from factors such as urban, rural and tribal residence, ethnicity and socio economic levels of the family. Lifestyle of urban adolescents from upper SES is quite different from that of middleclass and lower-class adolescents. Former have access to private, good quality education and are influenced by western ways of life style through travel and exposure; their preferences for music, clothes and interaction with opposite sex are very close to the western counter parts. On the surface there does not appear to be any gender discrimination in the families of these adolescents but covertly they do exist. Pursuing educational endeavors is encouraged both in upper and middle urban class. Urban Adolescents from lower class have to struggle for survival and grow in impoverished, disadvantaged environment making them vulnerable to several risks. Malnutrition, risk of poor health, becoming victims of antisocial activities, brewing and sale of illicit liquor, sex exploitation, prostitution and drug peddling were reported threats for adolescents from slums in a multi indicator survey (Khosla 1997).The picture of rural adolescents is different; the disparity between boys and girls is even greater among them. Less emphasis on formal education makes boys and girls participate in adult activities at home and outside at an early age. The boys are expected to join men in work to earn their living, may it be on a farm or a factory or a traditional craft at home. The routine of a Pre-adolescent/adolescent rural girl is demanding-cleaning the house, cooking, washing, fetching water, bathing younger siblings. Rural girls rarely pursue education beyond primary school level. Early marriage as a trend is common even now, both for boys and girls in rural India.
Bayesian bootstrapping (Analysis 3) overcomes the drawbacks of the other three techniques, using all of the data, analysing patients as-randomised and avoiding bias by taking account of interactions. This approach assumes that the evidence collected in patients randomised to one comparison is applicable to patients randomised to > 1 comparison, although in principle it would be possible to down-weight the evidence from the former group. In par- ticular, evidence from patients randomised only in compari- son A (for whom treatment B was not randomly allocated) is used to vet the bootstraps before we estimate outcomes for comparison B, although outcomes are always analysed as-randomised. This is similar to using external evidence from an A-versus-no-A trial alongside a factorial trial on A and B. It may therefore be prudent to present a sensitivity analysis using inside-the-table or at-the-margins analysis alongside Bayesian bootstrapping — especially for regula- tory submissions. Bayesian methods also enable interactions to be down-weighted using sceptical priors [27, 28], providing a compromise between including or exclud- ing interaction terms. Rejection sampling is a useful way to implement the Bayesian bootstrap for economic evaluations, since it facilitates estimation of CEACs. How- ever, importance sampling [18, 25], whereby a weighted average is calculated across the bootstraps rather than rejecting a proportion of bootstraps, may be more con- venient and computationally faster when analysing clinical endpoints from partial factorial trials.
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However, Dr. Arosanyin, the National Technical Adviser, All Farmers Association (AFAN) underscored the need for increased investments in the agricultural sector, saying that Nigeria was facing several Economic challenges which included growth decline, decline in oil prices and over dependence on imports. He said that the other challenges were poor infrastructural facilities such as electricity, roads and water which inhibited Secondary Production and Industrial growth as well as corruption and insecurity. He stressed the wisdom in addressing the challenges pragmatically, insisting that at the moment, Nigeria ought not to be imparting products like textiles, biscuit, fruit juice, rice and sugar. Arosanyin in 2015 added that considering the vast agricultural potential of the country, it should be able to produce these products amongst others locally.
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Analysis of causes of cardiovascular disease on age groups in table 2 has shown that in age group <30 year, 50% male and 94.1% female patients are suffering from high blood pressure. While in age group 30-50 year, 91.4% male and 91.9% female patients
There is a certain continuity in the direction of migration flows, even though some minor changes occur in them. The economic opportunities of the receiving country play a decisive role, although the historical, ethnic, recipient country and donor countries, and geographical links, also have an impact on that. The distinctive feature of our time is the significant changes that have occurred in the areas of immigration.
The Total Frequency Rate of accidents could be influenced by a country’s industrial structure, so as the sectoral growth rate. The standardization of industrial structures into NACE divisions or sub-divisions ( and not only on an aggregate activity level), has proved very useful as an integral part of the statistical infrastructure used within the European statistical system for producing comparable statistics. Moreover, thanks to its relation to the International Standard Industrial Classification of all Economic Activities this framework is also an important tool for comparing statistical data on economic activities at an international level.
