Globalization and Multinational Corporations Essay

Globalization and Multinational Corporations - Essay Example The globalisation concept does not reveal the challenges leaving the companies to look at the positive side of the concept. There are very many management challenges due to different cultural issues and government intervention in different nations. As it will be discussed in the paper, countries differ in their levels of technology, development, availability of labour and resources and policies targeting trade and taxation. Both local and global companies normally do not have the right information concerning such issues thus end up making the wrong decisions in location and strategies (Karsten, 2000, pp.120-134). The best example of a multinational company to use is the Coca Cola Company as it has gone through very many challenges as it was in its race to meeting the global concept. Global strategy is defined in business as guidelines of an organisation to globalisation. For a firm to succeed in expanding globally it requires to define the extent to which it can expand its service and products provision. Local and global enterprises are facing a lot of challenges in expanding globally and this does not leave out the Coca Cola Company. The decisions Coca Cola makes on where it needs to locate its business are highly affected by the fact it usually defines how far it needs to allocate. Many multinational organisations that are failing expand unnecessarily. This occurs because of the lack of complete information on the different economic status of different nations. This limits them in attaining competitive advantage within the corporate world (Gupta, 2008, pp. 20-21). Strategic management Strategic management entails to plan and forecast, command, control, co-ordinate and organize. It is important for organizations to practice effective modes of management to ensure that at the end of the day they achieve their main objective; profit making. Though strategic management entails all this conditions, it is evident that they are not practised in all organisations globally. This is so because countries differ in their adoption of management strategies. This makes it hard for an organisation in a well established country that practises high management concepts to incorporate the concepts in another country that has not yet implemented them (Ghoshal, 1987, pp. 425-440). However, with Coca Cola being a multinational company for a very long time, it has identified that different areas need different ways of management though people are being urged to embrace global ways of management. Business courses and beliefs are very different in all nations. For instance, in developing countries, the business courses are outdated and it is only recently that they are trying to educate its people on the global strategic management principles. Many organisations that want to expand globally are misled by believing that all nations embrace the concept globalisation thus they set up their businesses in different localities only to find that they do not use the global strategies of management. This makes them to lag behind in making profits because they lack competent individuals to employ. It is evident that for a business to flourish there must be availability of labour within the area. Some multinational entities are forced to employ individuals from other countries which is a more expensive strategy because they demand a high pay for relocating from their native homes (Ghauri, 1995, pp.

What are the customer service channels people are more willing to use Essay

What are the customer service channels people are more willing to use to resolve problems The least willing Phone-based, face to face, self-service, online channels - Essay Example According to Perlitz & Hutton (2010), it is imperative for the customers to establish a sense of feeling that the business considered as interesting. Sending an apology through an email is one way of showing concern to the client. In addition, making a phone call is a path that many people are willing to take in solving customer issues (Perlitz & Hutton, 2010). Emphasize of the call is to inform the client that the business is handling the issue coupled by realistic promises that will ensure that the issue never comes up again. After fully fixing the problem, it would show courtesy to call or send an email to the customer on the same. Face-to-face and self-service are two methods that people least want to use when dealing with an issue involving a customer. Foremost, face-to-face channel creates a lot of unnecessary drama within the business premises. Usually, the customer attempts to prove a point that the business personnel are responsible for the problem. In the processing of putting across the point, the customers tend to become aggressive and may interfere with normal business operations (Perlitz & Hutton, 2010). On the other hand, self-service creates a huge inconvenience to the business because the customer is likely to interfere with the resources of the business. More often than not, Self-service does not resolve a problem. If anything, it fuels the problem further there will be no understanding between the parties. Some customer service channels are more preferred in resolving client issues than others. The preferred ones include online channels and phone calls while the least preferred include face-to-face and self-service. The preferred ones tend to create an understanding that ultimately resolves the issue. The least preferred channels drives intended issue further thereby causing more

The Economic Impact Of The One-Child Policy

The Economic Impact Of The One-Child Policy The One-Child Policy helped China to raise its economic growth in the past decades. China was able to control the rate of the population growth lower than the rate of the GDP growth, and thus the GDP per capita increases dramatically in the past decades. In regression model 1, over 53% of the economic growth can be explained by the policy; in regression model 2, over 74% of the economic growth can be explained by the policy. Hence this paper has shown the change in the economic growth of China could be explained by the effects of the One-Child Policy. Although the crude birth rate is not shown to have long term or short term effect on the GDP per capita, the gross fixed capital formation has a significant positive impact on the GDP per capita. The gross fixed capital formation could not have increased that much without the presence of the One-Child Policy. While the population growth decreases, more resources are used to improve the living standard. The long term effect of the One-Child policy was also considered in the research. The results obtained in regression model 2 have indicated the graduate economic growth in China can be well explained by the effect of the One-Child Policy. The coefficients of the crude birth rate were negative in both regression models; it suggested that part of the Malthusian theory and the neo-Malthusian theory were support. The main criticism of the theories was the theories did not account the advance in the technology, and thereby the food supply has increased faster than arithmetic progress. The science and technology in China has evolved tremendously in the past thirty years since the One-Child Policy has implemented. Therefore, the Malthusian theory and the neo-Malthusian may not be applicable in the modern world today. This view has been support in the work of Galor and Weil (1999, pp.150-154). Moreover, part of the Revisionism theory was supported. The theory suggested that the population growth does not hinder the population growth in dense area and China is a densely populated country. In regression model 2, lagged crude birth rate was used. Since the population will enter the workforce at the aged of 16, the crude birth rate was tested for the impact on the GDP per capita. The variable was found insignificant to explain the changes in the GDP per capita. The results suggested that China was not facing the diminishing return of labour. Since the crude birth rate is not correlated with the growth of GDP per capita, there is no population theory which is totally supported in the analysis of China. Although China was not facing a Malthusian dynamic of overpopulation and diminishing return of labour dynamics, it is essential for the implementation of the One-Child Policy. If the population was not controlled and continued to increase, China would soon have to face the problems associated with overpopulation and diminishing return to labour. In conclusion, the decision of the implementation of the One-Child Policy in 1979 was supported in this research. Although the One-Child Policy has shown to have benefitted the economic growth of China in the short term and 16 years long term, it may have an adverse effect in the very long term. The one child now has to support his/her two parents and four grandparents. Therefore, the implementation of the One-Child Policy was supported in 1979 but the decision of the continuation of the One-Child Policy is to be remained uncertain. 6.2 Limitations of the Study The results obtained in the research only give a suggestion of the implementation of the One-Child Policy. There are certain limitations in the research. A number of measurement issues need to be addressed are stated below. As a proxy of the education level, it is better to use the average number of schooling as it gives a clearer picture of the education level of the population. Unfortunately, the National Bureau of Statistics of China has not recorded this variable for the period, 1979 2007. As a proxy of the living standard, it is better to use the gross fixed capital formation per capita as it accounts the fact that the living standard increases faster than the population growth. Unfortunately, the size labour force was also not recorded. (Gross fixed capital formation per capita = Gross fixed capital formation/ Workforce) There are several missing figures in the data. The missing figures usually occur in 1980 to 1985. Although interpolation has used to calculate the missing data in between, the lack of data may lead to inaccuracies in the results. There may be inaccuracies in the figures of the crude birth rate. Many illegal birth of baby girls occurred due to the traditional son preference in China. The actual crude birth rate should be higher as the illegal births were not recorded. The lack of the sample sizes may also lead to inaccuracies in the results which determine the long term effect of the One-Child Policy. There are only 13 observations after the adjustments, which may lead to no significant variable being detected even if there is a one present. Furthermore, only the labour market was accounted to determine the long term effect of the One-Child Policy in this study. The 4-2-1 problem can not accounted in the study, as the policy has only implemented for 31 years and it is not long enough for the analysis of this effect. Although the implementation of the One-Child Policy was generally supported in the results, it may not be supported in different areas of China. The average crude birth rate was used in the research, and thus the decision of the One-Child Policy may not be supported in individual cities. E.g. Urban areas The official numbers from the National Bureau of Statistics of China may have exaggerated the growth of GDP [The Economist: Chinas dismal statistics (Anon., 2009)], which will lead to the overestimation of the effect of the One-Child Policy. 6.3 Potential Areas of Study The research provides general study on the implementation of the One Child Policy in China. It can be further studied to achieve a deeper level of understanding of the policy. As mentioned in the previous section, the analysis of the implementation of the One-Child Policy may differ from cities. The number of births has been largely reduced, and the population started to age. Urban areas may have started to face the shortage of labour and problems related to demographic aging. This suggestion has been supported as the citizens in Shanghai were encouraged to have two children per family since 2009 (Xie Linli, 2009). Furthermore, the action taken in Shanghai has supported my conclusion in the research which China was not facing the diminishing return of labour. The relationship between the GDP per capita and the crude birth rate in different cities can be revised by cities. The population theories will possibly be supported by the analyses in different cities. Same methods and tests ca n be used and the data required can also be found in the official website of the National Bureau of Statistics of China. Since the One-Child Policy was criticised to have violated the human rights, the results obtained from this further research will aid the find suggestions to other family planning in China. If the crude birth rate was found positively correlated with the economic growth in different cities, some policy suggestions can be made. For example, more births can be allowed or only the spacing between births is controlled. Alteration of the policy will possibly bring advantages to China. The criticisms of the family planning may reduce; the number of female infanticides may also be reduced, and may lead to the further increase in the economic growth in China. The One-Child Policy has always been a source of controversy since its execution; there are many more potential studying areas. In the analysis chapter, the growth in the number of tertiary enrolment in China was found insignificant to explain the economic growth. Another independent variable such as the percentage of people that have finished secondary schools can be used as a proxy of the education level. More research can be done on the relationships between the One-Child Policy, education and crude birth rate. The relationship between the variables can also be found using the time series OLS regression. Although the education level of the people was increased by the One-Child Policy, there are other factors that affect the education level. As the education level of the people increased, the desire of improving the qualities of life may increase and the desire having children may decrease. As a result, the crude birth rate may not only be affected by the One-Child Policy, but also the increased level of education. The results obtained can help to notice if the effect of the One-Child Policy was overestimated in the present study, and at the same time help to gain a better understanding of the economic growth in China. Further study could include analysing the sex ratios in China. It has always been an active debating topic. The One-Child Policy has affected to the sex ratio due to the traditional son preference in China. The sex selective abortion has led to the excess births of males and the unbalance sex ratio in China. A research has been done on the unbalanced sex ratios, and the researcher, Hesketh states that, males under the age of 20 exceeded females by more than 32 million in China, and more than 1.1 million excess births of boys occurred. Since there are 32 million more males than females, some of the men will be unable to get married and have a family. Fewer births will be occurred as there are less married couples, and therefore the unbalanced sex ratios may also decrease the crude birth rate of the population. Moreover, the children may have to take care even more elderly rather than only their own 2 parents and 4 parents, but their relatives as well. The GDP per capita may be negativ ely affected by the sex ratios. Same as the suggested research in the previous paragraph, the results obtained can help to notice if the effect of the One-Child Policy was overestimated in the present study. The last suggestion of the potentials area of study is based on the past of the One-Child Policy effects on the economic growth, and to estimate the future effect on the economy. The changes in the variables which are affected by the One-Child Policy can be predicted. The least squares regression can be used to estimate the lines of best fit. Based on the predicted changes of the variables, the growth of GDP in the future can then be estimated. Further analysis on the implementation of the One-Child Policy can be done along with the results obtained. The Peoples Republic of China seems to have faith in the influences on the One-Child Policy. As to how deep the influence of the One-Child Policy, only time can tell.

