feat: romer model
This commit is contained in:
parent
b6b3e08886
commit
71a959708d
7 changed files with 515 additions and 31 deletions
1
aggieland.txt
Normal file
1
aggieland.txt
Normal file
|
|
@ -0,0 +1 @@
|
|||
the 12th man
|
||||
1
compile_flags.txt
Normal file
1
compile_flags.txt
Normal file
|
|
@ -0,0 +1 @@
|
|||
-std=c++20
|
||||
5
filename.txt
Normal file
5
filename.txt
Normal file
|
|
@ -0,0 +1,5 @@
|
|||
This is an example text file.
|
||||
This file contains several words, some of which are repeated.
|
||||
For example, the word "this" appears multiple times in this file.
|
||||
We can use a shell command to find the most frequent words.
|
||||
Let's see how many times each word appears in this example text file.
|
||||
10
map.cc
Normal file
10
map.cc
Normal file
|
|
@ -0,0 +1,10 @@
|
|||
#include <fstream>
|
||||
#include <iostream>
|
||||
|
||||
int main() {
|
||||
std::ifstream ifs{"aggieland.txt"};
|
||||
std::string read1;
|
||||
int read2;
|
||||
ifs >> read1 >> read2;
|
||||
std::cout << read1 << read2;
|
||||
}
|
||||
|
|
@ -147,7 +147,7 @@
|
|||
type="range"
|
||||
id="sliderD"
|
||||
min="0.01"
|
||||
max="1"
|
||||
max="0.99"
|
||||
step="0.01"
|
||||
value="0.50"
|
||||
/>
|
||||
|
|
@ -165,7 +165,7 @@
|
|||
type="range"
|
||||
id="sliderS"
|
||||
min="0.01"
|
||||
max="1"
|
||||
max="0.99"
|
||||
step="0.01"
|
||||
value="0.50"
|
||||
/>
|
||||
|
|
@ -179,7 +179,7 @@
|
|||
type="range"
|
||||
id="sliderAlpha"
|
||||
min="0.01"
|
||||
max="1"
|
||||
max="0.99"
|
||||
step="0.01"
|
||||
value="0.33"
|
||||
/>
|
||||
|
|
@ -213,8 +213,6 @@
|
|||
</div>
|
||||
<div class="fold">
|
||||
<h3>analysis</h3>
|
||||
</div>
|
||||
<div>
|
||||
<p>
|
||||
Using both mathematical intuition and manipulating the
|
||||
visualization above, we find that:
|
||||
|
|
@ -262,10 +260,250 @@
|
|||
alter the most important predictor of output, TFP.
|
||||
</p>
|
||||
</div>
|
||||
<h2>romer</h2>
|
||||
<!-- TODO: transition talking about "Romer model does, though" -->
|
||||
<!-- TODO: say the romer model provides avenue for LR growth -->
|
||||
<!-- Solow TODO -->
|
||||
<!-- TODO: dynamics?????? -->
|
||||
<!-- TODO: K_0 -->
|
||||
<h2>romer</h2>
|
||||
<div class="fold"><h3>introduction</h3></div>
|
||||
<div>
|
||||
<p>How, then, can we address these shortcomings?</p>
|
||||
<p>
|
||||
The Romer Model provides an answer by both modeling ideas \(A_t\)
|
||||
(analagous to TFP in the Solow model) endogenously and utilizing
|
||||
them to provide a justification for sustained long-run growth.
