Models of strategic behavior are usually too complex to conduct large scale analyses, and frequently rely on accurate descriptions of the strategic environment, or unrealistic assumptions which render empirical studies very sensitive to misspecification. This dissertation relates game-theoretic frameworks to models of causality inference and thus provides a reliable method to identify price leadership. Therefore, causal models can be used to study large sets of data without imposing strategic behavior a priori. A case study is provided by analyzing the supply chain relationship among Dominick's Finer Foods and its suppliers. Although our data required aggregation, this empirical analysis successfully determined causal patterns for 60 percent of our sample. Of these price leaderships, 70 percent elicit Manufacturer Stackelberg relationships which tend to be associated with manufacturers that hold big market shares, 25 percent elicit Retailer Stackelbergs which seem to be associated with the biggest retailer margin profits, and only 5 percent elicit a monopolistic retailer with vertical coordination. These results agree with observations made by other authors and the market structure of the 1990's. Moreover, the strategic relationship among the suppliers is also studied. Interestingly, the dominant firms tend to isolate themselves from the price leadership, whereas the second largest firms seem to become price leaders. Our studies agree with the market literature as well. In particular, we find price leadership in a firm which was identified as a low cost leader. Finally, we discovered that the private label does not lead any firm's price unless this firm is the provider of a generic brand.

In this dissertation, three related issues of building empirical time series models for financial markets are investigated with respect to contemporaneous causality, dynamics, and structural change. In the first essay, nation-wide industry information transmission among stock returns of ten sectors in the U.S. economy is examined through the Directed Acyclical Graph (DAG) for contemporaneous causality and Bernanke decomposition for dynamics. The evidence shows that the information technology sector is the most root cause sector. Test results show that DAG from ex ante forecast innovations is consistent with the DAG fro m ex post fit innovations. This supports innovation accounting based on DAGs using ex post innovations. In the second essay, the contemporaneous/dynamic behaviors of real estate and stock returns are investigated. Selected macroeconomic variables are included in the model to explain recent movements of both returns. During 1971-2004, there was a single structural break in October 1980. A distinct difference in contemporaneous causal structure before and after the break is found. DAG results show that REITs take the role of a causal parent after the break. Innovation accounting shows significantly positive responses of real estate returns due to an initial shock in default risk but insignificant responses of stock returns. Also, a shock in short run interest rates affects real estate returns negatively with significance but does not affect stock returns. In the third essay, a structural change in the volatility of five Asian and U.S. stock markets is examined during the post-liberalization period (1990-2005) in the Asian financial markets, using the Sup LM test. Four Asian financial markets (Hong Kong, Japan, Korea, and Singapore) experienced structural changes. However, test results do not support the existence of structural change in volatility for Thailand and U.S. Also, results show that the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) persistent coefficient increases, but the Autoregressive Conditional heteroskedasticity (ARCH) impact coefficient, implying short run adjustment, decreases in Asian markets. In conclusion, when the econometric model is set up, it is necessary to consider contemporaneous causality and possible structural breaks (changes). The dissertation emphasizes causal inference and structural consistency in econometric modeling. It highlights their importance in discovering contemporaneous/dynamic causal relationships among variables. These characteristics will likely be helpful in generating accurate forecasts.

The aim of this thesis is to examine performance and relationship between the US and Asian REITs indices. We find two-year (2005/3/10~2007/3/12) return of T-REITs is 15.87%, which is much lower than the return of US, Japan and Singapore. However, T-REITs has the lowest risk in selected sample countries because the lowest VaRs is found. We estimate one-day horizon holding periods VaRs and find T-REITs¡¦ performance is better than other country by the Sharpe Ratio of VaRs. The Granger causality approach indicates some lead-lag relationships between these REITs. The NAREIT EQUITY index is leading the Hong-Kong and Singapore REITs indices; Singapore REITs index is leading the J-REITs index; J-REITs index is leading the NAREIT EQUITY index. However, Causality tests show no significant lead-lag relationships between Taiwan REITs market and other REITs markets.

