Please see my homepage for further information.
Leif Anders Thorsrud is a Professor at the BI Norwegian Business School, and manager of the research centre CAMP (Centre for Applied Macroeconomics and Commodity Prices) at the BI Norwegian Business School. He holds a Bachelor of Arts in Journalism and International Relations, and a Master of Philosophy in Economics from the University of Oslo. He obtained his Phd in Economics from BI Norwegian Business School.
His main area of research is within applied macroeconomics, time series, and machine learning. Special interests include the study of natural resources, business cycles, textual analysis and forecasting. He has published in leading journals such as the Economic Journal, Journal of Econometrics, Journal of Business and Economic Statistics, and Journal of Applied Econometrics. He is also the co-author of the book “Applied Time Series Macroeconomics”.
Thorsrud has previously held positions as staff economist at Norges Bank and the Reserve Bank of New Zealand, and as senior researcher at Norges Bank.
Publikasjoner
Anundsen, André Kallåk; Kivedal, Bjørnar Karlsen, Røed Larsen, Erling & Thorsrud, Leif Anders (2022)
Behavioral changes in the housing market before and after the Covid-19 lockdown
Ellingsen, Jon; Larsen, Vegard Høghaug & Thorsrud, Leif Anders (2022)
News media versus FRED-MD for macroeconomic forecasting
Journal of applied econometrics, 37(1), s. 63- 81. Doi: 10.1002/jae.2859
Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on US GDP, consumption and investment growth, our results suggest that the news data contains information not captured by the hard economic indicators, and that the news-based data are particularly informative for forecasting consumption developments.
ter Ellen, Saskia; Larsen, Vegard Høghaug & Thorsrud, Leif Anders (2022)
We propose a simple method to quantify narratives from textual data, and identify what we label “narrative monetary policy surprises” as the difference in narrative focus in central bank communication accompanying interest rate meetings and economic media coverage prior to those meetings. Identifying narrative surprises in this way using Norwegian data provides surprise measures that are uncorrelated with conventional monetary policy surprises, and, in contrast to such surprises, have a significant effect on subsequent media coverage. In turn, narrative monetary policy surprises lead to macroeconomic responses similar to what recent monetary policy literature associates with the information component of monetary policy communication, highlighting media’s role as information intermediaries.
Larsen, Vegard Høghaug & Thorsrud, Leif Anders (2021)
Asset returns, news topics, and media effects
The Scandinavian Journal of Economics, 124(3), s. 838- 868. Doi: 10.1111/sjoe.12469
We decompose the textual data in a daily Norwegian business newspaper into news topics and investigate their predictive and causal role for asset prices. Our findings suggest that news published through the mass media has significant, persistent, and potentially economically profitable predictive power for returns. Moreover, during an exogenous media strike returns for firms particularly exposed to our news measure experience a substantial fall relative to the control group. Together these findings lend support for a view where the media act as “information intermediaries” between agents and the state of the world, and disseminate fundamental information to investors.
Larsen, Vegard Høghaug; Thorsrud, Leif Anders & Zhulanova, Julia (2021)
News-driven inflation expectations and information rigidities
Using a large news corpus and machine learning algorithms we investigate the role played by the media in the expectations formation process of households, and conclude that the news topics media report on are good predictors of both inflation and inflation expectations. In turn, in a noisy information model, augmented with a simple media channel, we document that the time series features of relevant topics help explain time-varying information rigidity among households. As such, we provide a novel estimate of state-dependent information rigidities and present new evidence highlighting the role of the media in understanding inflation expectations and information rigidities.
Røed Larsen, Erling; Anundsen, André Kallåk, Kivedal, Bjørnar Karlsen & Thorsrud, Leif Anders (2020)
Behavioral changes and policy effects during Covid-19: Evidence from day-by-day sales and bid-by-bid auction logs in the housing market, (with André K. Anundsen, Bjørnar Karlsen Kivedal, and Leif Anders Thorsrud. Housing Lab Working Paper Series 2020-3.
In this paper we develop the first model to incorporate the dynamic productivity consequences of both the spending effect and the resource movement effect of oil abundance. We show that doing so dramatically alters the conclusions drawn from earlier models of learning by doing (LBD) and the Dutch disease. In particular, the resource movement effect suggests that the growth effects of natural resources are likely to be positive, turning previous growth results in the literature relying on the spending effect on their head. We motivate the relevance of our approach by the example of a major oil producer, Norway. Empirically we find that the effects of an increase in the price of oil may resemble results found in the earlier Dutch disease literature, while the effects of increased oil activity increases productivity in most industries. Therefore, models that only focus on windfall gains due to increased spending potential from higher oil prices, would conclude – incorrectly based on our analysis – that the resource sector cannot be an engine of growth.
Larsen, Vegard Høghaug & Thorsrud, Leif Anders (2019)
This article quantifies the epidemiology of media narratives relevant to business cycles in the US, Japan, and Europe (euro area). We do so by first constructing daily business cycle indexes computed on the basis of the news topics the media writes about. At a broad level, the most influential news narratives are shown to be associated with general macroeconomic developments, finance, and (geo-)politics. However, a large set of narratives contributes to our index estimates across time, especially in times of expansion. In times of trouble, narratives associated with economic fluctuations become more sparse. Likewise, we show that narratives do go viral, but mostly so when growth is low. While narratives interact in complicated ways, we document that some are clearly associated with economic fundamentals. Other narratives, on the other hand, show no such relationship, and are likely better explained by classical work capturing the market’s animal spirits.
Bjørnland, Hilde C & Thorsrud, Leif Anders (2018)
Commodity prices and fiscal policy design: Procyclical despite a rule