The Chinese insurance industry has been growing substantially, and this provides a motivation to examine the insurance market in China. This study used survey data to identify key determinants related to Chinese consumers’ ownership of life insurance, by using a probit model. The results revealed that several groups of variables influence Chinese consumers’ life insurance purchases, including knowledge and trust, consumer profile and investment preferences, importance of product attributes, and socio-demographics. Also, this study applied factor analysis to investigate factors that are important for Chinese consumers regarding life insurance. Factor analysis results indicated that four factors are identified including importance of product attributes, consumers’ financial strength, consumers’ attitude and trust toward the life insurance industry, and consumer attributes. Lastly, to better understand Chinese consumers regarding life insurance, consumers were segmented into three main groups through applying cluster analysis. Each cluster shows distinct differences in purchasing criteria and socio-demographic characteristics.

Using a unique panel data set for German grocery prices we find significant price synchronization within food retail chains as well as within individual food stores (between products). Price synchronization between chains appears to be less pronounced. Common shocks can only explain some synchronization, indicating that strategic motives as well as menu costs are of significant importance. (author's abstract) / Series: Working Papers Series "Growth and Employment in Europe: Sustainability and Competitiveness"

This dissertation comprises two essays that attempt to determine, empirically, the fiscal response of governments’ to international assistance. The first essay examines whether an increasingly popular recommendation in international aid policy to switch from tied foreign assistance to untied foreign assistance affects investment in critical development expenditure sectors by developing countries. In the past, most international aid has been in the form of tied assistance as donors believed that tying aid will improve its effectiveness. It has been argued, that if tied aid is well designed and effectively managed then its overall effectiveness can be improved. On the contrary, it is also believed that tied aid acts as an impediment to donor cooperation and the building of partnership with developing countries. In addition, it is also argued that it removes the ‘feeling’ of ownership and responsibility of projects from partner countries in aid supported development. Two other more popular arguments used to challenge the effectiveness of foreign aid is that it is compromised when tied to the goods and services of the donor countries because almost 30 percent of its value is eliminated and also because it does not allow recipient countries to act on their priorities for public spending. These problems bring into question whether tied aid is truly the most effective way to help poor countries. A recommendation by the international community is that a switch to untied aid would be necessary. With untied aid, the recipient country is not obligated to buy the goods of the donor country neither is it compelled to pursue the public expenditure priorities of donors. Instead with untied aid they will have greater flexibility over spending decisions and can more easily pursue the priorities of their countries as they see fit. Hence, one could expect that a one dollar increase in untied aid will increase spending in the critical priority sectors by more than a one dollar increase in tied assistance. The question therefore is whether national domestic priorities coincide or not with what the international community has traditionally deemed should be priority. Empirically, we test this prediction using country-by-country data for 57 countries for the period 1973 to 2006. The results suggest that on average untied aid has a greater impact on pro-poor spending than do tied aid. In addition, the results also suggest that fungibility is still an issue even after accounting for the effects of untied aid. However, one could argue that fungibility may not be as bad as it appears since the switch to untied aid improves spending in the sectors that are essential for growth and development. The second essay explores the hypothesis that the expectations of debt forgiveness can discourage developing countries from attaining fiscal independence through an improvement of their tax effort. On the one hand, the international financial community typically advises poor countries to improve revenue mobilization but, on the other hand, the same international community routinely continues to bail-out poor countries that fail to meet their loan repayment obligations. The act of bailing-out these countries creates an expectation on the part of developing country governments that they will receive debt forgiveness time and again in the future. Therefore, the expectation of future bail outs creates a moral hazard that leads to endemic lower tax efforts. The key prediction of our simple theoretical model is that in the presence of debt forgiveness, tax ratios will decline and this decline will be stronger the higher the frequency and intensity of the bailouts. Empirically, we test this prediction using country-level data for 66 countries for the period 1989 to 2006. The results strongly suggest that debt forgiveness plays a significant role in the low tax effort observed in developing countries. Our empirical model allows for the endogeneity of tax effort and debt forgiveness. Interestingly we find that more debt forgiveness is actually provided to countries with lower tax effort. The results are robust to various specifications.

Universiẗat, Diss., 2001--Göttingen.

Master of Science / Department of Statistics / Trevor Hefley / Binary regression models for spatial data are commonly used in disciplines such as epidemiology and ecology. Many spatially-referenced binary data sets suffer from location error, which occurs when the recorded location of an observation differs from its true location. When location error occurs, values of the covariates associated with the true spatial locations of the observations cannot be obtained. We show how a change of support (COS) can be applied to regression models for binary data to provide bias-corrected coefficient estimates when the true values of the covariates are unavailable, but the unknown location of the observations are contained within non-overlapping polygons of any geometry. The COS accommodates spatial and non-spatial covariates and preserves the convenient interpretation of methods such as logistic and probit regression. Using a simulation experiment, we compare binary regression models with a COS to naive approaches that ignore location error. We illustrate the flexibility of the COS by modeling individual-level disease risk in a population using a binary data set where the location of the observations are unknown, but contained within administrative units. Our simulation experiment and data illustration corroborate that conventional regression models for binary data which ignore location error are unreliable, but that the COS can be used to eliminate bias while preserving model choice.

