deploy: ckarag/academic-kickstart@864e280

index.xml

@@ -229,7 +229,7 @@ console.log('code block');
 <p>Wowchemy supports the popular <a href="https://plot.ly/" target="_blank" rel="noopener">Plotly</a> format for interactive charts.</p>
 <p>Save your Plotly JSON in your page folder, for example <code>line-chart.json</code>, and then add the <code>{{< chart data="line-chart" >}}</code> shortcode where you would like the chart to appear.</p>
 <p>Demo:</p>
-<div id="chart-873154269" class="chart"></div>
+<div id="chart-495817362" class="chart"></div>
 <script>
 (function() {
 let a = setInterval( function() {
@@ -238,7 +238,7 @@ return;
 }
 clearInterval( a );
 Plotly.d3.json("./line-chart.json", function(chart) {
-Plotly.plot('chart-873154269', chart.data, chart.layout, {responsive: true});
+Plotly.plot('chart-495817362', chart.data, chart.layout, {responsive: true});
 });
 }, 500 );
 })();
@@ -851,7 +851,13 @@ style="border:none;">
 <li>Babii, A., Ghysels E., & Striaukas, J. (2022). “Machine learning time series regressions with an application to nowcasting.” Journal of Business & Economic Statistics, 40(3), 1094-1106.</li>
 <li>Stock, J. H., & Watson, M. W. (2002). “Macroeconomic forecasting using diffusion indexes.” Journal of Business & Economic Statistics, 20(2), 147-162.</li>
 </ul>
-&lt;iframe width="700" height="600" frameborder="0" scrolling="no" src="//plotly.com/~ckara/73.embed?show_link=false">&lt;/iframe></description></item><item><title>The Big Macro Nowcasting Ranking</title><link>https://ckarag.github.io/bmnr/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://ckarag.github.io/bmnr/</guid><description>&lt;h3 id="list-of-forecasting-models">List of forecasting models&lt;/h3>
+&lt;iframe width="700" height="600" frameborder="0" scrolling="no" src="//plotly.com/~ckara/73.embed?show_link=false">&lt;/iframe></description></item><item><title>The Big Macro Nowcasting Ranking</title><link>https://ckarag.github.io/bmnr/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://ckarag.github.io/bmnr/</guid><description>&lt;p>The objective of this page is to maintain and populate the ranking below, with newly introduced statistical models in an effort to provide a continuously updated comprehensive comparison of methodologies for nowcasting and forecasting macroeconomic activity. The model comparison is based on a set of (pseudo) real-time vintages, formed using a rich standardized set of variables at mixed-frequencies.&lt;/p>
+&lt;p>The performance evaluation currently covers US real GDP growth rate (QoQ%), comparing 20 distinct methodologies (including ML, as well as standard econometric techniques and workhorse benchmarks), which are combined with three data transformations (D1,D2,D3) for taking into account the mixed-frequency dimension. This results into a ranking containing a total of 85 specifications.&lt;/p>
+&lt;p>The dataset consists of 87 quarterly, and 171 monthly (including 31 financial market) indicators. The indicators correspond to the series found in the FRED-MD and -QD datasets and were downloaded at their original (i.e. highest-available) sampling frequency, whenever possible. Publication release delays were inferred from the metadata in the FRED database (&lt;a href="https://fred.stlouisfed.org" target="_blank" rel="noopener">https://fred.stlouisfed.org&lt;/a>) and then applied to each series to mimic the ragged-edge structure the forecaster would face in reality. The out-of-sample evaluation uses end-of-month vintages at a monthly periodicity, assuming that economic activity is monitored in \textit{real-time} by updating the projections at the end of every month.&lt;/p>
+&lt;p>A list of the indicators that compose the mixed-frequency dataset, can be accessed
+&lt;a href="https://ckarag.github.io/research/datasetMF.csv" target="_blank">here.&lt;/a>
+SeriesID refers to the FRED mnemonic, while the release delay (RDelay) measures the approximate number of days it takes for the respective indicator to be released after the closing of the reference month or quarter. The monthly mixed-frequency vintages used in the POOS model evaluation can be downloaded &lt;a href="https://drive.google.com/file/d/1HpshcZK7v35X5xJNlaQhsFGY9-zd5iDf/view?usp=share_link" target="_blank" rel="noopener">here&lt;/a>. The full set consists of 376 end-of-month vintages spanning the period 19900131-20210430, including monthly and quarterly unbalanced panels whose ragged edge has been imposed by applying the inferred publication delays.&lt;/p>
+&lt;h3 id="list-of-forecasting-models">List of forecasting models&lt;/h3>
 &lt;table class="table">
 &lt;tr> &lt;th>Acronym&lt;/th> &lt;th>Model Description&lt;/th> &lt;/tr>
 &lt;tr>
@@ -952,6 +958,7 @@ style="border:none;">
 &lt;/tr>
 &lt;/table>
 &lt;h2 id="the-ranking-real-time-model-evaluation">The Ranking: Real-time model evaluation&lt;/h2>
+&lt;p>The table reports RMSE’s relative to the AR(1) benchmark for the n-quarters ahead prediction, with n=0 reflecting the nowcast. The models have been ranked wrt the last column which corresponds to the average relative RMSE over all 5 horizons. The real-time POOS evaluation is based on 220 monthly vintages over the period Jan-2003 to Apr-2021. D1 denotes single-frequency information set; D2 U-MIDAS polynomials; and D3 Legendre polynomials. The table ranks specifications coming from the different combinations of ML models with all the transformations D1, D2 and D3 plus their factor-only counterparts. Models with an acronym ending in ‘F’ contain only factors on the RHS.&lt;/p>
 &lt;table class="table">
 &lt;tr> &lt;th>Models&lt;/th> &lt;th>n=0&lt;/th> &lt;th>n=1&lt;/th> &lt;th>n=2&lt;/th> &lt;th>n=3&lt;/th> &lt;th>n=4&lt;/th> &lt;th>avg&lt;/th> &lt;/tr>
 &lt;tr>
@@ -1720,6 +1727,7 @@ style="border:none;">
 &lt;td data-table-dtype="text">NaN&lt;/td>
 &lt;/tr>
 &lt;/table>
+&lt;p>The graph provides a visualization of the horse race. Furthermore, it adds a second crucial metric for measuring comparative performance, the MAE. The axes show the relative error measures (RMSE and MAE) averaged over all 5 horizons. Candidate models that are closest to the origin (-bottom left) are the best performers.&lt;/p>
 &lt;p>
 &lt;figure >
 &lt;div class="d-flex justify-content-center">

