2076

2. Bing – Bing is Microsoft’s attempt to challenge Google in the area of search but despite their efforts they still did not manage to convince users that their search engine can produce better results than Google.

3. Yahoo – Since October 2011 Yahoo search is powered by Bing. Yahoo is still the most popular email provider and according to reports holds the third place in search.

С4. Ask.com – Formerly known as Ask Jeeves, Ask.com receives

approximately 3% of the search share. ASK is based on a question/answer format where most questions are answered by other users or are in the form of polls. It also has the general search functionality but the results returned lack quality compared to Google or even Bing and Yahoo.

и6. Blekko.com – Blekko.com was developed by ex-Googlers and they present themselves as the “spam free search engine”. It is better suited for

5. AOL.com – According to netmarketshare the old time famous AOL is still in the top 10 search engines with a market share that is close to 0.6%. The AOL network includes many popular web sites like engadget.com,

calculations,бАfor example if you enter “mortgage 2000” as input it will calculate your loan amount, interestДpaid etc. based on a number of assumptions.

techchrunch.com and the huffingtonpost.com.

webmasters and SEO’s who need more data for SEO purposes rather than

normal users.

7. Wolframalpha – wolframalpha is different that all the other

search engines. They market it as a Computational Knowledge Engine which

can give you facts and data for a number of topics. It can do all sorts of

8. DuckDuckGo – Has a number of advantages over the other search engines. It has a clean interface, it does not track users, it is not fully loaded

with ads and has a number of very nice features (only one page of results, you can search directly other web sites etc)И. I am sure that some of the

features of duckduckgo will be used by other search engines and with some proper funding duckduckgo can get a decent search engine market share.

9. WayBackMachine – archive.org is the internet archive search engine. You can use it to find out how a web site looked since 1996. It is very useful tool if you want to trace the history of a domain and examine how it has changed over the years.

10.ChaCha.com – According to alexa chacha.com is the 8th most popular search engine with a ranking position of 297 in the US. It is similar to ask.com where users can ask or answer a particular question. They also have a number of quizzes that can help you decide on a number of topics. It’s not bad at all and the answers are precise and to the point. For example if you search “What is the best search engine?” you will get an answer that Google is the best and most popular search engine and Yahoo is on the second place.

111

These are the 10 best and most popular search engines on the Internet today. The list is by no means complete and for sure many more will be created in the future but as far as the first places are concerned, Google and Bing will hold the lead positions for years to come.

What pluses and minuses do these engines have?

С28. Give a talk on your speciality (IT engineering) using this plan. a) qualifications of your faculty;

b) your specialized subjects;

с) where can you work after graduating. и бА Д И

112

REFERENCES

APPENDIX I

Реферирование текста (rendering the text/article)

1. Headline of the article (text), title of the newspaper or the magazine, date of publication, the author.

113

114

115

APPENDIX II

Texts on specialties

ECONOMICS

HOW DID THE FINANCIAL CRISIS THREATEN MAIN STREET? СCredit crunch

The shock of massive losses in mortgage-related investments made financial institutions and investors much more wary of lending to households and businesses. Bad loans also eroded bank capital, the financial cushion these иinstitutions maintain to cover losses. Moreover, banks were unable to sell most types of loans to investors because the markets that packaged these loans as securities had stopped working. As a result, banks and investors clamped down on many types of loans by tightening standards and demandingбАhigher interest rates—a classic credit crunch.

Plummeting wealth

The financial crisis wiped out over 25% of Americans' net worth. Plummeting house prices and the resulting loss in home equity reduced the wealth of American households by over $7 trillion. In addition, stock prices around the world crashed following the panic of late 2008 and the intensifying global recession. In the United States, nearly half of stock market wealth was lost, a percentage decline that exceeded the 2000-2002 stock market crash. Foreign households didn't fare any better, as stock markets around the world crashed.Д

Global recession

The credit crunch and loss of wealth were a one-two punch that sent the United States and many other economies into deep recession. Tight credit weakened spending on big-ticket items financed by borrowing: houses, cars, and business investment. The hit to householdИwealth caused people to cut back on spending as they struggled to rebuild depleted savings. With demand weakening, businesses canceled expansion plans and laid off workers. Beginning in December 2007, economic activity in the United States and many other countries began to shrink. When financial panic intensified in the fall of 2008, the recession intensified and job losses soared.

