The main purpose of this study is to empirically assess the relationship between inflation and economic growth in Ethiopia using quarterly dataset from 1992Q1 to 2010Q4. In doing so, an interesting policy issue arises. What is the threshold level of inflation for the Ethiopian economy? Based on the Engle-Granger and Johansen co-integration tests it is found out that there is a positive long-run relationship between inflation and economic growth. The error correction models show that in cases of short-run disequilibrium, the inflation model adjusts itself to its long-run path correcting roughly 40% of the imbalance in each quarter. In addition, based on the conditional least square technique, the estimated threshold model suggests 10% as the optimal level of inflation that facilitates growth. An inflation level higher or lower than the threshold level of inflation affects the economic growth negatively and hence fiscal and monetary policy coordination is vital to keep inflation at the threshold. / Economics / M. Com. (Economics)

Parameter estimation techniques have been successfully and extensively applied to deterministic models based on ordinary differential equations but are in early development for stochastic models. In this thesis, we first investigate using parameter estimation techniques for a deterministic model to approximate parameters in a corresponding stochastic model. The basis behind this approach lies in the Kurtz limit theorem which implies that for large populations, the realizations of the stochastic model converge to the deterministic model. We show for two example models that this approach often fails to estimate parameters well when the population size is small. We then develop a new method, the MCR method, which is unique to stochastic models and provides significantly better estimates and smaller confidence intervals for parameter values. Initial analysis of the new MCR method indicates that this method might be a viable method for parameter estimation for continuous time Markov chain models.

介紹幾種具有良好性質的共積模型估計方法，這些方法因其估計目的不同，而採取相異的模型表示式、相異的估計準則。在論文的連貫性與完整性考量上，須從最簡單的單變數非恆定模型開始介紹整篇論文的基礎。考慮變數間的累積性質關聯，採取空間投影的方法，將共積向量空間、模型虛假迴歸性質、甚至非恆定模型的單根來源連結在一起。充份說明了共積模型裡變數彼此的關聯後，採用共積空間表示式來完備誤差修正表示式裡無法說明的變數相關性。兩種表示式相互配合後，可以建立不同估計方法一致的比較基礎。比較不同估計方法的同時，也系統的介紹幾種估計方法。其中Phillips的完全修正法是主要介紹的估計法，也是後續不同方法間的比較基礎。比較不同方法的異同，主要著重點在於不同方法的估計準則或是修正動機。比較後的結論，可以對照原來方法的估計步驟，唯有暸解不同角度看出的變數性質，才能更精確的掌握估計方法。

Closed-end funds’ (CEF) discount and discount fluctuations have been puzzling researchers for decades. Up to date, there are no multidimensional or cross-sectional variables that have been proved to influence CEFs simultaneously. Fact is that, earlier research and theories on the subject are contradictious and several suggestions on the origin of the CEF’s discount and its fluctuations have been proposed. To mention a few, investor sentiments, taxation issues, dividend policies, agency costs and agency problems are considered to influence these discounts. The purpose of this report is to examine the relationship between micro- and macroeconomic variables fluctuations, and how these can explain the discount fluctuation of the Swedish CEFs. This report focuses upon the CEFs traded at NASDAQ OMX Stockholm, which have been selected through a comprehensive multistage selection process. 10 CEFs were selected. Monthly data for calculating micro- and macroeconomic variables was collected for the period March 2003 – February 2013, which resulted in approximately 1 200 observations. OLS regression analysis, Fixed- and Random Effect Models and Hausman tests were conducted. The findings conclude that some of this report’s chosen micro- and macro variables influence on the Swedish CEFs’ discount fluctuation, although these findings are conditioned. The CEFs’ individual characteristics or traits result in a significant impact on the fluctuation of CEFs’ discount. Hence, only by controlling these characteristics, multidimensional or cross-sectional micro- and macroeconomic variables can be proved to affect the CEFs’ discount fluctuation.

民國94年7月1日開始施行的勞工退休金條例，是政府近年來對勞工退休規劃的重要施政政策，依據此條例規定，員工超過二百人以上的企業，多了企業年金保險的選項可供選擇。而依據第14條第三款規定，勞工得在其每月工資百分之六範圍內，自願另行提繳退休金。勞工自願提繳部份，得自當年度個人綜合所得稅總額中全數扣除。本研究開始之時適逢勞退新制實施之初，並無企業年金中個人相對提撥之實際資料，因此藉分析個人年金保險保戶之屬性及對年金保險消費型態之探討，推論企業年金中選擇自願提繳之個人因素，供各界參考。 本研究整理與回顧國內外相關之職業退休金制度，並探討OECD各國企業年金的運作方式，以及國內年金市場的結構與產品。在實証模型上，則利用線性迴歸模型（OLS），分析影響年金保險保額的原因，並利用間斷性機率模型Probit Model 探討影響傳統型年金保險或投資型年金保險的因素。 / The Labor Pension Act, one of the major policies for the labor retirement planning of the R.O.C. government, was officially put into practice on July 1st, 2005. Based on the regulation of the Act, companies with more than 200 employees will have the Annuity Insurance as alternatives. According to the Article 14 -3 of the Act, a worker may voluntarily contribute per month, up to 6% of his/her monthly wages to his/her pension fund account. The full amount of the voluntary pension contribution made by a worker may be deducted from the worker's taxable income in the year concerned. Therefore, this research intends to analysis between the attributions and consumption behaviors of the employees joining in the policy of the Annuity Insurance, and then generalizes the factors why the workers choose the voluntary pension contribution policy. In this research, I would compare the pension policies used in different countries, look into the ways that the OECD are running their Enterprise Annuity policies, and evaluate the various pension policies. By using the real diagnosis Model, I would use the OLS to analysis the influences over Annuity Insurance Insured value and then use the Probit Model to explore the influences over traditional Annuity Insurance and the Investment Annuity Insurance.

