3. (a) We saw in Chapter 4 that the TFP for Brazil is about 0.43 (=43%). Briefly and clearly explain what this number 0.43 tells us. O TFP refers to Total Factor Productivity of a nation, and it measures how effective is an economy by applying all factors of production. At the given question, the 0.43 TFP for Brazil refers to the quantity produced using 100% of inputs. (b) Relative to the USA, Argentina's y = 0.30 and k = 0.18. Calculate its TFP (Ā) using the production model we studied (round to the 2nd decimal place). y=Ak1/3 0.30= A*(0.18)¹3 A= 3.33333 A=3.33

Principles of Microeconomics
7th Edition
ISBN:9781305156050
Author:N. Gregory Mankiw
Publisher:N. Gregory Mankiw
Chapter18: The Markets For The Factor Of Production
Section: Chapter Questions
Problem 8PA
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Related questions
Question
Cheep
flowing
If this were true, how would firms and entrepreneurs respond? They would ha
incentives to move capital out of rich countries, where the return to capital is low.
into poor countries, where the return to capital is supposed to be high. And yet the
are not the directions of capital flows that we see in the data. Instead, recall from C
ter 2, for example that the United States has nun very large trade deficits for most
the past three decades. And in fact, China has an enormous trade surplus. The c
nese are saving more than they are investing, and much of that difference is
to the United States. Capital is flowing "backward" relative to what the
Figure 4.4 would suggest. Hence, the Lucas question: Why doesn't capital flow from
86 Chapter 4 A Model of Production
simple s
ductivity
story i
rich to poor countries?
y across coun
y useful
...
The short answer is that the simple production model with no differences in t
countries is misguided. We will pursue this explanation in detail belo
mot insight into the explanation, however, is provided in a recent paper b
Francesco Casell of the London School of Economics and James Feyrer of Dartmou
function to measure the marginal product of capital directly for many countries around
College Caselli and Fevrer use data on GDP. capital, and the shape of the production
the world. What they find is striking: the marginal product of capital is quite simila
across a range of countries In fact, the marginal product in rich countries is slicht
more than the marginal product in poor countries, at 8.4 and 6.9 percent, respectively
The puzzle, then, is not why capital fails to flow to poor countries. The puzzle is, rathe
why the marginal product of capital in poor countries is not much higher, given that the
have so little capital. A key part of the explanation turns out to be that poor countries
12
have low levels of the productivity parameter, as we discuss next.5
Productivity Differences: Improving the Fit of the Model
Recent research in macroeconomics has employed the production model in a
different way to explain differences in incomes across countries. This approach is
based on the up-to-now mysterious parameter A. Recall our original produc
tion function:
Y = F(K,L) = AK 1/312/3.0s Theod
If a country has a high value of A, it will have a higher level of output for any
given values of K and L. What is A? We can interpret it as an efficiency a
productivity parameter: it measures how productive countries are at using the
factor inputs (in this case K and L) to produce output. For this reason, A is often
referred to as total factor productivity, or TFP.7
5 For more details related to this case study, see Robert E. Lucas Ir.. "Why Doesn't Capital Flow from Rich
Poor Countries?" American Economic Review Papers and Proceedings, vol. 80 (May 1990), pp. 92-96; and France
Caselli and James Feyrer, "The Marginal Product of Capital," Quarterly Journal of Economics, vol. 122 (May 20
Pp. 535-68
*It is also sometimes called multifactor productivity.
Gone Too Far?" in NBER Macroeconomics Annual, Ben Bernanke and Julio Rotemberg, eds. (Cambridge, Ma
Sec, for example, Peter Klenow and Andrés Rodríguez, "The Neoclassical Revival in Growth Economics He
More Output per Worker Than Others?" Quarterly Journal of Economics (February 1999), pp. 83-116.
Press, 1997), pp. 73-102; and Robert E. Hall and Charles I. Jones, "Why Do Some Countries Produce So Ma
4.3 Analyzing the Production Model 87
Now recall how this parameter shows up in the equilibrium of our production
model:
y-Aus
What we have seen so far is that if 7-1 for all countries, the model predicts
(4.10)
that most countries should be substantially richer than they are. One way of
explaining why they are not so rich, then, is by assigning them values of A that
are less than 1. Countries can be rich either because they have a high level of
capital per person or because they use their capital and labor very efficiently and
therefore exhibit a high level of TFP (Ā).
An important limitation on our ability to implement the production model
with TFP is that we have no independent measure of this efficiency parameter.
For capital, we could count the number of machines, factories, computers, and so
on in the economy, but for TFP there is nothing comparable we can do.
