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Let C and d be as in Exercise 5.

  1. Determine the production level necessary to satisfy a final demand for 1 unit of output from sector 1.
  2. Use an inverse matrix to determine the production level necessary to satisfy a final demand of \(\left[ {\begin{array}{*{20}{c}}{51}\\{30}\end{array}} \right]\).
  3. Use the fact that \(\left[ {\begin{array}{*{20}{c}}{51}\\{30}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{50}\\{30}\end{array}} \right] + \left[ {\begin{array}{*{20}{c}}1\\0\end{array}} \right]\) to explain how and why the answers to parts (a) and (b) and to Exercise 5 are related.

Short Answer

Expert verified
  1. The production level necessary to satisfy the final demandfor 1 unit of output from sector 1 is \({x_1} = \left[ {\begin{array}{*{20}{c}}{1.6}\\{1.2}\end{array}} \right]\).
  2. The production level necessary to satisfy a final demand of \(\left[ {\begin{array}{*{20}{c}}{51}\\{30}\end{array}} \right]\) is \({x_2} = \left[ {\begin{array}{*{20}{c}}{111.6}\\{121.2}\end{array}} \right]\).
  3. The relation of parts (a) and (b) and Exercise 5 is \({{\mathop{\rm x}\nolimits} _2} = x + {x_1}\).

Step by step solution

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01

The value of C and d

Consider the production model \[x = Cx + {\mathop{\rm d}\nolimits} \] for an economy with two sectors, where \(C = \left[ {\begin{array}{*{20}{c}}{.0}&{.5}\\{.6}&{.2}\end{array}} \right],\,{\mathop{\rm d}\nolimits} = \left[ {\begin{array}{*{20}{c}}{50}\\{30}\end{array}} \right]\).

02

Determine the production level

(a)

Theorem 11 states that C is the consumption matrix for an economy. Let d be the final demand. If C and d have non-negative entries and each column sum of C is less than 1, then \({\left( {I - C} \right)^{ - 1}}\) exists. Also, the production vector \(x = {\left( {I - C} \right)^{ - 1}}{\mathop{\rm d}\nolimits} \) has non-negative entries and is the unique solution of \(x = Cx + {\mathop{\rm d}\nolimits} \).

From Exercise 5, \({\left( {I - C} \right)^{ - 1}} = \left[ {\begin{array}{*{20}{c}}{1.6}&1\\{1.2}&2\end{array}} \right]\).

The production level necessary to satisfy the final demand is shown below:

\[\begin{array}{c}{x_1} = {\left( {I - C} \right)^{ - 1}}{{\mathop{\rm d}\nolimits} _1}\\ = \left[ {\begin{array}{*{20}{c}}{1.6}&1\\{1.2}&2\end{array}} \right]\left[ {\begin{array}{*{20}{c}}1\\0\end{array}} \right]\\ = \left[ {\begin{array}{*{20}{c}}{1.6 + 0}\\{1.2 + 0}\end{array}} \right]\\ = \left[ {\begin{array}{*{20}{c}}{1.6}\\{1.2}\end{array}} \right]\end{array}\]

This corresponds to the first column of \({\left( {I - C} \right)^{ - 1}}\).

Thus, the production level necessary to satisfy the final demandfor 1 unit of output from sector 1 is \({x_1} = \left[ {\begin{array}{*{20}{c}}{1.6}\\{1.2}\end{array}} \right]\).

03

Use the inverse matrix to determine the production level

(b)

The production level necessary to satisfy the final demand of \(\left[ {\begin{array}{*{20}{c}}{51}\\{30}\end{array}} \right]\) is shown below:

\[\begin{array}{c}{x_2} = {\left( {I - C} \right)^{ - 1}}{{\mathop{\rm d}\nolimits} _2}\\ = \left[ {\begin{array}{*{20}{c}}{1.6}&1\\{1.2}&2\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{51}\\{30}\end{array}} \right]\\ = \left[ {\begin{array}{*{20}{c}}{81.6 + 30}\\{61.2 + 60}\end{array}} \right]\\ = \left[ {\begin{array}{*{20}{c}}{111.6}\\{121.2}\end{array}} \right]\end{array}\]

Thus, the production level necessary to satisfy the final demand of \(\left[ {\begin{array}{*{20}{c}}{51}\\{30}\end{array}} \right]\) is \({x_2} = \left[ {\begin{array}{*{20}{c}}{111.6}\\{121.2}\end{array}} \right]\).