台灣經濟屬於淺碟型經濟，且受限於缺乏自然資源，所以資本的形成相當的不容易。為求經濟的發展，資本的形成，尤其是固定投資的累積相當的重要。而資本形成的數種財源中，以僑外直接投資對國際收支與通貨膨脹的壓力影響較小，並能引進新生產技術及經營管理知識，從而促進產業的持續成長與企業管理現代化理想的實現。台灣之所以能成為經濟上的亞洲四小龍之一，這當中經濟成長的背後資金來源，僑外商的直接投資是不可或缺的。近年來，台灣的名目利率不斷下跌，甚至實質利率為負的情況下，投資動能卻仍顯不足。為瞭解構成廠商投資意願的決定因素，故以對投資具相當敏感度的僑外商為研究的主要對象，所以本文的主要目的即是探討僑外直接投資台灣的決定因素。 本研究使用1995年至2004年間的時間數列月資料，以普通最小平方迴歸模型，估計僑外資、僑資、外資、製造業及服務業等五種模型的直接投資決定因素。結果顯示在僑外資及外資的模型中，其顯著變數有工資、利率、世界競爭力及政黨輪替。僑資模型的顯著因素有犯罪率及政黨輪替。製造業模型的顯著變數有工資、匯率及利率。而服務業模型則有工資、利率及研究發展經費為顯著變項。另各模型時間變數方面，僑外資、外資及服務業等模型的第6年虛擬變數具顯著效果。在月虛擬變數上，投資正相關的月份僑外資為6、7月及10至12月；僑資為7、8兩月；外資於5月後各月；製造業則為3月及5月後各月；服務業則為7、11及12月。又僑資及服務業兩模型中，4月均為負相關。至於經濟成長率、每人國內生產毛額及政黨比率等不顯著變項，表示均非僑外商投資所關注的因素。 / Taiwan’s saucer-shallow economic scale and scarce natural resources make capital formation very difficult. Nevertheless, capital formation, especially accumulation of fixed investment, is essential to economic development. Among various sources of capital formation, foreign direct investment imposes least pressure on the balance of payments and inflation, introduces innovative technology and management skills, and hence contributes most significantly to sustainable industrial development and the realization of business management ideals. Taiwan ranks among the four newly-industrialized Asian tigers. Among the funding sources that have promoted Taiwan’s economic growth over the years, direct investment from overseas Chinese and foreigners plays an indispensable part. In recent years, however, even though nominal interest rates have continuously fallen, at times even to the level of negative real interest rates, investment momentum still appeared weakened. Based on this observation, this study tries to understand what drives decisions to invest in Taiwan by focusing on overseas Chinese and foreign investors who are highly investment sensitive. The main purpose of the study is to discuss the determinants of overseas Chinese and foreign direct investment in Taiwan. This study applies the Ordinary Least Square (OLS) Regression model to analyze the monthly time-series data during the period of 1995-2004. Determinants of direct investment are examined in five groups, i.e. overseas Chinese & foreign investment, overseas Chinese investment, foreign investment, the manufacturing sector, and the services sector. The result shows that wages, interest rates, world competitiveness, and the rotation of ruling parties are the most important factors for overseas Chinese & foreign investment, and foreign investment. Overseas Chinese investment is significantly affected by the crime rate and the rotation of ruling parties. For the manufacturing sector, wages, exchange rates and interest rates are important variables. Wages, interest rates and R&D spending significantly affect investment in the services sector. In terms of the time variables in each group, the sixth year dummy variable has a significant effect on overseas Chinese & foreign investment, foreign investment, and the services sector. With regard to monthly dummy variables, positively correlated to investment are June, July, and October to December for overseas Chinese & foreign investment; July and August for overseas Chinese investment; May to December for foreign investment; March, and May to December for the manufacturing sector; and July, November, and December for the services sector. In addition, April shows a negative correlation for both overseas Chinese investment and the services sector. Variables with insignificant effects, including economic growth rates, per capita GDP, and the congressional seats of political parties, are not among the concerns of overseas Chinese and foreign investors.