<p>In October 2000 the Initiative for the Integration of Regional Infrastructure in South America (IIRSA) was launched. The purpose of the IIRSA is to improve integration of the South American countries and intraregional trade between them. One of the ultimate goals is to promote sustainable growth. The purpose of this paper is to find out if a better quantity and quality of transport infrastructure increases intraregional trade in South America. It is found that the quantity of transport infrastructure increases intraregional trade. On the other hand, there is no evidence for the quality of transport infrastructure increasing intraregional trade in South America. Furthermore, this paper investigates whether economic growth can be obtained through more trade. In other words, this paper examines if trade causes growth. The results do not confirm the trade-growth causality for all countries. The difference between the existence of a trade-growth causal relationship or not could be explained by the core commodities that the different South American countries export.</p>

<p>The purpose of this paper is to investigate if real stock returns are related to real GDP growth for the case of Sweden between 1980 and 2008. By using correlation tests, the paper presents evidence that there is almost no correlation between current real stock returns and current real GDP growth. On the other hand, Granger causality tests show that stock returns are related to future production growth for the period 1980-2008. Stock returns therefore indicate real economic activity in the next quarter. Between 1980 and 1992, there is no evidence of Granger causality from stock returns to GDP growth. However, stock returns Granger-cause production growth between 1993 and 2008, which suggests that the market has become better at predicting future economic activity. The paper also documents that GDP growth does not indicate future stock returns.</p>

The objective of this Thesis research is to develop algorithms for temporally consistent semantic segmentation in videos. Though many different forms of semantic segmentations exist, this research is focused on the problem of temporally-consistent holistic scene understanding in outdoor videos. Holistic scene understanding requires an understanding of many individual aspects of the scene including 3D layout, objects present, occlusion boundaries, and depth. Such a description of a dynamic scene would be useful for many robotic applications including object reasoning, 3D perception, video analysis, video coding, segmentation, navigation and activity recognition. Scene understanding has been studied with great success for still images. However, scene understanding in videos requires additional approaches to account for the temporal variation, dynamic information, and exploiting causality. As a first step, image-based scene understanding methods can be directly applied to individual video frames to generate a description of the scene. However, these methods do not exploit temporal information across neighboring frames. Further, lacking temporal consistency, image-based methods can result in temporally-inconsistent labels across frames. This inconsistency can impact performance, as scene labels suddenly change between frames. The objective of our this study is to develop temporally consistent scene descriptive algorithms by processing videos efficiently, exploiting causality and data-redundancy, and cater for scene dynamics. Specifically, we achieve our research objectives by (1) extracting geometric context from videos to give broad 3D structure of the scene with all objects present, (2) Detecting occlusion boundaries in videos due to depth discontinuity, (3) Estimating depth in videos by combining monocular and motion features with semantic features and occlusion boundaries.

While the referent of a non-reflexive pronoun clearly depends on context, the nature of these contextual restrictions is controversial. The present study seeks to characterize one representation that guides pronoun resolution. In causal dependant clauses, the preferred referent of a pronoun varies systematically with the verb in the main clause (contrast Sally frightened Mary because she... with Sally feared Mary because she...), a phenomenon known as "implicit causality". A number of researchers have tried to explain and predict such biases with reference to semantic classes of verbs and linguistic structure. However, the classes and representations invoked have been partly ad hoc and fitted to the phenomenon itself. In this dissertation, evidence is presented that an independently-motivated semantic theory accounts for many known and new phenomena in implicit causality. In the first study, it is shown that verbs within syntactically-defined classes show similar implicit causality biases. In the second study, it is shown that information about the participants in an event (such as their relative social status) do not affect pronoun biases, even when they do affect event representations. In the third study, it is shown that two syntactically-defined verb classes show the same pronoun biases in eight different languages. In combination, these results suggest that implicit causality biases derive primarily from the same underlying semantic representations that determine syntactic behavior and not from general, non-linguistic event representations. / Psychology

