Miss.Independent Essay Example for Free

Miss.Independent Essay Abstract We survey the phenomenon of the growth of ? rms drawing on literature from economics, management, and sociology. We begin with a review of empirical ‘stylised facts’ before discussing theoretical contributions. Firm growth is characterized by a predominant stochastic element, making it di? cult to predict. Indeed, previous empirical research into the determinants of ? rm growth has had a limited success. We also observe that theoretical propositions concerning the growth of ? rms are often amiss. We conclude that progress in this area requires solid empirical work, perhaps making use of novel statistical techniques. JEL codes: L25, L11 Keywords: Firm Growth, Size Distribution, Growth Rates Distribution, Gibrat’s Law, Theory of the Firm, Diversi? cation, ‘Stages of Growth’ models. ? I thank Giulio Bottazzi, Giovanni Dosi, Ha? da El-Younsi, Jacques Mairesse, Bernard Paulr? , Rekha Rao, e Angelo Secchi and Ulrich Witt for helpful comments. Nevertheless, I am solely responsible for any errors or confusion that may remain. This version: May 2007 †  Corresponding Author : Alex Coad, Max Planck Institute of Economics, Evolutionary Economics Group, Kahlaische Strasse 10, D-07745 Jena, Germany. Phone: +49 3641 686822. Fax : +49 3641 686868. E-mail : [emailprotected] mpg. de 1 #0703 Contents 1 Introduction 3 2 Empirical evidence on ? rm growth 2. 1 Size and growth rates distributions . . . . 2. 1. 1 Size distributions . . . . . . . . . . 2. 1. 2 Growth rates distributions . . . . . 2. 2 Gibrat’s Law . . . . . . . . . . . . . . . . 2. 2. 1 Gibrat’s model . . . . . . . . . . . 2. 2. 2 Firm size and average growth . . . 2. 2. 3 Firm size and growth rate variance 2. 2. 4 Autocorrelation of growth rates . . 2. 3 Other determinants of ? rm growth . . . . 2. 3. 1 Age . . . . . . . . . . . . . . . . . 2. 3. 2 Innovation . . . . . . . . . . . . . . 2. 3. 3 Financial performance . . . . . . . 2. 3. 4 Relative productivity . . . . . . . . 2. 3. 5 Other ? rm-speci? c factors . . . . . 2. 3. 6 Industry-speci? c factors . . . . . . 2. 3. 7 Macroeconomic factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 4 4 5 9 9 11 14 15 18 18 19 23 25 26 28 29 3 Theoretical contributions 3. 1 Neoclassical foundations – growth towards an ‘optimal size’ . . . . 3. 2 Penrose’s ‘Theory of the Growth of the Firm’ . . . . . . . . . . . 3. 3 Marris and ‘managerialism’ . . . . . . . . . . . . . . . . . . . . . 3. 4 Evolutionary Economics and the principle of ‘growth of the ? tter’ 3. 5 Population ecology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 31 32 34 35 38 . . . . . . . 39 39 40 43 44 45 46 49 5 Growth of small and large ? rms 5. 1 Di? erences in growth patterns for small and large ? rms . . . . . . . . . . . . . 5. 2 Modelling the ‘stages of growth’ . . . . . . . . . . . . . . . . . . . . . . . . . . 51 51 53 6 Conclusion 56 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Growth strategies 4. 1 Attitudes to growth . . . . . . . . . . . . . . . . . . . 4. 1. 1 The desirability of growth . . . . . . . . . . . 4. 1. 2 Is growth intentional or does it ‘just happen’ ? 4. 2 Growth strategies – replication or diversi? cation . . . 4. 2. 1 Growth by replication . . . . . . . . . . . . . 4. 2. 2 Growth by diversi? cation . . . . . . . . . . . . 4. 3 Internal growth vs growth by acquisition . . . . . . . 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . #0703 1 Introduction The aim of this survey is to provide an overview of research into the growth of ? rms, while also highlighting areas in need of further research. It is a multidisciplinary survey, drawing on contributions made in economics, management and also sociology. There are many di? erent measures of ? rm size, some of the more usual indicators being employment, total sales, value-added, total assets, or total pro? ts; and some of the less conventional ones such as ‘acres of land’ or ‘head of cattle’ (Weiss, 1998). In this survey we consider growth in terms of a range of indicators, although we devote little attention to the growth of pro? ts (this latter being more of a ? nancial than an economic variable). There are also di? erent ways of measuring growth rates. Some authors (such as Delmar et al. , 2003) make the distinction between relative growth (i. e. the growth rate in percentage terms) and absolute growth (usually measured in the absolute increase in numbers of employees). In this vein, we can mention the ‘Birch index’ which is a weighted average of both relative and absolute growth rates (this latter being taken into account to emphasize that large ? rms, due to their large size, have the potential to create many jobs). This survey focuses on relative growth rates only. Furthermore, in our discussion of the processes of expansion we emphasize positive growth and not so much negative growth. 1 In true Simonian style,2 we begin with some empirical insights in Section 2, considering ? rst the distributions of size and growth rates, and moving on to look for determinants of growth rates. We then present some theories of ? rm growth and evaluate their performance in explaining the stylised facts that emerge from empirical work (Section 3). In Section 4 we consider the demand and supply sides of growth by discussing the attitudes of ? rms towards growth opportunities as well as investigating the processes by which ? rms actually grow (growth by ‘more of the same’, growth by diversi? cation, growth by acquisition). In Section 5 we examine the di? erences between the growth of small and large ? rms in greater depth. We also review the ‘stages of growth’ models. Section 6 concludes. 2 Empirical evidence on ? rm growth To begin with, we take a non-parametric look at the distributions of ? rm size and growth rates, before moving on to results from regressions that investigate the determinants of growth rates. 1 2 For an introduction to organizational decline, see Whetten (1987). See in particular Simon (1968). 3 #0703 2. 1 Size and growth rates distributions A suitable starting point for studies into industrial structure and dynamics is the ?rm size distribution. In fact, it was by contemplating the empirical size distribution that Robert Gibrat (1931) proposed the well-known ‘Law of Proportionate E? ect’ (also known as ‘Gibrat’s law’). We also discuss the results of research into the growth rates distribution. The regularity that ? rm growth rates are approximately exponentially distributed was discovered only recently, but o? ers unique insights into the growth patterns of ? rms. 2. 1. 1 Size distributions The observation that the ? rm-size distribution is positively skewed proved to be a useful point of entry for research into the structure of industries. (See Figures 1 and 2 for some examples of aggregate ? rm size distributions. ) Robert Gibrat (1931) considered the size of French ? rms in terms of employees and concluded that the lognormal distribution was a valid heuristic. Hart and Prais (1956) presented further evidence on the size distribution, using data on quoted UK ? rms, and also concluded in favour of a lognormal model. The lognormal distribution, however, can be viewed as just one of several candidate skew distributions. Although Simon and Bonini (1958) maintained that the â€Å"lognormal generally ? ts quite well† (1958: p611), they preferred to consider the lognormal distribution as a special case in the wider family of ‘Yule’ distributions. The advantage of the Yule family of distributions was that the phenomenon of arrival of new ? rms could be incorporated into the model. Steindl (1965) applied Austrian data to his analysis of the ? rm size distribution, and preferred the Pareto distribution to the lognormal on account of its superior performance in describing the upper tail of the distribution. Similarly, Ijiri and Simon (1964, 1971, 1974) apply the Pareto distribution to analyse the size distribution oflarge US ? rms. E? orts have been made to discriminate between the various candidate skew distributions. One problem with the Pareto distribution is that the empirical density has many more middlesized ? rms and fewer very large ? rms than would be theoretically predicted (Vining, 1976). Other research on the lognormal distribution has shown that the upper tail of the empirical size distribution of ? rms is too thin relative to the lognormal (Stanley et al. , 1995). Quandt (1966) compares the performance of the lognormal and three versions of the Pareto distribution, using data disaggregated according to industry. He reports the superiority of the lognormal over the three types of Pareto distribution, although each of the distributions produces a best-? t for at least one sample. Furthermore, it may be that some industries (e. g. the footwear industry) are not ? tted well by any distribution. More generally, Quandt’s results on disaggregated data lead us to suspect that the regu4 #0703 larities of the ? rm-size distribution observed at the aggregate level do not hold with sectoral disaggregation. Silberman (1967) also ? nds signi? cant departures from lognormality in his analysis of 90 four-digit SIC sectors. It has been suggested that, while the ? rm size distribution has a smooth regular shape at the aggregate level, this may merely be due to a statistical aggregation e? ect rather than a phenomenon bearing any deeper economic meaning (Dosi et al, 1995; Dosi, 2007). Empirical results lend support to these conjectures by showing that the regular unimodal ? rm size distributions observed at the aggregate level can be decomposed into much ‘messier’ distributions at the industry level, some of which are visibly multimodal (Bottazzi and Secchi, 2003; Bottazzi et al. , 2005). For example, Bottazzi and Secchi (2005) present evidence of signi? cant bimodality in the ? rm size distribution of the worldwide pharmaceutical industry, and relate this to a cleavage between the industry leaders and fringe competitors. Other work on the ? rm-size distribution has focused on the evolution of the shape of the distribution over time. It would appear that the initial size distribution for new ? rms is particularly right-skewed, although the log-size distribution tends to become more symmetric as time goes by. This is consistent with observations that small young ? rms grow faster than their larger counterparts. As a result, it has been suggested that the log-normal can be seen as a kind of ‘limit distribution’ to which a given cohort of ? rms will eventually converge. Lotti and Santarelli (2001) present support for this hypothesis by tracking cohorts of new ? rms in several sectors of Italian manufacturing. Cabral and Mata (2003) ? nd similar results in their analysis of cohorts of new Portuguese ? rms. However, Cabral and Mata interpret their results by referring to ? nancial constraints that restrict the scale of operations for new ? rms, but become less binding over time, thus allowing these small ?rms to grow relatively rapidly and reach their preferred size. They also argue that selection does not have a strong e? ect on the evolution of market structure. Although the skewed nature of the ? rm size distribution is a robust ? nding, there may be some other features of this distribution that are speci? c to countries. Table 1, taken from Bartelsman et al. (2005), highlights some di? erences in the structure of industries across countries. Among other things, one observes that large ? rms account for a considerable share of French industry, whereas in Italy ? rms tend to be much smaller on average. (These international di? erences cannot simply be attributed to di? erences in sectoral specialization across countries. ) 2. 