Econometrics of vice: Idle students, partisan prosecutors and environmental predators

This thesis is organized in three clearly differentiated chapters. The three of them deal with currently relevant issues: The effect of low-quality of standardized tests on research, the high levels of political corruption in Spain and the collective capacity of tackle climate change. In the first chapter “Straightening PISA: When Students do not Want to answer Standardized Tests”, I study one of the key elements on current education policies: The standardized-tests. Concretely, I analyze how students approach standardized tests in different ways. I use a measure of effort exerted by students belonging to different countries and social groups in order to assess the impact of low effort on the student's final score. The measure links an acknowledged psychological tests (Dot-Counting test) with one PISA-item, in which students had to merely count dots. In this chapter, I measure to which extent different effort levels may distort the score of students. This problem would affect social-science research when standardized-tests are use. At the end of the chapter, I propose a simple solution to design standard tests which would eliminate this problem. Given the importance of standardized-tests on the design of education programs, this paper may be a contribution to implement more accurate education policies. The second chapter focuses on one key issue of Spanish current political crisis: The level of political corruption. Political institutions developed during the Spanish transition to democracy are currently criticized due to their inability to stop political corruption. For instance, Spanish Attorney Generals are appointed by the government and their impartiality is usually criticized. In “Stories on Corruption: How Media and Prosecutors Influence Elections”, I analyze systematically the partiality of the last two Attorney Generals. Concretely, I study whether Attorney Generals try to influence elections by adjusting the tempo of their investigations to the electoral calendar. This possibility is combined with the mass media editorial decisions. I analyze whether mass media have a partisan bias and hide corruption activities of their preferred parties. For doing so, I have created a unique database: I have coded the number of articles containing the word “corruption” of the two main Spanish newspapers “El Pais” and “El Mundo" every week in the last ten years. After the econometric analysis I found significant evidence of the partisan behavior of both the Attorney Generals and mass media. The last chapter is a joint work with Karolina Safarzynska from the Wirtschaftsuniversität Wien. “Responding to the Climate Change Challenge: Experimental Evidence” tackles the problem of climate change and the capacity of societies to overcome it. This chapter has also a different methodology. Precisely, it is based on experimental methods. We consider isolated groups of individuals which must extract resources form a renewable common-pool. The novelty is the study of the impact of resource uncertainty on individual harvests in common-pool resource dilemmas together with the possibility of group collapse. The uncertainty is modeled as a weather shock diminishing the groups' resources, which is drawn from the distribution known in advance to participants. On the other hand, the group collapses if the resources go below a certain threshold. In that case all accumulated resource-extraction get lost. This can be interpreted as the minimum harvests below which a group does not have sufficient nutrition to survive. We find that in the long run, sufficiently severe weather shocks can induce individuals to conserve resources. However, in the short-run uncertainty leads to resources over-exploitation. In addition, our results suggest that resource uncertainty undermines effectiveness of costly sanctioning. In some treatments, individuals can punish others at their own cost. We found that the possibility to punish others induce individuals to harvest significantly more resources in the beginning of the experiment, compared to the situation when sanctioning is not possible. The presence of punishment paradoxically increases the probability of resource exhaustion. We interpret these results in the context of the World climate change. We conclude that the positive impact of environmental pressure on individual behavior and the effect of new institutions are likely to come too late to prevent damage to the environment

A Methodology for Measuring the Property Flood Resilience (PFR) of Households at the Risk of Flooding

The risks of flooding have been ever present for homes located in flood plains or close to coastal areas. Surface water flooding and flash flooding in urban areas means that homes located away from flood plains and coastal areas may also be exposed to flooding. While some of these homes have developed a level of resilience over time, many have very poor, inadequate or lack any level of resilience to flooding. This raises the questions as to what level of resilience is appropriate; how best to quantify flood resilience at the level of the individual homes; and what steps to take to improve resilience. However, despite the current focus on resilience within UK flood risk management policy and strategy, no accepted definition for the term exists and, more significantly, there is a lack of a general measurement framework for determining the level of flood resilience for an individual home. Hence, the aim of this research is to develop a model for reliably measuring the level of resilience present in individual homes at risk of flooding. In order to establish the framework for this research, a comprehensive literature review was conducted on the concept of resilience and flood risk management in the context of households. Based on a synthesis of the literature, a conceptual framework of Property Flood Resilience (PFR) at the household level was developed which comprises both building and human components. A quantitative research methodology was employed towards testing the design and validity of the PFR framework, with data collected through a questionnaire survey of homeowners who have experienced flood events on their properties. Different sets of analyses were performed on the data collected, including the normality test, analysis of variance (ANOVA), correlation analysis, and regression analysis. The overall PFR was modelled with the building and human resilience using multiple linear regression, and from this model it can be inferred that building and human resilience significantly predicts the level of the overall PFR. Further, building resilience were found to be positively and significantly associated with human resilience (at r = 0.407). This implies that increases in the resilience of the building component will result in an increase in the human resilience and ultimately increase in the overall resilience of the individual household. The PFR model developed provides valuable information on the flood resilience levels currently present in the home for the benefit of homeowners. It also provides property experts and surveyors with a tool to estimate resilience levels within a property, enabling them to provide impartial and professional advice on risk exposure and measures that can be adopted to help further protect properties. The model also serves as an evidence based tool to inform insurers on the levels of resilience present within a given property and to consider how this might affect insurance premiums and excesses which will in turn improve the role of flood insurance as a market-based incentive, and to complement Government‘s effort in encouraging homeowners to invest in PFR

