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Posts tagged with: "GDPC1"

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Shaking things up in China

During President Obama’s recent visit to China, even getting off the plane involved political upheaval: The New York Times described the mood as “tense” when disagreements between Chinese and U.S. officials compelled the president to use an alternative stairway to deplane Air Force One.

Chinese economic policy has also been tense for some time now, independent of their ability or willingness to accommodate a foreign 747. The graph above plots the Economic Policy Uncertainty Index from Baker, Bloom, and Davis for the U.S. and China. This index scans news articles about a country and records the frequency of phrases that connote economic policy uncertainty. When it’s high, the press is using language that suggests the government could change its regulations, spending, and/or taxes in the near future. As the authors point out, this uncertainty complicates planning and can adversely affect investment. It can also, however, reflect economic conditions themselves; as the economy sours, the political response is often uncertain as sides debate how best to respond.

Until recently, China and the U.S. tracked each other quite well, and such a connection might reflect common economic conditions in the two countries. But China did not share the U.S. experience during the 2001 recession; it shared only the rise in uncertainty. The bottom graph adds GDP growth to the mix, and the “pattern” we see has almost no pattern to it. GDP is slowing in China, but policy uncertainty seems to be hyperactive. Chinese GDP declined during the Great Recession, and since then the decline seems to have been smooth and slight. Policy language, however, has vacillated quite wildly. Perhaps President Obama should feel lucky his stairway remained in place as he descended.

How these graphs were created: Top graph: Search for “Economic Policy Uncertainty Index” and select the U.S. and China among the countries given. Convert both to a quarterly frequency for two reasons: The frequency of U.S. GDP is also quarterly, and the monthly swings in the Chinese index are so great they make it difficult to visualize the U.S. index. Bottom graph: Add two lines to the top graph: seasonally adjusted real U.S. GDP (converting it to a percentage change) and constant China GDP, which should give the U.S. dollar-denominated GDP (again, converting it to a percentage change). For both these new lines, go to the “Format” tab in the “Edit Graph” section and move the units to the right vertical axis. Note: FRED doesn’t have updated Chinese real GDP after 2014, but the latest figure from the National Bureau of Statistics in China puts growth at 6.7% in 2016:Q2, slightly lower than the 7.3% recorded in 2014, as shown in the graph.

Suggested by David Wiczer.

View on FRED, series used in this post: CHIEPUINDXM, GDPC1, RGDPNACNA666NRUG, USEPUINDXM

Measure for measure: Judging the economy

How do you know if the economy is improving? FRED has plenty of commonly used data to help you. Typically, you’d measure real gross domestic product (GDP)—in particular, its growth rate. This rate is almost always positive. Because population growth is also almost always positive, this isn’t too surprising. So FRED lets you measure real GDP per capita—that is, GDP divided by the population.

But let’s complicate matters, because economies can go through demographic transitions. In fact, because many industrialized countries now face a substantially older population, dividing GDP by the overall population may not be precise either. So, FRED lets you divide GDP by the working age population, age 15 to 64. FRED even lets you refine the measurement by considering only the working age population in the labor force—that is, by excluding those who choose not to work or who cannot work. Finally, FRED lets you measure only those who are actually working by excluding the unemployed still looking for work. (By the way, dividing real GDP by the working population corresponds to labor productivity.)

The graph above shows these five different measures of U.S. economic growth since 1948. Each has its merits, but their growth rates look remarkably similar—so much so that it may not seem worthwhile to distinguish between them. One possible exception is the last series, since the working population fluctuates much more than any of the other population measures.

How this graph was created: All five lines use real GDP, so add real GDP to the graph five times. For line 1, change units to “Percent Change from Year Ago.” For line 2, add the monthly population series, apply formula a/b, and change the units again for this new, transformed line. Repeat this for the remaining lines by searching for and selecting the other population data to divide with. Finally, use the “Format” panel to remove the many axis titles.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CLF16OV, GDPC1, LFWA64TTUSQ647S, PAYEMS, POP

A counterclaim on countercyclical policy

Keynesian theory tells us that, when economic activity falls, government expenditures should rise. That is, government expenditures should be countercyclical and lean against the business cycle. Has this happened in the U.S.? In the graph, the red line shows growth of government expenditures and the blue line shows growth of private (nongovernmental) economic activity. And it looks like when one line is high the other is low. Does this mean government expenditures are countercyclical?

Actually, this is partly an optical illusion: On average, government expenses have grown more slowly than the rest of the economy, and thus the red line is more often low and the blue line is more often high.

A better way to examine this question is with a scatter plot, shown below. Each axis represents one indicator, and each dot corresponds to a quarterly data point. If government expenses were countercyclical, the cloud of dots would have a somewhat negative slope, with more dots in the top left and bottom right quadrants than the top right and bottom left. The scatter plot actually has a congregation in the middle, which shows there’s little correlation between the public and private sectors of the economy, at least in terms of expenditures.

How these graphs were created: For the top graph: From the Domestic Income and Product release, select “Real Gross Domestic Product, Chained Dollars” and then “Quarterly”; select the GDP and government expenses series; click “Add to Graph.” In the “Edit Graph” panel, add to line 1 (GDP) the government expenditure series again and apply the formula a-b. Use “Percentage Change from Year Ago” as units for the lines and use the slider to start the data in 1953:Q2 (which is after the explosion of government expenses for the Korean War) to avoid distorting the view. For the bottom graph: Use the top graph, but use the format tab to select graph type “Scatter.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: GCEC1, GDPC1


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