Managing and Developing the Human Resources Research Paper

Overseeing and Developing the Human Resources - Research Paper Example Dickens (1994) battles that the business case for overseeing decent variety offers an approach to work equivalent open doors as a vital issue, a basic belief connected to authoritative seriousness. So as to improve quality and stay serious various associations have begun offering capability levels required for better adequacy in the business. For instance, McDonald's has been given the authorisation to grant their own capabilities proportionate to GCSEs, A levels and degrees, in subjects like drive-through eatery the executives (BBC, 2008). System Rail and Flybe are different organizations which have been conceded such consent by Qualifications and Curriculum Authority (QCA), to present degrees and confirmations for setting up the workforce for a serious tomorrow (Woolcock and Elliott, 2008). These are a portion of the pointers towards the expanding acknowledgment that obtaining and updating the aptitudes isn't truth be told, significant for serious quality of the organization, howev er it is similarly urgent for the person to stay pertinent to the business. This investigation is, along these lines, a push to break down the HR situation by and large and how the UK is setting up the HR for a superior and serious tomorrow. Independent of the nature and specialization of the organization, it tends to be said without a doubt that, 'individuals' structure the center of its exercises and consequently, the conduct and character of these very 'individuals' will influence the general character of the association. The presentation level of this workforce relies on the sorts of inspirations gave by the association. It is thusly very intelligent to state that Human Resource Management is an exceptionally urgent and a fundamental piece of any organization.â

Method Overloading Default Parameters in Delphi

Strategy Overloading Default Parameters in Delphi Capacities and methods are a significant piece of the Delphi language. Beginning with Delphi 4, Delphi permits us to work with capacities and strategies that help default parameters (making the parameters discretionary), and grants at least two schedules to have an indistinguishable nameâ but work as totally various schedules. Lets perceive how Overloading and default parameters can assist you with coding better. Over-burdening Basically, over-burdening is proclaiming more than one daily practice with a similar name. Over-burdening permits us to have numerous schedules that share a similar name, however with an alternate number of parameters and types. For instance, lets think about the accompanying two capacities: {Overloaded schedules must be proclaimed with the over-burden directive} work SumAsStr(a, b :number): string; over-burden; start  â Result : IntToStr(a b) ; end; work SumAsStr(a, b : broadened; Digits:integer): string; over-burden; start  â Result : FloatToStrF(a b, ffFixed, 18, Digits) ; end; These presentations make two capacities, both called SumAsStr, that take an alternate number of parameters and are of two distinct sorts. At the point when we call an over-burden schedule, the compiler must have the option to advise which routine we need to call. For instance, SumAsStr(6, 3) calls the first SumAsStr work, since its contentions are whole number esteemed. Note: Delphi will assist you with picking the correct usage with the assistance of code fruition and code knowledge. Then again, consider in the event that we attempt to call the SumAsStr work as follows: SomeString : SumAsStr(6.0,3.0) Well get a blunder that peruses: there is no over-burden form of SumAsStr that can be called with these contentions. This implies we ought to likewise incorporate the Digits parameter used to indicate the quantity of digits after the decimal point. Note: There is just one guideline when composing over-burden schedules, and that will be that anâ overloaded routine must contrast in at any rate one parameter type. The arrival type, rather, can't be utilized to recognize among two schedules. Two Units - One Routine Lets state we have one everyday practice in unit An, and unit B utilizes unit A, however announces a daily schedule with a similar name. The affirmation in unit B needn't bother with the over-burden mandate - we should utilize unit As name to qualify calls to As variant of the daily schedule from unit B. Think about something like this: unit B; ... utilizes A; ... method RoutineName; start  Result : A.RoutineName; end; An option in contrast to utilizing over-burden schedules is to utilize default parameters, which typically brings about less code to compose and keep up. Default/Optional Parameters So as to rearrange a few explanations, we can give a default an incentive for the parameter of a capacity or strategy, and we can call the daily practice with or without the parameter, making it discretionary. To give a default esteem, end the parameter announcement with the equivalent () image followed by a steady articulation. For instance, given the statement work SumAsStr (a,b : expanded; Digits : number 2) : string; the accompanying capacity calls are equal. SumAsStr(6.0, 3.0) SumAsStr(6.0, 3.0, 2) Note: Parameters with default esteems must happen toward the finish of the parameter list, and should be passed by esteem or as const. A reference (var) parameter can't have a default esteem. When calling schedules with more than one default parameter, we can't skip parameters (like in VB): work SkipDefParams(var A:string; B:integer5, C:booleanFalse):boolean; ... /this call produces a blunder message CantBe : SkipDefParams(delphi, , True) ; Over-burdening With Default Parameters When utilizing both capacity or system over-burdening and default parameters, dont present vague routine revelations. Think about the accompanying affirmations: strategy DoIt(A:extended; B:integer 0) ; over-burden; strategy DoIt(A:extended) ; over-burden; The call to DoIt strategy like DoIt(5.0), doesn't gather. As a result of the default parameter in the main methodology, this announcement may call the two strategies, since it is difficult to advise which system is intended to be called.

Five Reasons Why Blogging Leads to Writing Jobs

Five Reasons Why Blogging Leads to Writing Jobs Five Reasons Why Blogging Leads to Writing Jobs Five Reasons Why Blogging Leads to Writing Jobs By Ali Hale Day by day Writing Tips has just secured Five reasons why blogging improves your composition. In any case, once you’ve cleaned up your abilities, and become used to composing as often as possible and accepting input, blogging can likewise assist you with getting paid for your composition. 1. It’s a free (or exceptionally modest) approach to independently publish your composition Posting your composition on a blog is a type of independently publishing, regardless of whether you don’t consider it that way. All things considered, blogging programming utilizes a Publish catch to present a post, and in the event that you run Google Adsense on your blog, Google alludes to you as a Publisher. Before, to get distributed you either convinced a manager to print your work, or you paid to have the piece printed yourself. Blogging permits you to independently publish for nothing (or at the little expense of facilitating and a web association). On the off chance that your blog gets mainstream, you could run promotions to bring in some cash or welcome sponsorship from organizations †look over to one side to see some of Daily Writing Tips’s supports. 2. Blogging causes you develop an arrangement of pieces Perhaps the hardest thing about beginning as an independent author is getting together an arrangement of your composition to show potential customers. Having a blog permits you to develop an example of distributed pieces that you can use to show your composing ability. In the event that you’re aiming to utilize blogging to begin your portfolio, why not compose visitor posts for different websites? For instance, I have Daily Writing Tips, Diet Blog, Freelance Switch, The Change Blog, Dumb Little Man and Pick the Brain on my rundown of locales I’ve composed for. Editors may pay attention to you more in the event that they can see that others think your composing is sufficient to distribute. 