feat(posts): slider for romer time dynamics
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2 changed files with 126 additions and 74 deletions
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@ -525,6 +525,24 @@
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</li>
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</ul>
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</div>
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<div style="padding-left: 20px">
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<ul start="3">
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<li>
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<div class="slider">
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<label for="slidert0">\(t_0:\)</label>
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<span id="outputt0">50</span>
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<input
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type="range"
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id="slidert0"
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min="1"
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max="99"
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step="1"
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value="50"
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/>
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</div>
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</li>
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</ul>
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</div>
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</div>
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<p>
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Notably, while both the Romer and Solow Models help to analyze
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@ -588,68 +606,98 @@
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</div>
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</div>
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<div class="fold"><h3>solving the model</h3></div>
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<p>
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Based on the the motivations for creating this model, it is more
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useful to first analyze the growth rates of equilibrium long run
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output \(Y_t^*\).
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</p>
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<p>
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According to the production function, \[g_Y=g_A+\alpha
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g_K+(1-\alpha)g_{L_{y}}\]
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</p>
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<p>
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From previous analysis it was found that
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\(g_A=\bar{z}\bar{l}\bar{L}\).
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</p>
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<p>
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Based on the <u>Law of Capital Motion</u>, \[g_K=\frac{\Delta
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K_{t+1}}{K_t}=\bar{s}\frac{Y_t}{K_t}-\bar{d}\]
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</p>
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<p>
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Because growth rates are constant on the Balanced Growth Path,
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\(g_K\) must be constant as well. Thus, so is
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\(\bar{s}\frac{Y_t}{K_t}-\bar{d}\); it must be that
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\(g_K^*=g_Y^*\).
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</p>
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<p>
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The model assumes population is constant, so
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\(g_{\bar{L}}=0\rightarrow g_{\bar{L}_yt}=0\) as well.
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</p>
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<p>
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Combining these terms, we find:
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\[g_Y^*=\bar{z}\bar{l}\bar{L}+\alpha g_Y^*+(1-\alpha)\cdot 0\]
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\[\rightarrow g_Y^*=\frac{\bar{z}\bar{l}\bar{L}}{1-\alpha}\]
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</p>
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<p>
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Solving for \(Y_t^*\) is trivial after discovering \(g_K=g_Y\)
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must hold on a balanced growth path.
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</p>
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<p>
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Invoking the <u>Law of Capital Motion</u> with magic chants,
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\[g_K^*=\bar{s}\frac{Y_t^*}{K_t^*}-\bar{d}=g_Y^*\rightarrow
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K_t^*=\frac{\bar{s}Y_t^*}{g_Y^*+\bar{d}}\]
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</p>
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<p>
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Isolating \(Y_t^*\), \[Y_t^*=A_t^*
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(\frac{\bar{s}Y_t^*}{g_Y^*+\bar{d}})^\alpha
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({(1-\bar{l})\bar{L}})^{1-\alpha}\] \[\rightarrow
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{Y_t^*}^{1-\alpha}=A_t^*(\frac{\bar{s}}{g_Y^*+\bar{d}})^\alpha({(1-\bar{l})\bar{L}})^{1-\alpha}\]
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</p>
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<p>
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Plugging in the known expressions for \(A_t^*\) and \(g_Y^*\), a
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final expression for the Balanced Growth Path output as a function
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of the endogenous parameters and time is obtained: \[
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Y_t^*={(A_0(1+\bar{z}\bar{l}\bar{L})^t})^\frac{1}{1-\alpha}(\frac{\bar{s}}{\frac{\bar{z}\bar{l}\bar{L}}{1-\alpha}+\bar{d}})^\frac{\alpha}{1-\alpha}(1-\bar{l})\bar{L}\]
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</p>
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</div>
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<div class="fold"><h3>analysis</h3></div>
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<div>
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<p>
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Intuitively, this means that idea-driving factors, as well as an
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increased allocation of labor to output, will increase the
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Balanced Growth Path (the <i>level</i> of long-run growth),
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combining both the Romer and Solow model.
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</p>
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<div>
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<p>
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Based on the the motivations for creating this model, it is more
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useful to first analyze the growth rates of equilibrium long run
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output \(Y_t^*\).
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</p>
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<p>
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According to the production function, \[g_Y=g_A+\alpha
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g_K+(1-\alpha)g_{L_y}\]
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</p>
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<p>
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From previous analysis it was found that
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\(g_A=\bar{z}\bar{l}\bar{L}\).
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</p>
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<p>
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Based on the <u>Law of Capital Motion</u>, \[g_K=\frac{\Delta
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K_{t+1}}{K_t}=\bar{s}\frac{Y_t}{K_t}-\bar{d}\]
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</p>
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<p>
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Because growth rates are constant on the Balanced Growth Path,
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\(g_K\) must be constant as well. Thus, so is
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\(\bar{s}\frac{Y_t}{K_t}-\bar{d}\); it must be that
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\(g_K^*=g_Y^*\).
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</p>
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<p>
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The model assumes population is constant, so
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\(g_{\bar{L}}=0\rightarrow g_{\bar{L}_yt}=0\) as well.
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</p>
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<p>
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Combining these terms, we find:
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\[g_Y^*=\bar{z}\bar{l}\bar{L}+\alpha g_Y^*+(1-\alpha)\cdot 0\]
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\[\rightarrow g_Y^*=\frac{\bar{z}\bar{l}\bar{L}}{1-\alpha}\]
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</p>
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<p>
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Solving for \(Y_t^*\) is trivial after discovering \(g_K=g_Y\)
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must hold on a balanced growth path.
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</p>
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<p>
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Invoking the <u>Law of Capital Motion</u> with magic chants,
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\[g_K^*=\bar{s}\frac{Y_t^*}{K_t^*}-\bar{d}=g_Y^*\rightarrow
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K_t^*=\frac{\bar{s}Y_t^*}{g_Y^*+\bar{d}}\]
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</p>
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<p>
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Isolating \(Y_t^*\), \[Y_t^*=A_t^*
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(\frac{\bar{s}Y_t^*}{g_Y^*+\bar{d}})^\alpha
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({(1-\bar{l})\bar{L}})^{1-\alpha}\] \[\rightarrow
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{Y_t^*}^{1-\alpha}=A_t^*(\frac{\bar{s}}{g_Y^*+\bar{d}})^\alpha({(1-\bar{l})\bar{L}})^{1-\alpha}\]
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</p>
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<p>
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Plugging in the known expressions for \(A_t^*\) and \(g_Y^*\), a
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final expression for the Balanced Growth Path output as a
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function of the endogenous parameters and time is obtained: \[
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Y_t^*={(A_0(1+\bar{z}\bar{l}\bar{L})^t})^\frac{1}{1-\alpha}(\frac{\bar{s}}{\frac{\bar{z}\bar{l}\bar{L}}{1-\alpha}+\bar{d}})^\frac{\alpha}{1-\alpha}(1-\bar{l})\bar{L}\]
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</p>
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</div>
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<div class="fold"><h3>analysis</h3></div>
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<div>
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<p>
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First looking at the growth rate of output,
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\(g_Y^*=\frac{\bar{z}\bar{l}\bar{L}}{1-\alpha}\), idea-driving
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factors and an increased allocation of labor to output increase
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the equilibrium Balanced Growth Path—the
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<i>level</i> of long-run growth. Thus, this model captures the
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influences of both capital and ideas on economic growth.
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<!-- TODO: t_0 graph break in romer-model and post -->
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</p>
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<p>
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Looking at \(Y_t^*\), ideas have both a direct and indirect
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effect on output. Firstly, ideas raise output because they
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increase productivity (directly); second, with the introduction
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of capital stock, ideas also increase capital, in turn
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increasing output further (indirectly). Mathematically, this is
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evident in both instances of \(g_A^*\) in the formula for output
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\(Y_t^*\)—note that
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\(\frac{1}{1-\alpha},\frac{\alpha}{1-\alpha}>0\) for any
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\(\alpha\in(0,1)\), so \(\frac{d}{dg_A^*}Y_t^*>0\).
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</p>
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<p>
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Expectedly, output has a positive relationship with the savings
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rate and a negative relationship with the depreciation rate.
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</p>
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<p>
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However, do economics grow <i>faster</i>/<i>slower</i> the
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further <i>below</i>/<i>above</i> they are from their Balanced
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Growth Path, as initially desired? While this can be
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mathematically proven (of course), sometimes a visualization
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helps.
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</p>
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<div class="graph">
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<div id="romer-solow-visualization"></div>
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</div>
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</div>
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</div>
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</article>
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</div>
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