Study On Faith Seeking Understanding Theology

Study On Faith Seeking Understanding Theology Daniel L. Migliore in the book he authored, the 2nd edition of Faith Seeking Understanding: An Introduction to Christian Theology, made an effort to strengthen the fullness of Trinitarian faith and its relational understanding of God, creation, reconciliation, and consummation. It is an expanded and updated version to the earlier edition which presents a foreword to Christian Theology that is both critically respectful of the classical theological tradition and critically open to the new voices and emphases of recent theology. As an introduction to Christian Theology, Faith Seeking Understanding contains fundamentally theological themes which are catholic in nature and critical of the beliefs and way of living of the faith community. Its basic coverage makes it suitable to first readers in theology and its criticism from the liberal theologians point of view recommends reflection to renew and rethink the beliefs and practices of traditionalists or of those who observe the beliefs and practices they had but have totally forgotten the core message of what they believe and practice. In line with the spirit of optimism, humility of heart and open-mindedness, the criticisms employed, having their respective criterion, entails a challenge to rediscover the journey of faith. Upon reviewing it, one was reminded that a believer in the true sense is a learner who constantly looks for the truth and searches for the way. As the impetus of various theological movements became obvious, the first edition of the Faith Seeking Understanding was born in the immediate context of the mainline Protestant church in North America. The authors reflections on the inseparability of faith and practice were formed in a small Presbyterian congregation in Pennsylvania. Unsatisfied with its inadequacy in the present human situation of widespread anxiety and insecurity, Migliore brought to existence these updated and expanded edition. This was done to respond to the need of the church especially in times of crisis where clarity of conviction and purpose is certainly necessary in this time of uncertainty. In order to obtain a better understanding of the values it points, one needs to notice where the author with his reflections is coming from. Three methods were utilized and influenced its contents in one way or another. First, theology was presented in a way that highlighted the Word of God posing questions to man. Second, theological questions were formulated by an analysis of the human situation in a given period as seen in its philosophy, literature, art, science, and social institutions. Lastly, praxis approach of liberation theology is apparent. Faith Seeking Understanding discusses the importance and purpose of the pursuit of faith for understanding. Here and now, faith sees only dimly and the questions of faith abound. There are events that will challenge our beliefs and practices which may, at the same time, open us up to a praxis that may overcome evil and suffering, violence and ambiguity. Faith seeks understanding not for the sake of obtaining knowledge but seeks wisdom that will illumine life and practice of Christian virtues. It is not speculative knowledge! Quoting various philosophers, theory without practice is empty, practice without theory is blind. When faith is rethought and understanding of it is sought, its purpose and meaning gains clarity. The author provides sources from which believers may claim to have knowledge of God in relation to human condition. It does not confirm what we already know about Him rather utterly surprises and disturbs a believer. God reveals himself but remains hidden. As Tersteegen states, A God comprehended is no God. Understanding of faith does not mean to know all the known and the unknown but the application of what was understood in service of God and his creation. Although man cant fully understand God or faith, the seeking is not a waste but leads one to become a better person with better understanding and better witnessing with an open mind and a humble heart. The Triune God revealed and celebrated in Jesus Christ by the power of the Holy Spirit attested by the Sacred Scripture viewed through the eyes of those who are suffering and weak connects the main points. It tells the reader that the understanding of God is always an initiative of God! Mans is a response. The tradition of faith is interpreted from its center, in Jesus Christ, allowing Him to become a transforming power in human life. Faith seeks development not in theory but through personal encounter and witnessing of God sought through faith. This lays down the liberating love that creates a new community. In this time of crisis, in a world characterized by violence, nuclear threats, ecological crisis, spiritual confusion and what not, a right understanding of the confession of faith in God the Creator is perhaps more important today than ever before. A Christian faith that seeks understanding clearly emboldens, sharpens and makes patent its identity respecting the character of other religions. Understanding may be achieved through attentive and trustful reading and hearing of the witness of scripture in company with other members of the people of God. Faith Seeking Understanding truly captured its purpose of reexamining faith in order to appreciate it fully and become an active and responsible believer who consciously recognize our identity as we freely respond in faith and in joyful hope of discovering the truth of what was handed to us and what was hidden from us. This will help us posses a new perspective and a new criterion of understanding. There is so much to discover in faith thus the use of intelligence is essential to avoid reducing faith into a euphoric feeling. There is lot of things to learn about the Triune God thus we are in need to intensify our witnessing of charity. As Pope Benedict XVI states in his Apostolic Letter Porta Fidei, Faith is choosing to stand with the Lord so as to live with him, this standing with Him points towards and understanding of the reasons for believing. Faiths real prize is not realized until its worth is examined. Faith Seeking Understanding by Daniel L. Migliore proves to be a timely response to the signs of the time as the world encounters crisis of ambiguity and precariousness. The honesty of the author is to be commended for there is no pretension as he acknowledges that some topics remain broken and incomplete. However, it is also just to subject the criticism of the author into criticism for he is also doomed to human condition. In addition, Catholic readers should remember the background of the author to reconsider the apparent biases towards Catholicism.

