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The sustainability of European Monetary Union : evidence from business cycle synchronisation, monetary policy effectiveness and the Euro fiscal dividendZhang, H. E. January 2014 (has links)
EMU as the only functioning single currency area has been criticised as a non-optimal currency area since the Treaty on European Union was signed. Despite this, it has been seen as, probably, the most complete economic project that has ever been conducted by any group of governments. Through Dynamic Factor model and Panel VAR method, we are focusing on the issues of business cycle synchronisation, effectiveness of ECB monetary policy and the euro fiscal dividend, thus to advances the current studies on EMU through assessing whether it can be a sustainable system. For example, whether economic fluctuations can be effectively managed by implementing a single ECB monetary policy and financial market can be relied upon as a monitoring and enforcing device to discipline fiscal behaviour of Eurozone countries. Overall, we concluded that EMU could be more sustainable if it was just formed by its core members, leaving the periphery outside the single currency area. However, since the EU has recently conducted many rescue measures to save the Eurozone, we are unlikely to see those troubled countries to quit EMU, at least, at the present time. The sustainability of the current EMU can be improved if more intra-trade can be promoted to enhance business cycle convergence; hence, it will be more likely to have a union-wide appropriate monetary policy. This will also reduce the requirement of depending upon using fiscal measures to compensate the loss of monetary sovereignty. Moreover, fiscal activities can also be better monitored/enforced since the financial market has begun to adequately adjust the long-term interest rates on Eurozone government bonds according to the development in those countries fiscal stance.
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Structural Models for Macroeconomics and ForecastingDe Antonio Liedo, David 03 May 2010 (has links)
This Thesis is composed by three independent papers that investigate
central debates in empirical macroeconomic modeling.
Chapter 1, entitled “A Model for Real-Time Data Assessment with an Application to GDP Growth Rates”, provides a model for the data
revisions of macroeconomic variables that distinguishes between rational expectation updates and noise corrections. Thus, the model encompasses the two polar views regarding the publication process of statistical agencies: noise versus news. Most of the studies previous studies that analyze data revisions are based
on the classical noise and news regression approach introduced by Mankiew, Runkle and Shapiro (1984). The problem is that the statistical tests available do not formulate both extreme hypotheses as collectively exhaustive, as recognized by Aruoba (2008). That is, it would be possible to reject or accept both of them simultaneously. In turn, the model for the
DPP presented here allows for the simultaneous presence of both noise and news. While the “regression approach” followed by Faust et al. (2005), along the lines of Mankiew et al. (1984), identifies noise in the preliminary
figures, it is not possible for them to quantify it, as done by our model.
The second and third chapters acknowledge the possibility that macroeconomic data is measured with errors, but the approach followed to model the missmeasurement is extremely stylized and does not capture the complexity of the revision process that we describe in the first chapter.
Chapter 2, entitled “Revisiting the Success of the RBC model”, proposes the use of dynamic factor models as an alternative to the VAR based tools for the empirical validation of dynamic stochastic general equilibrium (DSGE) theories. Along the lines of Giannone et al. (2006), we use the state-space parameterisation of the factor models proposed by Forni et al. (2007) as a competitive benchmark that is able to capture weak statistical restrictions that DSGE models impose on the data. Our empirical illustration compares the out-of-sample forecasting performance of a simple RBC model augmented with a serially correlated noise component against several specifications belonging to classes of dynamic factor and VAR models. Although the performance of the RBC model is comparable
to that of the reduced form models, a formal test of predictive accuracy reveals that the weak restrictions are more useful at forecasting than the strong behavioral assumptions imposed by the microfoundations in the model economy.
The last chapter, “What are Shocks Capturing in DSGE modeling”, contributes to current debates on the use and interpretation of larger DSGE
models. Recent tendency in academic work and at central banks is to develop and estimate large DSGE models for policy analysis and forecasting. These models typically have many shocks (e.g. Smets and Wouters, 2003 and Adolfson, Laseen, Linde and Villani, 2005). On the other hand, empirical studies point out that few large shocks are sufficient to capture the covariance structure of macro data (Giannone, Reichlin and
Sala, 2005, Uhlig, 2004). In this Chapter, we propose to reconcile both views by considering an alternative DSGE estimation approach which
models explicitly the statistical agency along the lines of Sargent (1989). This enables us to distinguish whether the exogenous shocks in DSGE
modeling are structural or instead serve the purpose of fitting the data in presence of misspecification and measurement problems. When applied to the original Smets and Wouters (2007) model, we find that the explanatory power of the structural shocks decreases at high frequencies. This allows us to back out a smoother measure of the natural output gap than that
resulting from the original specification.
