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Un guide pratique et accessible pour comprendre comment fonctionne le modèle Mundell-Fleming Si les tenants et aboutissants des politiques budgétaire, fiscale et monétaire appliquées au niveau national apparaissent déjà complexes, comment donc comprendre les liens qu'elles entretiennent avec les mouvements monétaires à l'échelle mondiale? Qu'est-ce que le taux de change ou encore la balance des paiements? Quels sont les avantages qu'offrent des espaces monétaires tels que la zone euro? Ce livre vous aidera à: •Vous représenter l'équilibre macroéconomique mondial •Percevoir la dynamique des marchés de change •Comprendre les effets des politiques étatiques sur les échanges internationaux •Et bien plus encore! Le mot de l'éditeur: « Avec l'auteur, Jean Blaise Mimbang, nous avons cherché à présenter aux lecteurs un condensé structuré et clair portant sur une extension du célèbre modèle IS-LM afin qu'ils puissent percevoir la dynamique des échanges en économie ouverte. » Juliette Nève À PROPOS DE LA SÉRIE 50MINUTES | Culture économique La série « Culture économique » de la collection 50MINUTES propose des documents qui invitent tous les curieux à réfléchir sur les enjeux et les réalités qui façonnent le monde économique actuel. Nous avons conçu la collection Business & Economics en pensant aux nombreux professionnels obligés de se former en permanence en économie, en management, en stratégie ou en marketing. Nos auteurs combinent des éléments de théorie, des pistes de réflexion, et dans certains cas des études de cas et de nombreux exemples pratiques pour permettre aux lecteurs de développer leurs compétences et leur expertise.

A contributors' \"who's who\" from the academic and policy communities explain and provide perspectives on John Taylor's revolutionary thinking about monetary policy. They explore some of the literature that Taylor inspired and help us understand how the new ways of thinking that he pioneered have influenced actual policy here and abroad.

Rational Expectations and Econometric Practice: Volume 2 was first published in 1981. Assumptions about how people form expectations for the future shape the properties of any dynamic economic model. To make economic decisions in an uncertain environment people must forecast such variables as future rates of inflation, tax rates, government subsidy schemes and regulations. The doctrine of rational expectations uses standard economic methods to explain how those expectations are formed. It assumes that people form expectations in an optimal way, given their limited information and all of the uncertainties of the environment. This work collects the papers that have made significant contributions to formulating the idea of rational expectations. Selections range from John F. Muth’s classic essays of the early sixties to unpublished research of Muth, Gregory Chow, Robert E. Lucas, and Lars P. Hansen and Thomas J. Sargent. Most of the papers deal with the connections between observed economic behavior and the evaluation of alternative economic policies. The editors have focused on work that will be valuable for applied economists who are interested in constructing and estimating econometric models. Their introductory essay unifies the collection and explains the relationship among various aspects of work in rational expectations theory. This collection thus presents a valuable record of the development of the concept as well as an overview of current work in the field. Contributors besides the editors and those mentioned above are: Edward C. Prescott, Neil Wallace, Robert J. Barro, Stanley Fischer, B.T. McCallum, Kenneth F. Wallis, C. W. J. Granger, Christopher A. Sims, Robert E. Hall, F. E. Kydland, Guillermo A. Calvo, and John B. Taylor._x000B_The paperback edition of this work is bound as two volumes. Volume I contains the editors’ introduction and covers the topics of Implications of Rational Expectations for Time Series, Macroeconomic Policy, and Econometric Methods. Volume II discusses the subjects of General Applications, Testing for Neutrality, and Macroeconomic Control Problems._x000B_

Assumptins about how people form expectations for the future shape the properties of any dynamic economic model. To make economic decisions in an uncertain environment people must forecast such variables as future rates of inflation, tax rates, government subsidy schemes and regulations. The doctrine of rational expectations uses standard economic methods to explain how those expectations are formed. This work collects the papers that have made significant contributions to formulating the idea of rational expectations. Most of the papers deal with the connections between observed economic behavior and the evaluation of alternative economic policies.

Testing Monetarism pursues the complex question of the nature of the controversy surrounding monetarist theory and evidence, and the reasons for the persistence of this controversy. The theory of monetarism is examined in its old guise as the Quantity Theory of Money, and subsequent chapters look at the evolution of the theory to its present form in the period since the 1950's, and Desai weaves together issues of theory with those of econometric evidence. He looks in turn at major predictions of monetarism, critically examining the claims made in the literature in the light of his discussion of the methodology of testing theories and highlights flaws in the empirical data surrounding monetarism.