Indian Education Essay

A strong education system is the cornerstone of any country’s growth and prosperity. Over the last decade, India has made great strides in strengthening its primary education system. The District Information System for Education (DISE) reported in 2012 that 95% of India’s rural populations are within one kilometer of primary schools. The 2011 Annual Status of Education Report (ASER), which tracks trends in rural education, indicated that enrollment rates among primary-school-aged children were about 93%, with little difference by gender. However, behind the veil of such promising statistics, the learning outcomes of India’s children show little progress. The country ranked 63 out of 64 in the latest Program for International Student Assessment (PISA) study, with some of its best schools ranked about average among those surveyed. The 2011 ASER stated that only 48. 2% of students in the fifth grade can read at the second grade level. The number of students completing their primary education with inadequate numeracy and literacy skills is startling. To see this manifest in an economic sense, one may attribute India’s productivity growth — lagging behind that of East Asian economies — to a lack of progress in the foundational elements of countrywide, high-quality education. India’s private-schooled, English-speaking urban elite may attract global attention, but they are in the minority. The vast majority of Indian children attend government-run primary schools in rural areas. In 2008-2009, rural India accounted for more than 88% of India’s primary-school students, of whom over 87% were enrolled in government-run schools. This is where we see some of the nation’s toughest challenges. A Diverse Set of Problems India’s education system has not achieved strong learning outcomes for reasons that are as diverse and nuanced as the country itself. Key among these reasons is poor teaching quality, which results from a multitude of factors. Inadequate Teacher Qualification and Support: Teachers working in primary schools across rural India have a difficult job. Dhir Jhingran, a senior civil servant in the Indian Administrative Service, with more than two decades of experience in rural primary education, explained the multiple challenges they face: â€Å"Teachers have to teach multiple grades, textbooks are pitched far above the comprehension level of students, and each classroom has children with different levels of learning achievements. † Anurag Behar, CEO of the Azim Premji Foundation, an education non-profit, noted that â€Å"the average school teacher in India does not get adequate pre-service or in-service education, nor does she get the support to overcome these problems. † Compounding this is the relatively low educational qualifications of many teachers themselves. In 2008-2009, on average, 45% of these teachers had not studied beyond the 12th grade. Low Teacher Motivation and High Absenteeism: A key factor affecting the quality of primary education appears to be low levels of teacher motivation. In 2002-2003, 25% of primary-school teachers in rural India were absent on any given day. The impact of absenteeism is exacerbated by the fact that the average primary school in India has a workforce of no more than three teachers. At a school for girls in rural Rajasthan, we observed this problem first hand: Of the eight teachers assigned, only five were present. The three who were actually teaching were juggling eight different grades. The obvious reason — remuneration — does not appear to be a driver. In fact, both education experts and ordinary citizens argue that government-employed school teachers are paid relatively well. UNESCO surveys from as early as 2004 indicated that the annual statutory salary of primary school teachers in India with 15 years’ experience was more than $14,000, adjusted for purchasing power. This was significantly higher than the then-statutory salaries of $3,000 in China and Indonesia, and the Indian GDP per capita in 2004, which was $3,100. Indian primary-school teachers may not be underpaid, but some argue that they may be overworked. For Vivekanand Upadhyay, a seasoned educator and language professor at a leading national University, one reason for the lack of motivation is that â€Å"primary school teachers employed by the government, particularly in rural India, are required to perform a wide range of duties completely unrelated to imparting education. † These duties — including administering government programs such as immunization clinics, assisting with data-collection for the national census, and staffing polling stations during elections — in addition to their teaching responsibilities, place significant demands on teachers’ time. Another disheartening factor has been a highly bureaucratic administrative system that discourages bold decision making and makes implementation difficult. For example, as Jhingran observed, â€Å"it is difficult to test new practices on a small scale before rolling them out: If a new program has been developed, the philosophy is that every school must have it. † Such indiscriminate application often means that teachers are implementing programs without understanding their key principles and ultimate goals. Flawed Teaching Methodology: In India, rote learning has been institutionalized as a teaching methodology. â€Å"Primary school teachers in rural India often try to educate students by making them repeat sections of text over and over again,† said Jhingran. Often they do not explain the meaning of the text, which results in stunted reading comprehension skills over the course of the children’s education. For example, many students in grades two and three in one particular school struggle to read individual words, but can neatly copy entire paragraphs from their textbooks into their notebooks as though they were drawing pictures. Linguistic Diversity: Finally, India’s linguistic diversity creates unique challenges for the nation’s education system. The country’s 22 official languages and hundreds of spoken dialects often differ considerably from the official language of the state or region. Jhingran commented that â€Å"the teacher not only has to account for varying learning abilities within the classroom, but also dialectic nuances which affect students’ comprehension of the subject matter. † Government-school-educated children from rural India struggle to speak even basic sentences in English. â€Å"Students with rural primary schooling are at a significant disadvantage as they transition to higher education, because India’s best universities teach exclusively in English,† said Upadhyay. Part of the problem is that there is no one to teach them. As Chandrakanta Khatwar, an experienced middle school teacher in a rural government-run school in Rajasthan, asked: â€Å"When teachers themselves know little English, especially spoken English, how will students learn? † A Parallel, Non-governmental Education Universe Since the late 1980s, government efforts to augment rural primary education have been supplemented by the emergence of an intervention-based non-governmental system that spans multiple institutional types. While private schools have emerged as a parallel system over the last two decades, their impact is limited because they serve less than 13% of India’s rural primary-school children. However, do private schools really make a difference? Some studies have found a small, but statistically significant, â€Å"private school advantage† in rural India. Behar was skeptical about the superiority of private rural schools over their government-run counterparts, noting, â€Å"Once we control for a child’s socioeconomic background, private schools add little-to-no value. In many ways, private schools are in much worse shape. † However, according to Khatwar, â€Å"more and more parents in small towns are choosing to send their children to private schools if they can afford it† — perhaps