1. 2 Growth rates distributions It has long been known that the distribution of ? rm growth rates is fat-tailed. In an early contribution, Ashton (1926) considers the growth patterns of British textile ? rms and observes 5 US 86. 7 69. 9 87. 9 16. 6 5. 8 Western Germany 87. 9 77. 9 90. 2 23. 6 11. 3 78. 6 73. 6 78. 8 13. 9 17. 0 France Italy 93. 1 87. 5 96. 5 34. 4 30. 3 74. 9 8. 3 UK Canada Denmark 90. 0 74. 0 90. 8 30. 2 16. 1 92. 6 84. 8 94. 5 25. 8 13. 0 Finland Netherlands 95. 8 86. 7 96. 8 31. 2 16. 9 86. 3 70. 5 92. 8 27. 7 15. 7 Portugal Source: Bartelsman et al. (2005: Tables 2 and 3). Notes: the columns labelled ‘share of employment’ refer to the employment share 6 26. 4 17. 0 33. 5 10. 5 12. 7 13. 3 13. 0 6. 5 16. 8 Total economy 80. 3 39. 1 32. 1 15. 3 40. 7 40. 5 30. 4 27. 8 18. 3 31. 0 Manufacturing 21. 4 11. 5 35. 7 6. 8 12. 0 12. 7 9. 9 5. 3 11. 4 Business services Ave. No. Employees per ? rm of ? rms with fewer than 20 employees. 20. 6 33. 8 12. 1 46. 3 33. 4 33. 0 41. 9 39. 8 Business services Total economy Manufacturing Share of employment (%) Business services Total economy. Manufacturing Absolute number (%) Table 1: The importance of small ? rms (i. e. ?rms with fewer than 20 employees) across broad sectors and countries, 1989-94 #0703 #0703 1 Pr 1998 2000 2002 0. 1 0. 01 0. 001 1e-04 -4 -2 0 s 2 4 6 Figure 1: Kernel estimates of the density of ?rm size (total sales) in 1998, 2000 and 2002, for French manufacturing ? rms with more than 20 employees. Source: Bottazzi et al. , 2005. Figure 2: Probability density function of the sizes of US manufacturing ? rms in 1997. Source: Axtell, 2001. that â€Å"In their growth they obey no one law. A few apparently undergo a steady expansion.. . With others, increase in size takes place by a sudden leap† (Ashton 1926: 572-573). Little (1962) investigates the distribution of growth rates, and also ? nds that the distribution is fat-tailed. Similarly, Geroski and Gugler (2004) compare the distribution of growth rates to the normal case and comment on the fat-tailed nature of the empirical density. Recent empirical research, from an ‘econophysics’ background, has discovered that the distribution of ? rm growth rates closely follows the parametric form of the Laplace density. Using the Compustat database of US manufacturing ? rms, Stanley et al. (1996) observe a ‘tent-shaped’ distribution on log-log plots that corresponds to the symmetric exponential, or Laplace distribution (see also Amaral et al. (1997) and Lee et al. (1998)). The quality of the ? t of the empirical distribution to the Laplace density is quite remarkable. The Laplace distribution is also found to be a rather useful representation when considering growth rates of ? rms in the worldwide pharmaceutical industry (Bottazzi et al. , 2001). Giulio Bottazzi and coauthors extend these ? ndings by considering the Laplace density in the wider context of the family of Subbotin distributions (beginning with Bottazzi et al., 2002). They ? nd that, for the Compustat database, the Laplace is indeed a suitable distribution for modelling ? rm growth rates, at both aggregate and disaggregated levels of analysis (Bottazzi and Secchi 2003a). The exponential nature of the distribution of growth rates also holds for other databases, such as Italian manufacturing (Bottazzi et al. (2007)). In addition, the exponential distribution appears to hold across a variety of ? rm growth indicators, such as Sales growth, employment growth or Value Added growth (Bottazzi et al. , 2007). The growth rates of French manufacturing ? rms have also been studied, and roughly speaking a similar shape was observed, although it must be said that the empirical density was noticeably fatter-tailed than the Laplace (see Bottazzi et al. , 2005). 3 3 The observed subbotin b parameter (the ‘shape’ parameter) is signi? cantly lower than the Laplace value of 1. This highlights the importance of following Bottazzi et al. (2002) and considering the Laplace as a special 7 #0703 1998 2000 2002 1998 2000 2002 1 prob. prob. 1 0. 1 0. 01 0. 1 0. 01 0. 001 0. 001 -3 -2 -1 0 1 2 -2 -1. 5 -1 conditional growth rate -0. 5 0 0. 5 1 1. 5 2 conditional growth rate. Figure 3: Distribution of sales growth rates of French manufacturing ? rms. Source: Bottazzi et al. , 2005. Figure 4: Distribution of employment growth rates of French manufacturing ? rms. Source: Coad, 2006b. Research into Danish manufacturing ? rms presents further evidence that the growth rate distribution is heavy-tailed, although it is suggested that the distribution for individual sectors may not be symmetric but right-skewed (Reichstein and Jensen (2005)). Generally speaking, however, it would appear that the shape of the growth rate distribution is more robust to disaggregation than the shape of the ?rm size distribution. In other words, whilst the smooth shape of the aggregate ? rm size distribution may be little more than a statistical aggregation e? ect, the ‘tent-shapes’ observed for the aggregate growth rate distribution are usually still visible even at disaggregated levels (Bottazzi and Secchi, 2003a; Bottazzi et al. , 2005). This means that extreme growth events can be expected to occur relatively frequently, and make a disproportionately large contribution to the evolution of industries. Figures 3 and 4 show plots of the distribution of sales and employment growth rates for French manufacturing ?rms with over 20 employees. Although research suggests that both the size distribution and the growth rate distribution are relatively stable over time, it should be noted that there is great persistence in ? rm size but much less persistence in growth rates on average (more on growth rate persistence is presented in Section 2. 2. 4). As a result, it is of interest to investigate how the moments of the growth rates distribution change over the business cycle. Indeed, several studies have focused on these issues and some preliminary results can be mentioned here. It has been suggested that the variance of growth rates changes over time for the employment growth of large US ? rms (Hall, 1987) and that this variance is procyclical in the case of growth of assets (Geroski et al. , 2003). This is consistent with the hypothesis that ? rms have a lot of discretion in their growth rates of assets during booms but face stricter discipline during recessions. Higson et al. (2002, 2004) consider the evolution of the ? rst four moments of distributions of the growth of sales, for large US and UK ?rms over periods of 30 years or more. They observe that higher moments of the distribution of sales growth rates have signi? cant cyclical patterns. In case in the Subbotin family of distributions. 8 #0703 particular, evidence from both US and UK ? rms suggests that the variance and skewness are countercyclical, whereas the kurtosis is pro-cyclical. Higson et al. (2002: 1551) explain the counter-cyclical movements in skewness in these words: â€Å"The central mass of the growth rate distribution responds more strongly to the aggregate shock than the tails. So a negative shock moves the central mass closer to the left of the distribution leaving the right tail behind and generates positive skewness. A positive shock shifts the central mass to the right, closer to the group of rapidly growing ? rms and away from the group of declining ? rms. So negative skewness results. † The procyclical nature of kurtosis (despite their puzzling ? nding of countercyclical variance) emphasizes that economic downturns change the shape of the growth rate distribution by reducing a key parameter of the ‘spread’ or ‘variation’ between ? rms. 2. 2 Gibrat’s Law. Gibrat’s law continues to receive a huge amount of attention in the empirical industrial organization literature, more than 75 years after Gibrat’s (1931) seminal publication. We begin by presenting the ‘Law’, and then review some of the related empirical literature. We do not attempt to provide an exhaustive survey of the literature on Gibrat’s law, because the number of relevant studies is indeed very large. (For other reviews of empirical tests of Gibrat’s Law, the reader is referred to the survey by Lotti et al (2003); for a survey of how Gibrat’s law holds for the services sector see Audretsch et al. (2004). ) Instead, we try to provide an overview of the essential results. We investigate how expected growth rates and growth rate variance are in? uenced by ? rm size, and also investigate the possible existence of patterns of serial correlation in ? rm growth. 2. 2. 1 Gibrat’s model Robert Gibrat’s (1931) theory of a ‘law of proportionate e? ect’ was hatched when he observed that the distribution of French manufacturing establishments followed a skew distribution that resembled the lognormal. Gibrat considered the emergence of the ?rm-size distribution as an outcome or explanandum and wanted to see which underlying growth process could be responsible for generating it. In its simplest form, Gibrat’s law maintains that the expected growth rate of a given ? rm is independent of its size at the beginning of the period examined. Alternatively, as Mans? eld (1962: 1030) puts it, â€Å"the probability of a given proportionate change in size during a speci? ed 9 #0703 period is the same for all ? rms in a given industry – regardless of their size at the beginning of the period. † More formally, we can explain the growth of ? rms in the following framework. Let xt be the size of a ? rm at time t, and let ? t be random variable representing an idiosyncratic, multiplicative growth shock over the period t ? 