Business Cycle Synchronization in Latin America

Business Cycle Synchronization in Latin America Business cycles synchronization in Latin America:  A TVTPMS Approach Introduction: Over the last decades, there has been a growing interest in the business cycle transmissions among countries and interdependencies. The design of regional co-operations and integrations, such as Mercosur or Latin America countries, has the purpose to reduce poverty, amplify society welfare and enhance macroeconomic stability. However, it is crucial to understand the influence of regional integration and the role of external factors on regional business cycle synchronization. Fiess (†¦..) find that a relatively low degree of business cycle synchronization within Central America as well as between Central America and the United States. Grigoli (2009) analyzed the causation relations among business activities of the Mercosur countries to determine which cycles are dependent on others, considering trade intensity, trade structure and the influences of the EU and US as well. He find some causation relations among the South-American countries; however, the EU and US do not play a relevant role in determining the fluctuations of their cycles. Gutierrez and Gomes (†¦..) use the Beveridge-Nelson-Stock-Watson multivariate trend-cycle decomposition model to estimate a common trend and common cycle. Aiolfi et al. (2010) identify a sizeable common component in the LA countries’ business cycles, suggesting the existence of a regional cycle Caporale and Girardi (2012) show that the LA region as a whole is largely dependent on external developments and the trade channel appears to be the most important source of business cycle co-movement. They report that the business cycle of the individual LA countries appears to be influenced by country-specific, regional and external shocks in a very heterogenous way. In order to investigate the degree of synchronization of the business cycles among the six major LA economies[1] (namely, Argentina, Brazil, Chile, Mexico, Colombia and Venezuela) as a whole, we consider the presence of a regional cycle by estimating the common growth cycle with the aim of testing its effect on each country-specific cycle. Besides this introduction, this paper is organized as follows. Section 2 contains the model and describes the data. Section 3 presents the empirical results and finally, section 4 concludes. Data and Methodology : We use quarterly data of the real GDP growth rate of the LAC countries, extracted from Penn World Table , namely †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦, covering the period from the first quarter of †¦Ã¢â‚¬ ¦ to the last quarter of †¦Ã¢â‚¬ ¦. We focus on whether the economic activity in the LAC countries is driven by a joint business cycle. We first look at the engine of growth lies within the LA countries. We therefore firstly begin by studying the existence of a common cycle among the economies studied. Second, we attempt to find the influence of a common factor referred to as the LAC’s business cycle extracted from the estimation of a dynamic common factor model. We employ a measure of business cycles synchronization based on Hamilton’s (1989) original Markov-switching model and the time– varying Markov–switching model developed by Filardo (1994) and reconsidered recently by Kim et al. (2008) to investigate the regional common factor in dating the regional business cycles. This study analyzes whether the synchronization pattern of business cycles in a country has systematically changed with the expansion or recession phases of regional business cycle. In this context, we assumed business cycles in a particular country are driven by regional cycles proxied by the common dynamic factor in real GDP growth of the LA countries, thus we use a dynamic factor model to extract the regional cycle. The main interest of the analysis is that a latent dynamic factor drives the co-movement of a high-dimensional vector of time-series variables which is also affected by a vector of mean-zero idiosyncratic disturbances, ÃŽ µt (Stock, 2010) . The common factors are assumed to follow a first-order autoregressive process. This linear state-space model can be written as follows: (1) (2) where L1,t,†¦,Lk,t are common to all the series, ÃŽ µ and ÃŽ · are independent Gaussian white noise terms. The L matrix of factor loadings measures the instantaneous impact of the common factors on each series. There are two growth phases or regimes with a transition between them governed by a time-varying transition probability matrix. The advantage of such a model is that the regimes can be easily interpreted as regimes of recession and expansion. The estimated equation is the following[2]: , (3) where and The endogenous variable, yt (the real growth rate in a given country at time t) is assumed to visit the two states of a hidden