Instead, we exploit the fact that we do possess data on per capita GDP and
capital per person. That is, we have data on every term in equation (4.10) other
than TFP. As a way of moving forward, then, we can assume our model is correct
and calculate the level of TFP for each country that would be needed to make
equation (4.10) hold exactly.
This is best understood in the context of an example. Recall from Table 4.3
that Italy's capital per person is equal to 0.80 times the U.S. level but its GDP is
only about 0.68 times the U.S. level. Now we take this information and apply it
to equation (4.10). That is, we compute
A=
(4.11)
Thus for Italy is equal to 0.73 times the U.S. level, since 0.68/(0.80)1/3=0.73.
It must be the case that Italy is significantly less efficient in using its machines
than the United States is, at least if the model is correct.
Because we don't have independent measures of A but rather compute it assum-
ing the model holds, we can also think of A as a measure of how big the gap is
between our model and the data. In addition to being called TFP, therefore, A
is sometimes also referred to as "the residual" or "a measure of our ignorance."
Table 4.4 shows the TFP measures for the same countries as in Table 4.3. Per
apita GDP in the first column is equal to the product of capital per person (raised
to the 1/3 power) in the second column and "implied TFP" in the third. As we saw
earlier, if countries differed only in terms of capital per person, we would expect
the t countries to be much richer. The fact that they are not suggests that
poorest
they must have TFP levels that are substantially below that in the United States.
For example, given its capital per person, we would expect China to have a per
capita income of about 65 percent of the U.S. level if its TFP were the same as that
of the United States. Instead, its income is only 28 percent of the U.S. level. Our
model suggests that the way to understand China's lower income is that its TFP
is only about 0.43 times the U.S. level. So if we gave China the same amount of
capital per person as the United States, we would still expect its per capita GDP
to be only 43 percent of that in the United States.
The comparison between China and the United States is shown graphically in
Figure 4.6. With a TFP level equal to about 43 percent of the U.S. level, China's
production function is shifted down substantially relative to the U.S. production
Transcribed Image Text:Cheep flowing If this were true, how would firms and entrepreneurs respond? They would ha incentives to move capital out of rich countries, where the return to capital is low. into poor countries, where the return to capital is supposed to be high. And yet the are not the directions of capital flows that we see in the data. Instead, recall from C ter 2, for example that the United States has nun very large trade deficits for most the past three decades. And in fact, China has an enormous trade surplus. The c nese are saving more than they are investing, and much of that difference is to the United States. Capital is flowing "backward" relative to what the Figure 4.4 would suggest. Hence, the Lucas question: Why doesn't capital flow from 86 Chapter 4 A Model of Production simple s ductivity story i rich to poor countries? y across coun y useful ... The short answer is that the simple production model with no differences in t countries is misguided. We will pursue this explanation in detail belo mot insight into the explanation, however, is provided in a recent paper b Francesco Casell of the London School of Economics and James Feyrer of Dartmou function to measure the marginal product of capital directly for many countries around College Caselli and Fevrer use data on GDP. capital, and the shape of the production the world. What they find is striking: the marginal product of capital is quite simila across a range of countries In fact, the marginal product in rich countries is slicht more than the marginal product in poor countries, at 8.4 and 6.9 percent, respectively The puzzle, then, is not why capital fails to flow to poor countries. The puzzle is, rathe why the marginal product of capital in poor countries is not much higher, given that the have so little capital. A key part of the explanation turns out to be that poor countries 12 have low levels of the productivity parameter, as we discuss next.5 Productivity Differences: Improving the Fit of the Model Recent research in macroeconomics has employed the production model in a different way to explain differences in incomes across countries. This approach is based on the up-to-now mysterious parameter A. Recall our original produc tion function: Y = F(K,L) = AK 1/312/3.0s Theod If a country has a high value of A, it will have a higher level of output for any given values of K and L. What is A? We can interpret it as an efficiency a productivity parameter: it measures how productive countries are at using the factor inputs (in this case K and L) to produce output. For this reason, A is often referred to as total factor productivity, or TFP.7 5 For more details related to this case study, see Robert E. Lucas Ir.. "Why Doesn't Capital Flow from Rich Poor Countries?" American Economic Review Papers and Proceedings, vol. 80 (May 1990), pp. 92-96; and France Caselli and James Feyrer, "The Marginal Product of Capital," Quarterly Journal of Economics, vol. 122 (May 20 Pp. 535-68 *It is also sometimes called multifactor productivity. Gone Too