1 to t. We have xt ? xt? 1 = ? t xt? 1 (1) xt = (1 + ? t )xt? 1 = x0 (1 + ? 1 )(1 + ? 2 ) . . . (1 + ? t ) (2) which can be developed to obtain It is then possible to take logarithms in order to approximate log(1 + ? t ) by ? t to obtain4 t log(xt ) ? log(x0 ) + ? 1 + ? 2 + . . . + ? t = log(x0 ) + ?s (3) s=1 In the limit, as t becomes large, the log(x0 ) term will become insigni? cant, and we obtain t log(xt ) ? ?s (4) s=1 In this way, a ? rm’s size at time t can be explained purely in terms of its idiosyncratic history of multiplicative shocks. If we further assume that all ? rms in an industry are independent realizations of i. i. d. normally distributed growth shocks, then this stochastic process leads to the emergence of a lognormal ? rm size distribution. There are of course several serious limitations to such a simple vision of industrial dynamics. We have already seen that the distribution of growth rates is not normally distributed, but instead resembles the Laplace or ‘symmetric exponential’. Furthermore, contrary to results implied by Gibrat’s model, it is not reasonable to suppose that the variance of ? rm size tends to in? nity (Kalecki, 1945). In addition, we do not observe the secular and unlimited increase in industrial concentration that would be predicted by Gibrat’s law (Caves, 1998). Whilst a ‘weak’ version of Gibrat’s law merely supposes that expected growth rate is independent of ?rm size, stronger versions of Gibrat’s law imply a range of other issues. For example, Chesher (1979) rejects Gibrat’s law due to the existence of an autocorrelation structure in the growth shocks. Bottazzi and Secchi (2006a) reject Gibrat’s law on the basis of a negative relationship between growth rate variance and ? rm size. Reichstein and Jensen (2005) reject Gibrat’s law 4 This logarithmic approximation is only justi? ed if ? t is ‘small’ enough (i. e. close to zero), which can be reasonably assumed by taking a short time period (Sutton, 1997). 10 #0703after observing that the annual growth rate distribution is not normally distributed. 2. 2. 2 Firm size and average growth Although Gibrat’s (1931) seminal book did not provoke much of an immediate reaction, in recent decades it has spawned a ? ood of empirical work. Nowadays, Gibrat’s ‘Law of Proportionate E? ect’ constitutes a benchmark model for a broad range of investigations into industrial dynamics. Another possible reason for the popularity of research into Gibrat’s law, one could suggest quite cynically, is that it is a relatively easy paper to write. First of all, it has been argued that there is a minimalistic theoretical background behind the process (because growth is assumed to be purely random). Then, all that needs to be done is to take the IO economist’s ‘favourite’ variable (i. e. ?rm size, a variable which is easily observable and readily available) and regress the di? erence on the lagged level. In addition, few control variables are required beyond industry dummies and year dummies, because growth rates are characteristically random. Empirical investigations of Gibrat’s law rely on estimation of equations of the type: log(xt ) = ?+ ? log(xt? 1 ) + (5) where a ? rm’s ‘size’ is represented by xt , ? is a constant term (industry-wide growth trend) and is a residual error. Research into Gibrat’s law focuses on the coe? cient ?. If ? rm growth is independent of size, then ? takes the value of unity. If ? is smaller than one, then smaller ? rms grow faster than their larger counterparts, and we can speak of ‘regression to the mean’. Conversely, if ? is larger than one, then larger ? rms grow relatively rapidly and there is a tendency to concentration and monopoly. A signi?cant early contribution was made by Edwin Mans? eld’s (1962) study of the US steel, petroleum, and rubber tire industries. In particular interest here is what Mans? eld identi? ed as three di? erent renditions of Gibrat’s law. According to the ? rst, Gibrat-type regressions consist of both surviving and exiting ? rms and attribute a growth rate of -100% to exiting ? rms. However, one caveat of this approach is that smaller ? rms have a higher exit hazard which may obfuscate the relationship between size and growth. The second version, on the other hand, considers only those ?rms that survive. Research along these lines has typically shown that smaller ? rms have higher expected growth rates than larger ? rms. The third version considers only those large surviving ? rms that are already larger than the industry Minimum E? cient Scale of production (with exiting ? rms often being excluded from the analysis). Generally speaking, empirical analysis corresponding to this third approach suggests that growth rates are more or less independent from ? rm size, which lends support to Gibrat’s law. 11 #0703 The early studies focused on large ? rms only, presumably partly due to reasons of data availability. A series of papers analyzing UK manufacturing ? rms found a value of ? greater than unity, which would indicate a tendency for larger ? rms to have higher percentage growth rates (Hart (1962), Samuels (1965), Prais (1974), Singh and Whittington (1975)). However, the majority of subsequent studies using more recent datasets have found values of ? slightly lower than unity, which implies that, on average, small ? rms seem to grow faster than larger ? rms. This result is frequently labelled ‘reversion to the mean size’ or ‘mean-reversion’. 5 Among a large and growing body of research that reports a negative relationship between size and growth, we can mention here the work by Kumar (1985) and Dunne and Hughes (1994) for quoted UK manufacturing ? rms, Hall (1987), Amirkhalkhali and Mukhopadhyay (1993) and Bottazzi and Secchi (2003) for quoted US manufacturing ? rms (see also Evans (1987a, 1987b) for US manufacturing ? rms of a somewhat smaller size), Gabe and Kraybill (2002) for establishments in Ohio, and Goddard et al. (2002) for quoted Japanese manufacturing ? rms. Studies focusing on small businesses have also found a negative relationship between ? rm size and expected growth – see for example Yasuda (2005) for Japanese manufacturing ? rms, Calvo (2006) for Spanish manufacturing, McPherson (1996) for Southern African micro businesses, and Wagner (1992) and Almus and Nerlinger (2000) for German manufacturing. Dunne et al. (1989) analyse plant-level data (as opposed to ? rm-level data) and also observe that growth rates decline along size classes. Research into Gibrat’s law using data for speci? c sectors also ? nds that small ? rms grow relatively faster (see e. g. Barron et al. (1994) for New York credit unions, Weiss (1998) for Austrian farms, Liu et al. (1999) for Taiwanese electronics plants, and Bottazzi and Secchi (2005) for an analysis of the worldwide pharmaceutical sector). Indeed, there is a lot of evidence that a slight negative dependence of growth rate on size is present at various levels of industrial aggregation. Although most empirical investigations into Gibrat’s law consider only the manufacturing sector, some have focused on the services sector. The results, however, are often qualitatively similar – there appears to be a negative relationship between size and expected growth rate for services too (see Variyam and Kraybill (1992), Johnson et al. (1999)) Nevertheless, it should be mentioned that in some cases a weak version of Gibrat’s law cannot be convincingly rejected, since there appears to be no signi? cant relationship between expected growth rate and size (see the analyses provided by Bottazzi et al. (2005) for French manufacturing ? rms, Droucopoulos (1983) for the world’s largest ? rms, Hardwick and Adams (2002) for UK Life Insurance companies, and Audretsch et al. (2004) for small-scale Dutch services). Notwithstanding these latter studies, however, we acknowledge that in most cases a negative relationship between ? rm size and growth is observed. Indeed, 5 We should be aware, however, that ‘mean-reversion’ does not imply that ? rms are converging to anything resembling a common steady-state size, even within narrowly-de? ned industries (see in particular the empirical work by Geroski et al. (2003) and Ce? s et al. (2006)). 12 #0703 it is quite common for theoretically-minded authors to consider this to be a ‘stylised fact’ for the purposes of constructing and validating economic models (see for example Cooley and Quadrini (2001), Gomes (2001) and Clementi and Hopenhayn (2006)). Furthermore, John Sutton refers to this negative dependence of growth on size as a ‘statistical regularity’ in his revered survey of Gibrat’s law (Sutton, 1997: 46). A number of researchers maintain that Gibrat’s law does hold for ? rms above a certain size threshold. This corresponds to acceptance of Gibrat’s law according to Mans? eld’s third rendition, although ‘mean reversion’ leads us to reject Gibrat’s Law as described in Mans? eld’s second rendition. Mowery (1983), for example, analyzes two samples of ? rms, one of which contains small ? rms while the other contains large ? rms. Gibrat’s law is seen to hold in the latter sample, whereas mean reversion is observed in the former. Hart and Oulton (1996) consider a large sample of UK ? rms and ? nd that, whilst mean reversion is observed in the pooled data, a decomposition of the sample according to size classes reveals essentially no relation between size and growth for the larger ? rms. Lotti et al. (2003) follow a cohort of new Italian startups and ? nd that, although smaller ? rms initially grow faster, it becomes more di? cult to reject the independence of size and growth as time passes. Similarly, results reported by Becchetti and Trovato (2002) for Italian manufacturing ? rms, Geroski and Gugler (2004) for large European ? rms and Ce? s et al. (2006) for the worldwide pharmaceutical industry also ? nd that the growth of large ? rms is independent of their size, although including smaller ? rms in the analysis introduces a dependence of growth on size. It is of interest to remark that Caves (1998) concludes his survey of industrial dynamics with the ‘substantive conclusion’ that Gibrat’s law holds for ? rms above a certain size threshold, whilst for smaller ? rms growth rates decrease with size. Concern about econometric issues has often been raised. Sample selection bias, or ‘sample attrition’, is one of the main problems, because smaller ? rms have a higher probability of exit. Failure to account for the fact that exit hazards decrease with size may lead to underestimation of the regression coe? cient (i. e. ?). Hall (1987) was among the ? rst to tackle the problem of sample selection, using a Tobit model.

