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Solution Manual for Macroeconomics: Understanding the Global Economy, 3rd Edition

Solution Manual for Macroeconomics: Understanding the Global Economy, 3rd Edition is designed to reinforce textbook concepts through clear explanations.

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    C H A P T E R 1 W h a t i s M a c r o e c o n o m i c s ? 2 INTRODUCTION As might be expected, this first chapter sets the scene for the whole textbook and attempts to motivate the study of macroeconomics. Although there is probably only enough material here for about fifteen minutes of lecture, it obviously needs to be well delivered. Teaching Tips ALTERNATIVE ROUTES THROUGH THE CHAPTER This chapter is likely to form only the first part of a lecture and should probably be combined with the material in Chapter 2. The chapter can be tailored to your audience. For example, if the students are mainly working in business, give examples of how macroeconomics influences business decisions. Think about touching on the key macroeconomic issues in the news at the time e.g. tax policy, the business cycle etc. CHAPTER GUIDE 1.1 What is Macroeconomics About? It is a good idea to contrast a recent short - term macroeconomic issue (like the latest change in monetary policy) with the longer - term issue of growth and inequality between regions. The Background Material below gives more information on comparative world growth since 1500. 1.2 But What about that Definition? Milton Friedman’s favorite description of the wonders of the price mechanism (the invisible hand) is “I Pencil” by Leonard Reed (see www.econlib.org/library/Essays/rdPncl1.html ) . However, business students may find it a little patronizing. 1.3 The Difference between Macro and Microeconomics. Like most distinctions, this one is somewhat blurred around the edges. It may be worth underlining that good macroeconomics tend to have strong microfoundations (i.e. based on microeconomic analysis and built up to macroeconomic behavior). 1.4 Why Should People Interested in Business Study Macroeconomics? There are many good examples of how macro economic analysis can help solve real world problems. The case study below gives a lighter example; how macroeconomics can help to predict the next U.S. president. CHAPTER 1: WHAT IS MACROECONOMICS?

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    C H A P T E R 1 W h a t i s M a c r o e c o n o m i c s ? 3 CASE STUDY: ECONOMIC EVENTS AND PRESIDENTIAL VOTING Introduction Not only is economic policy a key issue in presidential politics, the state of the economy is a key determinant of the outcome of the election. To illustrate this point, Professor Ray Fair has devised a simple model of presidential voting based on macroeconomic and political variables. The model correctly predicted the outcome of 20 out of 22 elections since 1916 (Nixon - Kennedy 1960 and Bush - Clinton 1992 were its two failures). Its prediction for the 20 12 election (made in early 2012 ) was for an Obama victory with a marginally reduced share of the vote The Model Fair’s original model considers the following questions in respect of each presidential candidate  Is your party already in power and has the economy been doing well in the last three quarters? – Positive impact  Is your party already in power and has the economy grown 3.2% p.a. or more in the last 15 quarters? – Positive impact.  Is your party already in power and has inflation been low over the last 15 quarters? – Positive impact.  Are you an incumbent? – Positive impact.  Is America involved in a world war? – Forget the economy. It is perhaps troubling that such simple determinants seem to explain so many election results, particularly since short term factors - such as growth over the last 9 months - seem so important (see also “It’s the economy stupid” in the Background Material for Chapter 2). Source Fair(1998) “The Effect of Economic Events on Votes for President” http://fairmodel.econ.yale.edu/ vote2012/index2.htm Discussion Questions 1) Why is voting s o influenced by economics events? Can politicians really improve/worsen economic outturns over a normal electoral cycle? 2) If economics is the key to political success how come so few politicians have an economics training? Additional Questions Question 1) Look at the chart below of per capita GDP (1990 US dollars) for a number of regions. 1) Why did the world economy grow so slowly before the 20 th Century? 2) Why was growth concentrated in a few regions? Africa and the US had the same output per capita in 1500. 3) Is increasing inequality between countries inevitable?