variable, st, that follows a first-order Markov chain, over the T observations[3]. ÃŽ ¼st, ÏÆ', à Ã¢â‚¬ ¢ are real coefficients to be estimated. Denoting zt the leading variable (the regional common factor at time t), we want to know whether zt causes yt+k, k= 1,2, †¦.Under the assumption that both y and z have ergodic distributions, we define the following transition probability functions: (4) where and are elements of the following transition probability matrix: (5) with Pij the probability of switching from regime j at time t − 1 to regime i at time t and i, j =1, 2 with for all i,j∈{1,2. k is a lag. In order to estimate the coefficients of equation (1), we need to maximize the log-likelihood of the unconditional density function of yt: (6) The unconditional density function is the product of the conditional density function and the unconditional probability of st. This is written as[4]: (7) Transition probabilities indicate that the states of expansion and recession are equally persistent, and this persistency is very strong. These probabilities aim to provide information about the likelihood of staying or switching from a given regime of k periods after a regime change in z. If the estimate of ÃŽ ¼1 is positive and ÃŽ ¼2 is negative, then regime 1 can be interpreted as one of expansion and regime 2 as one of contraction. Furthermore, assume that in eq. (†¦) ÃŽ ³1,2 is positive. This indicates that while any increase in leading indicator (z) increases P11, probability that y stays in regime 1, any decrease in z increases 1-P11, probability that y switches from regime 1 k periods later; that is, an expansion (recession) in z leads to an expansion (recession) in another country. Similarly, a negative ÃŽ ³1,2 means that an expansion in z leads to a recession in another country. Additionally, a negative ÃŽ ³2,2 means that any decrease (increase) in leading indicator in creases the probability of staying in regime 2 (switching from regime 2). If both ÃŽ ³1,2 and ÃŽ ³2,2 are insignificant, this would mean that there is no statistically meaningful impact of the occurrence of expansions or recessions in a leading market on the growth regime of the other markets[5]. Empirical Results Fig. 1 refers to the common factor, i.e. the regional growth cycle of the Latin America countries. As we can see, the common factor easily captures the well-known common features of the LA business cycle such as the 1994–95 Mexican crisis and the Tequila crisis. To test the hypothesis of a joint business cycle in the LA, we estimate the TVTPMS model given by Eqs. (1) and (2) with the variable z referring to the common factor (regional cycle). Fig. 1. Common factor in real GDP growth of the Latin America countries The estimation results for the regional cycle as leading variable are reported in Table 1. We find significantly positive ÃŽ ¼1 and negative ÃŽ ¼2 which correspond to a situation of distinct expansion and contraction regimes. Our main findings are based on the significance of the estimated coefficients ÃŽ ³1,2 and ÃŽ ³2,2. When looking at the significance of the coefficient ÃŽ ³1,2 , it is found that the common factor exerts direct effects on Mexico and Venezuela, implying that a high growth rate in regional cycle is informative of GDP expansion phases in these countries. That is, an expansion in common factor increases the probability that Mexico and Venezuela will continue to evolve in an expansion regime (i.e. P11). However, we see that ÃŽ ³2,2 is never significant for these countries. This suggests that the regional cycle can never be considered as a leading indicator of the future state of the cycle in Mexico and Venezuela when they are already in the contraction regime (i.e. P2 2 and P1-22). Conversely, our results show that regional cycle is sensitive to economic fluctuations in Colombia, Chile and Brazil because ÃŽ ³2,2 is significant, thereby implying that any change in regional factor does help predict whether these economies will stay into or escape from contractions. Table 1 Estimation results for the regional cycle as leading variable. The numbers in bold indicate that a high growth rate in Mexico, Venezuela, Colombia, Chile, and the Brail has an impact on the expansion and recession phases of the regional cycle. The evidence presented here indicates that Latin America countries’ increasing economic interdependence has strengthened both interregional business cycles synchronization. A regional cycle could provide significant informational content in predicting the future state of Mexico and Venezuela only when they are already into the expansionary state and the future state of Colombia, Chile and Mexico when they are already in the contraction regime. That is, the high level of integration reached within the region has enabled Mexico and Venezuela to emerge as a pole of economic growth where their business cycles are mutually