Tax differentials and inflow of foreign direct investments : evidence from foreign operations of U.S. multinational companies

This paper concerns the measurement of the impact of tax differentials across countries on inflow of Foreign Direct Investment (FDI) by using comprehensive data on the foreign operations of U.S. multinational corporations that has been collected by the Bureau of Economic Analysis (BEA), the U.S. Department of Commerce. In particular, this research focuses on examining: (1) how responsive FDI locations are to tax differentials across countries, (2) how different the tax effect on FDI inflow is between developed and developing countries, and (3) whether investment location decisions have become more or less sensitive to tax differences between countries over time ranging from the late 1990s to the early 2000s. Estimation results suggest that high rates of corporate income taxation are associated with reduced foreign assets of U.S. multinational firms in all industries by decreasing the return to foreign asset investment. Further, foreign assets of U.S. multinationals in all industries have become more responsive to non-income tax differentials across countries than to income tax differences from 1999 to 2004. Empirical estimates also indicate that foreign investment by American firms is associated with higher tax sensitivity more in developed countries than in those that are developing.

Impact of foreign capital entry in the Indonesian banking sector

After the Asian financial crisis of 1997/98, the Indonesian banking sector experienced significant changes. Ownership structure of banking sector is substantially-changed. Currently, ownership of major commercial banks is dominated by foreign capital through acquisition. This paper examines whether foreign ownership changes a bank’s lending behavior and performance. Foreign banks tend to lend mainly to large firms; this paper examines whether the credit to small and medium-sized enterprises (SMEs) is affected by foreign capital entry into the Indonesian banking sector. Empirical results show that banks owned by foreign capital tend to decrease SME credit.

Regime survival strategies and the conduct of foreign policy in Egypt

エジプトではムバーラク大統領の国内政策と域内におけるエジプトの影響力低迷が引き金となって、2011年1月25日に抗議運動起こった。抗議運動はエジプト全土に拡がり、18日間の民衆的な反体制運動によってムバーラクは軍に見捨てられ、失脚に追い込まれた。この民衆蜂起によって警察は街頭から撤退し、シナイ半島の警察署は焼き放たれ、ムバーラクが率いていた国民民主党の建物や国内治安機関の本部は襲撃され、国家機関が数ヶ月にもわたって機能不全となり、ムバーラク体制の崩壊は国内的な混乱を招くこととなった。振り返れば、エジプトでの政治的大変動は社会的な革命へと展開することはできなかった。その理由は独裁体制からの移行を先導できる組織化された反体制勢力が存在しなかったためである。民衆による抗議運動は一時的に体制を転覆できても旧体制のエリートを分裂させることはできず、軍の影響下にある体制の復活を防ぐこともできなかった。2011年以降のエジプトは現在まで混乱状態に陥ったままであるが、1カ月に及ぶエジプト軍最高評議会(SCAF)の暫定統治、エジプト史上初の自由な大統領選挙によって選出された文民大統領のムルスィーによる一年余りの統治、そして2013年7月の軍事クーデターによって権力の座に就いたスィースィーの統治といった過程で、民衆蜂起がエジプトの外交関係に及ぼした影響はごく僅かであった。本稿は、現在のエジプトの外交政策が2011年の革命にほとんど影響を受けていないのはなぜか、またエジプトの統治者たちが政権の正統性、体制の強化および政治的な安定性を確保し、国内的な課題に対処するための戦略をいかに策定しているのかを説明することを試みる。本稿での主張は、ムバーラク以降のエジプトが体制の強化と保全のために外交政策を進めており、国内的な混乱によって地域内アクターへの依存度が高まっていることである。

Impacts of foreign exchange auctions on the informal market rate in Myanmar

Since the abolition of the official peg and the introduction of a managed float in April 2012, the Central Bank of Myanmar has operated the daily two–way auctions of foreign exchange aimed at smoothing exchange rate fluctuations. Despite the reforms to the foreign exchange regime, however, informal trading of foreign exchange remains pervasive. Using the daily informal exchange rate and Central Bank auction data, this study examines the impacts of auctions on the informal market rate. First, a VAR analysis indicates that the official rate did not Granger cause the informal rate. Second, GARCH models indicate that the auctions did not reduce the conditional variance of the informal rate returns. Overall, the auctions have only a quite modest impact on the informal exchange rate.

