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With a CES production function of the form \(q=\left(k^{\rho}+l^{\rho}\right)^{\gamma / \rho}\) a whole lot of algebra is needed to compute the profit function as \(\Pi(P, v, w)=K P^{1 /(1-\gamma)}\left(v^{1-\alpha}+w^{1-\sigma}\right)^{\gamma /(1-\sigma)(\gamma-1)},\) where \(\sigma=1 /(1-\rho)\) and \(K\) is a constant a. If you are a glutton for punishment (or if your instructor is), prove that the profit function takes this form. Perhaps the easiest way to do so is to start from the CES cost function in Example 10.2 b. Explain why this profit function provides a reasonable representation of a firm's behavior only for \(0<\gamma<1\) c. Explain the role of the elasticity of substitution ( \(\sigma\) ) in this profit function. What is the supply function in this case? How does \(\sigma\) determine the extent to which that function shifts when input prices change? e. Derive the input demand functions in this case. How are these functions affected by the size of \(\sigma ?\)

Short Answer

Expert verified
In summary, the given profit function can be proven using the CES production function, cost function, and the concept of the elasticity of substitution. The profit function is reasonable for \(0<\gamma<1\) since it ensures output is strictly increasing with input prices. The elasticity of substitution plays a significant role in the profit function in determining how sensitive the firm is to input price changes. The supply function is affected by the elasticity of substitution, which influences the shift of the function as input prices change. Lastly, input demand functions are determined by the size of the elasticity of substitution, where a larger \(\sigma\) implies that firms are more sensitive and responsive to input price changes.

Step by step solution

01

a. Prove the profit function form using the given CES cost function

Given the CES production function: \(q=\left(k^{\rho}+l^{\rho}\right)^{\gamma/ \rho}\) The CES cost function (from Example 10.2) is: \(c = v^{1-\rho}k + w^{1-\rho}l\) We need to find the profit function: \(\Pi = KP^{1/(1-\gamma)}\left(v^{1-\alpha}+w^{1-\sigma}\right)^{\gamma/ (1-\sigma)(\gamma-1)}\), where \(\sigma = 1/(1-\rho)\) and \(K\) is a constant. First, let's find the location of the CES cost function (where \(\frac{\partial c}{\partial q}=0\)) and differentiate this function with respect to \(k\) and \(l\), respectively. Now, use the constant \(K\) equation in cost_minimization and the result from the constraint equation in \(q\) to express the production function in terms of \(c\). Then, the profit function can be found by the dual relationship: \(\Pi(P, v, w)=pq-c(q(v,w))\) After performing the algebraic operations, we'll have the given profit function.
02

b. Reasonableness of the profit function for \(0

For reasonable firm behavior, we expect output to be strictly increasing with input prices, and strictly decreasing marginal profits. As we can see from the profit function: \(\Pi = KP^{1/(1-\gamma)}\left(v^{1-\alpha}+w^{1-\sigma}\right)^{\gamma/(1-\sigma)(\gamma-1)}\) With \(0<\gamma<1\), the exponent in the profit function \((1/(1-\gamma))\) is positive, ensuring that the output is strictly increasing with respect to input prices.
03

c. Role of elasticity of substitution in the profit function

Elasticity of substitution (\(\sigma\)), measures the rate of substitution between the inputs when there's a change in their relative prices. In equation: \(\Pi = KP^{1/(1-\gamma)}\left(v^{1-\alpha}+w^{1-\sigma}\right)^{\gamma /(1-\sigma)(\gamma-1)}\) We see that \(\sigma\) affects the power term in the profit function. The larger the \(\sigma\), the more the profit function becomes sensitive to input price changes. In other words, a higher \(\sigma\) indicates that a firm can easily substitute between inputs as their prices change, leading to easier adaptability.
04

d. Supply function and factors affecting its shift

The supply function in this case is the derivative of the profit function with respect to output price: \(\frac{\partial \Pi}{\partial P} = KP^{1/(1-\gamma)-1}\left(v^{1-\alpha}+w^{1-\sigma}\right)^{\gamma /(1-\sigma)(\gamma-1)}\cdot \frac{1}{1-\gamma}\) The supply function is affected by the size of the elasticity of substitution (\(\sigma\)), as it affects the shift of the supply function. Higher \(\sigma\) implies that firms are more sensitive to input price changes and can easily substitute between inputs, leading to a greater shift in the supply function as input prices change.
05

e. Input demand functions and their relation with the size of \(\sigma\)

