Wu, Zhouheng. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 44-46). / Abstract also in Chinese. / Chapter 1. --- Introduction --- p.1 / Chapter 2. --- Literature Review --- p.3 / Chapter 3. --- Overview of Key Factors that affect inflation in China --- p.6 / Chapter 3.1 --- Output Growth --- p.6 / Chapter 3.2 --- Money Supply --- p.7 / Chapter 3.3 --- Exchange Rate --- p.7 / Chapter 3.4 --- Wage --- p.8 / Chapter 3.5 --- Other Exogenous Shocks --- p.10 / Chapter 4. --- The Model --- p.11 / Chapter 4.1 --- Households --- p.12 / Chapter 4.2 --- Production Firms --- p.16 / Chapter 4.2.1 --- Non-Traded Sector --- p.16 / Chapter 4.2.2 --- Traded Sector --- p.19 / Chapter 4.3 --- Import Prices --- p.20 / Chapter 4.4 --- Monetary Policy Rules --- p.21 / Chapter 4.5 --- Domestic and External Shocks --- p.23 / Chapter 4.6 --- Market Clearing Conditions --- p.24 / Chapter 5. --- Calibration --- p.26 / Chapter 5.1 --- Calibration of parameter values --- p.26 / Chapter 5.2 --- Theoretical Impulse Responses and Variance Decomposition --- p.28 / Chapter 6. --- Model Fitness --- p.33 / Chapter 7. --- Conclusion Remarks --- p.35 / References --- p.38 / Appendix / Appendix A Equilibrium Conditions --- p.41 / Appendix B Steady State --- p.43 / Appendix C Simulation --- p.45 / Appendix D Data Description and Empirical Results --- p.56

Call number: LD2668 .T4 1986 A33 / Master of Science / Agricultural Economics

Thesis (MBA (Business Management))--University of Stellenbosch, 2009. / ENGLISH ABSTRACT: Tobin's q value is widely used by financial analysts as a performance indicator ratio. The market value of a firm over the replacement cost of fixed assets and inventory serves as an indication of whether value is created by investing internally in the firm, or whether value is destroyed by investing in negative net present value projects. Where Tobin's q is greater than one (q > 1), the market value of the firm is greater than what it would cost to replace fixed assets and inventory. Therefore value is created. Firms that have a Tobin's q value of less than one are advised to pay dividends rather than invest in negative net present value projects. Over 200 different methods exist of calculating Tobin's q. By increasing the complexity of the algorithm to determine q, very little is achieved to improve the measurement quality. A strong link exists between excess market returns, free cash flow spending announcements and Tobin's q value for the firm. Firms with a high Tobin's q value should ensure that good investment possibilities are pursued. The use of internal funds to fund new investment is viewed in a positive light by the market and above average returns are generated. Firms with a high Tobin's q value and high free cash flow show lower returns. These lower returns happen as a result of the market recognising the firm's failure to capitalise on favourable internal investment opportunities. / AFRIKAANSE OPSOMMING: Tobin se q-waarde word wyd gebruik as prestasie aanwyser deur finansiele ontleders. Die markwaarde van 'n firma gedeel deur die vervangingskoste van vaste bates en voorraad, dien as 'n maatstaf om aan te dui of waarde geskep word deur intern in die firma te belê en of waarde vernietig word deur in projekte met 'n negatiewe netto teenswoordige waarde te belê. Waar Tobin se q-waarde groter is as een (q > 1) is die markwaarde van die firma groter as wat dit sal wees om die vaste bates en voorraad te vervang. Sodoende word waarde geskep. Firmas met 'n q-waarde van minder as een word aanbeveel om eeeder dividende uit te betaal as om die beskikbare fondse in projekte met 'n negatiewe netto teenswoordige waarde te investeer. Meer as 200 verskillende metodes bestaan om Tobin se q-waarde te bereken. Deur die kompleksiteit van die algoritme te vergroot om q te bereken, dra min by tot groter akkuraatheid van die meting. 'n Sterk verband bestaan tussen bo-gemiddelde markopbrengste, aankondigings oor die besteding van vrye kontantvloei en die Tobin q-waarde van die firma. Firmas met 'n hoë Tobin q-waarde moet verseker dat goeie investeringsgeleenthede aangegryp word. Die gebruik van interne fondse om nuwe investering te finansier word deur die mark in 'n positiewe lig beskou en bogemiddelde opbrengste word gelewer. Firmas met 'n hoë Tobin q-waarde en hoë vrye kontantvloei toon laer opbrengste. Hierdie laer opbrengste is as gevolg van die mark wat besef dat die firma nalaat om gunstige interne investeringsgeleenthede te gebruik.

A history of statistical economic indicators in America, this dissertation uncovers the protracted struggle which took place in the nineteenth century over how economic life should be quantified, how social progress should be valued and how American prosperity should be measured. By revealing the historical origins of contemporary indicators such as Gross Domestic Product, and by uncovering the alternative measures that ended up on the losing side of history, this work denaturalizes the seemingly objective nature of modern economic indicators while offering a fresh take on the rise of American capitalism.