The impact of foreign firms on industrial productivity : evidence from Japan

With a newly constructed dataset on foreign firms in Japan for the period 1995-2008 from firm-level surveys, this paper estimates the impact of foreign firms on industrial productivity at the regional level. A Bayesian-model averaging approach is taken to account for model uncertainty resulting from various linkages between foreign firms and domestic industries. The results show that the foreign firms may contribute to industrial efficiency directly through their above-average productivity and indirectly through positive spillovers in intra-industry and local backward linkages. Forward linkages with foreign firms may have a negative impact on industrial productivity. However, these impacts depend on the nationality and entry mode of foreign investors. Aggregating foreign firms may mask their distinctive impacts on productivity.

Self-learning of fault diagnosis identification

A good and early fault detection and isolation system along with efficient alarm management and fine sensor validation systems are very important in today¿s complex process plants, specially in terms of safety enhancement and costs reduction. This paper presents a methodology for fault characterization. This is a self-learning approach developed in two phases. An initial, learning phase, where the simulation of process units, without and with different faults, will let the system (in an automated way) to detect the key variables that characterize the faults. This will be used in a second (on line) phase, where these key variables will be monitored in order to diagnose possible faults. Using this scheme the faults will be diagnosed and isolated in an early stage where the fault still has not turned into a failure.

Integrated learning of computer applications for production engineering

A high productivity rate in Engineering is related to an efficient management of the flow of the large quantities of information and associated decision making activities that are consubstantial to the Engineering processes both in design and production contexts. Dealing with such problems from an integrated point of view and mimicking real scenarios is not given much attention in Engineering degrees. In the context of Engineering Education, there are a number of courses designed for developing specific competencies, as required by the academic curricula, but not that many in which integration competencies are the main target. In this paper, a course devoted to that aim is discussed. The course is taught in a Marine Engineering degree but the philosophy could be used in any Engineering field. All the lessons are given in a computer room in which every student can use each all the treated software applications. The first part of the course is dedicated to Project Management: the students acquire skills in defining, using Ms-PROJECT, the work breakdown structure (WBS), and the organization breakdown structure (OBS) in Engineering projects, through a series of examples of increasing complexity, ending up with the case of vessel construction. The second part of the course is dedicated to the use of a database manager, Ms-ACCESS, for managing production related information. A series of increasing complexity examples is treated ending up with the management of the pipe database of a real vessel. This database consists of a few thousand of pipes, for which a production timing frame is defined, which connects this part of the course with the first one. Finally, the third part of the course is devoted to the work with FORAN, an Engineering Production package of widespread use in the shipbuilding industry. With this package, the frames and plates where all the outfitting will be carried out are defined through cooperative work by the studens, working simultaneously in the same 3D model. In the paper, specific details about the learning process are given. Surveys have been posed to the students in order to get feed-back from their experience as well as to assess their satisfaction with the learning process. Results from these surveys are discussed in the paper

The Learning of the subject Biology in a Master in Biomedical Physics

BIOLOGY is a dynamic and fascinating science. The study of this subject is an amazing trip for all the students that have a first contact with this subject. Here, we present the development of the study and learning experience of this subject belonging to an area of knowledge that is different to the training curriculum of students who have studied Physics during their degree period. We have taken a real example, the “Elements of Biology” subject, which is taught as part of the Official Biomedical Physics Master, at the Physics Faculty, of the Complutense University of Madrid, since the course 2006/07. Its main objective is to give to the student an understanding how the Physics can have numerous applications in the Biomedical Sciences area, giving the basic training to develop a professional, academic or research career. The results obtained when we use new virtual tools combined with the classical learning show that there is a clear increase in the number of persons that take and pass the final exam. On the other hand, this new learning strategy is well received by the students and this is translated to a higher participation and a decrease of the giving the subject up

The Learning of the Mathematical Models to Aid Decision Making in the High Level Engineering Schools?

At present, in the University curricula in most countries, the decision theory and the mathematical models to aid decision making is not included, as in the graduate program like in Doctored and Master´s programs. In the Technical School of High Level Agronomic Engineers of the Technical University of Madrid (ETSIA-UPM), the need to offer to the future engineers training in a subject that could help them to take decisions in their profession was felt. Along the life, they will have to take a lot of decisions. Ones, will be important and others no. In the personal level, they will have to take several very important decisions, like the election of a career, professional work, or a couple, but in the professional field, the decision making is the main role of the Managers, Politicians and Leaders. They should be decision makers and will be paid for it. Therefore, nobody can understand that such a professional that is called to practice management responsibilities in the companies, does not take training in such an important matter. For it, in the year 2000, it was requested to the University Board to introduce in the curricula an optional qualified subject of the second cycle with 4,5 credits titled " Mathematical Methods for Making Decisions ". A program was elaborated, the didactic material prepared and programs as Maple, Lingo, Math Cad, etc. installed in several IT classrooms, where the course will be taught. In the course 2000-2001 this subject was offered with a great acceptance that exceeded the forecasts of capacity and had to be prepared more classrooms. This course in graduate program took place in the Department of Applied Mathematics to the Agronomic Engineering, as an extension of the credits dedicated to Mathematics in the career of Engineering.

