The Unassuming Economist

From the IMF’s latest report on Spain:

“House prices have increased in recent years, although from a low level and without signs of a construction boom. While there is no clear evidence of a significant price misalignment yet, the authorities need to be vigilant. The set of macroprudential tools should be expanded to deal with potential financial stability risks.

The ongoing price recovery is not associated with a construction boom. House prices have increased by around 15 percent between 2014–17, boosted by fast recoveries in cities like Madrid and Barcelona. Registered sales have disproportionately risen among existing dwellings, whereas new-dwelling transactions are still well below their pre-crisis peak. Despite early signs of mild supply-side recovery, such as an increase in new construction approvals from a low level, the housing stock has barely risen so far. In the overall economy, the contribution of value added from the construction sector is nearly half of what it was before the crisis. These trends have been accompanied by a small decline in home ownership (from 80 to 77 percent between 2008–17), while renting activity has strengthened. Against this background, new rent subsidy programs and social home loans were recently introduced. The authorities are also considering expanding the social housing stock.

Although house prices are rising, there is no strong evidence of a clear overvaluation yet. Two approaches are used to assess house price misalignment. The first approach measures deviations from historical averages of the price-to-rent and the price-to income ratios. As of 2017:Q4, both ratios stand at roughly similar levels as in mid-2003 and less than one standard deviation above their historical averages, thus indicating no overvaluation. The second approach is a regression that includes the growth rates of income per capita, working-age population, interest rates, equity prices, and construction costs, as well as a long-term equilibrium relationship with the price-to-income ratio, which measures housing
affordability. This model suggests a slight overvaluation in 2017:Q4. However, this regression-based result should be treated with caution given that the model is particularly
limited in capturing supply-side dynamics.

To prevent financial stability risks emerging, the macroprudential toolkit should be expanded and ready to be used. While housing valuation gaps are not significant so far and households’ balance sheets have gradually improved since 2012, persistent demand pressures in the housing market could increase risks to financial stability. As noted in the 2017 FSAP, banks are highly exposed to real estate sector developments, and therefore the macroprudential toolkit should be expanded to deal with risks associated with that exposure (see IMF Country Reports No. 17/321 and 17/336). Other actions would be welcome to: (i) further improve balance sheets in the construction and real estate sectors; (ii) encourage greater use of fixed-rate mortgages; (iii) ensure that eligibility criteria for social home loans and rent subsidies are prudently assessed; and (iv) improve housing development regulation to address supply constraints. Any new measures aimed at reducing rent pressures should avoid causing negative supply-side effects with adverse impact on low-income renters.”

From a new working paper by Angelina Hackmann and Torben Klarl:

“Exploiting the cascade structure of cities and based on a dataset for U.S. cities between 1840 and 2016, the aim of this short paper is to answer three important questions: First, do we
observe that the U.S. city size distribution exhibits a smooth transition to Zipf’s law from the beginning or are there periods showing a pronounced departure from Zipf’s law? Second, if we observe periods of departure, which alternative laws instead should be used to accurately describe the city size distribution? Third, employing information from the cascade structure of cities, do we always find evidence for primate cities for a specific period of time? Inter alia, we find that the exact Zipf’s law has evolved over time from the more general, so-called threeparameter Zipf’s law which can be traced back to Mandelbrot (1982).”

 

From Conversable Economist:

“Imagine two people who have seemingly equal skills and background. They go to work for two different companies. However, one “superstar” company grows much faster, so that wages and opportunities in that company also grow much faster. Or they go to work in two different cities. One “superstar” urban economy grows much faster, so that wages and opportunities in that city also grow faster.

Of course, such patterns of unequal growth have always existed  to some extent. When evaluating a potential employer or location choice, people  have always taken into account the potential for joining a superstar performer. The interesting question is whether the gap between superstar and ordinary firms, or between superstar and ordinary cities, has been growing or changing over time. For example, some argue that the rise of superstar firms, and the resulting rise in between-firm performance and labor compentiation, can explain most of the rise in US income inequality.

The McKinsey Global Institute has a nice report summarizing past evidence and offering new evidence of their own in Superstars: The Dynamics of Firms, Sectors, and Cities Leading the Global Economy(October 2018). It’s written by a team led by James Manyika, Sree Ramaswamy,  Jacques Bughin, Jonathan Woetzel, Michael Birshan, and Zubin Nagpal. Short summary: Superstar firms and cities do seem to be widening their economic leadership gap, with the evidence that certain sectors are superstars seems weaker.