Pagrindinis šio bakalaurinio darbo tikslas – išsiaiškinti kaip ekonominės situacijos pokyčiai šalyje turi įtakos įmonių bankrotų skaičiaus svyravimams. Darbo uždaviniai: išsiaiškinti kokia yra įmonių bankroto situacija Lietuvoje, nustatyti kokie ekonominiai rodikliai turi didžiausią įtaką įmonių bankroto skaičiaus svyravimui, suskaičiuoti kokią įtaką įmonių bankrotui turi reikšmingiausi ekonominiai rodikliai, pateikti pastabas, rekomendacijas ir pasiūlymus problemai spręsti. Atliekant tyrimą buvo naudojami du metodai: horizontalios analizės metodas ir tiesinės regresijos metodas. Analizuojant lyginami ekonominiai rodikliai laiko perspektyvoje. Regresinės analizės metu įvertinama, kurie ir kaip ekonominiai rodikliai labiausiai turi įtakos įmonių bankroto skaičiaus svyravimams. Atlikus tyrimą nustatyta, kad reikšmingiausi laikotarpiai Lietuvai tiriamuoju laikotarpiu yra 1999 metų pabaiga (kritimas dėl Rusijos federacijos krizės), 2002-2008 metai (kilimas, dėl stipriai augančios ekonomikos, įstojimo į ES), 2008 metų antras pusmetis (kritimas, dėl pasaulinės finansų krizės). Regresinės analizės metu nustatyta, kad reikšmingiausi ekonominiai rodikliai yra: įmonių pelningumas, mokumo koeficientas, vartotojų kainų indeksas, bankrutavusių įmonių turtas bankroto paskelbimo dieną, vidutinė mėnesinė alga, įsiskolinimo koeficientas, tiesioginiai mokesčiai. Didžiausią įtaką įmonių bankrotui turi vidutinės mėnesinės algos padidėjimas, o mažėjimui – įsiskolinimo koeficiento padidėjimas. / The main purpose of this thesis is to explore how changes in economic situation influence corporate bankruptcies in Lithuania. The thesis objectives are: to find out the situation of corporate bankruptcies, identify which economic indicators have a major impact on corporate bankruptcies, calculate the impact that the most meaningful economic indicators have on corporate bankruptcies. Propose notes, recommendations, and suggestions. These two methods have been used for the analysis: horizontal comparable analysis and linear regression model. Economic indicators from different time periods were compared during comparable analysis. Linear regression provided information which main economic indicators had a major impact on corporate bankruptcies and how those indicators influence corporate bankruptcies. The analysis showed that major fluctuations in Lithuanian economy were recorded in the year of 1999 (Russion crisis), year of 2002-2008 (major rise in the economy, the EU), second half of 2008 (world financial crisis). Linear regression analysis revealed that corporate profitability, solvency credit, CPI, assets of bankrupt corporates on the day they were bankrupt, average monthly salary, debt credit and direct taxes have major impact on corporate bankruptcies. The biggest influence to rising corporate bancktupcy is made by changes in average monthly salary and solvency credit.

This study tests the relationship between certain economic scenarios and the state of the economy in regard to inflation and recession. Using data gathered from government publications, the economy was divided into periods of inflation, recession, and recession recovery. These periods were regressed against variables representing four schools of economic thought: monetarist scenario, structural scenario, power scenario, and micro, or supply side scenario. This study concludes that because of the complex nature of the economy, all representative variables have both positive and negative effects on the economy and no one scenario holds the key to economic stability.

The focus of this thesis is to seek and observe the patterns of economic development around local public schools of varying quality. The Greater Richmond Region (consisting of the City of Richmond and the counties of Chesterfield, Hanover and Henrico) were used as the basis of the study. The scores for the schools were derived from an equation that took into account some of the main quality aspects. The factors that went into the equation were graduation rates, dropout rates, standardized test scores and AP (Advance Placement) enrollment. The basis of the economic development evaluation is based on a set of indicators published by the King County (Washington) Department of Planning. These indicators include real wages per worker, poverty rate and high school graduation rate. Using GIS, these two data sets were observed for patterns and trends. The findings of this study show that not only do the economic development indicators change based on quality but also on geographic location. This study ends with recommendations for cities to improve both their education systems as well as their economic development opportunities.

M.Comm. / This study uses annual data for five SACU members over the period 1991-2005 to investigate the evidence for convergence in macroeconomic variables. Panel unit root test as an econometric tool is utilised together with other several approaches for this analysis. The results show significant evidence that the SACU countries have reached a reasonable level of convergence on specific macroeconomic variables. This can be attributed to common economic policies and institutional features. It is also evident that the countries that are members of the CMA show a dramatically higher convergence rate. As far as monetary policy is concerned, a high degree of convergence has been achieved in SACU. However, the results show no convergence on fiscal policies. This could be attributed to data constraint on debt to GDP which was used as a proxy for fiscal policy.

