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The Federal Reserve and its balance sheet: A Herculean task in mitigating the economic effects of the coronavirus pandemic (Part I)

Fotis Siokis
July 30, 2020

Introduction

Global pandemic events in history, beyond death and destruction, have caused major economic fallout and collapses in international trade. The recent COVID-19 pandemic belongs to this category and is considered the most perilous pandemic in the last 150 years apart from the Spanish influenza. The effects of the pandemic on the global and particularly on the U.S. real economy were immediate and devastating, causing a paralysis in economic activity and a dramatic increase in the unemployment rates, while financial market functioning was severely disrupted. To ensure that the economic damage induced by the pandemic would not be permanent or long lasting in light of these developments, the Federal Reserve (FED) responded rapidly and boldly by expanding the scope of its tools and instituting exceptional and unprecedented measures. In this post we describe the array of both conventional and unconventional monetary tools that were put to work and discuss some of the challenges for monetary policy going forward.

An Outline of Recent Federal Reserve Actions

In early March, the Fed went to work beginning with the reduction of the federal funds target rate to near zero in two subsequent not regularly scheduled Fed meetings. Moving beyond the conventional monetary policy tools, in mid-March the Fed proceeded with the use of unconventional tools, many of them employed in the previous financial crisis of 2007-2009. The Fed introduced an aggressive quantitative easing plan with purchases of unlimited amounts of longer-term assets, that is, U.S. Treasuries and agency mortgage-backed securities (ABS). The stated purpose of the purchases was to improve liquidity in the treasury and ABS markets. Similarly, the Fed utilized a variety of liquidity facilities, ranging from U.S. dollar swap lines to primary- and secondary-market corporate and municipal liquidity facilities, to main street new and expanded loan facilities for small- to medium-size enterprises. Although the analysis of all liquidity facilities initiatives is not within the scope of this article, we present them on Table 1.

Table 1: The FED’s action in response to the coronavirus threat

Source: Federal Reserve Board

We also discuss two main initiatives, namely the Commercial Paper Funding Facility and the introduction of a new-implemented measure, the Secondary Market Corporate Credit Facility. The reader should consult https://www.brookings.edu/research/fed-response-to-covid19/ for a thorough analysis of all facilities.

Two Liquidity Facilities explained

  1. Commercial Paper Funding Facility.

The Fed introduced for the second time the Commercial Paper Funding Facility in an attempt to provide ample liquidity and to encourage investors to reengage in term lending in the market. It was first created on October 27, 2008, as a result of the credit crunch faced by the financial intermediaries. Commercial paper is a short-term mostly unsecured debt instrument, issued with a discount, by corporations. Its purpose is to finance a wide range of economic activity and tends to have very short maturities ranging from a few days to several months. As an instrument, commercial paper is used widely for financing short-term liabilities. But because of the COVID-19, the market was placed under severe pressure. With very limited market demand, and investors reluctant in assuming unsecured debt, corporations were constrained and unable to issue longer-term commercial paper. The Fed, as of April 6th, and acting as a Lender of Last Resort began making purchases, mostly of high-rated eligible 3-month commercial paper (both unsecured and asset backed paper). The purchases are made through the employment of a Special Purpose Vehicle with a private corporation to serve as the investment manager. Since the introduction of this specific facility, the interest rates for all grade paper seem to have fallen (figure 1).

Figure 1. Interest rate on overnight AA Nonfinancial Commercial Paper
Source: Federal Reserve
  1. Secondary Market Corporate Credit Facility.

The second facility that distinguished itself from the others is the Secondary Market Corporate Credit Facility. While other major central banks have regularly used this facility in purchasing investment-grade corporate debt, the Fed engaged in such an action for the first time. Since May 12, it started purchasing exchange-traded funds (ETFs), and bonds mainly with investment grade of BBB and higher, in order to provide ample liquidity to corporates and calm down the volatile bond markets. As of May 20, the Fed holds around $1.8 billion of ETFs. The rational of buying ETF’s lies in the fact that such action could impact the prices of a wider spectrum of bonds. However, in addition to investment grade bonds, the Fed engages in ETFs purchases with high yield bonds including the so-called “fallen angels”, corporates that lost their investment grade due to adverse economic conditions. On some occasions “fallen angels” bonds were downgraded to speculative or junk grade. Purchasing of high-yield bonds, and, also investment grade corporate bonds could open Pandora’s box, since not only does the Fed assume credit risk, which could be quite worrisome and constrain the efficacy of monetary policy but also could threaten, along with other multidimensional activities, the Fed’s policy independence. The recent announcement of Hertz’s bankruptcy could be served as an example. Although, Fed’s exposure is limited or non-existent, the assumption of such credit risk could send mixed and blurred signals to the market. The purchases under the Secondary Market Corporate Credit Facilities program are made through the introduction of a special purchase vehicle and managed by a private firm. Since the introduction of the facility, the index of the high-yield ETFs increased considerably (figure 2).

Figure 2. The evolution of Investment Grade and high-yield ETFs Indexes
Source: Bloomberg

An Anatomy of the Fed’s Balance Sheet and the Emerging Challenges

The particularly aggressive response to the coronavirus crisis caused an enormous expansion of the Fed’s balance sheet, much higher than the already-elevated levels generated by the Great Recession crisis. The Fed’s balance sheet consists of assets and liabilities (plus the capital account). The asset side contains mainly the purchases of US treasury debt, Mortgage Back Securities (MBS) and federal agency debt securities, among other items, while the liability side contains Depositary Institutions’ reserves, both required and excess, plus outstanding currency (Federal Reserve Notes). Both of these items, in general, comprise the monetary base. When the Fed conducts expansionary monetary policy, it buys securities from commercial banks (and other dealers) and credits the related fund in depository institutions’ account held at the Fed. Therefore, it should be made clear that an increase in assets causes an increase in liabilities as well. Depository institutions keep required and excess reserves at the Fed for regulation compliance, to take care of transaction obligations, and to build a liquidity buffer in adverse situations. Depository institutions borrow and lend excess reserves at the effective Fed funds rate, which is influenced by the Fed’s policy.