post/index.xml

@@ -145,7 +145,7 @@ console.log('code block');
 <p>Wowchemy supports the popular <a href="https://plot.ly/" target="_blank" rel="noopener">Plotly</a> format for interactive charts.</p>
 <p>Save your Plotly JSON in your page folder, for example <code>line-chart.json</code>, and then add the <code>{{< chart data="line-chart" >}}</code> shortcode where you would like the chart to appear.</p>
 <p>Demo:</p>
-<div id="chart-873154269" class="chart"></div>
+<div id="chart-495817362" class="chart"></div>
 <script>
 (function() {
 let a = setInterval( function() {
@@ -154,7 +154,7 @@ return;
 }
 clearInterval( a );
 Plotly.d3.json("./line-chart.json", function(chart) {
-Plotly.plot('chart-873154269', chart.data, chart.layout, {responsive: true});
+Plotly.plot('chart-495817362', chart.data, chart.layout, {responsive: true});
 });
 }, 500 );
 })();

post/writing-technical-content/index.html

@@ -68,7 +68,7 @@
       console.log('hello');
       console.log('code block');
       ```
-    - Math: $x = {-b \pm \sqrt{b^2-4ac} \over 2a}$</pre></div><h3 id=charts>Charts</h3><p>Wowchemy supports the popular <a href=https://plot.ly/ target=_blank rel=noopener>Plotly</a> format for interactive charts.</p><p>Save your Plotly JSON in your page folder, for example <code>line-chart.json</code>, and then add the <code>{{&lt; chart data="line-chart" >}}</code> shortcode where you would like the chart to appear.</p><p>Demo:</p><div id=chart-873154269 class=chart></div><script>(function(){let e=setInterval(function(){if(typeof window.Plotly=="undefined")return;clearInterval(e),Plotly.d3.json("./line-chart.json",function(e){Plotly.plot("chart-873154269",e.data,e.layout,{responsive:!0})})},500)})()</script><p>You might also find the <a href=http://plotly-json-editor.getforge.io/ target=_blank rel=noopener>Plotly JSON Editor</a> useful.</p><h3 id=math>Math</h3><p>Wowchemy supports a Markdown extension for $\LaTeX$ math. You can enable this feature by toggling the <code>math</code> option in your <code>config/_default/params.yaml</code> file.</p><p>To render <em>inline</em> or <em>block</em> math, wrap your LaTeX math with <code>{{&lt; math >}}$...${{&lt; /math >}}</code> or <code>{{&lt; math >}}$$...$${{&lt; /math >}}</code>, respectively. (We wrap the LaTeX math in the Wowchemy <em>math</em> shortcode to prevent Hugo rendering our math as Markdown. The <em>math</em> shortcode is new in v5.5-dev.)</p><p>Example <strong>math block</strong>:</p><div class=highlight><pre tabindex=0 class=chroma><code class=language-latex data-lang=latex><span class=line><span class=cl><span class=nb>{{</span>&lt; math &gt;<span class=nb>}}</span>
+    - Math: $x = {-b \pm \sqrt{b^2-4ac} \over 2a}$</pre></div><h3 id=charts>Charts</h3><p>Wowchemy supports the popular <a href=https://plot.ly/ target=_blank rel=noopener>Plotly</a> format for interactive charts.</p><p>Save your Plotly JSON in your page folder, for example <code>line-chart.json</code>, and then add the <code>{{&lt; chart data="line-chart" >}}</code> shortcode where you would like the chart to appear.