3. You get the opportunity to expound on themes that you love †and assemble your mastery and accreditations Much has been said about the need to have a blog on a specialty point †one theme that you expound consistently on, as opposed to attempting to incorporate everything that you’re keen on. This makes it a lot simpler to develop an intrigued readership, yet it likewise assists with building your insight about the subject. On the off chance that you’re perusing different online journals and books regarding your matter and composing unique material a few times each week, you’ll very likely be gaining some new useful knowledge. Having a settled blog on a specific subject is an extraordinary method to exhibit your aptitude. For instance, on the off chance that you need to compose film audits for a paper, highlighting your long-running online journal with a week by week gather together of the most recent discharges could be an incredible method to demonstrate that you’re capable. 4. A well known blog could prompt a book bargain In the disconnected world, the offer of â€Å"blooks† is rising †books dependent on web journals. A few bloggers who I read have marked book bargains: Darren Rowse from Problogger, Shauna Reid from The Amazing Adventures of Diet Girl and Jennette Fulda (otherwise known as PastaQueen) from Half of Me. Furthermore, obviously, there are some exceptionally acclaimed models, for example, Belle de Jour’s The Intimate Adventures of a London Call Girl. On the off chance that your blog turns out to be enormous, it could conceivably grab the eye of a specialist. Also, regardless of whether the operators aren’t calling you at this time, a blog could assist you with selling your own book. Elizabeth Soutter Schwarzer (‘Liz’ or ‘DaMomma’) from Motherhood isn't for Wimps has independently published one book and has another in transit. Collis and Cyan Ta’eed from Freelance Switch independently published How to be a Rockstar Freelancer (in both digital book and printed organizes) and have another book in transit, How to be a Rockstar WordPresser. Numerous different bloggers offer incredible free articles on their blog yet additionally sell digital books which go into more profundity on similar points. 5. On the off chance that you’re a consultant, a blog is an extraordinary showcasing apparatus Notable bloggers who distribute definitive and elegantly composed posts can utilize their blog as a mean of promoting themselves. Skellie does this splendidly on Skelliewag, with a â€Å"Hire me† page and advertisments on the correct hand side for her own administrations. Harry and James from Men with Pens have â€Å"Guns for Hire† which clarifies the composition and configuration administrations which they offer. Ensure your blog tells potential customers how they can connect. In the event that somebody adores your blog’s style and substance, they may well need to employ you. Likewise, websites will in general position well in web crawlers (because of the measure of substance, and on the grounds that different web journals regularly need to connection to your posts), so you’ll have more prominent perceivability on the web. On the off chance that you have a blog, has it helped you †legitimately or in a roundabout way †to bring in cash from your composition? On the off chance that you’re not blogging yet, do you have thoughts of how you’d like to utilize a blog? Need to improve your English in a short time a day? Get a membership and begin getting our composing tips and activities day by day! Continue learning! Peruse the Freelance Writing classification, check our well known posts, or pick a related post below:The Royal Order of Adjectives 7 Tips for Writing a Film ReviewEmpathic or Empathetic?

Definition of the Hastert Rule

Meaning of the Hastert Rule The Hastert Rule is a casual strategy in House Republican administration intended to confine the discussion on charges that dont have support from a larger part of its gathering. At the point when Republicans hold a lion's share in the 435-part House, they utilize the Hastert Rule to restrict any enactment that doesnt have support from a larger part of the lion's share from coming up for a vote. I don't get that's meaning? It implies if Republicans control the House and bit of enactment must have the help of most individuals from the GOP to see a decision on the floor. The Hastert Rule is significantly less unbending that the 80-percent rule held by the ultraconservative House Freedom Caucus. The Hastert Rule is named for former Speaker of the House Dennis Hastert, a Republican from Illinois who filled in as the chambers longest-servingâ speaker, from 1998 until his abdication in 2007. Hastert accepted the job of a speaker was, in his words, not to speed up enactment that contradicts the desires of most of his lion's share. Past Republican speakers of the House followed the equivalent core value, including previous U.S. Rep. Newt Gingrich. Analysis of the Hastert Rule Pundits of the Hastert Rule say its excessively inflexible and limits banter on significant national issues while issues supported by Republicans get consideration. As it were, it puts the interests of an ideological group over the interests of individuals. Pundits additionally accuse the Hastert Rule for spiking House activity on any enactment went in a bipartisan manner in the U.S. Senate. The Hastert Rule was accused, for example,â for holding up House decides on the ranch bill and movement change in 2013. Hastert himself endeavored to separate himself from the standard during the administration shutdown of 2013, when Republican House Speaker John Boehner would not permit a decision on a measure subsidizing central government tasks under the conviction that a moderate coalition of the GOP meeting was against it. Hastert disclosed to The Daily Beast that the alleged Hastert Rule wasnt truly unchangeable. â€Å"Generally, I expected to have a lion's share of my dominant part, in any event half of my meeting. This wasn’t a ruleâ †¦ The Hastert Rule is somewhat of a misnomer.† He included of Republicans under his leadership: â€Å"If we needed to work with Democrats, we did.† Also, in 2019, in the midst of the longest government shutdown ever, a congressman alluded to the arrangement as the most moronic guideline at any point made - named after someone who is in jail that has permitted a minority of dictators in the Congress. (Hastert served 13 months in jail in the wake of confessing to disregarding government banking laws. He conceded overstepping the law to pay quiet cash to a young kid he had explicitly attacked during the 1960s and 1970s when he was a wrestling trainer.) In any case, Hastert is on the record saying the accompanying during his residency as speaker: Now and again, a specific issue may energize a lion's share made up for the most part of the minority. Battle fund is an especially genuine case of this marvel. The activity of speaker isn't to speed up enactment that opposes the desires of most of his larger part. Norman Ornstein of the American Enterprise Institute has called the Hastert Rule unfavorable in that it puts party in front of the House all in all, and in this way the desire of the individuals. As House speakers, he said in 2004, You are the gathering head, however you are confirmed by the entire House. You are a sacred official. Backing for the Hastert Rule Preservationist support bunches including the Conservative Action Project have contended that the Hastert Rule ought to be made composed approach by the House Republican Conference so the gathering can stay on favorable terms with the individuals who chose them for office. Not exclusively will this standard forestall awful arrangement being passed against the desires of the Republican larger part, it will reinforce the hand of our administration in dealings †realizing that enactment can't pass the House without huge Republican help, wroteâ former Attorney General Edwin Meese and a gathering of similarly invested, unmistakable moderates. Such concerns, in any case, are just fanatic and the Hastert Rule stays an unwritten rule directing Republican House speakers. Adherence to the Hastert Rule A New York Times investigation of adherence to the Hastert Rule discovered all Republican House speakers had abused it at some point. Boehner had permitted House bills to come up for a vote despite the fact that they didnt have support from a dominant part of the larger part. Additionally infringing upon the Hastert Rule at any rate multiple times over his profession as speaker: Dennis Hastert himself.