Table 2. The Fed’s balance sheet, selected dates (in $ billions)

Source: Board of Governors, Factors affecting Reserve Balances, Consolidated Statement of Condition of All Federal Reserve Banks

Table 2 depicts the Fed’s balance sheet in three different time periods. Since the onset of the 2007 crisis, the assets as well as the liabilities have grown dramatically as a result of bond buying, commonly known as quantitative easing. The balance sheet expanded from $850 billion at the onset of the Great Recession crisis to almost $ 4.5 trillion by the end of 2014 and to the gargantuan size of $ 7.1 trillion in May 2020. The major component of the assets comprises the holdings of the U.S. Treasury bonds, which grew from $ 768 billion in 2007 to $ 4.4 trillion in 2014 and to approximately $6.0 trillion in May 2020. From the liability side, the reserves have grown from $28 billion prior to the crisis to almost $ 2.6 trillion at end of 2015 and owing to coronavirus monetary policy actions spiked to $ 4.8 trillion on May 20th, 2020, almost 160 times as great as the August 2007 figure. The growth of the balance sheet over time is also depicted in figure 3.

Figure 3. The evolution of the Fed’s balance sheet up to June 2020 (in $ billions)
Source: FRED, Federal Reserve of St. Louis.

The superabundance of reserve balances is attributed predominantly to the vast preponderance of excess reserves. It is argued that this could potentially be inflationary, since banks reserves are a component of the monetary base, which in the last decade grew at an unprecedented pace. However, although the balance sheet expanded to over $ 7 trillion, which ranks the highest among the major central banks, as a ratio to GDP, it is modest. Specifically, the Fed’s holdings are equal to 37% of GDP, compared with112% for Bank of Japan, 50% for European Central Bank and 57% for the Bank of England.

Conclusion

The recent events of increased purchases of longer-term assets illustrate the fact that central banks will rely more and more on balance sheet policy than on the traditional interest rate policy. Based on market estimates, the Fed’s balance sheet will grow further to the level of $9 as we entered into a deep recession placing over 38 million people out of employment. The liquidity facilities introduced by the Fed, with most of them extended through the end of this year, certainly could not cure the economic damage induced by the pandemic. But it is an imperative and a novel effort of mitigating the disastrous effects of it.

The Federal Reserve and its balance sheet: A Herculean task in mitigating the economic effects of the coronavirus pandemic (Part I)2020-10-04T16:25:08+00:00

New York’s Labor Market Steadies in May  

By Jim Orr,

The New York State Department of Labor reported that employment statewide increased by 98,000 (seasonally adjusted) in May, a recovery of about 5.0 % of the nearly 2 million jobs lost in the March/April period.  This gain was below the nationwide recovery in May of about 11.0 % of the jobs lost.  The bulk of May’s job gains in the state occurred outside of New York City: The U.S. Bureau of Labor Statistics reported that employment in the city was up by 6,000 in May, after having fallen by 944,000 in March/April.

New York State’s unemployment rate fell to 14.5% in May from 15.3% in April.  The state’s rate was moderately above the 13.3% unemployment rate nationwide in May.  The unemployment rate in New York City rose to 18.3% in May from 15.0% in April. 

The New York State Department of Labor reported filings of initial claims for Unemployment Insurance in the state totaled 97,000 during the week ending June 13; one month ago (the week ending May 16) new filings totaled 229,000.  In New York City, filings of initial claims for Unemployment Insurance totaled 50,000 during the week ending June 13; one month ago the number of new filings was more than 116,000. 

New York’s Labor Market Steadies in May  2020-06-27T06:27:01+00:00

The Pandemic and the Emerging Markets Crisis: How Fragile are the Economies?

Utku Demir and Merih Uctum 
June 11, 2020

The Emerging Market (EM) economies that came out of the 2008 financial crisis relatively faster than advanced economies are hard hit by a quadruple-whammy this time: the pandemic, capital outflows, economic recession, and debt crisis. In March 2020, more than USD100 billion flew out of the EMs.

This analysis looks at the flight to the safety of global investors and its impact on these economies that owe more than $8 trillion in foreign-currency debt.

The EMs have come a long way since the 1990s when they were unable to borrow in their currency, a phenomenon dubbed “the original sin” by Eichengreen and Hausmann, which made them dependent on external financial conditions. Adverse global conditions could lead to capital flight and depreciation of their exchange rate, which pushed their economies into insolvency since the value of the debt burden rose in local currency. If foreign creditors lost confidence in the local economy, they could abruptly reduce the international flow of the capital in the economy. This phenomenon is also often accompanied by domestic residents increasing their investment abroad. Called a “sudden stop,” the abrupt reversal of capital flows would be often accompanied by recession and a currency crisis through a run on EMs currency. During the last several decades, however, following improved economic and financial management and strengthened banking systems, most EMs have been able to borrow in their currencies. Yet, they now face another problem, the “original sin-redux,” as described by Carstens and Shin: since the performance of investors in EMs in local currency is evaluated in USD, a depreciation of the EM currency is costly for investors. So, during an international crisis, this heightened risk leads to capital flight and further depreciation of the currencies.  

EM economies are no strangers to capital flight. In recent history, several episodes led to capital outflows from these countries. Since the Global Financial crisis, they have been hit by the Taper Tantrum when the Fed decided to stop quantitative easing, which led to a market selloff of EM currencies in a panic; a Renminbi devaluation that reduced its value against the USD for the first time in 20 years and rattled the markets; and the 2018 EM selloff following global trade uncertainties and the strength of the USD. The market panic of this year has been more severe. As the spread of the coronavirus ripped through financial markets and fears of a recession gripped investors, capital flows to EMs collapsed at the onset of the pandemic. Although some of the outflows slowed down and new inflows took place since then, the decline has been much more severe than the financial crisis or any other episode of market disturbance to these economies (Figure 1).

Figure 1. Comparison of portfolio outflows episodes (percent of International Investment Position)

Source: International Monetary Fund, World Economic Outlook, April 2020.

In conjunction with massive capital flight, the value of EM currencies collapsed. Since January 2020, the fall in EM exchange rates due to the pandemic-induced lockdown was compounded by plummeting oil and commodity prices, which adversely affected the exporters. The flight to safety by investors, who piled into the dollar as the virus spread over the continents, exacerbated the free fall of these currencies. Figure 2 depicts the change in the value of EM currencies since the beginning of each episode. In the first 90 days of the pandemic, the decline in the currencies was severe but more abrupt than the decline during the same period of the Great Financial crisis.

