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Cold Test / Graphs


Grade Range Class Avg = 82
100-96 A+ 95-91 A
88-90 A- 85-97 B+
81-84 B 76-80 B-
68-75 C+ 64-67 C
59-63 C- 54-58 D+
50-54 D 50 F

Closed Book | 90 minutes total
Questions 1-6 are worth 15 points, Question 7 is worth 10 points

Read all the questions before you start. You have enough time to write several sentences for each, but make your main point in the first sentence. USE JARGON – precise use of appropriate terminology is central in any subject. Please answer on a separate sheet of paper.

Note that I set 14 points as the baseline for a good answer. You had to go above and beyond the call of duty to get 15 points, and only for a few answers across all 40×7 = 280 questions did I give 16 points.

1. CPI
a. What is it?

The Consumer Price Index provides a monthly update of the cost of purchasing a standardized basket of goods and services consumed by urban consumers (who comprise 94% of the US population). The Bureau of Labor Statistics compiles this list and then reprices it every month. The cost of this basket in Montht is then compared to the base period Month0 to give CPI = 100 * Montht / Month0. The CPI covers core areas such as housing, food and beverages, apparel and medical services. Sub-series of the CPI are available in tremendous detail, with 200 main series and many sub-series, available on a regional basis.

Details (FYI): The underlying basket is updated on a rolling basis with about 24,000 diaries and 48,000 interviews over a 2-year period. A separate survey is used to track where people make their purchases so as to reflect actual consumer habits. The underlying CPI contains, with the monthly update collecting 80,000 prices. See the BLS FAQ for additional details.

b. Is it a good measure for you?

Because the basket is constructed to represent an average consumer where at least one household member is employed, it likely won’t capture what matters for retirees or full-time students, for whom (respectively) healthcare and tuition are likely higher than average. (These examples are deliberate, because prices for these have been rising faster than the CPI so a more “appropriate” basket may actually behave differently from the average. Likewise, if you live in San Francisco then housing prices may be rising much faster than in the country as a whole.)
The CPI also fails to capture substitution effects, exaggerating the impact of the increase in price of a specific item (if the of Pink Lady apples rises while that of Red Delicious apples falls). It may lag changes in shopping habits, and find it hard to capture the impact of online shopping, and will miss new goods and (except for a few items for which explicit corrections are made) changes in quality. All told, these mean the CPI will overstate the rise in the “true” cost of living, by perhaps 1% point.

2. U
a. Are you U? Why is that an appropriate classification?
b. What does our “headline” measure of U miss? (FYI, technically, it’s called U-3.)

a. Are you U? Why is that an appropriate classification?
U is Unemployed and seeks to measure how many people don’t have a job but would like to work. To make that concrete, the BLS will ask whether you have looked for a job in the past 4 weeks, sent out a resume. However, the presumption is that if you are a full-time student then that is your primary focus. So even if you are actively searching for a summer or post-graduation job, you would be classed as NILF (not-in-the-labor-force) rather than U (unemployed) or E (employed). Depending on the detailed phrasing –
which question is asked first – you might show up as “employed” if you are working part-time and the surveyor doesn’t ask followup questions. But if they ask your age then they should ask if you’re a student and then still count you as NILF. After all, it’s not that your primary focus is work and school is just a side thing…

b. What does our “headline” measure of U miss? (FYI, technically, it’s called U-3.)
A single number can only capture so much of something as complex as the labor market. So “headline” U will not capture discouraged workers, who have given up looking and so fail the “searched in the last 4 weeks” test. It will also undercount marginally attached workers, those who float in and out of employment. Supplemental questions try to ferret out these categories. The U/E/NILF categorization treats part-time and full-time workers identically, and we surely care about those working part-time because they can’t find a full-time job. In the opposite direction, some individuals are working undesired overtime or want a part-time job but can only find full-time work. And how should we count people working multiple jobs?
In a different direction, we really don’t want to worry about people who quit their job in anticipation (realistic or not) of finding a better job (which may be to co-locate with a significant friend). It’s hard to get at “frictional U” through surveys. There’s also “structural U” due to changes in the economy (e.g., the closing of the principal employer in a small town). That is potentially the most costly from a human perspective, but is also the hardest to address in policy terms. Finally there’s “cyclical U” that will rise and fall with poor/good GDP growth. That’s our focus in Econ 102.
The first part is more important, but a realistic answer is likely to focus on only one of these two broad areas. The second qualitative focus is worth almost full points.

