Housing Boom and Headline Inflation: Insights from Machine Learning

Housing Boom and Headline Inflation: Insights from Machine Learning
Author: Yang Liu
Publisher: International Monetary Fund
Total Pages: 45
Release: 2022-07-28
Genre: Business & Economics
ISBN:

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Inflation has been rising during the pandemic against supply chain disruptions and a multi-year boom in global owner-occupied house prices. We present some stylized facts pointing to house prices as a leading indicator of headline inflation in the U.S. and eight other major economies with fast-rising house prices. We then apply machine learning methods to forecast inflation in two housing components (rent and owner-occupied housing cost) of the headline inflation and draw tentative inferences about inflationary impact. Our results suggest that for most of these countries, the housing components could have a relatively large and sustained contribution to headline inflation, as inflation is just starting to reflect the higher house prices. Methodologically, for the vast majority of countries we analyze, machine-learning models outperform the VAR model, suggesting some potential value for incorporating such models into inflation forecasting.

Price Expectations and the U.S. Housing Boom

Price Expectations and the U.S. Housing Boom
Author: Pascal Towbin
Publisher: International Monetary Fund
Total Pages: 35
Release: 2015-07-30
Genre: Business & Economics
ISBN: 1513596233

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Between 1996 and 2006 the U.S. has experienced an unprecedented boom in house prices. As it has proven to be difficult to explain the large price increase by observable fundamentals, many observers have emphasized the role of speculation, i.e. expectations about future price developments. The argument is, however, often indirect: speculation is treated as a deviation from a benchmark. The present paper aims to identify house price expectation shocks directly. To that purpose, we estimate a VAR model for the U.S. and use sign restrictions to identify house price expectation, housing supply, housing demand, and mortgage rate shocks. House price expectation shocks are the most important driver of the boom and account for about 30 percent of the real house price increase. We also construct a model-based measure of exogenous changes in price expectations and show that this measure leads a survey-based measure of changes in house price expectations. Our main identification scheme leaves open whether expectation shifts are realistic or unrealistic. In extensions, we provide evidence that price expectation shifts during the boom were primarily unrealistic and were only marginally affected by realistic expectations about future fundamentals.

The Pricing-Out Phenomenon in the U.S. Housing Market

The Pricing-Out Phenomenon in the U.S. Housing Market
Author: Francesco Beraldi
Publisher: International Monetary Fund
Total Pages: 47
Release: 2023-01-06
Genre: Business & Economics
ISBN:

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The COVID-19 pandemic further extended the multi-year housing boom in advanced economies and emerging markets alike against massive monetary easing during the pandemic. In this paper, we analyze the pricing-out phenomenon in the U.S. residential housing market due to higher house prices associated with monetary easing. We first set up a stylized general equilibrium model and show that although monetary easing decreases the mortgage payment burden, it would raise house prices, lower housing affordability for first-time homebuyers, and increase housing wealth inequality between first-time and repeat homebuyers. We then use the U.S. household-level data to quantify the effect of the house price change on housing affordability relative to that of the interest rate change. We find evidence of the pricing-out effect for all homebuyers; moreover, we find that the pricing-out effect is stronger for first-time homebuyers than for repeat homebuyers. The paper highlights the importance of accounting for general equilibrium effects and distributional implications of monetary policy while assessing housing affordability. It also calls for complementing monetary easing with well-targeted policy measures that can boost housing affordability, particularly for first-time and lower-income households. Such measures are also needed during aggressive monetary tightening, given that the fall in house prices may be insufficient or too slow to fully offset the immediate adverse impact of higher rates on housing affordability.

Boom-Bust Cycles in Housing: The Changing Role of Financial Structure

Boom-Bust Cycles in Housing: The Changing Role of Financial Structure
Author: Calvin Schnure
Publisher: INTERNATIONAL MONETARY FUND
Total Pages: 27
Release: 2005-10-01
Genre: Business cycles
ISBN: 9781451862195

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Why are housing markets so prone to boom-bust cycles? The mortgage market structure prior to the Savings and Loan crisis contributed to the volatility in real housing activity which, in turn, amplified the volatility in housing prices. The subsequent development of a national, market-based system of securitized mortgage finance has damped this boom-bust cycle. We test whether deviations of actual housing prices from values forecast by a model based on economic fundamentals have responded to the change in financial structure, and find that pricing errors have fallen significantly since the mid-1980s. Tests of the relative importance of the change in financial market structure versus the reduction of inflation over this period indicate a primary role for market structure in improving pricing efficiency.