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    C H A P T E R 1 W h a t i s M a c r o e c o n o m i c s ? 4 GDP per capita 1500 - 1998 (in 1990 US dollars) 0 5000 10000 15000 20000 25000 30000 1500 1530 1560 1590 1620 1650 1680 1710 1740 1770 1800 1830 1860 1890 1920 1950 1980 United States Japan Western Europe Latin America Former USSR China Africa Source: OECD Answer 1) There is of course no accepted answer to these questions. A poor reflection on economics as a science Question 2) If per capita income in Ethiopia grows 3% per annum for the next fifty years and per capita income in the US grows at 3% per annum for the next fifty years, what will happen to the income gap (in dollars) between Ethiopia and the US? Answer 2) the gap will widen. 3% of a big number (i.e. US GDP) is more than 3% of a small number (i.e. Ethiopian GDP)

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    C H A P T E R 2 T h e L a ng u a g e of M a c r o e c o n o m i c s : T h e N a t i o n a l I n c o m e A c c o u n t s 5 INTRODUCTION This chapter is more interesting than its title implies as it offers opportunities to discuss current issues. As with several chapters, one can either give a worldwide view with lots of comparative statistics or focus on aspects of a particular economy. Teaching Tips ALTERNATIVE ROUTES THROUGH THE CHAPTER This chapter takes the logical route of discussing how to measure output before going on to its time series properties – it is hard to teach any other way. Output trends and business cycles naturally combine with material from Chapters 4 and 14. Welfare and output can be discussed either at the beginning or end of a lecture and can be extended by discussing the Human Development Index in more detail. It is useful to point out the two types of problem with GDP measures. First, it is simply a narrow measure of what is produced in the economy and so would not correspond precisely to welfare even if well measured. Second, it does not even measure output properly since it cannot include components such as non - remunerated services and the underground economy. CHAPTER GUIDE 2.1 What Do Macroeconomists Measure? The discussion concerning output versus welfare (which reappears at the end of the chapter) is easy to motivate. The ecological damage of higher output is a current example and can be used to extend the discussion to missing markets (i.e. properly measured output could include pollution costs if these were tradeable) . 2.2 How do Macroeconomists Measure Output? URL’s for National Accounts data: USA http://www.bea.gov/ Euro - Area http://sdw.ecb.europa.eu/browse.do?node=2018805 Japan http://www.esri.cao.go.jp/index - e.html UK http://www.statistics.gov.uk/hub/economy/national - accounts/national - income - - expenditure - and - output/index.html Canada http://www.statcan.ca/ 2.3 Output as Value Added Figure 2.2 in the main text is worthy of discussion. By showing how rich countries tend to have small agriculture sectors (i.e. only a small proportion of value added comes from agriculture), it illustrates why many economists have argued that industrialization is the key to growth. Certainly, the Asian tigers followed this route to CHAPTER 2: THE LANGUAGE OF MACROECONOMICS: THE NATIONAL INCOME ACCOUNTS