|
||||
</p>
|
||||
<p>The Model divides the world into two parts:</p>
|
||||
<ul style="list-style: unset">
|
||||
<li>
|
||||
<u>Objects</u>: finite resources, like capital and labor in the
|
||||
Solow Model
|
||||
</li>
|
||||
<li>
|
||||
<u>Ideas</u>: infinite,
|
||||
<a
|
||||
target="blank"
|
||||
href="https://en.wikipedia.org/wiki/Rivalry_(economics)"
|
||||
>non-rivalrous</a
|
||||
>
|
||||
items leveraged in production (note that ideas may be
|
||||
<a href="blank" href="https://www.wikiwand.com/en/Excludability"
|
||||
>excludable</a
|
||||
>, though)
|
||||
</li>
|
||||
</ul>
|
||||
<p>
|
||||
The Romer Models' production function can be modelled as:
|
||||
\[Y_t=F(A_t,L_{yt})=A_tL_{yt}\] With:
|
||||
</p>
|
||||
<ul>
|
||||
<li>\(A_t\): the amount of ideas \(A\) in period \(t\)</li>
|
||||
<li>
|
||||
\(L_{yt}\): the population working on production-facing
|
||||
(output-driving) tasks
|
||||
</li>
|
||||
</ul>
|
||||
<p>
|
||||
Assuming \(L_t=\bar{L}\) people work in the economy, a proportion
|
||||
\(\bar{l}\) of the population focuses on making ideas:
|
||||
\(L_{at}=\bar{l}\bar{L}\rightarrow L_{yt}=(1-\bar{l})\bar{L}\).
|
||||
</p>
|
||||
<!-- TODO: footnotes - dynamic JS? -->
|
||||
<p>
|
||||
Further, this economy garners ideas with time at rate
|
||||
<u>\(\bar{z}\)</u>: the "speed of ideas". Now, we can
|
||||
describe the quantity of ideas tomorrow as function of those of
|
||||
today: the <u>Law of Ideal Motion</u> (I made that up).
|
||||
\[A_{t+1}=A_t+\bar{z}A_tL_{at}\leftrightarrow\Delta
|
||||
A_{t+1}=\bar{z}A_tL_{at}\]
|
||||
</p>
|
||||
<p>
|
||||
Analagously to capital in the solow model, ideas begin in the
|
||||
economy with some \(\bar{A}_0\gt0\) and grow at an
|
||||
<i>exponential</i> rate. At its core, this is because ideas are
|
||||
non-rivalrous; more ideas bring about more ideas.
|
||||
</p>
|
||||
<p>Finally, we have a model:</p>
|
||||
<div style="display: flex; justify-content: center">
|
||||
<div style="padding-right: 50px">
|
||||
<ol>
|
||||
<li>\(Y_t=A_tL_{yt}\)</li>
|
||||
<li>\(\Delta A_{t+1} = \bar{z}A_tL_{at}\)</li>
|
||||
</ol>
|
||||
</div>
|
||||
<div style="padding-left: 50px">
|
||||
<ol start="3">
|
||||
<li>\(L_{yt}+L_{at}=\bar{L}\)</li>
|
||||
<li>\(L_{at}=\bar{l}\bar{L}\)</li>
|
||||
</ol>
|
||||
</div>
|
||||
</div>
|
||||
<p>
|
||||
A visualization of the Romer Model shows that the economy grows
|
||||
exponentially—production knows no bounds (<a
|
||||
target="blank"
|
||||
href="https://en.wikipedia.org/wiki/Ceteris_paribus"
|
||||
><i>ceteris parbibus</i></a
|
||||
>, of course). A graph of \(log_{10}(Y_t)\) can be seen below:
|
||||
</p>
|
||||
<div class="graph">
|
||||
<div id="romer-visualization"></div>
|
||||
</div>
|
||||
<div class="sliders">
|
||||
<div style="padding-right: 20px">
|
||||
<ul>
|
||||
<li>
|
||||
<div class="slider">
|
||||
<label for="sliderZ">\(\bar{z}:\)</label>
|
||||
<span id="outputZ">0.50</span>
|
||||
<input
|
||||
type="range"
|
||||
id="sliderZ"
|
||||
min="0.1"
|
||||
max="0.99"
|
||||
step="0.01"
|
||||
value="0.50"
|
||||
/>
|
||||
</div>
|
||||
</li>
|
||||
<li>
|
||||
<div class="slider">
|
||||