with good reason, because, on average, the number of students in each classroom in private schools is often smaller and school heads exert greater control over teachers. Some organizations are attempting to innovate with new formats and systems of education. Avasara Academy, a new school for girls, is a private institution whose mission is to mold leaders from among the best and brightest girls in India, regardless of their background. While admission is merit-based, the school intends to draw half its students from disadvantaged rural and urban backgrounds, awarding them full scholarships. In addition, it is developing a special curriculum that encourages excellence beyond academics. â€Å"Avasara seeks to identify high potential young women and guide them along a powerful journey of leadership development. We expect that our graduates will form a network of leaders who will collaborate to drive positive change across the country,† explained Mangala Nanda, humanities department chair for Avasara. While still in the early stages of its development, Avasara’s successful implementation would provide a viable model for high-quality, accessible education and integration across socioeconomic boundaries. Governmental Efforts The Indian government at every level recognizes the need for educational reform and has made a conscientious effort to achieve it. The midday-meal plan, for example, is a highly publicized nationwide program through which government school children across India are provided with a midday meal every day of the school week. The program is largely considered a success. A study in 2011 by Rajshri Jayaraman and Dora Simroth found that grade one enrollment increased by 20. 8% simply if a midday meal was offered. According to Behar, â€Å"The Indian government has worked very hard to provide rural schools with adequate infrastructure, something that was critically lacking a few decades ago. † For instance, DISE reported in 2012 that more than 91% of primary schools have drinking-water facilities and 86% of schools built in the last 10 years have a school building. However, there is still a long way to go: Only 52% of primary schools have a girls’ toilet, and just 32% are connected to the electricity grid. In 2012, the Central Government enacted the Right to Education (RTE) Act, under which every child between the ages of six and 14 receives a free and compulsory education. In addition to regulating access to education, the act contains certain provisions that could positively impact the quality of education. According to Jhingran, one of its major achievements has been â€Å"the dramatic reduction of non-teaching duties assigned to government school teachers, freeing up valuable time and lowering absenteeism. † Partnering with the Government Over the past few decades, many organizations have begun working with government schools and teachers to improve learning outcomes. Pratham, a joint venture between UNICEF and the Municipal Corporation of Mumbai, runs multiple programs to supplement school education, such as learning support classes, libraries and additional learning resources. A hallmark of these initiatives is that Pratham engages volunteers from local communities and trains them to run these programs. Another important initiative that has resulted from Pratham is the annual ASER, an assessment that measures reading and arithmetic abilities by surveying more than 600,000 children across 16,000 villages in India. This remarkable exercise in data-gathering constitutes the foundation for informed decision-making and benchmarking. Other initiatives address teaching quality by placing specially trained teachers in government schools. Teach for India, modeled after the Teach for America program, was introduced in 2006. Young, motivated Indian college graduates and professionals apply for two-year fellowships to teach at government-run and low-income private schools that lack sufficient resources. An important distinction of Teach for India is that instruction is, by design, always in English. As Mohit Arora, fellowship recruitment manager for Teach for India, noted, the organization’s philosophy on this point is that â€Å"learning English is essential to future success, as English in today’s world is more than just a language. It is a skill set. † Students who do not speak English may have some difficulty initially, but the organization has made learning at these schools experiential and therefore engaging. The dynamics of one particular grade 3 Teach for India classroom were in stark contrast to other classrooms at the same school — students were listening intently, contributing in class, answering questions beyond the textbook and demonstrating a strong command over English. The challenge is scaling this model to rural India. Still other organizations focus on capacity development of teachers in government schools, such as the Azim Premji Foundation. As CEO, Behar is categorical in his view that the foundation â€Å"works in partnership with the government,† and that it â€Å"does not believe in supplanting the government school system. † The foundation has established scores of institutes at the district level that provide in-service education and also empower teachers to learn from each other. For example, Behar described a voluntary teacher forum in a district of Rajasthan, initially organized by the Azim Premji Foundation, but now being run increasingly independently by teachers in the district. The Future of Primary Education in India Education in India has improved dramatically over the last three decades. Schools are accessible to most children, both student enrollment and attendance are at their highest level, and teachers are adequately remunerated. The RTE Act guarantees a quality education to a wider range of students than ever before. However, challenges in implementing and monitoring high standards in teaching and learning outcomes across regional, cultural and socioeconomic subsets prevent India from fully achieving this goal. In addition, teacher support and scalability of high-performing teaching professionals in disparate areas, funding allocation for schools in remote districts and limited use of technology in the classroom remain barriers to reforming primary education. India’s growth story remains one of the most anticipated global economic trends, and its fulfillment relies on a well-educated and skilled workforce. Improving education is a critical area of investment and focus if the country wants to sustain economic growth and harness its young workforce. A weak foundation in primary education can derail the lives, careers and productivity of tens of millions of its citizens. Already, a significant proportion of the adult workforce in India is severely under-equipped to perform skilled and semi-skilled jobs. As Rajesh Sawhney, former president of Reliance Entertainment and founder of GSF Superangels, noted, â€Å"No one is unemployed in India; there are just a lot of people who are unemployable. † Furthermore, in order to develop India as a consumer market of global standards, it is imperative that all of its children reap the full benefits of a high-quality education. Otherwise, large segments of the population in rural India will continue to have low purchasing power, find themselves in highly leveraged scenarios and, more often than not, continue to make a living through agricultural means. While some of this can be attributed to deficiencies in secondary and tertiary education, the root of these issues lies in low-quality primary education.

Study On Monetary Policy And The Stock Market - Free Essay Example

