This paper investigates the proximate causes of excessively cyclical employment growth and persistently high unemployment among Black workers, relative to White workers. Using data from the Quarterly Workforce Indicators and Job-to-Job Flows, we find that the concentration of Black workers in highly cyclical industries cannot account for the excess cyclicality; rather, Black employment tends to be more volatile regardless of industry. The high level and excessive cyclicality of unemployment among Blacks compared to Whites can be traced to lower job finding rates overall and higher and more cyclical separation rates in most industries.

This paper investigates the past decade's increase in wealth inequality along racial and ethnic lines. Using a new measure of wealth stratification based on data from the Survey of Consumer Finances, we find that stratification increased significantly for blacks from 2007 to 2016; Hispanics exhibited a similar but less pronounced trend. Our regression analysis shows that relative to whites, blacks and Hispanics tend to invest more in houses and less in stocks, controlling for observable demographic factors. Consequently, these groups did not benefit as much as whites from the decade's spectacular increase in stock prices.

This paper's goal is to determine whether the degree of labor market tightness affects the frequency of discrimination charges. State-level panel data on enforcement and litigation actions from the US Equal Employment Opportunity Commission, along with disaggregated labor market statistics, allow us to assess the effects of labor market conditions on discrimination based on race or ethnicity, and how these effects vary across states and over time. Our findings have implications for how macroeconomic policies might be used to promote equal opportunity in the labor market.

In November 2008, the Federal Reserve faced a deteriorating economy and a financial crisis. The federal funds rate had already been reduced to virtually zero. Thus, the Federal Reserve turned to unconventional monetary policies. Through “quantitative easing,” the Fed announced plans to buy mortgage-backed securities and debt issued by government-sponsored enterprises. Subsequent purchases would eventually lead to a five-fold expansion in the Fed’s balance sheet, from $900 billion to $4.5 trillion, and leave the Fed holding over 20 percent of all mortgage-backed securities and marketable Treasury debt. In addition, Fed policy statements in December 2008 began to include explicit references to the likely path of the federal funds interest rate, a policy that came to be known as “forward guidance.” The Fed ceased its direct asset purchases in late 2014. Starting in October 2017, it has allowed the balance sheet to shrink gradually as existing assets mature. From December 2015 through June 2018, the Fed has raised the federal funds interest rate seven times. Thus, the time is ripe to step back and ask whether the Fed’s unconventional policies had the intended expansionary effects—and by extension, whether the Fed should use them in the future.

This paper’s goal is to determine whether the degree of labor market tightness affects the frequency of discrimination charges. State-level panel data on enforcement and litigation actions from the U.S. Equal Employment Opportunity Commission, along with disaggregated labor market statistics, allow us to assess the effects of labor market conditions on discrimination based on race or ethnicity, and how these effects vary across states and over time. Our findings have implications for how macroeconomic policies might be used to promote equal opportunity in the labor market.

Using data from 57 countries spanning more than three decades, this paper investigates the effectiveness of nine non-interest rate policy tools, including macroprudential measures, in stabilising house prices and housing credit. In conventional panel regressions, housing credit growth is significantly affected by changes in the maximum debt-service-to-income (DSTI) ratio, the maximum loan-to-value ratio, limits on exposure to the housing sector and housing-related taxes. But only the DSTI ratio limit has a significant effect on housing credit growth when we use mean group and panel event study methods. Among the policies considered, a change in housing-related taxes is the only policy tool with a discernible impact on house price appreciation.

