GDP data provide us with one way of comparing the productivity of different nations. But it doesn’t necessarily give us an accurate picture of the standard of living in each country. For example, China, India, and Brazil each have a GDP that places them among the top ten largest economies in the world. But clearly one would not describe the average citizen in these countries as wealthy. This section describes some of the factors that make it challenging to use GDP measures to compare the standard of living of average citizens across countries.

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The previous section described the two ways of measuring GDP using total expenditures and total income in an economy. But once the value of GDP is determined, does that mean it can be used to compare the size of the overall economy between two countries? To some extent, yes, in that countries with larger GDP do produce more output based on the final value of goods and services in that country and in a particular year. Herein lies an important caveat regarding GDP measures: Nominal GDP statistics do not do a good job of factoring changes in the prices of goods and services over time, nor taking into account differences in the cost of living between countries.

To address the first issue of changing prices, the U.S. Bureau of Economic Analysis reports GDP statistics in both nominal terms as well as in real terms. Real GDP statistics adjust each year’s data to prices in a single base year (such as 2005). Therefore, real GDP does a better job of measuring actual growth in output, rather than counting the rise in prices of goods and services over time. The next chapter on inflation discusses nominal and real values in greater detail.

To address the second issue of differences in the cost of living between countries, organizations that report GDP statistics across countries, such as the World Bank’s World Development Indicators, also report GDP statistics based on purchasing-power-parity–adjusted measures, or GDP-PPP. For example, a haircut in India may cost $3, while that same haircut in Switzerland may cost $30. Since the service is the same, is it accurate to count a haircut ten times more in Switzerland than in India in terms of GDP? By using a GDP-PPP measure, countries in which prices of goods and services (especially nontraded items such as haircuts and restaurant meals) are lower than a representative base country will have their GDP numbers increased, while countries in which prices are higher than the base country will have their GDP statistics lowered.

The effect of using GDP-PPP can be substantial. Although the United States remains the world’s largest economy in terms of nominal GDP, it falls to second place behind China when GDP-PPP is used. The reason is because the cost of living in China (on average) is still lower than the cost of living in the United States. But despite this remarkable achievement by China in terms of GDP-PPP, the average Chinese citizen is much less well off than the average American. This is because aggregate GDP measures do not take into account population.

How can GDP measures better reflect a country’s population? The most common approach is to divide GDP by a country’s population, resulting in a statistic known as GDP per capita. GDP per capita is a useful measure of the relative standard of living of citizens in different countries. However, by simply dividing GDP by population, GDP per capita does not take into account the differences in wealth between the rich and poor within a country, and therefore might not fully reflect the standard of living of the typical citizen. For example, U.S. GDP per capita is about $55,000, but certainly the typical American family of four does not earn $220,000 a year. Yet, GDP per capita data are fairly easy to measure, and thus are a useful measure of relative wealth between countries.

An alternative measure of the standard of living is median household income. Being the median household means that half of all households make less and the other half make more. Using this statistic reduces the effect of outliers (i.e., the very destitute or the superrich) skewing the averages. The U.S. median household income in 2016 was about $57,000, an amount that is closer to what middle-income households make.

People around the globe have become increasingly concerned with the impact economic activity has on the natural world. These days, it is difficult to watch a nightly newscast without seeing a report about some ecological disaster or looming environmental problem. U.S. consumers, businesses, and the government spend hundreds of billions of dollars annually to protect the environment at home and abroad. Surprisingly, however, our national income and production statistics do little to account for the environmental benefits or harmful impacts of economic activity.

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In 1992 the Bureau of Economic Analysis decided to develop an experimental set of economic accounts known as the Integrated Environmental and Economic Satellite Accounts. Preliminary versions of these green GDP accounts were published in 1994, and later Congress directed the DOC to set up an outside panel of experts to study this issue in greater depth. The DOC asked the National Academy of Sciences to look at green economic accounting, which it did, appointing a select panel.

