Individuals On Games Empowering Violent Behaviors

This paper is going to show individuals on games empowering violent behaviors. Each time playing is happening your mind begins building up a considerable measure all the more in an unexpected way. Playing these games make individuals more aggressive. Regardless of a child s belief that these games are nothing they truly do lead to a change in a persons mind. Individuals additionally may get addicted on the gaming which leads to a man trying to be aggressive more frequently. A clear understanding on the ESRB rating in which stands for entertainment software rating board is critical. Folks should be included in some way or another in the decisions they are allowing their children’s play. A few children wont escape from their room because†¦show more content†¦More methods for playing violent games are made every year. Being so excessive in playing video games can have numerous consequences for teenagers. They need to start limiting their gameplay which may have various beneficial outcomes. Some of the consequences players can have from playing a lot of violent videos games is having poor social skills. Video games require no physical movement and a great chunk of people eat while playing this kind of games for days. These games restrict the teenager’s mind into playing more the games. This causes them to get away and forget about their actual social life outside of it. Also it gives them more problem of actually talking and interacting in everyday basis. They have no interest to make friends because they are in the gaming world trying to beat the new level or conquering a new island. Gaming system now have Wifi capability which lets the gamers have outside experiences with other people with the game. It helps them interact and play against one another. This is enough for them to feel comfortable with them and actually think they are actual real life friends. They just talk thought a headset that is it no real life connection. Individuals d on t see them as who they truly are they seem them in the body of the player. They only speak through a headset. People do not view them as who they really are they view them as their players identity in the

The Impact Of Firm Level Characteristics - Free Essay Example

Sample details Pages: 7 Words: 1964 Downloads: 8 Date added: 2017/06/26 Category Statistics Essay Did you like this example? Abstract Organizational performance has attracted scholarly attention in corporate finance literature over the several decades. However, in the context of insurance sector, it has received a little attention. Current study examines the impact of firm level characteristics (size, leverage, tangibility, risk, growth, liquidity and age) on performance of listed life insurance companies of Pakistan over seven years from 2001 to 2007. Don’t waste time! Our writers will create an original "The Impact Of Firm Level Characteristics" essay for you Create order The results of Ordinary Least Square (OLS) regression analysis indicate that size, risk and leverage are important determinants of performance of life insurance companies of Pakistan while ROA has statistically insignificant relationship with growth, profitability, age and liquidity. Keywords: performance, firm level characteristics, life insurance companies. Introduction The performance of any firm not only plays the role to increase the market value of that specific firm but also leads towards the growth of the whole industry which ultimately leads towards the overall prosperity of the economy. Measuring the performance of insurers has gained the importance in the corporate finance literature because as intermediaries , these companies are not only providing the mechanism of risk transfer but also helps to channelizing the funds in an appropriate way to support the business activities in the economy . Insurance companies have importance both for businesses and individuals as they indemnify the losses and put them in the same positions as they were before the occurrence of the loss. In addition, insurers provide economic and social benefits in the society i.e. prevention of losses, reduction in anxiousness, fear and increasing employment. Therefore, the current business world without insurance companies is unsustainable because risky businesses have not a capacity to retain all types of risk in current extremely uncertain environment. For the past six decades, Pakistani life insurance companies have shown the impressive progress which not only creates the employment opportunities but also enhances the business activities in the economy. Financial statistics reported the phenomenal growth of Pakistani life insurance companies as these companies comprise 52% and 69% share of entire (life plus non-life) insurance