Doppler Orbit Determination of Deep Space Probes by the Bernese GNSS Software: First Results of the Combined Orbit Determination from DSN and Inter-Satellite Ka-Band Data from the Grail Mission

Navigation of deep space probes is most commonly operated using the spacecraft Doppler tracking technique. Orbital parameters are determined from a series of repeated measurements of the frequency shift of a microwave carrier over a given integration time. Currently, both ESA and NASA operate antennas at several sites around the world to ensure the tracking of deep space probes. Just a small number of software packages are nowadays used to process Doppler observations. The Astronomical Institute of the University of Bern (AIUB) has recently started the development of Doppler data processing capabilities within the Bernese GNSS Software. This software has been extensively used for Precise Orbit Determination of Earth orbiting satellites using GPS data collected by on-board receivers and for subsequent determination of the Earth gravity field. In this paper, we present the currently achieved status of the Doppler data modeling and orbit determination capabilities in the Bernese GNSS Software using GRAIL data. In particular we will focus on the implemented orbit determination procedure used for the combined analysis of Doppler and intersatellite Ka-band data. We show that even at this earlier stage of the development we can achieve an accuracy of few mHz on two-way S-band Doppler observation and of 2 µm/s on KBRR data from the GRAIL primary mission phase.

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Can FDI promote export diversification and sophistication of host countries? : dynamic panel system GMM analysis

Recent trade literature highlights the importance of export diversification and upgrading in fostering faster and sustainable economic growth. This study investigates the impact of FDI inflow and stock on the level of export diversification and sophistication in host country's export baskets. By utilizing the dynamic panel data model, we find that the five-year lagged FDI inflow correlates positively with both export diversification and sophistication, and FDI stock makes the positive contribution to export sophistication. These findings provide support for the possibility of successful capabilities transfer to and building by local firms. We also find that these positive impacts of FDI exist only in developing countries.

Tariff reductions and labor demand elasticities : evidence from Chinese firm-level data

International production fragmentation has been a global trend for decades, becoming especially important in Asia where the manufacturing process is fragmented into stages and dispersed around the region. This paper examines the effects of input and output tariff reductions on labor demand elasticities at the firm level. For this purpose, we consider a simple heterogenous firm model in which firms are allowed to export their products and to use imported intermediate inputs. The model predicts that only productive firms can use imported intermediate inputs (outsourcing) and tend to have larger constant-output labor demand elasticities. Input tariff reductions would lower the factor shares of labor for these productive firms and raise conditional labor demand elasticities further. We test these empirical predictions, constructing Chinese firm-level panel data over the 2000--2006 period. Controlling for potential tariff endogeneity by instruments, our empirical studies generally support these predictions.

Implications of agricultural production, policy and land use changes on water resource assessment