There are many possible causes of housing cycles, such as housing demand, interest rates, and credit supply—not to mention irrational exuberance. This paper's goal is to assess the contribution of one specific factor, the worldwide supply of bank credit, to house price fluctuations. This is particularly relevant to the previous decade's boom–bust cycle, which coincided with a significant increase in the volume of international lending. Motivated by the observation that much of this lending flowed to emerging market economies (EMEs), the paper investigates the possibility that changes in global lending supply had a disproportionate impact on those economies. The analysis is methodologically innovative, using a panel vector autoregression (VAR) and utilizing instruments external to the system to achieve identification. Another contribution is the assembly of an impressive global data set of property prices, pulling together data from the Bank for International Settlements (BIS), the Organisation for Economic Co-operation and Development (OECD), and a variety other public and private sources. The relationship between credit and house prices is straightforward and at some level almost mechanical. After all, financing the purchase of houses with accelerating prices will inevitably require an ever-increasing volume of credit. What is interesting is that so much of the credit growth from 2002 to 2007 came from foreign sources. The price–credit link is clearly evident in Figure 1, which plots an index of the average level of real house prices for 57 countries along with the real “global liquidity” series used in the paper and interpreted as a measure of worldwide loan supply.1 The fit is striking. House prices and “global liquidity” both accelerated sharply in the early 2000s and contracted in 2008. In addition, there appears to be a robust long-run relationship between the two, although the authors do not model it explicitly. Aggregate House Prices and Liquidity. Notes: The aggregate house price is based on the data used in Kuttner and Shim (2012, 2013), calculated as the cumulative average real growth rate of house prices for each of the 57 countries in the data set. The real liquidity series is the same data as those used in the paper. This pattern does not prove that shifts in global credit supply cause house price fluctuations, of course. The “global liquidity” variable used in the paper, which is based on data from the BIS, is simply the observed amount of cross-border bank lending. Since this is an equilibrium outcome, it will be affected by both supply and demand factors.2 In order to disentangle the two, the authors make the plausible assumption that demand (“pull”) factors are domestic in origin while supply (“push”) factors are external or global in nature. The difficulty is that two of the external variables used in the analysis—the real exchange rate and the current account balance—are also influenced by domestic developments. The distinction between internal and external variables is therefore not sufficient to isolate credit supply. The authors’ identification strategy makes clever use of the “small country” assumption, which allows them to treat foreign variables as exogenous, and the use of monetary and financial variables from the U.S. as instruments. This is an excellent idea in principle, but in practice some of these variables are influenced by non-U.S. factors. The VIX, for example, rose sharply in 1997–98 during the Asian and Russian crises, reflecting instability in emerging markets rather than conditions in the U.S. Its validity as an instrument for global loan supply is therefore questionable. The salient empirical finding is that that property markets are considerably more volatile in EMEs than in advanced economies. More importantly, the VAR analysis shows that the EMEs respond much more strongly to “global liquidity” shocks than advanced economies: the current account response is twice as large in EMEs, and the house price response is five times the size. Missing from the analysis is a quantitative assessment of the shocks’ contribution to house price volatility, something analogous to the variance decomposition from a conventional VAR model. For example, it would be interesting to know what proportion of the doubling of Poland's house prices between 2005 and 2007 was due to global credit supply, as opposed to factors specific to that country. Such an assessment would have important policy implications. If the growth in domestic demand accounted for most of the boom, then contractionary monetary policy might have been warranted. On the other hand, contractionary policy would have been counterproductive if the lending was primarily the result of “push” factors, as tighter policy would have exacerbated the capital inflow and put upward pressure on the exchange rate. In addition, the results shed little light on what explains the disparities between countries in the response to “global liquidity” shocks. Why did Estonia experience a fourfold price increase followed by a collapse, while prices in Switzerland only took off after the global bust? The domestic variables in the regression play a role, of course, but so do monetary and exchange rate policies. More generally, the paper's broad-brush dichotomy between advanced economies and EMEs conceals a great deal of interesting heterogeneity within these categories. Very different results might have been obtained had the set of countries been partitioned along different lines. Stark intracategory differences are visible in Figure 2, which plots real house prices for four distinct sets of countries. Panels (a) and (b) in the top row show prices and “global liquidity” for advanced economies, distinguished according to the state of the housing market post-2007. The countries plotted in (a) are those with pronounced price declines, a group that includes the U.S. and Great Britain. Not all countries experienced busts, however. Panel (b) shows the aggregate house price for a distinct set of countries, including Switzerland and Canada, whose prices continued to rise, despite the pullback in cross-border lending. Another observation is that in both sets of countries, rapid house price growth preceded the 2002 surge in cross-border lending, and did not accelerate once lending took off. These patterns suggest that “global liquidity” did not play much of a role in these countries’ housing markets. This inference is consistent with the paper's findings, and not surprising in light of the depth of these countries’ financial markets. House Prices and Liquidity for Four Alternative Country Groupings. Notes:The “advanced economies, boom and bust” group (panel (a)) includes Spain, France, Great Britain, Greece, Ireland, Iceland, Italy, Malta, the Netherlands, New Zealand, and the U.S. The “advanced economies, boom but no bust” group (panel (b)) includes Austria, Australia, Belgium, Canada, Switzerland, Finland, Norway, and Sweden. The “emerging Asia + Latin America” group (panel (c)) includes China, Indonesia, Hong Kong, India, Korea, Malaysia, Thailand, Singapore, Taiwan, Chile, Colombia, Mexico, and Peru. The “transition economy” group (panel (d)) includes Bulgaria, the Czech Republic, Estonia, Croatia, Hungary, Latvia, Lithuania, Poland, Romania, Serbia, Russia, Slovenia, Slovakia and the Ukraine. See also notes to Figure 1. Panel (c) in the bottom row displays the relationship between house prices and “global liquidity” for the emerging economies in Asia and Latin America.3 Prices fell steeply in 1997–98 due to the Asian financial crisis. (The magnitude of the decline is attenuated by the inclusion of Latin America.) House price growth remained relatively restrained throughout the early- to mid-2000s, however, even as cross-border lending accelerated. And after a relatively mild downturn in 2008, prices continued their upward trend in spite of the drying up of “global liquidity.” The overall real appreciation over the 2000–12 period was approximately 40%, similar to house price growth in the advanced economies. The story is very different for the transition economies of Central and Eastern Europe, shown in Panel (d). The housing booms in some of these countries were nothing short of spectacular. In Estonia, for example, prices shot up by a factor of 4. As a group, those countries’ housing prices peaked in 2007 at 180% of their 2000 level and fell sharply during the global financial crisis. Interestingly, the relationship between house prices and “global liquidity” for this group appears to be much tighter than for the other three. Taken together, these observations suggest that the volatility the authors attribute to EMEs generally is actually specific to the transition economies of Central and Eastern Europe. And we know that many factors unique to the region were at least partly responsible to the countries’ boom–bust cycles. The prevalence of currency boards and hard pegs is one. In addition, having just gone through a period of radical economic liberalization, there was an explosion in housing demand and a seemingly limitless appetite for borrowing. With very little domestic saving and poorly developed financial systems, the lion's share of the funding naturally came from abroad—much in the form of loans denominated in Swiss francs and other foreign currencies. Overall, the paper contributes a great deal to our understanding of housing cycles. Its carefully crafted empirical analysis provides compelling evidence on the impact on house prices of shocks in the global supply of bank credit. The underlying economic sources of the shocks remain unclear, however. Was the previous decade's increase in lending due to the global savings glut? Financial innovation? Expansionary monetary policy? Formulating an appropriate policy response requires a better grasp of what exactly drives global loan supply. We also need to know more about the country-specific characteristics that affect the transmission of global credit supply shocks. Besides the monetary and exchange rate policies mentioned earlier, other relevant attributes include things like the structure of the mortgage market and the degree of financial development. Loan supply and demand will also be affected by regulatory measures, including the non–interest rate policies examined in Kuttner and Shim (2012, 2013). The emerging market/advanced economy breakdown is not informative in these respects. For example, Hong Kong is similar to Bulgaria in that both have currency boards, but by any measure Hong Kong's financial system is much more highly developed than Bulgaria's. Similarly, the financial systems of Bulgaria and Serbia are probably roughly comparable in terms of depth and development, but unlike Bulgaria, Serbia had a managed float. Distinguishing between economies along some of these other dimensions is likely to yield a better understanding of the transmission mechanism. Kenneth N. Kuttner is at the Department of Economics at Williams College (E-mail: [email protected]).

This chapter establishes the failure to exercise standard macroeconomic stabilization polices in Japan over the last twenty years and look at why this happened. The chapter charts a future course for fiscal and monetary policy in Japan, based on a reasonable degree of Bank of Japan (BoJ) and Ministry of Finance (MoF) coordination and sounder policy approaches in line with international norms. It argues that the institutional reform and change in bureaucratic culture to limit the potential for a repeat of macroeconomic policies to go astray for long periods. By allowing fiscal considerations to affect monetary policy, policy coordination would make the promise of higher inflation more credible. Similarly, a rapidly rising public debt-to-GDP Gross domestic product (GDP) ratio, largely driven by population ageing and an arguably unsustainable level of social security and medical expenditures, has constrained the Japanese government's open-ended use of expansionary fiscal policy.

Prime Minister Shinzo Abe's economic policies--dubbed Abenomics--have been successful on some but not all fronts. The Japanese government must still pursue policies to increase economic growth. This PIIE Briefing, released on the heels of Prime Minister Abe's election victory in December, calls on Japan, for example, to be flexible in the negotiations for a Trans-Pacific Partnership (TPP) trade deal and to take steps to achieve fiscal sustainability over the medium and long term. The papers in this volume were presented at the first seminar of the High-Level Working Group on Japan-US Common Economic Challenges on June 3, 2014, and it includes an assessment of Abenomics by PIIE president Adam S. Posen. The initiative, launched by the Peterson Institute for International Economics, the Sasakawa Peace Foundation USA, and the Sasakawa Peace Foundation, brings together distinguished economists and former government officials from both countries, providing a forum to illuminate important US-Japan issues and produce policy advice and research ideas. The second session of this Working Group was held on December 18-19, 2014 in Tokyo.

This paper revisits the relationship between interest rates and house prices. Surveying a number of recent studies and bringing to bear some new evidence on the question, this paper argues that in the data, the impact of interest rates on house prices appears to be quite modest. Specifically, the estimated effects are uniformly smaller than those implied by the conventional user cost theory of house prices, and they are too small to explain the previous decade’s real estate boom in the U.S. and elsewhere. However in some countries, there does appear to have been a link between the rapid expansion of the monetary base and growth in house prices and housing credit.

Since the global financial crisis of 2007–09, economists and policymakers have struggled to understand the causes of asset price booms and busts. The challenge is illustrated in Figure 1, which shows the path of real property prices from 2000 through 2010 for seven advanced economies (Austria, Canada, Denmark, Ireland, Norway, the United Kingdom and the United States). One question is why property prices in all seven of these countries (and many more besides) all rose and fell over roughly the same period. Was a common factor at work across countries, and if so, what was it? The second question is why the size of the boom differed across countries. What explains the fact that house prices doubled in the United Kingdom, but appreciated only slightly in Austria?

Recent events have underscored the importance of asset price booms and busts as sources of financial instability. Unsustainable property price appreciation figured prominently in the 2007–2009 financial crisis, in the 1997–1998 Asian financial crisis, and in Japan’s property market collapse in the early 1990s. Monetary policy has come under intense scrutiny as a possible factor contributing to the escalation in real estate prices, with some blaming the US Federal Reserve’s low interest rate policy for creating a bubble in the US housing market.