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How has the U.K. stock market fared lo these past 300 years?

An historical data literacy lesson on U.K. stock prices

FRED offers some historical time series that the Bank of England has compiled, including the series shown above that tracks the price of stock market shares. The series starts way back in 1709 with the shares of the South Sea Company and the British East India Company. Other companies have been added and subtracted as they’ve entered and left the U.K. stock market. Just glancing at the graph reveals two things: First, the series is close to zero most of the time and then explodes. Second, there are wild fluctuations in recent decades.

For both these “observations,” though, there’s a mirage at work. Don’t worry: This optical illusion is common in very long time series. But let’s clear it up. Back in the 18th century, all prices, including share prices, were much lower  And when a long time series includes regular growth, recent changes are amplified while initial changes aren’t readily visible.

One way to sidestep these visual pitfalls is to use logarithms. Their big advantage is that any change you can measure on a graph, such as those mentioned above, is a change in percentages: Anywhere in the graph, one inch corresponds to the same percentage change. In this graph, the share price doesn’t look explosive at all; actually, it seems quite stable except for growth periods in the mid 19th century and second half of the 20th century. Also, the recent wild fluctuations have been tamed. (But note the blip in 1720, due to the South Sea Bubble.)

An even better way to represent the data is to remove the growth of the general price level so the growth of stock prices themselves is better captured. A tip of the hat to the Bank of England for offering a time series on the consumer price index that, remarkably, begins in 1206. By dividing share prices by this series (shown in the graph below), we can see that there are longer periods where the real share price has actually declined.

That concludes our historical data literacy lesson for today. Your homework? Convert the units in the graph below to logarithms.

How these graphs were created: For the first graph, search for “share price UK.” For the second, take the first, click on “Edit Graph,” and select units “natural logarithm.” For the third, take the first, click on “Edit Graph,” add a series by searching for “CPI UK” (selecting the one with the earliest start date), and then apply formula a/b.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CPIUKA, SPPUKQ

An economic encomium for Sub-Saharan Africa

Good news from Ethiopia, Ghana, and Rwanda

Sub-Saharan Africa has long been hindered by economic development traps: National economies have not been able to sustain significant growth for various reasons—such as high poverty leading to low savings, which  leads to low or negative economic growth. These days, there are some good reasons for optimism, as several countries have shown robust growth for a couple of decades. The FRED data in the graph above focus on three of these countries: Ethiopia, Ghana, and Rwanda, which have all more than doubled their per capita GDP in less than two decades.

Of course, not all African countries follow this pattern. But the example of the “Asian Tigers” (Hong Kong, Singapore, South Korea, and Taiwan) has shown that a few leading countries can help propel other countries forward as well. It may be that these “African Lions” are following the same strategy: concentrating on labor-intensive manufacturing and limiting agriculture to highly productive crops.*

How this graph was created: Search FRED for “Constant GDP Ethiopia” and click on the link. From the “Edit Graph” panel, use the “Add Line” tab to search for and select “Constant GDP Ghana” and “Constant GDP Rwanda.” Select “Index” as the units with a date of 1990-01-01 and click “Apply to all.”

*While we’re accentuating the positive… Ethiopia, Ghana, and Rwanda have also been celebrating some political, cultural, and resource developments.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: NYGDPPCAPKDETH, NYGDPPCAPKDGHA, NYGDPPCAPKDRWA

Whither the workers?

How the working-age population affects productive capacity

One way to measure the productive capacity of a country is to look at its working-age population. Members of this group are most likely to be available for productive employment that can sustain a country’s economic growth. The age range is generally considered to be 15 to 64, although some statistics start later. The graph above shows this population for the United States, Canada, and Japan.

Japan stands out in this trio: Its working-age population has been declining as a result of declining fertility and little immigration. These conditions make it difficult for Japan’s economy to grow. If sustained positive growth is the objective, Japan would need to improve the productivity of its smaller workforce much more than other countries with larger workforces would need to.

The story is different for the United States and Canada. They show continuous growth. While fertility rates have declined a little, immigration has helped sustain population growth. Immigrants are typically of working age, so immigration can increase the working-age population specifically. Although these populations for the United States and Canada track each other pretty well (they were almost identical in late 2016), a little bit of separation has occurred in recent years.

How this graph was created: Search FRED for “population 15-64,” check the relevant series, and click “Add to Graph.” Then change the sample to start on 1995-01-01. Click “Edit Graph,” choose units “Index” with 1995-01-01, and click on “Apply to All.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: LFWA64TTCAM647N, LFWA64TTJPM647N, LFWA64TTUSM647N


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