The DOC panel concluded that “extending the U.S. NIPA to include assets and production activities associated with natural resources and the environment is an important goal.”4 In terms of natural resources, these include the flow of services that are produced by environmental capital such as forests, national parks, and ocean fisheries.

4 Nordhaus and Kokkelenberg, Nature’s Numbers, pp. 2–3.

But from a consumer’s perspective, a cleaner environment also provides value. The ability to hike in parks, to suntan on clean beaches, and to swim in lakes and rivers all depend on a level of environmental quality that does not show up in our national accounts.

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In addition to addressing such concerns as environmental impacts and the value of nonmarket natural resources, the DOC panel’s recommendations highlight some of the broader shortcomings of the NIPA. For example, the national accounts ignore nonmarket transactions, investments in human capital, and the use of people’s time.

Nonmarket transactions are an important part of our everyday lives. If a maid cleans your apartment, GDP rises, but if you did the same job yourself, GDP is unaffected. The same is true for babysitting, lawn care, and car maintenance. There is one exception—NIPA already imputes (estimates) the rental value, less expenses, of owner-occupied homes and adds this to GDP.

Many people believe that the NIPA should be an index of the well-being found within our economy. In that case, it would ideally need to take into account the implications of economic activity the DOC panel noted and more, perhaps including data on life expectancy; business spending on research and development; the stock of human capital, including education and health; greenhouse gas emissions; income distribution; poverty rates; and unemployment rates.

The informal economy (the underground or black market) is a large unmeasured component of our economy. The informal economy can be as simple as the money earned from a garage sale or from items sold on eBay that are not reported to the IRS. It also includes transactions dealing with illegal goods and services, such as drugs, prostitution, or unlicensed gambling. Finally, the informal economy includes the income earned by undocumented residents—those working on farms, factories, or restaurants for cash, or workers hired for housekeeping or babysitting services who are easily paid under the table. The size of the informal economy in the United States is estimated at around 10% of GDP. This is relatively small compared to many developing countries that can have an informal economy valued at as much as 50% of their GDP.

The effects of the informal economy can be positive and negative. On the upside, people working in the informal economy are generating and spending income, contributing to national economic activity. Countries with large informal markets have total output that is significantly larger than what is officially reported in their GDP statistics. On the downside, those working in the informal economy do not pay much if any taxes, placing a greater tax burden on the rest of society. Also, the informal economy is less regulated, which increases the probability of corruption and crime.

Despite these shortcomings in the NIPA measurements, it is important to keep the NIPA’s original purpose in mind. As the DOC panel noted,

The modern national income and product accounts are among the great inventions of the twentieth century. Among other things, they are used to judge economic performance over time, to compare the economies of different nations, to measure a nation’s saving and investment, and to track the business cycle. Much as satellites in space can show the weather across an entire continent, the national accounts can give an overall picture of the state of the economy.5

5 Nordhaus and Kokkelenberg, Nature’s Numbers, p. 12.

The NIPA has served us well. Still, making adjustments to account for various environmental and other nonmarket considerations might provide us with an even better picture of the health of our economy. But we must keep in mind that an aggregate measure of the economy cannot be all things to all people. As we add complexity to an already complex undertaking, the NIPA may lose some effectiveness as a measure of economic activity, as pointed out earlier in the discussion of environmental quality. This is a difficult balancing act facing policymakers.

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The NIPA allow us to track business cycles, compare the domestic economy with that of other nations, and take a crude measure of our standard of living. In the next chapter, we will see how two other important policy variables, unemployment and inflation, are measured.

The next several chapters will focus on developing explanations of short-term movements in the business cycle and long-term economic growth (the trend line in Figure 2). If we can understand why upturns and downturns occur, we may be able to devise policies that reduce the severity of business cycle swings while promoting economic growth. These investigations and policy objectives form the essence of modern macroeconomic analysis.