This paper examines trade openness and economic growth. What has been the effect of openness to trade on economic growth in Kenya? Kenya’s trade policies have emerged since independence, it has improved from import substitution to progressive liberalization through emergence of export processing zones, reduction of tariffs levels, eliminated price controls and licensing requirements leading to modest growth in trade Republic of Kenya (2005). Although the country has improved in it’s trade policies, it is still counted as mostly unfree. Empirical evidence suggests that free trade leads to a better economic performance in different channels, however the evidence has been questioned because of the doubts on how trade openness of a country should be measured and methodology estimation. The study uses trade intensity as a measure of trade openness. Applying Ordinary least squares using a time series data obtained from the World Development Indicators a negative relationship is seen between trade openness measure and Gross domestic product in Kenya. A Granger causality test is done also to determine whether trade liberalization can be used to give significant information about the economic growth of Kenya or vice versa. Vector Auto regression model (VAR) is used to determine the Granger causality. In the OLS regression model measures of openness, labor and capital are significant.

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Michotte's theory of ampliation suggests that causal relationships are perceived by objects animated under appropriate spatiotemporal conditions. In this thesis I extend the theory of ampliation and propose that the immediate perception of complex causal relations is also dependent upon a set of structural and temporal rules. The thesis aims at achieving two main goals. The first goal is to define a taxonomy of semantics that describe different causal events in the environment. Ten semantics are defined in this thesis and divided into two main groups; simple causal semantics and complex causal semantics. Simple causal semantics describe basic semantics, which form the building blocks for more complex information and include causal amplification, causal dampening, causal strength, and causal multiplicity. Complex causal semantics are built by enhancing or combining one or more simple semantics and include additive causality, contradictive causality, fully-mediated causality, partially-mediated causality, threshold causality, and bidirectional causality. The second goal of this thesis is to design simple visual representations to describe the causal information. Three representation types were designed during the course of this research; static-graph, static-sequence, and animation. Nine experiments were also conducted to test the effectiveness of these representations. The first five experiments compared the static-graph and the animated representations through Memory Recall and Intuitiveness Evaluations tests. Results of these experiments suggest that animations were ~8% more accurate and performed ~9% faster than the static-graph representations. The last four experiments compared an enhanced static representation, called static-sequence, to the animations to test if sequential animation of causal relations had any influence on the superior performance of the animations in the previous experiments. Results of these experiments suggest that there was no significant difference in the performance of the static-sequence representations when compared to the static-graph representations. The results also suggest that the animations performed more accurately than their static counterparts mainly due to their intuitiveness. Overall our results show that animated diagrams that are designed based on perceptual rules such as those proposed by Michotte have the potential to facilitate comprehension of complex causal relations.

One of the most immediately compelling arguments against the disjunctivist position within the philosophy of perception points to the well-accepted fact that hallucinations can have the same neural cause as veridical perceptions; this is known as the causal argument. Since the main motivation for disjunctivism is to preserve naive realism, critics claim that naive realism is then incompatible with certain, well-accepted claims of neuropsychology, and, thus, disjunctivism is false. After surveying the general arguments for disjunctivism offered by Hinton, Snowden, and Martin, the causal argument is split into a stronger version and a weaker version. The strong argument relies on a narrow conception of the ‘same cause, same effect’ principle and this narrow conception is extremely controversial, ultimately entailing that mental events supervene only on the total brain state of an individual. The weak argument, which embraces a wider conception of the ‘same cause, same effect’ principle finds the disjunctivist position explanatorily redundant. The two major camps within disjunctivism, positive disjunctivism and negative disjunctivism, offer different approaches to the weak argument, and what emerges from the discussion of these two theories is that negative disjunctivism has a major dialectical advantage against positive disjunctivism, and that negative disjunctivism offers a satisfying response to the weak causal argument. M. G. F. Martin offers an insightful analysis of ‘indistinguishability’ and in doing so clarifies the disjunctivist thesis, sets limits to our understanding of our own mental states, and places the burden with the common-kind theorist.