Una gestión más eficiente y equitativa del agua a escala de cuenca no se puede centrar exclusivamente en el recurso hídrico en sí, sino también en otras políticas y disciplinas científicas. Existe un consenso creciente de que, además de la consideración de las cambiantes condiciones climáticas, es necesaria una integración de ámbitos de investigación tales como la agronomía, planificación del territorio y ciencias políticas y económicas a fin de satisfacer de manera sostenible las demandas de agua por parte de la sociedad y del medio natural. La Política Agrícola Común (PAC) es el principal motor de cambio en las tendencias de paisajes rurales y sistemas agrícolas, pero el deterioro del medio ambiente es ahora una de las principales preocupaciones. Uno de los cambios más relevantes se ha producido con la expansión e intensificación del olivar en España, principalmente con nuevas zonas de regadío o la conversión de olivares de secano a sistemas en regadío. Por otra parte, el cambio de las condiciones climáticas podría ejercer un papel importante en las tendencias negativas de las aportaciones a los ríos, pero no queda claro el papel que podrían estar jugando los cambios de uso de suelo y cobertura vegetal sobre las tendencias negativas de caudal observadas. Esta tesis tiene como objetivo mejorar el conocimiento de los efectos de la producción agrícola, política agraria y cambios de uso de suelo y cobertura vegetal sobre las condiciones de calidad del agua, respuesta hidrológica y apropiación del agua por parte de la sociedad. En primer lugar, el estudio determina las tendencias existentes de nitratos y sólidos en suspensión en las aguas superficiales de la cuenca del río Guadalquivir durante el periodo de 1998 a 2009. Desde una perspectiva de política agraria, la investigación trata de evaluar mediante un análisis de datos de panel las principales variables, incluyendo la reforma de la PAC de 2003, que están teniendo una influencia en ambos indicadores de calidad. En segundo lugar, la apropiación del agua y el nivel de contaminación por nitratos debido a la producción del aceite de oliva en España se determinan con una evaluación de la huella hídrica (HH), teniendo en cuenta una variabilidad espacial y temporal a largo de las provincias españolas y entre 1997 y 2008. Por último, la tesis analiza los efectos de los cambios de uso de suelo y cobertura vegetal sobre las tendencias negativas observadas en la zona alta del Turia, cabecera de la cuenca del río Júcar, durante el periodo 1973-2008 mediante una modelización ecohidrológica. En la cuenca del Guadalquivir cerca del 20% de las estaciones de monitoreo muestran tendencias significativas, lineales o cuadráticas, para cada indicador de calidad de agua. La mayoría de las tendencias significativas en nitratos están aumentando, y la mayoría de tendencias cuadráticas muestran un patrón en forma de U. Los modelos de regresión de datos de panel muestran que las variables más importantes que empeoran ambos indicadores de calidad del agua son la intensificación de biomasa y las exportaciones de ambos indicadores de calidad procedentes de aguas arriba. En regiones en las que el abandono agrícola y/o desintensificación han tenido lugar han mejorado las condiciones de calidad del agua. Para los nitratos, el desacoplamiento de las subvenciones a la agricultura y la reducción de la cuantía de las subvenciones a tierras de regadío subyacen en la reducción observada de la concentración de nitratos. Las medidas de modernización de regadíos y el establecimiento de zonas vulnerables a nitratos reducen la concentración en subcuencas que muestran una tendencia creciente de nitratos. Sin embargo, el efecto de las exportaciones de nitratos procedente de aguas arriba, la intensificación de la biomasa y los precios de los cultivos presentan un mayor peso, explicando la tendencia creciente observada de nitratos. Para los sólidos en suspensión, no queda de forma evidente si el proceso de desacoplamiento ha influido negativa o positivamente. Sin embargo, los mayores valores de las ayudas agrarias aún ligadas a la producción, en particular en zonas de regadío, conllevan un aumento de las tasas de erosión. Aunque la cuenca del Guadalquivir ha aumentado la producción agrícola y la eficiencia del uso del agua, el problema de las altas tasas de erosión aún no ha sido mitigado adecuadamente. El estudio de la huella hídrica (HH) revela que en 1 L de aceite de oliva español más del 99,5% de la HH está relacionado con la producción de la aceituna, mientras que menos del 0,5% se debe a otros componentes, es decir, a la botella, tapón y etiqueta. Durante el período estudiado, la HH verde en secano y en regadío representa alrededor del 72% y 12%, respectivamente, del total de la HH. Las HHs azul y gris representan 6% y 10%, respectivamente. La producción de aceitunas se concentra en regiones con una HH menor por unidad de producto. La producción de aceite de oliva ha aumentado su productividad del agua durante 1997-2008, incentivado por los crecientes precios del aceite, como también lo ha hecho la cantidad de exportaciones de agua virtual. De hecho, las mayores zonas productoras presentan una eficiencia alta del uso y de productividad del agua, así como un menor potencial de contaminación por nitratos. Pero en estas zonas se ve a la vez reflejado un aumento de presión sobre los recursos hídricos locales. El aumento de extracciones de agua subterránea relacionadas con las exportaciones de aceite de oliva podría añadir una mayor presión a la ya estresada cuenca del Guadalquivir, mostrando la necesidad de equilibrar las fuerzas del mercado con los recursos locales disponibles. Los cambios de uso de suelo y cobertura vegetal juegan un papel importante en el balance del agua de la cuenca alta del Turia, pero no son el principal motor que sustenta la reducción observada de caudal. El aumento de la temperatura es el principal factor que explica las mayores tasas de evapotranspiración y la reducción de caudales. Sin embargo, los cambios de uso de suelo y el cambio climático han tenido un efecto compensatorio en la respuesta hidrológica. Por un lado, el caudal se ha visto afectado negativamente por el aumento de la temperatura, mientras que los cambios de uso de suelo y cobertura vegetal han compensado positivamente con una reducción de las tasas de evapotranspiración, gracias a los procesos de disminución de la densidad de matorral y de