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

Unconventional Monetary Policies Become Conventional After All?

Fotios Siokis
October 21, 2019

What are unconventional monetary policies? How are they implemented in the European Union? What does the future look like? In this article we address these questions. On September 12,2019, the President of the European Central Bank (ECB) announced a new monetary stimulus package, prompted by the entrenched low inflation rate and an economic slowdown that has proved to be more protracted than initially expected. The inflation and economic growth prospects in the euroarea, which were both revised downward to 1.2% and 1.1% for this year and 1.0% and 1.2% in 2020 respectively, have taken a heavy toll due to the persistent weakness in manufacturing and extraordinary uncertainty concerning international trading arrangements and geopolitical alignments.

A zero lower bound (ZLB) on the Main Refinancing Operation interest rate (currently at zero and equivalent to the Federal Reserve’s target rate) had eroded the use of traditional monetary tools, prompting the ECB to adopt unconventional measures. These were first introduced in early 2000 by Japan in its battle against deflation and had been previously employed in periods of heightened financial distress amid severe economic downturns, such as the recent Great Recession in the United States and the great sovereign and banking crisis in the euro area. Table 1 outlines these complementary monetary measures.

Table 1: ECB’s monetary policy decisions as of September 12, 2019
Tools Action Taken
Deposit (overnight facility) rate Rate decrease to -0.5% from -0.4%
Two-tier system Introduction of two-tier system for reserve remuneration
Forward Guidance Measures will remain at work until projected inflation stabilizes close to but lower than the targeted 2%
Quantitative Easing (QE) Restart asset purchase program at a monthly pace of €20 bn from November 1 until the ECB begins to raise key interest rates.
Targeted Longer-term Refinancing Operations (TLTRO) Lower interest rates for loans while maturity extends from 2 to 3 years
Source: ECB

Monetary Policy Tools Εxplained

  1. Deposit (overnight) facility rate. Unlike the Main Refinancing Operation rate that remained at the zero level (figure 1), the deposit rate – the rate that the ECB remunerates for deposits that commercial banks hold at the central bank, in excess of the required reserves – decreased by 10 basis points, from -0.4% to -0.5%.

Figure 1. Deposit rate and the (a)synchronization of the main intervention rates
Sources: ECB and Federal Reserve

The negative deposit rate is a policy measure aiming at decreasing the yield curve at all maturities. It is designed to encourage commercial banks to lend their excess liquidity to households, firms, financial intermediaries, or to invest it in sovereign bonds, rather than to “stash” it in the Central Bank. Although this measure is intended to provide extra liquidity, critics argue that negative rates may adversely affect the profitability of the fragile European banking system. To the extent that a negative overnight rate reduces longer-term interest rates, the income that banks earn from interest bearing financial assets, such as bonds or mortgages, is reduced. Furthermore, the possibility that negative rates may lead to less lending and more risk taking by high-deposit banks cannot be ignored. Neither can the fact that negative rates could be passed on to corporate depositors and savers. For these reasons, the ECB introduced a two-tier system for the banks, under which a portion of reserves, set up to six times the mandatory reserves they hold at the Central Bank, will be exempt from negative rates and earn 0%, while the rest of the reserves will be subject to the -0.5% rate.

  1. Forward guidance. Forward guidance occurs when Central Banks communicate with the public about the current state of the economy and the future path of monetary policy. By revealing the path of policy rates, the ECB seeks to influence longer term interest rates and to reduce uncertainty about the mean and variance of asset prices. Central Banks have used two types of forward guidance policy so far: the time- or calendar-dependent guidance and the state-dependent commitment. The ECB’s forward guidance announcement along with the deposit facility rate is state-dependent, conditional on the inflation outlook. The ECB states that as long as the inflation rate remains low and away from the targeted level (close to but less than 2%, as shown in the figure below), the interest rates and the other unconventional monetary policy measures will be accommodative. This is called an “Odyssean guidance” – a form of commitment where the Central Bank pledges to stay on course regarding the interest rate path and other accommodative measures.

Figure 2. Inflation rates in the euro area
Source: ECB
  1. Quantitative easing (QE). This toolinvolves large-scale purchases of longer-term bonds by the ECB with the aim of easing monetary and financial conditions in order to boost spending. Purchases of government bonds increase their asset prices and consequently lower their respective yields. Asset prices and yields are influenced through two channels, namely the portfolio balance and the signaling channels. The first postulates–given that assets are imperfect substitutes–that purchases of longer-term government assets can also decrease the yields of other assets bearing similar credit risk and duration characteristics. In other words, the sellers of these bonds will seek to rebalance their portfolios by buying other assets that are substitutes for the ones that they have sold. This process will raise the price of other assets (wealth effect) and decrease their yields (lowering borrowing costs for firms and households as well as governments) an action that stimulates spending and investment. The signaling channel operates through the effect on expected future policy rates and can reduce the inflation expectations component (term premia) of long-term interest rates. In this respect, the QE measure is complementary to forward guidance, supporting the ECB’s commitment to stick with the announced accommodative policy. QE seems to have become a key instrument of monetary policy in the euro area which will embark again on asset buying on November 1 at a monthly rate of € 20 billion.  Based on the forward guidance rhetoric, QE is intended to last for quite some time and go beyond the €2.6 trillion bond-buying program that was first implemented and lasted through the end of 2018. But such actions are not harmless. QE could distress market conditions by diminishing the supply of long-term bonds in the market, and create a shortage of bonds that institutional investors and others used as collateral.

