Stock market investors are making investment decisions in an information-rich environment. In their attempt to afford investors all the decision-relevant information, standard setters are continually adding to the already weighty load seemingly oblivious to the cognitive limitations of humans. Information overload has long been recognized as a problem to decision-makers. The information overload literature is robust with studies supporting the inverted U hypothesis: Decision accuracy will increase with additional information to the point of maximum processing capability, then decline. The decision style literature has supported the theory that individuals can be classified according to the quantity of information that they are able to process effectively. This study combined the two theories to develop hypotheses about how investors with differing decision styles might behave differently in an information-rich environment. The hypotheses were tested in an internet-based stock market investment experiment. In general, the study did not find significant differences in the decisions of investors with different decision styles. Though the results of the experiment failed to support most of the hypotheses, the study revealed some interesting facts about the investors who participated in this study. There was an unusually high concentration of the analytic decision style in this group. This style, according to the theory, is the one best able to manage high information processing demands. A further analysis of the respondent style dominance reveals that all of the styles had significant analytic influence. This could explain the lack of variation in the decision accuracy of the respondents. It is also possible that the respondents in this study did not reach a point of information overload. Based on prior literature, the study incorporated ten information items. However, the particular items selected may not have created a sense of information overload for the respondents. Future research should increase the information available to respondents and observe whether differences in decisions can be explained by differences in decision styles in an information overload situation. This study provides a baseline for future studies examining how investors make decisions when so much information is available.

This thesis has investigated the validity of the Environmental Kuznets Curve in the provinces of China which assumes the increase in GDP per capita (income per capita) would generate the raise of CO2 emissions (pollution) until a turning point in which CO2 emissions start decreasing. The study includes 30 provinces over a period spanning from 2000 to 2019 by applying OLS and Fixed-effects regression model with panel data. The findings demonstrate that the provinces of China conform to the EKC theory's projections by exhibiting an inverted-U shape. Apart from that, this study also confirmed the presence of differences in turning points between provinces with high income and those with low income, and the former exhibiting a significantly higher value. Our research findings suggest that policymakers should tailor their CO2 emission reduction policies to the specific circumstances of each region. In the absence of appropriate measures, a negative outcome may arise.

<p>The economic development and industrialization that has taken place in many parts of the world during the past century has brought about a huge increase in economic welfare. During this process, it has repeatedly been debated whether the gains from economic development are shared by everyone or just a few. In the field of economics, vast research has been conducted on this particular subject ever since the 1950’s. The most famous contribution might be said to be Simon Kuznets article, Growth and Income Inequality from 1955 and the ”inverted U”-hypothesis that was formulated on the basis of that article. The essence of the hypothesis is that a country, during its development, moves from agricultural to industrial production. At first, income inequality increases and then, at the end of the process, decreases.</p><p>The aim of this paper has been to investigate the relationship between income distribution and economic development in a particular region, namely the countries of the former Soviet Union, during 1992-2003. Also, we have tested whether Kuznets theory and the “inverted U”-hypothesis hold true for our sample. The investigations method is a survey, which uses secondary data collected from the World Bank’s database of World Development Indicators. Regression-analysis has been employed to conduct cross-sections between 20 countries over 4 periods in Eastern Europe and Central Asia. The number of observations equals to 62. The variables that we use are: the Gini index, GDP per capita and the agricultural sector’s share of GDP.</p><p>The results of the regression do not indicate any resemblance to the pattern of the “inverted U”-hypothesis. The curve we get is that of a “positive U”. Countries with high GDP per capita as well as countries with low GDP per capita have high income inequality. Countries with mediate GDP per capita levels have low income inequality. Our analysis concludes that the countries in our sample might have had a very unique economic development following the fall of the Soviet Union. Only 7 countries partly follow the Kuznets theory if tested individually. Since these seven countries seem to have a reversed development with increasing agricultural sector and the remainder of the countries show increasing income inequality, we reject the “inverted U”-hypothesis and question the ability of Kuznets’ theory to explain income distribution for our sample.</p>