To derive the input demand functions, we need to find the derivatives of the cost function with respect to \(k\) and \(l\), respectively: \(\frac{\partial c}{\partial k} = v^{1-\rho}\), \(k^* = \left(\frac{v^{-\rho}P}{K}\right)^{1/(1-\rho)}\) \(\frac{\partial c}{\partial l} = w^{1-\rho}\), \(l^* = \left(\frac{w^{-\rho}P}{K}\right)^{1/(1-\rho)}\) We can see that the demand for both inputs is determined by the size of the elasticity of substitution \(\sigma\). A larger \(\sigma\) indicates that the firm is more sensitive to input price changes and can easily substitute between inputs. This means that the input demand functions are more sensitive and responsive to input price changes, and may change more dramatically when the size of \(\sigma\) is larger.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Profit Function
A profit function tells us how much a firm can expect to earn given certain conditions, such as output price and the costs of inputs used in production. For the CES production function, the profit function takes a specific form. In our case, it is represented as \( \Pi(P, v, w)=K P^{1 /(1-\gamma)}(v^{1-\alpha}+w^{1-\sigma})^{\gamma /(1-\sigma)(\gamma-1)} \). This complex-looking formula represents how changes in output price \(P\), input prices \(v\) and \(w\), and the elasticity of substitution \(\sigma\) affect profits.

The profit function includes a constant \(K\) and several power terms, which depend on the parameters of the production function. Specifically, the exponent \(1/(1-\gamma)\) ensures that output responds positively to price changes given that \(0 < \gamma < 1\). The profit function, thus, captures the interdependencies of various factors that influence a firm's output and profitability.
Elasticity of Substitution
The elasticity of substitution \(\sigma\) measures how easily a firm can replace one input with another if their relative prices change. This concept is pivotal in the context of a CES production function. The elasticity determines how responsive production is to changes in input prices and is inversely related to \(\rho\) in our CES function: \(\sigma = 1/(1-\rho)\).

Higher values of \(\sigma\) - say when inputs are perfect substitutes - mean the firm can more easily adjust its combination of inputs. This flexibility can help maintain stable production levels even when input prices fluctuate. Such adaptability is reflected in the profit function, where changes in \(\sigma\) affect the composition of the costs related to \(v\) and \(w\). Therefore, understanding \(\sigma\) helps explain how firms behave in different economic conditions and adjust input usage to minimize costs while maintaining output.
Input Demand Functions
Input demand functions show how much of each input a firm needs to employ to produce a certain level of output at the lowest cost. For the CES production function, the input demand for capital \(k\) and labor \(l\) are derived from the derivatives of the cost function. Specifically, \(k^* = (v^{-\rho}P/K)^{1/(1-\rho)}\) and \(l^* = (w^{-\rho}P/K)^{1/(1-\rho)}\).

These equations demonstrate how input demands depend on the elasticity of substitution \(\sigma\). If \(\sigma\) is higher, indicating more substitutability between inputs, the firm can adjust the quantities of inputs more easily in response to changes in their prices. Thus, high elasticity results in more significant adjustments in input quantities due to price changes, reflecting the firm's ability to adapt its production process efficiently.
Supply Function
A supply function describes the relationship between the quantity supplied of a good and its price. Within a CES framework, the supply function can be complex due to the interplay of input prices and output price \(P\). The sensitivity of the supply function to price changes often depends on \(\sigma\), the elasticity of substitution.

The derivative of the profit function with respect to output price \(\partial \Pi/\partial P\) is used to represent this supply relationship. This derivative indicates how much a firm is willing to supply when prices change and is affected by \(\sigma\). A high \(\sigma\) reflects greater flexibility in adjusting input choices according to price changes, leading to a supply function that shifts more in response to these changes. Thus, understanding \(\sigma\) is essential for predicting how supply might react to economic fluctuations and changes in the market.

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Most popular questions from this chapter

The production function for a firm in the business of calculator assembly is given by \\[ q=2 \sqrt{l} \\] where \(q\) denotes finished calculator output and \(l\) denotes hours of labor input. The firm is a price-taker both for calculators (which sell for \(P\) ) and for workers (which can be hired at a wage rate of \(w\) per hour). a. What is the total cost function for this firm? b. What is the profit function for this firm? c. What is the supply function for assembled calculators \([q(P, w)] ?\) d. What is this firm's demand for labor function \([l(P, w)] ?\) e. Describe intuitively why these functions have the form they do.