Berry ripening in lowbush blueberry (Vaccinium angustifolium Ait.) is influenced by developmental, physiological and climatic factors resulting in a heterogenous mix of maturities at harvest. This study characterizes the physico-chemical changes which occur during fruit ontogeny and links ripening patterns to micoclimate. Individual clones in five commercial fiels were followed in the 2006 and 2007 growing seasons. Phenolic acids, flavonols, and flavan-3-ols decreased and anthocyanins increased with maturity. Peak maturity consistently occurred at 1200 accumulated growing degree days (GDD). There was a sharp decline in fruit retention at the end of the growing season suggesting a date after which harvested yield declines but no consistent pattern was detected between years or fields.The consistency of GDD accumulation in relation to ripening pattern suggests GDDs can be used as a predictive ripening index. The physico-chemical nature of ripe berries indicates ripe berries could be harvested earlier than is currently the practice.

Balance between energy consumption and production of electricityis a very important for the electric power system operation and planning. Itprovides a good principle of effective operation, reduces the generation costin a power system and saves money. Two novel approaches to reduce thetotal errors between forecast and real electricity consumption wereproposed. An Adaptive Linear Regression of Original Predictions (ALROP)was constructed to modify the existing predictions by using simple linearregression with estimation by the Ordinary Least Square (OLS) method.The Weighted Least Square (WLS) method was also used as an alternativeto OLS. The Modeling of Prediction Errors (MPE) was constructed in orderto predict errors for the existing predictions by using the Autoregression(AR) and the Autoregressive-Moving-Average (ARMA) models. For thefirst approach it is observed that the last reported value is of mainimportance. An attempt was made to improve the performance and to getbetter parameter estimates. The separation of concerns and the combinationof concerns were suggested in order to extend the constructed approachesand raise the efficacy of them. Both methods were tested on data for thefourth region of Sweden (“elområde 4”) provided by Bixia. The obtainedresults indicate that all suggested approaches reduce the total percentageerrors of prediction consumption approximately by one half. Resultsindicate that use of the ARMA model slightly better reduces the total errorsthan the other suggested approaches. The most effective way to reduce thetotal consumption prediction errors seems to be obtained by reducing thetotal errors for each subregion.

Submitted by Levi Santos (levis@ufba.br) on 2018-01-30T21:19:42Z No. of bitstreams: 1 Tese Levi PPGCI-UFBA 05.12.2017.pdf: 3296241 bytes, checksum: c7064236d23f11486d498f569f5185f1 (MD5) / Approved for entry into archive by Urania Araujo (urania@ufba.br) on 2018-02-19T20:06:50Z (GMT) No. of bitstreams: 1 Tese Levi PPGCI-UFBA 05.12.2017.pdf: 3296241 bytes, checksum: c7064236d23f11486d498f569f5185f1 (MD5) / Made available in DSpace on 2018-02-19T20:06:50Z (GMT). No. of bitstreams: 1 Tese Levi PPGCI-UFBA 05.12.2017.pdf: 3296241 bytes, checksum: c7064236d23f11486d498f569f5185f1 (MD5) / Analisa a produção científica brasileira (artigos nacionais, artigos internacionais, anais de eventos e livros) através dos Mínimos Quadrados Ordinários (MQO). Para tanto, discorre sobre o percurso histórico e de aplicação das metrias que a Ciência da Informação (CI) vem construindo, desde a mais primordial de todas, a bibliometria, oriunda da biblioteconomia, passando pelas visões modernas como a cienciometria até a informetria. Explica como a econometria constrói o seu modelo de análise, que é utilizado para pesquisas na economia e, ao mesmo tempo, reflete como esse método pode ser trazido para as metrias da informação. Explica e expõe o método de estimação por MQO para a análise de regressão, que é a proposta desta tese. Pesquisa aplicada descritiva com abordagem quantitativa com procedimentos baseados no tipo de pesquisa estudo de caso do levantamento de dados a partir do Portal do Plano Tabular do CNPq do ano de 2010. Os critérios para delineamento da pesquisa foram aprofundados, na revisão de literatura, em referências tanto da área da CI quanto da bibliometria, estatística e econometria. Este estudo, metodologicamente, conta com a abordagem conceitual da bibliometria e da CI em busca de teorias aplicáveis aos estudos em MQO e a aplicação empírica do MQO se aproxima da concepção econométrica. A tese conclui que a utilização de técnicas de análises das funções de regressão construída por meio de MQO possibilita a criação de um modelo de previsão da produção científica brasileira. Esse modelo é construído a partir da correlação e determinação detectada entre o número de doutores e a produção científica destes em cada estado do Brasil. Com a aplicação de estratégias econométricas (índice de correlação, índice de determinação, forma funcional de curva de regressão e cálculo dos parâmetros da função por MQO), foi possível construir um modelo de previsão.

This thesis aims to examine whether it is possible to forecast which firmswill be shorted. To do this a regression was constructed using a sample of thecompanies currently included in S&P 500. Short interest as percentage offloat was set as the dependent variable with volatility, institutionalownership, past stock returns, growth in net sales and price-to-earnings ratio(P/E) as the independent variables. Our results concluded that all variablesexcept institutional ownership were statistically significant at a 5% level withthree of these being significant even at a 1% level. Based on these results, webelieve that it to a certain degree is possible to forecast which firms will beshorted.