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It is essential to identify the socio-economic and demo- graphic risk factors associated with the prevalence of mal- aria using data obtained from the rapid diagnosis test. Such a study of the identification of the socio-economic and demographic risk factors is helpful in identifying house- holds who have a critical need for intervention. In previous studies, Ayele, Zewotir and Mwambi (2012) have concluded that malaria problem in Amahara, Oromiya and SNNP regions of Ethiopia are associated with key socio-economic, demographic and geographic factors, in particular it was noted that poverty levels of households are highly associ- ated with the risk of malaria. Nevertheless the spatial distri- bution of malaria was not considered or investigated . Though identification of the household characteristics is essential for grass root level intervention, the government goals and targets are focused on achieving malaria eradication/reduction within specific geographical areas. Such studies are limited, and hence the conception of this study. Therefore, the objective of this study is to undertake a statistical analysis of malaria incidence. This will identify important socio-economic, demographic and geographic variables associated with the disease and ultimately a prevalence map of the area illustrating variations in malaria risk.
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Going from the area of information production to that of information use, the issue of correct or wrong, moral or immoral still remains of importance. A large part of the information content used in the decisional process is given by the receiver, i.e. the information user. The information does not consist only of the data and the indicators obtained from the statistical analysis, but also of the the specificity given by the user’s professional, economic, social, and scientific context. We speak of transinformation, as a factor reducing enthopy (4). From a theoretical perspective, transinformation is defined as the information about the emitter contained in the receiver field, or as a correspondence between the emitted and the received message. How much of what information users know is statistical information? Using example no 2 from point 2, the question which arises is: which of the five indicators is useful in decision making and best answers the need for information?
Therefore, efforts have been make to determine the expenditure of different crops in the selected sample villages for understanding the efficient use of agricultural input - output relation. There is a great need to study the cropping pattern, crop combination and size of holding in agricultural geography to measure the socio-economic status of the farmers in agro- economic of the district (Department of economic and statistical analysis, Haryana, 2010). Study area
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Various techniques are in use for conducting the co-integration analysis such as: the maximum likelihood-based approach that was proposed by Johansen and Julius (1990) and Johansen (1992), Engle and Granger (1987). Both approaches necessitate that the variables must share the order of integration. It is usually this necessity that makes it difficult for the researchers in cases where the system includes variables with diverse orders of integration. A new approach was suggested by Pesaran et al. (1996, 2001) to overcome this problem. This new approach, the Autoregressive Distributed Lag (ARDL) is used for co-integration test and it does not need the classification of variables into I (0) or I (1) 1 . The approach is also applicable for studies that use a moderately small-sized sample, as seen in the current study. The small model characteristics of the approach of the Autoregressive Distributed Lag (ARDL) are better and more sophisticated than the Johansen and Juselius (1990) co-integration technique as Pesaran & Shin demonstrated (1999). This method is also found to be highly advantageous due to the fact that it can guarantee an estimation even in the case of endogenous explanatory variables. Moreover, this method assures long and short-term parameters’ estimation for variables under the same framework. For these advantages, Autoregressive Distributed Lag (ARDL) approach has gained popularity over recent years, and it is conducted as follows:
Roefie Hueting (1929), recently turned 79 years of age, has been working on the subject of economics and the environment since around 1965. Seminal results are his notion of environmental functions (WWF, 1969), his Ph.D. thesis “New Scarcity and Economic Growth. More welfare through less production ?” (1974), the definition of (environmentally) sustainable national income (eSNI, UNEP/World Bank 1989), the eSNI methodology (CBS Statistics Netherlands 1992) and his contributions to the 1999 Hueting Congress (presentation and rejoinders, 2001bc). The figure of national income NI gives production while the figure of eSNI gives the production level that maintains the availability for future generations of the vital environmental functions. For many economists, the current focus is on climate change but the ecological challenge is much wider and more fundamental, see also the Convention on Biological Diversity, Bonn 2008. The figure for eSNI still isn’t included in the system of national accounts (SNA) which means that current statistical reporting on national income and economic growth provides incomplete information to policy makers and the general public. With the dictum “What you measure is what you get”, we currently get “economic growth” that works against sustainability. This review provides a reflection on advance and adversity in 40 years of Hueting’s research in a world that only slowly recognizes the global environmental problem. How do governments decide under risk, how do they grow aware of that very risk, what is the role of the national statistical offices in providing information on that risk, especially when that risk concerns survival for large sections of the planet ? The reflection provides insights that themselves are useful for our understanding of the political economy of research on issues that are politically sensitive.