How Does Internet Influence Society Nowadays - 550 Words

How Does Internet Influence Society Nowadays (Essay Sample) Content: Student NameProfessor/InstructorCourse Number5 September 2014How Does Internet Influence Society NowadaysIntroductionFounded over five decades ago and gained super recognition in the late 1990à ¢Ã¢â€š ¬s, the internet is now the greatest human discovery. Despite being the largest single communication network in history, the internet is also the most influential tool of our society today. By influence, the internet surpasses other traditional tools considered to have great influence on the society. The internet has shaped propositions that individual members of the society now hold (Heiderich 5). He further notes that the internet has amassed great following due to the immense benefits it has on individuals and the society at large (8).Internet and the societyConsidered in isolation, the internet has the greatest influence on humanity; especially in the 21st Century. In the changing face of humanity, the internet plays a pivotal role as it has transformed the way we d o business, run our individual affairs or even interact with other members of the society.In her DVD; Living in the cyberspace, Picard observes that the internet has created the broadest shopping mall. Here, the use of the internet has made the globe a digital village making shopping possible from anywhere irrespective of your location. For instance, via the internet, one can shop in the U.K from his office in USA. This not only simplifies the way entrepreneurs conduct their business but also eliminates the need for unnecessary transport costs on shopping fairs. According to Heiredich, such influence on individual lives may be classified as part of the internetà ¢Ã¢â€š ¬s micro-influence (4).Additionally, the internetà ¢Ã¢â€š ¬s use in communication has made the art both easy and feasible at almost all locations around the world. As a result of a robust internet infrastructure, sharing information is now a virtual reality made possible (Picard 16). Unlike in the traditional regime where offline communication is used, the internet makes it possible to virtually reach masses of correspondents in real-time. Furthermore, the social media has transformed the way we share our messages (25). From the traditional telegraphs, letters, telephones and now the internet, we all feel the great role the internet has had on human life and the society at large.Another sphere of humanity the internet has not spared influencing is how research and reading is conducted (Picard 19). By availing millions of inf...

How The Stock Market Contributes To Economic Growth - Free Essay Example

Introduction The debate of whether stock market is associated with economic growth or the stock market can be served as the economic indicator to predict future. According to many economists stock market can be a reason for the future recession if there is a huge decrease in the stock price or vice versa. However, there are evidence of controversial issue about the ability of prediction from the stock market is not reliable if there is a situation like 1987 stock market crashed followed by the economic recession and 1997 financial crises. (Stock market and economic growth in Malaysia: causality test). The aim of the study is to find the relation between the stock market performance and the real economic activity in case of four countries The UK, The USA, Malaysia and Japan. With my limited knowledge I have tried to find out the role of financial development in stimulating economic growth. A lot of economists have different view about stock market development and the economic growth. If we focus on some related literature published on this topic one question arises: Is economic development is affected by stock market development? Even though there are lots of debate on some are saying that stock market can help the economy but the effect of stock market in the economy especially in the economy is very little. Ross Levine suggested in his paper published in 1998 that recent evidence suggested stock market can really give a boom to economic growth. (REFERENCE) It is not really possible to measure the growth by simply looking at the ups and down in the stock market indicator and by looking at the rates of growth in GDP. A lot of things can cause in the growth of stock market like changes in the banking system, foreign participation in the in the financial market may participate strongly. Apparently it seems that these developments can cause development of stock market followed by the good economic growth. But to check the accuracy one required to follow an appropriate method which would meaningfully measure whether stock price is really effecting the economic growth or not? In my work I have tried to find out the co integrating relationship between Stock price and GDP and tried to check if there is a long run and short run relationship between the stock price and GDP. The method used for the studies is Engle Granger co integration method. To do this I have used ADF (Augmented Dickey Fuller Test) to check for the stationary behaviour of the variables and then I have performed the Engle Granger Engle Granger co integration method followed by residual based error correction model. To check for the short run relationship I have used 2nd stage Engle Granger co integration method. To check the causal effect of the four countries stock market and economic growth I used Granger Causality Method. In this paper I have reviewed some studies of scholars which I have discussed on the literature review part. This paper contains five parts Part two is about the literature based on the past wok of scholars. Part Three discussed about the Data. Part four is about the methodology, Results are discussed on part five and part six is all about the summary and conclusion of the whole study. In my work I have founded there is no long run relationship between stock market and economic growth in all four countries. In addition there is no causal relation between stock index yield and the national economy growth rate. The empirical results of the thesis concludes that the possibility of seemingly abnormal relationship between the stock index and national economy of these for countries. Literature Review: Stock market contributes to economic growth in different ways either directly or indirectly. The functions of stock market are savings mobilization, Liquidity creation, and Risk diversification, keep control on disintermediation, information gaining and enhanced incentive for corporate control. The relationship between stock market and economic growth has become an issue of extensive analysis. There is always a question whether the stock market directly influence economic growth. A lot of research and results shows that there is a strong relationship between stock market and economic growth. Evidence on whether financial development causes growth help to reconcile these views. If we go back to the study of Schumpeter (1912) his studies emphasizes the positive influence on the development of a countrys financial sector on the level and the potential risk of losses caused by the adverse selection and moral hazard or transaction costs are argued by him how necessary the rate of growth argues that financial sectors provides of reallocating capital to minimize the potential losses. Empirical evidence from king and Levine (1983) show that the level of financial intermediation is good predictor of long run rates of growth, capital accumulation and productivity. Enhanced liquidity of financial market leads to financial development and investors can easily diversify their risk by creating their portfolio in different investments with higher investment. Demiurgic and Maksimovic (1996) have found positive causal effects of financial development on economic growth in line with the à ¢Ã¢â€š ¬Ã‹Å"supply leading hypothesis. According to his studies countries with better financial system has a smooth functioning stock market tend to grow much faster as they have access to much needed funds for financially constrained economic enterprises by the large efficient banks. Related research was done for the past three decades focusing on the role of financial development in stimulating economic growth they never considered about the stock market. An empirical study by Ming Men and Rui on Stock market index and economic growth in China suggest that possible reason of apparent abnormal relationship between the stock Index and national economy in china. Apparent abnormal relationship may be because of the following reason inconsistency of Chinese GDP with the structure of its stock market, role played by private sector in growth of GDP and disequilibrium of finance structure etc. The study was done using the cointegration method and Granger causality test, the overall finding of the study is Chinese finance market is not playing an important role in economic development. (Men M 2006 China paper). An article by Indrani Chakraborti based on the case of India presented in a seminar in kolkata in October, 2006 provides some information about the existence of long run stable relationship between stosk market capitalization, bank credit and growth rate of real GDP. She used the concept of the granger causality after using both the Engle-Granger and Johansen technique. In her study she found GDP is co-integrated with financial depth, Volatility in the stock market and GDP growth is co integrated with all the findings the paper explain that the in an overall sense, economic growth is the reson for financial development in India.