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.

This thesis examines the linkages between macroeconomic variables and the number of domestic Mergers & Acquisitions (M&A) in Sweden during 1998-2011 (in terms of changes). This study treats stationary times series data, from which multiple regression models are assembled. These models include gross domestic product, OMX Stockholm price index, lending rate, money supply, debt rate, consumer confidence, the unemployment rate and capacity utilization as explanatory variables. Aggregate number of M&As is set to the dependent variable. The outcome was that gross domestic product, money supply, unemployment rate and stock prices can help explain fluctuations in M&A activity during different time frames. However, the majority of the explanation for fluctuations in M&A activity lies within factors beyond ourestimation model. Through a Granger-causality test, we establish if the significant variables can help to predict M&A activity and vice versa. During different time periods gross domestic product and unemployment helps in predicting M&A activity. M&A activity also improves the prediction of gross domestic product in some time periods.

This paper investigates whether the inherent non-stationarity of macroeconomic time series is entirely due to a random walk or also to non-linear components. Applying the numerical tools of the analysis of dynamical systems to long time series for the US, we reject the hypothesis that these series are generated solely by a linear stochastic process. Contrary to the Real Business Cycle theory that attributes the irregular behavior of the system to exogenous random factors, we maintain that the fluctuations in the time series we examined cannot be explained only by means of external shocks plugged into linear autoregressive models. A dynamical and non-linear explanation may be useful for the double aim of describing and forecasting more accurately the evolution of the system. Linear growth models that find empirical verification on linear econometric analysis, are therefore seriously called in question. Conversely non-linear dynamical models may enable us to achieve a more complete information about economic phenomena from the same data sets used in the empirical analysis which are in support of Real Business Cycle Theory. We conclude that Real Business Cycle theory and more in general the unit root autoregressive models are an inadequate device for a satisfactory understanding of economic time series. A theoretical approach grounded on non-linear metric methods, may however allow to identify non-linear structures that endogenously generate fluctuations in macroeconomic time series. (authors' abstract) / Series: Working Papers Series "Growth and Employment in Europe: Sustainability and Competitiveness"

The profitability and the sources of the returns on momentum strategy have always been a popular subject of study in the financial field. Nevertheless, there exist significant discrepancies between the conclusions of the papers due to the difference in time period and the emphasis on average results. Thus, the purpose of this paper is to investigate momentum strategy with information uncertainty in Taiwan stock market during the period 1990-2009 given the basis on the research method of Jegardeesh and Titman(1993). The result shows that momentum strategy cannot averagely obtain significantly positive returns in the long run in Taiwan stock market and moreover it presents an enormous short-term reversal. Besides, in terms of business cycle, there is still no significant return on momentum strategy either; there will be significantly negative return when implementing momentum strategy in the recession of business cycle. On the other hand, from the view of investor psychological biases, it should be seen greater psychological biases owing to greater information uncertainty. As a result, a stronger stock price continuation may be observed under high information uncertainty stocks. However, the effect of information uncertainty is only pronounced among loser portfolios. To summarize, compared with the profitability and the stability of contrarian strategy, the findings support that there is no significant momentum phenomena in Taiwan stock market at all.

This article will verify whether the central banks create political business cycles or not. To refer to the Opportunistic Model operated by Leetouwer and Maier (2002), this research will expand the acquisition time of data till the fourth season of 2008, and added Korea¡BMalaysia and Taiwan into the model. In this article, the independent variables will be the rates announced by central banks of these ten countries. The dependent variables will be the date of president/parliamentary elections and the independence of central bank to verify before the elections whether will the central banks create political business cycles through setting lower rate in monetary policy are pressured by rules or not. The empirical results show that: 1.The assumption of Central banks will use interest rates to create a political business cycle does not hold. This complements with Leetouwer and Maier¡¦s results studied in 2002, the interest rate cannot be used as a tool to create political business cycle. 2. The higher independence of central bank, the interest rate introduced by central bank will be lower, and as well as the inflation rate.