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    C H A P T E R 2 T h e L a ng u a g e of M a c r o e c o n o m i c s : T h e N a t i o n a l I n c o m e A c c o u n t s 6 success. Whilst in principle there is now reason why a country cannot transition from being poor to rich by becoming a highly efficient agricultural producer – no country in the world has managed this transition in practice (New Zealand is a rich economy that is largely dependent on agriculture, but its development was largely due to colonization). 2.4 National Income Accounts Further explanations for some of the big GNP/GDP differences shown in figure 2.5 are given in the Chart and Table tips. Students find that a practical discussion of individual countries extremely useful as a way of understanding the concepts. 2.5 How Large Are Modern Economies? A useful way of expanding this section is to discuss the data on national economies published by the World Bank http://www.worldbank.org/poverty/wdrpoverty/report/index.htm 2.6 Total Output and Total Happiness. To stimulate discussion here it is worth getting hold of some Human Development Index (HDI) figures ( http://hdr.undp.org ). The tables give comparisons between the HDI and standard GDP figures. Generally speaking, the HDI and GDP are pretty similar, with some interesting exceptions - Oil exporters: Far higher GDP than HDI USA: Top in GDP but not in HDI. Cuba: Far higher on the HDI than on GDP. Brunei: Higher GDP than HDI since a large proportion of to tal GDP goes exclusively to the Sultan. The Case Study “It’s the Economy, Stupid” shows how data errors and the slow dispersion of economic data influenced the 1992 US presidential election. Details on the release of US data are given in the Case Study to Chapter 15. TABLE & CHART TIPS Figure 2.5. GDP is generally higher than GNP for recipients of foreign investment who have to remit profits (e.g. US). As we shall see in Chapter 14, recipients of substantial foreign investment have been amongst the fastest growing economies in the world (Chile, Ireland). Ireland in particular has benefited from huge investments by US firms (e.g. Dell). Oil exporters like Kuwait tend to be net investors in the rest of the world and therefore receive net interest profits and dividends from overseas. Norway is now an oil exporter and is rapidly moving towards a larger GNP than GDP as it uses oil receipts to invest overseas. A significant proportion of the population of Bangladesh work overseas and their remittances back home substantially boost GNP. The Philippines is an even more extreme example of this phenomenon. Figure 2. 9 Economists have used three main methods of measuring the underground economy. 1) Statistical discrepancies. In most countries, figures for the expenditure measure of GDP are higher than the income measure even though they should in fact be the same. This

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    C H A P T E R 2 T h e L a ng u a g e of M a c r o e c o n o m i c s : T h e N a t i o n a l I n c o m e A c c o u n t s 7 discrepancy arises because people tend to attempt to avoid or evade income tax and so income is under - recorded. There can be similar discrepancies between the recorded labor force (people in employment or claiming benefit) and the actual labor force as people in the shadow economy withdraw from the official labor market. However, these discrepancies tend to capture only a small part of the shadow economy. 2) Cash demand. As we shall see in Chapter 12, economists often analyze the relationship between cash circulating in the economy and total transactions in the economy. If cash demand is much higher than recorded output, it may be because the shadow economy prefers the anonymity of cash. In fact, a very high ratio of cash to bank deposits suggests the presence of a large shadow economy. 3) Physical input. Since the shadow economy still needs to use measured inputs such as electricity, it is possible to gauge the size of the shadow economy by looking at the demand for such inputs. If the demand outstrips what is necessary for official output, it is a good indication that the shadow economy is important. The chart in the text shows figures for the electricity - input method only, as this gives the broadest sample of countries. Figure 2.13 Further information on environmental accounting can be found at http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/ENVIRONMENT/EXTDATASTA/0,,content MDK:21060933~menuPK:7333796~pagePK:64168427~piPK:64168435~theSitePK:2875751,00.h tml CASE STUDY: “IT’S THE ECONOMY, STUPID” In 1992, campaign adviser James Carville came up with the slogan that is thought to have won Bill Clinton his first presidential election - “it’s the economy, stupid”. Under President George Bush (senior), the economy had suffered a mild recession (negative output growth) after the Gulf War. However, by the time of the election, the economy had already begun to recover strongly (growth was 3.2% in 1992) and so Bill Clinton’s campaign slogan should probably not have struck home as strongly as it did. Why didn’t Bush get the credit for the recovery? 1) Slowly changing expectations . Even after you come out of a recession you don’t feel better off. This makes sense because if output has fallen, it may take a year or more to get income back up to its pre - recession level. 2) Data collection lags . Although US GDP data are amongst the most rapidly compiled in the world, it still takes several months for the final data to be reported. So in 1992, although the preliminary Q3 GDP figures were available in late October, the final numbers were not reported until much later. 3) Preliminary data errors . When the preliminary Q3 GDP figures arrived, they were a pleasant surprise for Mr. Bush - the economy had supposedly grown by 2.7% (at an annualized rate). However, many commentators dismissed them as incorrect. For example, CBS reporter Susan Spencer filed from the Bush campaign: "He crowed today