(Chakraboty Indrani). Few writers from Malaysia found that stock market does help to predict future economy. Stock market is associated with economic growth play as a source for new private capital. Causal relationship between the stock market and economic growth which was done by using the formal test for causality by C.J. Granger and yearly Malaysia data for the period 1977-2006. The result from the study explain that future prediction is possible by stock market. A study focused on the relationship between stock market performance and real economic activity in Turkey. The study shows existence of a long run relationship between real economic activity and stock pricesà ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦ Result from the study pointed out that economic activity increases after a shock in stock prices and then declines in Turkish market from the second quarter and a unitary (Turkish paper) An international time series analysis from 1980-1990 by By RAGHURAM G. RAJAN AND LUIGI ZINGALES shows some evidence of the relation between stock market and economic growth. This paper describes whether economic growth is facilitated by financial development. He found that financial development has strong effect on economic growth. (Rajan and Zingales, 1998) The study of Ross LEVINE AND SARA ZERVOS on finding out the long run relationship between stock market and bank suggest a positive effect both the variables has positive effect on economic growth. International integration and volatility is not properly effected by capital stock market. And private save saving rates are not at all affected by these financial indicators. (Levine and Zervos 1998) Belgium Stock market study with economic development shows the positive long run relationship between both the variables. In case of Belgium the evidences are quiet strong that Economic growth is caused by the development of the stock market. It is more focused between the period 1873 and 1935, basically this period is considered as the period of rapid industrialization in Belgium. The importance of the stock market in Belgium is more pronounced after liberalization of the stock market in 1867-1873. The time varying nature of the link between stock market development and economic growth is explained by the institutional change in the stock exchange. They also tried to find out the relationship to the universal banking system. Before 1873 the economic growth was based on the banking system and after 1873 stock market took the place. (Stock Market Development and economic growth in Belgium, Stijin Van Nieuwerburg, Ludo Cuyvers, Frans Buelens July 5, 2005) Senior economist of the World Banks Policy research department Ross Levine has discussed about Stock market in his paper Stock Markets: A Spur to economic growth on the impact of development. Less risky investments are possible in liquid equity market and it attracts the savers to acquire an asset, equity. As they can sell it quickly when they need access to their savings, and if they want to alter their portfolio. Though many long term investment is required for the profitable investment. But reluctance of the investors towards long term investment as they dont have the access to their savings easily. Permanent access to capital is raised by the companies through equity issues as they are facilitating longer term, more profitable investments and prospect of long term economic growth is enhanced as liquid market improves the allocation of capital. The empirical evidence from the study strongly suggests that greater stock markets create more liquidity or at least continue economic gro wth. (Levine. R A spur to economic Growth) Another paper was focused on the linkages between financial development and economic growth using TYDL model for the empirical exercises by Purna Chandra Padhan suggests that both stock price and economic activity are integrated of order one and Johansen-Juselias Coin-integration tests for this study found one co integrating vector exists. It is proved by the spurious relation rule in this study the existence of at least one direction of causality. He described that bi-directional causality between stock price and economic growth meaning that economic activity can be enhanced by well developed stock exchange and vice-versa. ( Title:  The nexus between stock market and economic activity: an empirical analysis for India Author(s): Purna Chandra Padhan Journal: International Journal of Social Economics Year: 2007 Volume: 34 Issue: 10  Page: 741 à ¢Ã¢â€š ¬Ã¢â‚¬Å" 753 DOI: 10.1108/03068290710816874 Publisher: Emerald Group Publishing Limited) Chee Keong Choong (Universiti Tunku Abdul Rahman Malaysia) Zulkornain Yusop (Universiti Putra Malaysia) Siong Hook Law (Universiti Putra Malaysia) Venus Liew Khim Sen (Universiti Putra Malaysia) Date of creation: 23 Jul 2003 tried to find out the importance of the causal relationship of Financial development and economic growth. The findings of their study usin autoregressive Distributed lag (ARDL) describes about the positive long run impact on economic growth Granger causality also suggest same results. However, another study on Iran by N. Shahnoushi, A.G Daneshvar, E Shori and M. Motalebi 2008 Financial development is not considered as an effective factor to the economic growth. The study was focused on the causal relationship between the financial development and economic growth. Time series data used for the study from the period 1961-2004. Granger causality shows there is no co integrating relationship between financial development and economic growth in Iran only the economical growth leads to financial development. Establishing link between savings and investment is very much important and financial market provides that. Transient or lasting growth is the ultimate affect of the financial market. Economic growth can be influenced by financial market by improving the productivity of the capital, Investment to firms can be channelled and greater capital accumulation by increasing savings. To ensure the stability of the financial market potential regulation is important due to asymmetric information, especially at the time of financial liberalization. (Economic Development and Financial Market Tosson Nabil Deabes Moderm Academy for technology aand computer sciences; MAM November 2004 Economic Development Financial Market Working Paper No. 2 ) Data: The empirical analysis was carried out using the quarterly data for The UK, The USA, Japan and Malaysia. The data were collected from the DataStream for the period 1993I to 2008III. Economic growth is measured as the growth rate of gross domestic product (GDP) of each country with the help of stock prices SP. For the software processing I used Eviews 6.0 for the planned regression in order to get the results. The empirical analysis is done from the quarterly data from the stock market indices and the and the GDP between the first quarter of 1993 and the fourth quarter of 2008. All the data has been extracted from the data stream and expressed in US$. The data for Japan share price is from Tokyo Stock Exchange. Malaysias Share price is form Kuala Lumpur Composite Index, UKs is from UK FT all share price index and USA share price is taken from the DOW Jones industrial share price index. The nature of the Data is series used for the time series regression. List of Variables: UGDP UK GDP USP UK Share price LUGDP Log of UK GDP LUSP Log of UK Share price USGDP USA GDP USSP USA (DOW Jones) Share price LUSGDP Log of USA GDP LUSSP Log of USA Share price MGDP Malaysia GDP MSP Malaysia Share price LMGDP Log of Malaysia GDP LMSP Log of Malaysia Share price JGDP Japan GDP JSP Japan Share Price LJGDP Log of Japan GDP LJSP Log of