Othello :: essays research papers

Othello. Othello is the title of the character and play that we all studied earlier this semester. However, it is Othello the character that I intend to discuss. Othello is the husband to the beautiful and innocent Desdemona, whom he murders because the villainous and honest Iago has misled him. A Moorish general in Venice, a society plagued with racism and where adultery is neither condemned nor approved of, Othello is in the midst of a society that will hinder and not support his progress. The central theme of the drama is the alteration of a noble lover to a raving killer, under the influence of the deliberate connivance of his aide, Iago, who convinces him that his wife is having a love affair with another officer named Cassio. Unable to trust the falsely corrupted Desdemona - he lacks the essential element of love and it is this absence of trust that causes Othello to disintegrate morally. This destructiveness extends to his own suicide, when his error of judging Desdemona to be an adulteress fails him. Our closely woven relationship with this traumatised and gullible Othello causes us to suffer with him, as he experiences emotional agonies, such as the destruction of his once reputable nobility, character and marriage to the young Desdemona. Through Act II, Scene I, Othello presents himself to us as a grandly positive and content character, "It gives me wonder great as my content To see you here before me. O my soul's joy!" (Act II, Scene II). At this stage in the play Othello has also assembled his character to impose on us an impression, that he is a noble and prominent figure in the Venetian establishment, and respected military man and a loving husband. He carries himself with an impressive dignity while frankly delighting in his young wife's unconditional love, which he values above the "seas worth", (Act II, Scene I). When the couple defend their marriage against the prejudiced Brabantio, father to Desdemona, who associates Othello with witchcraft, (because Othello is black), in Act I, Scene III, it becomes evident that the couple share an unconditional love for one another. However, in the second half of the play Othello abandons this perfect love, for a blind and unfounded jealousy too strong to act in a just manner. He loses all faith not only in Desdemona, but especially himself, "That's he that was Othello; Here I am.

Digital and Analog TV Essay

On February 17, 2009, the Congress of the United States mandates the full shift to digital television transmission. The law is perceived to bring several benefits to the US viewing public. Broadcast frequency bands will be available mainly for public safety purposes, for example, police and fire department concerns. Remaining portions of the old TV broadcast spectrum can be offered for technologically advanced applications such as wireless broadband. The use of digital-capable television sets allows American viewers more choices of what programs to watch, since digital broadcasts can accommodate so much more programs (Federal Communications Commission, 2008). The law is not expected to be received openly by the television viewing public, 100 percent. Since it leaves them no choice but to convert millions of TV sets from analog to digital and give up the true fidelity that analog audio signals offer. This paper aims to point out the differences of digital and analog TV. By doing so, advantages and disadvantages of each can be compared and the individual viewer can make a better choice. Robert Silva (2008) lists differences between analog TV and Digital TV. He says these these differences lie mainly in the manner of transmitting broadcasts, signal content within a bandwidth in the broadcast spectrum, and the ability to broadcast in widescreen (16Ãâ€"9) format. Transmission Analog television transmission is based on and started after World War II with black and white broadcasts. It complied with the US analog TV standard known as NTSC. After several years, color broadcasting was introduced and accommodated under the NTSC system. The video is transmitted through the AM radio band while audio is transmitted through the FM band. The reception quality depends on the distance from the television station transmitters and obstacles in between. The farther away from the transmission station the TV reception is more prone to ghosting and other video disturbances. Although analog transmission can accommodate all the technicalities of high fidelity reception, the assigned bandwidth to a television channel restricts and limits broadcast quality. Digital TV is based on modern digital technology. It was designed for BW and color broadcasts as well as audio. It handles information in the same manner as computers: on (with a binary value of â€Å"1†) or off (with a binary value of â€Å"0†). Digital broadcasts allow viewers to see uniform reception quality regardless of the distance from the transmitter. Either the digital television receives the broadcast or the TV screen remains blank (it does not receive anything at all). Signal Content Digital TV broadcasts can accommodate complete video, audio, and other information signals within the same bandwidth. Furthermore, digital television can accommodate advances in technology like High Definition (HDTV) signals. In contrast, analog TV broadcast can only send limited traditional video signals. Format The development of wide screen format programming allows the broadcast of the 16Ãâ€"9 format. Today, widescreen LCD television are getting more popular; but still expensive. It offers the advantage of portraying on the TV screen wide footages of events without the camera lens distortion caused by distances. Furthermore, the widescreen image occupies the whole digital television screen. On the other hand, analog television sets will show widescreen images with portions on top and below blacked out. The widescreen format may not be important to the regular TV viewer. For millions of television watchers, the old analog screen is good enough. Conclusion Paul Wotel (2008) gives an objective assessment of the advantages and disadvantages of both digital and analog television. Some people may opt for the old traditional analog equipment such as phones while others prefer the cordless digital phones. If you want sound fidelity, he recommends the old phones. For more advanced applications, such as the PABX systems, he recommends a digital system. The same reasoning may be applied to television sets. However, the present situation requires new priorities which did not exist before. Today, there is much concern on security and priority is given to police and fire department communications. By requiring television stations to convert to digital transmission, most of the broadcast bandwidth can be assigned to security applications. The advantages of digital television allow the viewing public to benefit from the information age we find ourselves in. Digital television can also take advantage of the internet which has become part of the lives of many, particularly the young generation. Considering the continuing evolution in information and entertainment technology we just have to follow the trend – out with old, in with the new.

Stability of Beta over Market Phases

International Research Journal of Finance and Economics ISSN 1450-2887 Issue 50 (2010)  © EuroJournals Publishing, Inc. 2010 http://www. eurojournals. com/finance. htm Stability of Beta over Market Phases: An Empirical Study on Indian Stock Market Koustubh Kanti Ray Assistant Professor, Financial Management at Indian Institute of Forest Management (IIFM), Bhopal, India. E-mail: [email  protected] ac. in Abstract The significant role played by beta in diverse aspects of financial decision making has forced people from small investors to investment bankers to rethink on beta in the era of globalization.In the present changing market condition, it is imperative to understand the stability of beta which augments an efficient investment decisions with additional information on beta. This study examined the stability of beta for India market for a ten year period from 1999 to 2009. The monthly return data of 30 selected stocks are considered for examining the stability of beta in diffe rent market phases. This stability of beta is tested using three econometric models i. e. using time as a variable, using dummy variables and the Chow test. The results obtained from the three models are mixed and inconclusive.However there are 9 stocks where all the three models reported similar signal of beta instability over the market phases. Keywords: Stability of Beta, Phase wise beta, Indian Market Beta, Dummy Variable, Chow Test 1. Introduction The Capital Asset Pricing Model (CAPM) developed by Sharpe (1964), Lintner (1965) and Mossin (1966) has been the dominating capital market equilibrium model since its initiation. It continues to be extensively used in practical portfolio management and in academic research. Its essential implication is that the contribution of an asset to the variance of the market portfolio – he asset’s systematic risk, or beta risk – is the proper measure of the asset’s risk and the only systematic determinant of the asse t’s return. Risk is the assessable uncertainty (Knight, 1921) in predicting the future events that are affected by external and internal factors. Sharpe (1963) had classified risks as systematic risk and unsystematic risk. The elements of systematic risk are external to the firm. The external factors are changes in economic environment, interest rate changes, inflation, etc. On the other hand, internal factors are the sources of unsystematic risk.Unsystematic risks are categorized as business risk or financial risk specific to the firm. The systematic risk related with the general market movement cannot be totally eradicated through diversification. The unsystematic risk, which is confine to a firm, can be eliminated or reduced to a considerable extent by choosing an appropriate portfolio of securities. Some of the sources of unsystematic risk are consumer preferences, worker strikes and management competitiveness. These factors are independent of the factors effecting stock market.Hence, systematic risk will influence all the securities in the market, whereas unsystematic risk is security specific. International Research Journal of Finance and Economics – Issue 50 (2010) 175 Theoretically defined, beta is the systematic relationship between the return on the portfolio and the return on the market (Rosenberg and Marathe, 1979). It refers to the slope in a linear relationship fitted to data on the rate of return on an investment and the rate of return of the market (or market index). Beta is a technique of telling how volatile a stock is compared with the rest of the market.When the return on the portfolio is more than the return on the market, beta is greater than one and those portfolios are referred to as aggressive portfolios. That means, in a booming market condition, aggressive portfolio will achieve much better than the