3. Y = _ + ….
a. Provide the definitions, elaborate a phrase on each component.
b. What is / is not in “I”?

a. Provide the definitions, elaborate a phrase on each component.
Y = C + I + G + X – IM, the final demand approach to measuring Gross Domestic Product. Here C is personal consumption expenditures on (new) goods, services. This includes rental housing and (while we did not delve into it) imputed rent on owner-occupied housing. (The BLS treats someone living in a house they [or their bank!] owns as renting from themselves.) I is gross private domestic investment, which includes business fixed investment and new residential construction. G is government purchases of goods and services, which does not include transfers such as Social Security. Most of “G” is local government, not Federal – Leviathan is fed by children (public schools), fire and police. At the Federal level the Department of Defense is the biggest component, larger than all the rest of the “swamp” but highly resisted to being drained. X and IM are exports and imports of goods and services. The US runs a trade deficit on goods, a surplus on services.

b. What is / is not in “I”?
Investment does NOT include the shifting around assets. While you may use that term in a Finance class, in macroeconomics drawing down a bank deposit to buying a bond or stock or an existing house is not “I”. However, any broker fees (large for housing) would show up under C as the purchase of the associated service.

4. g
a. What does not matter in the long run, particularly for the US and other developed countries?
b. What does matter in the long run? What’s happened to that component since WWII?

a. What does not matter in the long run, particularly for the US and other developed countries?
In the long run output is a function of inputs and (total factor) productivity, Y=f(K,L,TFP). As a first approximation with US levels, population growth cancels out, because we’re interested in per capita output and not total GDP. Likewise, Kapital accumulation suffers from diminishing returns, particularly for a high-income economy such as that of the US. Go from no computers to some can boost the economy of South Africa, but going from a lot to even more doesn’t do much for the US. In addition, the higher K is, the more that we are investing (in the I sense above) just to cover depreciation.

b. What does matter in the long run? What’s happened to that component since WWII?In the long run, therefore, ALL that matters is TFP. “Big push” investment-oriented industrialization can only take an economy so far. Focusing on rebuilding is one reason that the US, Europe and Japan grew so quickly in the 1950s and 1960s, but that factor diminished over time. All that matters now is productivity, and that too seems to have slowed as the transportation, power and information revolutions seem to have picked all the low-hanging fruit. In any event, what happens to TFP will be perhaps the single most important thing in your lifetimes.

5. π
a. Why does it matter? When does it typically not matter?
b. If π = 2%, year-over-year, and the yield on 1-year bonds is i = 1.9% what is the real return?

a. Why does it matter? When does it typically not matter?
Pi “π” is inflation, typically measured as the rate of increase in the CPI. At low levels of 0%-2% that typify the US economy since 2008 π doesn’t matter a lot. That’s because on average wages track inflation, so that real wages don’t suffer. In addition, interest rates generally reflect expected inflation. An unexpected increase in inflation hurts creditors and helps debtors (with +4% inflation the real value of a mortgage payment falls by 50% after 18 years). Of course there’s Venezuela and Zimbabwe, but hyperinflation is more a symptom of other problems than a cause.

b. If π = 2%, year-over-year, and the yield on 1-year bonds is i = 1.9% what is the real return
We care about real not nominal values. That is, we want to know how much we can buy with our annual income, not how many dollars we are getting. With low levels of inflation, you can calculate this using percentage growth with real = nominal – π. Here that means with a nominal 1-year interest rate of 2.0%, the real return is 1.9% – 2.0% = -0.1% so that at the end of a year we are slightly behind. Similarly, if wages are rising at 2.6% (late 2017-early 2018) then real wages are rising at a mere 0.6% pa. Even with compounding, that’s only 6% over a decade, not enough to be readily felt by the average American – and the minimum wage has not risen at all, so many Americans are seeing an erosion of their standard of living. Of course that’s one of the motivations for Marc Levinson to write An Extraordinary Time.

6. China and Trade

Under Mao Zedong the Chinese economy was closed, an autarky. They couldn’t trade with the US or Europe due to the Cold War. They couldn’t trade with the USSR after 1959 due to many bilateral that culminated in a brief “hot” war in 1969. Then in 1976 Mao died, and by 1980 a leadership group headed by Deng Xiaoping was in firm control. Mao focused on national survival. Deng and his peers focused on economic growth. Over the next 2 decades they gradually enabled the country to engage in international trade, beginning with a handful of Special Economic Zones in the 1980s, a stable exchange rate from 1994, and accession to the World Trade Organization in December 2001.
a. What would we expect China to import? export? Why?
b. So what did they get out of it? What did we get out of it, good and bad?

a. What would we expect China to import? export? Why?

We want to think about specialization to take advantage of comparative advantage. As a labor-abundant economy China wants to specialize in that area and to do so must import capital- and skill-intensive goods and services where it is (comparatively) inefficient. So we would expect China to be exporting garments and shoes and iPhones while importing Gorilla Glass (the high-tech material used for iPhone screens, manufactured in Kentucky) and passenger jets (Boeing, with production in Washington State).

b. So what did they get out of it? What did we get out of it, good and bad?

