The pace of productivity growth has been rising again, but now it seems to be lifting fewer boats. If you take into account the value of employee benefits, such as health care, the contrast is a little less stark. But, whatever the measure, it seems clear that only the most skilled workers have seen their pay packets swell much in the current economic expansion.
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The fruits of productivity gains have been skewed towards the highest earners, and towards companies, whose profits have reached record levels as a share of GDP. Even in a country that tolerates inequality, political consequences follow when the rising tide raises too few boats. The impact of stagnant wages has been dulled by rising house prices, but still most Americans are unhappy about the economy. The White House professes to be untroubled. He is right, but his claim is misleading, since the median worker—the one in the middle of the income range—has done less well than the average, whose gains are pulled up by the big increases of those at the top.
Privately, some policymakers admit that the recent trends have them worried, and not just because of the congressional elections in November. The statistics suggest that the economic boom may fade. Americans still head to the shops with gusto, but it is falling savings rates and rising debts made possible by high house prices , not real income growth, that keep their wallets open.
A bust of some kind could lead to widespread political disaffection. Eventually, the country's social fabric could stretch.
America is nowhere near Brazil yet see chart 1. Despite a quarter century during which incomes have drifted ever farther apart, the distribution of wealth has remained remarkably stable. The richest Americans now earn as big a share of overall income as they did a century ago see chart 2 , but their share of overall wealth is much lower. Indeed, it has barely budged in the few past decades. The elites in the early years of the 20th century were living off the income generated by their accumulated fortunes. Today's rich, by and large, are earning their money.
The rise of the working rich reinforces America's self-image as the land of opportunity. But, by some measures, that image is an illusion. In America about half of the income disparities in one generation are reflected in the next.
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In Canada and the Nordic countries that proportion is about a fifth. It is not clear whether this sclerosis is increasing: the evidence is mixed. Many studies suggest that mobility between generations has stayed roughly the same in recent decades, and some suggest it is decreasing. Even so, ordinary Americans seem to believe that theirs is still a land of opportunity. The proportion who think you can start poor and end up rich has risen 20 percentage points since That helps explain why voters who grumble about the economy have nonetheless failed to respond to class politics.
Americans tend to blame their woes not on rich compatriots but on poor foreigners. More than six out of ten are sceptical of free trade. A new poll in Foreign Affairs suggests that almost nine out of ten worry about their jobs going offshore. Congressmen reflect their concerns. Though the economy grows, many have become vociferous protectionists. Other rich countries are watching America's experience closely. For many Europeans, America's brand of capitalism is already far too unequal. Such sceptics will be sure to make much of any sign that the broad middle-class reaps scant benefit from the current productivity boom, setting back the course of European reform even further.
The conventional tale is that the changes of the past few years are simply more steps along paths that began to diverge for rich and poor in the Reagan era. During the s and s, the halcyon days for America's middle class, productivity boomed and its benefits were broadly shared. The gap between the lowest and highest earners narrowed. After the oil shocks, productivity growth suddenly slowed.
A few years later, at the start of the s, the gap between rich and poor began to widen. The exact size of that gap depends on how you measure it. Look at wages, the main source of income for most people, and you understate the importance of health care and other benefits. Look at household income and you need to take into account that the typical household has fallen in size in recent decades, thanks to the growth in single-parent families. Look at statistics on spending and you find that the gaps between top and bottom have widened less than for income.
But every measure shows that, over the past quarter century, those at the top have done better than those in the middle, who in turn have outpaced those at the bottom.
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The gains of productivity growth have become increasingly skewed. If all Americans were set on a ladder with ten rungs, the gap between the wages of those on the ninth rung and those on the first has risen by a third since Economists have long debated why America's income disparities suddenly widened after The consensus is that the main cause was technology, which increased the demand for skilled workers relative to their supply, with freer trade reinforcing the effect.
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A circle represents a group as a whole. Figure 6 shows how the U. The information is first conveyed with numbers in Table 4 , and then in three pie charts. The first column of Table 4 shows the total U. Columns 2—4 categorize the total in terms of age groups—from birth to 18 years, from 19 to 64 years, and 65 years and above. In columns 2—4, the first number shows the actual number of people in each age category, while the number in parentheses shows the percentage of the total population comprised by that age group.
In a pie graph, each slice of the pie represents a share of the total, or a percentage. The three pie graphs in Figure 6 show that the share of the U. The pie graphs allow you to get a feel for the relative size of the different age groups from to to , without requiring you to slog through the specific numbers and percentages in the table. Some common examples of how pie graphs are used include dividing the population into groups by age, income level, ethnicity, religion, occupation; dividing different firms into categories by size, industry, number of employees; and dividing up government spending or taxes into its main categories.
A bar graph uses the height of different bars to compare quantities. Table 5 lists the 12 most populous countries in the world. Figure 7 provides this same data in a bar graph. The height of the bars corresponds to the population of each country. Although you may know that China and India are the most populous countries in the world, seeing how the bars on the graph tower over the other countries helps illustrate the magnitude of the difference between the sizes of national populations.
Bar graphs can be subdivided in a way that reveals information similar to that we can get from pie charts. Figure 8 offers three bar graphs based on the information from Figure 6 about the U. Figure 8 a shows three bars for each year, representing the total number of persons in each age bracket for each year. Figure 8 b shows just one bar for each year, but the different age groups are now shaded inside the bar.