market performance. While in a bearish market environment the fall of aggressive portfolios will also be much prominent. O n the other hand, when the return on portfolio is less than the market return, beta measure is less than one and those portfolios are treated as defensive.In case of defensive portfolios, when the market is rising, the performances associated with it will be less than the market portfolio. However, when the market moves down, the fall in the defensive portfolios would also be less than the market portfolio. In those situations where, the return of the portfolio accurately matches the return of the market, beta is equal to one that rarely happens in real life situations. Beta estimation is central to many financial decisions such as those relating to stock selection, capital budgeting, and performance evaluation. It is significant for both practitioners and academics.Practitioners use beta in financial decision making to estimate cost of capital. Beta is also a key variable in the academic research; for example it is used for testing asset pricing models and market efficiency. Given the importance of this variable a pertinent question for both practitioners and academics is how to obtain an efficient estimation. This study is aimed at testing the beta stability for India. Further the stability of beta is of great concern as it is a vital tool for almost all investment decisions and plays a significant role in the modern portfolio theory.The estimation of beta for individual securities using a simple market model has been widely evaluated as well as criticized in the finance literature. One important aspect of this simple market model is the assumption of symmetry that propounds the estimated beta is valid for all the market conditions. Many studies questioned this assumption and examined the relationship between beta and market return in different market conditions, but the results are mixed and inconclusive. In this paper, an attempt is made to investigate the stability of beta in the Indian stock market during the last 10 years i. . from August 1999 to August , 2009. With this objective, the paper is divided into five sections including the present section. Section 2 reviews the existing literature and discusses the findings of major empirical researches conducted in India and other countries. Section 3 describes the data sources and methodology. Section 4 outlines the results of tests for investigating the stability of beta and its findings. Section 5 is dedicated to summary, conclusion and scope for further research in the area. 2. Literature reviewSeveral studies are carried out to study the nature and the behavior of beta. Baesel (1974) studied the impact of the length of the estimation interval on beta stability. Using monthly data, betas were estimated using estimation intervals of one year, two years, four years, six years and nine years. He concluded that the stability of beta increases significantly as the length of the estimation interval increases. Levy (1971) and Levitz (1974) have shown that portfolio betas are very stable w hereas individual security betas are highly unstable.Likewise Blume (1971) used monthly prices data and successive seven-year periods and shown that the portfolio betas are very stable where as individual security betas are highly unstable in nature. He shows that, the stability of individual beta increases with increase in the time of estimation period. Similar results were also obtained by Altman et al (1974). In both the cases, initial and succeeding estimation periods are of the same length. Allen et al. (1994) have considered the subject of comparative stability of beta coefficients for individual securities and portfolios.The usual perception is that the portfolio betas are more stable than those for individual securities. They argue that if the portfolio betas are more stable than those for individual securities, the 176 International Research Journal of Finance and Economics – Issue 50 (2010) larger confidence can be placed in portfolio beta estimates over longer peri ods of time. But, their study concludes that larger confidence in portfolio betas is not justified. Alexander and Chervany (1980) show empirically that extreme betas are less stable compared to interior beta.They proved it by using mean absolute deviation as a measure of stability. According to them, best estimation interval is generally four to six years. They also showed that irrespective of the manner portfolios are formed, magnitudes of inter-temporal changes in beta decreases as the number of securities in the portfolios rise contradicting the work of Porter and Ezzell (1975). Chawla (2001) investigated the stability of beta using monthly data on returns for the period April 1996 to March 2000. The tability of beta was tested using two alternative econometric methods, including time variable in the regression and dummy variables for the slope coefficient. Both the methods reject the stability of beta in majority of cases. Many studies focused on the time varying beta using cond itional CAPM (Jagannathan and Wang (1996) Lewellen and Nagel (2003)). These studies concluded that the fluctuations and events that influence the market might change the leverage of the firm and the variance of the stock return which ultimately will change the beta.Haddad (2007) examine the degree of return volatility persistence and time-varying nature of systematic risk of two Egyptian stock portfolios. He used the Schwert and Sequin (1990) market model to study the relationship between market capitalization and time varying beta for a sample of investable Egyptian portfolios during the period January, 2001 to June, 2004. According to Haddad, the small stocks portfolio exhibits difference in volatility persistence and time variability. The study also suggests that the volatility persistence of each portfolio and its systematic risk are significantly positively related.Because of that, the systematic risks of different portfolios tend to move in a different direction during the per iods of increasing market volatility. The stability of beta is also examined with reference to security market conditions. For example, Fabozzi and Francis (1977) in their seminal paper considered the differential effect of bull and bear market conditions for 700 individual securities listed in NYSE. Using a Dual Beta Market Model (DBM), they established that estimated betas of most of the securities are stable in both the market conditions.They experienced it with three different set of bull and bear market definitions and concluded with the same results for all these definitions. Fama and French (1992, 1996), Jegadeesh (1992) and others revealed that betas are not statistically related to returns. McNulty et al (2002) highlight the problems with historical beta when computing the cost of capital, and suggest as an alternative- the forward-looking market-derived capital pricing model (MCPM), which uses option data to evaluate equity risk. In the similar line, French et al. (1983) m erge forward-looking volatility with istorical correlation to improve the measurement of betas. Siegel (1995) notes the improvement of a beta based on forward-looking option data, and proceeds to propose the creation of a new derivative, called an exchange option, which would allow for the calculation of what he refers to as â€Å"implicit† betas. Unfortunately the exchange options discussed by Siegel (1995) are not yet traded, and therefore his method cannot be applied in practice to compute forward-looking betas. A few studies are carried out to explore the reason for instability of beta.For example, Scott & Brown (1980) show that when returns of the market are subjected to measurement errors, the concurrent autocorrelated residuals and inter-temporal correlation between market returns and residual results in biased and unstable estimates of betas. This is so even when true values of betas are stable over time. They also derived an expression for the instability in the esti mated beta between two periods. Chen (1981) investigates the connection between variability of beta coefficient and portfolio residual risk. If beta coefficient changes over time, OLS method is not suitable to estimate portfolio residual risk.It will lead to inaccurate conclusion that larger portfolio residual risk is associated with higher variability in beta. A Bayesian approach is proposed to estimate the time varying beta so as to provide a precise estimate of portfolio residual risk. Bildersee and Roberts (1981) show that during the periods interest rates fluctuate, betas would fluctuate systematically. The change would be in tune with their value relative to the market and the pattern of changes in interest rate. International Research Journal of Finance and Economics – Issue 50 (2010) 177Few research studies are available in the Indian context to examine the factors influencing systematic risk. For example, Vipul (1999) examines the effect of company size, industry gro up and liquidity of the scrip on beta. He considered equity shares of 114 companies listed at Bombay Stock Exchange from July 1986 to June 1993 for his study. He found that size of the company affects the value of betas and the beta of medium sized companies is the lowest which increases with increase or decrease in the size of the company. The study also concluded that industry group and liquidity of the scrip do not affect beta.In another study, Gupta & Sehgal (1999) examine the relationship between systematic risk and accounting variables for the period April 1984 to March 1993. There is a confirmation of relationship in the expected direction between systematic risk and variables such as debt-equity ratio, current ratio and net sales. The association between systematic risk and variables like profitability, payout ratio, earning growth and earnings volatility measures is not in accordance with expected sign. The relationship was investigated using correlation analysis in the stu dy. 3. Data Type and Research MethodologyThe data related to the study is taken for 30 stocks from BSE-100 index. The top 30 stocks are chosen on the basis of their market capitalization in BSE-100 index. These 30 stocks are selected from BSE100 stocks in such a way that the continuous price data is available for the study period. The adjusted closing prices of these 30 stocks were collected for the last 10 years period i. e. from August 1999 to August 2009. The stock and market (BSE-100) data has been collected from prowess (CMIE) for the above period. BSE-100 index is a broad-based index and follows globally accepted free-float methodology.Scrip selection in the index is generally taken into account a balanced sectoral representation of the listed companies in the universe of Bombay Stock Exchange (BSE). As per the stock market guideline, the stocks inducted in the index are on the basis of their final ranking. Where the final rank is arrived at by assigning 75 percent weightage t o the rank on the basis of three-month average full