Sample details Pages: 18 Words: 5331 Downloads: 5 Date added: 2017/06/26 Category Economics Essay Type Analytical essay Did you like this example? Monetary policy is the regulation of the interest rate and money supply of a country by its Central Bank or Federal Reserve in other to achieve the major economic goals which include price stability, full employment, economic growth etc.  Ãƒâ€šÃ‚   The stock market on the other hand is often considered a primary indicator of a countryà ¢Ã¢â€š ¬Ã¢â€ž ¢s economic strength and development as it is a major source of savings and income for most individuals. History has shown that the economy of any country reacts strongly to movements in stock prices and is replete with examples in which large swings in stock, housing and exchange rate markets coincided with prolonged booms and busts (Cecchetti, Genberg, Lipsky and Wadhwani, 2000). Recent happenings even confirm this as the latest economic recession was preceded by a crash in the stock market. Don’t waste time! Our writers will create an original "Study On Monetary Policy And The Stock Market" essay for you Create order As a result of the relationship between the stock market and the economy, it is very important to the Central bank that the stock market performs well as bad performance can seriously disrupt the economy. This is because the stock market serves as a primary source of income and retirement savings to many and movements in stock prices can have a major effect on the economy as it influences real activities such as consumption, investments, savings etc While some economists say that monetary policy decisions depend on stock price movements, some others believe that stock price movements depend on monetary policy decisions. In this paper, we analyze both sides of the coin by looking at how stock markets react to monetary policy and how monetary policy reacts to movements in stock markets. This research work is aimed at finding out which granger causes which using the Granger Causality test. We will also analyze the relationship between both interest rates and monetary policy and th at between money supply and monetary policy. In section II, a thorough review of the relevant literature of the topic is carried out as we try to understand more about the relationship between monetary policy and the stock market and the effects of both components (money supply and interest rates) of monetary policy 0n the stock market. In the next section, we describe the variables and data set used in the study and the empirical model is developed. Results are presented and discussed in the next section. We conclude the paper in section V and suggestions for further studies are pointed out and policy implications are considered. REVIEW OF RELEVANT LITERATURE Monetary policy is one of the most effective tools a Central Bank has at its disposal (Maskay, 2007) and is used to achieve the macroeconomic goals set by the government. This is done by regulating the two components of monetary policy which are interest rates and money supply to maintain balance in the economy. The stock market is an important indicator of the wellbeing of the economy as stock prices reflect whether the economy is doing well or not. Movements in stock prices have a significant impact on the macroeconomy and are therefore likely to be an important factor in the determination of monetary policy (Rigobon and Sack, 2001). The stock market is a financial market where equities are bought and sold either as an IPO (Initial Public Offer) in the primary market or exchange of existing shares between interested parties in the secondary market. Although stocks are claims on real assets and researchers have found considerable evidence that monetary policy can affect real stock prices in the short run (e.g Bernanke and Kuttner, 2005), monetary neutrality implies that monetary policy should not affect real stock prices in the long run (Bordo, Dueker and Wheelock, 2007). To understand the relationship between monetary policy and the stock market, we must first understand what monetary policy is. Lamont, Polk and Saa-Requejo (2001), Perez-Quiros and Timmerman (2000) among others use change in market interest rates or official rates as their measures of monetary policy. This measure of monetary policy, however, coincides with changes in business cycle conditions and other relevant economic variables. Christiano, Eichenbaum and Evans (1994) extracted monetary policy as the orthogonalized innovations from VAR models proposed by Campbell (1991) and Campbell and Ammer (1993). Research methodology based on this has shown that the response of US stocks returns to monetary policy shocks based on federal fun rates show that returns of large firms react less strong ly than those of small firms (Thorbecke, 1997), that the overall policy for stock returns is quite low ( Patelis, 1997) and that international stock markets react to both to changes in their local monetary policies and that of the United states ( Conover, Jensen and Johnson ( 1999). Monetary policy shocks that are extracted from structural VAR models or from changes in interest rates using monthly or quarterly data are likely to subject to the endogeneity problem i.e they are unlikely to be purely exogenous ( Ehrmann and Fratzscher, 2004). Another VAR-based method was used by Goto ad Valkanov (2000) to focus on the covariance between inflation and stock returns while Boyd, Jagan and Hu (2001) considered the linkages between policy and stock prices. Their analysis did not focus directly on monetary policy; rather it focused on marketà ¢Ã¢â€š ¬Ã¢â€ž ¢s response to employment news (Bernanke and Kuttner, 2005). In their own research paper, Ehrmann and Fratzscher (2004) find that SP 500 shows a strong effect of monetary policy on equity returns, that the effect of monetary policy is stronger in an environment of increased market uncertainty, that that negative surprises ( i.e monetary policy has tightened less and loosened more than expected) has larger effects on the stock market than positive surprises, that small firms are react more to policy shocks than large firms, that firms with low cash flows are affected more by US monetary shocks and that firms with poor ratings are more prone to monetary policy shocks than those with good ratings. They find that firms react more strongly when no change had been expected, when there is a directional change in the monetary policy stance and during periods of high market uncertainty. There has also been cross-sectional dimensions of the effect of monetary policy on the stock markets in literature though few. Hayo and Uhlenbruck (2000), Dedola and Lippi (2000), Peersman and Smets ( 2002), Ganley and Salmon (1997) etc are some economists who have analyzed this and overall, their findings show that the stock prices of firms in cyclical industries, capital-intensive industries and industries that are relatively open to trade are affected more strongly by monetary policy shocks (Ehrmann and Fratzscher, 2004). According to Bernanke and Kuttner (2005), changes in monetary policy are transmitted through the stock market via changes in the values of private portfolios (à ¢Ã¢â€š ¬Ã…“wealth effectà ¢Ã¢â€š ¬?), changes in the cost of capital and by other mechanisms. In their paper, they analyzed the stock markets response to policy actions both in the aggregate and at the level of industryà ¢Ã¢â€š ¬Ã¢â€ž ¢s portfolios and they also tried to understand the reasons for the stock markets response. Their findings show that monetary policy is, for the most part, not directly attributable to policyà ¢Ã¢â€š ¬Ã¢â€ž ¢s effects on the real interest rate instead it seems to come either through its effects o n expected future excess returns or expected future dividends. While economists commonly associate restrictive/expansive monetary policy with higher/lower levels of economic activity, financial economists discuss various reasons why changes in the discount rate affect stock returns. (Durham, 2000) Changes in the discount rate affect the expectations of corporate profitability ( Waud, 1970) and discrete policy rate changes influence forecasts of market determined interest rates and the equity cost of capital ( Durham, 2000). Modigliani (1971), suggests that