market in terms of net premiums and assets (Insurance Year Book, 2007). In addition, the premium of these life insurers increased by 36% in 2007 (Insurance Year Book, 2007) shows the remarkable progress of life insurance sector of Pakistan. Therefore, what determines the performance of the life insurance industry is an important discussion for the regulators and policy makers to support the sector in achieving the excellence so that desirable economic fruits could be reaped from the help of the life insurance sector of Pakistan. Literature Review The Determinants of performance have been extensively studied in corporate finance literature from the last several decades. For instance; by selecting the sample of US banks, Berger (1995) investigated the impact of capital asset ratio on return on equity. He concluded that capital asset ratio has a positive relationship with profitability. Anghazo (1997) examined the impact of firm level characteristics on US bank net interest margin. The results documented that bank interest margin positively related with leverage, opportunity cost, and default risk and management efficiency. Neeley and Wheelock (1997) explored the determinants of profitability of commercial banks and find that profitability positively related with changes in per capita income. To investigate the performance of banks (Naceur Goaied, 2001)used the sample of Tunisian banks over the period of 1980 to 1995. They advocated that the banks who tried to maintain their high deposits and improve their capital and labor productivity are performed well. Guru et al. (2002) examined the determinants of performance of Malaysian banks over the 10 years period from 1986 to 1995. For this purpose, they selected both micro and macro level characteristics. The results revealed that inflation positively while efficient expense management and high interest rate negatively related with profitability. The results of Goddard et al. (2004) showed that Profit is an important prerequisite for future growth of banks and the banks that maintain a high capital assets ratio tend to grow slowly. A study conducted by the (Sufian Parman, 2009)to investigate the determinants of profitability by selecting the non-commercial banks financial institutions. The findings indicated that credit risk and loan intensity negatively related with profitability while large size and financial institutions with high operational expenses tended to high profitability ratio. (Hakim Neaime, 2005) Observed that liquidity, current capital and investment are the important determinants of banks profitability. (Aburime, 2006) Identified the firm level determinants of profitability of Nigerian banks over the five years period from 2000 to 2004. He concluded that credit portfolio, size, capital size and ownership concentration are important determinants of Nigerian banks. (Kosmidou, 2008) showed that money supply growth has insignificant impact on profitability while GDP and stock market capitalization to assets are significant and have negative relation with the ROA. (Asimakopoulos, Samitas, Papadogo nas, 2009) illustrated that Firms profitability is positively affected by size, sales growth and investment. On the other hand, leverage and current assets negatively related with profitability. Severeral studies also have been conducted to measure the performance of the insurance compnies. For instance; Sloan, A and Conover, J.(1998) deduced that functional status of insurers do not affect the profitability of being insured but public coverage have significant impact on profitability of insurance companies. Chen and Wong ( 2004) examined that size, investment, liquidity are the important determinants of financial health of insurance companies. Chen et al.( 2009) examined the determinants of profitability and the results showed that profitability of insurance companies decreased with the increase in equity ratio. In addition, insurance companies must have to diversify their investment and use effective hedging techniques which help them to create better financial revenues. Research Methodology Sample and Data Currently, there are five life insurance companies operating in Pakistan and all these five companies are selected to measuring their performance over the period of seven years from 2001 to 2007. For this purpose, financial data has been collected from financial statements (Balance Sheets and Profit and Loss a/c) of insurance companies and à ¢Ã¢â€š ¬Ã…“Insurance Year Bookà ¢Ã¢â€š ¬? which is published by Insurance Association of Pakistan. Model PR = ÃŽÂ ²0 + ÃŽÂ ²1 (LG) + ÃŽÂ ²2 (TA) + ÃŽÂ ²3 (SZ) + ÃŽÂ ²4 (LQ) + ÃŽÂ ²5 (AG) + ÃŽÂ ²6 (RK) + ÃŽÂ ²7 (GR) + ÃŽÂ µ Where: PR = Performance (Net income before interest and tax divided by total assets) LG = Leverage (Total debts divided by total assets) TA = Tangibility (Fixed assets divided by total assets) SZ = Size (Log of premiums) LQ = Liquidity (Current assets divided by current liabilities) AG = Age (Difference b/w observation year and establishment year) RK = Risk (standard deviation of ratio of total claims to total premiums) GR = Growth (Percentage change in premiums) ÃŽÂ µ = the error term Descriptive Statistics Table 4.1 presents descriptive analysis of the firm level characteristic associated with life insurance sector. This study considers performance as dependent variable whereas leverage, size, growth, tangibility, liquidity, age and risk as independent variables. The industry average is provided by mean along with are the minima and maxima for respective year while standard deviation indicates the inter-industry variation of the variables value within the respective year. Table 4.1 indicates that the minimum value of industry mean of leverage is 0.79 in 2004 and 2007 while the mean value is at its maximum level in 2006 at 0.84.The maximum variation in leverage is observed in 2007 valuing at 0.30 and minimum is found in 2003 at 0.19. The variable size constantly shows the increasing trend from year 2001 to 2007. The mean value of size is at maximum level in 2007 i.e. 7.51 whereas minimum mean value for size is observed at 6.02 in 2001. In addition, the inter industry variation is minimum in 2001 at 2.12. Table 4.1 also shows that growth of Pakistani life insurance companies is not consistent in all seven years and mean value of growth is reached 34.84 in 2007 from 11.53 which is observed in 2001. The mean value of performance (dependent variable) is maximum in 2007 valuing at 0.07 and the minimum value is observed in 2001, 2002, 2003 and 2005 at 0.02. The standard deviation is also not very high i.e. around 0.02 as compare to other variables except in the year 2007 in which it touches it maximum of 0.07. Table 4.2 also provides descriptive results of tangibility, liquidity, age and risk for the period of seven years from 2001 to 2007 for the life insurance sector of Pakistan. The mean values and standard deviations of tangibility is around 0.03 and 0.02 respectively in all seven years from 2001 to 2007.The mean values of liquidity are indicating an increasing trend from the minimum of 1.70 in 2001 to the maximum value at 6.36 in 2007. The standard deviation is also establishing an increasing trend from a minimum value of 0.76 in 2001 to a maximum value of 8.63 in 2007.The mean value of risk is at its lowest level in 2003 at 0.58 with a minimum standard deviation of 0.45 while these values have reached their maximum level in 2007 i.e. 6.35 and 6.51 respectively. Analysis Table 4.2 reports the results of regression analysis in which seven independent variables are regressed by using the data of life insurance sector of Pakistan from 2001 to 2007. The value of R square (0.816) indicates that performance of life insurance companies is nearly 82% dependent on independent variables i.e. size, leverage, growth, tangibility, age, risk and liquidity. Therefore, performance is mainly defined by these seven variables of life insurers in Pakistan over seven years. Table 4.2 indicates that leverage is negatively and significantly related with the performance of the life insurance companies. This predicts that the performance of highly levered Pakistani life insurance companies is not up to the mark. Table 4.2 also shows that coefficient of variable size is positive and statistically significant at 1% level. This predicts that performance of large size life insurance companies is better than small size companies. The negative coefficient of growth indicates a negative relationship between growth and performance. However, this negative relationship is found to be statistically insignificant with the p-value of 0.809. Therefore, growth is not considered as a proper explanatory variable of performance in life insurance sector. The beta values of explanatory variables tangibility and liquidity are 0.507 and 0.001 respectively with the positive coefficient sign. However, tangibility and liquidity are not statistically significant with the large p-values. Therefore, tangibility and liquidity are not Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (Constant) .010 .051 .204 .841 Leverage -.265 .090 -1.579 -2.940 .008* Size .038 .009 1.722 4.120 .001* Growth -4.69 .000 -.032 -.245 .809 Tangibility .507 .367 .183 1.382 .183 Liquidity .001 .003 .058 .205 .840 Age -.003 .003 -.235 -1.169 .257 Risk .004 .002 .374 1.903 .072** considered a powerful explanatory variable to define the performance of life insurance companies in Pakistan over seven years. Negative coefficient of variable age specifies the Table: 4.2 Regression Coefficients Their