<label for="sliderL">\(\bar{L}:\)</label>
|
||||
<span id="outputL">505</span>
|
||||
<input
|
||||
type="range"
|
||||
id="sliderL"
|
||||
min="10"
|
||||
max="1000"
|
||||
step="19"
|
||||
value="505"
|
||||
/>
|
||||
</div>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div style="padding-left: 20px">
|
||||
<ul start="3">
|
||||
<li>
|
||||
<div class="slider">
|
||||
<label for="sliderl">\(\bar{l}:\)</label>
|
||||
<span id="outputl">0.50</span>
|
||||
<input
|
||||
type="range"
|
||||
id="sliderl"
|
||||
min="0.01"
|
||||
max="0.99"
|
||||
step="0.01"
|
||||
value="0.50"
|
||||
/>
|
||||
</div>
|
||||
</li>
|
||||
<li>
|
||||
<div class="slider">
|
||||
<label for="sliderA0">\(\bar{A}_0:\)</label>
|
||||
<span id="outputA0">5000</span>
|
||||
<input
|
||||
type="range"
|
||||
id="sliderA0"
|
||||
min="1"
|
||||
max="10000"
|
||||
step="100"
|
||||
value="5000"
|
||||
/>
|
||||
</div>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
<p>
|
||||
Playing with the sliders, this graph may seem underwhelming in
|
||||
comparison to the Solow Model. However, on a logarithmic scale,
|
||||
small changes in the parameters lead to massive changes in the
|
||||
growth rate of ideas and economices:
|
||||
</p>
|
||||
<div class="romer-table-container">
|
||||
<table id="romer-table">
|
||||
<thead>
|
||||
<tr id="romer-table-header"></tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr id="row-A_t"></tr>
|
||||
<tr id="row-Y_t"></tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
</div>
|
||||
<div class="fold"><h3>solving the model</h3></div>
|
||||
<div>
|
||||
<p>
|
||||
To find the output in terms of exogenous parameters, first note
|
||||
that \[L_t=\bar{L}\rightarrow L_{yt}=(1-\bar{l})\bar{L}\]
|
||||
</p>
|
||||
<p>
|
||||
Now, all that remains is to find ideas \(A_t\). It is assumed that
|
||||
ideas grow at some rate \(g_A\): \[A_t=A_0(1+g_A)^t\]
|
||||
</p>
|
||||
<p>
|
||||
Using the growth rate formula, we find: \[g_A=\frac{\Delta
|
||||
A_{t+1}-A_t}{A_t}=\frac{A_t+\bar{z}A_tL_{at}-A_t}{A_t}=\bar{z}L_{at}=\bar{z}\bar{l}\bar{L}\]
|
||||
</p>
|
||||
<p>
|
||||
Thus, ideas \(A_t=A_0(1+\bar{z}\bar{l}\bar{L})^t\). Finally,
|
||||
output can be solved the production function: \[Y_t=A_t
|
||||
L_{yt}=A_0(1+\bar{z}\bar{l}\bar{L})(1-\bar{l})\bar{L}\]
|
||||
</p>
|
||||
<!-- <p> -->
|
||||
<!-- It follows that the intensive form can be written as: -->
|
||||
<!-- \[y_t=\frac{Y_t}{\bar{L}}=A_0(1+\bar{z}\bar{l}\bar{L})(1-\bar{l})\]. -->
|
||||
<!-- </p> -->
|
||||
</div>
|
||||
<div class="fold"><h3>analysis</h3></div>
|
||||
<div>
|
||||
<p>
|
||||
We see the Romer model exhibits long-run growth because ideas have
|
||||
non-diminishing returns due to their nonrival nature. In this
|
||||
model, capital and income eventually slow but ideas continue to
|
||||
yield increasing, unrestricted returns.
|
||||
</p>
|
||||
<p>
|
||||
Further, all economy continually and perpetually grow along a
|
||||
"Balanced Growth Path" as previously defined by \(Y_t\) as a
|
||||
function of the endogenous variables. This directly contrasts the
|
||||
Solow model, in which an economy converges to a steady-state with
|
||||
transition dynamics.