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Dynamic Factor Analysis as a Methodology of Business Cycle ResearchKholodilin, Konstantin A. 23 April 2003 (has links)
El objetivo principal de la investigación emprendida en la presente tesis doctoral es elaborar una técnica de construcción de un indicador económico compuesto o un conjunto de dichos indicadores que, correspondiendo al concepto teorético del ciclo económico (comercial), permitirán detectar y predecir los puntos de giro del ciclo económico.Como el punto de partida hemos escogido la definición del ciclo económico propuesta por Burns y Mitchell (1946). Según nuestra opinión, el analisis dinámico factorial es el método idóneo para captar los puntos de giro del ciclo económico en el sentido de Burns y Mitchell. Por un lado, tiene en cuenta los movimientos comunes de varias series macroeconómicas que bajan y suben simultaneamente durante las fases de recesiones y expansiones, respectivamente. Por otro lado, refleja las asimetrías que existen entre las dos fases cíclicas, como, por ejemplo, las tasas de crecimiento y la volatilidad distintas durante las recesiones y expansiones. Ambos rasgos estan subrayados por Burns y Mitchell como características definitivas del ciclo económico.El análisis dinámico factorial en su estado actual exige sin duda ciertas modificaciones y algunas extensiones para obtener las estimaciones insesgadas y consistentes de los indicadores económicos compuestos y para utilizar la información disponible de la mejor manera posible.Nuestra investigación está dirigida, en primer lugar, hacia los economistas prácticos que han optado por utilizar el análisis dinámico factorial para la construcción del indicador del ciclo económico tanto a nivél regional como nacional.La tesis esta compuesta por cinco capítulos donde el primer y el último capítulos son, respectivamente, la introducción y la conclusión. En ellos se exponen los objetivos del estudio y los resultados alcanzados en el curso de la investigación.En el capítulo dos describimos varios metodos de análisis de las fluctuaciones económicas que han sido propuestos durante los últimos 20 años. Por un lado, consideramos los modelos con la dinámica nolineal, concretamente el cambio de regímenes o el Markov switching. Por otro lado, examinamos los modelos lineales del análisis dinámico factorial. Al final del capítulo analizamos el modelo del factor común latente con la dinámica nolineal (con cambios de regímenes) que está construido como una combinación de estos dos metodos principales.En el capítulo tres introducimos un modelo general dinámico multifactorial con la dinámica lineal y nolineal. Este modelo permite captar la dimensión intertemporal (indicador avanzado versus indicador coincidente) de los factores comunes inobservables. Se examinan dos modelos dinámicos alternativos con un factor común inobservable avanzado y un factor común inobservable coincidente. En el primer modelo el factor común coincidente esta influido por el factor común avanzado a través del mecanismo de causalidad de Granger. Mientras que en el segundo modelo los dos factores estan relacionados via la matríz de las probabilidades de transición. Debido a que el factor avanzado contiene información sobre los cambios futuros de las fases cíclicas, ambos modelos permiten hacer predicciones de los puntos de giro del ciclo económico.En el capítulo cuatro elaboramos las técnicas sumplementarias necesarias para resolver algunos problemas de datos que son bastante frecuentes en la actividad de un economista empírico. Los dos problemas más importantes son los cambios estructurales y la falta de observaciones, particularmente cuando los datos que estan disponibles con distintas frecuencias (por ejemplo: los datos mensuales y trimestrales). Estos problemas quiebran la continuidad de la serie temporal y reducen el número de observaciones válidas para el análisis estadístico. Se demuestra que estos problemas se resuelven modificando el modelo de análisis dinámico factorial, con lo que se obtienen estimaciones más eficientes de los parametros del modelo. / The main objective of our research undertaken in this thesis is to elaborate a technique of constructing a composite economic indicator or a set of such indicators which would correspond to the theoretical concept of business cycle and reflect a phenomenon which may be interpreted as the cyclical dynamics of the economy.As a point of departure we have chosen the definition of business cycle proposed by Burns and Mitchell (1946). We believe that the most appropriate method to capture the Burns and Mitchell's cycle would be the dynamic factor analysis.The dynamic factor analysis in its current state requires undoubtedly some refinements and extensions to obtain unbiased and consistent estimates of the composite economic indicators and to use the available information in the best possible way.Our research is mostly oriented towards the practitioners who have opted for using the dynamic factor approach in the construction of the business cycle indicator both at the regional and national levels.The thesis is comprised of five chapters where the first and the last chapters are the introduction and conclusion delineating the objectives of the study and summarizing the results achieved during research.Chapter two describes various approaches to the analysis of economic fluctuations proposed during the last 20 years. On the one hand, it concentrates on models with nonlinear, namely Markov-switching, dynamics, on the other hand, it is concerned with dynamic factor models. Finally, it shows the combined techniques which unify these two principal approaches, thus, modeling common latent factor with regime-switching dynamics.In chapter three we introduce a general multifactor dynamic model with linear and regime-switching dynamics. This model allows capturing the intertemporal (leading versus coincident) dimension of the latent common factors. Two alternative multifactor dynamic models with a leading and a coincident unobserved common factors are examined: a model where the common coincident factor is Granger-caused by the common leading factor and a model where the leading relationship is translated into a set of specific restrictions imposed on the transition probabilities matrix.Chapter four concentrates on the supplementary devices which allow to overcome some data problems which are very frequent in the practitioner's life. Among the most prominent are the structural breaks and missing observations. It is shown that some of these troubles can be coped with by modifying the dynamic common factors models, which leads to more efficient estimates of the parameters of the models.