IMPLICATIONS FOR INFLATION DYNAMICS

IN THE CURRENT RECOVERY

In an extended period of high unemployment, such as the current slow recovery, does unemployment lose its disinflationary effect? Based on the flexible statistical model with time-varying trends estimated in the previous

116

section, the extent that unemployment exerts downward pressure on inflation depends, in part, on the estimated trend rates of unemployment and inflation. The apparent lack of disinflationary pressure in the current recovery can be attributed largely to an increase in trend unemployment, not a reduction in

the strength of the relationship between the unemployment gap and cyclical inflation. This section examines the robustness of trend estimates and discusses implications of the statistical model for the probability of deflation and for the conduct of monetary policy.

Сunemployment by estimating and removing time-varying trends. Because such trend estimates are often imprecise and unreliable, it is important to compare the model’s trend estimates to alternative estimates. Alternative estimates of trend inflation, such as survey data on long-term inflation

The statistical model estimates the cyclical components of inflation and

иIn contrast, trend unemployment is subject to greater uncertainty.

expectations, show only modest variations over the recent period, ranging from 2.0 percent to 2.3 percent (Chart 6). The pattern is in line with the model-based estimates in this article.

EstimatesбАof trend unemployment based on the Job Openings and Labor Turnover Survey (JOLTS) have ranged from 5.9 percent to 8.9 percent since the recession of 2007-09 (Kocherlakota). Additional data sources, such as business surveys and micro-level data, help validate the estimate of trend unemployment. In fact, the estimated trend unemployment rate of about 7 percent in this article is consistent with the estimates based on micro-level data on labor markets (Barclays Capital; Sahin and others). Together, this evidence suggests that trend unemployment may be around 7 percent, which is 1 percentage point higher than the historical average of unemployment since 1960.

Deflation probability forecastsД

The sluggish pace of economic recovery, coupled with a low level of inflation since the recession of 2007-09, has raised concerns that the United

States may duplicate Japan’s prolonged periodИof deflation. While total PCE inflation briefly moved to a negative rate during 2009, this short-term deflation was largely attributed to substantial declines in energy prices (Chart 7). Core PCE inflation remained positive throughout the recession. Nonetheless, the high level of unemployment indicates that the possibility of deflation cannot be ruled out. In fact, Clark and Doh (2011) find that adding the unemployment gap to univariate inflation forecasting models boosts the probability of deflation compared to a model relying only on inflation data.

The specification of statistical uncertainty in the model generates a range of possible trajectories for future inflation, which can be used to construct the probability of deflation (Chart 8). Forecasts of the one-year-ahead annual inflation rate are used to compute the probability of deflation from the third

117

quarter of 1999 to the second quarter of 2011. The forecasts incorporate statistical uncertainty related to time variation in the coefficients of the model as well as uncertainty about future shocks to the variables in the model.

While the probability of deflation is determined by many factors, a drift in trend inflation and a rise in unemployment are two dominant ones during the past few years. The decomposition of the empirical estimates of these two

Сfactors suggests that higher unemployment is a key determinant of the probability of deflation.14 In particular, the rise in unemployment since the fourth quarter of 2008 is a dominant factor in increasing the risk of deflation.

Deflation probability peaked in the first quarter of 2009, reaching almost 3 иpercent. Although small, the number indicates non-negligible downward pressure on inflation, given that inflation expectations from survey data were above 2 percent. In periods with lower unemployment, such as early 2007, the probability of deflation would have been below 1 percent with a similar level of inflationбАexpectations.

Implications for monetary policy

A large unemployment gap during economic downturns implies downward pressure on inflation in Phillips curve models. This outlook can justify substantial easing of monetary policy given the Federal Reserve’s dual mandate to promote maximum employment and stable prices. In the current recovery, such easing has been accomplished through large scale asset purchases, given the constraint currently imposed by the zero lower bound on short-term interest rates. The following quote from the FOMC statement on Nov. 3, 2010, illustrates this point.Д

Currently, the unemployment rate is elevated, and measures of underlying inflation are somewhat low, relative to levels that the Committee judges to be consistent, over the longer run, with its dual mandate. Although the Committee anticipates a gradual return to higher levels of resource utilization in a context of price stability, progressИtoward its objectives has been disappointingly slow. To promote a stronger pace of economic recovery and to help ensure that inflation, over time, is at levels consistent with its mandate, the Committee decided today to expand its holdings of securities.

Trend unemployment increases during periods of extended high unemployment, reducing the estimated size of the unemployment gap. As a result, during such periods, the amount of slack in the economy is less than previously estimated. Although the Phillips curve relationship continues to hold, a smaller estimate of the unemployment gap produces less disinflationary pressure.