market capitalization and 25 percent weightage to the liquidity rank based on three-month average daily turnover & three-month average impact cost.The average closing price for each month of 30 socks is computed for the period August 1999 to August 2009. Therefore we have 120 average monthly prices for each of the 30 stocks included in the research. The following method has been used to compute the monthly return on each of the stock. P i,t – P i,t-1 ri,t = –––––––––– P i, t-1 Where: P i,t = Average price of stock â€Å"i† in the month t Pi,t-1 = Average price of stock â€Å"i† in the month t-1 r i,t= Return of ith stock in the month t. The monthly market return is computed in the following way: Bt – Bt-1 mt = –––––––––– B t-1Where: Bt = BSE-100 Index at time period t Bt-1 = BSE-100 Index at time period t-1 mt = Market return at time period t. After the monthly stock and market returns are calculated as per the above formula, we identified the different market phases to compute beta separately. The market phases are identified, by creating a cumulative wealth index from the market returns. The cumulative wealth index data is presented in annexure-1. As per the cumulative wealth index, we identified five different market 178 International Research Journal of Finance and Economics – Issue 50 (2010) hases in BSE-100 index. We recognized that there are three bullish phases (Jan-1999 to Feb-2000, Oct-2001 to Dec-2007 and Dec-2008 to August 2009) and two bearish phases (Mar-2000 to Sept2001, Jan-2008 to Nov-2008). The summary of different market phases is depicted in Table -1& figure-1 below. Table-1: Different Market Phases Market Phases Phase I Phase II Phase III Phase IV Phase V Market Phase Timing Start End Jan-1999 Feb-2000 Mar-2000 Sep-2 001 Oct-2001 Dec-07 Jan-2008 Nov-08 Dec-2008 Aug-09 Market Type Bullish Bearish Bullish Bearish Bullish Figure-1: Different Market PhasesAfter these five market phases are identified, the beta value has been computed for each stock for each market phases following the below mentioned regression equation. ri,t = ? + ? mt + e (1) ri,t = Return on scrip i at time period t mt = Market rate of return at time period t e = Random error ? & = Parameters to be estimated The above regression equation is applied to calculate beta coefficient of each stocks for each market phases separately and taking the entire ten years period. As the objective of the paper is to test the stability of beta in different market phases, the hypothesis has been set accordingly.The null hypothesis (H0) being the beta is stable over the market phases, whereas the alternative hypothesis (H1) is that the beta values are not stable and varies according to phases in the market. The hypothesis has been tested with the help of three econometric models- using time as a variable, using dummy variables to measure the change of slope over the period and through Chow test. International Research Journal of Finance and Economics – Issue 50 (2010) 179 3. 1. Testing the Stability of Beta using time as a variableIn case of measuring stability of beta using time as a variable, in the above regression model (1) another variable i. e. † t mt† is used as a separate explanatory variable. Where the time variable t takes a value of t=1 for the first market phase, t=2 for the second market phase and so on for all other market phases identified. In this method the objective is to see whether the beta values are stable over time or not. After including the tmt variable, the above regression model (1) can be written as: ri,t = ? + ? 1mt + ? 2( t*mt) + e (2) The above regression equation can be re-framed as below: ri,t = ? + (? + ? 2*t )*mt + e (2) To test the stability of beta, we basically have to see whether the expression ? 2 is significant or not. If it is significant, we need to reject the null hypothesis and accept alternative hypothesis. It is implied that the sensitivity of stock return to market return i. e. (? 1 + ? 2*t)* mt changes with time, and hence, beta is not stable. If ? 2 is not significant, (? 1 + ? 2*t)* mt will get reduced to ? 1*mt , implying that ? 1, or the beta of stock, does not vary with time and is thus stable over time. The statistical significance of ? 2 is tested using the respective p-values. . 2. Testing the Stability of Beta using dummy variable In case of the second method of testing the beta stability, dummy variables are used in above mentioned regression equation (1) for the slope coefficients. As five market phases discovered, there are 4 dummy variables used in the new equation (Levine et al. 2006). The new regression equation is reframed as follows: ri,t = ? 0 + ? 1* mt + ? 2*D1* mt + ? 3*D2* mt + ? 4*D3* mt + ? 5*D4*mt + e (3) Where: D1 = 1 for phase 1 (Jan 1999 to Feb 2000) data = 0 otherwise. D2 = 1 for phase II (May 2000 to Sept 2001) data = 0 otherwise D3 1 for phase III (Oct 2001 to Dec 2007) data = 0 otherwise D4 = 1 for phase IV (Jan 2008 to Nov 2008) data = 0 otherwise = return on stock I in period t. r i,t mt = return on market in period t. e = error term and ? 0, ? 1, ? 2, ? 3, ? 4 & ? 5 = coefficients to be estimated. As there are 5 market phases, we use 4 dummy variables in the above equation (3). The use of 5 dummy variable would lead to a dummy variable trap. We treat the 5th phase viz. Dec-08 to Aug-09 as the base period. The significance of ? 2, ? 3, ? 4 and ? 5 will tell us whether the beta is stable over the time periods or not.For the beta to be truly stable over the entire period, all coefficients like, ? 2, ? 3, ? 4 and ? 5 should be statistically insignificant and where we need to accept the null hypothesis. The logic is that if ? 2, ? 3, ? 4 and ? 5 are insignificant, the equation reduces to the following, thus implying that beta is stable over time. ri,t = ? 0 + ? 1*mt + e (4) th 3. 3. Testing for Structural or Parameter Stability of Regression Model: The Chow Test In the third method, for structural or parameter stability of regression models, the Chow test has been conducted (Gujarati, 2004).When we use a regression model involving time series data, it may happen 180 International Research Journal of Finance and Economics – Issue 50 (2010) that there is a structural change in the relationship between the regress and the regressors. By structural change, we mean that the values of the parameters of the model do not remain the same through the entire time period. We divide our sample data into five time periods according to the different market phases identified earlier.We have six possible regressions for each stock (five regressions for each market phases and one for the whole ten year period). The regression equations are mentioned below. ri,t = ? 1 + ? 2 mt + ut (5) (6) r i, t = ? 1 + ? 2mt + ut Equation (5) is for each market phases and equation (6) is for the whole period. There are 128 observations (n=128) for the whole period and n1=14, n2=19, n3=75, n4=11 and n5=9 are the number of observations for phase-I to phase-V respectively. The u’s in the above regression equations represent the error terms.Regression (6) assumes that there is no difference over the five time periods and therefore estimates the relationship between stock prices and market for the entire time period consisting of 128 observations. In other words, this regression assumes that the intercept as well as the slope coefficient remains the same over the entire period; that is, there is no structural change. Now the possible differences, that is, structural changes, may be caused by differences in the intercept or the slope coefficient or both. This is examined with a formal test called Chow test (Chow, 1960). The mechanics of the Chow test are as follows: First the regression (6) is estimated, which is appropriate if there is no parameter instability, and obtained the restricted residual sum of squares (RSSR) with df = [(n1+n2+n3+n4+n5) ? k], where k is the number of parameters estimated, 2 in the present case. This is called restricted residual sum of squares because it is obtained by imposing the restrictions that the sub-period regressions are not different. Secondly estimated the phase wise other regression equations and obtain its residual sum of squares, RSS1 to RSS8 with degrees of freedom, df = (no of observations in each phase ? ). Since the five sets of samples are deemed independent, in the third step we can add RSS1 to RSS8 to obtain what may be called the unrestricted residual sum of squares (RSSUR) with df = [(n1+n2+n3+n4+n5)? 2k]. Now the idea behind the Chow test is that if in fact there is no structural change (i. e. , all phases regressions are essentially the same), then the RSSR and RSSUR should not be statistical ly different. Therefore in the fourth step the following ratio is formed to get the F-value. F = [(RSSR ? RSSUR)/k] / [(RSSUR)/ ((n1 + n2+n3+n4+n5) ? 2k)] ~ F [k, ((n1+n2+n3+n4+n5) ? 2k)] (7)We cannot reject the null hypothesis of parameter stability (i. e. , no structural change) if the computed F value is not statistically significant (F value does not exceed the critical F value obtained from the F table at the chosen level of significance or the p value). Contrarily, if the computed F value is statistically significant (F value exceeds the critical F value), we reject the null hypothesis of parameter stability and conclude that the phase wise regressions are different. 4. Test Results and Findings Initially the beta coefficient is calculated using the Ordinary Least Square (OLS) technique as defined in equation (1).The estimation was carried out by using monthly return data for the 5 market phases for each of the 30 stocks. To compare the phase wise beta estimation with the enti re 10 year period, the same estimation also carried out taking the whole 10 years for each stock separately. Stock wise beta values over 5 market phases and the entire period is reported in appendix-2. From annexure-2, it is revealed that there are 14 stocks beta value is greater than 1 in phase I. This figure (beta value greater than 1) has reduced to 6, 11, 12 and 10 for phase-2 to phase-5 respectively.It is also illustrated that, there are 8 stocks whose beta value is greater than 1 in respect to overall between Jan-99 to Aug-09 and highest being for Wipro of 1. 