Understanding chemical reactions is crucial in learning chemistry at all educational levels. Nevertheless, research in science education has revealed that many students struggle to understand chemical processes. Improving teaching and learning about chemical reactions demands that we develop a clearer understanding of student reasoning in this area and of how this reasoning evolves with training in the discipline. Thus, we have carried out a qualitative study using semi-structured interviews as the main data collection tool to explore students reasoning about reaction mechanism and causality. The participants of this study included students at different levels of training in chemistry: general chemistry students (n=22), organic chemistry students (n=16), first year graduate students (n=13) and Ph.D. candidates (n=14). We identified major conceptual modes along critical dimensions of analysis, and illustrated common ways of reasoning using typical cases. Main findings indicate that although significant progress is observed in student reasoning in some areas, major conceptual difficulties seem to persist even at the more advanced educational levels. In addition, our findings suggest that students struggle to integrate important concepts when thinking about mechanism and causality in chemical reactions. The results of our study are relevant to chemistry educators interested in learning progressions, assessment, and conceptual development.

This thesis investigates whether or not changes in a country’s government debt could affect its domestic stock market performance. The relationship is investigated by examining three different European countries, Germany, Portugal and Sweden, on the basis of two variables; (1) quarterly government debt changes as a percentage of gross domestic product and (2) the quarterly stock market changes over the time period2000:Q2 – 2011:Q2. The evidence is presented with help of Ordinary Least Square Method and Granger Causality test for each respective country. According to the Efficient Market Hypothesis, stock market prices should fully reflect all relevant information, e.g. government debt changes, as soon as they occur, without any delay, if the market is efficient. Past information should be insignificant and therefore not affect the stock market prices in an efficient market. In the cases of Sweden and Germany, the results proved to be ambiguous and thus do not allow for either rejection or acceptance of the Efficient Market Hypothesis with respect to government debt changes. However, some support was found in the case of Germany since the government debt changes and the stock market performance were instantaneously correlated. The empirical results presented in this thesis further allowed for the assumption that Portugal was not able to efficiently capture changes in the debt levels without any delay. This indicates that the Efficient Market Hypothesis can be rejected in regards for Portugal with respect to government debt changes. Furthermore, since the Portuguese stock market performance was not able to capture efficiently changes in the government debt level, it hence could possibly mislead the direction of the economy when looking into the stock prices to determine economic conditions. Moreover, the results imply that each country faces different relationships between the variables and that the relationships possibly could depend on the economic health of a country.

This dissertation investigates the determinants of China's exports and regional economic growth, the direction of causality between foreign direct investment (FDI) and exports; and convergence analysis among Chinese provinces. The study firstly discusses the evolutional process of China's foreign trade regime through comparing the strategies and policies before 1978 with those after 1978. It is emphasised that the export-promotion development policies result in the recent basic export patterns and characteristics. Furthermore, the study reviews the existing literature on exports, FDI, and convergence/growth determinants in the case of China. The empirical work comprises three parts. Firstly, fixed-effects ordinary least squares (OLS) and random-effects generalised least squares (GLS) panel data estimators are applied to test the determinants of provincial exports from 1994 to 2003. It is found that FDI, geographical location, investment in manufacturing innovation, and human capital have significant influences on regional export performance. Secondly, the augmented Dickey-Fuller (ADF) tests are carried out to test stationarity and the Granger causality tests are conducted to test the causal direction between FDI and exports, based on monthly national data from January, 2002 to June, 2006. The empirical results indicate that there is a one-way complementary causal link from FDI inflows to China's export flows. Thirdly, three methods, beta convergence, sigma convergence, and Markov Chain analysis, are used to do convergence debate among China's regions and the standard OLS cross-section and random-effects GLS panel data are applied to test the conditional convergence. The results suggest that the convergence hypothesis does not hold in China between 1994 and 2003 and there is a sign of conditional convergence, conditioning the explanatory variables such as exports, human capital, and population growth. / Thesis (Ph.D. (Economics))--North-West University, Potchefstroom Campus, 2007.