History Of Optic Fiber Usage Information Technology Essay

History Of Optic Fiber Usage Information Technology Essay The idea of fiber optics communication system is basically sending information through light. Optical fiber was first developed in 1970 as a basic communication purpose with a very low attenuation as transmitting light through fiber optics cable for long distance communication. In 1975, the first commercial fiber optics communication system was developed using semiconductor laser and operated at 0.8 Â µm wavelength and a bit-rate of 45 Mbps (Mega bits per second) up to 10 km (Elion Elion 1978) (Sullivan Curt 2003). In long beach California was the first live telephone traffic sent at about 6 Mbps and it was in 1977. After that, generations of fiber optics system technologies were developed, improved, and upgraded to achieve the first transatlantic operation in 1988. All fiber optics systems are limited by something called dispersion. The initial thought of fiber optics was an experiment involving a bucket of water and sunlight. It demonstrated the suns reflection within the bucket with a hole and water pouring out illuminating the water and the sunlight can be seen in the stream of water (Elion Elion 1978). Then it moved on to optical voice transmission known as photo phone. Further, it went to fiberscope that was used to inspect welds within reactor vessels, combustion chambers of the jet engines, and then to the medical field utilized in laparoscopic surgery. Researches and improvements continued through the fiber optics generations to overcome the dispersion phenomena by using dispersion-shifted fibers to minimize the dispersion at 1.55 Â µm or by limiting the laser spectrum to a single longitudinal mode (Alwayn 2004) (Sullivan Curt 2003). The idea of using fiber optical amplification came with the development of the fifth generation. The amplification development reduced the need of using repeaters and wavelength division multiplexing (WDM); which will be described in details later; and increases the data capacity. By these developments, a bit rate of 10 Tb/s was achieved in 2001. The developments of fiber optics generations are a continuous operation to especially for the huge market of the internet communications which requires an increase in communications bandwidth such as video on demand. These growing in using internet protocol data traffic are increasing side by side with faster rate integrated systems complexity. (Elion Elion 1978) Fiber optics manufacturers had reduced the cost by the huge request of communication companies such as ATT to take the advantage of delivering the technology of internet and telephone through higher data broadband services to customers homes (Sullivan Curt 2003) (Snell 1996). Fiber optics is already being used nowadays in military and commercial aircraft, and some of the areas it altogether replaced the Digital Flight Data Recorder with the newer Distributed Flight Data Acquisition Unit that performs the same thing but evaluates much more information. Indeed, future aircrafts will see fiber optics technology in the flight controls. Fiber optics has evolved practically from ideas to a thing of the future (Alwayn 2004) (Elion Elion 1978). Fiber optics Application The demand and usage of optical fiber has grown rapidly and optical fiber applications are numerous. Ranging from global networks to desktop workstation, telecommunication applications are widespread. These involve the transmission of data, voice, or video across distances of less than a meter to thousands of kilometers by utilizing one of a few standard fiber designs within one of several cable designs. Optical fibers are used by carriers to carry plain old telephone service (POTS) over their nationwide networks. Furthermore, local exchange carriers (LECs) employ fiber to carry the same service across central office switches at local levels and often as far as the individual home (fiber to the home, FTTH) or neighborhood (Alwayn 2004) (Elion Elion 1978). Moreover, optical fiber has a widespread use in transmission of data. Multinational firms require reliable and secure systems for transferring data and financial information among buildings to the computers of desktop terminals and around the world. Fiber is also used by cable televising companies in order to deliver digital video and data services. Due to the high bandwidth offered by fiber, it is the ideal choice for transmitting broadband signals like the high-definition television telecasts. Furthermore, intelligent transportations systems including smart highways equipped with intelligent traffic signals, changeable message signs, and automated tollbooths, also utilize telemetry systems based on fiber-optics (Alwayn 2004) (Fiber-Optics.Info 2010). Biomedical industry is another significant application of optical fiber. Fiber-optic systems are used in almost all modern telemedicine systems and devices for transmission of digital diagnostic images. Additionally, other applications for optical fiber also include military, space, industrial and the automotive sector (Elion Elion 1978) (Snell 1996). Fiber optics communication technology is used by todays telecommunications companies such as ATT in the United States and BT in the UK. Also it is used by internet providers and cable television signal providers such as Sky. For the huge expense of fiber optics system, the technology was first used for long-distance communication only. But, now days developments of the cities infrastructure had to take place to install the fiber optics communication system regardless of the cost and time consuming. The challenge of fiber optics technology companies was reflected positively on the market and the cost of fiber optics communications dropped considerably (Alwayn 2004) (Elion Elion 1978) (Fiber-Optics.Info 2010). By the developments of optical amplification system, an intercontinental network of 250,000 km of submarine-communication-cable was developed with a capacity of about 2.5 Tb/s was achieved. Also, the optical communication system was installed onboard aircrafts for data, video, and radio signals communication. It was first introduced to aviation industry by NASA researches on military aircrafts such as the first F/A-18 hornet through its RTDP; radar tracking and detecting system processor, missile video tracing system, and with the FLIR system; forward looking infra red sensor, and the integrated radar system with increased speed and memory capacity. Military aircrafts are always in-need to reduce weight when it is in slick phase to improve its capability of maneuvering and delivering various types of ordnance in a very precise targeting and accurate guidance. Lately, this technology was used on the F-22 airforce raptor on its high speed data bus and fiber optics transceiver (Alwayn 2004). This idea was reflected on the civil aircrafts later on as they always in-need to reduce weight to overcome the fuel usage and deliver larger number of passengers which means saving mo ney and increasing profits. Besides that, the new avionics systems technology and complexity required new communication system other than the copper wires such as the normal ARINCs (Fiber-Optics.Info 2010). Boeing and Airbus developed very complex integrated systems that control the aircraft performance at an altitude of 30,000 ft and above which required bigger and more complicated communication systems which means: More chance of shorting the wires. More EMI (electro-magnetic-interference) which can cause a distortion for the signals More weight More chance of shorting and cause sparks and fire on-board and aircraft The first official usage of fiber optics technology usage was on-board the Boeing 777 after the development of its AIMS (Aircraft Information Management System) which have more than 2 million of computer codes. Also Boeing 777 was the first aircraft to install an optical LAN (local area network) for on-board data communication and on its cabin systems communications (Sullivan Curt 2003) (Snell 1996). After that, fiber optics system was installed on the Boeing 757 flown by Air Mexico who did not experience a single failure. So here comes the safety, reliability, durability and stability of signals communications on-board an aircraft which can make the affordability part negligible. We have to mention that the cost of optical fiber systems are dropping for the establishments and marketing competition of huge number of manufacturers and suppliers (Alwayn 2004) (Fiber-Optics.Info 2010). Fiber Optics vs. Electrical Copper Wires: Fundamentally, there are three types of transmission media: copper wires, waveguides and free space. Copper wire, such as coaxial cable is broadly used. A signal is transmitted across the wire in either digital or analog form to a receiver placed at the end of the wire. Free-space transmission is also widely used through which radio, television and other across-the-air signals are carried. Waveguides describe the fiber-optic transmission. Significantly, a waveguide such as a optical fiber restrains the electromagnetic radiation, light (Bidgoli 2010). Fiber optic transmission provides the best elements of both free-space and coaxial transmission. It is capable of carrying a signal from point A to point B in the absence of any limited electromagnetic spectrum. Nonetheless, it does not suffer from limited data rate and bandwidth is the same way as the coaxial cables do. The advantages of fiber optics system over the copper wires are: No Electro-Magnetic-Interference (EMI). No radio-Frequency-interference (EMF). Immunity from electromagnetic noise High Signal quality Lighter weight cables Longer distance capability (Bidgoli 2010) Smaller diameter cables which mean saving more space. Greater bandwidth for data transfer Safety against shorting and sparking High bandwidth and greater information capacity Easy upgrade: Can be upgraded easier without ripping and replacing cable harnesses. Easier maintenance and handling, proved by Boeing and Lockheed martin engineers Lower cost (Bidgoli 2010) Lower signal loss for long distance communication Higher resistance against stress, temperature and vibration and higher lightning strikes incidence. Doesnt require repeaters for long distance communication Can operate for up to 100 km without passive or active processing But, we have to say that copper wires have some specifications that fiber optics doesnt: Can carry electrical power beside the signals Lower material costs Doesnt have minimum bending radius Can easily be installed between boxes and chips (Bidgoli 2010) Cable technology is used for connecting networks together; however, as optical fiber technology is moving forward, it is gradually replacing copper wires as an excellent medium of communication signal transmission. The main reason for this is that fiber optics offers much more benefits than conventional copper wires and cables, as stated above (Sullivan Curt 2003). Moreover, these benefits can be elaborated as follows: Resistance to Interference: Fiber optics do not conduct electricity as it is obtained from glass, which eliminates activities like grounding and makes it potentially immune to electromagnetic interruption. Working of Fiber optics, unlike copper cables, is based on light pulses that make it usable outdoors and in close proximity to electrical cables (Bidgoli 2010). Low Maintenance: This entails that optical fiber is not sensitive to elements like water and chemicals because it is produced from glass. Additionally, Fiber optics cannot be damaged by harsh elements. This makes the overall cost of maintenance and service lesser than its counterpart. Efficiency and Security: Information can be transmitted with greater fidelity with the help of fiber optics unlimited bandwidth. It can offer nearly 1,000 times as much bandwidth across distances approximately 100 times farther than copper cables. This provides a super-fast connection running in circles around the bandwidth assigned by cable connections. Moreover, since fiber optics is harder to tap than regular copper wires, it can offer additional data security (Bidgoli 2010). Picture Quality: In comparison to copper wires, the high quality technology embedded in fiber optics is much more powerful. One can obtain high-definition picture quality from fiber technology as there is no external interference. Safety: Fiber optics poses no threat of physical injuries during breakage of fiber optic cables. Instead of transmitting through electricity, it transmits data via light. Users face no risk of injury from dangers such as sparking, electrocution, fire, etc. (Bidgoli 2010). Interestingly, the benefits of converting into fiber technology such as Ethernet converters show proven advantages, considering that internet infrastructure is steadily making this transition rather than conventional copper cabling. Furthermore, applications of fiber optic include manufacturing and process control, supervisory control as well as data acquisition. Using transceiver modules provide a cutting edge and most importantly the highest quality data transmission for users television, home phone and internet (Sullivan Curt 2003). Basic components of fiber optics system: It is consisted of: Core: it is basically a cylinder of glass or plastic material. Cladding: a layer causing the light signal to be confined to the core by using the total internal reflection method. Buffer: a layer used to capsulate one or more core and cladding providing mechanical isolation and a protection from physical damage. Jacket: a further isolation and protection. Characteristics The major characteristics of optical fiber transmission lines are: Attenuation and its variation with transmission input wavelength, cable temperature and modal distribution. Radiation: and its variation with