Figure 2. Comparison of currency depreciation episodes (bilateral EM rates against the US$)

Source: Federal Reserve Economic Data and authors’ calculations. EM economies include China, Mexico, Korea, India, Brazil, Taiwan, Singapore, Hong Kong, Vietnam, Malaysia, Thailand, Israel, Indonesia, Philippines, Chile, Colombia, Saudi Arabia, Argentina, and Russia.

Not all countries have been impacted by capital flight in the same way. To examine this, we can consider variations in exchange-traded funds (ETFs). 

An ETF is a type of investment fund that consists of portfolios that track the price and yield of an underlying index. As such, EM ETFs are readily available and can give an understanding of the recent fluctuations in portfolio flows from these economies. Earlier in the year, most EMs, except for the Philippines, have seen sharp declines in net ETF positions, which shows the extent of capital flight from these economies in March (Figure 3). The outflow was abrupt and substantial, paralleling the collapse of their currencies. 

Although the net positions subsequently improved, they remain well below the 2018 levels.

Figure 3: Exchange-Traded Funds (year-over-year percent change)

Source: Investing.com, ETF Equities in the United States Market, issuers: iShares for all countries except Argentina. The issuer for Argentina: Global X

As a result of these massive shocks, EM economies are grappling with the fallout from the pandemic, shutdowns, loss of cheap financing, a staggering recession both at home and abroad, and an inability to service their debt to foreign creditors. Despite the G20’s initiative to suspend debt repayment by the poorest countries, it does not cover the debt owed to private creditors. Further, many EM countries are excluded from this deal; several of them are therefore facing a risk of default, as illustrated by Argentina’s May 22 default, its 9th since 2001.

To analyze the severity of default risk, various indicators are used to assess the vulnerability of economies to sudden stops. 

Typical indicators include the level of external debt as a share of exports, the ratio of debt service to international reserves, and the ratio of current account balance to GDP. In this analysis, we will instead use the Guidotti-Greenspan rule, since it compares the country’s international reserves to its short-term external debt with a maturity of one year or less. If the ratio is greater than or equal to 1, then the economy has built sufficient reserves to weather a massive flight of short-term capital for one year (Figure 4).  

Figure 4: Guidotti-Greenspan rule of reserve adequacy (Reserves/short-term external debt by remaining maturity)

Source: SP Global Ratings, Sovereign Risk Indicators 2020 Estimates, as of April 24, 2020, and authors’ calculations.

Argentina and, in particular, Turkey stand out as having chronically inadequate international reserves to resist a sudden stop of capital flows. In 2020, South Africa fell into the same category of dangerously low reserves. India and Indonesia are currently in a relatively safe zone. They both have just sufficient reserves to cover a short-term crisis, although Indonesia’s ratio has been declining since 2017. If the EM crisis deepens, both of these economies are likely to suffer from a run on reserves. The other five countries, Brazil, China, Mexico, the Philippines, and Russia, have sufficient reserve adequacy without needing foreign borrowing for at least one year.

These conclusions should be evaluated against the current health crisis that the economies are facing. If a country’s health system is overwhelmed by infected people who need to be hospitalized, the economy’s opening will only aggravate the crisis and delay recovery. Figure 5 displays total cases, cases per 1 million population, and tests per 1 million population.

Figure 5: Total cases of infection as of June 6/2020

Source: https://www.worldometers.info/coronavirus/?utm_campaign=homeAdvegas1?

Despite Brazil and Russia satisfying the reserve adequacy criterion, they have the world’s second and third highest numbers of cases respectively after the United States and are ranked above all the EM countries in our analysis (first panel). Brazil is holding second place worldwide even after accounting for the population; among the EM countries studied, it has the highest cases per 1 million people (second panel). Some political leaders argue that high numbers only reflect high rates of testing.
If a country has high testing and high number of cases, then this is a valid argument. However, if there are low testing and a high number of cases, then this is not the case–in fact, the actual number of cases is likely to be even higher than the official numbers. In regards to testing, the worst performing countries in our sample are mostly those economies satisfying the reserve adequacy condition: Brazil, the Philippines, India, Mexico, and Indonesia (third panel). Argentina stands out as deficient in both reserve adequacy and testing. With low rates of testing and increasing numbers of infections, India and Indonesia are in danger of facing adverse economic conditions and/or a financial crisis.
EM economies are facing a rare case of twin crises, economic/financial, and pandemic. These potentially amplify each other and therefore need to be addressed simultaneously. Countries that tackle the health crisis as seriously as the economic slowdown are expected to fare better and return to attracting foreign investment in a virtuous cycle. By contrast, countries prioritize solving the economic crisis over protecting people for a rough ride.

 

 

The Pandemic and the Emerging Markets Crisis: How Fragile are the Economies?2020-06-15T08:07:05+00:00

Europe unveiled $2 trillion stimulus to combat the Covid19 crisis

By Fotis Siokis,

As a great leap of solidarity, the European Commission unveiled on Wednesday, May 27th, the “Next Generation EU” recovery fund plan equal to  $ 825 billion (€750 billion).  Of this amount, nearly $ 550 billion will be in the form of grants and the rest will be made up of loans. The funds would be disbursed to 27 EU countries, through an application process, in order to help and whether the recession caused by the pandemic.  European Commission will raise the fund by borrowing from the financial markets with very favorable terms since it enjoys a AAA credit rating. Next Generation EU plan will be included in the long-term EU budget, increasing the total for the 2021-2027 period to €1.85 trillion.

“Europe’s moment: Repair and prepare for the next generation.” Read more in the European Commission website. 

“European Union Plans $2 Trillion Coronavirus Response Effort.” Read more in the WSJ website. 

 

Europe unveiled $2 trillion stimulus to combat the Covid19 crisis2020-05-30T03:22:10+00:00

New York Employment Declines Severely in April

By Jim Orr,

The New York State Department of Labor reported a (seasonally adjusted) loss of 1.83 million jobs statewide in April, a year-over-year decline of 19.4%.  This decline exceeds the 12.9% job loss nationwide in April reflecting the much stronger impact of COVID-19 in New York.  Combining the job losses in March and April brings the state’s total jobs decline to over 20%.     About one-third of the job losses in April were in the Leisure & Hospitality sector, particularly in Accommodation and Food Service, followed by significant losses in Trade, Transportation and Utilities, especially Retail Trade.    