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Synchronization of Economic Fluctuations across Countries---The Application of the Dynamic Factor Model in State SpaceWang, Bao-Huei 27 July 2011 (has links)
In this thesis, we use the dynamic factor model in state space, proposed by Stock and Watson (1989), to estimate the fluctuations of common factor by using lots of macroeconomic variables. Besides, with the combination of two stage dynamic factor analysis model which is proposed by Aruba et. al (2010), we want to discuss the possibility for the correlation of economic fluctuations across countries to change with different time periods.
The thesis verifies the following three conclusions: First, the correlations of the economic fluctuations across countries are significant due to the regional economics. Second, the global or regional common shocks will increase the correlations of the economic fluctuations across countries. Finally, developed countries and emerging countries response differently during the Financial Tsunami from 2008 to 2009.
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Nowcasting Brazilian GDP: a performance assessment of dynamic factor modelsGomes, Guilherme Branco 19 March 2018 (has links)
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Previous issue date: 2018-03-19 / This work compares dynamic factor model’s forecasts for Brazilian GDP. Our approach takes into account mixed frequencies and can handle missing data. We implement three models: the first is based on the Principal Components Analysis methodology; the second employs a two-step estimation method with quarterly inputs; the last is similar to the former but uses monthly series. A real-time out-of-sample exercise is proposed to assess the performance of these models. A dataset is created for each day within 27 quarters - from the fourth quarter of 2010 up to the second quarter of 2017. For recent periods, the nowcasts estimated by both two-step procedures perform better than the average predictions of Focus Survey, a bulletin organized by the Brazilian Central Bank. We also show evidence that the average of GDP forecasts from this survey may be biased / Esse trabalho compara previsões para o PIB brasileiro utilizando modelos de fatores dinâmicos. Nossa abordagem leva em consideração frequências mistas e lida com dados incompletos na base (missing data). Nós implementamos três modelos: o primeiro é baseado na metodologia de componentes principais; o segundo emprega uma estimação por dois estágio com variáveis trimestrais; o último é similar ao anterior mas utiliza series mensais. Um exercício em tempo real, fora da amostra, é proposto para comparar o desempenho desses modelos. Uma base de dados é criada para cada dia dentro de 27 trimestres - do quarto trimestre de 2010 até o segundo de 2017. Para períodos recentes, os nowcasts estimados para ambos os procedimentos de dois estágios se mostram melhores do que a média de previsão da pesquisa Focus, um boletim organizado pelo Banco Central do Brasil. Nós também mostramos evidências que a média das previsões do PIB dessa pesquisa pode ser viesada
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The sustainability of European Monetary Union. Evidence from business cycle synchronisation, monetary policy effectiveness and the Euro fiscal dividend.Zhang, H.E. January 2014 (has links)
EMU as the only functioning single currency area has been criticised as a non-optimal currency area since the Treaty on European Union was signed. Despite this, it has been seen as, probably, the most complete economic project that has ever been conducted by any group of governments. Through Dynamic Factor model and Panel VAR method, we are focusing on the issues of business cycle synchronisation, effectiveness of ECB monetary policy and the euro fiscal dividend, thus to advances the current studies on EMU through assessing whether it can be a sustainable system. For example, whether economic fluctuations can be effectively managed by implementing a single ECB monetary policy and financial market can be relied upon as a monitoring and enforcing device to discipline fiscal behaviour of Eurozone countries.