|
||||
</p>
|
||||
<p>
|
||||
Changes in the growth rate of ideas, then, alter the growth rate
|
||||
of output itself—in this case, parameters \(\bar{l},
|
||||
\bar{z}\), and \(\bar{L}\). This is best exemplified by comparing
|
||||
the growth rate before and and after a parameter changes. In the
|
||||
below example, a larger \(\bar{l}\) initially drops output due to
|
||||
less workers being allocated to production. Soon after, though,
|
||||
output recovers along a "higher" Balanced Growth Path.
|
||||
</p>
|
||||
<div class="graph">
|
||||
<div id="romer-lchange-visualization"></div>
|
||||
</div>
|
||||
<div class="sliders">
|
||||
<div style="padding-right: 20px">
|
||||
<ul>
|
||||
<li>
|
||||
<div class="slider">
|
||||
<label for="sliderlChange">\(\bar{l}:\)</label>
|
||||
<span id="outputlChange">0.50</span>
|
||||
<input
|
||||
type="range"
|
||||
id="sliderlChange"
|
||||
min="0.1"
|
||||
max="0.99"
|
||||
step="0.01"
|
||||
value="0.50"
|
||||
/>
|
||||
</div>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<h2>romer-solow</h2>
|
||||
</article>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -11,10 +11,10 @@ function drawSolowGraph() {
|
|||
};
|
||||
});
|
||||
|
||||
const A = document.getElementById("outputA").textContent,
|
||||
D = document.getElementById("outputD").textContent,
|
||||
S = document.getElementById("outputS").textContent,
|
||||
alpha = document.getElementById("outputAlpha").textContent;
|
||||
const A = parseFloat(document.getElementById("outputA").textContent),
|
||||
D = parseFloat(document.getElementById("outputD").textContent),
|
||||
S = parseFloat(document.getElementById("outputS").textContent),
|
||||
alpha = parseFloat(document.getElementById("outputAlpha").textContent);
|
||||
const solowOutput = (K) => A * Math.pow(K, alpha) * Math.pow(L, 1 - alpha);
|
||||
const solowDepreciation = (K) => D * K;
|
||||
const solowInvestment = (Y) => S * Y;
|
||||
|
|
@ -34,12 +34,10 @@ function drawSolowGraph() {
|
|||
.attr("transform", `translate(${margin.left}, ${margin.top})`);
|
||||
|
||||
const x = d3.scaleLinear().domain([0, K_MAX]).range([0, width]);
|
||||
const xAxis = svg
|
||||
svg
|
||||
.append("g")
|
||||
.attr("transform", `translate(0, ${height})`)
|
||||
.call(d3.axisBottom(x));
|
||||
|
||||
xAxis
|
||||
.call(d3.axisBottom(x))
|
||||
.append("text")
|
||||
.attr("fill", "#000")
|
||||
.attr("x", width + 10)
|
||||
|
|
@ -50,9 +48,9 @@ function drawSolowGraph() {
|
|||
|
||||
const Y_MAX = solowOutput(K_MAX) + K_MAX / 10;
|
||||
const y = d3.scaleLinear().domain([0, Y_MAX]).range([height, 0]);
|
||||
const yAxis = svg.append("g").call(d3.axisLeft(y));
|
||||
|
||||
yAxis
|
||||
svg
|
||||
.append("g")
|
||||
.call(d3.axisLeft(y))
|
||||
.append("text")
|
||||
.attr("fill", "#000")
|
||||
.attr("x", 0)
|
||||
|
|
@ -87,9 +85,7 @@ function drawSolowGraph() {
|
|||
.append("xhtml:body")
|
||||
.style("font-size", "0.75em")
|
||||
.html(`<div class="solow-visualization-y"></div>`);
|
||||
katex.render("Y", document.querySelector(".solow-visualization-y"), {
|
||||