degradación forestal. El estudio proporciona una visión que fortalece la interdisciplinariedad entre la planificación hidrológica y territorial, destacando la necesidad de incluir las implicaciones de los cambios de uso de suelo y cobertura vegetal en futuros planes hidrológicos. Estos hallazgos son valiosos para la gestión de la cuenca del río Turia, y el enfoque empleado es útil para la determinación del peso de los cambios de uso de suelo y cobertura vegetal en la respuesta hidrológica en otras regiones. ABSTRACT Achieving a more efficient and equitable water management at catchment scale does not only rely on the water resource itself, but also on other policies and scientific knowledge. There is a growing consensus that, in addition to consideration of changing climate conditions, integration with research areas such as agronomy, land use planning and economics and political science is required to meet sustainably the societal and environmental water demands. The Common Agricultural Policy (CAP) is a main driver for trends in rural landscapes and agricultural systems, but environmental deterioration is now a principal concern. One of the most relevant changes has occurred with the expansion and intensification of olive orchards in Spain, taking place mainly with new irrigated areas or with the conversion from rainfed to irrigated systems. Moreover, changing climate conditions might exert a major role on water yield trends, but it remains unclear the role that ongoing land use and land cover changes (LULCC) might have on observed river flow trends. This thesis aims to improve the understanding of the effects of agricultural production, policies and LULCC on water quality conditions, hydrological response and human water appropriation. Firstly, the study determines the existing trends for nitrates and suspended solids in the Guadalquivir river basin’s surface waters (south Spain) during the period from 1998 to 2009. From a policy perspective, the research tries to assess with panel data analysis the main drivers, including the 2003 CAP reform, which are having an influence on both water quality indicators. Secondly, water appropriation and nitrate pollution level originating from the production of olive oil in Spain is determined with a water footprint (WF) assessment, considering a spatial temporal variability across the Spanish provinces and from 1997 to 2008 years. Finally, the thesis analyzes the effects of the LULCC on the observed negative trends over the period 1973-2008 in the Upper Turia basin, headwaters of the Júcar river demarcation (east Spain), with ecohydrological modeling. In the Guadalquivir river basin about 20% of monitoring stations show significant trends, linear or quadratic, for each water quality indicator. Most significant trends of nitrates are augmenting than decreasing, and most significant quadratic terms of both indicators exhibit U-shaped patterns. The panel data models show that the most important drivers that are worsening nitrates and suspended solids in the basin are biomass intensification and exports of both water quality indicators from upland regions. In regions that agricultural abandonment and/or de-intensification have taken place the water quality conditions have improved. For nitrates, the decoupling of agricultural subsidies and the reduction of the amount of subsidies to irrigated land underlie the observed reduction of nitrates concentration. Measures of irrigation modernization and establishment of vulnerable zones to nitrates ameliorate the concentration of nitrates in subbasins showing an increasing trend. However, the effect of nitrates load from upland areas, intensification of biomass and crop prices present a greater weight leading to the final increasing trend in this subbasins group, where annual crops dominate. For suspended solids, there is no clear evidence that decoupling process have influenced negatively or positively. Nevertheless, greater values of subsidies still linked to production, particularly in irrigated regions, lead to increasing erosion rates. Although agricultural production has augmented in the basin and water efficiency in the agricultural sector has improved, the issue of high erosion rates has not yet been properly faced. The water footprint (WF) assessment reveals that for 1 L Spanish olive oil more than 99.5% of the WF is related to the olive fruit production, whereas less than 0.5% is due to other components i.e. bottle, cap and label. Over the studied period, the green WF in rainfed and irrigated systems represents about 72% and 12%, respectively, of the total WF. Blue and grey WFs represent 6% and 10%, respectively. The olive production is concentrated in regions with the smallest WF per unit of product. The olive oil production has increased its apparent water productivity from 1997 to 2008 incentivized by growing trade prices, but also did the amount of virtual water exports. In fact, the largest producing areas present high water use efficiency per product and apparent water productivity as well as less nitrates pollution potential, but this enhances the pressure on the available water resources. Increasing groundwater abstractions related to olive oil exports may add further pressure to the already stressed Guadalquivir basin. This shows the need to balance the market forces with the available local resources. Concerning the effects of LULCC on the Upper Turia basin’s streamflow, LULCC play a significant role on the water balance, but it is not the main driver underpinning the observed reduction on Turia's streamflow. Increasing mean temperature is the main factor supporting larger evapotranspiration rates and streamflow reduction. In fact, LULCC and climate change have had an offsetting effect on the streamflow generation during the study period. While streamflow has been negatively affected by increasing temperature, ongoing LULCC have positively compensated with reduced evapotranspiration rates, thanks to mainly shrubland clearing and forest degradation processes. The research provides insight for strengthening the interdisciplinarity between hydrological and spatial planning, highlighting the need to include the implications of LULCC in future hydrological plans. These findings are valuable for the management of the Turia river basin, as well as a useful approach for the determination of the weight of LULCC on the hydrological response in other regions.