Far?" in NBER Macroeconomics Annual, Ben Bernanke and Julio Rotemberg, eds. (Cambridge, Ma Sec, for example, Peter Klenow and Andrés Rodríguez, "The Neoclassical Revival in Growth Economics He More Output per Worker Than Others?" Quarterly Journal of Economics (February 1999), pp. 83-116. Press, 1997), pp. 73-102; and Robert E. Hall and Charles I. Jones, "Why Do Some Countries Produce So Ma 4.3 Analyzing the Production Model 87 Now recall how this parameter shows up in the equilibrium of our production model: y-Aus What we have seen so far is that if 7-1 for all countries, the model predicts (4.10) that most countries should be substantially richer than they are. One way of explaining why they are not so rich, then, is by assigning them values of A that are less than 1. Countries can be rich either because they have a high level of capital per person or because they use their capital and labor very efficiently and therefore exhibit a high level of TFP (Ā). An important limitation on our ability to implement the production model with TFP is that we have no independent measure of this efficiency parameter. For capital, we could count the number of machines, factories, computers, and so on in the economy, but for TFP there is nothing comparable we can do. Instead, we exploit the fact that we do possess data on per capita GDP and capital per person. That is, we have data on every term in equation (4.10) other than TFP. As a way of moving forward, then, we can assume our model is correct and calculate the level of TFP for each country that would be needed to make equation (4.10) hold exactly. This is best understood in the context of an example. Recall from Table 4.3 that Italy's capital per person is equal to 0.80 times the U.S. level but its GDP is only about 0.68 times the U.S. level. Now we take this information and apply it to equation (4.10). That is, we compute A= (4.11) Thus for Italy is equal to 0.73 times the U.S. level, since 0.68/(0.80)1/3=0.73. It must be the case that Italy is significantly less efficient in using its machines than the United States is, at least if the model is correct. Because we don't have independent measures of A but rather compute it assum- ing the model holds, we can also think of A as a measure of how big the gap is between our model and the data. In addition to being called TFP, therefore, A is sometimes also referred to as "the residual" or "a measure of our ignorance." Table 4.4 shows the TFP measures for the same countries as in Table 4.3. Per apita GDP in the first column is equal to the product of capital per person (raised to the 1/3 power) in the second column and "implied TFP" in the third. As we saw earlier, if countries differed only in terms of capital per person, we would expect the t countries to be much richer. The fact that they are not suggests that poorest they must have TFP levels that are substantially below that in the United States. For example, given its capital per person, we would expect China to have a per capita income of about 65 percent of the U.S. level if its TFP were the same as that of the United States. Instead, its income is only 28 percent of the U.S. level. Our model suggests that the way to understand China's lower income is that its TFP is only about 0.43 times the U.S. level. So if we gave China the same amount of capital per person as the United States, we would still expect its per capita GDP to be only 43 percent of that in the United States. The comparison between China and the United States is shown graphically in Figure 4.6. With a TFP level equal to about 43 percent of the U.S. level, China's production function is shifted down substantially relative to the U.S. production
3.
(a) We saw in Chapter 4 that the TFP for Brazil is about 0.43 (=43%). Briefly
and clearly explain what this number 0.43 tells us.
O
TFP refers to Total Factor Productivity of a nation, and it measures how
effective is an economy by applying all factors of production. At the
given question, Ithe 0.43 TFP for Brazil refers to the quantity produced
using 100% of inputs.
(b) Relative to the USA, Argentina's y = 0.30 and k = 0.18. Calculate its TFP (Ā)
using the production model we studied (round to the 2nd decimal place).
y=Ak¹/3
0.30= A*(0.18)¹3
A= 3.33333
A=3.33
4. (a) Explain clearly the job separation rates and the job finding rate f in the
bathtub model of unemployment. Write out the formula for each rate.
O
In the bathtub model, the separation rate captures the number of
employed people who lose their job. While Job finding rate captures the
Transcribed Image Text:3. (a) We saw in Chapter 4 that the TFP for Brazil is about 0.43 (=43%). Briefly and clearly explain what this number 0.43 tells us. O TFP refers to Total Factor Productivity of a nation, and it measures how effective is an economy by applying all factors of production. At the given question, Ithe 0.43 TFP for Brazil refers to the quantity produced using 100% of inputs. (b) Relative to the USA, Argentina's y = 0.30 and k = 0.18. Calculate its TFP (Ā) using the production model we studied (round to the 2nd decimal place). y=Ak¹/3 0.30= A*(0.18)¹3 A= 3.33333 A=3.33 4. (a) Explain clearly the job separation rates and the job finding rate f in the bathtub model of unemployment. Write out the formula for each rate. O In the bathtub model, the separation rate captures the number of employed people who lose their job. While Job finding rate captures the
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