throwOnError: false,
|
||||
});
|
||||
katex.render("Y", document.querySelector(".solow-visualization-y"));
|
||||
|
||||
const depreciationData = Array.from({ length: K_MAX }, (_, k) => ({
|
||||
K: k,
|
||||
|
|
@ -118,9 +114,7 @@ function drawSolowGraph() {
|
|||
.append("xhtml:body")
|
||||
.style("font-size", "0.75em")
|
||||
.html(`<div class="solow-visualization-d"></div>`);
|
||||
katex.render("\\bar{d}K", document.querySelector(".solow-visualization-d"), {
|
||||
throwOnError: false,
|
||||
});
|
||||
katex.render("\\bar{d}K", document.querySelector(".solow-visualization-d"));
|
||||
|
||||
const investmentData = outputData.map((d) => ({
|
||||
K: d.K,
|
||||
|
|
@ -149,9 +143,7 @@ function drawSolowGraph() {
|
|||
.append("xhtml:body")
|
||||
.style("font-size", "0.75em")
|
||||
.html(`<div class="solow-visualization-i"></div>`);
|
||||
katex.render("I", document.querySelector(".solow-visualization-i"), {
|
||||
throwOnError: false,
|
||||
});
|
||||
katex.render("I", document.querySelector(".solow-visualization-i"));
|
||||
|
||||
const k_star = L * Math.pow((S * A) / D, 1 / (1 - alpha));
|
||||
svg
|
||||
|
|
@ -177,13 +169,230 @@ function drawSolowGraph() {
|
|||
katex.render(
|
||||
`(K^*,Y^*)=(${k_star.toFixed(0)},${y_star.toFixed(0)})`,
|
||||
document.querySelector(".solow-visualization-eq"),
|
||||
{
|
||||
throwOnError: false,
|
||||
},
|
||||
);
|
||||
}
|
||||
|
||||
const formatNumber = (num) => {
|
||||
return `~${num.toExponential(0)}`;
|
||||
};
|
||||
|
||||
const normalFont = `style="font-weight: normal"`;
|
||||
|
||||
const updateRomerTable = (romerData) => {
|
||||
const tableHeader = document.getElementById("romer-table-header");
|
||||
const rowA_t = document.getElementById("row-A_t");
|
||||
const rowY_t = document.getElementById("row-Y_t");
|
||||
|
||||
tableHeader.innerHTML = `<th ${normalFont}><div class="romer-table-time"></th>`;
|
||||
katex.render(`t`, document.querySelector(".romer-table-time"));
|
||||
rowA_t.innerHTML = `<td class="romer-table-at"></td>`;
|
||||
rowY_t.innerHTML = `<td class="romer-table-yt"></td>`;
|
||||
katex.render("A_t", document.querySelector(".romer-table-at"));
|
||||
katex.render("Y_t", document.querySelector(".romer-table-yt"));
|
||||
|
||||
romerData.forEach((d) => {
|
||||
if (d.year % 20 === 0 || d.year === 1) {
|
||||
tableHeader.innerHTML += `<th ${normalFont}>${d.year}</th>`;
|
||||
rowA_t.innerHTML += `<td>${formatNumber(d.A)}</td>`;
|
||||
rowY_t.innerHTML += `<td>${formatNumber(d.Y)}</td>`;
|
||||
}
|
||||
});
|
||||
};
|
||||
|
||||
function drawRomerGraph() {
|
||||
const T_MAX = 100;
|
||||
margin = { top: 20, right: 100, bottom: 20, left: 50 };
|
||||
|
||||
["Z", "L", "l", "A0"].forEach((param) => {
|
||||
const slider = document.getElementById(`slider${param}`);
|
||||
slider.oninput = function () {
|
||||
slider.previousElementSibling.innerText = this.value;
|
||||
drawRomerGraph();
|
||||
};
|
||||
});
|
||||
|
||||
const z = parseFloat(document.getElementById("outputZ").textContent),
|
||||
L = parseFloat(document.getElementById("outputL").textContent),