a decrease in interest rates boosts stock prices and therefore financial wealth and lifetime resources, which in turn raises consumption through the welfare effect. Mishkin (1977) on the other hand suggests that lower interest rates increase stock prices and therefore decrease the likelihood of financial distress, leading to increased consumer durable expenditure as consumer liquidity concerns abate (Durham, 2000). Tobins q is the equity market value of a firm divided by its book value. It can also be defined as the ratio of the market value of a firmà ¢Ã¢â€š ¬Ã¢â€ž ¢s existing shares to the replacement cost of the firmà ¢Ã¢â€š ¬Ã¢â€ž ¢s physical assets. Higher stock prices reduce the yield on stocks and reduce the cost of financing investment spending through equity issuance (Bosworth, 1975). Tobins q explains on e of the mechanisms through which movements in stock prices can affect the economy: the wealth channel. The other channels of monetary policy transmission include; the interest rate channel and the exchange rate channel. The wealth channel has the investment effect, wealth effects and balance sheet effects (www.oenb.at/en). Bernanke and Blinder (1992) and Kashyap, Stein and Wilcox (1993) show that a tightening of monetary policy has a very strong impact on firms that highly depend on banks loans to financing their investments as banks reduce their overall supply of credit. Deteriorating market conditions affect firms by also weakening their balance sheets as the present value of collateral falls with rising interest rates and that this effect can be stronger for some firms than for others (Bernanke and Gertler 1989, Kiyotaki and Moore 1997). These two arguments are based on information asymmetries as firms for which more information is publicly available may find it easier to collect loans when credit conditions become tighter (Gertler and Hubbard 1988, Gertler and Gilchrist 1994).Stock returns of small firms generally respond more to monetary policy than those of large firms ( Thorbecke 1997, Perez-Quiros and Timmermmann 2000). Some economists (Sprinkle (1964), Homa and Jaffee (1971), Hamburger and Kochin (1972)) in the early 1970,s alleged that past data on money supply could be used to predict future stock returns. These finding where not in line with the efficient market hypothesis which states that all available information should be reflected in current pr ices (Fama, 1970) meaning that anticipated information should not have any effect on current stock prices. Most economists believe that stock prices react differently to the anticipated and unanticipated effects of monetary policy ( Maskay, 2007). The Keynesian economists argue that there is a negative relationship between stock prices and money supply whereas real activity theorists argue that the relationship between the two variables is positive (Sellin, 2001). The Keynesian economists believe that a change in money supply or interest rates will affect stock prices only if the change in the money supply alters expectations about future monetary policy while the real activity economists argue that increase in money supply means that money demand is increasing in anticipation of increase in economic activity (Maskay, 2007). Another factor discussed by Sellin (2001) is the risk premium hypothesis proposed by Cornell i.e higher money supply indicates higher money demand and higher money demand suggests increased risk which leads investors to demand higher risk premiums for holding stocks making them less attractive. The real activity and risk premium hypothesis is combined by Bernanke and Kuttner (2005) who argue that the price of a stock is a function of the present value of future returns and the perceived risk in holding the stock. While advocates of the efficient market hypothesis hold that all available information is included in the price of a stock, the opponents argue otherwise and that stock prices can also be affected by unanticipated changes in money (Corrado and Jordan, 2005). The effect of anticipated and unanticipated changes in money supply on stock prices was analyzed by Sorensen (1982) who found out that unanticipated changes in money supply have a larger impact on the stock market than anticipated changes. Bernanke and Kuttner (2005) on the other hand analyze the impact of announced and unannounced changes in the federal funds rate and f ind that the stock market reacts more to unannounced changes than to announced changes in the federal funds rate which is also in line with the efficient market hypothesis. Studies by Husain and Mahmood (1999) have opposing results. They analyze the relationship between the money supply and changes (long run and short run) in stock market prices and find that changes in money supply causes changes in stock prices both in the short run and long run implying that the efficient market hypothesis does not always hold. Maskay(2007) analyzes the relationship between money supply and stock prices. He also seperates money supply into anticipated and unanticipated components and adds consumer confidence, real GDP and unemployment rate as control variables. The result from his analysis shows that there is a positive relationship between changes in the money supply and the stock prices thereby supporting the real activity the theorists. The result from his analysis on the effect of anticipa ted and unanticipated change in the money supply on stock market prices shows that anticipated changes in money supply matters more than unanticipated changes. This supports the critics of the efficient market hypothesis. According to Cecchetti, et al. (2000), macroeconomic performance can be improved if the central bank increases the short-term nominal interest rate in response to temporary à ¢Ã¢â€š ¬Ã…“bubble shocksà ¢Ã¢â€š ¬? that raise the stock price index above the value implied by economic fundamentals. On the other hand, Bernanke and Gertler (2001) assumed in their research that the Central Bank cannot tell whether an increase in stock prices is driven by a bubble shock or a fundamental shock. This study will analyze both exogenous and endogenous components of the relationship between monetary policy and the stock market i.e the effect of monetary policy on the stock market and the the effect if any of the stock market on monetary policy decisions. This particular analysis will be done using the federal funds rate as a representative of monetary policy. We also follow the methodology used by Maskay (2007) closely as we try to find the effect of money supply on the stock market. Although Maskay used M2 as a measure of money supply, this study will separate money supply into M1 and M2 and analyze their relationship with the stock prices. Following from the theory and review of literature, this paper is aimed at answering the following questions: How do movements in the stock market affect monetary policy decisions on federal funds rates? How does monetary policy affect stock market prices? Do stock market prices react differently to the M1 and M2 components of money supply? RESEARCH METHODOLOGY The effect of stock market prices on monetary policy. In this section, I test for the relationship between monetary policy and stock prices using the Taylor rule. The Taylor rule is a monetary policy rule that stipulates how much the central bank would or should change the nominal interest rate in response to the divergence of actual inflation rates from target inflation rates and of actual GDP from potential GDP. The rule is written as; it = r*t + ÃŽÂ ² (à Ã¢â€š ¬ tà ¢Ã¢â€š ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t) +ÃŽÂ ³ (yt Ã…Â ·t)à ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦.. (1) Where; it = target short-term nominal interest rate. r*t = assumed equilibrium real interest rate. à Ã¢â€š ¬t = the observed rate of inflation. à Ã¢â€š ¬*t = the desired rate of inflation. yt = the logarithm of real GDP. Ã…Â ·t = the potential output. But, to analyze the behavior of monetary policy, the following regression equation is estimated; it = ÃŽÂ ± + ÃŽÂ ²Et(à Ã¢â€š ¬ t+ià ¢Ã¢â€š ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t+i) +ÃŽÂ ³Et (yt+i+ Ã…Â ·t+i)+ÃŽÂ µt à ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦..(2) Where: Et = the expected value conditional to information available at the time. A good conduct of monetary policy should have ÃŽÂ ² and ÃŽÂ ± each equal to 0.5 as suggested by John Taylor. To conduct our study, we use the following equation; it = ÃŽÂ ± + ÃŽÂ ²Et(à Ã¢â€š ¬ t+ià ¢Ã¢â€š ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t+i) +ÃŽÂ ³Et (yt+i+ Ã…Â ·t+i)+à ¢Ã‹â€ Ã¢â‚¬ËœÃƒÅ½Ã‚ ´k à Ã¢â‚¬ ¦t-k + ÃŽÂ µt ..(3) Because the monetary authorities target variables other than inflation and output deviations from the target (asset prices in this case) thereby making equation (2) mis-specified. A standard Taylor rule is well specified when the monetary authorities target only inflation and output deviations from the target. The addition to this variable is the lagged change in asset prices which is added in order to determine the relationship between monetary policy and stock prices. The data for the CPI (Consumer Price Index), real GDP (Gross Domestic Product) and the federal funds rate are obtained from the IMF Washington website while the data for SP 500 Index are obtained from the Federal Reserve Economic Data (FRED) of the Federal Reserve Bank of St Louis website; www.federalreserve.gov. The effect of monetary policy on stock market prices. In this section, we test whether movements in stock prices are sometimes dependent on monetary policy. This test is carried out by regressing the actual change in federal funds rates upon the SP 500 index. We us the following simple model for this purpose: SP500 = ÃŽÂ ²1 + ÃŽÂ ²2*actual change in federal funs rate + ÃŽÂ ²3*real GDP + ÃŽÂ ²4* unemployment rate. Real GDP and Unemployment rate are added as control variables. The data for real GDP is obtained from IMF, Washington while the data for unemployment rates in obtained from www.federalreserves.gov. We add GDP because it is an important determinant of the stock prices as most industries react to changes in the economy and do well as the economy does well and vice versa i.e they are procyclical in nature. When the GDP is low, the stock prices generally tend to be low, as the companyà ¢Ã¢â€š ¬Ã¢â€ž ¢s performance would be worse than before. A direct, positive relationship is expected between stock prices and the GDP. Unemployment rate is also used as a control variable in this model because it is one of the major factors that determines the demand for stocks thereby either driving the stock prices up or down. When the unemployment rate is high, demand for stock reduces as less people can afford to buy them and this subsequently drives down stock prices and vice versa. The unemp loyment rate is also a proxy for for overall aggregate demand in the economy ( Maskay, 2007) and when it is low, aggregate demand is high. We expect an inverse relationship between the unemployment rates and stock prices. The effect of M1 and M2 components of money supply on stock prices. In this section, we test the relationship between monetary policy and stock prices from the money supply angle of monetary policy. We use the M1 and M2 components of money supply for this analysis. This is done by first testing the relationship between the percentage change in M1 and the stock prices and then testing the relationship between M2 and the stock market. The simple empirical model used for this test is; SP500 = ÃŽÂ ²1 + ÃŽÂ ²2*%à ¢Ã‹â€ Ã¢â‚¬  M1 + ÃŽÂ ²3*Real GDP + ÃŽÂ ²4*Unemployment rateà ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦.. (1) SP500 = ÃŽÂ ² 1+ ÃŽÂ ²2*%à ¢Ã‹â€ Ã¢â‚¬  M2 + ÃŽÂ ²*3Real GDP + ÃŽÂ ²4*Unemployment rateà ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦.. (2) Unemployment rate and real GDP are also used here as control variables for the same reasons given above. The data on percentage change in M1 and M2 were obtained from Federal Reserve Economic Data from the website of the Federal Reserve Bank of St. Louis. We were able to get the monthly data of M1 and M2 and then got the quarterly averages to produce the quarterly data. DATA DESCRIPTION In this section, we define and describe the various data used in this study. We used quarterly data from 1990 to 2009. The variables used in this analysis include; The Federal Funds Rate; The federal funds rate is a monetary policy tool used by the Central Bank/Federal reserve of the country to regulate the economy. Economists believe it has an inverse relationship with stock prices as because when there is an upward movement in stock prices above the desirable level, the federal reserve increases (contractionary) the federal funds rate . This leads to a decrease in the amount of money demanded by individuals thereby causing a lower demand for stocks and pushing down stock prices. We obtained data on the federal funds rate from the website of the federal reserve bank of Louisiana. 2. The Consumer Price Index; A consumer price index (CPI) is an index that estimates the average price of consumer goods and services purchased by households. It is used in our study to calculate inflation. We do this using the eviews software (100 ÃÆ'— (cpi à ¢Ã¢â€š ¬Ã¢â‚¬Å" cpi ( -4)). We obtained the quarterly data on CPI from the website of the International Monetary fund in washington. The CPI has an inverse relationship with monetary policy actions. 3. Real Gross Domestic Product (Real GDP); This can be defined as a measure which adjusts for inflation and reflects the value of all goods and services produced in a given year, expressed in base year prices. Real GDP provides a more accurate figure as it accounts for changes in the price level. The quarterly data on Real GDP is obtained from the website of the International Monetary Fund, Washington. 4. SP 500; It is a capital weighted index of the prices of 500 large-cap common stocks actively traded in the United States. It is believed to have an inverse relationship with monetary policy as an expansionary (interest rate reduction) monetary policy leads to an upward movement of the sp500 index. The quarterly data for the sp500 is obtained from the federal reserve bank of Louisiana. 5. Unemployment Rate; The unemployment rate is used as one of the control variables. It is an important indicator of the wellbeing of an economy. The lower the unemployment rate, the higher the aggregate demand for stock thereby pushing up stock prices. The quarterly data on unemployment rate is obtained from the website of the Federal Reserve Bank of Louisiana. We get the quarterly data by finding quarterly averages from the monthly data provided. 