This paper apply a threshold model to examine the nonlinear relationship between economic growth and unemployment rate. The key innovation of our model is that it takes into account endogenous explanatory variables and endogenous threshold variables. Empirical results show that Okun¡¦s law is nonlinear. Among different models under consideration,the absolute value of Okun¡¦s coefficient during contraction period is larger than that during expansion period.

Since Bretton Woods System break down in year 1973. Many economists found that there are more similar business cycle between industrial countries. Recently, Doyle and Faust(2002) proposed the correlation of business cycle between two countries becomes weaker. Therefore in this search, we try to carry out two different aspect factor that effects the countries¡¦ business cycle correlation. The factor is so-called ¡§transmission mechanism.¡¨ Generally specking, Many empirical analysis have pointed out the temporary factors to the business cycle mainly come from the transferred factors of economic aspect. What is ¡§Transmission Mechanisms?¡¨ Economists often try to substitute it in good markets, financial markets, and the coordination of monetary policies. However, in this duration of the empirical analysis, using only these proxy variables to explain BCCs between two countries seems too limited. According to this situation, we believe if the BCCs can be explained by using proxy factors of non-economic variable, the result can be utilized by making up the defect. We attempt to find new factors in political approach and combine with the ¡§Transmission Mechanisms¡¨ that we have introduced earlier. To analyze further economic implication in our research, five conclusions have been summarized below: Firstly, increasing bilateral trade has significantly provided positive effect to BCCs among G7 countries from 1980 to 2002. Because bilateral trade intensity index is endogenous , we use exogenous variable as instrumental variable to estimate ¡§Trade¡¨. Secondly, we use Panel method to expand its matrix. Finally, we improve the empirical estimators of insignificant statistics before. So, when we talk about the relations between BCCs and good and service markets, we must consider these exogenous factors. Eventually, we will receive more detailed results. Secondly, although to trade in financial markets can increase the BCCs between two countries, the statistic report is insignificant . About this empirical result, we can obtain reasonable explanations from the researches (for instance: Imbs, 2004 or Kose et al, 2003), they point out that financial markets are bound excessively by globalization. Therefore, this will aggravatingly make each country to focus on its specialization. Finally, this situation will make the BCCs getting collapsed among these countries. This also explains that the specialization among these countries will reduce the positive effect from the BBCs to financial markets. Thirdly, in the research, the statistics effect of the trade intensity index and specialization are significant negative. It means that when good in transaction will result in more specialization. Two countries have similar industrial structure.Imbs(2004) consider the problem is the index we use to measure bilateral trade intensity. This index was effected from two countries¡¦ size . If use Clark and van Wincoop¡¦s trade intensity index to measure the effect, we can find that significant specialization by comparative advantage effect. Fourth, there are high level financial integration between two countries, because international risk sharing result in two countries have different industrial structure. Lastly, in the research, the statistics effect of the party variables and business cycle of correlations are very significant. This also indicates the political factor will play an important role for many sources of the fluctuation tread of BCCs. In other words, when we discuss the issue of BCCs if miss the contribution of political factors to the BCCs. Then, this might cause the omitted variable biased, and finally cause the whole computation become inefficient. In addition, we can have further discussion by an input of a factor: to conserve the joint benefit of all the member countries in an economic organization, these countries need to be ruled by the same ideal political party. Otherwise, the institute will never reach its essential result. Combining all the conclusions we have shown above, we can find out the BCCs among G7 countries from 1980-2002. Besides the influence of the ¡§Transmission Mechanisms,¡¨ the result will be varied by the political factors. In conclusion, we need to consider the contribution of the political party variables to the BCCs when talking about this issue, therefore; the original theoretical model can be more persuasive. According to a statistics of IMF, the BCCs among those industrial countries are falling little by little in recent years. Therefore, consolidating trade cooperation is essential for what we believe to improve the BCCs among G7. At the same time, pass through a strong integrate monetary policy can move forward all the incumbent parties from all the countries to agree among themselves, and even reach more substantial effect. From the example like this, we might find evidence from BCCs issues by discussing the integration process in European Monetary Union.