We enhance our ability to specialize and hence raise (average) productivity and incomes. At the macro level, importing labor-intensive goods has allowed us to reallocate labor and capital to higher-productivity sectors (and to non-tradable sectors, such as healthcare and lawn services). That means higher incomes for workers and businesses. On the flip side, the average American has seen the cost of clothing fall by $200 per year ($800 for a family of four), a real boon. Meanwhile we’ve been able to expand other sectors of our economy, such as healthcare.
The downside is that these are long-run gains. Imports that led to the closing of a local factory can result in structural unemployment made worse because when the main employer in a small town closes, it becomes much harder to sell your house and move to where jobs are better. Ditto the erosion of skills – and of course factory owners scream, too. These latter costs tend to be geographically concentrated and individually large and sudden in their occurrence, while the gains tend to be widespread and (very) large in the aggregate while individually small and accumulated only gradually.
Now empirically it’s hard to disentangle the impact of trade and of on-going productivity increases that cut the number of workers needed in manufacturing. Trade also leads to interesting questions in political economy.

7. Bonus Question: Thinking About Data – You’re in Beijing, meeting with economists there to discuss China’s domestic macroeconomic trends. For better and for worse you have the graph below.
a. What can you learn from this graph?
b. What is hard to tell from the graph? How might you make it more useful? Units, etc, etc…

It shouldn’t need mentioning, but the “answer” below is way beyond the scope of what you could/should do in the context of a single question on a 90-minute exam. It took me a solid hour to create and paste in the following graphs. However, thinking about data, what it means, and how to present it is really important. I want you to demonstrate sensitivity to this. To repeat: a bonus question is not the place for an extended treatment such as that below!

Here is the graph with the (i) seasonally adjusted and (ii) unadjusted data. I didn’t include the slider, but add a second version that focuses on a particular time period to see the variation. I also added (iii) data in Chinese currency (officially the Renminbi 人民币 but more commonly simple the Chinese yuan 元). Because the exchange rate between the US$ and the RMB hasn’t varied much, the two are almost the same. If you’re Chinese, however, then “almost” isn’t close enough, because that easily represents a 元10 billion discrepancy! For the purposes of thinking about trade issues in the context of Econ 102, the trends and levels are qualitatively identical. That would not be true if we picked a country pair where the bilateral exchange rate was volatile. Anyway, the monthly data are very volatile and so in this case using seasonal data makes it much easier to eyeball.

However, because this is a long time trend that goes from fairly small to very large, it’s not possible to eyeball growth rates. There are two ways of handling that. One (duh) is to calculate a year-over-year growth rate. As we can see, there are some strong periods and some weak ones, but overall growth has slowed a lot and between early 2015 and the end of 2016 was on average negative. We can also see (i) the impact of the Asian Financial Crisis that began in July 1997 (and coincided at the start with a recession in Japan). We also see the Great Recession in 2008-2009 and slow growth following the collapse of the bubble in 2000. The 1996 slowdown reflected domestic Chinese factors, including an appreciation of the RMB.

Another way of presenting data over a long time trend is a log scale. This helps us eyeball periods of rapid and slow increases, and (unlike with growth rates) gauge the cumulative impact, which is a substantial overall increase. If we look at the graph, we can see that (i) there wasn’t much change in 1992-93, a big jump (1 year for one increment) in 1994, then slower growth (5 years for one increment), then 2.5 years (through early 2003), 1 year and then 2 years for the next 2 increments, then 4 years (through early 2005), and now after 12 years exports have yet to grow another increment. Now the dollar amounts are large,
since the total is near enough $200 billion dollars, but the change is small in percentage terms. Whether you want to look at the former or the latter is a function of why you’re looking at the data.

Then there’s the question of price increases and overall economic growth. One way is to look at exports to China versus China’s GDP. One awkward aspect is that the data aren’t both seasonally adjusted – FRED only provides a handful of GDP series for China. But while we see a rise and fall, the bottom line is that most of the long-run rise in US exports to China reflect the growth of the Chinese market. How could it be otherwise? Well, China could be importing more overall, so growing imports amplified by a growing economy. This graph by the way uses nominal GDP in RMB and nominal exports in RMB.

Next we can look at US exports to China relative to total US exports. In 1992 China was still very poor; not today! So we would expect exports to comprise a modest share at the start, and rise over time – which is what we observe. In 1992 only 2% of our exports went to China. Now it’s 15%.

Finally, there’s the politically important question of bilateral trade. As an economist, I’m fundamentally not interested in that. Instead I want to know whether aggregate US trade is balanced. But those inside the Beltway, and most of our news media, don’t view things that way. Of course this graph is seasonally adjusted, but not with a log scale…you now know how to adjust.