Integrated learning of production engineering software applications in a shipbuilding context

Acourse focused on the acquisition of integration competencies in ship production engineering, organized in collaboration with selected industry partners, is presented in this paper. The first part of the course is dedicated to Project Management: the students acquire skills in defining, using MS-PROJECT, the work breakdown structure (WBS), and the organization breakdown structure (OBS) in Engineering projects, through a series of examples of increasing complexity with the final one being the construction planning of a vessel. The second part of the course is dedicated to the use of a database manager, MS-ACCESS, in managing production related information.Aseries of increasing complexity examples is treated, the final one being the management of the piping database of a real vessel. This database consists of several thousand pipes, for which a production timing frame is defined connecting this part of the course with the first one. Finally, the third part of the course is devoted to working withFORAN,an Engineering Production application developed bySENERand widely used in the shipbuilding industry. With this application, the structural elements where all the outfittings will be located are defined through cooperative work by the students, working simultaneously in the same 3D model. In this paper, specific details about the learning process are given. Surveys have been posed to the students in order to get feedback from their experience as well as to assess their satisfaction with the learning process, compared to more traditional ones. Results from these surveys are discussed in the paper.

On-line learning of a fuzzy controller for a precise vehicle cruise control system

Usually, vehicle applications require the use of artificial intelligent techniques to implement control methods, due to noise provided by sensors or the impossibility of full knowledge about dynamics of the vehicle (engine state, wheel pressure or occupiers weight). This work presents a method to on-line evolve a fuzzy controller for commanding vehicles? pedals at low speeds; in this scenario, the slightest alteration in the vehicle or road conditions can vary controller?s behavior in a non predictable way. The proposal adapts singletons positions in real time, and trapezoids used to codify the input variables are modified according with historical data. Experimentation in both simulated and real vehicles are provided to show how fast and precise the method is, even compared with a human driver or using different vehicles.

Autonomous Acquisition of Natural Situated Communication

An important part of human intelligence, both historically and operationally, is our ability to communicate. We learn how to communicate, and maintain our communicative skills, in a society of communicators – a highly effective way to reach and maintain proficiency in this complex skill. Principles that might allow artificial agents to learn language this way are in completely known at present – the multi-dimensional nature of socio-communicative skills are beyond every machine learning framework so far proposed. Our work begins to address the challenge of proposing a way for observation-based machine learning of natural language and communication. Our framework can learn complex communicative skills with minimal up-front knowledge. The system learns by incrementally producing predictive models of causal relationships in observed data, guided by goal-inference and reasoning using forward-inverse models. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime TV-style interview, using multimodal communicative gesture and situated language to talk about recycling of various materials and objects. S1 can learn multimodal complex language and multimodal communicative acts, a vocabulary of 100 words forming natural sentences with relatively complex sentence structure, including manual deictic reference and anaphora. S1 is seeded only with high-level information about goals of the interviewer and interviewee, and a small ontology; no grammar or other information is provided to S1 a priori. The agent learns the pragmatics, semantics, and syntax of complex utterances spoken and gestures from scratch, by observing the humans compare and contrast the cost and pollution related to recycling aluminum cans, glass bottles, newspaper, plastic, and wood. After 20 hours of observation S1 can perform an unscripted TV interview with a human, in the same style, without making mistakes.

Autonomous Acquisition of Natural Language

An important part of human intelligence is the ability to use language. Humans learn how to use language in a society of language users, which is probably the most effective way to learn a language from the ground up. Principles that might allow an artificial agents to learn language this way are not known at present. Here we present a framework which begins to address this challenge. Our auto-catalytic, endogenous, reflective architecture (AERA) supports the creation of agents that can learn natural language by observation. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime mock television interview, using gesture and situated language. Results show that S1 can learn multimodal complex language and multimodal communicative acts, using a vocabulary of 100 words with numerous sentence formats, by observing unscripted interaction between the humans, with no grammar being provided to it a priori, and only high-level information about the format of the human interaction in the form of high-level goals of the interviewer and interviewee and a small ontology. The agent learns both the pragmatics, semantics, and syntax of complex sentences spoken by the human subjects on the topic of recycling of objects such as aluminum cans, glass bottles, plastic, and wood, as well as use of manual deictic reference and anaphora.