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lectures/cass_koopmans_1.md

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</div>
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```
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# Cass-Koopmans Planning Problem
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# Cass-Koopmans Model
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```{contents} Contents
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:depth: 2
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```
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## Overview
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This lecture and lecture {doc}`Cass-Koopmans Competitive Equilibrium <cass_koopmans_2>` describe a model that Tjalling Koopmans {cite}`Koopmans`
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This lecture and {doc}`Cass-Koopmans Competitive Equilibrium <cass_koopmans_2>` describe a model that Tjalling Koopmans {cite}`Koopmans`
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and David Cass {cite}`Cass` used to analyze optimal growth.
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The model can be viewed as an extension of the model of Robert Solow
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described in [an earlier lecture](https://lectures.quantecon.org/py/python_oop.html)
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but adapted to make the saving rate the outcome of an optimal choice.
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but adapted to make the saving rate be a choice.
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(Solow assumed a constant saving rate determined outside the model.)
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This lecture is devoted to the planned economy version.
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In the planned economy, there are
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- no prices
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- no budget constraints
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Instead there is a dictator that tells people
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- what to produce
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- what to invest in physical capital
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- who is to consume what and when
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The lecture uses important ideas including
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- A min-max problem for solving a planning problem.
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Time is discrete and takes values $t = 0, 1 , \ldots, T$ where $T$ is finite.
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(We'll study a limiting case in which $T = + \infty$ before concluding).
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(We'll eventually study a limiting case in which $T = + \infty$)
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A single good can either be consumed or invested in physical capital.
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The consumption good is not durable and depreciates completely if not
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consumed immediately.
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The capital good is durable but depreciates some each period.
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The capital good is durable but depreciates.
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We let $C_t$ be a nondurable consumption good at time $t$.
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We let $C_t$ be the total consumption of a nondurable consumption good at time $t$.
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Let $K_t$ be the stock of physical capital at time $t$.
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Let $\vec{C}$ = $\{C_0,\dots, C_T\}$ and
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$\vec{K}$ = $\{K_0,\dots,K_{T+1}\}$.
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### Digression: an Aggregation Theory
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We use a concept of a representative consumer to be thought of as follows.
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There is a unit mass of identical consumers.
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For $\omega \in [0,1]$, consumption of consumer is $c(\omega)$.
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Aggregate consumption is
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$$
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C = \int_0^1 c(\omega) d \omega
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$$
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Consider the a welfare problem of choosing an allocation $\{c(\omega)\}$ across consumers to maximize
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$$
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\int_0^1 u(c(\omega)) d \omega
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$$
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where $u(\cdot)$ is a concave utility function with $u' >0, u'' < 0$ and maximization is subject to
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$$
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C = \int_0^1 c(\omega) d \omega .
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$$ (eq:feas200)
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Form a Lagrangian $L = \int_0^1 u(c(\omega)) d \omega + \lambda [C - \int_0^1 c(\omega) d \omega ] $.
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Differentiate under the integral signs with respect to each $\omega$ to obtain the first-order
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necessary condtions
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$$
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u'(c(\omega)) = \lambda.
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$$
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This condition implies that $c(\omega)$ equals a constant $c$ that is independent
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of $\omega$.
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To find $c$, use the feasibility constraint {eq}`eq:feas200` to conclude that
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$$
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c(\omega) = c = C.
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$$
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This line of argument indicates the special *aggregation theory* that lies beneath outcomes in which a representative consumer
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consumes amount $C$.
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It appears often in aggregate economics.
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We shall use it in this lecture and in {doc}`Cass-Koopmans Competitive Equilibrium <cass_koopmans_2>`.
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#### An Economy
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A representative household is endowed with one unit of labor at each
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$t$ and likes the consumption good at each $t$.
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\mathcal{L}(\vec{C} ,\vec{K} ,\vec{\mu} ) =
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\sum_{t=0}^T \beta^t\left\{ u(C_t)+ \mu_t
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\left(F(K_t,1) + (1-\delta) K_t- C_t - K_{t+1} \right)\right\}
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$$
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$$ (eq:Lagrangian201)
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and then pose the following min-max problem:
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### First-order necessary conditions
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We now compute **first order necessary conditions** for extremization of the Lagrangian:
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We now compute **first-order necessary conditions** for extremization of the Lagrangian {eq}`eq:Lagrangian201`:
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```{math}
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:label: constraint1
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In computing {eq}`constraint3` we recognize that $K_t$ appears
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in both the time $t$ and time $t-1$ feasibility constraints.