|
||||
l = parseFloat(document.getElementById("outputl").textContent),
|
||||
A0 = parseFloat(document.getElementById("outputA0").textContent);
|
||||
|
||||
const container = document.getElementById("romer-visualization");
|
||||
const width = container.clientWidth - margin.left - margin.right;
|
||||
const height = container.clientHeight - margin.top - margin.bottom;
|
||||
|
||||
container.innerHTML = "";
|
||||
|
||||
const svg = d3
|
||||
.select("#romer-visualization")
|
||||
.append("svg")
|
||||
.attr("width", width + margin.left + margin.right)
|
||||
.attr("height", height + margin.top + margin.bottom)
|
||||
.append("g")
|
||||
.attr("transform", `translate(${margin.left}, ${margin.top})`);
|
||||
|
||||
let A = A0;
|
||||
const romerData = [];
|
||||
|
||||
for (let t = 1; t <= T_MAX; ++t) {
|
||||
const A_t = A * (1 + z * l * L);
|
||||
const Y_t = A_t * (1 - l) * L;
|
||||
romerData.push({ year: t, A: A_t, Y: Math.log10(Y_t) });
|
||||
A = A_t;
|
||||
}
|
||||
|
||||
const x = d3.scaleLinear().domain([1, T_MAX]).range([0, width]);
|
||||
svg
|
||||
.append("g")
|
||||
.attr("transform", `translate(0, ${height})`)
|
||||
.call(d3.axisBottom(x))
|
||||
.append("text")
|
||||
.attr("fill", "#000")
|
||||
.attr("x", width + 10)
|
||||
.attr("y", -10)
|
||||
.style("text-anchor", "end")
|
||||
.style("font-size", "1.5em")
|
||||
.text("t");
|
||||
|
||||
const y = d3
|
||||
.scaleLinear()
|
||||
.domain([0, romerData[romerData.length - 1].Y])
|
||||
.range([height, 0]);
|
||||
svg
|
||||
.append("g")
|
||||
.call(d3.axisLeft(y).ticks(10, d3.format(".1s")))
|
||||
.append("text")
|
||||
.attr("fill", "#000")
|
||||
.attr("x", 0)
|
||||
.attr("y", -10)
|
||||
.style("text-anchor", "start")
|
||||
.style("font-size", "1.5em")
|
||||
.text("log(Y)");
|
||||
|
||||
svg
|
||||
.append("path")
|
||||
.datum(romerData)
|
||||
.attr("fill", "none")
|
||||
.attr("stroke", getTopicColor(urlToTopic()))
|
||||
.attr("stroke-width", 2)
|
||||
.attr(
|
||||
"d",
|
||||
d3
|
||||
.line()
|
||||
.x((d) => x(d.year))
|
||||
.y((d) => y(d.Y)),
|
||||
);
|
||||
|
||||
svg
|
||||
.append("foreignObject")
|
||||
.attr("width", "4em")
|
||||
.attr("height", "2em")
|
||||
.attr("x", x(T_MAX))
|
||||
.attr("y", y(romerData[T_MAX - 1].Y))
|
||||
.append("xhtml:body")
|
||||
.style("font-size", "0.75em")
|
||||
.html(`<div class="romer-visualization-y"></div>`);
|
||||
katex.render("log_{10}Y", document.querySelector(".romer-visualization-y"));
|
||||
|
||||
updateRomerTable(romerData);
|
||||
}
|
||||
|
||||
function drawRomerlGraph() {
|
||||
const T_MAX = 100,
|
||||
z = 0.01,
|
||||
L = 50,
|
||||
A0 = 50;
|
||||
margin = { top: 20, right: 100, bottom: 20, left: 50 };
|
||||
|
||||
const slider = document.getElementById(`sliderlChange`);
|
||||
slider.oninput = function () {
|
||||
slider.previousElementSibling.innerText = this.value;
|
||||
drawRomerlGraph();
|
||||
};
|
||||
|
||||
const l = parseFloat(document.getElementById("outputlChange").textContent);
|
||||
|
||||