Japan Share price Methodology: Engle and Granger (1987) first established the cointegration method. It is a method of measuring long term diversification based on data. Linear combination of two non stationary series shows that they are integrated in order one I(1) that is stationary. And this is a co integrated series. Cointegration Long term common random trend between non stationary time series. The linear combination of both the nonstationary series can be stationary if both the variables are integrated in same order. Cointegration is a very powerful approach in the long term analysis because a common stochastic trend is shared in cointegration that mean two series will not drift separately too much. They might deviate from each other but in the long run but eventually the will revert back in the long run. If there is very low correlation between the series still the series can be co-integrated as high correlation is not implied in cointegration. The reason for choosing the method as it will allow us to check the move between the variable in the long run even there might be a divergence in the short run. The first step in the analysis is check each index series whether the series for the presence of unit root which shows whether the series is non stationary. The method that I followed to do this is Augmented Dickey Fuller Test (ADF). I proceed the Granger cointegration technique 1987 when the stationary requirements are met. Cointegration long term common stochastic trend between nonstationary time series. If non-stationary series x and yare both integrated of same order and there is a linear combination of them that is stationary, they are called cointegrated series. A common stochastic trend is shared in Cointegration. It follows that these two series will not drift apart too much, meaning that even they may deviate from each other in the short-term, they will revert to the long-run equilibrium. This fact makes cointegration a very powerful approach for the long-term analyses. Meanwhile, cointegration does not imply high correlation; two series can be co integrated and yet have very low correlations. Cointegration tests allow us to determine whether financial variables of different national markets move together over the long run, while providing for the possibility of short-run divergence. The first step in the analysis is to test each index series for the presence of unit roots, which shows whether the series are nonstationary. All the series must be nonstationarity and integrated of the same order. To do this, we apply both the Augmented Dickey-Fuller (ADF) test. Once the stationarity requirements are met, we proceed Granger bivariate cointegration (1987) procedure. 30 International Research Journal of Finance and Economics Issue 24 (2009) Series Stationary Test: In this study I have used Augmented Dickey Fuller Test (ADF) to test the stationarity of variables. ADF is test for unit root where I have checked the Unit root and strong negative numbers of unit root is being rejected by the null hypothesis (level of significance). The following regression for the unit root test in Eviews: Is the white noise error tem. Is the difference operator. , () () Here with the test we can find the estimates of are equal to zero or not. Y is said to be stationary if the cumulative distribution of the ADF statistics by showing that if the calculated ratio of the coefficient is less than the critical value according to Fuller (1976). If we accept the Ho the sequence is predicted to be having unit root and if Ho is rejected then we can say that the series doesnt have unit root. This proves that the series is stationary. The co à ¢Ã¢â€š ¬Ã¢â‚¬Å"integration test can only be performed if both the sequences are all integrated of order I (1). Cointegration Test: According to Engle and Granger (1987) to check for cointegration if both the variables and are integrated with order one the proposed method for cointegration residual-based test for cointegration (Engle-Granger method). So from the above method we can find the equation By regressing with And after that and is denoted as the estimated regression coefficient vectors. Then, = à ¢Ã¢â€š ¬Ã¢â‚¬Å" is representing the estimated residual vector. If the residual is itegrated with zero that means the series for the residual is stationary, and and are then co integrated. An in this situation (1, -) is called co-integrating vector. Therefore is a co integrating equation, so, from it we can say that there is long run relationship between and. Granger causality test: Granger causality test is applied if the relationship is lagged between the two variables to determine the direction of relation in statistical term. It gives information about the short term relationship between the variables. In terms of conceptual definition causality is consist of different ideas, this concept produce a relation between caused and results were agreed upon. Aristo defines that there exist a link between causes and results and without causes these results are impossible. And this strong relationship. Some economists believe that the idea of causality is the mix of both theoretical and explanation and statistical concept. The frontline operational definition of causality is given by some economist, but Granger is the one who provided the information to understand it correctly and completely. Granger s operational causality definition depends of below hypotheses, Next cannot be the reason of past. 1. Next cannot be reason of past. Certain causality is possible only with past causes present time or future time. Cause is always to be come true before the result. In addition, this makes time lagged between causes and results. 2. Causality can be determined only stochastic process. It is not possible to determine the causality between two deterministic processes. After 1990s, Granger and Engle contributed to time series literature importantly. On these developments about time series analysis, some variations were done with Granger Causality test. According to this, possible long-term relationship would be tested and if 20 variables were co-integrated, long-term regression error equation s lagged value would be included in Granger Error Correction model as error correction term. Thus, Granger Causality test should be applied. If there is no co-integration between the variables, it can be continued with Granger Causality Test without including error correction terms. If there is a co-integration between the variables, Granger Causality Test will be failed and it will be certainly necessary to be included error correction term into the models. Granger Causality Test, which depends on time series data, is made by the estimation of the equations below with Least Squares Method (LSM). Xt = + j t j X + i t i Y + Ut Yt = + j t j Y + j t j X + Ut In Granger Causality test, there are three possible situations that one directional causality from x to y or y to x, opposite direction between x and y or one affect to other and independency of x and y each other. This situation changes according to chosen of null hypothesis and lagged values randomly in equations above whose parameters are whether equal to zero or not. According to researches, randomly choice makes causality incline to deviations importantly. To understand this test clearly it can be talked about below equation; t (LNGDP) = 0 + t inii (LNGDP)1+ t I nii (LND1)1+ Ut To apply Granger Causality test under null hypothesis, which illustrates coefficients of financial deepening variables (LND1) are meaningful (equal to zero) and then F-statistics can be calculated. If null hypothesis is not rejected then it is possible to say that Granger causality test accepts that financial deepening causes economic growth. The direction can be either negative or positive (Granger and Engle, 1987). Indicators of the economic growth and the financial deepening are variables, which are used for Granger Causality test. Moreover, this test can determine the effects of one variable on the other. Test result for Unit Root: Augmented Dickey Fuller Model (ADF) is used to test the stationary of each variable. Null and alternative hypothesis describes about the investigation of unit root. If the null is accepted and alternative is rejected then the variable non stationary behaviour and vice versa is stationary. Form the result of Augmented Dickey Fuller test of the four countries variables (Log GDP and Log Share price) shows that the entire variable has unit root at level which proves that the series is not stationary. However, the result from the first difference shows the significance at 1%, 5% and 10% critical value and found to be