fiber temperature and bend radius Distortion and its variation with bandwidth, amplitudes, wavelength and modal distribution of the input light, length of the fiber, and lastly, environmental temperature (Snell 1996) Physical Parameters: This includes weight, size, ease of installation, total volume, coupling and splicing. Environmental parameters: This includes resistance to stress, water and chemical corrosion, temperatures and mechanical stresses (Alwayn 2004). Types: single mode and multi-mode fibers. A single-mode optical fiber Multi-mode optical fiber There are two categories of optical fibers, namely, single-mode fiber optical cable and multi-mode fiber optic cable. In essence, these types of fiber optic cables are comprised of numerous layers of glass, each having refractive index lower than the one next to moving from the center outwards. Since light is faster in lower glass refractive index, the wavelengths of light are broken outside the fiber, capable of traveling to the middle (Snell 1996). Multi-mode Fiber Optic Cable: Optical fiber with a base diameter greater than 10 microns can be analyzed through geometrical optics, and is called a multi-mode fiber. In this type of optic cable, the rays of light along the core of the fiber are led by total reflection. Moreover, rays meeting the core-mantle border at a high angle over the critical angle for this limit are fully considered. The critical angle is said to be the difference in refractive index between the mantle and core materials. Rays hitting the border at a shallow angle form the base breaks into the mantle and does not transmit the light and information along the fiber. Moreover, the acceptance of the fiber is determined by the critical angle, and is often referred to as a numerical aperture (Snell 1996). A greater numerical aperture allows light to spread into two distinct beams at different angles near the axis, for the effective coupling of light into the fiber. Single-mode Fiber Optic Fiber Fiber core diameter of nearly ten times the wavelength of light propagation is impossible to model with geometric optics. Rather, they can be studied as an electromagnetic structure by solving Maxwells equations that are reduced to the electromagnetic wave equation. It acts as an optical waveguide and supports one or more confined transverse modes which allows light to propagate through the fiber. Fiber that supports only one mode is known as mono-mode or single mode fiber. It is an extremely focused source of light which limits beams to a smaller range or angles closed to the horizontal. A fiber optic data cable has three primary functions. It converts an electrical input signal into an optical signal, transmit the optical signal across an optical fiber, and lastly, convert the optical signal back to an electrical signal (Green 2006). Transmitter: It is a semiconductor device and can be an LED (light emitting diode) or a laser diode. It converts the electrical input signal into an optical signal, and its drive circuit changes the current flow across the light source, which in turn changes the irradiance of the source. This process of changing the irradiance of the source as a function of time is known as modulation. Receiver: It is a photo-detector and the main component of the receiver which converts light signals into electrical using the photoelectric effects method. It is basically a semiconductor-based photodiode. Amplifier: it is used instead of the complex repeaters. It amplifies the light and optical signals without converting it to electrical. Fiber-optic telecommunication systems operate on pulse-code modulation in which information is sent across as a series of pulses. Moreover, the digital pulse-code modulation is coupled into a fiber and the fiber end set up by a connector in order to maximize the input power. In fiber-optic communication systems, semi-conductor lasers are best suited. Their shape and size enables efficient coupling of light within the small-diameter core of an optical fiber (Sullivan Curt 2003). The fiber then carries the light towards the receiver which detects the light and recovers the digital signal. As scattering, dispersion and absorption in the fiber degrade the signal, optical amplifiers must be used to regenerate the signal (Snell 1996). The U.S. military quickly turned towards fiber optics for enhanced and improved communications as well as tactical systems. During the early 1970s, a fiber optic telephone link was installed by the U.S. Navy aboard the U.S.S. Little Rock. Toward that end, The Air Force developed its Airborne Light Optical Fiber Technology (ALOFT) program in 1976. Greatly motivated by the success of these practical applications, military R D programs developed stronger fibers, ruggedized, high-performance components, tactical cables, and several demonstration systems that ranged from aircraft to undersea applications. Soon after, commercial application followed that included both ATT and GTE installing fiber optic telephone systems in 1997 in Chicago and Boston respectively (Green 2006) (Keller 2010). Therefore, these successful applications resulted in the increase of fiber optic telephone networks. In the early 1980s, single-mode fiber running in the 1310 nm and then in 1550 nm wavelength ranges we re installed for these networks. Earlier, information networks, computers and data communications were far slower to employ fiber; however, today they are embracing the transmission system that has lighter weight cable, carries more data faster and across long distances, and resists lightning strikes (Elion Elion 1978) (Snell 1996). An average aircraft consists of over hundred miles of electrical wires and controls almost everything from landing gear to calls from flight-attendants. These insulated copper wires have proven to be a big bottleneck: it is heavy in weight, vulnerable to electromagnetic interference and if not accurately maintained, can cause system failures or fires. Some of these wires can be replaced with fiber-optic technology that is lighter than copper wire, immune to electrical shocks, and less sensitive to electromagnetic interference (Green 2006). Researchers have developed a new optical switch to be incorporated into the cockpit controls in order to manage operations that involve turning on and off, for instance, displays, landing gear, manual switching between fuel tanks, etc. Presently, on-off switches in a cockpit are connected to separate wires spread throughout a plane, controlling several functions. In case a switch fails to work due to wiring problems at the inside of the plane, dete cting the offending line can consume a lot of time and effort, since the wires are usually bundled together. Therefore, this switch is capable of sensing whether a button has been pressed fro off to on (Keller 2010). Then, the information from the fiber-based device can be directed toward a main fiber artery that carries hundreds of signals simultaneously. Through this, the bulk of wires, and cost is eliminated, and maintenance is simplified. Although engineers have been working to replace aircraft wiring with fiber for several years, unfortunately, they have had only moderate success. Built in mid-1990s, Boeings 777 uses a fiber-optic communication network, but the design and implementation being a part of an experiment. Moreover, the network was not a critical system and it was over-designed with more possibility of error than greater cost-effectiveness if in case it was broadly implemented in the industry. Nevertheless, Boeings 787 aircrafts, is equipped with a more cost-effectiv e optical fiber communication network (Green 2006) (Keller 2010) (Sullivan Curt 2003). ARINC 429 The first major variation in avionics databusing on military as well as commercial aircraft came during 1970s and 1980s. It was deployed as a 100 kilobit-per-second ARINC 429 databus which is a multiplex databus standard of ARNIC Inc. The databus is omnipresent on commercial airliners and is one of the most common avionics equipment used in flying today. The ARNIC 429 is equipped by all commercial aircrafts for legacy connections and for securing backup for flight critical controls. The ARNIC 429, apart from being the de-facto standard, is used on aircrafts for digital electronics, navigation and air data computers, engine control systems, and radios which are fully computerized and need to interact with each other. Furthermore, ARINC 429 is greatly responsible for setting up the digital era in commercial and military avionics. However, it is a comparatively slow twisted-pair databus and unidirectional like 1553. Only one terminal on the bus can broadcast and as much as 20 terminals can listen (Keller 2010). The ARINC 429 represents a tightly legalized architecture equipped with standard ARINC connectors. Before the introduction of ARINC 429, avionics designers utilized hard-wired point-to-point connectors with analog signals suitable for every sensor type, like the navigation gyros. Many sensors had multiple wires and multiple signals. In typical applications deployed on todays jetliners, systems designers extensively utilize ARINC 429 in order to connect avionic subsystem boxes and components digitally. One master subsystem on the bus sends information to at least 20 slave subsystems, but the slaves are unable to send information back to the master. Therefore, to enable a slave subsystem to transmit data back to the master, another ARINC 429 bus is used with its direction reversed, thereby enabling the original slave to send and the original master to listen. More frequently, designers make use of two ARINC 429 buses, amounting to point-to-point bi-directiona l interconnections between avionics subsystems: one bus transmitting in one direction, and another bus transmitting in the reverse direction (Green 2006) (Keller 2010). One such example includes jetliners flight-management computer that accepts and processes inbound signals from several different sensors and other subsystems, and estimates the paths taken by flights, their time of arrival, fuel burn, etc. In this approach, ARINC 429 busses send information from the sensors and allow the flight-management computer to listen to that data. Whenever the flight-management computer needs to transmit information tack to a particular sensor, designers employ another 429 bus that runs in the opposite direction. Regardless of its low speed, the digital ARINC 429 databus aids in increasing the efficiency, speed, and facilitates maintenance since it can move several digital data packages across the same twisted pair, where analog approaches required a different wire for each signal (Keller 2010). The digital ARINC 429 bus allows for multiplexing of the information on two wires. Since it is capable of sending data across only in one direction, it is greatly reli able due to its lower possibility of data corruption or data conflicts. Furthermore, this reliability of the databus makes it usable and well-known for flight-critical data involving avionics activities such as flight navigation and engine control (Keller 2010). The sheer size of ARINC 429 installed base drives its popularity; it is included in almost every commercial jetliner recently manufactured. ARINC 429 has limited addressing capacity and limited bandwidth; still it is proved as a highly robust physical bus and has served the industry well enough for several years. Moreover, it is a viable bus and protocol where installations require limited bandwidth and limited address space on the bus. However, modern avionics architecture demands more bandwidth, more address space, and greater flexibility than what the ARINC 429 can deliver (Keller 2010). ARINC 629 ARINC 629 is a 2-megabit-per-second databus that is borne from the MIL-STD-1553 technology. The conversion into an ARINC 629-type of bus topology strongly supported the move in the aviation industry to greater degrees of integration within the full systems throughout the avionics and the aircraft systems. The launch of ARINC 629 was set up on the highly-advanced architecture of the Boeing 777 double-engine jumbo jetliner. After its launch, the databus started as a Boeing invention known as Digital Autonomous Terminal Access Communications (DATAC). In comparison to ARINC 429, 629 is a completely different model altogether. It is bi-directional and does not need the master, which has been a potential single point of failure in 429. Although it is a sporty technology, it is still expensive. Additionally, ARINC 629 is far more cognate to 1553 than the ARINC 429, which has bi-directional flow of data (Keller 2010). One of the most attractive aspects of ARINC 629 was the bus efficiency, or rather the ratio of actual data transmitted by the bus to the routing overhead code. ARINC 429 has an efficiency of nearly 45 percent; however, with ARINC 629 efficiency can reach up to 85 percent if the bus is architected right. Furthermore, as compared to 429, ARINC 629 is a bus without connectors. In the ARINC 629 a twisted pair of wires is fed across the bus coupler that behaves like a transformer. Nonetheless, it was the price of the bus that got designers in a dilemma about the usage of ARINC 629. Although, ARINC 629 was more reliable, but it was much costlier than what the designers had actually thought (Keller 2010). Cost concerns, a lack of large new commercial aircraft projects when Boeing developed the 777, and the increasing popularity of Ethernet networking technology blended together to halt implementation of the ARINC 629 after the 777. ARINC 629 is heavy and expensive to implement. Future Fiber optics is anticipated to have a better future in military aviation industry. It exclusively provides high bandwidth, immunity against electromagnetic interference, and is light weight. Optical fiber was deployed