New York’s unemployment rate rose to 14.5% in April from 4.1% in March, roughly matching the nation’s unemployment rate.  The New York State Department of Labor reports weekly filings of initial claims for Unemployment Insurance continue to run above 200,000.  During the week ending May 16 initial claims totaled 229,562, and the cumulative number of claims filed since the onset of COVID-19 (week ending March 14) is now 2.27 million.   

In New York City, the U.S. Bureau of Labor Statistics reported that employment decreased by 860,000 in April, a decline of 19.2%, similar to the share of job losses statewide.  The combined March and April job losses in the city bring the total decline to over 20%.  The city’s unemployment rate rose to 14.2% in April from 4.1% in March.  The New York State Department of Labor reports 116,000 initial claims for Unemployment Insurance were filed in New York City in the week ending May 16.  The cumulative number of initial claims filed in the city since the onset of COVID-19 is 1.05 million.    

New York Employment Declines Severely in April2020-05-25T06:19:11+00:00

The New York Economy Amid the Coronavirus Crisis

James Orr and Zhuo Xi
April 26, 2020

New York, along with the rest of the nation and world, is in the midst of the coronavirus crisis. It is hard to comprehend the tragic loss of more than almost 17,000 lives (as of April 27) statewide including more than 11,000 in New York City.  The state’s shelter-in-place order for all residents and the closure of all non-essential businesses was initiated on March 20 and remains in effect. 

Recent business surveys and labor market indicators show a significant economic fallout from the virus and containment efforts across the state.  While the extent of the economic downturn from the crisis is not known at this time, policy discussions have turned to when, how and how fast to reopen the economy.  In this post we look for insights from two earlier crises that New York City has withstood–the 9/11 terror attack and the 2007-09 Great Recession.  But the scale of the current downturn will likely be deeper than any of these events, so we also look at the recovery of the New Orleans economy from the devastation of Hurricane Katrina in 2005. 

Early Labor Market Indicators of the Depth of the Crisis

Between the weeks ending March 14 and April 18, the period since the start of the coronavirus crisis, roughly 1.4 million workers, about 15% of the labor force, filed initial claims for Unemployment Insurance in New York State.  The largest number filed in the consumer-oriented Accommodation and Food Service, Health Care and Social Assistance, and Retail Trade industries, and also Construction, in all about 60% of the total.  Relatively less claims have been filed to date in the more office-intensive Information, Finance and Insurance, and Professional, Scientific and Technical Services industries.  Relative to the past two crises, this is an unprecedented increase as statewide weekly claims rarely arose above 50,000.

 Downturn and Recovery in New York City from Past Crises

How might a recovery from the crisis play out in New York City?  The city’s recovery from two major crises during the past two decades—the 9/11 attack and the Great Recession–offers some insight into the factors supporting a recovery of employment.  In the chart below we label employment in the crisis start month as 100 and plot an index of monthly employment 12 months prior to and 60 months after the start.   

The 9/11, 2001 attack on the World Trade Center in New York City and the Pentagon in Washington, D.C., was entirely unexpected and led to the loss of about 3,000 lives and, in New York City, heavily damaged the public transportation infrastructure, damaged or destroyed more than 30 million square feet of office space, and disrupted many financial firms located near the site.

In the two months after the attack, employment in the city dropped by roughly 90,000, a decline of 2.7%, and losses reached 5.0% by July 2003.  But, the national economy had entered a recession in March of 2001 and it is estimated that the effects on employment specifically due to the attack had worn off by the end of 2002.  The weakness of the national economy, and the “jobless recovery” that characterized the period was one factor in the city’s weak recovery.         

In the immediate aftermath of the attack, concerns centered on whether Lower Manhattan  would be able to repair the damage and avoid any permanent impacts as a location for business and residences.  The outcome was not nearly as bad as some of the worst case scenarios. The Federal policy response included assistance with the cleanup of the site, meeting a variety of immediate needs of households, and giving financial incentives to rebuild, work and live in Lower Manhattan.  A look at the city’s growth potential at the time pointed to the presence of a number of growing sectors and reasonably sound local finances, among other factors, and when combined with the Federal policy response gave reasons to think the area could recover.  A report highlights the resilience of the Lower Manhattan area, which is now a relatively thriving residential and commercial area. 

The Great Recession, lasting from late 2007 to mid-2009, was a home-grown nationwide housing crisis that developed into a full-blown financial crisis.  Employment growth in the city turned negative in September of 2008 as several major financial institutions failed or underwent significant restructuring.  Employment declined along with the nation as the recession worsened and the city lost roughly 160,000 jobs, or about 4.4% of total employment.  While the city was spared the extremes of the crisis in housing compared to other parts of the nation, as there was a fear that a severe downturn in financial  sector would harm the city’s prospects for recovery.

The policy responses to the recession included a $700 billion fiscal package, the 2009 American Recovery and Reinvestment Act (ARRA), about 2.6% of GDP, for expanded unemployment insurance benefits, aid to support state and local government revenues, and funding for infrastructure projects.  Monetary policy response was also supporting recovery through lower interest rates, Treasury bond purchases, and a variety of liquidity facilities set up to help stabilize financial markets.         

The recovery of employment to its level at the start of the crisis took almost three years, though it occurred quicker and more strongly in New York City than in the nation.  The city’s financial sector did suffer, losing almost 20% of employment.  But, while Wall Street was still shedding jobs, the city’s gains came from Main Street—a diversified set of local industries not directly linked to financial activities, such as retail trade, leisure and hospitality, professional and business services, and education and health services.

From these experiences, the elements of a recovery include a fundamentally healthy local economy, a growing national economy and effective Federal aid.  Unlike the earlier two crises, how the city gets fully back to business will also depend on medical advances in treatment and prevention of the coronavirus.  At the time of the crisis the city’s economy was growing though the pace was slowing and the probability of a national recession was relatively low but rising.  The Federal response to the crisis includes a spending package, the CARES Act, about 10% of GDP, targeting aid to unemployed workers, state and local governments and small business, among others.  Another proposed bill would help hospitals and small businesses.  Broad financial assistance is also being provided economywide through the Federal Reserve.   It remains to be seen if this fiscal and monetary efforts will be substantial enough in light of the huge and ongoing hit to output, unemployment and state and local budgets.  A recent report presents preliminary estimates of a decline of roughly 10 percent of city employment through the first quarter of 2021, larger than in the earlier two crises, followed by a gradual recovery.   