stationary behaviour. Therefore, it suggests that all the variables are integrated of order one. Variables level/1st Difference    Augmented Dickey Fuller Statistic(ADF) test Japan    Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -2.653258 -3.522887     -2.901779 -2.588280   -2.693600   -4.088713   -3.472558 -3.163450    1st Difference -9.053185 -3.524233   -2.902358 -2.588587 -9.003482   -4.090602   -3.473447 -3.163967    Share Price Level   -2.116137 -3.522887     -2.901779 -2.588280   -2.203273   -4.088713   -3.472558 -3.163450    1st Difference   -6.899295 -3.524233   -2.902358 -2.588587   -6.844396   -4.090602   -3.473447 -3.163967    Table 01: Unit root test for stationary Japan If we have a look on the unit root test for the variables GDP and Share price to find out the stationary behaviour the Augmented Dickey Fuller Test with intercept and with intercept and trend in level and first difference. The t statistic value with trend is -2.653258 which is higher than the critical values in 1%, 5% and 10% critical value. The same applies with intercept and trend as the t statistic value -2.693600 is higher than the critical value in all the level of critical value. So from the nature of stationary behaviour we can say in level GDP shows nonstationary behaviour. And the first difference LnGDP is integrated with order one. In case of LnSP the results with intercept and with intercept trend in level are -2.116137 and -2.203273 which is higher than the critical values shows non stationary behaviour as they are higher than the critical value. The unit root test for the variables at first difference shows stationary as the t statistic value is than the critical value i n all level and they are integrated in order one. Variables level/1st Difference    Augmented Dickey Fuller Statistic(ADF) test Malaysia    Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -1.195020 -3.522887     -2.901779 -2.588280 -1.933335   -4.088713   -3.472558 -3.163450    1st Difference -5.951843 -3.524233   -2.902358 -2.588587 -5.923595   -4.090602   -3.473447 -3.163967    Share Price Level   -1.900406 -3.522887     -2.901779 -2.588280   -1.891183   -4.088713   -3.472558 -3.163450    1st Difference   -7.842122 -3.524233   -2.902358 -2.588587   -7.779757   -4.090602   -3.473447 -3.163967    The unit root test result for LMGDP and LMSP values presented in natural logarithm. And the level values with intercept and with intercept and trend for LMGDP is -1.195020 and -1.93335 respectively. The values are higher than the critical value means the series has non stationary behaviour. On the other hand the 1st difference values with intercept and with intercept and trend are -5.951843 and -5.923595 respectively. The 1st difference values are integrated with order one. And in the same way I did the ADF test to check for Stationary behaviour of LMSP in level and first difference with intercept and trend. The values in level are -1.900406 and -1.891183 with intercept and trend us higher than the critical value and the series is not integrated with order one. The first difference t statistic values are -7.842122 and -7.779757 with intercept and with intercept and trend respectively are less than the critical value in both the case implies that the series is integrated with order on e. Variables level/1st Difference    Augmented Dickey Fuller Statistic(ADF) test UK    Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -0.690866 -3.522887     -2.901779 -2.588280 -2.377333   -4.088713   -3.472558 -3.163450    1st Difference -7.474388 -3.524233   -2.902358 -2.588587 -7.439027   -4.090602   -3.473447 -3.163967    Share Price Level -1.711599 -3.522887     -2.901779 -2.588280 -1.261546   -4.088713   -3.472558 -3.163450    1st Difference -7.254574 -3.524233   -2.902358 -2.588587 -7.391821   -4.090602   -3.473447 -3.163967    The results from Augmented Dickey Fuller test (ADF) for UK GDP in level with intercept and with intercept and trend is à ¢Ã¢â€š ¬Ã¢â‚¬Å"0.690866 and -2.377333 respectively. Both the values in level are higher than the critical value and are integrated in order 0 shows non stationary behaviour. The t statistic values in 1st difference with intercept and with intercept and trend are -7.474388 and -7.439207 respectively. Which suggest that the critical values are less than the critical values in 1%, 5% and 10% level. So from the above hypothesis it can be said that it series is integrated with order one. When I performed the unit root test using the same method the series in level with intercept and with intercept and trend the values in are -1.711599 and -1.261546 respectively. The values are higher than the critical values implies that they are not integrated in order one shows non stationary behaviour. However, the 1st difference value of log natural share price is -7.254573 and -7. 391821 with intercept and with intercept and trend respectively. So from the result we can say that the series is integrated in order one in both the cases with intercept and with intercept and trend. So the series in first difference is stationary. Variables level/1st Difference    Augmented Dickey Fuller Statistic(ADF) test USA    Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -3.244801 -3.522887     -2.901779 -2.588280   2.866507   -4.088713   -3.472558 -3.163450    1st Difference -5.010864 -3.524233   -2.902358 -2.588587 -5.010864   -4.090602   -3.473447 -3.163967    Share Price Level -2.074732 -3.522887     -2.901779 -2.588280 -0.359637   -4.088713   -3.472558 -3.163450    1st Difference -8.181234 -3.524233   -2.902358 -2.588587 -8.735399   -4.090602   -3.473447 -3.163967    Augmented Dickey Fuller Statistic in case of the variable of USA LUSSP and LUGDP I have used the same method using intercept and intercept and trend in level and first difference. The level t statistic value for LUSGDP is -3.244801 and -2.866507 respectively with intercept and with intercept and trend. The result for USA is same as the other country which is higher than the critical values. Proves that the series is not integrated with order one and is nonstationary. Whereas the first difference t statistic value for LUSGDP is less than the critical value. The t statistic value LUSGDP with intercept is -5.010864 and -5.010864 with intercept and trend. In this case both the values are lesser than the critical value implies that the series is integrated with order one in first difference. While taking the values in level and 1st difference in case of LUSSP the tstatistic value in level are -2.074732 and -0.359637 in level respectively with intercept and wit intercept and trend. Still t he series is showing the same nature in level as they are higher than the critical values and the series is not integrated in order 0. The first difference value for LUSSP series with trend and with trend and intercept is -8.181234 and -8.735399 respectively which is less than the critical value implies the series is integrated with order one. Co integration Test: Two step procedure of Engle-Granger cointegration is to check for the long run relationship between the variables. The first stage was run by using traditional OLS method. To do this we need to check whether the series is stationary or not. Which we have checked before by doing ADF test on each series. where the result shows that the series is integrated with order (1). Engle-Granger representation theorem that might have an error correction mechanism is the series is integrated. In this case the long run OLS model is as follows in case of Japan: LJGDP = 7.97824432568 + 0.163668097988*LJSP Dependent Variable: LJGDP Method: Least Squares Date: 12/17/09 Time: 20:30 Sample: 1991Q1 2009Q2 Included observations: 74    Coefficient Std. Error t-Statistic Prob. C 7.978244 0.120791 66.04995 0 LJSP 0.163668 0.048847 3.350602 0.0013 R-squared 0.134891 Mean dependent var    8.381114 Adjusted R-squared 0.122876 S.D. dependent var    0.10605 S.E. of regression 0.099321 Akaike info criterion    -1.75426 Sum squared resid 0.710261 Schwarz criterion    -1.69199 Log likelihood 66.90753 Hannan-Quinn criter.    -1.72942 F-statistic 11.22653 Durbin-Watson stat    0.310636 Prob(F-statistic) 0.001287          From the above model I have saved the residual series and performed ADF test with trend and without trend and the values are as follows in the table: Unit Root test for residual Series saved residual RJP T statistic Test critical values: 1% level 5% level 10% level   With intercept   -2.831807 -3.522887   -2.901779   -2.588280   With intercept and trend             From the above table we can see that the result is significant only in 10% level. Which suggest that there might be a long run relationship between the variables. But there is no long run relationship at 1% and 5% significant level as both the values are higher than the critical value. 