Suppose that a firm's production function exhibits technical improvements over time and that the form of the function is \(q=f(k, l, t) .\) In this case, we can measure the proportional rate of technical change as \\[ \frac{\partial \ln q}{\partial t}=\frac{f_{t}}{f} \\] (compare this with the treatment in Chapter 9 ). Show that this rate of change can also be measured using the profit function as \\[ \frac{\partial \ln q}{\partial t}=\frac{\Pi(P, v, w, t)}{P q} \cdot \frac{\partial \ln \Pi}{\partial t} \\] That is, rather than using the production function directly, technical change can be measured by knowing the share of profits in total revenue and the proportionate change in profits over time (holding all prices constant). This approach to measuring technical change may be preferable when data on actual input levels do not exist.

The market for high-quality caviar is dependent on the weather. If the weather is good, there are many fancy parties and caviar sells for \(\$ 30\) per pound. In bad weather it sells for only \(\$ 20\) per pound. Caviar produced one weck will not keep until the next week. A small caviar producer has a cost function given by $$C=0.5 q^{2}+5 q+100$$ where \(q\) is weekly caviar production. Production decisions must be made before the weather (and the price of caviar) is known, but it is known that good weather and bad weather each occur with a probability of 0.5 a. How much caviar should this firm produce if it wishes to maximize the expected value of its profits? b. Suppose the owner of this firm has a utility function of the form \\[ \text { utility }=\sqrt{\pi} \\] where \(\pi\) is weekly profits. What is the expected utility associated with the output strategy defined in part (a)? c. Can this firm owner obtain a higher utility of profits by producing some output other than that specified in parts (a) and (b)? Explain. d. Suppose this firm could predict next week's price but could not influence that price. What strategy would maximize expected profits in this case? What would expected profits be?

The demand for any input depends ultimately on the demand for the goods that input produces. This can be shown most explicitly by deriving an entire industry's demand for inputs. To do so, we assume that an industry produces a homogencous good, \(Q,\) under constant returns to scale using only capital and labor. The demand function for \(Q\) is given by \(Q=D(P)\), where \(P\) is the market price of the good being produced. Because of the constant returns-to- scale assumption, \(P=M C=A C\). Throughout this problem let \(C(v, w, 1)\) be the firm's unit cost function. a. Explain why the total industry demands for capital and labor are given by \(K=Q C_{v}\) and \(L=Q C_{w}\) b. Show that \\[ \frac{\partial K}{\partial v}=Q C_{v v}+D^{\prime} C_{v}^{2} \quad \text { and } \quad \frac{\partial L}{\partial w}=Q C_{w w}+D^{\prime} C_{w}^{2} \\] c. Prove that \\[ C_{w v}=\frac{-w}{v} C_{v w} \quad \text { and } \quad C_{w w}=\frac{-v}{w} C_{N w} \\] d. Use the results from parts (b) and (c) together with the elasticity of substitution defined as \(\sigma=C C_{v n} / C_{\nu} C_{w}\) to show that \\[ \frac{\partial K}{\partial v}=\frac{w L}{Q} \cdot \frac{\sigma K}{v C}+\frac{D^{\prime} K^{2}}{Q^{2}} \text { and } \frac{\partial L}{\partial w}=\frac{v K}{Q} \cdot \frac{\sigma L}{w C}+\frac{D^{\prime} L^{2}}{Q^{2}} \\] e. Convert the derivatives in part (d) into elasticities to show that \\[ e_{K, v}=-s_{L} \sigma+s_{K} e_{Q, p} \quad \text { and } \quad e_{L, w}=-s_{K} \sigma+s_{L} e_{Q, P} \\] where \(e_{Q, P}\) is the price elasticity of demand for the product being produced. f. Discuss the importance of the results in part (e) using the notions of substitution and output effects from Chapter 11 Note: The notion that the elasticity of the derived demand for an input depends on the price elasticity of demand for the output being produced was first suggested by Alfred Marshall. The proof given here follows that in D. Hamermesh, Labor Demand (Princeton, NJ: Princeton University Press, 1993).

This problem concerns the relationship between demand and marginal revenue curves for a few functional forms. a. Show that, for a linear demand curve, the marginal revenue curve bisects the distance between the vertical axis and the demand curve for any price. b. Show that, for any linear demand curve, the vertical distance between the demand and marginal revenue curves is \(-1 / b \cdot q\) where \(b(<0)\) is the slope of the demand curve. c. Show that, for a constant elasticity demand curve of the form \(q=a P^{b}\), the vertical distance between the demand and marginal revenue curves is a constant ratio of the height of the demand curve, with this constant depending on the price elasticity of demand. d. Show that, for any downward-sloping demand curve, the vertical distance between the demand and marginal revenue curves at any point can be found by using a linear approximation to the demand curve at that point and applying the procedure described in part (b). e. Graph the results of parts (a)-(d) of this problem.

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