Abstract With the processing of globalization and the large increases in international trade and openness, it is important to capture the business cycle correlation with the intimate countries for government to make better policies and keep the economy steady. This study investigated the changes in relationships between the G7 business cycle after the European integration. Choosing 1993 the Europe Union (EU) commencement as the segment, we separated the sample period into 1965:1-1992:4 and 1993:1-2006:4.We adopted kinds of unit root tests to exam if these variables were stationary and the Johansen co-integration analysis to test whether the stationary long-run equilibrium exist or not. With the consideration of long run information, the Vector Error Correction Model (VECM) was applied to study the relationship between the business cycles of United State, EU and the other G7 countries. By Johansen co-integration analysis, we found that the stationary long-run relationship did exist between their industrial productions¡]IP¡^. In addition, the VECM evidence supported the emergence of two cyclically coherent groups -- the Euro-zone and the English-speaking countries -- after the EU commencement in 1993. In conclusion, with the greater correlation of business cycles, the party in office should take account of the business cycle movement of the closed countries more deliberately in this regionalization era.

After East Asian financial crisis in 1997 and European monetary unification in 1999, if it is suitable of establishing the Asian common monetary area becomes the hot topic. The precondition of establishing the monetary policy cooperation depends on the synchronization of various countries¡¦ business cycle co-movement. And the trade is the connector among the countries. Trade linkages seemed to have an influence on business cycle co-movement. Countries with close international trade link are more likely to be members of an optimal currency area. According to the theoretical literature, the impact of trade integration on business cycle correlation may go either way. On the one hand, if trade occurs mainly by Heckscher-Ollin or is of the Ricardian type, higher specialization would induce the industrial structures of the trading countries to diverge, resulting in less synchronized movements of business cycle. In contrast, if trade occurs mainly through intra-industry trade, specialization does not necessarily lead to less synchronized. In summary, the total effect of trade intensity on cycle correlation is theoretically ambiguous and poses a question that could only be solved empirically. The volume of trade in East Asia has increased continuously. This paper extends the study of Frankel and Rose (1998) to analyze the impact of trade integration on business cycle correlation and intra-industry trade by using SITC data and other macroeconomic factors. Moreover, using two-stage estimation and instruments to take into account the fact that trade intensity itself may be endogenous. Then, we use panel data to estimate our equation. By gathering annual information of 10 East Asian countries from 1987 to 2005, we found that higher trade integration leads higher business cycle synchronization. To sum up, intra-industry trade is the process of establishing East Asian common monetary area.

This dissertation includes three different topics concerning the political business cycles in developed countries. In the first section, we use annual data for 48 states from 1951 to 2004 by the method of instrumental variables estimation. We find that the partisan theory created in statewide via two channels including the partisanship effect which include the interactive relationships between president and governors or among governors, and the partisan ideology including the policy preferences are both potential shocks to a real business cycle. Next, we investigate the theory of partisan cycles using panel cointegration and fully modified OLS techniques based on the same data as earlier. We propose the long-run co-movement and the causal relationships between partisan target and cycle variables. Meanwhile, the panel error correction model shows evidence of long-run unidirectional causality running from partisan variables to target variables. This shows that, in the long run, statewide economic performance must be directly based on politicians¡¦ concerns for policies and outcomes, as well as on exhibiting strong ideological differences in those preferences across parties in the United States. Overall, we contribute an essential reference to the voters. Finally, a new government popularity index (GPI) is constructed and using variables that include real GDP, industrial production, the unemployment rate and the inflation rate as measures of bilateral activity correlation beginning in 1981Q1 and ending in 2005Q4 for 15 European countries. The estimation procedure is developed by rolling the correlation of bilateral activity every twenty quarters and running it on partisan variables, namely, as a kind of government popularity index and the difference between partisan ideologies combined with traditional bilateral trade intensity variables. Overall, a strong and striking empirical finding is uncovered: countries with closer popular governments, incumbent ideologies as well as trade links, tend to have more closely correlated business cycles.