2nd stage regression result: LJGDP = 7.96681067902 + 0.170453164194*LJSP + 0.819211725701*RJP(-1) Dependent Variable: LJGDP Method: Least Squares Date: 12/31/09 Time: 18:51 Sample (adjusted): 1991Q2 2009Q2 Included observations: 73 after adjustments    Coefficient Std. Error t-Statistic Prob.                C 7.966811 0.064529 123.4601 0 LJSP 0.170453 0.026119 6.525992 0 RJP(-1) 0.819212 0.064206 12.75915 0                R-squared 0.747462 Mean dependent var    8.384005 Adjusted R-squared 0.740246 S.D. dependent var    0.103806 S.E. of regression 0.052906 Akaike info criterion    -3.00038 Sum squared resid 0.195932 Schwarz criterion    -2.90625 Log likelihood 112.5137 Hannan-Quinn criter.    -2.96286 F-statistic 103.5928 Durbin-Watson stat    1.958683 Prob(F-statistic) 0          2nd stage regression suggest that there is short run relationship between stock market and economic growth. As from the table values after running the regression with the help of one intercept and lagged value of the residual save from the first stage regression. Here we can see that the all the coefficient has positive values and r-sruared (0.747462) is less than the Durbin-Watson value(1.958683). so form the results we can see that there exists a short run relationship between stock market and economic growth. Malaysia Following the same stages on Malaysia, by running the regression on OLS to check the long run relationship between stock market and economic growth in Malasia. The equation to check the first stage regression is: LMGDP = 8.2331829641 + 0.340689829517*LMSP The result from the above regression are described in the following table: Dependent Variable: LMGDP Method: Least Squares Date: 12/17/09 Time: 21:00 Sample: 1991Q1 2009Q2 Included observations: 74    Coefficient Std. Error t-Statistic Prob. C 8.233183 0.644484 12.77484 0 LMSP 0.34069 0.116332 2.928597 0.0046 R-squared 0.106441 Mean dependent var    10.11598 Adjusted R-squared 0.094031 S.D. dependent var    0.407894 S.E. of regression 0.388243 Akaike info criterion    0.972285 Sum squared resid 10.85275 Schwarz criterion    1.034557 Log likelihood -33.97453 Hannan-Quinn criter.    0.997126 F-statistic 8.576678 Durbin-Watson stat    0.054361 Prob(F-statistic) 0.004557          Unit Root test for residual Series T statistic Test critical values: 1% level 5% level 10% level   With intercept   -1.301997 -3.522887   -2.901779   -2.588280   With intercept and trend             From the above regression and after saving the residual I performed and ADF test with trend and without trend on the residual series. Here the result suggests that the t statistic value is higher than the critical values of 1%, 5% and 10% level. Which suggest that residual series is non stationary and there is no relationship between the variables in long run. The estimated equation in error correction model is as follows: LMGDP = 8.13761928798 + 0.360964712114*LMSP + 0.965225800038*R(-1) Dependent Variable: LMGDP Method: Least Squares Date: 01/01/10 Time: 23:15 Sample (adjusted): 1991Q2 2009Q2 Included observations: 73 after adjustments    Coefficient Std. Error t-Statistic Prob. C 8.137619 0.147701 55.09505 0 LMSP 0.360965 0.02665 13.54478 0 R(-1) 0.965226 0.027335 35.31042 0                R-squared 0.952382 Mean dependent var    10.12619 Adjusted R-squared 0.951022 S.D. dependent var    0.401091 S.E. of regression 0.088766 Akaike info criterion    -1.96541 Sum squared resid 0.551553 Schwarz criterion    -1.87128 Log likelihood 74.7374 Hannan-Quinn criter.    -1.9279 F-statistic 700.0218 Durbin-Watson stat    2.075716 Prob(F-statistic) 0          2nd stage results are suggesting about the short run relationship between the variables. As we can see from the is less than the Durbin-Watson Statistic. So from the result we can say that there exist a co-integrating relationship between stock market and economic growth in short run. UK Considering the case of UK to find out the relationship both in long and short run I used the same procedure to find out the relationship. As all the variables are integrated with order one which suggests the variables are stationary. Now by applying the Engle Granger cointegration method to estimate the co integrating vector in OLS and then examining the residual series. Cointegration for the long run depends on the residual series. Here I defined the residual series a RUK for the variables LUGDP (log of UK GDP) and LUSP(log of UK share price). If we look at the table of the unit root test for the residual series of the Co-integrating regression of LUGDP and LUSP the residual series RUK is -1.355485 with intercept and   -2.426938 with intercept and trend. Where both the result for unit root test by applying Augmented Dickey Fuller test suggests that the residual series has a nonstationary behaviour in both the case with intercept and with intercept and trend. As the critical value for at 1%, 5% and 10% is -3.522887, -3.522887 and -2.588280 respectively with intercept and -4.088713, -3.472558 and -3.163450with intercept and trend. As the t statistic value is higher than the critical values in both the case, so from the result we can say that the residual series in non stationary and there is no long run relationship between the variable. Dependent Variable: LUGDP Method: Least Squares Date: 12/17/09 Time: 21:10 Sample: 1991Q1 2009Q2 Included observations: 74    Coefficient Std. Error t-Statistic Prob.                C 6.41427 0.52629 12.18771 0 LUSP 0.790239 0.064275 12.29475 0 R-squared 0.677363 Mean dependent var    12.87916 Adjusted R-squared 0.672882 S.D. dependent var    0.332711 S.E. of regression 0.190291 Akaike info criterion    -0.45386 Sum squared resid 2.607181 Schwarz criterion    -0.39159 Log likelihood 18.79298 Hannan-Quinn criter.    -0.42902 F-statistic 151.1608 Durbin-Watson stat    0.149084 Prob(F-statistic) 0          Unit Root test for residual Series residual saved T statistic Test critical values: RUK    1% level 5% level 10% level   With Intercept   -1.355485 -3.522887   -2.901779   -2.588280   With intercept and trend   -2.426938 -4.088713 -3.472558 -3.16345 2nd stage Dependent Variable: LUGDP Method: Least Squares Date: 01/04/10 Time: 17:57 Sample (adjusted): 1991Q2 2009Q2 Included observations: 73 after adjustments                   Coefficient Std. Error t-Statistic Prob.                C 6.375942 0.207063 30.79235 0 LUSP 0.795176 0.025265 31.47291 0 RUK(-1) 0.937553 0.046342 20.23103 0 R-squared 0.952647 Mean dependent var    12.88329 Adjusted R-squared 0.951294 S.D. dependent var    0.333094 S.E. of regression 0.073512 Akaike info criterion    -2.3425 Sum squared resid 0.378285 Schwarz criterion    -2.24837 Log likelihood 88.50121 Hannan-Quinn criter.    -2.30499 F-statistic 704.1223 Durbin-Watson stat    2.248029 Prob(F-statistic) 0          USA In case of USA to find out the relationship between stock market and economic growth using Engle Granger cointegration method we find the following results. LUSGDP = 6.422388123 + 0.32041281224*LUSSP Dependent Variable: LUSGDP Method: Least Squares Date: 12/31/09 Time: 02:02 Sample: 1991Q1 2009Q2 Included observations: 74    Coefficient Std. Error t-Statistic Prob.                C 6.422388 0.140166 45.82 0 LUSSP 0.320413 0.015722 20.38041 0 R-squared 0.852266 Mean dependent var    9.274948 Adjusted R-squared 0.850214 S.D. dependent var    0.166293 S.E. of regression 0.064359 Akaike info criterion    -2.62203 Sum squared resid 0.29823 Schwarz criterion    -2.55975 Log likelihood 99.01496 Hannan-Quinn criter.    -2.59719 F-statistic 415.3609 Durbin-Watson stat    0.124101 Prob(F-statistic) 0          Unit Root test for residual Series Residual saved RUS T statistic Test critical values: 1% level 5% level 10% level With intercept -0.638033 -3.522887 -2.901779 -2.588280 With intercept and trend -1.430799 -4.088713 -3.472558 -3.163450 After saving the residuals from the 1st stage regression RUS I did the ADF test on it where we can see the t statistic value is literally higher than the 1%, 5% and 10% critical value in both the cases with intercept and with intercept and trend. As we can see the critical values are -3.552287, -2.901779 and -2.588280 with intercept, -1.430799, -3.472558 and -3.163450 in 1%, 5% and 10% level respectively. So the possibility for having long run relationship between GDP and stock price doesnt exist in case of USA. 2nd stage regression: Dependent Variable: LUSGDP Method: Least Squares Date: 01/05/10 Time: 21:36 Sample (adjusted): 1991Q2 2009Q2 Included observations: 73 after adjustments                   Coefficient Std. Error t-Statistic Prob. C 6.400276 0.051084 125.29 0 LUSSP 0.323107 0.005722 56.46591 0 RUS(-1) 0.972896 0.043361 22.43708 0 R-squared 0.981148 Mean dependent var    9.278975 Adjusted R-squared 0.980609 S.D. dependent var    0.163769 S.E. of regression 0.022805 Akaike info criterion    -4.683433 Sum squared resid 0.036405 Schwarz criterion    -4.589305 Log likelihood 173.9453 Hannan-Quinn criter.    -4.645922 F-statistic 1821.53 Durbin-Watson stat    2.153933 Prob(F-statistic) 0          Granger Causality test: Pair wise Granger Causality Tests Date: 01/05/10 Time: 22:03 Sample: 1991Q1 2009Q2 Lags: 3 Null Hypothesis: Observation F-Statistic Prob. LJSP does not Granger Cause LJGDP 71 1.46842 0.2315 LJGDP does not Granger Cause LJSP    0.7659 0.5173 After performing the causality tests on the series DLJGDP and DLJSP with lag 3 according to the causality table to reject the null hypothesis that GDP does not granger cause LJSP. No causal relationship exists between share price and GDP in Japan. Pair wise Granger Causality Tests Date: 01/05/10 Time: 22:18 Sample: 1991Q1 2009Q2 Lags: 3 Null Hypothesis: Observations F-Statistic Prob. LMSP does not Granger Cause LMGDP 71 14.8418 0.0000002 LMGDP does not Granger Cause LMSP    0.65292 0.584 We can see the same result when we performed the causality test LMGDP and LMSP. Here we cannot reject the null which shows that there is no causal relationship between stock price and GDP. Pair wise Granger Causality Tests Date: 01/05/10 Time: 22:22 Sample: 1991Q1 2009Q2 Lags: 3 Null Hypothesis: Observations F-Statistic Prob. LUSP does not Granger Cause LUGDP 71 4.17743 0.0092 LUGDP does not Granger Cause LUSP 0.58556 0.6267 Pair wise Granger Causality Tests Date: 01/05/10 Time: 22:24 Sample: 1991Q1 2009Q2 Lags: 3 Null Hypothesis: Observations F-Statistic Prob. LUSSP does not Granger Cause LUSGDP 71 2.50276 0.0671 LUSGDP does not Granger Cause LUSSP 0.51256 0.6751 Analysis of the result:

Ancient Egypt The Greatest Ancient Civilizations

Ancient Egypt was one of the greatest ancient civilizations in human history. Ancient Egypt was the longest lasting civilization in the ancient world and lasted for about 2,500 years. ancient Egypt was able to last so long because of their many great accomplishments. The most important thing that lead to the accomplishments and success of ancient Egypt was The Nile River. Ancient Egypt is often referred to as the â€Å"Gift of the Nile† because of how important the Nile River was to the success and longevity of ancient Egypt. Without the Nile River, ancient Egypt would have never been able to things like farm, use papyrus, build boats, trade or fish. The Nile River was the sole reason as to why ancient Egypt was able to become so successful. There are many different areas that ancient Egypt excelled in to help make them successful. The reason that ancient Egypt was able to become so successful was the various ways the ancient Egyptians used the Nile River. Some of the ways the ancient Egyptians used the Nile River was as a water source for agriculture and as a way of transportation for trade. One of the key areas that the Nile River helped develop in ancient Egypt was agriculture. The Nile River allowed for the Ancient Egyptians the ability to grow their own crops. The predictable annual flooding allowed for ancient Egypt to farm. In the article Sustainable Agriculture in Ancient Egypt, the author J. Donald Hughes states that â€Å"The sustainability of Egyptian agriculture wasShow MoreRelatedAncient Egypt : The Greatest Civilization Of The Past863 Words   |  4 PagesBelieved to have begun around 3100 BCE; the stories of ancient Egypt still live on today. Built along the Nile River; Egypt was once the greatest civilization of the past. Egypt built several groundbreaking architectural structures from the world’s first dams, to the first super structures predating the Ziggurat of Ur. 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Most popularly and in this context it can be referred to as an advanced state of human society, in HYPERLINK http://dictionary.reference.com/browse/which which  a high level of HYPERLINK http://dictionary.referenceRead MoreEssay about Ancient Egypt and Ancient Greece903 Words   |  4 Pagesâ€Å"Ancient Egypt and Ancient Greece† According to history there existed two of many important ancient civilizations that left a significant mark in the history of human development that even today leaves modern society in awe of its greatness. In spite of being distant civilizations, Ancient Egypt and Ancient Greece share similarities and difference in terms of how they practiced religion,political structure, everyday life style, and how they built the monumental architectures that continued to amazeRead MoreAncient Egypt : Ancient Egyptian Art1308 Words   |  6 Pages Religious Architechture in ancient Egypt Egyptian art has journeyed through the centuries as one of the most influential phenomenon in human civilization. From the Greeks to the Romans to the people of today, Egyptians and their beautiful representations in art and architecture have proven a legacy in the creations of certain landmarks, statues, and even advertisements. The Greeks derived many of their statues from Egyptian sculptures, such as the Kouros 600 B.C.Read MoreAncient Egypt and Mondern Society981 Words   |  4 Pagesdozens of great civilizations have risen from nothing and fallen back into obscurity. Not all civilizations, however, leave a lasting mark on the world, especially not one so profound that influences the world as it exists today. One such civilization that has had a profound impact on daily modern lives was that of Ancient Egypt. Their systems of religion and technological innovation helped not only to leave a permanent impression on the world, but also served to mold both the civilizations that dir ectlyRead MoreThe Achievements Of Ancient Egypt1291 Words   |  6 PagesTemples, tombs and pyramids have all witnessed this earth for thousands of years. These architectural achievements show us that Egypt s greatest virtue lie in its architecture. One Ancient Egypt’s greatest cultural achievements was undoubtedly in their architecture associated with religion. If you were to travel to Egypt what would you expect to see? Pyramid after temple after tomb, each standing the test of time. They all stand out, they are all associated with religious beliefs, they all haveRead MoreThe Impact of Ancient Egypt1250 Words   |  5 PagesThe Impact of Ancient Egypt Ancient Egypt is a civilization of wealth and structure that flourished along the Nile River in northeastern Africa from about 3300 B.C to 30 B.C. In over 3,000 years, one of the most sophisticated and creative societies advanced where no other civilization did. 2,000 years later, it would be hard to think about the world without the impact of ancient Egypt, because it seems to have significantly affected every field of our American culture. The Egyptians have heavilyRead MoreAncient Egypt And Ancient Egyptian Civilization1495 Words   |  6 Pagesâ€Å"Egypt treated its women better than any of the other major civilizations of the ancient world† (Thompson). Over 6,000 years ago, the powerful civilization of Ancient Egypt began, lasting for almost 30 centuries. Ancient Egyptians treated their cats like royalty, used spells and animal flesh to heal almost anything (Napoli Balit). Most Importantly, the people of Ancient Egypt valued their polytheistic religion above everyth ing, they worked hard in order to get into the paradise of the afterlifeRead MoreAncient Sudan (Nubia)1715 Words   |  7 Pagesand southern Egypt. Their history and traditions can be traced to the dawn of civilization. They settled first along the banks of the Nile from Aswan. Along the Nile, they developed one of the oldest and greatest civilizations in Africa until they lost their last kingdom five centuries ago. The Nubians remained as the main rivals to the homeland of Africa’s earliest black culture with a history that can be traced from 3800 B.C. onward through the monuments and artifacts. Ancient Nubia was a landRead MoreEgyptian, Islamic and Roman Architecture Essay1539 Words   |  7 PagesEgyptian Civilization: I chose Egyptian civilization because it’s known as the birthplace of modern civilization. Another reason I chose Egyptian civilization is because its contributions to the world still seen, studied and absorbers. Egypt contribution has come along way and has mad an impact in on thousands of cultures worldwide. Some of Egypt’s contributions I will address are arts, literature and architecture. The Egyptians had little wood to build their buildings and monuments. The Egyptians