In Figure 8 c , still based on the same data, the vertical axis measures percentages rather than the number of persons. It is sometimes easier for a reader to run his or her eyes across several bar graphs, comparing the shaded areas, rather than trying to compare several pie graphs. Figure 7 and Figure 8 show how the bars can represent countries or years, and how the vertical axis can represent a numerical or a percentage value. Bar graphs can also compare size, quantity, rates, distances, and other quantitative categories. Now that you are familiar with pie graphs, bar graphs, and line graphs, how do you know which graph to use for your data?
Pie graphs are often better than line graphs at showing how an overall group is divided. However, if a pie graph has too many slices, it can become difficult to interpret. Bar graphs are especially useful when comparing quantities. For example, if you are studying the populations of different countries, as in Figure 7 , bar graphs can show the relationships between the population sizes of multiple countries. Not only can it show these relationships, but it can also show breakdowns of different groups within the population.
A line graph is often the most effective format for illustrating a relationship between two variables that are both changing. For example, time series graphs can show patterns as time changes, like the unemployment rate over time. Line graphs are widely used in economics to present continuous data about prices, wages, quantities bought and sold, the size of the economy.
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Graphs not only reveal patterns; they can also alter how patterns are perceived. To see some of the ways this can be done, consider the line graphs of Figure 9 , Figure 10 , and Figure These graphs all illustrate the unemployment rate—but from different perspectives. Suppose you wanted a graph which gives the impression that the rise in unemployment in was not all that large, or all that extraordinary by historical standards. You might choose to present your data as in Figure 9 a.
Figure 9 a includes much of the same data presented earlier in Figure 5 , but stretches the horizontal axis out longer relative to the vertical axis.
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By spreading the graph wide and flat, the visual appearance is that the rise in unemployment is not so large, and is similar to some past rises in unemployment. Now imagine you wanted to emphasize how unemployment spiked substantially higher in In this case, using the same data, you can stretch the vertical axis out relative to the horizontal axis, as in Figure 9 b , which makes all rises and falls in unemployment appear larger. A similar effect can be accomplished without changing the length of the axes, but by changing the scale on the vertical axis. Another way to alter the perception of the graph is to reduce the amount of variation by changing the number of points plotted on the graph.
Figure 10 e shows the unemployment rate according to five-year averages. By averaging out some of the year- to-year changes, the line appears smoother and with fewer highs and lows. In reality, the unemployment rate is reported monthly, and Figure 11 f shows the monthly figures since , which fluctuate more than the five-year average. Figure 11 f is also a vivid illustration of how graphs can compress lots of data. The graph includes monthly data since , which over almost 50 years, works out to nearly data points.
Reading that list of data points in numerical form would be hypnotic. You can, however, get a good intuitive sense of these data points very quickly from the graph. A final trick in manipulating the perception of graphical information is that, by choosing the starting and ending points carefully, you can influence the perception of whether the variable is rising or falling. The original data show a general pattern with unemployment low in the s, but spiking up in the mids, early s, early s, early s, and late s. In a pie chart with many small slices and one large slice, someone must decided what categories should be used to produce these slices in the first place, thus making some slices appear bigger than others.
If you are making a bar graph, you can make the vertical axis either taller or shorter, which will tend to make variations in the height of the bars appear more or less. Being able to read graphs is an essential skill, both in economics and in life. A graph is just one perspective or point of view, shaped by choices such as those discussed in this section.
Do not always believe the first quick impression from a graph. View with caution. Math is a tool for understanding economics and economic relationships can be expressed mathematically using algebra or graphs.
The slope of a line is the same at any point on the line and it indicates the relationship positive, negative, or zero between two economic variables. Economic models can be solved algebraically or graphically. Graphs allow you to illustrate data visually. They can illustrate patterns, comparisons, trends, and apportionment by condensing the numerical data and providing an intuitive sense of relationships in the data. A line graph shows the relationship between two variables: one is shown on the horizontal axis and one on the vertical axis.
A pie graph shows how something is allotted, such as a sum of money or a group of people. The size of each slice of the pie is drawn to represent the corresponding percentage of the whole. A bar graph uses the height of bars to show a relationship, where each bar represents a certain entity, like a country or a group of people. The bars on a bar graph can also be divided into segments to show subgroups. Any graph is a single visual perspective on a subject. The impression it leaves will be based on many choices, such as what data or time frame is included, how data or groups are divided up, the relative size of vertical and horizontal axes, whether the scale used on a vertical starts at zero.
Thus, any graph should be regarded somewhat skeptically, remembering that the underlying relationship can be open to different interpretations. Skip to content Increase Font Size. You will need to know: What a function is How to interpret the equation of a line i. Algebraic Models Often economic models or parts of models are expressed in terms of mathematical functions. For example, suppose your GPA was determined as follows: This equation states that your GPA depends on three things: your combined SAT score, your class attendance, and the number of hours you spend studying.
Review Questions Name three kinds of graphs and briefly state when is most appropriate to use each type of graph. What is slope on a line graph? What do the slices of a pie chart represent? Why is a bar chart the best way to illustrate comparisons?
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