For superstar firms, the report notes:

“For firms, we analyze nearly 6,000 of the world’s largest public and private firms, each with annual revenues greater than $1 billion, that together make up 65 percent of global corporate pretax earnings. In this group, economic profit is distributed along a power curve, with the top 10 percent of firms capturing 80 percent of economic profit among companies with annual revenues greater than $1 billion. We label companies in this top 10 percent as superstar firms. The middle 80 percent of firms record near-zero economic profit in aggregate, while the bottom 10 percent destroys as much value as the top 10 percent creates. The top 1 percent by economic profit, the highest economic-value-creating firms in our sample, account for 36 percent of all economic profit for companies with annual revenues greater than $1 billion. Over the past 20 years, the gap has widened between superstar firms and median firms, and also between the bottom 10 percent and median firms. … The growth of economic profit at the top end of the distribution is thus mirrored at the bottom end by growing and increasingly persistent economic losses …”

 

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On cross-country:

• Living and Leaving: Housing, Mobility and Welfare in the European Union – World Bank
• Why house prices in global cities are falling – Economist
• Comment – On building typologies of housing systems in the OECD – IDEAS

On the US:

• California Midterm Results: Funding for Affordable Housing and a Rent Control Defeat – New York Times
• Collateral Damage: The Impact of Foreclosures on New Home Mortgage Lending in the 1930s – NBER
• No boom, no bust in US housing – Financial Times
• Local Banks, Credit Supply, and House Prices – Federal Reserve Bank of New York
• Income Tax Expenditures for Housing and Homeownership – Tax Policy Center
• Housing America’s Older Adults 2018 – Harvard Joint Center for Housing Studies
• Housing Sentiment Continues Downward Trend Despite Favorable Economy – Fannie Mae
• Buy young, earn more: Buying a house before age 35 gives homeowners more bang for their buck – Urban Institute
• Consumer-Lending Discrimination in the Era of FinTech – UC Berkeley
• Supply Skepticism: Housing Supply and Affordability – NYU Furman Center
• Why Cities Must Tackle Single-Family Zoning – CityLab

On other countries:

• [Australia] Assessing the Effects of Housing Lending Policy Measures – Reserve Bank of Australia
• [China] A Fifth of China’s Homes Are Empty. That’s 50 Million Apartments – Bloomberg
• [France] New or old, why would housing price indices differ? An analysis for France – IDEAS
• [France] The impact of the 2014 increase in the real estate transfer taxes on the French housing market – IDEAS
• [France] Paris property benefits from Brexit bounce – Financial Times
• [France] Does issuing building permits reduce the cost of land? – Bourgogne Franche‑Comté
• [Italy] Home is where the ad is: online interest proxies housing demand – EPJ Data Science
• [Slovak Republic] Housing Policy in the Slovak Republic – Slovak University of Technology in Bratislava
• [Spain] La demanda sigue impulsando nuevos proyectos de inversión residencial – BBVA
• [United Kingdom] The collapse in public ownership of land – Financial Times

Photo by Aliis Sinisalu

From the IMF’s latest Regional Economic Outlook report for Europe:

“This chapter documents the increasing use of macroprudential policies (MaPPs) in Europe in recent years to build financial resilience, contain general and sectoral credit growth, and limit house price increases. Considering these objectives and drawing from case studies, the chapter finds evidence that borrower-side measures, supported by lender-side measures, helped limit the share of riskier mortgages, thereby building resilience. Evidence is more mixed as to the ability of MaPPs to contain house price and overall credit growth against the backdrop of a still-accommodative monetary policy and other factors.

Macroprudential Measures in European Countries

The recent reacceleration in house prices has prompted the adoption of MaPPs in several European countries. Though credit and house price concerns are not yet generalized, house prices have increased substantially in several European countries over the past few years (…). In most of these countries, higher house prices have been accompanied by rising household debt (…) and rapid household credit growth (…).

To contain the buildup of systemic risks, especially in the residential housing market, many European countries have strengthened their MaPPs (…). While MaPPs have been
implemented across Europe, countries with larger postcrisis increases in house prices and household debt tended to adopt more MaPPs (…).

The main objectives of the recently introduced MaPPs, as stated by country authorities, were improving financial stability, building financial resilience, and containing general and sectoral credit growth. Within these broader objectives, policies were generally focused on protecting borrowers, strengthening banking systems, and slowing down house price increases (…). The latter was an objective in most economies, but particularly in the Czech Republic, Estonia, Norway, and Sweden.

In some countries (Estonia, Norway, Switzerland), the relaxation of lending standards was a major concern. Constraining the rise in the share of loans denominated in foreign currency was a prominent goal in Hungary. The various capital buffers adopted beginning in 2013, in line with the EU Capital Requirements Directive (CRD IV), were aimed at containing not only housing sector imbalances, but also credit cycle swings.”

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