reinforced during expansions. In other words, while this increasing economic interdependence tends to strengthen output co-movements when these countries are already in the expansionary state, the shift from contractions to recovery, opposed to Colombia, Chile and Mexico, do not depend on the recovery in other countries. For Argentina, both ÃŽ ³1,2 and ÃŽ ³2,2 is insignificant, implying any change in the regional cycle regional cycle is not sensitive to economic fluctuations in this country. Conclusion The papers other main finding is that a regional cycle could provide significant informational content in predicting the future state of the five of the largest Latin American economies—Argentina, Brazil, Venezuela, Chile, and Mexico. However, the amplitude and duration of the business cycle are asymmetric, indicating that nonlinearities are important in the growth process. Thus, since the Latin America countries’ business cycles are well-tied together through a regional cycle, the costs of joining a monetary union would be reduced if a deeper regional economic cooperation, including intra-exchange rate stability and macroeconomic policy coordination, before turning on to a full-fledged monetary union. Since the Latin American economies have historically been highly dependent globalization process and demand from outside trading partners it would be interesting repeating a similar exercise with interest rates and cyclical output in advanced countries. References Hamilton, J.D., 1989. A new approach to the economic analysis of nonstationary time  series and the business cycle. Econometrica 57, 357–384. Filardo, A.J., 1994. Business cycle phases and their transitional dynamics. J. Bus. Econ. Stat.  12, 299–308. [1] These countries have accounted for some 70 percent of the region’s GDP over the past half century (Maddison, 2003, pp. 134–140) [2] The lag structure has been tested with standard AIC, HQ and SC criteria. [3] The occurrence of a regime is referred by a variable st that takes two values: 1 if the observed regime is 1 and 2 if it is regime 2 [4] The lags in the model are chosen using the Akaike information criterion. Moreover, we perform the Ljung–Box (LB) test to check that there is no residual autocorrelation [5] In this case, The TVPMS model converges to the Hamilton fixed probability model

The Effects of Acid Rain on Statues :: Acid Rain Chemical Reactions Essays

The Effects of Acid Rain on Statues Introduction ------------ During this investigation, I will use dilute hydrochloric acid as the acid rain and crushed calcium carbonate as the chemical of the statues. Then I will time how long it takes for the limestone powder to react until there is no more left when the acid is added to it. Rain contains acid naturally as it collects carbon dioxide from the air and makes carbonic acid. Rain normally has a pH of about 5.5 – it is slightly acidic due to the carbon dioxide dissolved in it. It is a stronger acid if gases like sulphur dioxide and nitrogen oxides escape into the air from the burning fossil fuels, because they are dissolved by the rain and produce sulphuric and nitric acids that does more damage in a faster time. Acid rain reacts with statues and buildings that contain calcium carbonate and form carbon dioxide and water. The dilute hydrochloric acid in this investigation will have the same effect on the limestone as the acid rain on the statues. Yet, the only difference is that in nature, the acid rain reacted with the statue as a whole body, which takes approximately hundred years to corrode the object, whereas the hydrochloric acid in this investigation will take only few seconds to react with the limestone powder. Planning Aim --- The aim of my experiment is to investigate if the speed at which the limestones are dissolved is changed by how concentrated the acid is. Equipment To do my experiment, I will need beakers, a paper spoon, a stop clock, limestone powders, stirring rod, measuring cylinders and an electronic balance for powders Plan For this experiment, I will use 30mls of the acid each time and 1gm of powdered calcium carbonate. The concentration of the acid will be changed by adding water and less acid each time. First, I will use a paper spoon to spoon out the limestone powder and weigh it on the electronic balance. Next, take out the excess powder until the weight is 1gm. Then use two measuring cylinders, with each measuring the amount of water and dilute hydrochloric acid that should be added, e.g. when there is 30mls of acid, 0mls of water will be added; when there is 25mls of acid, 5mls of water will be added, and so on. The total amount will always be 30mls. Afterwards, I will pour the powder into a beaker that contain correct amount of acid in it and use a stop clock to time how long it will take for the powder to disappear. A stirring rod will be used so that no lumps would form.

