<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Augusto Nieto-Barthaburu | Macro Paper Warehouse</title><link>https://macropaperwarehouse.com/authors/augusto-nieto-barthaburu/</link><description>Augusto Nieto-Barthaburu</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Thu, 01 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://macropaperwarehouse.com/authors/augusto-nieto-barthaburu/index.xml" rel="self" type="application/rss+xml"/><item><title>Forecasting with Feedback</title><link>https://macropaperwarehouse.com/papers/forecasting-with-feedback/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://macropaperwarehouse.com/papers/forecasting-with-feedback/</guid><description>&lt;p&gt;This paper develops a strategic model of point forecast production in environments where the forecast itself influences the outcome being predicted — what the authors call &amp;ldquo;forecasting with feedback.&amp;rdquo; The canonical example is Federal Reserve staff (Greenbook) inflation forecasts: these forecasts guide FOMC interest rate decisions, and those rate decisions in turn affect realized inflation. The central theoretical claim, proved formally, is that even a forecaster with purely quadratic (mean-squared-error) loss will optimally produce biased forecasts in such environments, provided there is some uncertainty about how strongly the decision maker (DM) will react to the forecast. This finding offers a third interpretation of observed forecast biases — beyond the two dominant explanations in the prior literature, namely forecaster irrationality and asymmetric loss functions.&lt;/p&gt;</description></item></channel></rss>