More broadly, estimates of trend unemployment and trend inflation from the model may provide information on changes in the NAIRU and affect our understanding of future inflation. Incorporating changes in trend unemployment into Phillips curve models may yield better forecasts for

118

policymakers as they seek to provide the proper level of accommodation to achieve the Federal Reserve’s dual mandate. Similarly, estimates of changes in trend inflation may provide information on changes in long-term inflation expectations just as surveys of inflation expectations may help provide information about the trend.

СTHE EFFECT OF GLOBALIZATION ON

INTERNATIONAL BUSINESS CYCLES

Economic theory is unclear about the effect of increased trade and financial integration on business cycle synchronization. While both trade and иfinancial linkages provide a channel through which demand shocks can be transmitted across economies — possibly leading to greater business cycle synchronicity — both types of connections can also produce offsetting effects that reduceбАbusiness cycle synchronicity. In theory, it is difficult to tell which effects will dominate.

Trade linkages provide a direct channel through which increased demand in one country is transmitted to increased production in another country. For example, suppose that there are only two countries in the world, country A and country B. Consumers in both countries consume a basket of goods that consists of products produced in both countries. Imagine what happens if the demand for final goods by consumers in country A increases. This demand shock raises the demand for all goods, including imports from country B. Country B will react by producingДmore goods to meet the extra demand from country A. Trade has transmitted this demand shock from A to B, leading to more synchronous business cycles because both countries produce both goods in response to the increased demand.

Another way that trade may lead to synchronous business cycles is through intra-industry trade. Hummels, Ishii, andИYi (2001) have documented the growing importance of intra-industry trade to the global economy. When one country imports intermediate goods — that is, goods that will be used to produce some other good — industry-specific shocks can be transmitted internationally. Continuing the example, suppose country A produces intermediate goods — wheat and steel — while country B produces final goods, bread and cars. In order to produce bread and cars, country B imports wheat and steel from country A. If country A experiences a drought such that wheat production (and therefore wheat exports) declines, then country B will produce less bread. As a result, the drought in country A affects output in country B in the same direction so business cycles will be more synchronized.

However, it is also possible that trade linkages could actually decrease the synchronization of business cycles between countries. Consider the case

119

where two countries specialize and trade different types of products. Instead of the example above, suppose that country A produces cars while country B produces and exports wheat. Again, suppose that a drought significantly reduces country B’s wheat production. Clearly both countries will consume

less bread, but country A’s car production will remain relatively unharmed by the drought. Thus, even though both countries are adversely affected by the drought, it is clear that country A is less affected than country B. In this way, if countries specialize and trade very different types of goods, and if industryspecific shocks are important, then trade may actually reduce the synchronicity of business cycle movements.

СThe impact of financial linkages on business cycle synchronization is also ambiguous in theory. On the one hand, standard international business cycle theory (Backus, Kehoe, and Kydland 1992) would predict that the free-

иexperiences a positive shock to its productivity while the other does not. Global investors will move their investments away from the relatively less

flow of capital internationally would decrease business cycle

productiveбАeconomy to the more productive economy. As a result, the country with the positive productivity shock sees an increase in output for two reasons: directly from the positive productivity shock and indirectly from the inflow of funds from the foreign country. Unfortunately, the country without the productivity shock sees a decline in output because funds flow out of the country and into the now more productive country. Thus financial linkages can lead to asynchronous business cycles. To further complicate matters, Heathcote and Perri (2004) point out that it is difficult to determine if financial linkages cause asynchronous business cycle fluctuations, or if the reverse is true, since asynchronous business cycle fluctuations also provide investors with good hedging opportunities.

synchronization. To understand the mechanism, suppose that one country

Д Access to international financial marketsИmeans that investors can hold

the assets of many different countries. Such diversification implies that shocks to the financial system of one country can affect the wealth of consumers in other countries, which in turn can affect consumption in that country. If consumers in one country hold a large portion of their equity assets in a foreign country, and the country’s stock market falls, then consumption in both countries will fall because consumers of both countries will be less wealthy. In a similar way, suppose that the value of an international bank’s assets in one country declines. In response, the bank may withdraw funds from many different countries simultaneously, leading to more highly correlated business cycles (see, e.g., Krugman 2008; Kollmann, Enders, and Muller 2011). Finally, as the European sovereign debt crisis has shown, financial market contagion can reduce growth internationally.

120