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{eq}`constraint4` comes from differentiating with respect
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Restrictions {eq}`constraint4` come from differentiating with respect
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to $K_{T+1}$ and applying the following **Karush-Kuhn-Tucker condition** (KKT)
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(see [Karush-Kuhn-Tucker conditions](https://en.wikipedia.org/wiki/Karush-Kuhn-Tucker_conditions)):
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plot_saving_rate(pp, 0.3, k_ss/3, [250, 150, 75, 50], k_ss=k_ss)
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```
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## A Limiting Economy
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## A Limiting Infinite Horizon Economy
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We want to set $T = +\infty$.
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In {doc}`Cass-Koopmans Competitive Equilibrium <cass_koopmans_2>`, we study a decentralized version of an economy with exactly the same
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technology and preference structure as deployed here.
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In that lecture, we replace the planner of this lecture with Adam Smith's **invisible hand**
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In that lecture, we replace the planner of this lecture with Adam Smith's **invisible hand**.
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In place of quantity choices made by the planner, there are market prices somewhat produced by
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the invisible hand.
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In place of quantity choices made by the planner, there are market prices that are set by a mechanism outside the model, a so-called invisible hand.
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Market prices must adjust to reconcile distinct decisions that are made independently
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Equilibrium market prices must reconcile distinct decisions that are made independently
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by a representative household and a representative firm.
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The relationship between a command economy like the one studied in this lecture and a market economy like that

lectures/cass_koopmans_2.md

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This lecture continues our analysis in this lecture
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{doc}`Cass-Koopmans Planning Model <cass_koopmans_1>` about the model that Tjalling Koopmans {cite}`Koopmans`
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and David Cass {cite}`Cass` used to study optimal growth.
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and David Cass {cite}`Cass` used to study optimal capital accumulation.
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This lecture illustrates what is, in fact, a
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more general connection between a **planned economy** and an economy
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organized as a **competitive equilibrium**.
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organized as a competitive equilibrium or a **market economy**.
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The earlier lecture {doc}`Cass-Koopmans Planning Model <cass_koopmans_1>` studied a planning problem and used ideas including
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- A min-max problem for solving the planning problem.
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- A Lagrangian formulation of the planning problem that leads to a system of difference equations.
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- A **shooting algorithm** for solving difference equations subject
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to initial and terminal conditions.
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- A **turnpike** property that describes optimal paths for
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long-but-finite horizon economies.
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The present lecture uses additional ideas including
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- Hicks-Arrow prices named after John R. Hicks and Kenneth Arrow.
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- A connection between some Lagrange multipliers in the min-max
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- Hicks-Arrow prices, named after John R. Hicks and Kenneth Arrow.
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- A connection between some Lagrange multipliers from the planning
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problem and the Hicks-Arrow prices.
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- A **Big** $K$ **, little** $k$ trick widely used in
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macroeconomic dynamics.
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* We shall encounter this trick in [this lecture](https://python.quantecon.org/rational_expectations.html)
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and also in [this lecture](https://python-advanced.quantecon.org/dyn_stack.html).
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- A non-stochastic version of a theory of the **term structure of
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interest rates**.
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- An intimate connection between the cases for the optimality of two
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competing visions of good ways to organize an economy, namely:
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- An intimate connection between two
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ways to organize an economy, namely:
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* **socialism** in which a central planner commands the
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allocation of resources, and
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* **capitalism** (also known as **a market economy**) in
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* **competitive markets** in
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which competitive equilibrium **prices** induce individual
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consumers and producers to choose a socially optimal allocation
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as an unintended consequence of their selfish
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as unintended consequences of their selfish
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decisions
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Let's start with some standard imports:
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In this lecture {doc}`Cass-Koopmans Planning Model <cass_koopmans_1>`, we studied a problem in which a planner chooses an allocation $\{\vec{C},\vec{K}\}$ to
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maximize {eq}`utility-functional` subject to {eq}`allocation`.
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The allocation that solves the planning problem plays an important role in a competitive equilibrium as we shall see below.
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The allocation that solves the planning problem reappears in a competitive equilibrium, as we shall see below.
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## Competitive Equilibrium
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But now there is no planner.
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Market prices adjust to reconcile distinct decisions that are made
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There are (unit masses of) price taking consumers and firms.
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Market prices are set to reconcile distinct decisions that are made
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separately by a representative household and a representative firm.