Figure 3. Yield curve in the euro area as of September 12, 2019
Source: ECB
  1. Targeted, Longer-Term, Refinancing Operations (TLTRO). TLTROs are monetary policy tools that provide long-term loans to banks. The aim is to provide a favorable bank credit environment, enhancing support for financing the real economy. It will also ensure the smooth functioning of the bank lending channel as the main monetary policy transmission mechanism. According to the new TLTRO, banks can borrow up to 30% of their outstanding loans to businesses and consumers at a rate equal to main refinancing operation rate (0%). In cases where a bank sufficiently improves its lending to the real economy, the interest rate applied could become negative up to the deposit rate (-0.5%).

Discussion

The ECB’s announced measures aim to revive inflation expectations and bring inflation close to its 2 percent target level, something the ECB has fallen short of since 2013 and raised concerns about its credibility. In addition, the new monetary measures can spur economic growth by lowering longer-term borrowing costs for firms and households, and by providing an opportunity for Euro area member states to finance a fiscal expansion with very favorable interest rates.

On the adverse side effects of the unconventional measures, this ample liquidity handed to the banking system could easily be simply deposited with the ECB, or invested in higher-risk and higher-yield assets offered. To a certain degree, the downward movement of long-term yields in parts of the euro area, shown in Figure 4, is a testament to “hunt for yield.” By now the Greek 10-year bond yield, a non-investment grade asset is lower than the corresponding AA+ U.S. Treasury. As negative rates narrow banks’ margins, financial institutions could decrease lending and slow the economy. Core banks from Germany, France and Benelux, which account for 85% of excess liquidity, bear the bulk of the cost of these negative rates.

Figure 4. 10-year bond yields of selected countries
Source: Federal Reserve Economic Data (FRED) and Central Banks’ sites

What does the future hold? It is evident that the significant accommodative stance of monetary policy is set for a long time. Although the unconventional measures are mutually reinforcing, monetary policy alone might not be sufficient to revive growth in the euro area. The ECB has willingly passed on the growth baton to the member states, though most have applied austerity measures throughout the crisis and now seem reluctant to conduct a vital, expansionary, fiscal policy.

Unconventional Monetary Policies Become Conventional After All?2019-11-05T15:31:41+00:00

Trump’s Trade Quagmire

Paul Krugman
August 30, 2019

Remember the Vietnam quagmire? In political discourse, “quagmire” has come to have a quite specific meaning. It’s what happens when a government has committed itself to a policy that isn’t working but can’t bring itself to admit failure and cut its losses. So, it just keeps escalating, and things keep getting worse.

Well, here’s my thought: Trump’s trade war is looking more and more like a classic policy quagmire. It’s not working — that is, it isn’t at all delivering the results Trump wants. But he’s even less willing than the average politician to admit to a mistake, so he keeps doing even more of what’s not working. And if you extrapolate based on that insight, the implications for the U.S. and world economies are starting to get pretty scary.

To preview, I’m going to make five points:

  1. The trade war is getting big. Tariffs on Chinese goods are back to levels we associate with pre-1930s protectionism. And the trade war is reaching the point where it becomes a significant drag on the U.S. economy.
  2. Nonetheless, the trade war is failing in its goals, at least as Trump sees them: the Chinese aren’t crying uncle, and the trade deficit is rising, not falling.
  3. The Fed probably can’t offset the harm the trade war is doing and is probably getting less willing even to try.
  4. Trump is likely to respond to his disappointments by escalating, with tariffs on more stuff and more countries, and — despite denials — in the end, with currency intervention.
  5. Other countries will retaliate, and this will get very ugly, very fast.

I could, of course, be wrong. But that’s how it looks given what we know now.

Let’s start with the scale of the policy. The Peterson Institute for International Economics (PIIE) generated a nice chart showing the escalation of tariffs on Chinese goods under Trump:

Average US tariff rates on imports from China before and after President Trump’s acts of protection

Source: PIIE

So roughly speaking, we’ve seen a 20 percent tax imposed on the $500 billion worth of goods we import from China each year. Although Trump keeps insisting that the Chinese are paying that tax, they aren’t. When you compare what has happened to prices of imports subject to new tariffs with those of other imports, it’s overwhelmingly clear that the burden is falling on U.S. businesses and consumers.