6. Monetary aggregates à ¢Ã¢â€š ¬Ã¢â‚¬Å" M1 and M2; M1 is a monetary aggregate and it includes the transaction deposits of banks and cash in circulati on and all other money equivalents that are easily convertible into cash while includes M1 plus short-term deposits in banks and 24-hour money market funds. Money supply has a positive relationship with stock prices because the higher the money supply, the higher the demand for stock which eventually increases stock prices. We split money supply into M1 and M2 to find out if they have the same relationship with stock prices. The quarterly data on percentage change in monetary aggregates is obtained from the website of the federal reserve bank of Louisiana. We also had to calculate the quarterly averages of the monthly data given. DATA ANALYSIS Model 1: The Taylor rule it = r*t + ÃŽÂ ² (à Ã¢â€š ¬ tà ¢Ã¢â€š ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t) +ÃŽÂ ³ (yt à ¢Ã¢â€š ¬Ã¢â‚¬Å" Ã…Â ·t)+ ÃŽÂ µt Dependent Variable: FED_FUNDS_RATE Method: Least Squares Date: 07/05/10 Time: 20:19 Sample(adjusted): 1991:1 2009:4 Included observations: 76 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. C 3.615513 1.220783 2.961634 0.0041 INFLATION 0.684264 0.156212 4.380348 0.0000 OUTPUT_GAP -1.42E-06 9.83E-07 -1.442803 0.1534 R-squared 0.249642 Mean dependent var 3.860658 Adjusted R-squared 0.229085 S.D. dependent var 1.686064 S.E. of regression 1.480394 Akaike info criterion 3.661167 Sum squared resid 159.9844 Schwarz criterion 3.753170 Log likelihood -136.1244 F-statistic 12.14348 Durbin-Watson stat 0.181830 Prob(F-statistic) 0.000028 The estimation results are; it =3.62 + 0.68(à Ã¢â€š ¬ tà ¢Ã¢â€š ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t) à ¢Ã¢â€š ¬Ã¢â‚¬Å" 1.42 (yt à ¢Ã¢â€š ¬Ã¢â‚¬Å" Ã…Â ·t) The coefficient associated to inflation is positive, 0.68, but is statistically significant with a p-value of 0.00. The coefficient associated with the output gap is negative (-1.42) and statistically significant. The estimated stabilizing rate of interest (c) is positive (3.61) and statistically significant. An R-squared of 0.25 means that we are only able to explain about 25% of the variability in the interest rate. The augmented taylor rule model: it = ÃŽÂ ± + ÃŽÂ ²Et(à Ã¢â€š ¬ t+ià ¢Ã¢â€š ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t+i) +ÃŽÂ ³Et (yt+i+ Ã…Â ·t+i)+à ¢Ã‹â€ Ã¢â‚¬ËœÃƒÅ½Ã‚ ´1 à Ã¢â‚¬ ¦t-1 + ÃŽÂ µt one lag Dependent Variable: FED_FUNDS_RATE Method: Least Squares Date: 07/05/10 Time: 21:30 Sample(adjusted): 1991:3 2009:4 Included observations: 74 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. C 8.298961 1.280893 6.479044 0.0000 INFLATION_F 0.548999 0.181198 3.029825 0.0034 OUTPUT_GAP_F -9.10E-06 1.51E-06 -6.041926 0.0000 S(-1) 4.24E-05 7.35E-06 5.775767 0.0000 R-squared 0.442430 Mean dependent var 3.809595 Adjusted R-squared 0.418534 S.D. dependent var 1.678852 S.E. of regression 1.280190 Akaike info criterion 3.384432 Sum squared resid 114.7220 Schwarz criterion 3.508976 Log likelihood -121.2240 F-statistic 18.51494 Durbin-Watson stat 0.214690 Prob(F-statistic) 0.000000 Interpretation: The estimated regression is; it = 8.30 + 0.55Et(à Ã¢â€š ¬ t+ià ¢Ã¢â€š ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t+i) -9.10Et (yt+i+ Ã…Â ·t+i)+4.24à ¢Ã‹â€ Ã¢â‚¬ËœÃƒ Ã¢â‚¬ ¦t-k The coefficient associated to expected inflation is positive (0.55) but is statistically significant because it has a p-value of 0f 0.003, the coefficient associated with expected output gap is negative (-9.10) and is statistically significant (p-value = 0.000). The coefficient associated with the ch ange in asset prices (lagged by 1 for better estimation) which is denoted by S (-1) is negative and it is statistically significant therefore we reject the null hypothesis. The measure of goodness of fit (R-square) is 0.44 meaning that we are able to explain about 44% of the variability in the interest rate Our model consistently overestimates the actual interest rate and the residuals do not seem to be independently and identically distributed. We therefore conduct some tests which include: 1. The Jacque-Bera test: This is a statistic that measures the difference of the skewness and kurtosis of the series with those from a normal distribution. By simply looking at the histogram, we can see that the distribution is roughly normal and the jarque-bera statistic of 0.58 shows that it is not statistically significant and we should accept the null hypothesis. The white test: This is used to test whether the errors are heteroskedastic or not. In the presence of heteroskedastic ity, OLS estimates are consistent but efficient. White Heteroskedasticity Test: F-statistic 3.846209 Probability 0.000621 Obs*R-squared 25.97528 Probability 0.002062 Test Equation: Dependent Variable: RESID^2 Method: Least Squares Date: 07/06/10 Time: 00:41 Sample: 1991:3 2009:4 Included observations: 74 Variable Coefficient Std. Error t-Statistic Prob. C -35.28961 24.46199 -1.442630 0.1540 INFLATION_F -5.419657 3.008210 -1.801622 0.0763 INFLATION_F^2 0.307231 0.200286 1.533961 0.1300 INFLATION_F*OUTPUT_GAP_F 5.95E-06 2.83E-06 2.105586 0.0392 INFLATION_F*S(-1) -2.78E-05 1.73E-05 -1.603361 0.1138 OUTPUT_GAP_F 9.90E-05 5.34E-05 1.852558 0.0686 OUTPUT_GAP_F^2 -6.19E-11 2.74E-11 -2.257288 0.0274 OUTPUT_GAP_F*S(-1) 3.35E-10 1.43E-10 2.337290 0.0226 S(-1) -0.000309 0.000140 -2.205282 0.0310 S(- 1)^2 -7.97E-11 5.33E-10 -0.149679 0.8815 R-squared 0.351017 Mean dependent var 1.550298 Adjusted R-squared 0.259754 S.D. dependent var 1.968439 S.E. of regression 1.693596 Akaike info criterion 4.016674 Sum squared resid 183.5692 Schwarz criterion 4.328034 Log likelihood -138.6169 F-statistic 3.846209 Durbin-Watson stat 0.580160 Prob(F-statistic) 0.000621 According to the two test statistics involved in the regression result, we can say that the distribution is statistically significant so we can reject null hypothesis. The Durbin-Watson test: This is used to test for serial correlation. Autocorrelated residuals means that OLS is no longer best, linear, unbiased estimators and that the standard errors computed using the OLS formula are not correct. The Durbin-Watson statistic of 0.214690 shows that there is positive serial correlation as DW 2 and since there are more than 50 observations in the sample (74), this also indicates strong first-order serial correlation. Model 2: SP500 = ÃŽÂ ²1 + ÃŽÂ ²2 federal funds rate + ÃŽÂ ²3real GDP + ÃŽÂ ²4unemployment rate. The aim of this model is to determine if the federal funds rate has any impact on the stock market. Real GDP and unemployment rate are used as control variables for reasons given in the research methodology. Dependent Variable: SP500 Method: Least Squares Date: 07/06/10 Time: 01:38 Sample: 1990:1 2009:4 Included observations: 80 Variable Coefficient Std. Error t-Statistic Prob. C -115.7008 222.2313 -0.520632 0.6041 FED_FUNDS_RATE 0.990301 12.96436 0.076386 0.9393 REAL_GDP01 0.159538 0.010327 15.44916 0.0000 UNEMPLOYMENT_RATE -119.5674 17.42177 -6.863101 0.0000 R-squared 0.872734 Mean dependent var 924.0339 Adjusted R-squared 0.867710 S.D. dependent var 378.2205 S.E. of regression 137.5651 Akaike info criterion 12.73478 Sum squared resid 1438237. Schwarz criterion 12.85388 Log likelihood -505.3912 F-statistic 173.7244 Durbin-Watson stat 0.350064 Prob(F-statistic) 0.000000 Interpretation: The estimated regression is: sp500 =-115.78 + 0.99*actual change in federal funds rate + 0.16*real GDP à ¢Ã¢â€š ¬Ã¢â‚¬Å" 119.57* unemployment rate. The coefficient associated with the federal funds rate is negative and is not statistically significant. The coefficient associated with the real GDP is positive and is statistically significant while the coefficient associated with the employment is negative but statistically significant. An R-square of 0.87 shows that we are able to explain about 87% of the variability in the sp500. Model 3: SP500 = ÃŽÂ ²1 + ÃŽÂ ²2*%à ¢Ã‹â€ Ã¢â‚¬  M1 + ÃŽÂ ²3*Real GDP + ÃŽÂ ²4*Unemployment rate Dependent Variable: SP500 Method: Least Squares Date: 07/06/10 Time: 02:20 Sample: 1990:1 2009:4 Included observations: 80 Variable Coefficient Std. Error t-Statistic Prob. C 46.44939 148.8335 0.312090 0.7558 M1 9.337596 5.174957 1.804382 0.0751 REAL_GDP01 0.157616 0.008466 18.61858 0.0000 UNEMPLOYMENT_RATE -150.2864 20.48732 -7.335580 0.0000 R-squared 0.877952 Mean dependent var 924.0339 Adjusted R-squared 0.873135 S.D. dependent var 378.2205 S.E. of regression 134.7151 Akaike info criterion 12.69291 Sum squared resid 1379261. Schwarz criterion 12.81201 Log likelihood -503.7163 F-statistic 182.2360 Durbin-Watson stat 0.378905 Prob(F-statistic) 0.000000 The estimated regression is: SP500 = 46.45 + 9.34%à ¢Ã‹â€ Ã¢â‚¬  M1 + 0.16Real GDP à ¢Ã¢â€š ¬Ã¢â‚¬Å" 150.29Unemployment rate Interpretation: The coefficient associated with the %à ¢Ã‹â€ Ã¢â‚¬  M1 is positive and it is not statistically significant. The coefficient associated with real GDP is positive and it is statistically independent while the coefficient associated with the unemployment rate is negative and it is statistically significant. The R-square shows that we are able to explain 87% of the