Nonlinear dynamics in discretionary accruals: An analysis of bank loan-loss provisions

Several studies have analyzed discretionary accruals to address earnings-smoothing behaviors in the banking industry. We argue that the characteristic link between accruals and earnings may be nonlinear, since both the incentives to manipulate income and the practical way to do so depend partially on the relative size of earnings. Given a sample of 15,268 US banks over the period 1996–2011, the main results in this paper suggest that, depending on the size of earnings, bank managers tend to engage in earnings-decreasing strategies when earnings are negative (“big-bath”), use earnings-increasing strategies when earnings are positive, and use provisions as a smoothing device when earnings are positive and substantial (“cookie-jar” accounting). This evidence, which cannot be explained by the earnings-smoothing hypothesis, is consistent with the compensation theory. Neglecting nonlinear patterns in the econometric modeling of these accruals may lead to misleading conclusions regarding the characteristic strategies used in earnings management.

Energy consumption, economic growth and prices: A reassessment using panel VECM for developed and developing countries

This paper reinvestigates the energy consumption-GDP growth nexus in a panel error correction model using data on 20 net energy importers and exporters from 1971 to 2002. Among the energy exporters, there was bidirectional causality between economic growth and energy consumption in the developed countries in both the short and long run, while in the developing countries energy consumption stimulates growth only in the short run. The former result is also found for energy importers and the latter result exists only for the developed countries within this category. In addition, compared to the developing countries, the developed countries' elasticity response in terms of economic growth from an increase in energy consumption is larger although its income elasticity is lower and less than unitary. Lastly. the implications for energy policy calling for a more holistic approach are discussed. (c) 2006 Elsevier Ltd. All rights reserved.

Constructing internationally comparable real income aggregates by combining sparse benchmark data with annual national accounts data: A state-space approach

The importance of availability of comparable real income aggregates and their components to applied economic research is highlighted by the popularity of the Penn World Tables. Any methodology designed to achieve such a task requires the combination of data from several sources. The first is purchasing power parities (PPP) data available from the International Comparisons Project roughly every five years since the 1970s. The second is national level data on a range of variables that explain the behaviour of the ratio of PPP to market exchange rates. The final source of data is the national accounts publications of different countries which include estimates of gross domestic product and various price deflators. In this paper we present a method to construct a consistent panel of comparable real incomes by specifying the problem in state-space form. We present our completed work as well as briefly indicate our work in progress.