on the AV-8B several years ago; it is used across the F/A-18E/F including several other aircrafts, and is likely to be fielded at a higher degree in coming years. However, before fiber-based applications in intense aviation environment can proliferate, a couple of standards are required in component, training, testing and other areas. Techniques such as WDM, short for wavelength division multiplexing, might dramatically increase the throughput and lower the footprint needed today for analog and digital data communications, beyond the immediate horizon (Keller 2010) (Sullivan Curt 2003). Fiber optic standardization within the aerospace sector leaves out something to be desired. Unfortunately, there are no standards for: The method for computing link loss power budgets The geometrics of critical parts like the end faces of optical fiber cable terminations, and Training military aviation personnel and technicians in the handling of optical fiber There has been a consensus for standardization. Operating with the Society of Automotive Engineers (SAE), NAVAIR, short for Naval Air Systems Command, avionic companies, airframers and components suppliers have put extreme efforts in developing training standards and components to enhance the supportability of current systems, and to cover various emerging technologies. In essence, fiber optics has been a corporate initiative within NAVAIR, holding its base in the commands Avionics Division instead of a particular program office (Adams 2005). Fiber optic technology has evolved at the major contractor or airframer level, in military aviation, as stated by researchers, engineers, personnel, and F/A-18 fiber optic experts with PMA 265 at NAVAIR. Fiber optics avionics components standardization will greatly assist in eliminating ambiguities and allowing test and inspection of equipments in order to sufficiently cover the technology fielded today (Adams 2005) (Sullivan Curt 2003). JELLI JELLI is an SAE group that is developing performance standards for the initial test and inspection processes of avionics fiber optic assemblies. JELLI is short for jumpers, endfaces, link loss and inspection; i.e. the processes and components used in optical networks. They are supported by the following definitions: Jumpers: The cables that are utilized in testing the overall optical performance of the fiber optic cables after installation. Endface: This is the polished end of the high-precision ceramic cap of the fiber optic termination that enables optical coupling. Link Loss: It is the attenuation of the signal, primarily from connector loss, and Inspection: It involves the examination of a cable installation in order to verify its performance. Different polish standards are required to apply to the physical vs. non-contact connections. However, within those areas, everyone should satisfy a termination endface range for that kind of polish. The cleanness of the endface is another important parameter. Test jumpers have endfaces and their polish requirements must match the component being installed within the aircraft. The test jumpers fail work on the airplane without such as standard (Adams 2005). Furthermore, standards for components like endfaces are essential to eliminate subjectivity on the engineering side. Additionally, it is mainly important since aircrafts with fiber optic systems have been launched in order to set up a baseline for the avionics technicians, and to instruct them on what exactly a good connector endface. In essence, work on inspection involves the magnification and several other criteria required of the equipment that is used for examining the termination endfaces and detect damages. For instance, tiny char

Explaining The Purpose Of The Main Financial Statements Finance Essay

Explaining The Purpose Of The Main Financial Statements Finance Essay A financial statement (or financial report) is a formal record of the financial activities of a business, person, or other entity. In British English-including United Kingdom company law-a financial statement is often referred to as an account, although the term financial statement is also used, particularly by accountants. For a business enterprise, all the relevant financial information, presented in a structured manner and in a form easy to understand, are called the financial statements. They typically include four basic financial statements: Balance sheet: also referred to as statement of financial position or condition, reports on a companys assets, liabilities, and Ownership equity at a given point in time. Income statement: also referred to as Profit and Loss statement (or a PL), reports on a companys income, expenses, and profits over a period of time. Profit Loss account provide information on the operation of the enterprise. These include sale and the various expenses incurred during the processing state. Statement of retained earnings: explains the changes in a companys retained earnings over the reporting period. Statement of cash flows: reports on a companys cash flow activities, particularly its operating, investing and financing activities. For large corporations, these statements are often complex and may include an extensive set of notes to the financial statements and management discussion and analysis. The notes typically describe each item on the balance sheet, income statement and cash flow statement in further detail. Notes to financial statements are considered an integral part of the financial statements. The Balance Sheet The balance sheets purpose is to show the assets of the company. Balance sheets are based on a fix point called a reporting perioda day, a month, a quarter, a year. A quick glance at a balance sheet will show you what the company owns and how much it owes. Balance sheets include assets (property, cash, anything owned of value), liabilities (debt owed) and shareholders equity. Income Statements Income statements show the revenue earned during a reporting period.  Included in this report are the expenses and cost of creating the revenue. Once the expenses and costs are removed from the total revenue, the bottom line of the report reveals whether or not the company lost money or made money. This report is sometimes referred to as the profit and loss statement. Another feature of the income statement is the EPS, or earnings per share. This reveals what a shareholder would receive if you were being paid dividends per each share owned. Cash Flow Statements Cash on hand is important because it supports the daily activities of a business. There must be enough cash on hand to pay expenses and buy assets as needed. Cash flow statements track the inflow and outflow of cash. They reveal whether or not cash was generated by the business. The data for a cash flow statement comes from an income statement and the balance sheet. The cash flow statement reveals net decreases or increases of cash for the reporting period. Retained Earnings Once liabilities and assets are known and a balance sheet is created, it is known whether or not the shareholders have a positive or negative equity. From the equity is taken retained earnings. Retained earnings are broken down and explained in the statement of retained earnings. This statement reveals what the company keeps and does not distribute to the owners and how that amount changes over the reporting period. Losses are called accumulated losses, retained losses or accumulated deficit. Financial Statements Once a set of financial statements are prepared they can be used for loan applications, fund-raising or to place a value on a business. But they are typically used for making business decisions that will affect operations. The numbers and calculations in the financial statements are also used to calculate ratios and make further analysis. Common figures derived are operating margins, debt-to-equity ratio, P/E, working capital and inventory turnover Purpose of financial statements by business entities The objective of financial statements is to provide information about the financial position, performance and changes in financial position of an enterprise that is useful to a wide range of users in making economic decisions. Financial statements should be understandable, relevant, reliable and comparable. Reported assets, liabilities and equity are directly related to an organizations financial position. Reported income and expenses are directly related to an organizations financial performance. Financial statements are intended to be understandable by readers who have a reasonable knowledge of business and economic activities and accounting and who are willing to study the information diligently. Financial statements may be used by users for different purposes: Owners and managers require financial statements to make important business decisions that affect its continued operations. Financial analysis is then performed on these statements to provide management with a more detailed understanding of the figures. These statements are also used as part of managements annual report to the stockholders. Employees also need these reports in making collective bargaining agreements (CBA) with the management, in the case of labor unions or for individuals in discussing their compensation, promotion and rankings. Prospective investors make use of financial statements to assess the viability of investing in a business. Financial analyses are often used by investors and are prepared by professionals (financial analysts), thus providing them with the basis for making investment decisions. Financial institutions (banks and other lending companies) use them to decide whether to grant a company with fresh working capital or extend debt securities (such as a long-term bank loan or debentures) to finance expansion and other significant expenditures. Government entities (tax authorities) need financial statements to ascertain the propriety and accuracy of taxes and other duties declared and paid by a company. Vendors who extend credit to a business require financial statements to assess the creditworthiness of the business. Media and the general public are also interested in financial statements for a variety of reasons. Financial ratio analysis groups the ratios into categories which tell us about different facets of a companys finances and operations. An overview of some of the categories of ratios is given below. * Leverage Ratios which show the extent that debt is used in a companys capital structure. * Liquidity Ratios which give a picture of a companys short term financial situation or solvency. * Operational Ratios which use turnover measures to show how efficient a company is in its operations and use of assets. * Profitability Ratios which use margin analysis and show the return on sales and capital employed. * Solvency Ratios which give a picture of a companys ability to generate cash flow and pay it financial obligations. Differences between the formats of financial statements for 3 different type of business- sole proprietorship, partnership and Limited company Government financial statements The rules for the recording, measurement and presentation of government financial statements may be different from those required for business and even for non-profit organizations. They may use either of two accounting methods: accrual accounting, or cash accounting, or a combination of the two (OCBOA). A complete set of chart of accounts is also used that is substantially different from the chart of a profit-oriented business Financial statements of non-profit organizations The financial statements of non-profit organizations that publish financial statements, such as charitable organizations and large voluntary associations, tend to be simpler than those of for-profit corporations. Often they consist of just a balance sheet and a statement of activities (listing income and expenses) similar to the Profit and Loss statement of a for-profit. Personal financial statements Personal financial statements may be required from persons applying for a personal loan or financial aid. Typically, a personal financial statement consists of a single form for reporting personally held assets and liabilities (debts), or personal sources of income and expenses, or both. The form to be filled out is determined by the organization supplying the loan or aid. Differences between Sole Proprietorship, Partnership Corporation I want to do this! Whats This? There are a number of different types of business organizations an individual or a group can form. However, three of the most common types of business organizations are sole proprietorships, partnerships and corporations. These three types of businesses are similar in some ways, but a number of differences are important to note. Formation A sole proprietorship or a partnership may be formed without filing any formal paperwork. The creators of a corporation, however, must file a document known as the articles of incorporation. Liability The owner(s) of a sole proprietorship or a partnership may be held liable for any business activity and/or obligation. Corporate shareholders, however, usually are liable only for the amount they invested. Record Keeping Corporations are required to keep strict records of meetings and other similar administrative activities, while a sole proprietorship or a partnership typically is not required to do so. Size A sole proprietorship can have only a single owner, but a partnership or a corporation may have any number of owners. Taxes The owner of a sole proprietorship is required only to report the business earnings on her tax return, while a corporation or a partnership must file a separate return for the business. BASIC FINANCIAL STATEMENT FORMAT PARTNERSHIP When preparing financial statements by hand the Income Statement would usually be prepared first