The essays in this dissertation explore issues related to health and retirement of older Americans, using longitudinal data on older Americans from ten waves of the Health and Retirement Study (1992-2010). The first essay explores the effect of both subjective and relatively more objective physical and mental health conditions on the probability of exit from full-time employment. Eight health indices (factors) are created from a wide range of health measures by principal component analysis. The effect of these health factors on the time until exit from full-time employment is empirically examined in a proportional hazard model. Single and competing risk specifications are estimated that allow for multiple spells of full-time employment and control for unobserved heterogeneity. The main results suggest that increase in functional limitation factor makes an individual more likely to exit via any route in general and the complete retirement route in particular. For mental health problems, increase in the depression factor increases the likelihood of exit from full-time employment via the complete retirement, part-time work and unemployment routes. While increase in cognitive disorders factor has no significant effect on the likelihood of exit via complete retirement, but increases the likelihood of exit via the disability route. These results have implications for public policies targeted towards retaining older workers within the labor market. The second essay examines the effect of retirement on post retirement physical and mental health and the extent to which the effects differ across these different health outcomes. The inherent issue of reverse causality between health and retirement that leads to endogeneity is addressed by using multiple sample stratification and instrumental variable estimation strategies. The stratified samples include individuals who are physically and mentally healthy prior to their retirement so that pure effect of retirement on post retirement health may be found. Five different instruments for complete retirement are also used to deal with endogeneity. The sample stratification results unanimously indicate that complete retirement has adverse effect on post retirement physical and mental health. While the instrumental variables approach results are mixed and are based on the choice of instrument for complete retirement.

Michotte's theory of ampliation suggests that causal relationships are perceived by objects animated under appropriate spatiotemporal conditions. In this thesis I extend the theory of ampliation and propose that the immediate perception of complex causal relations is also dependent upon a set of structural and temporal rules. The thesis aims at achieving two main goals. The first goal is to define a taxonomy of semantics that describe different causal events in the environment. Ten semantics are defined in this thesis and divided into two main groups; simple causal semantics and complex causal semantics. Simple causal semantics describe basic semantics, which form the building blocks for more complex information and include causal amplification, causal dampening, causal strength, and causal multiplicity. Complex causal semantics are built by enhancing or combining one or more simple semantics and include additive causality, contradictive causality, fully-mediated causality, partially-mediated causality, threshold causality, and bidirectional causality. The second goal of this thesis is to design simple visual representations to describe the causal information. Three representation types were designed during the course of this research; static-graph, static-sequence, and animation. Nine experiments were also conducted to test the effectiveness of these representations. The first five experiments compared the static-graph and the animated representations through Memory Recall and Intuitiveness Evaluations tests. Results of these experiments suggest that animations were ~8% more accurate and performed ~9% faster than the static-graph representations. The last four experiments compared an enhanced static representation, called static-sequence, to the animations to test if sequential animation of causal relations had any influence on the superior performance of the animations in the previous experiments. Results of these experiments suggest that there was no significant difference in the performance of the static-sequence representations when compared to the static-graph representations. The results also suggest that the animations performed more accurately than their static counterparts mainly due to their intuitiveness. Overall our results show that animated diagrams that are designed based on perceptual rules such as those proposed by Michotte have the potential to facilitate comprehension of complex causal relations.

Thesis (Ph. D.)--University of Canterbury, 2007. / Typescript (photocopy). Includes bibliographical references (p. 127-135). Also available via the World Wide Web.

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

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This thesis investigates the monetary sector in Cameroon within an open economy framework. Two main hypotheses: money demand and Granger-causality are investigated. The data used are found to be non-stationary. Consequently, the money demand relationship is tested for the null hypothesis that it is spurious or not co-integrated. This is rejected in all the models put forward. The models are estimated and found to exhibit elasticities that are not unusual. Price homogeneity is found to be data incompatible. Income elasticities are generally found to be significantly less than unity suggesting economies of scale in money holdings. Corresponding dynamic models in the form of error correction are constructed using the familiar general to specific methodology and generally found to exhibit desirable statistical properties. Model preference is in terms of the narrow Ml definition of money with explanatory variables which include a foreign interest rate. For Granger-causality, the non-stationary data are transformed into stationarity where the null hypothesis of noncausality is tested in bivariate and multivariate contexts. Lag length selection is by the Final Prediction Error statistic. Results are mixed but two appear striking: domestic money and prices are found to be independent while domestic prices are Granger-caused by foreign variables but not by domestic ones.