M.Comm. / The aim of this study is to discuss, analyse and forecast market volatility. Financial liberalisation and technological innovation have taken place during the past twenty-five years, producing a highly integrated and competitive world financial system in which trillions of dollars are traded every day (Murray, van Norden & Vigfusson, 1996:1). These developments have been positive, but there are concerns about the problems that such unregulated capital flows might pose for the efficient pricing of financial assets and the stability of domestic and international financial markets. Speculation has increased and greater competition, information technology and new securities lead to excessive price volatility. Stocks, bonds and foreign exchange are more sensitive to sudden shocks and trade at prices that appear inconsistent with market fundamentals. It is important to point out the causes of market volatility in order to determine if any precautions can be taken to prevent the enormous impact of market volatility on economic performance. The study could be useful for investors and dealers. It might enable them to forecast volatility and use it as a risk management instrument.

Nos tempos atuais, cada vez mais tem se discutido sobre a importância da Economia Criativa para países e regiões. De fato, praticamente toda atividade humana utiliza-se em alguma medida da criatividade, por isso, existe um movimento nos últimos anos para reconhecer em determinadas atividades conteúdo intelectual, cultural e artístico que agregam valor a bens e serviços. A partir dos anos 2000 surgiram diversas metodologias cujo objetivo era mensurar a Economia Criativa, isso despertou grande interesse dos governos locais e nacionais, pois isso poderia ser usado para direcionar esforços e investimentos públicos com a finalidade de alavancar o desenvolvimento econômico local. Dentre as metodologias lançadas, uma das primeiras, o Índice das Cidades Criativas desenvolvido por Richard Florida gerou grande repercussão na comunidade acadêmica e civil com a utilização de diversos indicadores divididos em três dimensões, Talento, Tecnologia e Tolerância (os 3 Ts). Diversas outras metodologias desenvolvidas posteriormente com o objetivo de mensurar a Economia Criativa foram fortemente influenciadas pela estrutura dos 3 Ts. Contudo, existe uma grande dificuldade para replicar qualquer uma dessas metodologias para as cidades brasileiras, em razão de diversos motivos, dentre eles a inexistência de dados públicos referentes aos indicadores utilizados. Com o objetivo de equacionar essa dificuldade, esse trabalho se propôs a identificar, a partir de quarto indicadores internacionais pré-selecionados, quais os dados que serão utilizados e compará-los aos existentes no Brasil, através da proposta de um índice chamado de Índice da Economia Criativa Brasileiro (IECBr). Após essa análise, foram escolhidas sete cidades (São Paulo, Rio de Janeiro, Curitiba, Brasília, Salvador, Fortaleza e Belém) para medir a Economia Criativa dessas regiões. Após o cálculo do IECBr foram utilizadas duas ferramentas estatísticas, o Coeficiente de Correlação de Pearson e a Análise de Clusters. A primeira ferramenta mostrou que existiam alguns indicadores contrários aos demais indicadores da mesma dimensão, por isso, optou-se por calcular novamente o índice sem esses indicadores. Por fim, foi utilizada a segunda ferramenta estatística para mostrar que as cidades escolhidas formariam dois grupos distintos, um grupo contendo as cidades do Sul e Sudeste do país e outro contendo as cidades das outras regiões. / In current times, the discussion around the importance of the creative economy for countries and regions has become notarial high. In fact, virtually all human activity has been used the creativity in some way, so there has been a movement in recent years to recognize certain activities in intellectual, cultural and artistic content that can add value to goods and services. Beginning in the 2000s, several methodologies emerged with the objective of measuring the Creative Economy, bolstered by high levels of interest on the part of local and national governments that are saw an opportunity to use direct efforts and public investments in order to boost local economic development. One of the first methods launched, the Index of Creative Cities, developed by Richard Florida, has generated significant repercussions in both the of academic community and civil society with the use of different indicators divided into three dimensions: Talent, Technology and Tolerance (the 3 T\'s). Several subsequent methodologies, with a similar goal of measuring the Creative Economy, were strongly influenced by the structure of the 3 T\'s. However, great difficulties are encountered when attempting to apply any of these methodologies to Brazilian cities, due to several reasons, most notably the lack of public data relevant to the indicators used. To mitigate this issue, this project aimed to identify, based on four international indexes previously selected, which data could be used to compare against the ones existing in Brazil, by proposing an index called the Brazilian Creative Economy Index (IECBr). After this analysis, we selected seven cities (São Paulo, Rio de Janeiro, Curitiba, Brasilia, Salvador, Fortaleza and Belem) to measure the Creative Economy. Two statistical tools were used, the Pearson correlation coefficient and Cluster Analysis. The first tool revealed that there were some indicators contradicted other indicators of the same dimension, so it was decided to recalculate the index without these indicators. Lastly, the second statistical tool showed that the chosen cities formed two distinct groups, one group consisting of Southern and Southeastern cities and the other consisting of all other regions.