<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Pascal Kieren | Macro Paper Warehouse</title><link>https://macropaperwarehouse.com/authors/pascal-kieren/</link><description>Pascal Kieren</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><atom:link href="https://macropaperwarehouse.com/authors/pascal-kieren/index.xml" rel="self" type="application/rss+xml"/><item><title>A choice-based approach to the measurement of inflation expectations</title><link>https://macropaperwarehouse.com/papers/a-choice-based-approach-to-the-measurement-of-inflation-expectations/</link><guid>https://macropaperwarehouse.com/papers/a-choice-based-approach-to-the-measurement-of-inflation-expectations/</guid><description>&lt;p&gt;Standard survey-based measurement of inflation expectations relies on density forecasts in which respondents assign probabilities to pre-specified inflation bins; this method has been found to induce biases through its bin structure (suggesting that values near zero are more likely), to impose cognitive demands that raise dropout rates, and to become uninformative during high-inflation episodes when responses cluster in open-ended extreme bins—making cross-time and cross-country comparisons unreliable. This paper proposes a new choice-based elicitation method rooted in decision theory that uses a bisection process: respondents first state a minimum and maximum inflation level for which they see almost no chance of actual inflation falling outside the range, avoiding external anchors, and then answer a series of binary choices from which the relevant percentiles of their subjective distribution can be inferred. Two large surveys (UK and US) and a laboratory experiment demonstrate that the method leads to well-defined expectations that fulfil both subjective and objective quality criteria, that it is neither perceived as more difficult nor more time-consuming than the density forecast standard, and that—unlike density forecasts—it is robust to differences in the state of the economy, enabling comparisons across time and countries. The method is portable and can be applied to elicit distributions over other macroeconomic variables beyond inflation.&lt;/p&gt;</description></item></channel></rss>