variability of the sp500. Although the actual and fitted line moves at almost the same frequency, the residual line is independently and identically distributed. This shows that their might be a misspecification in the model. The histogram shows that it is not very normal and the jarque-bera statistic shows that we cannot reject the null hypothesis. White Heteroskedasticity Test: F-statistic 15.31572 Probability 0.000000 Obs*R-squared 53.05639 Probability 0.000000 Test Equation: Dependent Variable: RESID^2 Method: Least Squares Date: 07/06/10 Time: 02:46 Sam ple: 1990:1 2009:4 Included observations: 80 Variable Coefficient Std. Error t-Statistic Prob. C 970357.2 210038.1 4.619911 0.0000 M1 29162.57 7778.598 3.749077 0.0004 M1^2 75.30446 198.5262 0.379317 0.7056 M1*REAL_GDP01 -0.795715 0.540692 -1.471661 0.1456 M1*UNEMPLOYMENT_RATE -3397.373 1332.934 -2.548792 0.0130 REAL_GDP01 -68.28240 28.44182 -2.400775 0.0190 REAL_GDP01^2 0.001171 0.001082 1.082364 0.2828 REAL_GDP01*UNEMPLOYMENT_RATE 7.582585 2.401815 3.157023 0.0024 UNEMPLOYMENT_RATE -211388.2 28973.71 -7.295863 0.0000 UNEMPLOYMENT_RATE^2 11536.47 2587.237 4.458994 0.0000 R-squared 0.663205 Mean dependent var 17240.76 Adjusted R-squared 0.619903 S.D. dependent var 26363.86 S.E. of regression 16253.85 Akaike info criterion 22.34652 Sum squared resid 1.85E+10 Schwarz criterio n 22.64427 Log likelihood -883.8607 F-statistic 15.31572 Durbin-Watson stat 1.553060 Prob(F-statistic) 0.000000 The two statistics in the white test show that evidence of no heteroskedasticity exists. SP500 = ÃŽÂ ² 1+ ÃŽÂ ²2*%à ¢Ã‹â€ Ã¢â‚¬  M2 + ÃŽÂ ²*3Real GDP + ÃŽÂ ²4*Unemployment rate Dependent Variable: SP500 Method: Least Squares Date: 07/06/10 Time: 02:25 Sample: 1990:1 2009:4 Included observations: 80 Variable Coefficient Std. Error t-Statistic Prob. C -87.42922 124.7649 -0.700752 0.4856 M2 13.44679 8.028875 1.674804 0.0981 REAL_GDP01 0.149376 0.010252 14.56981 0.0000 UNEMPLOYMENT_RATE -117.0021 12.34845 -9.475044 0.0000 R-squared 0.877254 Mean dependent var 924.0339 Adjusted R-squared 0.872409 S.D. dependent var 378.2205 S.E. of regression 135.0999 Akaike info criterion 12.69861 Sum squared resid 138 7151. Schwarz criterion 12.81771 Log likelihood -503.9445 F-statistic 181.0553 Durbin-Watson stat 0.372533 Prob(F-statistic) 0.000000 The estimated regression is: SP500 = -87.43 + 13.44%à ¢Ã‹â€ Ã¢â‚¬  M2 + 0.15Real GDP à ¢Ã¢â€š ¬Ã¢â‚¬Å" 117.00Unemployment rate Interpretation: The coefficients of M2 and real GDP are both positive while that of the unemployment rate is negative while the p-values show that real GDP and unemployment rate are statistically significant while M2 is not. The R-squared shows that we are able to explain the variability of the SP500 by 87%. This diagram shows that the actual and fitted lines do not move at exactly the same frequency but are close enough while the residual line is better than that of the M2 showing that it is not quite independently and identically distributed. From the histogram, we can see that the distribution is roughly distributed and the jarque-bera shows that the null hypothesis cannot b e rejected. White Heteroskedasticity Test: F-statistic 4.750272 Probability 0.000061 Obs*R-squared 30.33367 Probability 0.000385 Test Equation: Dependent Variable: RESID^2 Method: Least Squares Date: 07/06/10 Time: 02:49 Sample: 1990:1 2009:4 Included observations: 80 Variable Coefficient Std. Error t-Statistic Prob. C 746131.3 254782.4 2.928504 0.0046 M2 10672.81 13299.74 0.802483 0.4250 M2^2 -504.8870 659.6998 -0.765328 0.4466 M2*REAL_GDP01 1.417689 1.591493 0.890792 0.3761 M2*UNEMPLOYMENT_RATE -3338.505 1401.946 -2.381336 0.0200 REAL_GDP01 -85.91669 37.86747 -2.268879 0.0264 REAL_GDP01^2 0.001707 0.001357 1.257810 0.2126 REAL_GDP01*UNEMPLOYMENT_RATE 7.019909 2.298457 3.054183 0.0032 UNEMPLOYMENT_RATE -97773.44 21069.03 -4.640624 0.0000 UNEMPLOYMENT_RATE^2 2824.279 1386.827 2.0 36504 0.0455 R-squared 0.379171 Mean dependent var 17339.39 Adjusted R-squared 0.299350 S.D. dependent var 25364.16 S.E. of regression 21231.03 Akaike info criterion 22.88078 Sum squared resid 3.16E+10 Schwarz criterion 23.17854 Log likelihood -905.2313 F-statistic 4.750272 Durbin-Watson stat 1.045072 Prob(F-statistic) 0.000061 The relevant statistics in this test show that the residuals are heteroskedastic. CONCLUSION AND RECOMMENDATIONS The result of this study shows that there is a negative relationship between changes in asset prices and federal funds rates confirming that changes an increase in asset prices leads to a decrease in the federal funds rates ( i.e expansionary monetary policy). This is in line with the arguments of most of the economists who have carried out research on this topic. Model 2 provides results which show that there is a negative relationship between the federal funds rate even when the sp500 is used as the dependent variable and that the relationship is statistically insignificant which shows that the federal funds rate does not have much of an impact on the sp500. The third model which studies the relationship between money supply and asset prices shows that while there is a positive relationship between money supply and asset prices, both regressions (involving M1 and M2) are not statistically significant. I would recommend that the central bank continues to closely monitor t he stock market in order to make the necessary adjustments to the economy when necessary. It is also important that the federal government does not try to regulate stock market prices using federal fund rates because there is very little impact of federal funds rates on the stock market. Finally, I recommend that although money supply is positively related to the stock market, it does not matter if a particular monetary aggregate is used. The FOMC should focus on ensuring that the money supply is moderate and does not lead to inflation and increase in price levels in the economy

Navigating Our Mental Health Problem - 5632 Words

Navigating Our Mental Health Problem Wesley W. Austin HCA 450A Warner Pacific College June 18, 2015 Abstract The object of this paper is to shed light on the seriousness of mental illness and it is statistically affecting the United States. The history of how the mentally ill have been treated in this country will be discussed, followed by how we got to our current situation with a lack of treatment and an epidemic of mentally ill homeless people as well as, how the police are trained, or not trained and what can be done to improve upon it, and how our military funding has failed our veterans. Then the paper will take a look at how stigma has shaped how the public views mental illness, and how it shaped the writers young life.†¦show more content†¦Untreated mental health issues have many different outcomes, including homelessness, withdrawal from social activities and other people, and unfortunately suicide. Minorities are even more at risk as it is proven that they are becoming increasingly less likely to use mental health services when they are needed. Both Hispanics and African-American seek mental health treatment at half the rate of Caucasians in the United States, and Asians only seek treatment at about a third of the rate of Caucasians. African-Americans are also less likely to seek mental health care the more they are educated, while Caucasians see increased usage with higher education. Suicide rates have also climbed with minorities, with Hispanic girls in their teens having a 60 percent higher rate of suicide than their Caucasian counterparts. Culture and stigma about mental health are part of the problem. â€Å"A lot of immigrant families don’t feel comfortable turning to counseling services because there might not be someone there who will understood them and some of the unique cultural issues they face.† (PBS, Resources: Minorities and Mental Health, 2009). It is not only the severely mentally ill and minorities that are lacking in receiving the care they need, depression is huge