The economic development and industrialization that has taken place in many parts of the world during the past century has brought about a huge increase in economic welfare. During this process, it has repeatedly been debated whether the gains from economic development are shared by everyone or just a few. In the field of economics, vast research has been conducted on this particular subject ever since the 1950’s. The most famous contribution might be said to be Simon Kuznets article, Growth and Income Inequality from 1955 and the ”inverted U”-hypothesis that was formulated on the basis of that article. The essence of the hypothesis is that a country, during its development, moves from agricultural to industrial production. At first, income inequality increases and then, at the end of the process, decreases. The aim of this paper has been to investigate the relationship between income distribution and economic development in a particular region, namely the countries of the former Soviet Union, during 1992-2003. Also, we have tested whether Kuznets theory and the “inverted U”-hypothesis hold true for our sample. The investigations method is a survey, which uses secondary data collected from the World Bank’s database of World Development Indicators. Regression-analysis has been employed to conduct cross-sections between 20 countries over 4 periods in Eastern Europe and Central Asia. The number of observations equals to 62. The variables that we use are: the Gini index, GDP per capita and the agricultural sector’s share of GDP. The results of the regression do not indicate any resemblance to the pattern of the “inverted U”-hypothesis. The curve we get is that of a “positive U”. Countries with high GDP per capita as well as countries with low GDP per capita have high income inequality. Countries with mediate GDP per capita levels have low income inequality. Our analysis concludes that the countries in our sample might have had a very unique economic development following the fall of the Soviet Union. Only 7 countries partly follow the Kuznets theory if tested individually. Since these seven countries seem to have a reversed development with increasing agricultural sector and the remainder of the countries show increasing income inequality, we reject the “inverted U”-hypothesis and question the ability of Kuznets’ theory to explain income distribution for our sample.

The focal objective of this thesis was to examine the potential advantage of introducing the self-schema concept, indexed by response time, into personality assessment. The basic rationale for the use of response time is that a self-schema facilitates response time for self-referent information as it permits people to make assessments easier and automatic. A self-schema is a cognitive structure containing the generic knowledge that people have about themselves, influencing all aspects of the processing of self-relevant information in order to organize, summarize and explain their behavior. Paper I examined the self-schema proposition that the relation between personality score and response time for the Big Five personality factors is curvilinear in accordance with the inverted-U effect. Using more appropriate statistical methods than in previous studies, Study 1 and Study 2 confirmed the existence of the inverted-U effect for all Big Five factors. Thus the results provided support for the self-schema perspective as people scoring low or high on the Big Five traits responded faster than those scoring in the middle. Previous research has shown that the Big Five personality factors Openness to Experience and Agreeableness are powerful predictors of prejudice. The main question in Paper II was whether this prediction could be improved by including a measure of self-schema (schematicity). The results of Study 3 demonstrated that response time significantly improved the prediction of generalized prejudice from the mentioned personality factors and disclosed both an additive and a moderating effect. Thus, the relation between personality trait score and generalized prejudice is moderated by how schematic a person is. Paper III examined the potential linkage between heritability and self-schema. In Study 4, 5, and 6, the relation between heritability and response time for the Big Five personality facets (subfactors) was examined. The results revealed that personality response time is related to personality heritability so that shorter response times are associated with higher heritabilities. Putting the present results into the context of self-schemas, this means that Big Five personality facets with a large heritability on the average would have higher schematicity than those with small heritability estimates. The results of the present thesis extend previous work in the area of self-schema. The findings suggest that self-schema, measured by response time, may be a useful additional tool to fine-tune personality assessment. Also, the findings put emphasis on the importance of considering possible curvilinear relationships and interaction effects in order to better comprehend the rationale underlying self-schemata processing.  Finally, the results imply that the heritability of personality traits should be taken into account when we construct theories and models in personality psychology. The implications of these results are discussed and directions for future research are highlighted.

The Intergovernmental Panel on Climate Change 2018 highlights the importance of short-lived greenhouse gasses to combat global warming. This study explores the relationship between Gross Domestic Product per capita and methane per capita. The relationship is explored in relation to the Environmental Kuznets Curve theory where the subjects to examination used are High Income Countries and Low Income Countries based on United Nation classifications in 2019. In total 47 countries are examined where 30 countries are High Income Countries and 17 are Low Income Countries. The relationships are examined for the time periods 1970 to 2017 through Fixed Effect Models. To improve accuracy additional control variables are added: Population in agriculture (% of total employment), balance of payments and forest areas. With the added control variables, the time frame used in Fixed Effect Models changes to 1991 to 2017. The different Fixed Effect Models provide inverted U-shaped relationships for Low Income Countries and uncertain results for High Income Countries according to the Environmental Kuznets Curve.

This study re-examines the relationship between competition and innovation in a detailed firm-level dataset of publicly traded US companies spanning from 1975 to 2013. Using R&D expenditures, patent counts and patent citations as the measures of innovation, and Herfindahl-Hirschman Index, Lerner Index, Profit Elasticity and Product Market Fluidity as the proxies for competition we document a robust positive association between the two variables, as well as strong evidence of the non-linear relationship known as "inverted-U shape", when controlling for size, distance to technological frontier, level of knowledge spillovers, technological opportunities and other firm- and industry-specific characteristics. We address overdispersion in the data by using negative binomial and zero-inflated negative binomial count data regressions, and the results are robust in these specifications. Additionally, in order to address potential endogeneity issues, we employ a set of instruments based on the import tariff rates and the level of Chinese import penetration, and find a weak evidence of positive relationship as well. Overall the results strongly support the prediction of agency models, "replacement effect" and "escape- competition effect" about the positive influence of competition on innovation. Powered by TCPDF...