Significance level R Square 0.816 Adjusted R Square 0.749 F statistics 12.062 * Significant at 1% level **Significant at 10% level ______________________________________ negative relationship between performance and age of the Pakistani life insurance companies. However, the relationship between performance and age is statistically insignificant. Table 4.2 indicates that the coefficient of variable risk is positive and statistically significant at 10% level. According to the nature of insurance industry, ratio of total claims to total premiums (loss ratio) is used as a proxy to measure the risk of the life insurance companies in Pakistan. Positive sign shows a positive relationship between performance and risk of the insurance companies i.e. performance increases with the increase of loss ratio. Conclusion The current study investigates the impact of firm level characteristics on performance of the life insurance sector of Pakistan over the period of seven years from 2001 to 2007. For this purpose, size, profitability, age, risk, growth and tangibility are selected as explanatory variables while ROA is taken as dependent variable. The results of OLS regression analysis reveal that leverage, size and risk are most important determinant of performance of life insurance sector whereas ROA has statistically insignificant relationship with profitability, growth, tangibility and liquidity. TABLE 4.1: Descriptive Statistics Years Leverage Size Growth Performance Mean SD Min Max Mean SD Min Max Mean SD Min Max Mean SD Min Max 2001 0.80 0.21 0.45 0.99 6.02 2.12 3.06 8.93 11.53 11.90 3.22 32.39 0.02 0.01 0.00 0.03 2002 0.81 0.20 0.47 0.99 6.21 2.11 3.29 9.07 22.21 23.52 3.68 60.99 0.02 0.01 0.00 0.03 2003 0.82 0.19 0.51 0.99 6.50 2.08 3.57 9.20 37.18 32.62 8.30 90.71 0.02 0.01 0.00 0.03 2004 0.79 0.24 0.38 0.99 6.68 2.09 3.56 9.31 22.20 27.93 -1.78 61.16 0.03 0.02 0.00 0.05 2005 0.83 0.21 0.47 0.99 6.95 2.03 3.96 9.53 31.18 10.30 24.97 48.98 0.02 0.02 0.00 0.05 2006 0.84 0.20 0.49 0.99 7.21 2.02 4.24 9.68 31.79 26.14 3.74 72.78 0.03 0.02 0.00 0.06 2007 0.79 0.30 0.26 1.00 7.51 2.06 4.50 10.03 34.82 9.25 22.44 45.66 0.07 0.07 0.00 0.17 TABLE 4.1 (Continued): Descriptive Statistics Years Tangibility Liquidity Age Risk Mean SD Min Max Mean SD Min Max Mean SD Min Max Mean SD Min Max 2001 0.03 0.02 0.00 0.06 1.70 0.76 1.07 2.65 16.60 20.40 6.00 53.00 1.92 1.33 0.70 3.94 2002 0.03 0.02 0.00 0.06 1.73 0.86 1.14 3.01 17.60 20.40 7.00 54.00 0.83 0.47 0.40 1.34 2003 0.03 0.02 0.00 0.05 2.18 1.11 1.22 3.72 18.60 20.40 8.00 55.00 0.58 0.45 0.18 1.34 2004 0.02 0.02 0.00 0.04 2.24 1.77 1.09 4.85 19.60 20.40 9.00 56.00 3.34 3.08 0.00 7.23 2005 0.02 0.02 0.00 0.04 3.02 2.26 1.15 5.94 20.60 20.40 10.00 57.00 4.70 2.15 1.23 6.36 2006 0.02 0.01 0.00 0.03 3.98 2.72 1.36 7.37 21.60 20.40 11.00 58.00 3.60 3.86 0.51 9.72 2007 0.02 0.02 0.00 0.05 6.36 8.63 1.33 16.33 22.60 20.40 12.00 59.00 6.35 6.51 1.78 16.00 Table: 4.2 Regression Coefficients Their Significance level Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (Constant) .010 .051 .204 .841 Leverage -.265 .090 -1.579 -2.940 .008* Size .038 .009 1.722 4.120 .001* Growth -4.69 .000 -.032 -.245 .809 Tangibility .507 .367 .183 1.382 .183 Liquidity .001 .003 .058 .205 .840 Age -.003 .003 -.235 -1.169 .257 Risk .004 .002 .374 1.903 .072** R Square 0.816 Adjusted R Square 0.749 F statistics 12.062 * Significant at 1% level **Significant at 10% level

What is the Impact of ICT on Economic Growth Free Essays

Background: A nation’s standard of living is the most significant indicator of national economic performance. Economic growth is considered the most powerful engine for generating long term increases in standards of living. In today’s world economy, technology is a key factor that has a strong impact on economic growth both in short and long term. We will write a custom essay sample on What is the Impact of ICT on Economic Growth? or any similar topic only for you Order Now Thus, economists have become accustomed to associate long term economic growth with technological progress (Mokyr, 2005). Economists identify technology as ideas or knowledge that helps to produce output from inputs. Having more technology means being capable of producing more output with a given amount of inputs. People tend to focus on computers and the Internet as the icons of economic development, but it is the process that generates new ideas and innovations not the technologies themselves, that is the energy that sustains economic growth (Cortright, 2001). Accordingly, firms have invested in new technologies when they have seen an opportunity to earn profits. Investment in technology contributes to overall capital deepening. The greater use of technology may help firms reduce their costs, enhance their productivity and