The Example of Hurricane Katrina

The scale of the current coronavirus crisis in New York City compels a comparison with the experiences of New Orleans following Hurricane Katrina in August 2005. The extensive damage to that city’s residences and infrastructure and the loss of life, over 1200 people died directly from the storm, made it one of the worst in U.S. history.  The city and region turned out to be unprepared for the storm as the levees were unable to prevent the flooding of 80% of the city. 

Like New York, filings for initial claims rose sharply across Louisiana in the weeks following the storm to unprecedented levels.  One analysis of the early weeks of unemployment claims nationally notes the similarity with those a natural disaster, such as Hurricane Katrina.  There, the impact on workers in Louisiana can be seen in the highly concentrated filings in the weeks immediately following the hurricane.

A similarity with the developing data in New York City can also be seen in the rapid loss of employment.  The monthly index of employment plotted below shows that in the two months following the storm employment in New Orleans had declined by 25%.

What is unlike New York, and New York City, is that the immediate policy response to the storm included a mandatory evacuation order resulting in 400,000 residents leaving the city and more than one million residents leaving Southeast Louisiana.  The population fell by more than one half in the year following the hurricane and still remains 20% lower than its pre-storm level, and the number of businesses in the city is still below its pre-hurricane level.  And after a decade the levees had been rebuilt but the city is still considered to be at risk of another major storm.

So while there was initially a v-shaped recovery taking hold, it did not last.  Statewide, Louisiana has recovered to its pre-Katrina employment levels in about three years but New Orleans employment has still not fully recovered.  The Federal response to the storm was deemed by many to have been slow.  A number of residents who left the area permanently relocated to other areas and several low-income neighborhoods were never rebuilt. 

Obviously a lot of the dynamics of the recovery of New Orleans are not present in New York City.  In particular, business owners and workers have borne the brunt of the impact while infrastructure, stores and other workplaces remain largely intact.  The impact on the physical infrastructure in New York would depend on any changes to how business, transportation and other functions requiring close contact are to be conducted going forward.  But also obviously this is a scenario we would not like to see develop in the city.

The New York Economy Amid the Coronavirus Crisis2024-06-27T20:36:46+00:00

New York Labor Market Weakens Dramatically in March and April

The New York State Department of Labor reported a (seasonally adjusted) loss of 41,700 jobs statewide in March, a decline of 0.4% over the month and in line with the nationwide decline of 0.5%.  The Department notes that the reference period for collecting the data occurred before the many coronavirus-related business and school closures.  Therefore, all of the March job losses are not fully reflected in this figure. 

The New York State Department of Labor reports initial claims for Unemployment Insurance filed statewide during the week ending April 18 totaled 207,000, well beyond the weekly average of 15,000 claims filed prior to the increase as a result of COVID-19 (week ending March 14) though just a little more than half of the claims filed last week.  All industries in the state reported an increase in initial claims in the latest week over last year.  The cumulative number of COVID-19-related claims for Unemployment Insurance filed in the state reached 1.4 million.  The largest number of cumulative claims (well above their shares of employment) were filed in the service-oriented Accommodation and Food Service, Health Care and Social Assistance, and Retail Trade industries, and also Construction.  Relatively less claims have been filed in the office-intensive Information, Finance, and Professional, Scientific and Technical Services industries.

In New York City, the U.S. Bureau of Labor Statistics reported that employment decreased by 26,900 in March, a decline of 0.6% over the month.  The New York State Department of Labor reports 103,000 initial claims for Unemployment Insurance were filed in New York City in the week ending April 18.  The cumulative number of initial claims filed in the city since the week ending March 14 is 625,000.    

New York Labor Market Weakens Dramatically in March and April2020-04-24T01:27:10+00:00

The Opioid Crisis in the New York Area: A First Look

Robert Utzinger
February 17, 2020

The United States has been experiencing an increase in the number of deaths due to suicide and drug overdose. In this article I first explain this problem, review the theories behind this phenomenon focusing on drug abuse; I then summarize an analytical study I conducted examining the influence of economic factors on death rates in the greater New York metropolitan region and across different urban classifications in the region. 

Deaths of Despair

The concern with opioid addiction and related deaths nationwide reflects the sharp rise in deaths since 2000, seen in the chart below.  This is not the first episode of increasing deaths in despair, however, as there was also a rise nationwide into the early 1930s as the great depression began.  Unlike today, suicides and alcohol-related deaths were driving up the deaths in despair, while since 2000 they have been driven largely by drug-related deaths.

Deaths of Despair in the United States

Deaths of Despair is the sum of the number of suicides, alcohol-related, and drug deaths

Source: long-term trends in deaths of despair, scp report no. 4-19| September 2019

The current opioid problem dates from the early 2000s when doctors started to prescribe painkillers more often to their patients. This trend was primarily due to the development of new drug formulas that were less likely to cause addiction and to a change in the perspective on pain management. An “opioid” is a class of drugs that includes both legal versions，such as Oxycontin, and illegal versions, including street drugs such as heroin.   An opioid interacts with the brain and is primarily used to dull pain in the human body. It can also create a feeling of euphoria if taken in large quantities. Thus, opioids can lead to individuals becoming dependent on them. The combination of a large push by pharmaceutical companies and an increase in the willingness of doctors to prescribe these drugs， along with a lack of oversight by the government， created a situation for people to abuse the system. The influx of easily produced drugs resulted in a large group of patients who found themselves exposed and becoming dependent. When officials started to crack down on abusers it pushed people to turn to illegal options to satisfy their cravings1. Those who didn’t have access to alternative sources of opioids were forced to go through the process of withdrawal.