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The determinants of the long term growth performance of the Philippine economy have been the subject of considerable empirical research. Studies include, for example, Lampman (1967), Hooley (1968), Williamson (1969) and Sanchez (1983). While these studies covered different periods, they particularly addressed the 1950s through to the 1970s. They followed the Denison-Solow tradition of using a neoclassical production function to account for the sources of growth. Capital, labor and technology therefore played a significant role in explaining growth. Likewise, the estimation procedure used was non-parametric where assumed factor shares in total output were used as elasticities in decomposing the sources of the country's economic growth. Patalinghug (1984) extended the approach by including education as another factor contributing to growth. The common finding of these studies was that, for the economy as a whole, average productivity growth in the Philippines has been declining and even negative at various periods.
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At a first glance it seems that in this toy model there is no room for recessions, crisis, economic booms and alike. However, the total amount of money, which reflects the sum of all the transactions between the nodes, is not conserved, and therefore it may be changed due to psychological reasons like fear, optimism or even long period of prosperity that is expected to end. When the total amount of transactions reduces, there is an economic recession, and when it increases there is an economic growth.
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The works of McKinnon (1973) and Shaw (1973) highlighted the adverse effects of “financial repression” on economic development. The theory of financial liberalization advocates the freeing up of financial markets to reverse the detrimental effects of financial repression. Financial repression is a regime consisting of the imposition of interest-rate ceilings, directed credit allocation policies, high reserve requirements, foreign exchange regulations, and heavy taxation of the financial sector. McKinnon (1973) and Shaw (1973) both argue that financial repression exerts a negative effect on saving, investment and the rate of economic growth. McKinnon’s model stipulates that the higher the real rate of interest, the more willing the investor to accumulate real money balances before investing, while Shaw argues that the accumulation of financial capital is caused by higher real interest, mainly through an increase in the extent of financial intermediation. Both models argue that the removal of ceilings on deposits results in positive real interest rates, which increases saving, that is, the availability of funds for investment.
Third, both local economic development and public sector investment are associated with hospital bed density, albeit with different strength. This finding reflects struc- tural features of China’s mixed public-private healthcare financing arrangements. In particular, the fact that local economic development was the more powerful factor in our model - a 10 % increase in local savings per capita yielded a 2.32 % increase in hospital bed density - arguably points to the ongoing influence of out-of-pocket spending, especially in hospitals, which belong to higher tiers of the healthcare system, and thus have correspondingly higher expenses that are only partially covered by typical insur- ance plans . Nevertheless, local government revenue, which partially derives from central government transfers , was an independent factor in our model, and thus also plays an important role in resource allocation. Since the launch of the latest round of healthcare reform in 2009, the Chinese government has increased investment in public hospitals, while encouraging the establishment of private hospitals. Although private investment has un- doubtedly led to an overall increase in health resource funding, it has done little to address geographical dispar- ities. Limited government resources would therefore be most effectively employed in disadvantaged counties, for example, through the intensification of special-purpose grants from the central government to economically under-developed areas. The government could also con- sider introducing policies to attract investment to such regions.
Table 1: Modeled Relatively Weak Effect Predicted Class Actual Class Class 0 Class 1 Class 0 62 38 Class 1 38 62 In the simulation, optimal solutions having 2-, 3-, 4-, and 5-strata were modeled, because most globally optimal models 12 involve five or fewer sample strata. 11 These strata correspond to 1-, 2-, 3-, and 4- comparisons per experiment. Statistical power for the 2-strata model was evaluated for one test of a statistical hypothesis, having an associated p<0.05. For higher-dimensional solutions, Sidak-type 5,6 adjustments were made for multiple compari- sons (C) to maintain an experimentwise Type I error rate of p<0.05, where adjusted alpha = 1- (1-alpha) 1/C . Statistical power for the 3-strata model (which involved two tests of statistical hypotheses) was thus computed for p<0.0254; for the 4-strata model (involving three tests of statistical hypotheses) was computed for p< 0.0170; and for the 5-strata model (involving four tests of statistical hypotheses) was com- puted for p<0.0128.
