Conditional maximization of consumer utility

52 Views Asked by At

I'm trying to solve the following consumer problem:

Consumers: The economy is populated by an infinity of homogeneous individuals who inelastically supply an amount L of work. The individual has preference over the consumption of the N goods in the economy. Consumers are faced with the following problem:

$Max \left[ \sum_{i \in N} c_i^{\frac{\theta - 1}{\theta}} \right]^{\frac{\theta}{\theta - 1}}$
st: $\sum_{i \in N} p_i c_i = wL$

Where $c_i$ is consumption, the parameter $\theta$ provides the degree of complementarity between the goods, and $w$ is the wages.

I tried to solve this but I was not successful. My teacher said the solution is as follows:

$c_i = \left(\frac{p_1}{p_i}\right)^{\theta} \frac{wL}{p_1^\theta \sum_{i \in N} p_i^{1-\theta}} $

However, he did not demonstrate how to arrive at this result. So I'm not sure how to solve this.

1

There are 1 best solutions below

1
On BEST ANSWER

The Lagrangian for the problem is

$$L(c,\lambda)=u(c)+\lambda (wL-\sum_{i=1}^Np_ic_i)$$

where $u$ is the utility function.

The first order conditions are

$$u_i(c)=\lambda p_i\qquad (i=1,\ldots,n)$$

and

$$wL=\sum_{i=1}^Np_ic_i$$

For any $i\neq j$ the first-order conditions give

$$\frac{u_i(c)}{u_j(c)}=\frac{p_i}{p_j}$$

i.e. the marginal rate of substitution is equal to the price ratio. Now

$$\frac{u_i(c)}{u_j(c)}=\frac{c_i^{-\frac{1}{\theta}}}{c_j^{-\frac{1}{\theta}}}=\left(\frac{c_i}{c_j}\right)^{-\frac{1}{\theta}}$$

So for any $i\neq j$ we must have

$$\left(\frac{c_i}{c_j}\right)^{-\frac{1}{\theta}}=\frac{p_i}{p_j}$$

or

$$\frac{c_i}{c_j}=\left(\frac{p_j}{p_i}\right)^\theta $$

In particular,

$$c_i=\left(\frac{p_1}{p_i}\right)^\theta c_1\tag{1}$$

Substituting into the constraint gives

$$p_1c_1+\sum_{i=2}^Np_i\left(\frac{p_1}{p_i}\right)^\theta c_1=wL$$

or

$$c_1\left[p_1+p_1^\theta\sum_{i=2}^Np_i^{1-\theta}\right]=wL$$

so that

$$c_1=\frac{wL}{p_1+p_1^\theta\sum_{i=2}^Np_i^{1-\theta}}=\frac{wL}{p_1^{\theta}\sum_{i=1}^Np_i^{1-\theta}}$$

Substituting this into $(1)$ gives

$$c_i=\left(\frac{p_1}{p_k}\right)^\theta\frac{wL}{p_1^{\theta}\sum_{k=1}^Np_k^{1-\theta}}$$