a Kistler 6125C, and a Kistler 6054AR. The GH14D, GH15D, and 6054AR were M5 size transducers. The 6125C was a larger, 6.2mm transducer. Note that both of the AVL pressure transducers utilized a PH03 flame arrestor. Sweeps of ignition timing (spark sweep), engine speed, and engine load were performed to study the effects of thermal shock on each pressure transducer. The project consisted of two distinct phases which included experimental engine testing as well as simulation using a commercially available software package. A comparison was performed to characterize the quality of the data between the actual cylinder pressure and the simulated results. This comparison was valuable because the simulation results did not include thermal shock effects. All three sets of tests showed the peak cylinder pressure was basically unaffected by thermal shock. Comparison of the experimental data with the simulated results showed very good correlation. The spark sweep was performed at 1300 RPM and 3.3 bar NMEP and showed that the differences between the simulated results (no thermal shock) and the experimental data for the indicated mean effective pressure (IMEP) and the pumping mean effective pressure (PMEP) were significantly less than the published accuracies. All transducers had an IMEP percent difference less than 0.038% and less than 0.32% for PMEP. Kistler and AVL publish that the accuracy of their pressure transducers are within plus or minus 1% for the IMEP (AVL 2011; Kistler 2011). In addition, the difference in average exhaust absolute pressure between the simulated results and experimental data was the greatest for the two Kistler pressure transducers. The location and lack of flame arrestor are believed to be the cause of the increased error. For the engine speed sweep, the torque output was held constant at 203 Nm (150 ft-lbf) from 1500 to 4000 RPM. The difference in IMEP was less than 0.01% and the PMEP was less than 1%, except for the AVL GH14D which was 5% and the AVL GH15DK which was 2.25%. A noticeable error in PMEP appeared as the load increased during the engine speed sweeps, as expected. The load sweep was conducted at 2000 RPM over a range of NMEP from 1.1 to 14 bar. The difference in IMEP values were less 0.08% while the PMEP values were below 1% except for the AVL GH14D which was 1.8% and the AVL GH15DK which was at 1.25%. In-cylinder pressure transducer data quality was effectively analyzed using a combination of experimental data and simulation results. Several criteria can be used to investigate the impact of thermal shock on data quality as well as determine the best location and thermal protection for various transducers.

Looking left with left neglect: the role of spatial attention when active vision selects local image features for fixation

When we actively explore the visual environment, our gaze preferentially selects regions characterized by high contrast and high density of edges, suggesting that the guidance of eye movements during visual exploration is driven to a significant degree by perceptual characteristics of a scene. Converging findings suggest that the selection of the visual target for the upcoming saccade critically depends on a covert shift of spatial attention. However, it is unclear whether attention selects the location of the next fixation uniquely on the basis of global scene structure or additionally on local perceptual information. To investigate the role of spatial attention in scene processing, we examined eye fixation patterns of patients with spatial neglect during unconstrained exploration of natural images and compared these to healthy and brain-injured control participants. We computed luminance, colour, contrast, and edge information contained in image patches surrounding each fixation and evaluated whether they differed from randomly selected image patches. At the global level, neglect patients showed the characteristic ipsilesional shift of the distribution of their fixations. At the local level, patients with neglect and control participants fixated image regions in ipsilesional space that were closely similar with respect to their local feature content. In contrast, when directing their gaze to contralesional (impaired) space neglect patients fixated regions of significantly higher local luminance and lower edge content than controls. These results suggest that intact spatial attention is necessary for the active sampling of local feature content during scene perception.

A tutorial on data-driven methods for statistically assessing ERP topographies

Dynamic changes in ERP topographies can be conveniently analyzed by means of microstates, the so-called "atoms of thoughts", that represent brief periods of quasi-stable synchronized network activation. Comparing temporal microstate features such as on- and offset or duration between groups and conditions therefore allows a precise assessment of the timing of cognitive processes. So far, this has been achieved by assigning the individual time-varying ERP maps to spatially defined microstate templates obtained from clustering the grand mean data into predetermined numbers of topographies (microstate prototypes). Features obtained from these individual assignments were then statistically compared. This has the problem that the individual noise dilutes the match between individual topographies and templates leading to lower statistical power. We therefore propose a randomization-based procedure that works without assigning grand-mean microstate prototypes to individual data. In addition, we propose a new criterion to select the optimal number of microstate prototypes based on cross-validation across subjects. After a formal introduction, the method is applied to a sample data set of an N400 experiment and to simulated data with varying signal-to-noise ratios, and the results are compared to existing methods. In a first comparison with previously employed statistical procedures, the new method showed an increased robustness to noise, and a higher sensitivity for more subtle effects of microstate timing. We conclude that the proposed method is well-suited for the assessment of timing differences in cognitive processes. The increased statistical power allows identifying more subtle effects, which is particularly important in small and scarce patient populations.

Space–oriented EEG segmentation reveals changes in brain electric–field maps under the influence of a nootropic drug

Map landscape-based segmentation of the sequences of momentary potential distribution maps (42-channel recordings) into brain microstates during spontaneous brain activity was used to study brain electric field spatial effects of single doses of piracetam (2.9, 4.8, and 9.6 g Nootropil® UCB and placebo) in a double-blind study of five normal young volunteers. Four 15-second epochs were analyzed from each subject and drug condition. The most prominent class of microstates (covering 49% of the time) consisted of potential maps with a generally anterior-posterior field orientation. The map orientation of this microstate class showed an increasing clockwise deviation from the placebo condition with increasing drug doses (Fisher's probability product, p < 0.014). The results of this study suggest the use of microstate segmentation analysis for the assessment of central effects of medication in spontaneous multichannel electroencephalographic data, as a complementary approach to frequency-domain analysis.