Therefore, in order to find out the convergent validity of Affective disturbance and distress scale, a Principal Component Analysis technique was used, with Varimax Rotation and extraction done on Eigen values greater than 01. The Kaiser-Meyer-Olkin test of measure of sample adequacy was also computed, as recommended up to value of 0.60, indicating that data will be suitable for the Principal Component Analysis (Kaiser, 1974). Moreover, the factors loadings equal to 0.50 or greater than were considered to be significant. Principal component analysis was performed on 25 items. Inspection of correlation matrix revealed the presence of many coefficients 0.3 and above. The Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) was 0.71 which exceeded the recommended value of 0.6 (Kaiser, 1974), indicating that the present data was suitable for principal component analysis. Similarly, since the Bartlett’s test was significant (p<0.000), this signifies that there was sufficient correlation between variables to proceed with the analysis. The communalities for each of the 25 items ranged from .71 to 84 with factor loading 84 to 91. Such results suggest sufficient evidence of convergent validity for the Affective disturbance and distress scale (Harrel & Myer, 1984). The KMO, communalities, percentage of variance and item loading for each subscale are shown in Table 1.5.
a unit root test. In this study, we employed the Augmented Dickey-Fuller test for data verification. As shown in Table 1, all the variables selected for our analysis (except the index of diversification and inflation) are found non-stationary at level, but become stationary on first difference at the 1percent level. By this, with the exception of the index of diversification and inflation, all the other variables are I(1) and hence areassumed endogenous in the VAR specification. The index of diversification and inflation are however found stationary at level, the former being significant at the 5percent level and the latter at the 1percent level. Lag Order Selection and Test of Co-integration In selecting the appropriate lag order to use for the test of co- integration and in the respective long- and short-run specifications, the Akaike information criterion (AIC), the Schwarz criterion (SC) and the Hannan-Quinn criterion (HC) have been used extensively in literature as the primary criteria, with the sequential modified LR test statistic (each test at 5percent level) and the final prediction error being used as secondary criteria for check/control. In this study however, both the primary criteria and the secondary criteria selected lag order one. Accordingly, we select lag order one for the test of co-integration and for the VAR specification or VECM (should co-integration be confirmed). Similarly, assuming a linear deterministic trend (intercept in both normalized and short–run equations) in data, the trace test confirmed the existence of one co-integrating equation at the 5 percent level. Accordingly, the VECM specification as expressed in equation (3) is deemed the most appropriate equation for this study. Output for the respective long- and short-run equations are presented and discussed
Since 1980, total per capita GDP has decreased in sub-Saharan Africa at nearly 1 percent per year (Ibid: p. 5). The decrease has been prevalent: 32 countries became poorer than in 1980. Collier and Gunning report that today, Sub-Saharan Africa is the lowest-income region in the world. According to the statistics of growth measurements drawn from a snapshot offered by Collier and Gunning in 32 African countries, it is clear that Africa has suffered a chronic failure of economic growth. What are therefore the underlying issues confronting the debate of Africa’s persistent marginalization in the global market? It is against this backdrop that the Bretton Woods institutions argue that Africa’s stagnation was basically caused by poor policies, and the other, concomitant with the work of Geoffrey Kay contradicts that the formation of the world market was similarly the route to destruction and asymmetric development. The debate on the causes of Africa’s marginalization and slow growth has offered many different explanations apart from the two already mentioned.
current approaches to intrusion detection. Artificial neural networks have been proposed as alternatives to the statistical analysis component of anomaly detection systems. Statistical Analysis involves statistical comparison of current events to a predetermined set of baseline criteria. The technique is most often employed in the detection of deviations from typical behavior and determination of the similarly of events to those which are indicative of an attack. Neural networks were specifically proposed to identify the typical characteristics of system users and identify statistically significant variations from the user's established behavior.