because the net income or loss becomes part of the Statement of Partners Capital. The Statement of Partners Capital is usually prepared second because the ending partners capital balances become part of the Balance Sheet. Corporations are subject to income taxes but sole proprietorships and partnerships are not. Otherwise the income statements of each are identical. Income Statement (single-step format): HANSON RETAIL FOOD STORE Income Statement Year Ended December 31, 2006 Net Sales $262,000 Rent revenue 6,900 Interest revenue 1,400 Total Revenue 270,300 Expenses: Cost of Goods Sold $159,000 Salaries and wages 45,000 Advertising 12,400 Freight out 4,000 Depreciation 5,000 Taxes and licenses 3,000 Rent 6,300 Interest expense 350 Loss on sale of assets 250 Property taxes 2,000 Total expense 237,300 Net Income (loss) $ 33,000 ======== Owners equity statements of corporations are called Statement of Retained Earnings, those of sole proprietorships are called Statement of Capital and those of partnerships are called Statement of Partners Capital. Statement of Partners Capital: HANSEN RETAIL FOOD STORE Statement of Partners Capital Year Ended December 31, 2005 John Soo Mary Doe Totals Beginning balance $ 24,000 $ 33,000 $ 57,000 Net income (loss) 16,500 16,500 33,000 40,500 49,500 90,000 Withdrawals 500 1,500 2,000 Ending balance $ 40,000 $ 48,000 $ 88,000 =========== =========== ====== Balance Sheets of corporations have a Shareholders Equity section whereas sole proprietorships have an Owners Capital section and partnerships have a Partners Capital section. Otherwise the Balance Sheets would be identical. Balance Sheet: HANSEN RETAIL FOOD STORE Balance Sheet December 31, 2006 ASSETS Current Assets: Cash $ 3,000 Short-term investments/marketable securities 6,000 Accounts receivable, net 5,000 Inventory 10,000 Prepaid rent 2,000 Office supplies on hand 1,000 Total current assets 27,000 Long-Lived Assets: Long-term investments $ 10,000 Land 35,000 Building 86,000 Machinery equipment 50,000 Less accumulated depreciation ( 23,000) Patents 4,000 Total long-lived assets 162,000 Total Assets $189,000 ======== LIABILITIES Current Liabilities: Accounts payable $ 4,200 Notes payable 15,000 Interest payable 1,000 Wages payable 800 Total current liabilities 21,000 Long-Term Liabilities: Mortgage payable $ 30,000 Bonds payable 50,000 Total long-term liabilities 80,000 Total Liabilities 101,000 PARTNERS CAPITAL John Soo, Capital 40,000 Mary Doe, Captial 48,000 Total Partners Capital 88,000 Total Liabilities and Owners Equity $189,000 TASK 2 Last Year Current Ratio = C.A / C.L = 21 / 15 = 1.4 Acid Test = C.A / C.L = 15 / 15 = 0 Net Profit Margin = N.P / Sales =37/499 =0.07 Gross Profit Margin = G.P / Sales =99/499 =0.20 Return on Capital Employed = N.P / Equit + Debt = 17 / 75 = 0.23 Return on Ordinary Share holder fund = N.P after tax / Ordinary share holder equity = 17 / 14 = 1.2 Average Stock Turnover period = Avg Stock / CGS * 365 = 6 /400 X 365 =5.5 =6days Current Year Current Ratio = C.A / C.L = 11 / 11 = 0 Acid Test = C.A / C.L = 7 / 11 = 0.64 Net Profit Margin = N.P / Sales = 32 / 502 = 0. 06 Gross Profit Margin = G.P / Sales = 132 / 502 = 0.26 Return on Capital Employed = N.P / Equit + Debt = 5 / 79 = 0.06 Return on Ordinary Share holder fund = N.P after tax / Ordinary share holder equity = 5 / 14 = 0.36 Average Stock Turnover period = Avg Stock / CGS * 365 = 4 / 370365 =3.95 = 4 days

It Pays to Be Bilingual :: Argumentative Essay

It Pays to Be Bilingual Hoy en dà ­a es casi necesario ser bilingue si se desea tener à ©xito. Desde California a Washington, de Pensilvania a Florida, uno puede oà ­r muchas personas hablando espaà ±ol. Los Latinos como una gran parte de la sociedad ya no es una cosa del pasado, pero una realidad. Los Hispano Parlantes no se centralizan solamente en las ciudades mà ¡s grandes de Estados Unidos, sino en los pueblos pequeà ±os tambià ©n. Con una mirada de la poblacià ³n total en los Estados Unidos, unos trabajos tà ­picos y el estudio afuera, se puede ver que ser bilingue, especialmente con inglà ©s y espaà ±ol es un recurso con mucho valor. Spanish can be heard clear across the United States because Latin Americans are no longer living only in large cities, but in small towns as well. If you can read and understand this, you are at a great advantage in today’s job market. If you can’t, pay close attention to the reasons you should consider learning Spanish, and allow me to translate my thesis statement for you. By observing the population at large in the United States, some of the typical jobs and study abroad, one can see that being bilingual, especially with English and Spanish is a very marketable resource. By observing the population at large in the United States, one can see that "Caucasian" is not the only ethnic background being represented. In fact, "the United States is the fourth largest Spanish-speaking country in the world" (Olivares). In the past twenty years there has been an increase in the number of Spanish speakers needed in the US. "In 2000, 32.8 million Latinos resided in the United States, representing 12.0 percent of the total U.S. population" (Therrien et al.). As the Hispanic population grows we need to do our part by learning the second language of the US. By taking a look at journals and newspapers, one can see that Spanish is slowly and surely working its way in as a part of the culture. Companies are trying to foster an interest in Spanish among the native English speakers and to communicate to those Spanish-speakers who can’t understand English. The companies are evaluating the language situation of the population at large to decide how to go about speaki ng to everyone. For instance, the most recent ""Got Milk" advertisement features Marc Anthony, a Latin singer and artist. He has gained popularity not only in the Latin Market, but popularity here as well, after having released one of his discs in English.

Antigone :: essays research papers

The debate over who is the tragic hero in Antigone continue on to this day. The belief that Antigone is the hero is a strong one. There are many critics who believe, however, that Creon, the Ruler of Thebes, is the true protagonist. I have made my own judgments also, based on what I have researched of this work by Sophocles. Antigone is widely thought of as the tragic hero of the play bearing her name. She would seem to fit the part in light of the fact that she dies in doing what is right. She buries her brother without worrying what might happen to her. She "Takes into consideration death and the reality that may be beyond death" (Hathorn 59). Those who do believe that Antigone was meant to be the true tragic hero argue against others who believe that Creon deserves that honor. They say that the Gods were against Creon, and that he did not truly love his country. "His patriotism is to narrow and negative and his conception of justice is too exclusive... to be dignified by the name of love for the state" (Hathorn 59). These arguments, and many others, make many people believe the Antigone is the rightful protagonist. Many critics argue that Creon is the tragic hero of Antigone. They say that his noble quality is his caring for Antigone and Ismene when thier father was persecuted. Those who stand behind Creon also argue that Antigone never had a true epiphany, a key element in being a tragic hero. Creon, on the other hand, realized his mistake when Teiresias made his prophecy. He is forced to live, knowing that three people are dead because of his ignorance, which is a punishment worse than death. My opinion on this debate is that Antigone is the tragic hero. She tries to help her brother without worrying about what will happen to her. She says, "I intend to give my brother burial. I'll be glad to die in the attempt, -if it's a crime, then it's a crime that God commands" (Sophocles 4). She was also punished for doing what was right. Her epiphany came, hidden from the audience, before she hung herself. Creon's "nobleness" of taking in young Antigone and Ismene is overshadowed by his egotistical nature. He will not allow justice to come about simply because he wants to protect his image. He says, "If she gets away with this behavior, call me a woman and call her a man" (Sophocles 13). These elements prove that Antigone is the tragic hero. Creon, understanding his ignorance may lead one to believe that he

Individual Behavior Essay

Individual behavior differs from person to person and most differences are based on the background of the individual. Some elements that can affect ones background to influence their individual behavior can include religion, age, occupation, values and attitude differences, gender, and even ethnicity. These individual behaviors can cause people to act differently to situations and can create friction or even chemistry in the work place. The age of a person can be a large factor in the way they behave. There are studies that prove maturity can come at different ages but in most cases maturity is something that is learned and grown into. Age in a work place can work against someone or for them. A young age can be a downfall if there is lack of maturity and experience and old age can be a downfall due to lack of energy or knowledge of new technologies. With that being said I think that it is important that age should not be the deciding factor as to how someone will act. There are many young people who have the maturity to carry many responsibilities and show good individual behavior. Some older individuals have adapted their behavior to fit more suitable into the technologies that have developed over the past few years. More and more people are on Facebook (www. facebook. com) than ever, and it is common to see individuals of all ages on the popular website. You can also find with age individuals depending on their age will have their priorities in different orders. The occupation of a person can also attribute to their individual behavior. For example say there is an individual who works in the public eye like a Senator or Congressman, they are going to be more careful for the things that they say and do because they will not wish the media to catch wind and bring them in a negative media down pour about the situation. When you work in the lime light you have to be cautious about your wording and your actions. There are many occupations that are not in the public eye that also has to think about their individual behavior and make sure that they set a good example because of their occupation. Take a teacher for example it is very important that they do not act in an bad individual behavior because it can have an affect on their job. For instant it would be bad to post pictures of yourself drunk to a popular social networking sight if you are a teacher because you are to be a role model and that is individual behavior that you should not wish your students to witness. Many professionals will maintain their professional behavior when they are dealing with their work and with their lives. Professional behavior usually consists of being calm and thinking your actions and words through before acting upon them. Many professionals also like to make educated guesses instead of sporadic leaps into new things. Many individuals will learn their professionalism from their occupation and it is something that they can carry over into their individual behavior. Religion is a set of beliefs concerning the cause, nature, and purpose of life and the universe, especially when considered as the creation of a supernatural agency,[1] or human beings’ relation to that which they regard as holy, sacred, spiritual, or divine. [2] Many religions have narratives, symbols, traditions and sacred histories that are intended to give meaning to life. They tend to derive morality, ethics, religious laws or a preferred lifestyle from their ideas about the cosmos and human nature (www. wikipedia. com). That definition alone can should one how religion could influence someone’s individual behavior. Unlike the other elements religion is something, for the most part, that can be chosen by the individual. A person can be brought up with religious beliefs, can adapt to the beliefs, and can even change their religious beliefs. A religion can have strict guidelines as to how their followers should behave some may even have diets or wardrobe requirements that can affect their individual behavior. Values can run hand in hand with religion on some basis. Many religions have a foundation on values and morals that their followers should abide by. When a situation occurs and a decision needs to be made you can understand a lot about a person by their individual behavior. It is usually the person’s values or morals that help them make the decision on what action to take when the situation presented itself. Attitudes about differences can affect ones individual behavior. Someone who is high strung can tend to have a little more dramatic attitudes about differences opposed to a laidback individual who has a peaceful nature and can tend to look at differences with a positive. When attitudes turn negative ones individual behavior can become defenseful, frightful, or even protective. In conclusion there are many parts that tie together to create an individual behavior and those behaviors can be influenced by many different elements. Although many individuals can have common elements in their background it is hard to find an individual behavior that is the exact same. Individual behavior can show a lot about the way a person was brought up, their beliefs, age, and even gender. It can show their religious beliefs or just their attitude but it is certain that one’s individual behavior is something that the individual chooses for their self. It is a way they like to act regarding to a situation.