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    C H A P T E R 2 T h e L a ng u a g e of M a c r o e c o n o m i c s : T h e N a t i o n a l I n c o m e A c c o u n t s 8 at upbeat news of a third quarter growth rate of 2.7 percent, though some economists warned that may not hold.” In the event she was right to be suspicious of the Q3 number it was subsequently revised up to 3.9%! By the end of 1992, a year that some had predicted would see GDP fall by almost 2%, a healthy 3.2% growth rate had been posted. US GDP Growth: 1988 to 2000 US GDP Growth (Annual % change) Source: EcoWin 88 89 90 91 92 93 94 95 96 97 98 99 00 01 -2 -1 0 1 2 3 4 5 6 7 Discussion Questions 1) What possible defense could Bush have mounted to the economic attack made on him by Clinton? 2) Should the budgets of the statistical agencies have been increased or reduced after this incident?

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    C H A P T E R 2 T h e L a ng u a g e of M a c r o e c o n o m i c s : T h e N a t i o n a l I n c o m e A c c o u n t s 9 Additional Questions Question 1 ) Look at the chart below and describe what happened to Indonesia in 1998 Indonesia, Real and Nominal GDP growth Nominal GDP growth Real GDP Growth Source: EcoWin 90 91 92 93 94 95 96 97 98 99 00 01 02 Percent -20 -10 0 10 20 30 40 50 60 Answer1) The Asian currency crisis in 1997 triggered a recession in Indonesia so that real GDP fell by over 10%. At the same time, the decline in the Indonesian currency (the Rupiah) led to a dramatic rise in prices as imported goods cost more in Rupiah terms and these import prices fed through into domestic prices and wages (note that if the import price rise had been the only source of price inflation then nominal GDP would have been unaffected since it excludes imported goods). The rise in inflation meant that nominal GDP rose dramatically even though real GDP was falling. Question 2) Analyse the recent sectoral composition (agriculture, industry and services as a % of GDP) of output GDP for a selection of countries of your choice using either national sources or the World Bank’s World Development Indicators [ http://data.worldbank.org/data - catalog - > WDI databank]. Is the sectoral breakdown what you would expect given the country’s level of development (see Figure 2.2)?

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    C H A P T E R 3 T h e W ea l t h o f N a t i o n s 10 INTRODUCTION This chapter is excellent for motivating the study of economics and so is a key chapter in the book. By looking at growth from a historical and international perspective it offers students new insights and shows how important economics can be. Given that many students are impatient to focus on monetary policy and the business cycle (i.e. the stuff they read in the newspapers), it is important to motivate this topic well. Teaching Tips ALTERNATIVE ROUTES THROUGH THE CHAPTER The first three sections of this chapter give an entertaining account of the history of economic growth and could therefore be included in a separate opening lecture. The following sections introduce material that is analyzed in more detail in Chapters 4,5,6 and 7 and could be combined with lectures on those chapters. However, since these sections offer an overview of those later chapters, it would be natural to start with them or use this chapter as pre - lecture reading.. CHAPTER GUIDE 3.1 The Importance of Economic Growth. It is worth motivating this section by looking at economic reports in newspapers. Most of them will be concerned with cyclical rather than long run issues (e.g. the next move in interest rates). Although most students will not have heard of Thomas Malthus, they may have heard of economics described as “The Dismal Science”. Malthus’s theory of population was the inspiration for that description. It may also be worth noting that many of Marx’s dismal prophecies were predicated on the consequences of limited economic growth. 3.2 The Impact of Long - Run Growth. The relationship between growth and poverty reduction is a key one to those who are skeptical about the importance of economic growth. It is interesting to contrast the fact that global poverty reduction has been largely due to poverty reduction in China, despite the fact that China has actually experienced increased inequality (section 4.8) 3. 3 Explaining Cross - Country Income Differences . In developing countries, the phenomenon of underemployment is relatively common. This is where people who are notionally employed work fewer hours than they would wish. Often this occurs when a large extended family works on a small farm. As a result, drawing labour out of the agricultural sector (often during the process of industrialization can raise measured productivity in the agricultural sector. 3. 4 . The Production Function and Factor Inputs This, and the following sections, introduce material that will be covered in detail in the following four chapters. It also introduces the key supply side concept of the production function. CHAPTER 3: THE WEALTH OF NATIONS – THE SUPPLY SIDE