const container = document.getElementById("romer-lchange-visualization");
|
||||
const width = container.clientWidth - margin.left - margin.right;
|
||||
const height = container.clientHeight - margin.top - margin.bottom;
|
||||
|
||||
container.innerHTML = "";
|
||||
|
||||
const svg = d3
|
||||
.select("#romer-lchange-visualization")
|
||||
.append("svg")
|
||||
.attr("width", width + margin.left + margin.right)
|
||||
.attr("height", height + margin.top + margin.bottom)
|
||||
.append("g")
|
||||
.attr("transform", `translate(${margin.left}, ${margin.top})`);
|
||||
|
||||
let A = A0,
|
||||
l_ = 0.1;
|
||||
const romerData = [];
|
||||
|
||||
for (let t = 1; t <= Math.floor(T_MAX / 2) - 1; ++t) {
|
||||
const A_t = A * (1 + z * l_ * L);
|
||||
const Y_t = A_t * (1 - l_) * L;
|
||||
romerData.push({ year: t, A: A_t, Y: Math.log10(Y_t) });
|
||||
A = A_t;
|
||||
}
|
||||
|
||||
for (let t = Math.floor(T_MAX / 2); t <= T_MAX; ++t) {
|
||||
const A_t = A * (1 + z * l * L);
|
||||
const Y_t = A_t * (1 - l) * L;
|
||||
romerData.push({ year: t, A: A_t, Y: Math.log10(Y_t) });
|
||||
A = A_t;
|
||||
}
|
||||
|
||||
const x = d3.scaleLinear().domain([1, T_MAX]).range([0, width]);
|
||||
svg
|
||||
.append("g")
|
||||
.attr("transform", `translate(0, ${height})`)
|
||||
.call(d3.axisBottom(x))
|
||||
.append("text")
|
||||
.attr("fill", "#000")
|
||||
.attr("x", width + 10)
|
||||
.attr("y", -10)
|
||||
.style("text-anchor", "end")
|
||||
.style("font-size", "1.5em")
|
||||
.text("t");
|
||||
|
||||
const y = d3
|
||||
.scaleLinear()
|
||||
.domain([0, romerData[romerData.length - 1].Y])
|
||||
.range([height, 0]);
|
||||
svg
|
||||
.append("g")
|
||||
.call(d3.axisLeft(y).ticks(10, d3.format(".1s")))
|
||||
.append("text")
|
||||
.attr("fill", "#000")
|
||||
.attr("x", 0)
|
||||
.attr("y", -10)
|
||||
.style("text-anchor", "start")
|
||||
.style("font-size", "1.5em")
|
||||
.text("log(Y)");
|
||||
|
||||
svg
|
||||
.append("path")
|
||||
.datum(romerData)
|
||||
.attr("fill", "none")
|
||||
.attr("stroke", getTopicColor(urlToTopic()))
|
||||
.attr("stroke-width", 2)
|
||||
.attr(
|
||||
"d",
|
||||
d3
|
||||
.line()
|
||||
.x((d) => x(d.year))
|
||||
.y((d) => y(d.Y)),
|
||||
);
|
||||
}
|
||||
|
||||
document.addEventListener("DOMContentLoaded", function () {
|
||||
drawSolowGraph();
|
||||
window.onresize = drawSolowGraph;
|
||||
|
||||
drawRomerGraph();
|
||||
window.onresize = drawRomerGraph;
|
||||
|
||||
drawRomerlGraph();
|
||||
window.onresize = drawRomerlGraph;
|
||||
});
|
||||
|
|
|
|||
|
|
@ -68,3 +68,23 @@ ul {
|
|||
list-style: none;
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
.romer-table-container {
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
margin: 20px 0;
|
||||
}
|
||||
#romer-table {
|
||||
text-align: center;
|
||||
margin-top: 20px;
|
||||
margin: 0;
|
||||
font-size: 0.8em;
|
||||
border-collapse: collapse;
|
||||
}
|
||||
|
||||
#romer-table th,
|
||||
#romer-table td {
|
||||
border: 1px solid black;
|
||||
text-align: center;
|
||||
padding: 5px;
|
||||
}
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue