The Unassuming Economist

From a new ECB Research Bulletin:

“How beneficial is labour market flexibility – for instance, the ability to hire and fire workers – for firm growth? And how does such flexibility interact with a firm’s ability to obtain bank credit? This article provides evidence that less rigid employment protection benefits firms during times of scarce credit. We study the performance of credit constrained Spanish firms during the financial crisis of 2008-09, exploiting a firm-size-specific labour regulation that imposes more stringent employment protection on firms with more than 50 employees. We find that Spanish firms with fewer than 50 employees operating in sectors in which labour and capital are close substitutes grew faster during the financial crisis when exposed to a negative credit shock than similarly credit constrained but larger firms. This effect is more pronounced for firms that were more productive before the crisis, suggesting that flexible employment protection laws benefit otherwise healthy firms that are credit constrained, by enabling them to substitute labour for capital and continue growing.”

A new working paper introduces “an original panel dataset based on the text of country reports by the International Monetary Fund. It consists of a total of 2594 Article IV consultation and program review documents. The reports were published between 2004 and 2017 and cover 189 countries. The text of these reports provides a unique in-depth window into the IMF ‘s assessment of the most important macroeconomic issues. They provide indications of the perceived policy weaknesses, economic risks, ongoing reforms and implemented or neglected policy advice. Thus the content of IMF reports are widely used for qualitative and quantitative analysis in the economics, political science and IR literature.”

The paper also presents “three examples in applying text analytic techniques on the dataset to demonstrate and validate its application for research. First, [it] compares conventional measures of resource dependence with a metric based on term frequency in reports. ”

“Second, [it] analyzes mentions preceding reform events as a way to study reform intent.”

“Finally, [it] shows how mentions of keywords describing opposite fiscal policy stances mimic changes in IMF policy advice during the global financial crisis.”

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 …”

 

Continue reading here.

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.”

Continue reading here.