increase their overall efficiency, and thus raise economic growth. Moreover, greater use of information and communication technology may contribute to network effects, such as lower transaction costs, higher productivity of knowledge workers, and more rapid innovation, which will improve the overall efficiency of the economy (Moradi and Kebryaee, 2005). Research aim: This paper discusses the impact of Information and Communication technology on economic growth. Research hypothesis: The use of information and communication technology (ICT) is directly related to economic growth. Literature review: Although economic growth and technological progress are conceptually distinct, both theory and evidence suggest they often come together. Earlier economists had been interested in linking them together. Paul Romer’s New Growth theory, often called endogenous growth theory, is a view of the economy that incorporates two points. First, it views technological progress as a product of economic activity. Second, it holds that, unlike physical objects, knowledge and technology are characterized by increasing returns, and these increasing returns drive the process of growth (Cortright, 2001).The central idea of the New Growth theory is that the increase in returns is associated with new knowledge or technology. According to Romer, economic growth does not result from adding more labor to more capital, but from new and enhanced ideas articulated as technological development. In the 1950s, Robert Solow developed a model that added technical knowledge as a third factor -beside capital and labor- that continued to push economic productivity and growth (Cotright, 2001). In this model, Solow assumed that changes in technological progress have permanent effects on economic growth, while other changes have only level effects. Solow’s model pictured technology as a continuous, ever expanding set of knowledge. Chen and Kee in 2005 developed a theoretical model which states that knowledge is the main engine of economic growth, and that RD and human capital are tools to â€Å"endogenize† the accumulation of knowledge via technical progress (Detschew, 2008). Their main idea was that the increase in human capital in RD sector produces more innovations and at the same time the higher stock of human capital is considered as a factor of production, and using the innovations raises the rate of output growth. The rate of human capital growth biases the growth rate of productivity and output per worker, consequently, the growth rate per capita GDP (Detschew, 2008). Discussion: Taking into account the effects of technology on economic growth, we shift to emphasize on the Information and communication technology (ICT). ICT definition varies, causing intensive confusion. Many economists and agencies could not find a typical definition of ICT within the framework of economics. Patrick Bongo (2005) defined ICT as a set of activities that facilitate by electronic means the processing, transmission and display of information. According to the World Bank, ICT consist of the whole range of technologies designed to access, process and transmit information: hardware, software, networks and media for collection, storage, processing transmission, and presentation of information in the form of voice, sound, data, text and images. They range from the telephone, mobile phone, hardware, software to the internet (Detschew, 2008). Since economic growth is the ability of a nation to produce more goods and services (Bongo, 2005), therefore, the use of ICT enables the production of more goods in a shorter time as well as provides more efficient services. Miles (2001) explained that economic growth could happen in two ways; â€Å"the increased use of land, labor, capital and entrepreneurial resources by using improved technology or management techniques and increased productivity of existing resource use through rising labor and capital productivity†, which further explains the impact of ICT on economic growth. OECD (2003) mentioned three main impacts of ICT on economic growth. Capital deepening: investment in ICT contributes in overall capital deepening and consequently helps raise labor productivity. While the qualities and capabilities of ICTs have been improved all over the years, nominal prices of most ICTs have decreased (Hempell and Writschaftsforschung, 2006). Together, these developments had large declines in prices in real terms, which encouraged downstream sectors to increase their capital spending in real terms and consequently result in capital deepening. In addition, the decrease in ICTs prices and the resulting capital deepening contribute to overall labor productivity growth. Contribution of declining prices of ICT equipment to growth: Contribution of declining prices of ICT equipment to growth: http://www.imf.org/external/pubs/ft/wp/2010/wp1066.pdf (Haacker, 2010). 