Overall, we concluded that EMU could be more sustainable if it was just formed by its core members, leaving the periphery outside the single currency area. However, since the EU has recently conducted many rescue measures to save the Eurozone, we are unlikely to see those troubled countries to quit EMU, at least, at the present time. The sustainability of the current EMU can be improved if more intra-trade can be promoted to enhance business cycle convergence; hence, it will be more likely to have a union-wide appropriate monetary policy. This will also reduce the requirement of depending upon using fiscal measures to compensate the loss of monetary sovereignty. Moreover, fiscal activities can also be better monitored/enforced since the financial market has begun to adequately adjust the long-term interest rates on Eurozone government bonds according to the development in those countries fiscal stance.
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Factor Demand and Market PowerSjöström, Magnus January 2004 (has links)
The objective of Paper [I] is to analyze potential effects on the Swedish forest sector of a continuing rise in the use of forest resources as fuel in energy generation. An increasing use of forest resources as an energy input may have effects outside the energy sector. In this paper we consider this by estimating a system of demand and supply equations for the four main actors on the Swedish roundwood market. In Paper [II], we estimate a dynamic factor demand model for the Swedish pulp industry. We find weak evidence of adjustment costs for capital. The results suggest that the user cost of capital is a significant determinant of pulp industry investments. We also find that pulp industry investments are insensitive to variations in the price of electricity. Paper [III] proposes a flexible form of adjustment cost function. An empirical illustration shows that the flexible form can detect both convex and non-convex adjustment costs. Furthermore, the flexible form permits testing for the experience effect on adjustment cost. The objective of paper [IV] is to analyze the price formation for wood fuel used by the Swedish district heating sector. According to previous research there is a significant potential for increasing the use of wood fuel in Sweden. The question raised in this paper is why this potential is not realized. According to our results we cannot reject the efficient market hypothesis for all years. The objective of Paper [V] is to test for market power on the market for biofuels. To achieve our objective we make use of the idea of Granger causality. If past values of quantity contribute significantly to the determination of price, quantity is said to Granger cause price, which we will treat as a sign of market power. According to our findings this effect is present.
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FORECASTING WITH MIXED FREQUENCY DATA:MIDAS VERSUS STATE SPACE DYNAMIC FACTOR MODEL : AN APPLICATION TO FORECASTING SWEDISH GDP GROWTHChen, Yu January 2013 (has links)
Most macroeconomic activity series such as Swedish GDP growth are collected quarterly while an important proportion of time series are recorded at a higher frequency. Thus, policy and business decision makers are often confront with the problems of forecasting and assessing current business and economy state via incomplete statistical data due to publication lags. In this paper, we survey a few general methods and examine different models for mixed frequency issues. We mainly compare mixed data sampling regression (MIDAS) and state space dynamic factor model (SS-DFM) by the comparison experiments forecasting Swedish GDP growth with various economic indicators. We find that single-indicator MIDAS is a wise choice when the explanatory variable is coincident with the target series; that an AR term enables MIDAS more promising since it considers autoregressive behaviour of the target series and makes the dynamic construction more flexible; that SS-DFM and M-MIDAS are the most outstanding models and M-MIDAS dominates undoubtedly at short horizons up to 6 months, whereas SS-DFM is more reliable at long predictive horizons. And finally we conclude that there is no perfect winner because each model can dominate in a special situation.
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noneChen, Tze-Gan 12 August 2000 (has links)
none
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An Empirical Analysis of International Linkage and Productivity Growth---the Evidence from Taiwan Manufacturing IndustryHsu, Yao-wen 29 July 2008 (has links)
The purpose of this research is to analyze the dynamics of innovation and technological diffusion from the channels of international linkage at the microeconomic level. We specify and want to learn about the effects of sectoral innovation and technology transfer with international linkages: Imported technology, Information and Communication Technology, Foreign direct investment and its spillovers and trade. We apply a dynamic factor demand model to analyze the relationship between four channels of international technology transfer and diffusion, allowing for heterogeneous international linkages and their contribution to productive performance on Taiwan¡¦s manufacturing industries. We adopt the econometric method of the Generalized Method of Moment (GMM) to estimate the parameters of related equations. Throughout the empirical analysis, we hope to understand how degree of effects the four channels of technology transfer have on firm¡¦s productivity performance and the adjustment process of quasi-fixed input, capital, because of technology transfers. We found that:(1) It has the highest output level in Electrical and Electronic Manufacturing in Taiwan¡¦s manufacturing industry.(2) The exogenous technical change has a positive effect on output growth. As for the channels of international linkage, imported technology and R&D all have positive contribution to productivity. FDI has a negative impact on output growth except for Petroleum & Coal Products Manufacturing, but the effect of the FDI spillover has a positive contribution in the Taiwan¡¦s manufacturing industry.
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