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    C H A P T E R 3 T h e W ea l t h o f N a t i o n s 11 3. 5 Growth Accounting . The key point of this section is to show how output growth can be decomposed into Labor, Capital and TFP. Moreover, if students properly understand this section, it will provide an excellent foundation for Chapters 4 to 7. 3. 6 Growth Accounting an Application. The Case Study below “The Productivity Challenge” reviews an exercise in growth accounting, but focuses on the level of productivity rather than growth. CASE STUDY: “THE UK PRODUCTIVITY CHALLENGE” In June 2001, the newly re - elected UK Labour Government published a report on its strategy for productivity over the next Parliament. The report begins by outlining the UK’s poor labor productivity performance (i.e. GDP per worker). As the chart below shows, UK labor productivity is significantly below that of other major economies (even though the figures for Germany include the less efficient East) and, although there has been some catch - up with continental Europe since 1995, US labor productivity is actually increasing relative to the UK. Productivity per worker (UK=100) 0 20 40 60 80 100 120 140 160 US Germany France 1995 1999 Of course, one of the important factors behind the high productivity per worker in the US is the greater number of hours worked. As the chart below shows, when you compare output per hour worked rather than output per worker, the US and Continental Europe look more comparable. However, the UK still remains well below all of them.

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    C H A P T E R 3 T h e W ea l t h o f N a t i o n s 12 Productivity per worker and per hour worked (UK=100) 0 20 40 60 80 100 120 140 160 US France Germany GDP per worker GDP per hour worked What explains the UK’s poor productivity performance? Standard Growth Accounting points to two key weaknesses. Firstly, low levels of physical capital per worker. The average UK worker has access to far less physical capital than his German and US counterpart. Secondly, low levels of innovation - the UK is less effective at innovating in the production process. Relative to the US this may not be surprising, given that the US leads in most areas of technology. However, Germany also has a far stronger record of innovation which, added to its more skilled labor force, explains much of the gap. The table below summarizes the evidence on the UK productivity gap showing how each element of the production function helps explain the gap between UK and other countries’ labor productivity. It shows how the contribution of each factor to the gap shown in the chart above (i.e. in the case of the UK relative to the US, it shows the percentage contribution of each factor to the 21% shortfall of UK productivity).

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    C H A P T E R 3 T h e W ea l t h o f N a t i o n s 13 Explaining the UK productivity Gap (% contribution to the UK’s lower productivity relative to the US and Germany) Relative to US Relative to Germany Physical Capital 31 55 TFP 69 45 Of Which: Innovation 65 17 Skills 0 14 Other 4 14 Total 100 100 Armed with this evidence, the Labor government has focused its productivity enhancing measures on encouraging innovation (e.g. a newly introduced research and development tax credit for large firms) and investment (e.g. lower capital gains tax). Source: “Productivity in the UK” HM Treasury and DTI Discussion Questions 1) What factors might explain the UK’s low rate of innovation, skills and other elements of TFP? 2) What policies might help deal with the UK’s productivity gap? Background Material THE LORENZ CURVE AND GINI COEFFICIENT. The standard measure of income inequality is the Gini coefficient. It is based on a comparison of actual income distribution with a perfectly even one. The easiest way to understand the Gini Coefficient is first to construct a Lorenz curve.