Perspectivas e metodologias de pesquisa da Comunicação Social no contexto da internet com o Big Data e da especialização Data Scientist

O trabalho desenvolvido analisa a Comunicação Social no contexto da internet e delineia novas metodologias de estudo para a área na filtragem de significados no âmbito científico dos fluxos de informação das redes sociais, mídias de notícias ou qualquer outro dispositivo que permita armazenamento e acesso a informação estruturada e não estruturada. No intento de uma reflexão sobre os caminhos, que estes fluxos de informação se desenvolvem e principalmente no volume produzido, o projeto dimensiona os campos de significados que tal relação se configura nas teorias e práticas de pesquisa. O objetivo geral deste trabalho é contextualizar a área da Comunicação Social dentro de uma realidade mutável e dinâmica que é o ambiente da internet e fazer paralelos perante as aplicações já sucedidas por outras áreas. Com o método de estudo de caso foram analisados três casos sob duas chaves conceituais a Web Sphere Analysis e a Web Science refletindo os sistemas de informação contrapostos no quesito discursivo e estrutural. Assim se busca observar qual ganho a Comunicação Social tem no modo de visualizar seus objetos de estudo no ambiente das internet por essas perspectivas. O resultado da pesquisa mostra que é um desafio para o pesquisador da Comunicação Social buscar novas aprendizagens, mas a retroalimentação de informação no ambiente colaborativo que a internet apresenta é um caminho fértil para pesquisa, pois a modelagem de dados ganha corpus analítico quando o conjunto de ferramentas promovido e impulsionado pela tecnologia permite isolar conteúdos e possibilita aprofundamento dos significados e suas relações.

Technological diversification and new innovators in European regions:evidence from patent data

This paper assesses the impact of regional technological diversification on the emergence of new innovators across EU regions. Integrating analyses from regional economics, economic geography and technological change literatures, we explore the role that the regional embeddedness of actors characterised by diverse technological competencies may have in fostering novel and sustained interactions leading to new technological combinations. In particular, we test whether greater technological diversification improve regional ‘combinatorial’ opportunities leading to the emergence of new innovators. The analysis is based on panel data obtained merging regional economic data from Eurostat and patent data from the CRIOS-PATSTAT database over the period 1997–2006, covering 178 regions across 10 EU Countries. Accounting for different measures of economic and innovative activity at the NUTS2 level, our findings suggest that the regional co-location of diverse technological competencies contributes to the entry of new innovators, thereby shaping technological change and industry dynamics. Thus, this paper brings to the fore a better understanding of the relationship between regional diversity and technological change.

Privatisation, corporate control and employment growth:evidence from a panel of large Polish firms, 1996-2002

Using panel data on large Polish firms this paper examines the relationship between corporate control structures, sales growth and the determinants of employment change during the period 1996-2002. We find that privatised and de novo firms are the main drivers of employment growth and that, in the case of de novo firms, it is foreign ownership which underpins the result. Interestingly, we find that being privatised has a positive impact on employment growth but that this impact is concentrated within a range of three to six years after privatisation. In contrast with the findings of earlier literature, we find evidence that there are no systematic differences in employment response to negative sales growth across the ownership categories. On the other hand, employment in state firms is less responsive to positive sales growth. From these combined results we infer that the behaviour of state firms is constrained by both insider rent sharing and binding budget constraints. Consistent with this, we find that privatised companies, three to six years post-privatisation, are the firms for whom employment is most responsive to positive sales growth and as such, offer the best hope for rapid labour market expansion.

Essays in economic growth, political economy and institutions

This dissertation analyzes the effects of political and economic institutions on economic development and growth.^ The first essay develops an overlapping-generations political economy model to analyze the incentives of various social groups to finance human capital accumulation through public education expenditures. The contribution of this study to the literature is that it helps explain the observed differences in the economic growth performance of natural resource-abundant countries. The results suggest that the preferred tax rates of the manufacturers on one hand and the political coalition of manufacturers and landowners, on the other hand, are equal to the socially optimal tax rate. However, we show that owners of natural resources prefer an excessively high tax rate, which suppresses aggregate output to a suboptimal level.^ The second essay examines the relationship between the political influence of different social classes and public education spending in panel data estimation. The novel contribution of this paper to the literature is that I proxy the political power and influence of the natural resource owners, manufacturers, and landowners with macroeconomic indicators. The motivation behind this modeling choice is to substantiate the definition of the political power of social classes with economic fundamentals. I use different governance indicators in the estimations to find out how different institutions mediate the overall impact of the political influence of various social classes on public education spending. The results suggest that political stability and absence of violence and rule of law are the important governance indicators.^ The third essay develops a counter argument to Acemoglu et al. (2010) where the thesis is that French institutions and economic reforms fostered economic progress in those German regions invaded by the Napoleonic armies. By providing historical data on urbanization rates used as proxies for economic growth, I demonstrate that similar different rates of economic growth were observed in the regions of France in the post-Napoleonic period as well. The existence of different economic growth rates makes it hard to argue that the differences in economic performance in the German regions that were invaded by the French and those that were spared a similar fate follow from regional differences in economic institutions.^