47. The stocks having beta value International Research Journal of Finance and Economics – Issue 50 (2010) 181 more than 1 are considered to be volatile securities. It is noticed that, as we increase the period of estimation to full ten years period, there are less number of stocks proved to be more volatile. Out of the total 30 stocks considered in the study, only one company i. e.L&T has beta more than 1 in all p hases including the overall period. But none of the company’s overall beta value is more than the phase wise betas. There are seven companies (RIL, NALCO, ITC, GAIL, Hindustan Lever, Hero Honda and Cipla) whose beta values are less than 1 all through the phases including overall period. These stocks are considered to be less volatile than the market. There are 3 companies (Cipla, ITC and Hindustan Lever) recent beta value (Dec 2008 to August 2009) is negative, where Cipla’s phase I beta value is also negative along with other two stocks like SAIL and NALCO.It is observed from annexure-2 that there are only two companies’ from the software sector (Infosys and Wipro) whose beta values are consistently declining over time. However there are 7 stocks viz. Cipla, Sunpharma, Wipro, Grasim, Hindustan Lever, Infosys and ITC whose beta values are showing a decreasing trend from phase 3 onwards, while Tata steel is the only stock whose beta values are showing an increasin g trend during the same period. It is observed from the annexure-2 that, on an overall basis 29 out of 30 stocks have their beta values statistically significant at 5% level.This number has varied from 8 to 30 over the various phases, indicating that the beta values of the stocks have fluctuated significantly. This implies that the volatility of the stocks depend on the market phases i. e. bearish or bullish. Thus the result rejects the null hypothesis that the beta is stable over various market phases. The null hypothesis is rejected in 29 out of 30 cases in case of overall period, while 30 out of 30 cases in respect to phase-3. Since the period of estimation of beta is more in case of overall period and in phase-3, the obtained results are similar in both the cases.But the remaining phase wise results do not follow any pattern. In respect of period of estimating the value of beat the results are comparable to the finding of Baesel (1974) and Altman et al (1974). It is mentioned ea rlier that to examine the stability of beta over different market phases, three separate models have been used in paper. The results obtained from these models are interpreted in the following paragraphs. The estimated results for regression model-2 that includes t*mt as a separate variable are depicted in annexure-3.It is observed that the value of R2, a measure of goodness of fit varies from 0. 11 to 0. 61. It is only in 5 out of 30 regression results, the value is greater than 0. 50. The coefficient of mt (? 1) is found to be highly statistically significant at 5% level in 19 out of 30 cases. It is in 11 regressions, the coefficient is statistically insignificant. As discussed earlier, the significance of the coefficient of variable t*mt implies the rejection of the null hypothesis of stable beta over time. It is observed that the coefficient (? ) is significant in 14 cases out of 30. The regression results indicate that in 50% cases the null hypothesis of stability of beta over the market phases is rejected. This means 50% stocks reported stability of beta over different phases. So model (2) cannot infer that beta is not stable over market phases. The estimated results for coefficients for regression model-3 that incorporates dummy variables are depicted in annexure-4. It is noticed from the results that the R2 value fluctuates from 0. 15 to 0. 62 and in case of 8 stocks this value is greater than 0. 0. It is mentioned earlier that the null hypothesis of stability of beta will be rejected if any of the coefficients (? 2, ? 3, ? 4 & ? 5) corresponding to D1*mt, D2*mt, D3*mt or D4*mt were found to be statistically significant. It is observed from the results presented in appendix-4, that there are 17 out of 30 stocks represented statistically significant at 5% level at least one of the coefficient. There are only 2 cases where 3 coefficients are significant and none of the stocks reported significant for all the 4 coefficients.Further in 6 cases where 2 out of 4 coefficients are reported significant, where as in 9 cases depicted significant only for one coefficient. The outcome of this model in brief can be stated that, in case of 17 stocks out of 30 stocks, the stability of beta hypothesis is rejected meaning, in rest 13 cases there is a stability of beta over the market phases. 182 International Research Journal of Finance and Economics – Issue 50 (2010) The estimated results of Chow test are depicted in annexure-5. The results show that, 12 out of 30 cases the F-value is statistically significant and rest 18 stocks are reported insignificant at 5% level.Based on the F- statistics and its corresponding p-values, the null hypothesis of beta stability over the market phases is rejected in 12 cases and accepted in 18 cases. The F-values are also supported by log likelihood ratio and it p-values, which also reported statistical significance in 12 cases. The outcome of Chow test confirms that the beta values are not stable or there is a structural change in 12 out of 30 stocks in different market phases. But the rest 18 stocks reported stability or no structural change in beta values over the market phases.From the above deliberations, it is observed that all the three models described above exhibit a mixed and inconclusive result. There are 14, 17 and 12 stocks are statistically significant as per model2, model-3 and model-7 respectively. This means as per model-2 the beta values of 14 stocks out of 30 stocks are instable over the period. But this number is 17 and 12 in case of model3 and 7 respectively. However, on the basis of results obtained from different models, it is not possible to conclude that the beta values of the stocks are stable or instable over the market phases.But if we closely glance at the results obtained from three models, it is very apparent that in case of 9 stocks where all the three models represented similar results and rejected the null hypothesis. These stocks include Sun pharmac eutical, Wipro, Tata motors, Tata Steel, Hindalco, Hindustan Unilever, HDFC, Infosys and Zee Entertainment. This indicates that beta values are not stable over the market phases in these 9 stocks. Similarly there are 6 stocks where two models recommended instability of beta and 4 stocks where only one model reported a change in beta values over the period.There are 11 cases where none of the models rejected the null hypothesis, which proved that the beta values are stable over the time in these stocks. 5. Conclusion The objective of the present study is to examine the stability of beta in different Indian market phases. For the purpose of the study monthly return data of 30 stocks for the period from 1999 to 2009 is considered. Considering the bullish and bearish condition in the Indian market, we divided the whole 10 years into 5 different market phases. Initially the beta has been estimated for different market phases and also taking the whole 10 years period.The results show that the beta values are not showing any particular pattern but in the overall phase almost all the stocks are statistically significant. Further the beta stability is examined using three different models. In the first method the beta coefficient is calculated considering the market phases as time variable. The results show that in 50% of cases the null hypothesis is rejected as the beta is stable over different market phases. In the similar line the results obtained in respect to model two states that in 17 out of 30 cases the null hypothesis is rejected.This confirms that in 17 cases the stability of beta is not there over the market phases but in rest 13 cases it stable over the market phases. In the third method of investigating beta stability, the Chow test has been conducted. The F-statistics under Chow test reveals that, beta is instable in 12 out of 30 stocks considered in the study in different market phases. We can thus finally conclude that the results obtained from differen t models are mixed and inconclusive in nature, where it is less ground to conclude that the beta values are stable or instable over the market phases.But there are 9 stocks which gives a strong indication that their beta values are not stable over the market phases. In these 9 cases, all the three models reported similar signal of beta instability over the market phases. The instability of beta has its implications in taking sound corporate financial decisions. Financial decisions should not be based on the overall beta of the company. Rather, the company’s periodical beta should be relied upon for taking certain managerial decisions.Considering the inconclusive results obtained from present study, it is suggested that the future research on beta in Indian market may be investigated from (a) industry wise stability of beta in different market phases (b) stability of beta from portfolio point of view (c) optimal time limit for stability of beta (d) forward looking beta and its stability (e) impact of market and company specific factors and stability of beta and (f) market efficiency study using phase wise beta under the event study methodology. 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[26] [27] [28] [29] 30] [31] [32] [33] [34] 185 International Research Journal of Finance and Economics – Issue 50 (2010) Annexure-1: Month December 1998 January 1999 February 1999 March 1999 April 1999 May 1999 June 1999 July 1999 August 1999 September 1999 October 1999 November 1999 December 1999 January 2000 February 2000 March 2000 April 2000 May 2000 June 2000 July 2000 August 2000 September 2000 October 2000 November 2000 December 2000 January 2001 February 2001 March 2001 April 2001 May 2001 June 2001 July 2001 August 2001 September 2001 October 2001 November 2001 Dece mber 2001 January 2002 February 2002 March 2002 April 2002May 2002 June 2002 July 2002 August 2002 September 2002 October 2002 November 2002 December 2002 January 2003 February 2003 March 2003 April 2003 May 2003 June 2003 July 2003 August 2003 September 2003 October 2003 November 2003 December 2003 January 2004 February 2004 Identification of Market Phases Closing Price Return (R) 1+R Cumulative Wealth Index Market Phases 1359. 03 1461. 52 1506. 95 1651. 37 1449. 64 1714. 02 1790. 51 1988. 06 2192. 94 2213. 33 2071. 50 2253. 29 2624. 49 2875. 37 3293. 29 2902. 20 2396. 22 2156. 99 2397. 06 2153. 26 2306. 07 2075. 67 1916. 99 2061. 18 2032. 20 2209. 31 2139. 72 1691. 71 1682. 1 1763. 35 1630. 02 1564. 46 1534. 73 1312. 50 1389. 17 1557. 01 1557. 22 1592. 27 1707. 72 1716. 28 1671. 63 1596. 71 1650. 34 1506. 23 1580. 55 1473. 88 1458. 78 1594. 03 1664. 67 1600. 87 1628. 72 1500. 72 1470. 31 1641. 44 1819. 36 1893. 45 2229. 25 2314. 62 2485. 43 2594. 34 3074. 87 2946. 14 2923. 99 0. 0 8 0. 03 0. 10 -0. 12 0. 18 0. 04 0. 11 0. 10 0. 01 -0. 06 0. 09 0. 16 0. 10 0. 15 -0. 12 -0. 17 -0. 10 0. 11 -0. 10 0. 07 -0. 10 -0. 08 0. 08 -0. 01 0. 09 -0. 03 -0. 21 -0. 01 0. 05 -0. 08 -0. 04 -0. 02 -0. 14 0. 06 0. 12 0. 00 0. 02 0. 07 0. 01 -0. 03 -0. 04 0. 03 -0. 09 0. 05 -0. 07 -0. 01 0. 09 0. 04 -0. 04 0. 2 -0. 08 -0. 02 0. 12 0. 11 0. 04 0. 18 0. 04 0. 07 0. 04 0. 19 -0. 04 -0. 01 1. 08 1. 03 1. 10 0. 88 1. 18 1. 04 1. 11 1. 10 1. 01 0. 94 1. 09 1. 16 1. 10 1. 15 0. 88 0. 83 0. 90 1. 11 0. 90 1. 07 0. 90 0. 92 1. 08 0. 99 1. 09 0. 97 0. 79 0. 99 1. 05 0. 92 0. 96 0. 98 0. 86 1. 06 1. 12 1. 00 1. 02 1. 07 1. 01 0. 97 0. 96 1. 03 0. 91 1. 05 0. 93 0. 99 1. 09 1. 04 0. 96 1. 02 0. 92 0. 98 1. 12 1. 11 1. 04 1. 18 1. 04 1. 07 1. 04 1. 19 0. 96 0. 99 1. 08 1. 11 1. 22 1. 07 1. 26 1. 32 1. 46 1. 61 1. 63 1. 52 1. 66 1. 93 2. 12 2. 42 0. 88 0. 73 0. 65 0. 73 0. 65 0. 70 0. 63 0. 58 0. 63 0. 62 0. 67 0. 65 0. 51 0. 51 0. 54 0. 9 0. 48 0. 47 0. 40 1. 06 1. 19 1. 19 1. 21 1. 30 1. 31 1. 27 1. 22 1. 26 1. 15 1. 20 1. 12 1. 11 1. 21 1. 27 1. 22 1. 24 1. 14 1. 12 1. 25 1. 39 1. 44 1. 70 1. 76 1. 89 1. 98 2. 34 2. 24 2. 23 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 186 March 2004 April 2004 May 2004 June 2004 July 2004 August 2004 September 2004 October 2004 November 2004 December 2004 January 2005 February 2005 March 2005 April 2005 May 2005 June 2005 July 2005 August 2005 September 2005 October 2005 November 2005 ecember 2005 January 2006 February 2006 March 2006April 2006 May 2006 June 2006 July 2006 August 2006 September 2006 October 2006 November 2006 ecember 2006 January 2007 February 2007 March 2007 April 2007 May 2007 June 2007 July 2007 August 2007 September 2007 October 2007 November 2007 December 2007 January 2008 February 2008 March 2008 April 2008 May 2008 June 2008 July 2008 August 2008 September 2008 October 2008 November 2008 December 2008 January 2009 February 2009 Mar ch 2009 April 2009 May 2009 June 2009 July 2009 August 2009 International Research Journal of Finance and Economics – Issue 50 (2010) 2966. 31 3025. 14 2525. 35 2561. 16 2755. 22 2789. 07 2997. 97 027. 96 3339. 75 3580. 34 3521. 71 3611. 90 3481. 86 3313. 45 3601. 73 3800. 24 4072. 15 4184. 83 4566. 63 4159. 59 4649. 87 4953. 28 5224. 97 5422. 67 5904. 17 6251. 39 5385. 21 5382. 11 5422. 39 5933. 77 6328. 33 6603. 60 6931. 05 6982. 56 7145. 91 6527. 12 6587. 21 7032. 93 7468. 70 7605. 37 8004. 05 7857. 61 8967. 41 10391. 19 10384. 40 11154. 28 9440. 94 9404. 98 8232. 82 9199. 46 8683. 27 7029. 74 7488. 48 7621. 40 6691. 57 4953. 98 4600. 45 4988. 04 4790. 32 4516. 38 4942. 51 5803. 97 7620. 13 7571. 49 8176. 54 8225. 50 0. 01 0. 02 -0. 17 0. 01 0. 08 0. 01 0. 07 0. 01 0. 10 0. 07 -0. 02 0. 03 -0. 04 -0. 05 0. 9 0. 06 0. 07 0. 03 0. 09 -0. 09 0. 12 0. 07 0. 05 0. 04 0. 09 0. 06 -0. 14 0. 00 0. 01 0. 09 0. 07 0. 04 0. 05 0. 01 0. 02 -0. 09 0. 01 0. 07 0. 06 0. 02 0. 05 -0. 02 0 . 14 0. 16 0. 00 0. 07 -0. 15 0. 00 -0. 12 0. 12 -0. 06 -0. 19 0. 07 0. 02 -0. 12 -0. 26 -0. 07 0. 08 -0. 04 -0. 06 0. 09 0. 17 0. 31 -0. 01 0. 08 0. 01 1. 01 1. 02 0. 83 1. 01 1. 08 1. 01 1. 07 1. 01 1. 10 1. 07 0. 98 1. 03 0. 96 0. 95 1. 09 1. 06 1. 07 1. 03 1. 09 0. 91 1. 12 1. 07 1. 05 1. 04 1. 09 1. 06 0. 86 1. 00 1. 01 1. 09 1. 07 1. 04 1. 05 1. 01 1. 02 0. 91 1. 01 1. 07 1. 06 1. 02 1. 05 0. 98 1. 14 1. 16 1. 00 1. 07 0. 85 1. 00 0. 88 1. 12 . 94 0. 81 1. 07 1. 02 0. 88 0. 74 0. 93 1. 08 0. 96 0. 94 1. 09 1. 17 1. 31 0. 99 1. 08 1. 01 2. 26 2. 30 1. 92 1. 95 2. 10 2. 13 2. 28 2. 31 2. 54 2. 73 2. 68 2. 75 2. 65 2. 52 2. 74 2. 90 3. 10 3. 19 3. 48 3. 17 3. 54 3. 77 3. 98 4. 13 4. 50 4. 76 4. 10 4. 10 4. 13 4. 52 4. 82 5. 03 5. 28 5. 32 5. 44 4. 97 5. 02 5. 36 5. 69 5. 79 6. 10 5. 99 6. 83 7. 92 7. 91 8. 50 0. 85 0. 84 0. 74 0. 82 0. 78 0. 63 0. 67 0. 68 0. 60 0. 44 0. 41 1. 08 1. 04 0. 98 1. 07 1. 26 1. 66 1. 65 1. 78 1. 79 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5International Research Journal of Finance and Economics – Issue 50 (2010) Annexure-2: Beta values of individual securities over all the five phases Overall Phase I Phase II Phase III Phase IV ? p-val ? p-val ? p-val ? p-val ? p-val Bharat Heavy Electricals Ltd. 0. 86 0. 00* 0. 67 0. 21 1. 18 0. 00* 1. 10 0. 00* 0. 80 0. 02* Bharat Petroleum Corpn. Ltd. 0. 80 0. 00* 1. 02 0. 15 0. 66 0. 06 1. 13 0. 00* 1. 30 0. 06 Cipla Ltd. 0. 51 0. 00* -0. 04 0. 95 0. 75 0. 02* 0. 80 0. 00* 0. 51 0. 07 Sun Pharmaceutical Inds. Ltd. 0. 69 0. 00* 1. 13 0. 15 0. 80 0. 08 0. 57 0. 00* 0. 74 0. 00* Ranbaxy Laboratories Ltd. 0. 94 0. 00* 1. 19 0. 3 0. 63 0. 03* 0. 78 0. 00* 1. 07 0. 10 Wipro Ltd. 1. 47 0. 00* 2. 79 0. 02* 2. 63 0. 00* 0. 88 0. 00* 0. 87 0. 00* Reliance Infrastructure Ltd. 1. 24 0. 00* 1. 38 0. 02* 0. 26 0. 39 1. 20 0. 00* 1. 50 0. 00* Larsen & Toubro Ltd. 1. 30 0. 00* 1. 12 0. 08 1. 70 0. 00* 1. 21 0. 00 * 1. 07 0. 00* State Bank Of India 1. 01 0. 00* 1. 22 0. 08 0. 86 0. 00* 1. 03 0. 00* 1. 08 0. 01* Tata Motors Ltd. 1. 20 0. 00* 1. 07 0. 08 -0. 13 0. 65 1. 11 0. 00* 1. 20 0. 00* Oil & Natural Gas Corpn. Ltd. 0. 79 0. 00* 0. 43 0. 47 0. 59 0. 03* 1. 06 0. 00* 1. 03 0. 01* Steel Authority Of India Ltd. 1. 23 0. 00* -0. 31 0. 68 0. 99 0. 00* 1. 54 0. 0* 1. 12 0. 01* Tata Steel Ltd. 1. 22 0. 00* 0. 79 0. 17 0. 64 0. 05* 1. 25 0. 00* 1. 39 0. 00* Grasim Industries Ltd. 0. 94 0. 00* 1. 24 0. 13 0. 91 0. 01* 0. 95 0. 00* 0. 86 0. 00* H D F C Bank Ltd. 0. 79 0. 00* 1. 38 0. 03* 0. 36 0. 10 0. 68 0. 00* 0. 98 0. 00* Hero Honda Motors Ltd. 0. 47 0. 00* 0. 24 0. 64 0. 04 0. 85 0. 79 0. 00* 0. 93 0. 00* Hindalco Industries Ltd. 1. 00 0. 00* 0. 03 0. 95 0. 39 0. 06 1. 22 0. 00* 1. 44 0. 00* Hindustan Unilever Ltd. 0. 49 0. 00* 0. 78 0. 01* 0. 42 0. 06 0. 77 0. 00* 0. 67 0. 00* HDFC Ltd. 0. 74 0. 00* 0. 77 0. 01* 0. 50 0. 06 0. 85 0. 00* 1. 01 0. 00* Infosys Technologies Ltd. . 91 0. 00* 1. 33 0. 05* 1. 30 0. 00* 0. 73 0. 00* 0. 67 0. 06 G A I L (India) Ltd. 0. 49 0. 00* 0. 00 1. 00 0. 46 0. 11 0. 79 0. 00* 0. 34 0. 18 I C I C I Bank Ltd. 0. 84 0. 00* 1. 85 0. 05* 0. 06 0. 88 0. 50 0. 00* 0. 57 0. 14 I T C Ltd. 0. 37 0. 00* 0. 54 0. 13 0. 57 0. 01* 0. 42 0. 00* 0. 27 0. 24 National Aluminium Co. Ltd. 0. 49 0. 00* -0. 31 0. 75 0. 24 0. 37 0. 73 0. 00* 0. 21 0. 69 Indian Oil Corpn. Ltd. 0. 87 0. 10 0. 32 0. 56 0. 65 0. 00* 1. 24 0. 00* 0. 75 0. 01* Reliance Industries Ltd. 0. 51 0. 00* 0. 34 0. 47 0. 08 0. 81 0. 41 0. 00* 0. 74 0. 06 Sterlite Industries (India) Ltd. 1. 11 0. 00* 0. 99 0. 14 1. 3 0. 09 0. 87 0. 00* 0. 01 0. 96 Tata Communications Ltd. 0. 78 0. 00* 1. 10 0. 05* 1. 18 0. 00* 0. 87 0. 00* 0. 85 0. 09 Unitech Ltd. 0. 79 0. 00* 0. 47 0. 14 0. 48 0. 02* 0. 87 0. 00* 0. 21 0. 47 Zee Entertainment Ent. Ltd. 1. 00 0. 00* 1. 39 0. 08 0. 72 0. 07 0. 78 0. 00* 1. 13 0. 03* * indicates significance of coefficient at 5% level of significant Name of the Company Annexure-3: 187 Phase V ? p-val 0. 74 0. 00* 0. 48 0. 03* -0. 13 0. 65 0. 16 0. 55 1. 96 0. 01* 0. 78 0. 10 2. 46 0. 00* 1. 77 0. 00* 1. 55 0. 00* 1. 33 0. 02* 0. 94 0. 01* 1. 66 0. 00* 2. 07 0. 00* 0. 41 0. 29 0. 96 0. 00* 0. 29 0. 21 1. 63 0. 01* -0. 1 0. 68 0. 95 0. 00* 0. 07 0. 83 0. 38 0. 03* 1. 35 0. 02* -0. 01 0. 95 0. 50 0. 19 0. 98 0. 02* 0. 57 0. 10 0. 85 0. 03* 0. 43 0. 15 1. 27 0. 11 0. 74 0. 07 Estimates of regression equation using Time as a Variable Name of the Company Bharat Heavy Electricals Ltd. Bharat Petroleum Corpn. Ltd. Cipla Ltd. Sun Pharmaceutical Inds. Ltd. Ranbaxy Laboratories Ltd. Wipro Ltd. Reliance Infrastructure Ltd. Larsen & Toubro Ltd. State Bank Of India Tata Motors Ltd. Oil & Natural Gas Corpn. Ltd. Steel Authority Of India Ltd. Tata Steel Ltd. Grasim Industries Ltd. H D F C Bank Ltd. Hero Honda Motors Ltd. Hindalco Industries Ltd.Hindustan Unilever Ltd. HDFC Ltd. Constant 0. 02 0. 01 0. 02 0. 03 0. 01 0. 01 0. 01 0. 01 0. 01 0. 00 0. 01 0. 02 0. 01 0. 01 0. 0 2 0. 02 0. 00 0. 00 0. 02 mt (? 1) 0. 56 (0. 03) 0. 79 (0. 02) 0. 94 (0. 00) 1. 69 (0. 00) 0. 63 (0. 05) 3. 35 (0. 00) 0. 25 (0. 44) 1. 10 (0. 00) 0. 71 (0. 00) 0. 61 (0. 02) 0. 25 (0. 38) 0. 26 (0. 51) 0. 01 (0. 99) 0. 97 (0. 00) 0. 92 (0. 00) 0. 19 (0. 42) -0. 12 (0. 60) 0. 91 (0. 00) 0. 37 (0. 04) t*mt (? 2) 0. 10 (0. 22) 0. 00 (0. 96) -0. 14 (0. 10) -0. 33 (0. 00)* 0. 10 (0. 29) -0. 62 (0. 00)* 0. 33 (0. 00)* 0. 07 (0. 37) 0. 10 (0. 17) 0. 20 (0. 02)* 0. 18 (0. 03)* 0. 32 (0. 01)*

Human Growth And Development Social Work Essay Example

Human Growth And Development Social Work Essay Example Human Growth And Development Social Work Essay Human Growth And Development Social Work Essay Human being is non inactive and people are developing invariably ( Thompson and Thompson, 2008: 83 ) . For this ground, an apprehension of development is cardinal to set abouting professional societal work at a high degree of competency ( Ibid. : 99 ) . This instance survey focuses on Tony and Jan, their adopted nine twelvemonth old boy Sam, new babe and Jan s female parent Dorothy. It is apparent from reading this household s background information that a societal worker should see theories of human growing and development in order to to the full measure their fortunes and behavior. Hence, this is where our attending will now turn but as clip does non allow consideration of all household members, for the intent of this assignment two will be concentrated on ; Sam and Jan. Sam Sam was adopted by Tony and Jan at four old ages old, a move which, despite initial reserves, was successful. However, in recent months Sam s behavior has deteriorated and this, aboard other jobs, has led to the household seeking support. has long been regarded as important in kids s development ( Aldgate, 2007: 57 ) . Bowlby ( 1977: 203 ) described attachment behavior as behavior ensuing in a individual achieving or retaining propinquity to another differentiated and preferred single, normally considered stronger and/or wiser. He considered it built-in to human nature, seen to changing extents in all human existences and performed the biological map of protection ( Bowlby, 1988: 22 ) . can be affected when separated from a chief attachment figure ; particularly if this happens involuntarily such as when a kid is removed from their parents attention ( Aldgate, 2007: 64 ) . Irrespective of their old fond regard experiences, they will happen this terrorization because they do non cogni ze who to turn to assist them return to a province of equilibrium ( Ibid. ) . This explains why kids who have experienced maltreatment may still desire to be with their parents, even if they are insecurely attached to them ( Ibid. ) and could exemplify why Sam was late protesting that he wanted to travel back to his existent female parent. Daniel ( 2006: 193 ) asserts kids between the ages six months and four old ages are most vulnerable when separated from fond regard figures because: during these early old ages kids lack the cognitive accomplishments to grok the events taking to separation and this coupled with the leaning for charming thought, means immature kids are extremely likely to fault themselves for the loss . Sam was adopted at four old ages old and although we know small about the fortunes with his birth parents, significantly his fond regard bond was broken at this point. Aldgate ( 2007: 65 ) notes kids who have lost attachment figures through come ining the attention system are at hazard of farther injury by insensitive responses to their fond regard demands. Furthermore, kids get downing new arrangements with insecure attachment behavior may prove the parenting capacity of their carers ( Ibid. ) which could explicate Sam s recent deteriorating behavior. Following two decennaries of research showing that arrangement dislocation is an on-going job in the UK ( Ibid. ) , practicians working with this household should be particularly careful to seek to forestall this. Attachment theory differs from traditional psychoanalytic theories because it rejects the theoretical account of development suggesting an