Juvenile Corrections Essay

Juvenile corrections encompasses the portions of the criminal justice system that deal with juvenile offenders. Many of these facilities and programs seem to mirror jails and prisons, but juvenile corrections are not meant for long term sentences. Sometimes sentences for juveniles are only several weeks long. Juvenile corrections also have a strong focus on rehabilitation because studies have shown that juvenile offenders are more prone to rehabilitation than adult offenders. These programs and services were aimed to help to teach these youthful offenders how to better deal with situations and how to avoid entering the into the criminal justice system again. (wisegeek) The judges who handle these juvenile cases specialize in working with juvenile offenders and their crimes. Others who specialize in juvenile crime are a part of the juvenile corrections system as well. This includes social workers, probation officers, as well as others. Their aim is usually not to punish the juveniles alone, but to use the punishment as a way to rehabilitate them as well. (USLegal) Historical Background of Juvenile Corrections The origins of juvenile corrections are not entirely clear. Juvenile and adult offenders have been treated differently for some time, but what ages are considered to be juvenile has changed over time. The United States’ perspective on juvenile ages and law was greatly influenced by English law. In the 1700s, William Blackstone, an English lawyer, published his Commentaries on the Laws of England, where he identified that young persons are incapable of committing crime. Generally, anyone under of the age of seven was incapable of committing crime. Any child over the age of 14 was able to be tried as an adult. Children between the ages of 7 and 14 are a gray area, but were generally not held accountable for their actions unless it could be shown that they knew what was right or wrong. Punishments for being found guilty of crime included the death penalty, even for juvenile offenders. (ABA, 2011) The juvenile corrections system began to change and be reformed in the nineteenth century. â€Å"Social reformers began to create special facilities to rehabilitate troubled juveniles, especially in large cities†, (ABA, 2011, p 5). These reformers stated that they wanted to protect these juvenile offenders by keeping them separate from the adult populations because they were better able to be rehabilitated. The first court system for juveniles in the United States started in 1899 in Illinois. These courts also aimed to rehabilitate the juvenile offenders. They had juvenile court systems in most states by 1824. The courts became the â€Å"guardians† of the juvenile offenders, or their â€Å"parens patriae†. These court proceedings were considered to be civil matters and not considered to be criminal matters. Their basic focus was on rehabilitating the juvenile offenders. (ABA, 2011) The juvenile courts changed again in the 1960s and 1970s. In 1967, the case of Gerald in In re Gault, the Supreme Court granted many juveniles some, but not all, due process rights in the course of their court proceedings. This included the right to be notified of their pending charges, the right to have an attorney, the right to protect themselves against self-incrimination, and the rights to confront and cross-examine their witnesses. Three years later, in In re Winship, the Court also established that the accused must be proven guilty â€Å"beyond a reasonable doubt†. In 1971, in McKeiver v. Pennsylvania, the Courts ruled that juries are not required for juvenile proceedings. In most cases, the judge in charge of the juvenile corrections department will hear the case, judge the offender, and sentence the offender. (ABA, 2011) Recidivism Rates in Juvenile Corrections When it comes to measuring a correctional agency’s facilities and programs, recidivism rates are most frequently used. These rates guide spending and funding decisions aimed to effectively combat crime. While there is no standard rate that is aimed for, the idea is to try to reduce the recidivism rate or even keep it the same opposed to raising it. When the recidivism rates are not progressing in the manner expected, these agencies must try to find other avenues and strategies that will make a positive impact on the recidivism rates, and in the long run, these juvenile’s lives. (CJCA, 2011) â€Å"The Indiana Department of Correction (IDOC) defines recidivism as a return to incarceration within three years of the offender’s date of release from a state correctional institution.† (Schelle, 2012) The 2011 recidivism rate for all juvenile offenders was 36.7%. The recidivism rate for African American juvenile offenders was 43.8%. Eighty-two percent of the juveniles who recidivated did so with a new crime, and the other 18% returned because of technical violations. â€Å"Of all juveniles released in 2008, 40.9% of males returned to IDOC, while only 15.8% of females returned,† (Schelle, 2012). Surprisingly, juvenile sex offenders had the lowest recidivism rate at 13.6%. (Schelle, 2012) Risk-Focused Juvenile Crime Prevention Risk factors for juvenile delinquency have been identified from multiple studies. These risk factors are different for older and younger juveniles. When focusing on the individual juvenile between the ages of 6-11, delinquency risk factors include; being male, having a low IQ, having antisocial attitudes and beliefs, dishonesty, having medical and physical problems, hyperactivity, exposure to television violence, petty offenses, having poor attitude and performance at school, and substance use. In this same age group, the child’s family environment can also include risk factors as well. Some of these risk factors are; being in a low socioeconomic status or poverty, having antisocial parents, having poor relationships, receiving harsh or inconsistent discipline, having a broken home, being separated from their parents, and having abusive or neglectful parents. (Przybylski, 2008) For children between the ages of 12 and 14, the individual risk factors include; general offenses, having a low IQ, displaying antisocial behavior, committing crimes against others, using physical violence, being male, displaying risk taking behaviors, displaying aggression, having low concentration, restlessness, and general offenses. Other factors also include having a poor attitude in school, academic failure, having weak social ties, and gang membership. Living in a community with high neighborhood crime, drugs, and disorganization are also factors. In this same age group, the child’s family environment can also include risk factors as well. Some of these risk factors are; lax or harsh discipline by parents, lack of adult or parental supervision, lack of parental involvement, having antisocial parents, having poor relationships, coming from a broken home, living in poverty, being abused, and experiencing family conflict. With all of these risk factors being mentioned, â€Å"It is important to recognize that risk factors cannot be used to identify which particular children will grow up to be offenders,† (Przybylski, 2008, p 84). There are also protective factors that may help counter-act the risk factors mentioned above. These include the individual juvenile; having a strong attitude or being intolerant toward deviance, having a higher IQ, being female, having more positive social skills and orientation, and understanding the sanctions for any transgressions. Some familial protective factors include; having warm, strong, and supporting relationships with caregivers, good monitoring by parents, and the general support of the juvenile’s friends by the juvenile’s parents. Other protective factors include; the juvenile being committed to their education, gaining recognition for extracurricular activities, and having friends who are also against deviant behavior. (Przybylski, 2008) What Rehabilitation Efforts Work for Juveniles and Which Do Not There has been much research on what programs work to rehabilitate juvenile offenders. The general results have been that the majority of the programs have no real effect on the juvenile recidivism rate aside from a few exceptions. The reason why juveniles have lower recidivism rates is believed to be because juveniles are not completely aware of the ramifications of their actions and do not always understand the true damage they inflict on their victims. (Lieb, 1994) The results of multiple studies indicate several approaches to rehabilitation that do not work. Those include; visiting a probation officer one time per month, diagnostic assessments, behavior modification for any complex behaviors, broad discussion groups, attending school as a single approach, field trips, work programs, psychodynamic counseling, and therapeutic camping trips. The research used 50 different juvenile correctional programs and came to the conclusion that the results were, â€Å"far from encouraging,† and â€Å"correctional treatment has little effect on recidivism,† (Lieb, 1994, p 5). The results showed that some behavioral approaches received more positive results. An analysis used 90 residential and community programs for juvenile offenders. The analysis concluded that, â€Å"Behavior approaches had the most success in reducing recidivism although the effects were so small that â€Å"they could not reject the null hypothesis.† Group therapy and transactional analysis programs were more likely to produce negative effects,† (Lieb, 1994, p 5). What does seem to work is using correctional treatment and service utilizing three principles that include; getting service to the high-risk juveniles, paying attention to the risk factors mentioned above, and using different styles of treatment depending on the needs and learning styles of the individual juvenile offender. (Lieb, 1994) References ABA. (2011, June 29). The History of Juvenile Justice. Retrieved November 29, 2012, from American Bar Association: http://www.americanbar.org/content/dam/aba/migrated/publiced/features/DYJpart1.authcheckdam.pdf CJCA. (2011). Recidivism Committee. Retrieved December 2, 2012, from Council of Juvenile Correctional Administrators: http://cjca.net/index.php/initiatives/recidivism-committee Lieb, R. (1994). Juvenile Offenders: What Works? ; A Summary of Research Findings. The Evergreen State College. Olympia: Washington State Institute for Public Policy. Przybylski, R. (2008). What Works; Effective Recidivism Reduction and Risk-Focused Prevention Programs. Denver: RKC Group. Schelle, S. (2012). Juvenile Recidivism 2011. Indianapolis: Indiana Department of Correction. USLegal. (n.d.). Juvenile Corrections Law & Legal Definition. Retrieved November 22, 2012, from USLegal.com: http://definitions.uslegal.com/j/juvenile-corrections/ wisegeek. (n.d.). What is Juvenile Corrections? Retrieved November 22, 2012, from wisegeek.com: http://www.wisegeek.com/what-is-juvenile-corrections.htm