There have been many theories to explain this rapid increase in the number of deaths and who it is affecting. The loss of economic opportunity, increasing income inequality, and a changing economic/social landscape have all played a part in the number of deaths overtime.  The increasing number of deaths was first addressed in depth in two papers by Case and Deaton.  The authors noted that middle-aged high school educated whites were experiencing a slow increase in the number of suicides, drug overdoses and alcohol deaths. Subsequently they found this trend across all Caucasians with no college degree, while a decreasing number of deaths were associated with those who had a college degree or more. In the meantime, the Black, Hispanic, and Asian populations had experienced decreasing death rates across all educational levels. The authors argued that a slow buildup of inequality across regions because of fewer job opportunities for those workers with high school diplomas has led to dissipated lives and a feeling of isolation within local communities. Thus, deaths among such workers have been coined “Deaths of Despair”; these people died because of diminished opportunities, financial wellbeing, and social interactions. Case and Deaton’s paper has inspired many follow-up papers that explore different causes of deaths across the country. This research has given rise to two main branches of study, the impact of increasing/decreasing the supply of drugs vs. the factors that change the demand for these drugs.  The supply side argument implies that the increasing supply of drugs is pushing individuals to use them. This view suggests that if policymakers restrict the supply of drugs into a community it will cause individuals to stop using them. The research into the demand side estimates the impact of the economic, social, or political factors driving the demand for those drugs. This approach supports Case and Deaton’s deaths of despair argument, in that people who have experienced economic decline are turning to drugs to escape.

Opioid deaths in the Northeast region

I want to focus on four the northeastern states since they encompass a large variation in types of metropolitan areas and wealth levels. These states are particularly interesting because they are a mix of urban, suburban, and rural regions that have all been affected by varying levels of drug abuse. According to Case and Deaton’s model, if there is an increase in the minimum wage, it should increase the real wages across the states thus lowering the economic burden on the individuals. A better wage in these places can reduce the strain on individuals within those communities. Some previous research found that the increases in minimum wages had no significant negative effects on the number of individuals hired, and in one case was actually was associated with a small positive employment effect. Further research1 comparing state-by-state level shows that increases in minimum wages are associated with a lower probability of suicide and lower stress levels in individuals, but not with overall drug deaths.

The following graph shows the death rates due to various opioids per-ten thousand individuals in New York, Pennsylvania, New Jersey, and Connecticut between 1999 and 2017 annually. The data below are taken from the Center for Disease Control, the organization that tracks all deaths in the country. The deaths are broken down by state and metro type; consequently, we can see how state policies and economic factors play a role in death rates. It is important to note that the data are incomplete, as according to CDC rules if a region has fewer than ten deaths, CDC will not release the data. This practice is meant to protect the individuals’ identities as well as those of their families. As a result, regions with fewer people (generally small or non-core metro) are undercounted in the data. My model uses data for the period 2003 to 2017. 

The graphs show that there is a difference in death rates between the regions, state, and metro types. It is particularly interesting to observe that deaths in large central metro regions across all years are lower everywhere except for Pennsylvania. This fact implies that, despite the interconnectivity of the regions, there must be other factors that affect the deaths in Pennsylvania differently than those in other states. There are many possible reasons for these differences across states, but the one I explored is the impact of the variation in minimum wage among the four states on their death rates, respectively. The federal minimum wage is lower than the state minimum wage in all the states except Pennsylvania, whose minimum wage is still $7.15 an hour. The focus is on the minimum wages because changes in this factor  most likely affect low-skilled workers. By using a statistical method, I examined the relationship between deaths of despair, focusing on the change in minimum wages adjusted for inflation and controlling for a set of variables including the unemployment rate and poverty rate.  The results show that an increase in the minimum wage rate is associated with a lower the number of deaths. The unemployment rate and the poverty rate variable were also found to be significant in explaining the death rate, as an increase in the unemployment/poverty rate increases the death rate. An interesting result, and one that needs further exploration, is that the average income by metro region was associated with an increase in the number of deaths in that metro region.

Conclusion: 

Controlling for a small set of variables and despite a fairly small number of data points, we found support of Case and Deaton’s death in despair arguments in helping to explain the rise in opioid deaths in New York, New Jersey, Connecticut and Pennsylvania.  The decreasing economic prospects and increasing costs of living are impacting the deaths of despair. While our model can explain a portion of the variation in deaths, more research is required to understand the factors that explain the rise in mortality rates.

This study also focused on four states from 2003 to 2017 and the relationship between wages and overdoses could be different in other regions.   The opioid crisis is impacting many people and families across the country and across social economic groups. There is a still a lot of work to be done to get at what started the crisis and what can be done to mitigate it. This study is a first attempt at giving some insight into how economists view the topic, explaining some methods they have used to study the problem, and providing an understanding of how some factors affect overdoses.

 

The Opioid Crisis in the New York Area: A First Look2020-02-18T03:50:59+00:00

New York City Jobs Up but Growth Moderates Through the Third Quarter 2019

Meng-Ting Chen and James Orr
December 29, 2019

New York City employment is now well into its ninth year of growth and jobs across a variety of sector continue to expand.  Data for the third quarter show employment was up 1.6% over the same period last year, down from the stronger third quarter 2018 year-over-year performance but still modestly above the current nationwide employment growth rate.  Statewide, jobs are expanding as well though at a much slower pace, continuing the long-standing pattern in the state of a relatively stronger job performance in the city.  This post reviews job growth in the New York economy through the third quarter 2019 over a year ago, focusing on the performance of key sectors driving recent New York City’s job growth and highlighting some important influences on the city’s employment growth going forward.

Employment Trends in New York City, New York State and the Nation

The broad trends in employment over the past two decades in New York State, New York City and the nation are shown in the figure below.  The monthly indexes the decline and recovery of employment in the early 2000s and then at the time of the financial crisis, and show the subsequent robust recovery and expansion beginning in 2010, also seen here.   Job growth continued in the city through September of 2019, though not without some bumps in the second quarter.  Employment in the city is now well above its pre-downturn peak.

 

Third-quarter city job counts were up 71,000 over a year-ago, a gain of 1.6% which, while below its strong 2.1% performance in 2018, was modestly above the national average growth of 1.5%.  Statewide job growth has averaged closer to 1.0% over the past year.  This ranking of relative growth rates—New York City, the nation, and then New York State—has persisted for several years and reflects the combination of the sustained expansion of jobs in the city and a considerably slower pace of employment growth across the upstate and western New York metropolitan areas.  