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There is a representative consumer who has the same preferences over
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consumption plans as did the consumer in the planned economy.
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consumption plans as did a consumer in the planned economy.
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Instead of being told what to consume and save by a planner, the
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household chooses for itself subject to a budget constraint
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Instead of being told what to consume and save by a planner, a
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consumer (also known as a *household*) chooses for itself subject to a budget constraint
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- At each time $t$, the household receives wages and rentals
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of capital from a firm -- these comprise its **income** at
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- The representative household and the representative firm are both
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**price takers** who believe that prices are not affected by their choices
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**Note:** We can think of there being a large number
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$M$ of identical representative consumers and $M$
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**Note:** We can think of there being unit measures of identical representative consumers and
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identical representative firms.
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## Market Structure
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There are sequences of prices
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$\{w_t,\eta_t\}_{t=0}^T= \{\vec{w}, \vec{\eta} \}$
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where $w_t$ is a wage or rental rate for labor at time $t$ and
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$\eta_t$ is a rental rate for capital at time $t$.
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where
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- $w_t$ is a wage or rental rate for labor at time $t$
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In addition there is are intertemporal prices that work as follows.
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- $\eta_t$ is a rental rate for capital at time $t$
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Let $q^0_t$ be the price of a good at date $t$ relative
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In addition there is a vector $\{q_t^0\}$ of intertemporal prices where
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- $q^0_t$ is the price of a good at date $t$ relative
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to a good at date $0$.
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We call $\{q^0_t\}_{t=0}^T$ a vector of **Hicks-Arrow prices**,
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named after the 1972 economics Nobel prize winners.
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Evidently,
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Units of $q_t^0$ could be
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$$
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q^0_t=\frac{\text{number of time 0 goods}}{\text{number of time t goods}}
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\frac{\text{number of time 0 goods}}{\text{number of time t goods}}
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$$
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Because $q^0_t$ is a **relative price**, the units in terms of
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which prices are quoted are arbitrary -- we are free to normalize them.
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But because $q^0_t$ is a **relative price**, the units in terms of
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which prices are quoted are arbitrary, we are free to re-normalize them.
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## Firm Problem
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If $\frac{\partial F}{\partial \tilde k_t}> \eta_t$, then the
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firm makes positive profits on each additional unit of
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$\tilde k_t$, so it will want to make $\tilde k_t$
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$\tilde k_t$, so it would want to make $\tilde k_t$
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arbitrarily large.
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But setting $\tilde k_t = + \infty$ is not physically feasible,
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$\frac{\partial F}{\partial \tilde n_t}> w_t$.
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If $\frac{\partial \tilde k_t}{\partial \tilde k_t}< \eta_t$,
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the firm will set $\tilde k_t$ to zero, something that is not feasible.
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the firm would want to set $\tilde k_t$ to zero, which is not feasible.
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It is convenient to define
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$\vec{w} =\{w_0, \dots,w_T\}$and $\vec{\eta}= \{\eta_0, \dots, \eta_T\}$.
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k_{T+1}: \quad -\lambda q_0^{T+1} \leq 0, \ \leq 0 \text{ if } k_{T+1}=0; \ =0 \text{ if } k_{T+1}>0
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```
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Now we plug in our guesses of prices and embark on some algebra in the hope of derived all first-order necessary conditions
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Now we plug in our guesses of prices and embark on some algebra in the hope of recovering all first-order necessary conditions
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{eq}`constraint1`-{eq}`constraint4` for the planning problem from this lecture {doc}`Cass-Koopmans Planning Model <cass_koopmans_1>`.
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Combining {eq}`cond1` and {eq}`eq-price`, we get:
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\sum_{t=0}^T \beta^t \mu_{t} \left(C_t+ (K_{t+1} -(1-\delta)K_t)-f(K_t)+K_t f'(K_t)-f'(K_t)K_t\right) \leq 0
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$$
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which simplifies
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which simplifies to
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$$
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\sum_{t=0}^T \beta^t \mu_{t} \left(C_t +K_{t+1} -(1-\delta)K_t - F(K_t,1)\right) \leq 0
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which is exactly {eq}`eq-pr4`.
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So at our guess for the equilibrium price system, the allocation
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Thus, at our guess for the equilibrium price system, the allocation
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that solves the planning problem also solves the problem faced by a firm
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within a competitive equilibrium.
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plot_yield_curves(pp, 20, 0.3, k_ss/3, T_arr)
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```
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We aim to have more to say about the term structure of interest rates
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in a planned lecture on the topic.
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