MODELLING OPERATIONAL RISK MEASUREMENT IN ISLAMIC BANKING: A THEORETICAL AND EMPIRICAL INVESTIGATION

With the emergence and development of Islamic banking industry, the need to cater operational risks issues has attracted the attention of academics in recent years. Such studies commonly agree that operational risk is relatively higher and serious than credit risk and market risk for Islamic banks. However, there is not any single research in the context of Islamic banking which thoroughly tackles the issue of operational risks by tackling it in three main aspects: theoretical, methodological, and empirical. This may be due to the fact that operational risk is relatively new area, which requires further research to understand the complexities it carries. This is the sources of motivation for the research, which aims to fill this observed gap in the literature by responding to the mentioned three aspects. This research, hence, aims to develop a new measurement model of operational risk exposures in Islamic banking with the objective of theoretically determining the underlying features of operational risk exposures and its measurement particularly for Islamic banks. In its attempt to develop a theoretical framework of the proposed model, the research provides a classification of operational risks in major Islamic financial contracts. In addition, rather than adopting the existing operational risk measurement methods, this research develops a proposed measurement model attributed as Delta Gamma Sensitivity Analysis- Extreme Value Theory (DGSA-EVT) model. DGSA-EVT is a model to measure high frequency-low severity (HF-LS) and low frequency-high severity (LF-HS) type of operational risks. This is the core of this research’s methodological contribution. As regards to the empirical contributions, in analysing operational value at risk (opVaR), this research carefully analyses the behaviour of the data by taking into account volatility, skewness and kurtosis of the variables. In the modelling, volatility analysis employs two models: constant-variance model and exponential weighted moving average (EWMA) model. Results of the empirical tests show that the operational risk variables in this research are non-normal; thus, non-normality involving skewness and kurtosis as well as volatility has to be taken into account in the estimation of VaR. In doing so, this research employs Cornish-Fisher expansion upon which the confidence interval of operational variables is an explicit function of the skewness and kurtosis as well as the volatility. Empirical findings by deploying a set of econometrics tests reveal that for financing activities, the role of maintaining operational efficiency as part of an Islamic bank’s fiduciary responsibilities is immensely high. However, people risk is enormous and plays a dominant role in affecting the level of operational risk exposures in Islamic banks in investment activities

The evolution and dynamics of stocks on the Johannesburg Securities Exchange and their implications for equity investment management

[No subject] This thesis explores the dynamics of the Johannesburg Stock Exchange returns to understand how they impact stock prices. The introductory chapter renders a brief overview of financial markets in general and the Johannesburg Securities Exchange (JSE) in particular. The second chapter employs the fractal analysis technique, a method for estimating the Hurst exponent, to examine the JSE indices. The results suggest that the JSE is fractal in nature, implying a long-term predictability property. The results also indicate a logical system of variation of the Hurst exponent by firm size, market characteristics and sector grouping. The third chapter investigates the economic and political events that affect different market sectors and how they are implicated in the structural dynamics of the JSE. It provides some insights into the degree of sensitivity of different market sectors to positive and negative news. The findings demonstrate transient episodes of nonlinearity that can be attributed to economic events and the state of the market. Chapter 4 looks at the evolution of risk measurement and the distribution of returns on the JSE. There is evidence of fat tails and that the Student t-distribution is a better fit for the JSE returns than the Normal distribution. The Gaussian based Value-at-Risk model also proved to be an ineffective risk measurement tool under high market volatility. In Chapter 5 simulations are used to investigate how different agent interactions affect market dynamics. The results show that it is possible for traders to switch between trading strategies and this evolutionary switching of strategies is dependent on the state of the market. Chapter 6 shows the extent to which endogeneity affects price formation. To explore this relationship, the Poisson Hawkes model, which combines exogenous influences with self-excited dynamics, is employed. Evidence suggests that the level of endogeneity has been increasing rapidly over the past decade. This implies that there is an increasing influence of internal dynamics on price formation. The findings also demonstrate that market crashes are caused by endogenous dynamics and exogenous shocks merely act as catalysts. Chapter 7 presents the hybrid adaptive intelligent model for financial time series prediction. Given evidence of non-linearity, heterogeneous agents and the fractal nature of the JSE market, neural networks, fuzzy logic and fractal theory are combined, to obtain a hybrid adaptive intelligent model. The proposed system outperformed traditional models