</p><p>Demo:</p><div id=chart-495817362 class=chart></div><script>(function(){let e=setInterval(function(){if(typeof window.Plotly=="undefined")return;clearInterval(e),Plotly.d3.json("./line-chart.json",function(e){Plotly.plot("chart-495817362",e.data,e.layout,{responsive:!0})})},500)})()</script><p>You might also find the <a href=http://plotly-json-editor.getforge.io/ target=_blank rel=noopener>Plotly JSON Editor</a> useful.</p><h3 id=math>Math</h3><p>Wowchemy supports a Markdown extension for $\LaTeX$ math. You can enable this feature by toggling the <code>math</code> option in your <code>config/_default/params.yaml</code> file.</p><p>To render <em>inline</em> or <em>block</em> math, wrap your LaTeX math with <code>{{&lt; math >}}$...${{&lt; /math >}}</code> or <code>{{&lt; math >}}$$...$${{&lt; /math >}}</code>, respectively. (We wrap the LaTeX math in the Wowchemy <em>math</em> shortcode to prevent Hugo rendering our math as Markdown. The <em>math</em> shortcode is new in v5.5-dev.)</p><p>Example <strong>math block</strong>:</p><div class=highlight><pre tabindex=0 class=chroma><code class=language-latex data-lang=latex><span class=line><span class=cl><span class=nb>{{</span>&lt; math &gt;<span class=nb>}}</span>
 </span></span><span class=line><span class=cl><span class=sb>$$</span><span class=nb>
 </span></span></span><span class=line><span class=cl><span class=nb></span><span class=nv>\gamma</span><span class=nb>_{n} </span><span class=o>=</span><span class=nb> </span><span class=nv>\frac</span><span class=nb>{ </span><span class=nv>\left</span><span class=nb> | </span><span class=nv>\left</span><span class=nb> </span><span class=o>(</span><span class=nv>\mathbf</span><span class=nb> x_{n} </span><span class=o>-</span><span class=nb> </span><span class=nv>\mathbf</span><span class=nb> x_{n</span><span class=o>-</span><span class=m>1</span><span class=nb>} </span><span class=nv>\right</span><span class=nb> </span><span class=o>)</span><span class=nb>^T </span><span class=nv>\left</span><span class=nb> </span><span class=o>[</span><span class=nv>\nabla</span><span class=nb> F </span><span class=o>(</span><span class=nv>\mathbf</span><span class=nb> x_{n}</span><span class=o>)</span><span class=nb> </span><span class=o>-</span><span class=nb> </span><span class=nv>\nabla</span><span class=nb> F </span><span class=o>(</span><span class=nv>\mathbf</span><span class=nb> x_{n</span><span class=o>-</span><span class=m>1</span><span class=nb>}</span><span class=o>)</span><span class=nb> </span><span class=nv>\right</span><span class=nb> </span><span class=o>]</span><span class=nb> </span><span class=nv>\right</span><span class=nb> |}{</span><span class=nv>\left</span><span class=nb> </span><span class=nv>\|\nabla</span><span class=nb> F</span><span class=o>(</span><span class=nv>\mathbf</span><span class=nb>{x}_{n}</span><span class=o>)</span><span class=nb> </span><span class=o>-</span><span class=nb> </span><span class=nv>\nabla</span><span class=nb> F</span><span class=o>(</span><span class=nv>\mathbf</span><span class=nb>{x}_{n</span><span class=o>-</span><span class=m>1</span><span class=nb>}</span><span class=o>)</span><span class=nb> </span><span class=nv>\right</span><span class=nb> </span><span class=nv>\|</span><span class=nb>^</span><span class=m>2</span><span class=nb>}
 </span></span></span><span class=line><span class=cl><span class=nb></span><span class=s>$$</span>