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Mundellův - Flemingův model. Aplikace na ekonomiku ČR. / Mundell-Fleming model. Application to the Czech economy.Bouda, Milan January 2010 (has links)
Interpretation of Mundell-Fleming (M-F) model is very similar to IS -- LM model. The main difference is that M-F model is based on an assumption of small open economy. This openness is making this model more realistic then IS -- LM model. These assumptions are suitable for Czech economy. In this thesis, model is estimated and interpreted. The most important is an application to Czech economy concerning the period 2002 - 2010. There are ex post and ex ante predictions based on the estimated reduced form of the model. The ex post forecast is used for the purpose of evaluating whether the model is suitable for the prediction. After finding relevant suitability, prediction of endogenous variables is performed in the following four seasons.
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進口自由化對臺灣石化業市場結構與績效之影響 / The Free-Import Effect on Market Structure and Performance in Taiwan Petrochemical Industry王淑卿, Wang, Chu Ching Unknown Date (has links)
在國人的期待下,臺塑企業董事長王永慶終於於三月二十九日正式宣布,
六輕即將全面動工。延宕多年、總投資額高達二千餘億元的六輕案,從計
畫核准到建廠地點到宣布動工歷經波折,由於所牽涉的層面極廣,舉凡經
濟成長、國民所得和環境保護等等。 因此也使得有 " 火車頭工業 "之稱
的石化業成為眾所矚目的焦點。臺灣早期由於工業基礎薄弱,政府為扶植
國內產業,因此制定了高關稅及非關稅貿易措施管制進口,再加上出口導
向策略,使得臺灣自民國六十年起貿易順差逐漸擴大, 至民國七十五年
更高達 156 億美元,約佔國民生產毛額百分之二十左右,不但因此引起
貿易對手國的不滿,同時也對國內經濟發展造成不利的影響,再加上美國
貿易保護主義的壓力,我國於是逐漸調整對外貿易政策,降低關稅,開放
國內市場。因此政府於民國七十三年明白宣示貿易自由化政策,而民國七
十五年初也降低石化原料進口關稅,全面開放石化原料進口,但吾人發現
石化原料開放進口後,不僅產品的進口比增加,廠商的平均家數也增加,
但產品利潤率減少,進口自由化究竟對臺灣石化業的市場結構與績效造成
了何等影響,實有深入研究之必要。本文採用一個以廠商家數與產品利潤
率為主的兩條聯立方程式模型,藉由代表外國貿易變數的進口比係數之估
計與分析,來探討進口自由化對臺灣石化業的市場結構與績效之影響。本
文除了於第二章略述臺灣石化業之特性外,也將於第三章文獻回顧中將有
關國際貿易對國內市場結構與績效之影響的相關概念與實證結果做簡單介
紹。第四章透過理論架構推導,建立兩條方程式的聯立方程式模型以探討
進口自由化對廠商家數與產品利潤率的影響效果;第五章則為實證模型的
建立與結果分析;第六章為結論,總結全文之分析結果。
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The Relationships between Business Environment, Strategy, and Performance: An Identification of Opportunities and ThreatsWang, Tzu-wei 14 January 2009 (has links)
In recent years, corporate strategy has drawn a lot of attention in the academic an practice. However, there are fewer literatures on how to put these ideas into practice, that is, how to quantify the interrelationships between the three key elements in strategic management¡Ðperformance, strategies, and environments, and how to judge and measure the opportunities and threats (O & T) when the environments change. This study is an attempt to answer these questions.
The theoretical method developed incorporates a dynamic simultaneous equations model to express the interrelationship between these three elements. The method requires the identification of O & T in a three-step procedure. Step 1 relates the strategic components to the performance measures by the management¡¦s concept of business and philosophy of resource depolyment. Step 2 points out the suitable (unsuitable) environment circumstances for each of the scope and resource deployment elements. In Step 3, we link the results of Step 1 and Step 2 to identify and measure O & T.
The above methodology is applied to the case of Cathy Financial Holding Company, a Taiwan largest listed financial holding company, over the period 2002Q2-2007Q3. We use the Instrument Variables Three Stage Least Square Method (IV-3SLS) to estimate them. In addition, we also use some tests to ascertain the validity of the selected instrument variables in order to obtain the more reliable results. Our empirical results indicate that both the firm strategies and the environments play significant roles in influencing the firm¡¦s performance. More specifically, whereas the diversification of products, and the debt allowance reservation rate are negatively associated with the cost/income ratio and positively associated with adjusted ROE and Tobin¡¦s Q. Additionally, the managers also can increase the investment efficiency by adjusting the content of the asset allocation, especially with regard to the holding of bonds. We also extract some major environment factors such as unemployment rate that affect the firm¡¦s performance and use the estimated results to identify and measure O & T.
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The Impact of Electoral Cycles on Monetary Policies in Advanced and Developing EconomiesLupusor, Adrian January 2012 (has links)
The thesis provides a comparative estimation of the electoral cycles' influence on the monetary policies among a group of developed and developing countries. We use a non-linear central bank's reaction function which captures the regime switching behavior of the monetary authority depending on the proximity of elections. Moreover, we compare the reaction function with partial adjustment, which controls for policy inertia, with a non-inertial policy rule with serially correlated errors which takes into account other shocks determining the central bank to deviate from its policy rule. The estimation was performed via OLS, 2SLS and 3SLS, the preference being given to the last one due to correction of endogeneity problem and efficiency gains. Robust evidence about election induced monetary policies was found in 2 out of 10 developed economies and 4 out of 10 developing economies. In these countries, the central banks tend to be less inflation averse and/or less counter-cyclical (or even pro- cyclical) during electoral periods in comparison with normal times. Additionally, we find that the legislative framework, in these countries, incorporates significant deviations from the best practices of central bank independence. Finally, following the dynamic inconsistency problem, we document a strong...
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Estimation of the Impact of Single Airport and Multi-Airport System Delay on the National Airspace System using Multivariate Simultaneous ModelsNayak, Nagesh 01 January 2012 (has links)
Airline delays lead to a tremendous loss of time and resources and cost billions of dollars every year in the United States (U.S.). At certain times, individual airports become bottlenecks within the National Airspace System (NAS). To explore solutions for reducing the delay, it is essential to understand factors causing flight delay and its impact on airports in the NAS. Major causal factors of flight delay at airports include over-scheduling, en-route convective weather, reduced ceiling and visibility around airports, and upstream delay propagation. Delay at one airport can be passed on to other airports in the NAS, in another word, operational improvement at one airport will have network effect and benefit to other airports as well. Moreover delay at different airports in a region might agglomerate to cause delay at different regions in the NAS. Hence, to optimally allocate NAS resources, e.g. capital investment for airport capacity expansion, the impact of single airport delay to the NAS and vice versa need to be investigated and quantified.
For air transportation planning and policy purposes, this study concentrates on providing answers from a macroscopic point of view without being distracted by volatile operational details. In the first part, we estimate the interaction between flight delay at one single airport and delay at the rest of the NAS (RNAS) using case study for LaGuardia (LGA) and Chicago O'Hare (ORD) airports. In the second part, this research applies multivariate simultaneous regression models to quantify airport delay spillover effects across 34 of the 35 Operational Evolution Plan (OEP) airports and the RNAS. Observing the interactions between these two models, they are regressed with an econometric technique; three stage least square (3SLS). Thus, the regression results help us to determine the delay interactions between different airports and the RNAS and compare these airports based on delay propagation characteristics. Another significant contribution of this research is that, the estimated coefficients can be used for determining the marginal effects of all the delay causal factors presented in the model.
Also, regional airport system development has been a hot topic of research in the air transportation community in recent years. Many metropolitan regions are served with more than one airport making their operations synchronized and interdependent and are known as regional airport system. This paper studies nine different prospective regions with multi-airport systems in the U.S. and identifies various key factors affecting the delay in these regions. Econometrics models and three stage least square (3SLS) estimation method are used to explore interdependency of delay at the multi-airport system and the RNAS. Along with it, different factors affecting delay at the system and the RNAS is being identified from the research. The outcomes from this research will help aviation planners understand the spillover effects of delays from multi-airport systems and provide decision support for future NAS improvement.
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1987~2007年東亞國際旅遊競爭力研究 / A Study of International Tourism Competitiveness of East Asian Economies of 1987~2007陳勇安, Chen,yong an Unknown Date (has links)
本文目的為探討影響東亞九個經濟體(台灣、香港、韓國、中國、及東南亞國協五國─印尼、馬來西亞、菲律賓、新加坡、泰國)在國際旅遊觀光市場之相對競爭力的因素及利用國際旅遊觀光統計資料,透過三階段最小平方法(3SLS)及迴歸分析,分別針對東亞九個經濟體,探究相對價格、匯率及供給面變數,對其主要來源國家觀光客─美國、日本做實證分析。實證結果發現:(1) 如果旅遊目的為商務或探親,或者是以觀光團型態旅遊,則國際觀光客對於相對價格變動並不敏感。(2) 如果大部分在目的地國家的旅遊支出是以來源國家貨幣計價,則國際觀光客對於匯率變動並不敏感。(3) 供給面因素的確對經濟體之國際旅遊觀光市場佔有率具有決定性影響,然而其影響視來源國與各目的地國家之相關性而定。
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Modelling vehicle emissions from an urban air-quality perspective:testing vehicle emissions interdependenciesDabbas, Wafa M January 2010 (has links)
Doctor of Philosophy(PhD) / Abstract This thesis employs a statistical regression method to estimate models for testing the hypothesis of the thesis of vehicle emissions interdependencies. The thesis at the beginnings, reviews critically the formation of emissions in gasoline-fuelled engines, and also reviews existing and emerging models of automotive emissions. The thesis then, presents the relationships between the urban transport system and vehicle emissions. Particularly, it summarises different types of emissions and the contributory factors of the urban transport system to such emissions. Subsequently, the thesis presents the theory of vehicle emissions interdependencies and the empirical framework for testing the hypothesis of the thesis. The scope of testing the hypothesis of the thesis is only limited to gasoline-fuelled conventional vehicles in the urban transport environment. We use already available laboratory-based testing dataset of 542 passenger vehicles, to investigate the hypothesis of the thesis of vehicle emissions interdependencies. HC, CO, and NOX emissions were collected under six test drive-cycles, for each vehicle before and after vehicles were tuned. Prior to using any application, we transform the raw dataset into actionable information. We use three steps, namely conversion, cleaning, and screening, to process the data. We use classification and regression trees (CART) to narrow down the input number of variables in the models formulated for investigating the hypothesis of the thesis. We then, utilise initial results of the analysis to fix any remaining problems in the data. We employ three stage least squares (3SLS) regression to test the hypothesis of the thesis, and to estimate the maximum likelihood of vehicle variables and other emissions to influence HC, CO, and NOX emissions simultaneously. We estimate twelve models, each of which consists of a system of three simulations equations that accounts for the endogenous relations between HC, CO and NOX emissions when estimating vehicle emissions simultaneously under each test drive-cycle. The major contribution of the thesis is to investigate the inter-correlations between vehicle emissions within a well controlled data set, and to test the hypothesis of vehicle emissions interdependencies. We find that HC, CO, and NOX are endogenously or jointly dependent in a system of simultaneous-equations. The results of the analysis demonstrate that there is strong evidence against the null hypothesis (H0) in favour of the alternative hypothesis (H1) that HC, CO, and NOX are statistically significantly interdependent. We find, for the thesis sample, that NOX and CO are negatively related, whereas HC and CO emissions are positively related, and HC and NOX are positively related. The results of the thesis yield new insights. They bridge a very important gap in the current knowledge on vehicle emissions. They advance not only our current knowledge that HC, CO, and NOX should be predicted jointly since they are produced jointly, but also acknowledge the appropriateness of using 3SLS regression for estimating vehicle emissions simultaneously. The thesis measures the responses of emissions to changes with respect to changes in the other emissions. We investigate emission responses to a one percent increase in an emission with respect to the other emissions. We find the relationship between CO and NOX is of special interest. After vehicles were tuned, we find those vehicles that exhibit a one percent increase in NOX exhibit simultaneously a 0.35 percent average decrease in CO. Similarly, we find that vehicles which exhibit a one percent increase in CO exhibit simultaneously a 0.22 percent average decrease in NOX. We find that the responses of emission to changes with respect to other emissions vary with various test drive-cycles. Nonetheless, a band of upper and lower limits contains these variations. After vehicle tuning, a one percent increase in HC is associated with an increase in NOX between 0.5 percent and 0.8 percent, and an increase in CO between 0.5 percent and one percent Also, for post-tuning vehicles, a one percent increase in CO is associated with an increase in HC between 0.4 percent and 0.9 percent, and a decrease in NOX between 0.07 percent and 0.32 percent. Moreover, a one percent increase in NOX is associated with increase in HC between 0.8 percent and 1.3 percent, and a decrease in CO between 0.02 percent and 0.7 percent. These measures of the responses are very important derivatives of the hypothesis investigated in the thesis. They estimate the impacts of traffic management schemes and vehicle operations that target reducing one emission, on the other non-targeted emissions. However, we must be cautious in extending the results of the thesis to the modern vehicles fleet. The modern fleet differs significantly in technology from the dataset that we use in this thesis. The dataset consists of measurements of HC, CO, and NOX emissions for 542 gasoline-fuelled passenger vehicles, under six test drive-cycles, before and after the vehicles were tuned. Nevertheless, the dataset has a number of limitations such as limited model year range, limited representations of modal operations, and limitations of the measurements of emissions based only on averages of test drive-cycles, in addition to the exclusion of high-emitter emission measurements from the dataset. The dataset has a limited model year range, i.e., between 1980 and 1991. We highlight the age of the dataset, and acknowledge that the present vehicle fleet varies technologically from the vehicles in the dataset used in this thesis. Furthermore, the dataset has a limited number of makes - Holden, Ford, Toyota, Nissan, and Mitsubishi. There are also a limited number of modal operations. The model operations presented in the dataset are cold start, warming-up, and hot stabilised driving conditions. However, enrichment episodes are not adequately presented in the test-drive cycles of the dataset. Moreover, the dataset does not take into account driving behaviour influences, and all measurements are cycle-based averages. The emission measurements of laboratory-based testings are aggregated over a test drive cycle, and the test drive-cycle represents an average trip over an average speed. The exclusion of the measurements of high emitting vehicles from the dataset introduces further limitations. Remote sensing studies show that 20 percent of the on-road vehicle fleet is responsible for 80 percent of HC and CO emissions. The findings of the thesis assist in the identification of the best strategies to mitigate the most adverse effects of air-pollution, such as the most severe pollution that have the most undesirable pollution effects. Also, they provide decision-makers with valuable information on how changes in the operation of the transport system influence the urban air-quality. Moreover, the thesis provides information on how vehicle emissions affect the chemistry of the atmosphere and degrade the urban air-quality.
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Modelling vehicle emissions from an urban air-quality perspective:testing vehicle emissions interdependenciesDabbas, Wafa M January 2010 (has links)
Doctor of Philosophy(PhD) / Abstract This thesis employs a statistical regression method to estimate models for testing the hypothesis of the thesis of vehicle emissions interdependencies. The thesis at the beginnings, reviews critically the formation of emissions in gasoline-fuelled engines, and also reviews existing and emerging models of automotive emissions. The thesis then, presents the relationships between the urban transport system and vehicle emissions. Particularly, it summarises different types of emissions and the contributory factors of the urban transport system to such emissions. Subsequently, the thesis presents the theory of vehicle emissions interdependencies and the empirical framework for testing the hypothesis of the thesis. The scope of testing the hypothesis of the thesis is only limited to gasoline-fuelled conventional vehicles in the urban transport environment. We use already available laboratory-based testing dataset of 542 passenger vehicles, to investigate the hypothesis of the thesis of vehicle emissions interdependencies. HC, CO, and NOX emissions were collected under six test drive-cycles, for each vehicle before and after vehicles were tuned. Prior to using any application, we transform the raw dataset into actionable information. We use three steps, namely conversion, cleaning, and screening, to process the data. We use classification and regression trees (CART) to narrow down the input number of variables in the models formulated for investigating the hypothesis of the thesis. We then, utilise initial results of the analysis to fix any remaining problems in the data. We employ three stage least squares (3SLS) regression to test the hypothesis of the thesis, and to estimate the maximum likelihood of vehicle variables and other emissions to influence HC, CO, and NOX emissions simultaneously. We estimate twelve models, each of which consists of a system of three simulations equations that accounts for the endogenous relations between HC, CO and NOX emissions when estimating vehicle emissions simultaneously under each test drive-cycle. The major contribution of the thesis is to investigate the inter-correlations between vehicle emissions within a well controlled data set, and to test the hypothesis of vehicle emissions interdependencies. We find that HC, CO, and NOX are endogenously or jointly dependent in a system of simultaneous-equations. The results of the analysis demonstrate that there is strong evidence against the null hypothesis (H0) in favour of the alternative hypothesis (H1) that HC, CO, and NOX are statistically significantly interdependent. We find, for the thesis sample, that NOX and CO are negatively related, whereas HC and CO emissions are positively related, and HC and NOX are positively related. The results of the thesis yield new insights. They bridge a very important gap in the current knowledge on vehicle emissions. They advance not only our current knowledge that HC, CO, and NOX should be predicted jointly since they are produced jointly, but also acknowledge the appropriateness of using 3SLS regression for estimating vehicle emissions simultaneously. The thesis measures the responses of emissions to changes with respect to changes in the other emissions. We investigate emission responses to a one percent increase in an emission with respect to the other emissions. We find the relationship between CO and NOX is of special interest. After vehicles were tuned, we find those vehicles that exhibit a one percent increase in NOX exhibit simultaneously a 0.35 percent average decrease in CO. Similarly, we find that vehicles which exhibit a one percent increase in CO exhibit simultaneously a 0.22 percent average decrease in NOX. We find that the responses of emission to changes with respect to other emissions vary with various test drive-cycles. Nonetheless, a band of upper and lower limits contains these variations. After vehicle tuning, a one percent increase in HC is associated with an increase in NOX between 0.5 percent and 0.8 percent, and an increase in CO between 0.5 percent and one percent Also, for post-tuning vehicles, a one percent increase in CO is associated with an increase in HC between 0.4 percent and 0.9 percent, and a decrease in NOX between 0.07 percent and 0.32 percent. Moreover, a one percent increase in NOX is associated with increase in HC between 0.8 percent and 1.3 percent, and a decrease in CO between 0.02 percent and 0.7 percent. These measures of the responses are very important derivatives of the hypothesis investigated in the thesis. They estimate the impacts of traffic management schemes and vehicle operations that target reducing one emission, on the other non-targeted emissions. However, we must be cautious in extending the results of the thesis to the modern vehicles fleet. The modern fleet differs significantly in technology from the dataset that we use in this thesis. The dataset consists of measurements of HC, CO, and NOX emissions for 542 gasoline-fuelled passenger vehicles, under six test drive-cycles, before and after the vehicles were tuned. Nevertheless, the dataset has a number of limitations such as limited model year range, limited representations of modal operations, and limitations of the measurements of emissions based only on averages of test drive-cycles, in addition to the exclusion of high-emitter emission measurements from the dataset. The dataset has a limited model year range, i.e., between 1980 and 1991. We highlight the age of the dataset, and acknowledge that the present vehicle fleet varies technologically from the vehicles in the dataset used in this thesis. Furthermore, the dataset has a limited number of makes - Holden, Ford, Toyota, Nissan, and Mitsubishi. There are also a limited number of modal operations. The model operations presented in the dataset are cold start, warming-up, and hot stabilised driving conditions. However, enrichment episodes are not adequately presented in the test-drive cycles of the dataset. Moreover, the dataset does not take into account driving behaviour influences, and all measurements are cycle-based averages. The emission measurements of laboratory-based testings are aggregated over a test drive cycle, and the test drive-cycle represents an average trip over an average speed. The exclusion of the measurements of high emitting vehicles from the dataset introduces further limitations. Remote sensing studies show that 20 percent of the on-road vehicle fleet is responsible for 80 percent of HC and CO emissions. The findings of the thesis assist in the identification of the best strategies to mitigate the most adverse effects of air-pollution, such as the most severe pollution that have the most undesirable pollution effects. Also, they provide decision-makers with valuable information on how changes in the operation of the transport system influence the urban air-quality. Moreover, the thesis provides information on how vehicle emissions affect the chemistry of the atmosphere and degrade the urban air-quality.