From Data to Insights

From Data to Insights
Author: Jürgen Deppner
Publisher:
Total Pages: 0
Release: 2023
Genre:
ISBN: 9783882464900

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Apartment Pricing Prediction in the Panamanian Real Estate Market

Apartment Pricing Prediction in the Panamanian Real Estate Market
Author: Agustin Guerra
Publisher:
Total Pages: 0
Release: 2023
Genre:
ISBN:

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The development of urban spaces in big cities and the formulation of housing policies are closely intertwined with the pricing of houses. This relationship becomes particularly critical in developing countries where affordable housing is a significant concern due to issues such as lack of transparency and equality. In this study, we focus on evaluating house pricing in Panama City by leveraging five machine-learning models, including linear regression, polynomial regression, random forest, artificial neural networks, and extreme gradient boosting trees. Our evaluation reveals that house price variation in Panama City does not follow a linear pattern, and the extreme gradient boosting trees algorithm performs the best in terms of the accuracy of price prediction. Additionally, our findings indicate that house pricing in Panama is primarily influenced by hedonic factors such as area and location. By shedding light on these dynamics, this research contributes to a better understanding of the housing market in Panama City. Moreover, our insights can inform policymakers and stakeholders in addressing the issue of housing policy, urban planning, and investments. These findings have the potential to drive effective strategies to tackle the challenges associated with affordable housing in Panama City. Finally, this study serves as a stepping stone for the further development of robust predictive models considering more layers in urban computing, such as transportation networks, demographics, crime rate, and environmental factors.

Handbook of Economic Forecasting

Handbook of Economic Forecasting
Author: Graham Elliott
Publisher: Elsevier
Total Pages: 667
Release: 2013-08-23
Genre: Business & Economics
ISBN: 0444627405

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The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. Focuses on innovation in economic forecasting via industry applications Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications Makes details about economic forecasting accessible to scholars in fields outside economics

Global Waves of Debt

Global Waves of Debt
Author: M. Ayhan Kose
Publisher: World Bank Publications
Total Pages: 403
Release: 2021-03-03
Genre: Business & Economics
ISBN: 1464815453

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The global economy has experienced four waves of rapid debt accumulation over the past 50 years. The first three debt waves ended with financial crises in many emerging market and developing economies. During the current wave, which started in 2010, the increase in debt in these economies has already been larger, faster, and broader-based than in the previous three waves. Current low interest rates mitigate some of the risks associated with high debt. However, emerging market and developing economies are also confronted by weak growth prospects, mounting vulnerabilities, and elevated global risks. A menu of policy options is available to reduce the likelihood that the current debt wave will end in crisis and, if crises do take place, will alleviate their impact.

How I Became a Quant

How I Became a Quant
Author: Richard R. Lindsey
Publisher: John Wiley & Sons
Total Pages: 406
Release: 2011-01-11
Genre: Business & Economics
ISBN: 1118044754

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Praise for How I Became a Quant "Led by two top-notch quants, Richard R. Lindsey and Barry Schachter, How I Became a Quant details the quirky world of quantitative analysis through stories told by some of today's most successful quants. For anyone who might have thought otherwise, there are engaging personalities behind all that number crunching!" --Ira Kawaller, Kawaller & Co. and the Kawaller Fund "A fun and fascinating read. This book tells the story of how academics, physicists, mathematicians, and other scientists became professional investors managing billions." --David A. Krell, President and CEO, International Securities Exchange "How I Became a Quant should be must reading for all students with a quantitative aptitude. It provides fascinating examples of the dynamic career opportunities potentially open to anyone with the skills and passion for quantitative analysis." --Roy D. Henriksson, Chief Investment Officer, Advanced Portfolio Management "Quants"--those who design and implement mathematical models for the pricing of derivatives, assessment of risk, or prediction of market movements--are the backbone of today's investment industry. As the greater volatility of current financial markets has driven investors to seek shelter from increasing uncertainty, the quant revolution has given people the opportunity to avoid unwanted financial risk by literally trading it away, or more specifically, paying someone else to take on the unwanted risk. How I Became a Quant reveals the faces behind the quant revolution, offering you?the?chance to learn firsthand what it's like to be a?quant today. In this fascinating collection of Wall Street war stories, more than two dozen quants detail their roots, roles, and contributions, explaining what they do and how they do it, as well as outlining the sometimes unexpected paths they have followed from the halls of academia to the front lines of an investment revolution.