Earthquake research in China

A visit to China of an American seismological delegation, which took place October 5 to November 5, 1974, is covered in this report. The Americans were sponsored by the Committee on Scholarly Communication with the People's Republic of China (CSCPRC), and the hosts in China were the Scientific and Technical Association and the State Seismological Bureau. The CSCPRC is sponsored jointly by the National Academy of Sciences, the Social Science Research Council, and the American Council of Learned Societies. The visit had its origins in an invitation extended in January 1973 by Carl Kisslinger, as President of the Seismological Society of America, to the Chinese Academy of Sciences to send representatives to a Symposium on Earthquake Prediction Research. Although the Chinese declined to participate, this invitation was one step towards a reciprocal exchange of seismologists between the United States and the People's Republic of China. Several months after Kisslinger's letter the CSCPRC visited Peking. Their purpose was to arrange an exchange program with the Chinese Scientific and Technical Association. Prompted by Kisslinger, the committee's proposals for American delegations included seismology. Not only was this particular exchange accepted, but the Chinese in turn suggested that a Chinese seismology group visit the United States

Estimating Dependences and Risk between Gold Prices and S&P500: New Evidences from ARCH,GARCH, Copula and ES-VaR models

This thesis examines the correlations and linkages between the stock and commodity in order to quantify the risk present for investors in financial market (stock and commodity) using the Value at Risk measure. The risk assessed in this thesis is losses on investments in stock (S&P500) and commodity (gold prices). The structure of this thesis is based on three empirical chapters. We emphasise the focus by acknowledging the risk factor which is the non-stop fluctuation in the prices of commodity and stock prices. The thesis starts by measuring volatility, then dependence which is the correlation and lastly measure the expected shortfalls and Value at risk (VaR). The research focuses on mitigating the risk using VaR measures and assessing the use of the volatility measures such as ARCH and GARCH and basic VaR calculations, we also measured the correlation using the Copula method. Since, the measures of volatility methods have limitations that they can measure single security at a time, the second empirical chapter measures the interdependence of stock and commodity (S&P500 and Gold Price Index) by investigating the risk transmission involved in investing in any of them and whether the ups and downs in the prices of one effect the prices of the other using the Time Varying copula method. Lastly, the third empirical chapter which is the last chapter, investigates the expected shortfalls and Value at Risk (VaR) between the S&P500 and Gold prices Index using the ES-VaR method proposed by Patton, Ziegel and Chen (2018). Volatility is considered to be the most popular and traditional measure of risk. For which we have used ARCH and GARCH model in our first empirical chapter. However, the problem with volatility is that it does not take into account the direction of an investments’ movement: volatility of stocks is that they suddenly jump higher and investors are not distressed with gains. When we talk about investors for them the risk is about the odds of losing money, after my research and findings VaR is based on the common-sense fact. Hence, investors care about the odds of big losses, VaR answers the question, what is my worst-case scenario? Or simply how much I could lose in a really bad month? The results of the thesis demonstrated that measuring volatility (ARCH GARCH) alone was not sufficient in measuring the risk involved in an investment therefore methodologies such as correlation and VAR demonstrates better results. In terms of measuring the interdependence, the Time Varying Copula is used since the dynamic structure of the de- pendence between the data can be modelled by allowing either the copula function or the dependence parameter to be time varying. Lastly, hybrid model further demonstrates the average return on a risky asset for which Expected Shortfall (ES) along with some quantile dependence and VaR (Value at risk) is utilised. Basel III Accord which is applied in coming years till 2019 focuses more on ES unlike VaR, hence there is little existing work on modelling ES. The thesis focused on the results from the model of Patton, Ziegel and Chen (2018) which is based on the statistical decision theory. Patton, Ziegel and Chen (2018), overcame the problem of elicitability for ES by using ES and VaR jointly and propose the new dynamic model of risk measure. This research adds to the contribution of knowledge that measuring risk by using volatility is not enough for measuring risk, interdependence helps in measuring the dependency of one variable over the other and estimations and inference methods proposed by Patton, Ziegel and Chen (2018) using simulations proposed in ES-VaR model further concludes that ARCH and GARCH or other rolling window models are not enough for determining the risk forecasts. The results suggest, in first empirical chapter we see volatility between Gold prices and S&P500. The second empirical chapter results suggest conditional dependence of the two indexes is strongly time varying. The correlation between the stock is high before 2008. The results further displayed slight stronger bivariate upper tail, which signifies that the conditional dependence of the indexes is influence by positive shocks. The last empirical chapter findings proposed that measuring forecasts using ES-Var model proposed by Patton, Ziegel and Chen (2018) does outer perform forecasts based on univariate GARCH model. Investors want to 10 protect themselves from high losses and ES-VaR model discussed in last chapter would certainly help them to manage their funds properly

Urban food strategies in Central and Eastern Europe: what's specific and what's at stake?

Integrating a larger set of instruments into Rural Development Programmes implied an increasing focus on monitoring and evaluation. Against the highly diversified experience with regard to implementation of policy instruments the Common Monitoring and Evaluation Framework has been set up by the EU Commission as a strategic and streamlined method of evaluating programmes’ impacts. Its indicator-based approach mainly reflects the concept of a linear, measure-based intervention logic that falls short of the true nature of RDP operation and impact capacity on rural changes. Besides the different phases of the policy process, i.e. policy design, delivery and evaluation, the regional context with its specific set of challenges and opportunities seems critical to the understanding and improvement of programme performance. In particular the role of local actors can hardly be grasped by quantitative indicators alone, but has to be addressed by assessing processes of social innovation. This shift in the evaluation focus underpins the need to take account of regional implementation specificities and processes of social innovation as decisive elements for programme performance.

2010-2011, University of Memphis bulletin

University of Memphis bulletin containing the graduate catalog for 2010-2011.https://digitalcommons.memphis.edu/speccoll-ua-pub-bulletins/1430/thumbnail.jp

The Effect of Immigrant Composition on Student Achievement: Evidence from New York City

There has been a large body of recent literature focused on the effects of school composition on student outcomes. These studies have focused on peer group characteristics such as achievement, gender composition, ethnic and racial composition, and socioeconomic composition. This area of research has been commonly called peer effects. A relatively unexplored area of peer effects research involves the effect of immigrant children on their schoolmates. Because of the heterogeneity between immigrant groups, this study focuses on East Asian and Dominican immigrant children. As these two groups are on opposite sides of the socioeconomic spectrum, comparing results of the two analyses should provide a reasonably complete picture of immigrant composition effects. The data for this study come from New York City. New York City is arguably the ideal place to study immigration. Immigrants from though out the world attend New York City schools. While New York remains an outlier, it is quickly becoming the norm. In recent decades, various parts of the country that have not experienced large waves of immigration are doing so now. The experience of New York has potential to inform the larger debate on the cost of providing public services to immigrants. If immigrant children have negative effects on their schoolmates, they will increase the cost of education. On the other hand, if they have positive effects, they can serve as a positive externality and reduce the cost of public education. The estimation of peer effects is a daunting challenge. One of the most challenging of these problems is called the selection problem. The selection problem occurs because immigrant children are not randomly assigned to classes, schools, or neighborhoods. To overcome this problem, this study uses credibly exogenous variation that occurs as a student progresses with a cohort within a school. The results suggest that both East Asian and Dominican immigrant composition has a negative and significant effect on student achievement. This effect occurs for all subgroups and for both English-Language Arts and mathematics. Surprisingly, this immigrant composition effect is not driven by ELL status. This coefficient can be considered something of a reduced-form measure of immigrant composition effect. Regressions that control for other country variables suggest that schools with growth in East Asian and Dominican immigrant composition also have growth in other forms of immigrant composition. When including these other variables, the results suggest a cultural effect. East Asian immigrants have positive effects in mathematics while Dominican immigrants continue to have negative effects, though at smaller magnitudes. These results suggest that culture matters. As a matter of policy though, given that immigrants move together, it is not practical to separate specific ethnic immigrant effects. Rather policy recommendation should look at the reduced form effects. Potential policy recommendations include additional resources for immigrant education such as English as a second language and civics classes or newcomer schools. Ethnographic research on how immigrant children interact with their classmates and schools could also be valuable in deciphering the exact mechanism behind this negative effect