2. Technical progress in the ICT sector: for several years, there have been outstanding progress in the production of ICT goods and services; the qualities of these goods and services have improved. The production of ICT goods and services as a result of rapid technological progress may contribute to more rapid multifactor productivity (MFP) growth in the ICT producing sector (OECD, 2003). Increasing the amount and type of capital and labor used in production, plus reaching higher overall efficiency in how these factors of production can be used, would directly lead to economic growth, specifically higher multifactor productivity. http://coevolving.com/blogs/index.php/archive/ict-capital-and-the-services-sector-in-oecd-reports/ 3. Spillover effects: the greater use of ICT possibly will help out companies enhance their overall efficiency and thus raise MFP; also it may contribute to network effects, such as lower transaction costs and more innovations, which will improve the economy’s overall efficiency. Figure 1. The contribution of ICTs to economic growth (Source: ITU, World Telecommunication/ICT Development Report 2006: Measuring ICT for Social and Economic Development (Geneva: ITU, 2006), 44, http://www.unapcict.org/academy/academy-modules/english/Academy-Module8-Update-Section1.pdf Conclusion: The three impacts mentioned above all feed through economic growth, which prove that ICT has a positive impact on economic growth. But having this technology only is not enough to derive economic benefits. Many other factors are needed such as stable environment, the availability of the right skills, the organizational ability to make ICT effective in the workplace. It is important to mention that countries with equal flow of ICT will not always have equal impacts of ICT on their economic performances. Bibliography: Borros, M. 1997. Technology policy and Economic Growth. [Online]. Available at: http://brie.berkeley.edu/publications/WP%2097.pdf Mokyr, J. 2005. Long term Economic Growth and the History of Technology. [Online]. Departments of Economic and History, Northwestern University. Available at: http://faculty.wcas.northwestern.edu/~jmokyr/AGHION1017new.pdf Cortright, J. 2001. New growth theory: technology and learning. [Online]. Reviews of economic development literature and practice. No. 4. Available at: http://www.eda.gov/ImageCache/EDAPublic/documents/pdfdocs/1g3lr_5f7_5fcortright_2epdf/v1/1g3lr_5f7_5fcortright.pdf moradi, M. and Kebryaee, M. 2005. Impact of information and communication technology on economic growth in selected Islamic countries. [Online]. Available at: http://www.ecomod.org/files/papers/987.pdf Bongo, P. 2005. The impact of ICT on economic growth. [Online]. EconWPA, development and computer systems. Available at: http://129.3.20.41/eps/dev/papers/0501/0501008.pdf Miles, P. 2001. Globalization-Economic growth and development and development indicators. [Online]. Available at: http:// www.planetpapers.com/assets/4302.php OECD. 2003. ICT and economic growth: evidence from OECD countries, industries, and firms. [Online]. Available at: http://www.labs-associados.org/docs/OCDE_TIC.PDF Detschew, S. 2008. Impact of ICT in the developing countries on the economic growth. [Online]. Available at: http://books.google.co.uk/books?id=Gx8viG1uNK4Cprintsec=frontcoverdq=ICT+and+economic+growthhl=enei=XT2vTafMIIbOswafn63XDAsa=Xoi=book_resultct=resultresnum=2sqi=2ved=0CC4Q6AEwAQ#v=onepageqf=false Hempell, T. 2006. Computers and productivity: how firms make a general purpose technology work. [Online]. Vol.33. Available at: http://books.google.co.uk/books?id=oBzzBMa6Y-sCprintsec=frontcoverdq=Computers+and+productivity:+how+firms+make+a+general+purpose+technology+workhl=enei=GT6vTZHGFoX3sgasq-jXDAsa=Xoi=book_resultct=resultresnum=1ved=0CDgQ6AEwAA#v=onepageqf=false How to cite What is the Impact of ICT on Economic Growth?, Essay examples

By Fredrik Erixon of the European Centre for International Political Economy free essay sample