Performance of Key Industries

Underlying the overall growth in jobs in New York City over the past year is a diverse performance of its various industries.  Here we examine the changes in several industries that are among the key drivers of changes in employment.  Our focus is on the percent change in employment in the third quarter of 2019 over a year ago, as shown in the figure. 

Healthcare and social assistance accounts for almost 20% of total New York City employment and has been a stable source of new jobs for more than a decade.  Over the past year alone jobs expanded by 6.2% in the city, and features of some important healthcare occupations are discussed here.  A notable aspect of the growth of employment in the sector, detailed in a recent report,  is the surge in job growth in home health-related payrolls, mainly home healthcare services and services for the elderly and disabled.  The surge is linked to an expansion of a New York state program, the Consumer Directed Personal Assistance Program (CDPAP), under which the elderly and disabled can choose their own providers, including family members, supported by intermediaries who are paid through Medicaid.  The jobs are recorded mainly in two sub-sectors, ambulatory care services, which expanded 9.9% over the year, and social assistance, which expanded 5.1%.  Any legislative changes to the program could influence the growth in the sector and the broader city economy going forward.

The information industry includes a range of sub-sectors, including traditional book and newspaper publishing and radio and television broadcasting, movie and video production to the more high-tech software publishing and web search portals.  Jobs in the sector have expanded in each year over the past decade and total employment now exceeds 200,000.  The professional and business services industry continues to be an important source of job growth.  The industry includes three major categories; firms providing a range of professional services, such as accounting, legal, computer, consulting, etc., administrative and support services, and headquarters and corporate offices, and each category saw growth over the past year.    

Employment in the retail trade industry increased by about 7,000 jobs over the past year after seeing a slight decline in 2018.  Reports have suggested that employment in segments of the sector, particularly department stores, were facing ongoing pressures from the rapid expansion of online shopping, and jobs there have been essentially flat for the past several years.  The growth over the past year, however, has been supported by an expansion of jobs in clothing, health and personal care, and food retailers.   Employment in the leisure and hospitality industry also bounced back from a weak performance last year with job counts up close to 10,000, and tourism is poised to set a record for visitors this year.  Last year’s decline in food service employment was more than offset this year and overall employment in the sector is now close to a record high.

Two industries—finance and manufacturing—saw employment declines over the past year.    Employment in the finance industry fell by about 4,500 jobs which offset about half of the prior year’s gain.  About two-thirds of the lost jobs this year were in the securities sector (Wall Street).  Although that sector accounts for only about 5% of total city employment, its average salary of $422,000 (2017) give it an outsized importance in city earnings.  Employment in the sector still remains near its decade high.  

While nationwide manufacturing employment began a recovery in 2010, the manufacturing sector in both the state and the city have continued to decline.  Over the past year,  the city lost about 2,000 jobs, a decline of almost 3%.  One notable exception to this statewide trend has been in Albany where the manufacturing sector, while small, has seen employment grow by about 30% over the past decade as a result of the successful development of a nanotechnology cluster.  

Some Caveats and the Outlook

Reported job trends help to inform employment forecasts, but like many time series the monthly state and local employment numbers, used here to compute quarterly averages, get revised. This arises because the monthly state and local employment estimates are based on a survey of employers, the Current Employment Statistics (CES) and a more comprehensive accounting of employment is available from official unemployment insurance records is available, the Quarterly Census of Employment and Wages (QCEW), though with a six-month lag.  In March of each year, the Bureau of Labor Statistics benchmarks the initially reported state and local employment numbers to the QCEW counts.  To anticipate what the revised employment will be prior to the March release, the regular reporting of an early benchmarked series has been undertaken, described here.  To date, this series suggests that the level of employment in the city this year is now likely higher than initially reported though there are no significant differences with the reported growth rates. 

Some additional context to the reported job growth trends is a study showing the decline in the average workweek in the city’s private sector over the past ten years and continuing in 2019.  The average workweek fell from 35.5 hours to 34.1 hours, a decline of 4.1% and more than that in the nation and other large cities.  The decline suggests that new private-sector jobs do not all provide full-time employment and indicates that total hours worked, an important determinant of citywide output and earnings, have not expanded as much as employment.  As to the causes, the decline reflects, in part, though not entirely, the expansion of employment in industries with typically shorter workweeks, such as health services and leisure and hospitality.

Looking ahead, reports project that job growth in New York City will end the year up close to its current pace.  Each sees growth continuing in 2020 though at a slower pace than this year, with estimates from roughly 1.1 – 1.4%.   One risk to the outlook is the performance of the national economy, where slower than expected growth would dampen prospects for city firms with close links to national activity.  Another risk is more local and arises from the provisions of the 2017 tax bill that caps the size of the individual federal tax deduction for state and local tax payments.   One study showed the potential for the bill to raise the cost of homeownership in high tax states like New York.  More recently, a report documented an increase in the federal personal income taxes paid by New York residents in 2018, with part of that increase suggested to reflect the limits on deductions.  The bill may have other effects as well and it remains to be seen how big and sustained any effects will be in the state and what will be their ultimate economic impacts on the state and city economies.

New York City Jobs Up but Growth Moderates Through the Third Quarter 20192019-12-30T04:59:41+00:00

Lessons from Taiwan’s Healthcare Reform

William B. Thorne
November 27, 2019

Taiwan’s National Health Insurance Overhaul

Taiwan’s single-payer National Health Insurance system was implemented in 1995 and designed using the U.S. Medicare program as a template. At a time when the future of the US healthcare system is an important topic that is likely to affect election results, what lessons can we draw form the Taiwanese experience?  The switch to a single-payer system is appealing to study because it was a fundamental change and restructuring of how healthcare was provided, not a relatively small tweak to funding. The more major and transformative a change is made in a short time period, the easier it becomes  to detect effects in the data. Taiwan was one such major shift and it saw many improvements in health outcomes after the change. However, it is possible that those improvements would have happened anyway without the change in system; we do not know what health outcomes in Taiwan would have been without the change in its healthcare system. We can’t observe Taiwan with and without the policy reform, but statistical techniques allow us to get an  estimate of the causal effect of the healthcare reform on health outcomes. In this post we outline the key components of Taiwan’s healthcare reform and report the results of our analysis that show how the policy reform led to fundamental healthcare improvements.