single base on ballss through a series of phases, in which they may go fixated or reasoning backward ( Bowlby, 1988: 135 ) . Alternatively, this theoretical account sees the person as come oning along one of many possible developmental tracts, some of which are or are non compatible with healthy development ( Ibid. ) . Yet, the function of parents in determining a kid s personality has been critiqued by Harris ( 1999: fifteen ; 359 ) , who offers an alternate point of view in The Nurture Assumption and proposes it is experiences in childhood and adolescent equal groups that modify a kid s personality in ways that will be carried frontward to adulthood. What s more, OConnor and Nilson ( 2007: 319 ) argue that amongst kids in the Foster attention system, fond regard is considered a powerful but diffuse beginning of behavioral and emotional jobs. Alm ost any riotous behavior can be attributed to attachment troubles in early relationships and the early experiences are frequently suggested as the lone beginning of their jobs, later understating the function of the current arrangement experiences ( Ibid. ) . They contend following research showing surrogate parents attachment and caregiving does act upon the kid s fond regard to them, it is important that the impact of early fond regard experiences on later development should non be considered independently of current caregiving environments ( Ibid. : 320 ) . Finally, supplying that new attachment figures for kids can react to kids s fond regard needs sensitively and are committed to manage any behavior that may prove their remaining power, it is believed early forms can be modified or discontinued ( Aldgate, 2007: 66 ) . Bronfenbrenner s ( 1979 ) Ecology of Human Development looks beyond the impact of fond regard to health professionals on development and offers much in footings of helping our apprehension of this households state of affairs and behavior. Bronfenbrenner ( Ibid. : 3 ) developed his broader prospective to development, supplying new constructs of the developing individual, the environment and the germinating interaction between them. He focussed on: the progressive adjustment, throughout the life span, between the turning human being and the altering environments in which it really lives and grows. The latter include non merely the immediate scenes incorporating the developing individual but besides the larger societal contexts, both formal and informal, in which these scenes are embedded . ( Bronfenbrenner, 1977: 513 ) . Harmonizing to Bronfenbrenner ( 1979. : 22 ) , the ecological environment is comprised of a nested administration of homocentric constructions with each one contained within the following. He labelled these the microsystem, mesosystem, exosystem, and macrosystem and each bed of a kid s environment affects their development. When looking at the microsystem, the form of functions, interpersonal dealingss and activities experienced by the developing individual in a given scene ( Ibid. ) , there are ways this could hold affected Sam s development. For case, within the household puting Jan has struggled to get by since the unexpected reaching of their babe, which later could hold affected Sam s relationship with her. He now has to portion his female parents attending with his sibling and may be experiencing left out or covetous. Furthermore, the disbursal of IVF has resulted in Tony working more, rendering him absent from the family more often. This alteration may hold influenced Sam s relationship with Tony and he may be losing holding his male parent about as in the yesteryear. Additionally, following his acceptance, Dorothy felt unsure whether to see Sam as her existent grandson, a tenseness which Sam may sensed himself. Bronfenbrenner ( Ibid. :7 ) besides regarded the connexions between other people in the scene of equal importance because of their indirect influence on the development kid through the consequence they have on those who deal first manus with that individual. Sam s development could hold been affected by labored dealingss between his parents as a consequence of Jan non having the support she needs from her hubby due to his work committednesss. Similarly, dealingss between Jan and Dorothy have become tense since the babe s reaching with Jan anticipating Dorothy s aid, which has non materialised. Beyond the microsystem, an exosystem refers to scenes that the developing individual is non involved in as an active participant but in which events occur that affect, or are affected by, what happens in the scene incorporating the developing person ( Ibid. : 25 ) . Bronfenbrenner ( Ibid. ) offered a kid s parents topographic point of work as an illustration and with the demand for Tony to work every bit much as possible, any emphasiss he experiences in the work environment could encroach upon Sam s development even though Sam spends no clip in this scene himself. This theory recognises everyone exists within a context influencing who they are and how they respond to state of affairss in life ( Phelan, 2004: online ) . Whilst the edifice blocks in the environmental facet of this theory were familiar constructs in the societal and behavioral scientific disciplines, the manner in which these entities relate to one another and to development was new ( Bronfenbrenner, 1979: 8 ) . Hence, before this theory, sociologists, psychologists and other specializers studied narrow facet s of kids s universes ( Brendtro, 2006: 163 ) . However, Tudge et Al. ( 2009: 6 ) evaluated the application of Bronfenbrenner s theory in late published work and found merely 4 out of 25 documents claiming to be based on his theory had utilised it suitably. They contend if theory is to play an of import function in developmental surveies it must be applied right because: a failure to make so means that it has non been tested suitably ; informations seemingly back uping the theory do no such thing if the theory has been falsely described, and a distorted theory is imperviable to assail from nonsupportive data ( Ibid. : 206 ) . Adoption is required when it is non possible for a kid to return place, either because the parents are unable to care for them or alter their lives in a manner that would be safe for that kid ( Brent Council, 2010: online ) . Whilst we are unsure of the fortunes taking to Sam s acceptance, we can theorize that the attention provided by his birth parents was deficient. Infant encephalon research demonstrated that if there is grossly unequal attention in babyhood, the baby s encephalon and other abilities that depend on encephalon development can be compromised ( Linke, 2000: online ) . The bulk of the critical times for encephalon development occur before the age of six months and research indicated orphans adopted after this age made less advancement than those adopted earlier ( Ibid. ) . Furthermore, parts of the encephalon that regulate emotions and emphasis responses are organised early in a kid s life and may non be mutable subsequently ( Ibid. ) . Subsequently, parts of the orga nic structure and encephalon that respond to emphasis may go over sensitive and ready to react to menace even when a menace is non manifest if the baby is continually exposed to trauma and emphasize ( Ibid. ) . If Sam experienced unequal attention in babyhood it is possible that he has developed over sensitive emphasis responses and now regards the new babe as a menace, which could supply an account for his noncompliant behavior and neutrality in his sibling. Pollak and the University of Wisconsin Child Emotion Lab are active in researching how early life experiences affect encephalon development ( see Child Emotion Lab, 2009: online ) . However, he and his co-workers stress that non all kids sing disregard develop the same jobs ( Wismer-Fries et al. , 2005: 17239 ) . In their work on the function of early societal experience in subsequent encephalon development they found kids sing lower hormonal responsiveness may travel on to develop satisfactory interpersonal relationships and highlighted potentially important single differences runing across the control group and the antecedently neglected group of kids ( Ibid. ) . Furthermore, other research led by Pollak has demonstrated how adjustable the encephalon can be when in the right environment ( University of Wisconsin News, 2003: online ) . Their survey of 5-6 twelvemonth old s who lived in orphanhoods during their first seven to 41 months of life found that kids performed better in many trials the longer they had lived with their adoptive households ( Ibid. ) . Pollak ( quoted in University of Wisconsin News, 2003: online ) hopes these findings will promote kids to be placed in households instead than in institutional scenes and offer new avenues for planing more effectual intercessions that could assist kids who spent their early old ages in disadvantaged environments reach their full potential . Jan Erikson s life rhythm attack proposes at certain points in their lives, people encounter life crises making a struggle within themselves as persons and between themselves and other important people in their lives ( Gibson, 2007: 74 ) . Each life crisis provides a struggle, characterised by a pull in different waies by two opposing temperaments, and if the single achieves a favorable balance between these so they are every bit prepared as possible to travel onto the following phase in the procedure ( Ibid. ) . However, if one does non accomplish this favorable ratio, this renders wining in subsequent life crises debatable ( Ibid. ) . Generativity vs Stagnation is Erikson s 7th and next-to-last phase of psychosocial development covering in-between maturity and generativity is chiefly the concern in set uping and steering the following generation ( Erikson, 1965: 258 ) and represents the major struggle in maturity ( Slater, 2003: 57 ) . As Slater ( Ibid. ) asserts, everybody has to conf ront the crisis of parentage whereby: mmake a deliberate determination to go parents, but some become parents without witting determination, others decide non to go parents, and still others want to go parents but can non. The determination and its result provoke a crisis that calls for a re-examination of life roles . Successfully accomplishing this sense of generativity is of import for both the person and society and parents demonstrate it through caring for their kids ( Slater, 2003: 57 ) . A failure to accomplish this leads to a feeling of stagnancy and unproductivity ( Heffner, 2001: online ) . Jan spent a long clip seeking to go a female parent to carry through this phase in Erikson s theoretical account and accomplish a favourable ratio ( Erikson, 1965: 262 ) of generativity over stagnancy. After two old ages of seeking to gestate, three unsuccessful efforts at IVF and two gruelling old ages of the acceptance procedure, they adopted Sam and have since out of the blue conceived of course. However, as Erikson ( Ibid. : 259 ) asserts the mere fact of holding or even lacking kids does non achieve generativity . Blyth ( 1999: 730 ) composing