By Fredrik Erixon of the European Centre for International Political Economy Russia s command to fall in the World Trade Organisation ( WTO ) , filed in 1993, has been the longest accession saga in the history of the universe trade organic structure. Yet now, after bilateral trades with the US and the European Union that secured their support for the rank command, Russia looks set to fall in the pantheon of rules-based planetary capitalist economy at some point following twelvemonth. This is welcome intelligence. Russia would profit from being portion of the WTO nine. Its exports will non acquire much of a encouragement because they are dominated by the hydrocarbons and minerals ( stand foring more than two tierces of entire exports ) and they are already traded at zero or really low duties. But Russia will profit from lower monetary values of imported consumer and industrial goods, and, hopefully, from an addition in foreign direct investing ( FDI ) . If the Kremlin besides decides to follow the WTO regulation book, rank will assist to restrain Russia s fickle trade policy, particularly its regular descents into protectionism. Naturally, that would be of value for exporters to Russia ( and for importers of Russian goods, excessively, as Russia on a regular basis uses export revenue enhancements ) , but the biggest donee would be Russia itself. The biggest casualty of protectionism is ever the state that imposes such steps. Other states would profit from Russian WTO rank through a decrease in duties mean duties will travel down from 12-14 per centum to around 8 per centum and from an betterment in their predictability. The sectors that will profit specifically from a decrease in duties are civil aircraft, building, agricultural and scientific equipment, and medical devices. Russia will necessitate to present greater transparence ( and less favoritism ) in its system for merchandise criterions, licences and other alleged non-tariff barriers ( NTBs ) . Furthermore, sectors dependent on rational belongings, such as chemicals and biotechnology, will profit from holding resort to the WTO s agreement on rational belongings rights ( TRIPS ) to train Russia s shambolic IPR policy. Finally, foreign Bankss and insurance houses will be granted bigger chances to make concern in Russia. But there are besides hazards and downsides to holding Russia as member of the WTO. The biggest hazard is that the Kremlin will merely ignore opinions against Russia in the dispute-settlement system, the anchor of the WTO. As the WTO itself can non implement opinions that require policy alteration in a state, the system requires that states respect the authorization of the dispute-settlem ent organic structure and that bigger and more powerful states avoid playing power games with smaller states over opinions. The instance for esteeming opinions is simple: it is in everyone s involvement that states adhere to hold regulations. The failing is the same as for all systems that depend on enlightened involvement for a common good: some may liberate drive on the system in the belief that it benefits them, at least in the short term. And if some are free-riding, others will follow. And the system will unknot. This hazard is underlined by Russia s recent history of flashing international understandings ( and, as in the instance of the Energy Charter Treaty, retreating from understandings ) in the belief that no 1 would hold the bravery to contend the Kremlin to the acrimonious terminal. Russian rank will besides add a new bed of troubles for WTO dialogues, like the current Doha Round. Russia will be portion of the protectionist wing of the rank and will defy in countries that are cardinal to universe trade today and in future, like liberating up services trade, cutting ruddy tape that prevents trade, and restricting the freedom to subsidise domestic houses at the disbursal of foreign rivals. It will besides implement the resistance to turn toing old issues, like cut downing or extinguishing duties on consumer and industrial goods. Russia s fabrication sector is weak it merely represents 6-7 per centum of Russia s export and suffers from the Dutch disease: the heavy trust on hydrocarbon exports have pushed the existent exchange rate to such a grade that the fabrication sector has suffered. Many industries are saddled with old Soviet engineerings, and they survive on subsidies and boundary line protectionism. There are positive marks that Russia is acute to alter its economic theoretical account. The new Kremlin rhetoric on modernisation and the denationalization plans suggest that energy and state-based economic dictatorship is on a downward tendency. The new morning in its rank command for the WTO is besides a good mark. But the marks are far excessively few to be cheerful about Russian economic policy. Like earlier, optimism over the WTO accession can shortly switch to pessimism. The old theoretical account is entrenched in the Kremlin economic mind and there are many powerful figures that dislike the thought of being constrained by international understandings or increased foreign competition. President Medvedev has now secured the support from the US and the European Union for its WTO command. Now he needs to take the battle with Kremlin co-workers and oligarchs. That may go a far bigger job. Fredrik Erixon is manager of the European Centre for International Political Economy ( ECIPE ) , an economic think armored combat vehicle based in Brussels