Two factors which affected the Stuart economy of 1600-1660

The Stuart economy is always difficult to analyse. Unfortunately due to incomplete records we only have a rough idea of the economic growth that England underwent during this era. For example we do not have fully accurate records that state the exact population size at the time. We also therefore do not have accurate records on the economy either but from parish records and events during this period it is still possible to make informed conclusions on what the economy was like, and the factors that stimulated it. The first thing that is important to study when discussing the economy is the population size. According to records found in parishes at the time population was generally on the increase and rose from 4 to 5 million between 1600 and 1660. However although the population did rise considerably it was certainly not a steady increase and went through phases of decline as well as increase. Surprisingly, according to information now available, some year's burial rates were actually higher than baptism rates, suggesting a population decline. However due to the fact that these records are sometimes incomplete it is not possible to give completely accurate figures about the changes in population during this era. Some historians argue that these changes in population growth point to the fact that the Stuart economy was vastly agrarian. This theory is widely accepted as being true, it successfully answers the reason for very drastic changes in the population size in some areas as agrarian economy can be easily dislocated by bad winters and poor harvests. Also the records of bad harvests coincide with drops in population during this period, suggesting that the economy of the Stuart era was finding it very difficult to keep up with demand. In order to combat this rise in demand, farmers would need to innovate and experiment with new crops in order to compete. Some historians argue that this period due to the population increase led to a ‘farming revolution' as there is evidence that many villages adopted the concept of enclosure in order to become more productive. This commercialisation of farming is thought by many to be more popular than the previously adopted method of subsistence farming. (Growing enough to feed you and your immediate family. ) This technique of enclosure meant farmers were able to be more productive and meet higher demands and is generally accepted as a more efficient system than subsistence farming. This enclosure method of once community owned fields is thought to be the start of early capitalism in England, the commercialisation of the fields is therefore thought to be brought about by the pressures of a population on the increase. But were farmers of this period willing to innovate, experiment and try new techniques? Evidence found in the diary of an ordinary farmer of the period is a strong argument that farmers were willing to trial new crops. Robert Loder left a diary concerning his farming and the changes he made to his techniques and crops. It is possible to assume that this ordinary farmer was one of many who experimented in order to boost their production. However it is still possible to argue that there was a strong amount of conservative farmers who did not adopt these new techniques but there is no evidence to suggest this. Some historians also use examples such as the adoption of tobacco crops in England as a key piece of evidence for how adventuress and innovative farmers could be once convinced of the potential of the new farming enterprise. Despite the evidence presented for innovation and experimentation there is strong evidence that suggests that farmers struggled to keep up with demand. Sources found for some areas of England suggest that there were huge rises in prices during this period due to inflation. This evidence is known as the Phelps Brown price index. Although this is one of the most commonly used sources, due to lack of information it only covers certain areas of England, mainly the south meaning that it is hard to generalise these price rises across England however it is the best information available. This rise in prices is evidence suggesting that the farmers of the Stuart economy had great difficulty despite all their innovation and experimentation to keep up with demand. However some historians still disagree. So the key question still unanswered is whether the farmers were able to keep up with constantly growing demand. Obviously it is highlighted by bad harvests how susceptible the agrarian economy was to very cold long winters and the obvious problems this could create. However equally it can be argued that through innovation and experimentation farmers managed to meet demand, however evidence of heavy inflation during the Stuart period leads many historians to the conclusion that resources were scarce and that the economy due to reliance on uncontrollable variables such as weather was not able to keep up with demand. However on the other hand it is argued by some that the farmers willingness to implement new techniques and methods of farming lead to increased productivity and was able to keep up with increased demand. However due to lack of concrete evidence this issue is still in many historians' opinions open to interpretation. Another key factor in the development of the Stuart economy was industry. Although