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Statistical properties of the liquidity and its influence on the volatility prediction / Statistical properties of the liquidity and its influence on the volatility predictionBrandejs, David January 2016 (has links)
This master thesis concentrates on the influence of liquidity measures on the prediction of volatility and given the magic triangle phenomena subsequently on the expected return. Liquidity measures Amihud Illiquidity, Amivest Liquidity and Roll adjusted for high frequency data have been utilized. Dataset used for the modeling was consisting of 98 shares that were traded on S&P 100. The time range was from 1st January 2013 to 31st December 2014. We have found out that the liquidity truly enters into the return-volatility relationship and influences these variables - the magic triangle interacts. However, contrary to our hypothesis, the model shows up that lower liquidity signifies lower realized risk. This inference has been suggested by all three models (3SLS, 2SLS and OLS). Furthermore, we have used the realized variance and bi-power variation to separate the jump. Our second hypothesis that lower liquidity signifies higher frequency of jumps was confirmed only for one of two liquidity proxies (Roll) included in the resulting logit FE model. Keywords liquidity, risk, volatility, expected return, magic triangle, price jumps, realized variance, bi-power variation, three-stage least squares model, logit, high-frequency data, S&P 100 Author's e-mail david.brandejs@seznam.cz Supervisor's e-mail...
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台商赴海外投資對國內薪資的影響之探討-以製造業為例林芳儀 Unknown Date (has links)
1980-2004年,台灣製造業勞動薪資隨時間持續增加,但是技術與非技術勞動之相對薪資卻大致呈現下滑趨勢。根據過去文獻,影響技術與非技術勞動相對薪資的原因有很多,諸如貿易、對外投資等國際分工方法。本研究主要分析對外投資影響台灣技術與非技術勞動薪資變動的情形,至於貿易等其他因素造成之影響,本文將不進行討論。
我們先從廠商利潤極大化之角度出發,推導出本研究所需之薪資決定方程式後,利用1980-2004年間,台灣製造業之整合資料,以三階段最小平方法,同時對技術及非技術勞動薪資方程式,進行迴歸分析。融合林祖嘉與黃啟宏(2006)之研究,得到下列結果:
1.整體製造業對外投資促進產業升級。廠商在既有的產出下,對外投資增加技術勞動需求,減少非技術勞動需求。同時,技術勞動供給增加,且幅度小於需求增加之幅度,使得技術勞動均衡雇用量及薪資皆上揚。非技術勞動之薪資也因需求減少而下降。
2.資本密集製造業在對外投資的過程中,僅增加了技術勞動的需求,並未減少非技術勞動的需求。相反的,台商赴海外投資非資本密集製造業,將減少其非技術勞動需求。顯示資本密集製造業勞動在對外投資中受益,非資本密集製造業勞動在對外投資中受害。
3.對個別勞動者而言,無論其為技術或非技術勞動,在資本密集製造業工作,都能使其免於承受台商對外投資,間接造成之薪資銳減。
如同我們的預期,技術勞動供給因教育普及而增加,技術勞動的均衡薪資可能隨之降低,但因為對外投資抵銷了技術勞動供給的影響,甚至使技術勞動薪資上升。另一方面,非技術勞動因對外投資,造成產業之需求銳減,使其薪資下降。因此製造業技術及非技術勞動的薪資差距,會因為對外投資金額增加而上升。
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