04

Obtain the relation of parts (a) and (b) and Exercise 5

(c)

From Exercise 5, the production vector x corresponding to

\({\mathop{\rm d}\nolimits} = \left[ {\begin{array}{*{20}{c}}{50}\\{20}\end{array}} \right]\)is \(x = \left[ {\begin{array}{*{20}{c}}{110}\\{120}\end{array}} \right]\).

Use \({{\mathop{\rm d}\nolimits} _2} = d + {d_1}\) to obtain the relation between parts (a), (b), and Exercise 5, as shown below:

\(\begin{array}{c}{{\mathop{\rm x}\nolimits} _2} = {\left( {I - C} \right)^{ - 1}}{{\mathop{\rm d}\nolimits} _2}\\ = {\left( {I - C} \right)^{ - 1}}\left( {{\mathop{\rm d}\nolimits} + {{\mathop{\rm d}\nolimits} _1}} \right)\\ = {\left( {I - C} \right)^{ - 1}}{\mathop{\rm d}\nolimits} + {\left( {I - C} \right)^{ - 1}}{{\mathop{\rm d}\nolimits} _1}\\ = {\mathop{\rm x}\nolimits} + {{\mathop{\rm x}\nolimits} _1}\end{array}\)

Thus, the relation between parts (a), (b) and Exercise 5 is \({{\mathop{\rm x}\nolimits} _2} = x + {x_1}\).

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Most popular questions from this chapter

In Exercises 1–9, assume that the matrices are partitioned conformably for block multiplication. In Exercises 5–8, find formulas for X, Y, and Zin terms of A, B, and C, and justify your calculations. In some cases, you may need to make assumptions about the size of a matrix in order to produce a formula. [Hint:Compute the product on the left, and set it equal to the right side.]

5. \[\left[ {\begin{array}{*{20}{c}}A&B\\C&{\bf{0}}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}I&{\bf{0}}\\X&Y\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{\bf{0}}&I\\Z&{\bf{0}}\end{array}} \right]\]

Suppose Tand U are linear transformations from \({\mathbb{R}^n}\) to \({\mathbb{R}^n}\) such that \(T\left( {U{\mathop{\rm x}\nolimits} } \right) = {\mathop{\rm x}\nolimits} \) for all x in \({\mathbb{R}^n}\) . Is it true that \(U\left( {T{\mathop{\rm x}\nolimits} } \right) = {\mathop{\rm x}\nolimits} \) for all x in \({\mathbb{R}^n}\)? Why or why not?

Let \(A = \left[ {\begin{array}{*{20}{c}}B&{\bf{0}}\\{\bf{0}}&C\end{array}} \right]\), where \(B\) and \(C\) are square. Show that \(A\)is invertible if an only if both \(B\) and \(C\) are invertible.

Describe in words what happens when you compute \({A^{\bf{5}}}\), \({A^{{\bf{10}}}}\), \({A^{{\bf{20}}}}\), and \({A^{{\bf{30}}}}\) for \(A = \left( {\begin{aligned}{*{20}{c}}{1/6}&{1/2}&{1/3}\\{1/2}&{1/4}&{1/4}\\{1/3}&{1/4}&{5/12}\end{aligned}} \right)\).

In Exercises 27 and 28, view vectors in \({\mathbb{R}^n}\) as \(n \times 1\) matrices. For \({\mathop{\rm u}\nolimits} \) and \({\mathop{\rm v}\nolimits} \) in \({\mathbb{R}^n}\), the matrix product \({{\mathop{\rm u}\nolimits} ^T}v\) is a \(1 \times 1\) matrix, called the scalar product, or inner product, of u and v. It is usually written as a single real number without brackets. The matrix product \({{\mathop{\rm uv}\nolimits} ^T}\) is an \(n \times n\) matrix, called the outer product of u and v. The products \({{\mathop{\rm u}\nolimits} ^T}{\mathop{\rm v}\nolimits} \) and \({{\mathop{\rm uv}\nolimits} ^T}\) will appear later in the text.

27. Let \({\mathop{\rm u}\nolimits} = \left( {\begin{aligned}{*{20}{c}}{ - 2}\\3\\{ - 4}\end{aligned}} \right)\) and \({\mathop{\rm v}\nolimits} = \left( {\begin{aligned}{*{20}{c}}a\\b\\c\end{aligned}} \right)\). Compute \({{\mathop{\rm u}\nolimits} ^T}{\mathop{\rm v}\nolimits} \), \({{\mathop{\rm v}\nolimits} ^T}{\mathop{\rm u}\nolimits} \),\({{\mathop{\rm uv}\nolimits} ^T}\), and \({\mathop{\rm v}\nolimits} {{\mathop{\rm u}\nolimits} ^T}\).

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