Regional diversification and performance: Conceptualization and competing strategic objectives

This dissertation comprised of three essays provides justification for the need to pursue research on multinationality and performance with a more fine-grained approach. Essay one is a conceptual response to an article written by Jean-Francois Hennart in 2011 which questions the need and approach toward future research in this domain. I argue that internalization theory does not render multinationality and performance research meaningless and identify key areas where methodological enhancements can be made to strengthen our research findings with regard to Hennart's call for more content validity. Essay two responds to the need for more-fine grained research on the consequences of multinationality by introducing non-traditional measures of performance such as social and environmental performance and adopting a more theoretically relevant construct of regionalization to capture international diversification levels of the firm. Using data from the world's largest 600 firms (based on sales) derived from Bloomberg and the Directory of Corporate Affiliates; I employ general estimating equation analysis to account for the auto-correlated nature of the panel data alongside multivariate regression techniques. Results indicate that regionalization has a positive relationship with economic performance while it has a negative relationship with environmental and social performance outcomes, often referred to as the "Triple Bottom-Line" performance. Essay three builds upon the work in the previous essays by linking the aforementioned performance variables and sample to corporate reputation which has been shown to be a beneficial strategic asset. Using Structural Equation Modeling I explore economic, environmental and social signals as mediators on relationship between regionalization and firm reputation. Results indicate that these variables partially mediate a positive relationship between regionalization and firm reputation. While regionalization positively affects the reputation building signal of economic performance, it aids in reputation building by reducing environmental and social disclosure effects which interestingly impact reputation negatively. In conclusion, the dissertation submits opportunities for future research and contributes to research by demonstrating that regionalization affects performance, but the effect varies in accordance with the performance criterion and context. In some cases, regional diversification may produce competing or conflicting outcomes among the potential strategic objectives of the firm.

Energy efficiency in the Chinese provinces: a fixed effects stochastic frontier spatial Durbin error panel analysis

Energy efficiency improvement has been a key objective of China’s long-term energy policy. In this paper, we derive single-factor technical energy efficiency (abbreviated as energy efficiency) in China from multi-factor efficiency estimated by means of a translog production function and a stochastic frontier model on the basis of panel data on 29 Chinese provinces over the period 2003–2011. We find that average energy efficiency has been increasing over the research period and that the provinces with the highest energy efficiency are at the east coast and the ones with the lowest in the west, with an intermediate corridor in between. In the analysis of the determinants of energy efficiency by means of a spatial Durbin error model both factors in the own province and in first-order neighboring provinces are considered. Per capita income in the own province has a positive effect. Furthermore, foreign direct investment and population density in the own province and in neighboring provinces have positive effects, whereas the share of state-owned enterprises in Gross Provincial Product in the own province and in neighboring provinces has negative effects. From the analysis it follows that inflow of foreign direct investment and reform of state-owned enterprises are important policy handles.

Identifying treatment effects and counterfactual distributions using data combination with unobserved heterogeneity

This paper considers identification of treatment effects when the outcome variables and covari-ates are not observed in the same data sets. Ecological inference models, where aggregate out-come information is combined with individual demographic information, are a common example of these situations. In this context, the counterfactual distributions and the treatment effects are not point identified. However, recent results provide bounds to partially identify causal effects. Unlike previous works, this paper adopts the selection on unobservables assumption, which means that randomization of treatment assignments is not achieved until time fixed unobserved heterogeneity is controlled for. Panel data models linear in the unobserved components are con-sidered to achieve identification. To assess the performance of these bounds, this paper provides a simulation exercise.