Major Changes to Taiwan’s Healthcare System

Chen Shih-Chung Minister of Health and Welfare for Taiwan, summarized the 1995 switch:

National Health Insurance (NHI) integrated medical programs from existing insurance systems for laborers, farmers, and government employees, which covered only half the population, and has since been expanded to provide equal coverage to all citizens from birth, regardless of age, financial status or employment status. Furthermore, all foreigners who legally work or reside in Taiwan are also afforded the same coverage… Yet healthcare costs are far lower in Taiwan than in most highly developed countries in Europe and North America, at $1,430 per capita per year.

For the average person in Taiwan, the change meant that, when you use the healthcare system rather than buying insurance and billing the insurance company, your bill would be sent to the government with little or no payment out of pocket.  Healthy people enter the system to share the costs of healthcare; coverage in Taiwan increased dramatically, from 57% to 99%, and approval ratings for the program have been high.

The government can bargain and control costs and to distribute them through taxation. It also allows for economies of scale in administration, rather than each insurance company conducting its own administration. The administrative costs are now some of the lowest in the world, being around 2% of total healthcare spending.   By reducing the need to make a payment when visiting a doctor, people may be more inclined to visit a doctor before their illness gets worse. High-quality, available, preventative care might save on healthcare costs in the long run. Ultimately these are claims that must be assessed by what we see in the data. Comparing the results Taiwan saw after the reform with what Taiwan would have been like without the reforms, is the key problem researchers must solve.

How to Assess the Impact of Taiwan’s Healthcare Overhaul

A neat solution to the issue of what Taiwan’s healthcare system would have looked like absent the policy change, is the “Synthetic Control Method.” It works in the following way: consider Taiwan in the time period before their 1995 healthcare reform. Selecting several control countries whose life expectancy data, when combined, follow Taiwan’s data quite precisely for the years prior to 1995, we could expect them to continue to do so afterwards. Only the real Taiwan data will have the effect of the 1995 healthcare reform. Therefore, the difference we observe in outcomes between the synthetic group and the real Taiwan data can be considered the effect of the healthcare reform. For example, the synthetic group for Taiwan could be made from a weighted average of 40% Japan, 40% China, and 20% the United States, meaning these countries have data that look most like Taiwan from 1960 to 1994. In the post-reform period, keeping those same countries we get data that represent what Taiwan would look like post-1995 which can be compared to Taiwan’s actual data, and we can observe the difference. This method avoids the potential bias of selecting one particular country to judge the size and sign of the healthcare reform’s effect.

We use the post-reform data on the change in life expectancy as one measure of the new program’s impact. The complete dataset includes yearly life expectancy for Taiwan and 187 countries from 1960 to 2016. The basic model considered here takes data from all the available countries to calculate the synthetic control group, or Synthetic Taiwan. The top weights for the Synthetic Taiwan are: Japan 22%, United States 19%, Montenegro 16%, Armenia 9%, Iceland 6%, and others at less than 5%. The list is a mix of intuitive choices for comparisons, as well as some that are not quite as clear. This is the advantage of the Synthetic Control Method: because it is data-driven it chooses the countries that are most similar, and not just those that are perceived as similar.

Figure1. Life Expectancy Taiwan and Synthetic Taiwan

Figure 1 shows the output of this basic synthetic control model. The dotted line indicating life expectancy in years in the Synthetic Taiwan sits right on the solid line for Taiwan in the 1960-1994 pre-reform period. That means the country weights described above recreate the real Taiwan quite well.   After the 1995 healthcare reform we see a gap emerge as Taiwan’s life expectancy rises faster than in the Synthetic Taiwan. This means Taiwan’s healthcare reform improved life expectancy outcomes relative to what would have happened without the reforms (represented by the synthetic)

Figure2 presents the same information as the figure above, but shows the subtraction of the two lines plotted so the y-axis can be understood as the difference in life expectancy between the actual Taiwan and Synthetic Taiwan. In the 10 years immediately after the policy was implemented, Taiwan improved its life expectancy by roughly a year or more relative to the Synthetic. 

Figure 2.  Life Expectancy Gaps Taiwan and Synthetic Taiwan – All Country Donor Pool

Conclusion

Although preliminary, there are some lessons one can potentially take away from our look at Taiwan’s healthcare reform. Often countries are compared without a real reckoning of what those countries were like before reforming their systems nor what would have happened in the absence of a reform. The synthetic control method provides an opportunity to get at the true effect of these differing health system models, assuming no major changes occur in the control group. Here, life expectancy in a synthetic control group keeps very close to the actual life expectancy data in Taiwan in the pre-reform period, but then actual life expectancy immediately and unambiguously moves upwards after the 1995 healthcare reform. Given the results of Taiwan’s move to a single-payer system, there could be real gains in life expectancy, and likely other health outcomes as well.

In an interview with Jonathan Cohn for “The Treatment”, The New Republic’s healthcare blog, Dr. Michael Chen, Vice President and CFO of Taiwan’s National Health Insurance Bureau said:

We sent our people around the world to learn their programs, including the United States. Actually, the program is modeled after Medicare. And there are so many similarities – other than that our program covers all of the population, and Medicare covers only the elderly.

This Taiwan “Medicare For All” example shows potential benefits to other countries of potentially switching to such a system. It was not the case that the people of Taiwan were uniquely healthy, or long-living before the implementation of their new system, so that the reform itself had no effect. It is argued in the U.S., that the U.S. is less healthy due to poverty or obesity not our healthcare system. Given the results shown by Taiwan’s reform, this is not a sufficient explanation: major healthcare reforms can affect health outcomes. Of course, there will be unique challenges if the United States switches to a new healthcare system; Taiwan experienced a spike in administrative costs the first few years, and the U.S. might expect something similar. However, it seems clear from these preliminary results that the U.S. could also reasonably expect some improvements in health outcomes and cost savings after making a switch. Taiwan pays a fraction of the drug prices (for the same drugs) that the U.S. does, pays 6.1% of GDP on healthcare as opposed to 17.2%, pays 0.77% of total healthcare spending on administrative costs compared to 13% in the U.S., and Taiwan visits the doctor at three times the rate of the U.S.; we should learn from Taiwan’s single-payer healthcare reform.

 

Lessons from Taiwan’s Healthcare Reform2019-12-03T19:02:49+00:00
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