about assisted construct, significantly high spots parentage after such attempts will non needfully fit outlooks and Jan s feelings of being a useless fem ale parent and happening maternity a battle may be unexpected after seeking for a household for such a long clip. Furthermore, in this phase, the importance of grownup mature dependence is implicitly inferred and suggests there are psychological wagess for those grownups who can run into the demands of others and hold other people dependent on them ( Gibson, 2007: 83 ) . Jan reports experiencing unable to soothe her babe and run into their demands and this should be addressed by a societal worker to forestall a pervading sense of stagnancy and impoverishment ( Erikson, 1965: 258 ) in this phase of the life rhythm. Slater ( 2003: 53 ) acknowledges Erikson s work, whilst grounded in psychoanalytic theory, rejects Freud s impression that personality is fixed by childhood experiences entirely and provides an extension of the phases of development to cover adolescence, maturity and old age. However, Rutter and Rutter ( 1993: 1-2 ) criticised theories such as Erikson s sing psychological growing as a systematic patterned advance through a series of phases in a preset order, through which everyone moves, taking them closer to adulthood represented by grownup operation. This trust on the universals of development and the impression of one developmental tract has ignored single differences ( Ibid. ) . They believe that whilst this theory made important parts to understanding the procedures involved in development, Erikson s attack does non suit with what is known about socio-emotional development and it is likely that kids take a assortment of waies, and grownup results can non sanely be reduced to mer e differences in degrees of maturity ( Ibid. : 2 ) . Goffman ( 1963: preface- 3 ) employed the term stigma to mention to a deeply discrediting property of an person that disqualifies them from full societal credence. Their ownership of this property that makes them different means they can be reduced in people s heads from a whole individual to a discounted and tainted one ( Ibid. : 3 ) . Furthermore, the wider societies criterions mean the person is cognizant of what others regard as their weakness, which can necessarily do them to believe they fall short of what they ought to be and later shame becomes a cardinal possibility ( Ibid. : 7 ) . His work offers insight into how Jan may be experiencing about herself after being unable to gestate for such a long clip because for many adult females, infertility carries a concealed stigma Born of shame and secrecy ( Whiteford A ; Gonzales, 1995: 27 ) . Involuntary childlessness can adversely impact an persons relationships, their feelings about themselves and their ability to map, develop an d take part in society may be compromised by their inability to set about conventional functions associated with parenting ( Blyth, 1999: 729-730 ) . Whiteford A ; Gonzalez s ( Ibid. : 27-35 ) research on 25 adult females who sought medical intervention for sterility, demonstrated the concealed load of sterility reflected in the stigma, hurting and spoiled individualities of those interviewed. The adult females in their sample experienced the effects of their societal individuality and suffered because they had: internalized the societal norms expressed in dominant gender functions, and in so making see themselves as faulty. They suffer from being denied the chance proceed with their lives as others do ( Ibid. : 35 ) . Goffman ( 1963: 9 ) believed the stigmatised individual frequently responds to their state of affairs by doing an effort to rectify their weakness. This is apparent in Whiteford A ; Gonzales ( 1995. : 35 ) survey where the adult females attempted to rectify their job and repair the broken portion of them, giving all they could to go a normal and whole individual and take the stigma of being sterile. Unfortunately, failure is the most likely result of sterility intervention ( Blyth, 1999: 729-730 ) , as experienced by Tony and Jan, who had three unsuccessful efforts at IVF before retreating from the programme. Furthermore, Goffman ( 1963: 9 ) emphasised that where such a fix is possible, this does non needfully take to the acquisition of to the full normal position. Alternatively a transmutation of ego from person with a peculiar defect into person with a record of holding corrected a peculiar blemish ( Ibid. ) occurs, which Jan, who has successfully overcome her sterility and go a female parent may be sing. One important unfavorable judgment levelled at Goffman s theory is of the seemingly incapacitated function attributed to persons with stigmatic qualities ( Carnevale, 2007: 12 ) . Furthermore, Nettleton ( 2006: 96 ) reiterates the importance of recognizing stigma is non an property of the person but a thoroughly societal construct which is generated, sustained and reproduced in the context of societal inequalities alternatively. Nonetheless, Goffman s theoretical account remains dominant and extremely respected and his representation of the societal troubles people with stigmatic qualities face is still considered extremely valid ( Carnevale, 2007: 12 ) . Whilst attachment behavior is particularly apparent in childhood, it besides characterises people from cradle to the grave ( Bowlby, 1977: 203 ) . Furthermore, the capacity to organize intimate emotional bonds in both the attention giving and attention seeking function is considered a chief characteristic of effectual personality operation and mental wellness ( Bowlby, 1988: 121 ) . Bowlby ( 1977. : 206 ) proposed there was a strong relationship between a individual s experiences with their parents and their ulterior ability to organize affective bonds and that: common fluctuations in that capacity, attesting themselves in matrimonial jobs and problem with kids every bit good as in neurotic symptoms and personality upsets, can be attributed to certain common fluctuations in the ways that parents execute their roles ( Ibid. ) . Subsequently, attachment theory advocators believe many signifiers of psychiatric upsets can be attributed to failure of the development of attachment behavior ( Bowlby, 1977: 201 ) . This is supported by et Al s. ( 1996: 310 ) research which found insecure fond regard appeared to impact upon self-esteem and self worth eventualities ensuing in depressive symptoms in maturity. Whilst we know small of Jan s attachment behavior as a kid, her relationship with her female parent is unstable at present and when looking at the symptoms that Jan is exposing they could deduce she is sing postpartum depression. The Edinburgh Postnatal Depression Scale was developed by Cox et Al. ( 1987 ) to help wellness attention professionals recognise postpartum depression. Statements used to place the status include: Things have been acquiring on top of me ; I have been experiencing sad or miserable ; I have been dying or worried for no good reason and I have blamed myself unnecessarily when things went wr ong , all of which could be applied to how Jan is experiencing at present. Furthermore, her changeless low temper and feelings of insufficiency as a female parent lucifer some of the symptoms of postpartum depression described on NHS Direct s ( 2008: online ) web site. Therefore, whilst this is merely a probationary account of Jan s feelings, it should be explored by the societal worker working with this household. Additionally, unresolved childhood attachment issues can go forth grownups vulnerable to sing troubles in forming secure grownup relationships ( Evergreen Advisers in Human Behaviour, 2006: online ) . Attachment jobs can be handed down transgenerationally unless the concatenation is broken and hence, an insecurely attached grownup may miss the ability to organize a strong fond regard with their ain kid ( Ibid ) . Subsequently, uthis theory offers the possibility that hapless formation of affective bonds in Jan s ain childhood could explicate why she is fighting to organize an attachment bond with her ain babe. Furthermore, new dealingss can be affected by outlooks developed in old relationships and there is a strong correlativity between insecure grownup fond regard and matrimonial dissatisfaction ( Ibid. ) . This could offer an account for why Jan believes Tony does non supply the emotional support she requires. However, whilst trauma experienced in the early old ages can be associated with jobs in the long term, it should non be assumed this is black for a kid s physical, cognitive and emotional development and will automatically plague the remainder of a their life ( Daniel, 2006: 195 ) . As Barth et Al. ( 2005: 259 ) contend, while attachment jobs may predispose a kid towards subsequently jobs, these jobs must be evaluated and treated within the context of their current environment. Social work practicians supplying appropriate intercessions can do a long-run difference because hardship experienced in the early old ages can be compensated for and the worst effects ameliorated if support is given ( Daniel, 2006: 195 ) . Obviously, an apprehension of human development theory provides more than an interesting background subject and is indispensable to good societal work pattern ( and Thompson, 2008: 139 ) . Whilst no theories supplying penetrations into development are unfailing, in combination they have much to offer to a practicians apprehension of those they work with. Therefore, it is imperative a societal worker should see biological, psychological and sociological attacks in order to transport out a full and holistic appraisal of this household s demands. However, as Thompson and Thompson ( Ibid. ) assert, it is easy for practicians to wrongly believe the cognition base will offer off-the-rack, ready-made replies and merely use theories to pattern in a mechanical, across-the-board manner. Therefore, it is of import for skilled brooding practicians to be competent at pulling out relevant facets of the theory base and use them in a manner that is tailored to suit the state of affairs alternatively ( Ibid. ) . Furthermore, as Thompson ( 2009: 63 ) accents, there is a danger that when looking at development across the life class it can be used as a stiff model that we expect everyone to suit into and so see those who do non as abnormal or holding a job. Consequently, it must be recognised that this traditional attack taken to development across the the life class can be really oppressive and discriminate against those who do non conform to the tendency ( Ibid. ) . For this ground, the life class should be considered as a agency of beginning to understand common phases of development and is non a stiff model for doing opinions about abnormality ( Ibid. ) . To reason, as Thompson and Thompson ( 2008: 99 ) remind us, understanding development is non doing everyone tantrum into a stereotyped premise about what is normal but instead to recognize there are important forms that underpin growing and development and to the attitudes and behaviors associated with these.