industry only made up for around 10% of the economy it is still an important area to analyse to have a full understanding of the economic changes to took place in the Seventeenth century. Firstly it is commonly thought that the English industrial techniques were inferior to those of Europe. Most goods were thought to have been produced at home and sold locally. This technique of production suggests an undeveloped industry in England, however these limitations in manufacturing were overcome via exportation to the advanced Europe. The main industry in England at this time was textiles, located in East Anglia. In this period unfinished woollen cloth would be produced and then exported to other countries in order to create a finished product, such as the Netherlands who were thought to be the leading industrial nation of the times. The reason for exporting was purely because England lacked the techniques and resources to manufacture such products. As farming was the leading source of income in England it is thought that many industrial workers were involved in agriculture as well as the manufacturing of textiles. Although many combined farming with manufacturing and production some did seek industry as full-time employment usually through the ‘putting-out system'. Besides textiles England also produced coal, mainly mined in the north-east of England. As London grew in population the North East was able to produce more and more coal to meet demands, although limitations in technology prevented mining below the surface. However transporting vast quantities of coal is thought by many historians to have been a problem. Roads in this period were thought to be in quite a bad state, and therefore much of the coal mined was transported by sea. This transportation via sea is important. In order to transport such great amounts of coal England you would need a merchant fleet and Royal Navy to provide protection. Despite these measures the fleets that travelled between the North-East and London still suffered attacks during the wars England had with the Dutch. This is evident when we look at the prices of coal and see that prices doubled during this period suggesting heavy losses from attack. In conclusion it is probably right to suggest that industry looked for short-term solutions to meet the demands it faced, although no new techniques or technological advances are evident, this period did see the development of external trade, a key feature of the Stuart economy with the development of overseas colonies. However it can be argued that changes in agriculture and innovation were more significant, however it is still somewhat important to understand that the Stuart economy did not just rely on agriculture alone.

Representation Of Love In A Midsummer Night Dream

In A Midsummer’s Night Dream, love is represented in many ways, but the overall representation of love is how fake and sophisticated it is. We can see in the play that love isn’t a conscious choice but a cruel game. The characters perfectly display how sophisticated and powerful love is, yet it is also confusing. Specifically, the relationship between Theseus and Hippolyta has no pure love involved in it. Theseus had to capture the Amazons in order to marry Hippolyta, which means he doesn’t have any real feeling towards Hippolyta. There are many aspects of how this complex or fake or forced love is represented. In the play we can quarrel about the complex and sophisticated element of love, why fake love is the most important representation†¦show more content†¦When we are introduced to Titania and Oberon we are also introduced to a dispute they are having. Give me that boy, and I will go with thee, but Titania refuses and leaves (2.1.128). Titania confer s the problems going on in the forest, but Oberon is only interested in the changeling boy. Oberon’s selfishness cause his love for Titania a problem. Towards the end when he finally gains possession of the boy Oberon states, And now I have the boy, I will undo/ This hateful imperfection of her eyes: (4.1.46) Therefore, he loves Titania only because he has gotten possession of the boy and that is not a sign of easy going love but only selfishness. Hence, these three instances, state how eminently complex and sophisticated love is in the play. We see a lot of examples of fake or forced love throughout the play that make fake love an assertive representation of love throughout the book. Firstly, Hermia’s father Egeus is forcing her to marry Demetrius, while she wants to marry Lysander. â€Å"You can endure the livery of a nun, for aye to be in shady cloister mewed, to live a barren sister all your life.† (1.1.70-73) Theseus gave her three options to die, marry Demetrius, or become a widow. She refuses and runs away with Lysander to his aunt’s house. In this example, we can see Hermia is forced to love someone she does not. Another example of forced love can be seen when Oberon enchants Demetrius after seeing him be abhorrent towards Helena. So, sinceShow MoreRelatedEssay on Analysis of Rationality In A Midsummer Nights Dream1058 Words   |  5 PagesWilliam Shakespeare’s A Midsummer Night’s Dream is not simply a light-hearted comedy; it is a study of the abstract. Shakespeare shows that t he divide between the dream world and reality is inconstant and oftentimes indefinable. 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