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    C H A P T E R 3 T h e W ea l t h o f N a t i o n s 14 The Lorenz Curve % Share of National Income % of population Line of Perfect Equality Lorenz Curve The Lorenz Curve is constructed by ranking the population by income. Starting at the lowest income, the curve shows how the share of national income rises as we move up the income distribution and include more people. If income was perfectly equally distributed, the Lorenz curve would be the 45 - degree line shown above. In practice however, the curve will always tend to be below the 45 - degree line. The Gini coefficient is the ratio of the area between the 45 - degree line and the Lorenz curve to the whole area under the 45 - degree line (i.e. the shaded area in the diagram as a ratio to the whole area under the 45 - degree line). The table below displays Gini coefficients for a range of countries. Note that income inequality has increased in almost all countries during the 1990’s (most notably in Russia and other former soviet union countries), and that the US has the highest Gini coefficient of the major economies. Gini Coefficients Across the World country Gini index country Gini index Country Gini index Namibia 70.7 Turkmenistan 40.8 Pakistan 33.0 Botswana 63.0 United States 40.8 France 32.7 Sierra Leone 62.9 China 40.3 Netherlands 32.6 Brazil 60.7 Turkey 40.0 Spain 32.5 South Africa 59.3 Ghana 39.6 Bangladesh 31.8 Chile 57.5 Mozambique 39.6 Korea, Rep. of 31.6 Colombia 57.1 Portugal 38.5 Poland 31.6 Zimbabwe 56.8 Germany 38.2 Canada 31.5 Zambia 52.6 Tanzania 38.2 Belarus 30.4 Mexico 51.9 Uganda 37.4 Indonesia 30.3 Nigeria 50.6 New Zealand 36.2 Romania 30.3

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    C H A P T E R 3 T h e W ea l t h o f N a t i o n s 15 Venezuela 49.1 Viet Nam 36.1 Ukraine 29.0 Ethiopia 48.6 Italy 36.0 Rwanda 28.9 Cameroon 47.7 United Kingdom 36.0 Uzbekistan 26.8 Peru 46.2 Ireland 35.9 Norway 25.8 Philippines 46.1 Israel 35.5 Finland 25.6 Russian Federation 45.6 Greece 35.4 Czech Republic 25.4 Kenya 44.5 Algeria 35.3 Belgium 25.0 Hong Kong 43.4 Australia 35.2 Sweden 25.0 Thailand 43.2 Egypt 34.4 Japan 24.9 Iran, Islamic Rep. of 43.0 Yemen 33.4 Denmark 24.7 Singapore 42.5 Switzerland 33.1 Hungary 24.4 Source: UNDP. Note: Survey dates range from 1995 to 2000 Additional Questions Look at Figure 3.1 . Question 1a) What might explain the surge of growth in the 19 th and 20 th centuries Question 1b) What might explain the rise in world growth in the 14 th century Answer 1a) Although the causes of this rise in growth are unclear, the process did seem to be triggered off by the industrial revolution in the UK and the subsequent spread of industrialization to other countries Answer 1b) The spike in the 14 th century is probably attributable to the Black Death which not only increased GDP per capita of the survivors, but also led to more recorded transactions as workers entered paid employment rather than being tied to their local lord. Look at the two charts below both showing the level of the Dow Jones index since the early 20 th Century one on a liner scale one on a log scale Question 2) which of the two charts do you think gives a fairer picture of what has happened to share prices?

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    C H A P T E R 3 T h e W ea l t h o f N a t i o n s 16 The Dow Jones Index In the 20 th Century (LINEAR SCALE) Source: EcoWin 05 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 00 05 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000 The Dow Jones Index In the 20 th Century (LOG SCALE) Source: EcoWin 05 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 00 05 25 50 100 200 400 800 1600 3200 6400 12800 Answer 2) The two charts demonstrate the very different visual impression given by log and linear scales. Note how the 1929 crash is the most extreme event in the log chart but is barely visible in the linear version. A close look at the charts below shows the key difference between log and linear scales. In a linear scale, the gap between 1000 and 2000 is half the size of that between 2000 and 4000. With a log scale, the gaps are equal so that a doubling in the value of the stock market shows up as the same movement in the chart irrespective of the starting level. More generally, any

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