From f546ff34a671ddaba276bf434626c4ebc56fe04d Mon Sep 17 00:00:00 2001 From: Humphrey Yang Date: Mon, 31 Jul 2023 17:12:26 +1000 Subject: [PATCH] draft of application section --- lectures/sympy.md | 155 ++++++++++++++++++++++++++++++++++------------ 1 file changed, 115 insertions(+), 40 deletions(-) diff --git a/lectures/sympy.md b/lectures/sympy.md index b3acda1f..108321be 100644 --- a/lectures/sympy.md +++ b/lectures/sympy.md @@ -4,7 +4,7 @@ jupytext: extension: .md format_name: myst format_version: 0.13 - jupytext_version: 1.14.5 + jupytext_version: 1.14.4 kernelspec: display_name: Python 3 (ipykernel) language: python @@ -59,7 +59,7 @@ from sympy.stats import Poisson, Exponential, Binomial, density, moment, E import numpy as np # Enable the best printer available -init_printing() +init_printing(use_latex='mathjax') ``` ## Symbolic algebra @@ -491,89 +491,164 @@ p = plot3d(cos(2*x + y)) ## Applications -In this section, we apply SymPy to an economic model that explores the wage gap between college and high school graduates. +In this section, we apply SymPy to construct an equalizing differences model that explores the wage gap between college and high school graduates. + +The idea of this example is to imagine a person deciding whether to be admitted into a college or entering the workforce after high school. + +The person is indifferent between the two options if the present value of the earnings from the two options are the same. + +For more details on the model, please visit [the lecture](https://intro.quantecon.org/equalizing_difference.html) in A First Course in Quantitative Economics with Python. ### Defining the Symbols -The first step in symbolic computation is to define the symbols that represent the variables in our equations. In our model, we have the following variables: +The first step in symbolic computation is to define the symbols that represent the variables. - * $R$ The gross rate of return on a one-period bond +In our model, we need the following variables: - * $t = 0, 1, 2, \ldots T$ Denote the years that a person either works or attends college + * $R > 1$ be the gross rate of return on a one-period bond + + * $t = 0, 1, 2, \ldots T$ denote the years that a person either works or attends college - * $T$ denotes the last period that a person works + * $0$ denote the first period after high school that a person can go to work - * $w$ The wage of a high school graduate + * $T$ denote the last period that a person works - * $g$ The growth rate of wages - - * $D$ The upfront monetary costs of going to college + * $w_t^h$ be the wage at time $t$ of a high school graduate + + * $w_t^c$ be the wage at time $t$ of a college graduate - * $\phi$ The wage gap, defined as the ratio of the wage of a college graduate to the wage of a high school graduate + * $\gamma_h > 1$ be the (gross) rate of growth of wages of a high school graduate, so that + $ w_t^h = w_0^h \gamma_h^t$ -Let's define these symbols using sympy + * $\gamma_c > 1$ be the (gross) rate of growth of wages of a college graduate, so that + $ w_t^c = w_0^c \gamma_c^t$ + +Let's define these symbols using SymPy ```{code-cell} ipython3 # Define the symbols -w, R, g, D, phi = symbols('w R g D phi') +R, wh0, wc0, γ_c, γ_h, t, T = symbols( + 'R w^h_0 w^c_0 gamma_c gamma_h t T', positive=True) + +refine(γ_c, γ_c>1) +refine(γ_h, γ_h>1) +refine(R, R>1) + +# Define the wage for college +# and high school graduates at time t +w_ct = wc0 * γ_c**t +w_ht = wh0 * γ_h**t ``` -### Defining the Present Value Equations +```{code-cell} ipython3 +w_ct +``` -We calculate the present value of the earnings of a high school graduate and a college graduate. +```{code-cell} ipython3 +w_ht +``` -For a high school graduate, we sum the discounted wages from year 1 to $T = 4$. +### Defining the Present Value Equations -For a college graduate, we sum the discounted wages from year 5 to $T = 4$, considering the cost of college $D$ paid upfront +The present value of the earnings after going to college is $$ -PV_{\text{{highschool}}} = \frac{w}{R} + \frac{w*(1 + g)}{R^2} + \frac{w*(1 + g)^2}{R^3} + \frac{w*(1 + g)^3}{R^4} +PV_{\text{{college}}} = \sum_{t=4}^T R^{-t} w_t^c = w_0^c (R^{-1} \gamma_c)^4 \left[ \frac{1 - (R^{-1} \gamma_c)^{T-3} }{1 - R^{-1} \gamma_c } \right] \equiv w_0^c A_c $$ +It is the sum of the discounted earnings from the first year of graduation to the last year of work assuming the degree is obtained in the fourth year. + +The present value of the earnings from going to work after high school is + $$ -PV_{\text{{college}}} = D + \frac{\phi * w * (1 + g)^4}{R} + \frac{\phi * w * (1 + g)^5}{R^2} + \frac{\phi * w * (1 + g)^6}{R^3} + \frac{\phi * w * (1 + g)^7}{R^4} +PV_{\text{{highschool}}} = \sum_{t=0}^T R^{-t} w_t^h = w_0^h \left[ \frac{1 - (R^{-1} \gamma_h)^{T+1} }{1 - R^{-1} \gamma_h } \right] \equiv w_0^h A_h $$ +It is the sum of the discounted earnings from the first year of work to the last year of work. + +```{code-cell} ipython3 +PV_college = Sum(R**-t*w_ct, (t, 4, T)) + +PV_highschool = Sum(R**-t*w_ht, (t, 0, T)) +``` + +We can evaluate the sum using the `doit` method + ```{code-cell} ipython3 -# Define the present value equations -PV_highschool = w/R + w*(1 + g)/R**2 + w*(1 + g)**2/R**3 + w*(1 + g)**3/R**4 -PV_college = D + phi*w*(1 + g)**4/R + phi*w*(1 + g)**5 / \ - R**2 + phi*w*(1 + g)**6/R**3 + phi*w*(1 + g)**7/R**4 +PV_hs = simplify(PV_highschool.doit()) +PV_hs +``` + +```{code-cell} ipython3 +PV_c = simplify(PV_college.doit()) +PV_c ``` ### Defining the Indifference Equation -The indifference equation represents the condition that a worker is indifferent between going to college or not. This is given by the equation $PV_h$ = $PV_c$ +Now we introduce the symbol $\phi$ to represent the fraction of high school graduates who go to college and $D$ to represent the upfront monetary costs of going to college. ```{code-cell} ipython3 -# Define the indifference equation -indifference_eq = Eq(PV_highschool, PV_college) +D, ϕ = symbols('D phi', positive=True) ``` -We can now solve the indifference equation for the wage gap $\phi$ +We can solve for by solving the equation below with regards to $\phi$ + +$$ +PV_{highschool} = \phi PV_{college} - D +$$ + +so that + +$$ +\phi =\frac{PV_{highschool}}{PV_{college} - D} +$$ ```{code-cell} ipython3 -# Solve for phi -solution = solve(indifference_eq, phi) +indifference = Eq(PV_hs.args[1][0], + ϕ*PV_c.args[1][0] - D) +indiff_sol = solve(indifference, ϕ)[0] +indiff_sol +``` + +Using `Lambda` function, we can specify the parameters of the equation -# Simplify the solution -solution = simplify(solution[0]) -solution +```{code-cell} ipython3 +lambda_indiff = Lambda((R, wh0, wc0, γ_c, γ_h, D, T), indiff_sol) +lambda_indiff ``` -To compute a numerical value for $\phi$, we replace symbols $w$, $R$, $g$, and $D$ with specific numbers. +We can use the following parameters to compute the value for $\phi$ + +```{code-cell} ipython3 +R_value = 1.05 +γ_c_value, γ_h_value = 1.01, 1.01 +wh0_value = 1 +wc0_value = 2 +D_value = 10 +T_value = 40 + +lambda_indiff(R_value, wh0_value, wc0_value, γ_c_value, γ_h_value, D_value, T_value) +``` -Here we use $w = 1$, $R = 1.05$, $g = 0.02$, and $D = 0.5$. +Under this setting, we find college is more attractive to the person as $\phi < 1$. -Substituting them into the equation, we find a specific value for $\phi$ +We can take a step further by taking the derivative of $\phi$ with respect to $D$ to compute the marginal effect of tuition fee on $\phi$ ```{code-cell} ipython3 -# Substitute specific values -solution_num = solution.subs({w: 1, R: 1.05, g: 0.02, D: 0.5}) -solution_num +diff_D = lambda_indiff(R, wh0, wc0, γ_c, γ_h, D, T).diff(D) +simplify(diff_D) ``` -The wage of a college graduate is approximately 0.797 times the wage of a high school graduate. +```{code-cell} ipython3 +ϕ_D_func = Lambda((R, wh0, wc0, γ_c, γ_h, D, T), diff_D) +``` + +We can see that higher tuition fee gives more incentives for high school graduates to go to work directly. + +```{code-cell} ipython3 +ϕ_D_func(R_value, wh0_value, wc0_value, γ_c_value, γ_h_value, D_value, T_value) +``` ## Exercises