Prediction markets are online trading platforms where contracts on future events are traded with payoffs being exclusively linked to event occurrence. Scientific research has shown that market prices of such contracts imply high forecasting accuracy through effective information aggregation of dispersed knowledge. This phenomenon is related to incentives for truthful aggregation in the form of real-money or play-money rewards. The question whether real- or play-money incentives enhance higher relative forecast accuracy has been addressed by previous works with diverse findings. The current state of empirical research in his field is subject to two inherent deficiencies. First, inter-market studies suffer from market disparities and differences in the definition of underlying events. Comparisons between two different platforms (one for play-money contracts, one for real-money contracts) are potentially biased by different trading behaviour. Second, the majority of studies are based upon identical datasets of market platforms (IOWA stock exchange, Tradesports/Intrade, NewsFutures). Auszug aus dem Text Text Sample: Chapter 2.2, Other Factors With Influence on Forecasting Accuracy: Luckner (2008) discusses relevant studies based on various online platforms. Berg et al. (2000) consolidate findings of empirical studies on the IOWA prediction market, a prediction platform on political elections which has been operating since 1988. The study is limited to political, indexed contracts which pay off 1 for each per cent of votes or allocated seats a specific political party achieves in US or foreign elections. The dataset included 5 markets for presidential elections, 14 markets for other elections and 30 markets for non-US elections. A total of 237 predictions in 49 markets generated average forecast errors of 0.0137 for US elections, 0.043 for other US elections and 0.012 for non-US elections. The significant spread in overall forecast accuracy compared to the findings of Servan-Schreiber et al. (2004) and Rosenbloom and Notz (2006) is inherently tied to market factors (market maker, fees, deposit limits, etc.), contract design (sports/politics, binary/indexed) and market dynamics (trading volumes, quality of predictions, behavioural aspects). A further study on the IOWA prediction market by Berg, Forsythe and Rietz (1996) reveals significant aspects about influencing factors on the variance of forecast errors. Firstly, quantity (volume of trades) showed a significant positive influence on forecast accuracy. Forsythe, Rietz and Ross (1999) on the other hand, found highly accurate forecasting for small-scale laboratory based experiments. Likewise, Smith (1982) states that a number of individuals exposed to private information signals are sufficient for market efficiency. This calls into question whether trading volumes in fact influence forecast accuracy or whether high quality predictions can compensate for lower quantities. Second, some contract categories (presidential elections) attracted higher trading volumes than others. Third, trading activity grew in number and volume as contracts approached expiry. This finding supports the risk-averse nature of trading activity discussed above. Arrow et al. (2008) postulates forecast accuracy to be dependent on days until expiry for contracts on the IOWA prediction market. Whereas volatility did not decrease substantially, trading prices tended to fluctuate more closely around the ex-post value as more information was available to trading individuals. However, this interpretation is based on a graphical interpretation of a linear relationship and lacks quantification. 2.3, Closed Prediction Markets: Closed prediction markets are limited to individuals meeting certain criteria (e.g. employees of specific company, students of a certain university) or are limited to certain physical environments (e.g. laboratory, office space). Since the dataset studied in this paper was partly obtained through trading in a closed market environment, discussion is required whether markets with a limited number of participants have the same potential in forecasting accuracy as open ones. Closed prediction markets aggregate information held by a comparably small number of individuals in possession of private information signals. Companies have successfully implemented closed prediction markets for sales forecasts, project management and R&D processes in recent years (Ivanov, 2009). These markets are usually operated as play-money markets implemented by third-party vendors. Besides Google, Hewlett Packard, Nokia, Motorola, Microsoft, Intel, Best Buy, Chrysler and have implemented internal markets (Cowgill et al, 2008 ; Wolfers & Zitzewitz, 2006b). Chen and Plott (2009) found sales forecasts generated by the closed HP market to be more accurate than figures by a central corporate planning unit. However, it is unclear whether the predictions within this market would have been more accurate when being traded in an open market. Does a small number of participants predict as well as an unlimited body of individuals? Does the higher amount of expertise knowledge compensate the lower degree of heterogeneity and quantity? Existing research is lacking answers to such form of comparison. Summarising the current state of knowledge, prediction markets are agreed to be the most effective way of aggregating dispersed knowledge into accurate forecasts across various platforms, categories, contracts and methodologies in open and closed applications. The influence of incentives has been analysed in cross-platform comparison and found to be sensitive to different categories. Other studies found days-to-expiry and volumes to be significant drivers of forecasting performance. The role of quantities vs. qualities has not yet been analysed extensively - leaving the question of whether a higher number of predictors results in higher forecasting performance or whether predictions by a small number of well-informed participants can predict as effectively. Biographische Informationen Sebastian Diemer holds a Bachelor of Science from the European Business School as well as a Master of Science from the London School of Economics. He has published several studies on opportunities in the digital era and has started and sold several ventures. He likes travelling (travelled each continent and 52 countries), sports, and especially, water sports.

Key Features:Serves as a reference source for the increasing number of economists who now believe that financial asset quantities and prices contain important information for policymakersHelps as a reference source for professionals interested in improving central bank data qualitySurveys the theory and econometrics relevant to production of improved monetary aggregate and interest-rate aggregate data.

The book surveys modern literature on financial aggregation and index number theory, with special emphasis on the contributions of the book's two coauthors. In addition to an introduction and a systematic survey chapter unifying the rest of the book, this publication contains reprints of six published articles central to the survey chapter.