Master of Science / Department of Agricultural Economics / Glynn Tonsor / Stocker cattle economic research is very limited in scope. A focus of this research is to deepen our understanding of how cattle price and animal performance variability is viewed and approached by stocker cattle producers in the United States. Another part of this research focuses on what characteristics may be drivers of whether producers choose to practice different risk management strategies. To analyze how cattle price and animal performance variability is viewed and approached by stocker cattle producers, a stated preference valuation method was used to find willingness-to-pay (WTP) estimates. Two different approaches were used to provide outcome probability information where one approach had probabilities for expected ADG change across scenarios and ADG ranges were held constant (Treatment Group A) and the second approach had ADG ranges change across scenarios and the probabilities were held constant (Treatment B). The results of our study suggest that survey respondents process scenarios differently when presented in formats Treatment Group A versus Treatment Group B. The underlying reason for this is beyond identification in this study as respondent certainty and comfort as assessed in follow-up questions was similar across the treatments. Results indicate that producers value buying cattle versus opting out of purchasing cattle and they value higher performing cattle; however, each additional pound is not valued the same. To determine the characteristics of producers and their operations that use different risk management practices, we estimated multiple probit models with the dependent variables being use of the different risk management practices. Results from the probit models suggest how producers source cattle for their operation, whether it is the region or the different markets they source from, are key determinants on whether producers practice different management strategies for market and price risk. The results suggest the model were not a good fit. Of the 30 explanatory variables included in the model, on average five explanatory variables were significant throughout the seven different dependent variables. This could be attributed to factors our study does not explicitly observe; therefore it remains a knowledge gap for the industry.

TESIS PARA OPTAR AL GRADO DE MAGÍSTER EN ANÁLISIS ECONÓMICO / La innovación es un fenómeno relevante para el crecimiento económico. No obstante, es un proceso que no ha sido estudiado a cabalidad desde la óptica de los factores que la dificultan o restringen. En este sentido, esta investigación busca aportar a la literatura estudiando los efectos del conocimiento sobre la innovación utilizando una medida directa de su efecto y desentrañando los canales por los que opera este obstáculo para distintos tipos de empresas. Para esto se utiliza un modelo Probit Bivariado, se solucionan los problemas de endogeneidad y se elimina el sesgo de selección restringiendo la muestra a las firmas potencialmente innovadoras, problemas recurrentes en este tipo de investigaciones. Se encuentra que los obstáculos de conocimiento disminuyen significativamente la innovación para las empresas, pero que este efecto es mayor para las empresas medianas, que disminuyen su propensión a innovar en cerca de 40pp. De esta forma, se debe tener en consideración la heterogeneidad de la innovación y de sus obstáculos a la hora de diseñar e implementar políticas de innovación.

The surgical robot experienced rapid uptake throughout hospitals in the US despite lack of clinical evidence that it is superior to existing methods and undeterred by its high cost. This type of technology may be a “weapon” in the medical arms race hypothesis which asserts that competition among hospitals may be welfare reducing wherein it encourages resource use that is not commensurate with beneficial health outcomes. This paper is a case-study of the diffusion of the surgical robot among hospitals in Florida. We address the medical arms race hypothesis directly by investigating whether a hospital’s decision to adopt a robot is a function of the neighboring, competing hospitals’ decisions to do so. Using a spatial autoregressive probit model, we find that the spatial coefficient is significant and negative. That is, when neighboring hospitals operate a robot, a given hospital is less likely to operate one. Indeed, hospitals appear to consider the behavior of rival hospitals, but not in a way that would be consistent with a medical arms race. Support is lent to the hypothesis that as more hospitals become providers of robotic-assisted surgery, the less profitable it becomes to enter the market.

With evidence of increasing hurricane risks in Georgia Coastal Area (GCA) and Virginia in the U.S. Southeast and elsewhere, understanding intended evacuation behavior is becoming more and more important for community planners. My research investigates intended evacuation behavior due to hurricane risks, a behavioral survey of the six counties in GCA under the direction of two social scientists with extensive experience in survey research related to citizen and household response to emergencies and disasters. Respondents gave answers whether they would evacuate under both voluntary and mandatory evacuation orders. Bivariate probit models are used to investigate the subjective belief structure of whether or not the respondents are concerned about the hurricane, and the intended probability of evacuating as a function of risk perception, and a lot of demographic and socioeconomic variables (e.g., gender, military, age, length of residence, owning vehicles).

Aim of this application-oriented master's thesis is to prove a benefits from using data analysis techniques connected with geodata processing to support business decisions. As a conclusion two solutions are given which are more attractive then starting situation. Since the first solution proposed is oriented on giving maximum success ratio while considering transactions, the second one is oriented on business value of each transaction. In this thesis R programming language is widely used together with ArcGIS Online in its final part.