So that’s a $100 billion a year tax hike. However, we aren’t collecting nearly that much in extra tariff revenue: 

Customs duties receipts (in billions of Dollars)

Source: Federal Reserve Bank of St. Louis

 

Partly that’s because the revenue numbers don’t yet include the full range of Trump tariffs. But it’s also because one big effect of the Trump tariffs on China has been to shift the sourcing of U.S. imports — e.g., instead of importing from China, we buy stuff from higher-cost sources like Vietnam. When this “trade diversion” happens, it’s still a de facto tax increase on U.S. consumers, who are paying more, but it doesn’t even have the benefit of generating new revenue.

So, this is a pretty big tax hike, which amounts to contractionary fiscal policy. And we should add in two other effects: foreign retaliation, which hurts U.S. exports, and uncertainty: Why build a new factory when for all you know Trump will suddenly decide to cut off your market, your supply chain, or both?

I don’t think it’s outlandish to suggest that the overall anti-stimulus from the Trump tariffs is comparable in scale to the stimulus from his tax cut, which largely went to corporations that just used the money to buy back their own stock. And that stimulus is behind us, while the drag from his trade war is just getting started.

But why is Trump doing this? A lot of center-right apologists for Trump used to claim that he wasn’t really fixated on bilateral trade balances, which every economist knows is stupid, that it was really about intellectual property or something. I’m not hearing that much anymore; it’s increasingly clear that he is, indeed, fixated on trade balances, and believes that America runs trade deficits because other countries don’t play fair.

Strange to say, however, despite all those new tariffs the U.S. trade deficit is getting bigger, not smaller, on his watch:

US net exports of goods and services (in billions of dollars)

Source: Federal Reserve Bank of St. Louis

 

Adjusted for inflation, imports are still growing strongly, while U.S. exports have been shriveling:

Year-over-year percentage change in real (inflation-adjusted) exports and imports of goods and services

Source: Federal Reserve Bank of St. Louis

Why aren’t tariffs shrinking the trade deficit? Mainly the answer is that Trump’s theory of the case is all wrong. Trade balances are mainly about macroeconomics, not tariff policy. In particular, the persistent weakness of the Japanese and European economies, probably mainly the result of shrinking prime-age work forces, keeps the yen and the euro low and makes the U.S. less competitive.

When it comes to recent import and export trends, there may also be an asymmetric effect of the tariffs themselves. As I already mentioned, U.S. tariffs on Chinese goods don’t do much to reduce overall imports, because we just shift to products from other Asian economies. On the other hand, when the Chinese stop buying our soybeans, there aren’t any major alternative markets.

Whatever the explanation, Trump’s tariffs aren’t producing the results he wanted. Nor are they getting the other thing he wants: Splashy concessions from China that he can portray as victories (“tweetable deliveries”). As Gavyn Davies says, China seems “increasingly confident it can weather the trade wars,” and it’s not showing any urge to placate the U.S.

So, this might seem to be a good time to hit the pause button and rethink strategy. Instead, however, Trump went ahead and slapped on a new round of tariffs. Why?

Well, stock traders reportedly think that Trump was emboldened by the Fed’s rate cut, which he imagines means that the Fed will insulate the U.S. economy from any adverse effects of his trade war. We have no way of knowing if that’s true. However, if Trump does think that, he’s almost surely wrong.

For one thing, the Fed probably doesn’t have much traction: interest rates are already very low. And the sector most influenced by interest rates, housing, hasn’t shown much response to what is already a sharp drop in mortgage rates.

Furthermore, the Fed itself must be wondering if its rate cut was seen by Trump as an implicit promise to underwrite his trade war, which will make it less willing to do more — a novel form of moral hazard.

There is, by the way, a strong contrast here with China, which for all its problems retains the ability to pursue coordinated monetary and fiscal stimulus to a degree unimaginable. Trump probably can’t bully the Fed into offsetting the damage he’s inflicting (and just try to imagine him getting Nancy Pelosi to bail him out); Xi is in a position to do whatever it takes.

So, what will Trump do next? My guess is that instead of rethinking, he’ll escalate, which he can do on several fronts. He can push those China tariffs even higher. He can try to deal with trade diversion by expanding the trade war to include more countries (good morning, Vietnam!).

And he can sell dollars on foreign exchange markets, in an attempt to depreciate our currency. The Fed would actually carry out the intervention, but currency policy is normally up to the Treasury Department, and in June Jerome Powell reiterated that this is still the Fed’s view. So, we might well see a unilateral decision by Trump to attempt to weaken the dollar.

But a deliberate attempt to weaken the dollar, gaining competitive advantage at a time when other economies are struggling, would be widely — and correctly — seen as beggar-thy-neighbor “currency war.” It would lead to widespread retaliation, even though it would also probably be ineffective. And the U.S. would have forfeited whatever remaining claims it may still have to being a benevolent global hegemon.

A version of this article has been originally published in New York Times on 3/08/2019

Trump’s Trade Quagmire2019-08-31T00:02:55+00:00

U.S. – China Trade Conflict: Impacts on China

Zhuo Xi
July 23, 2019

Starting from the different positions held by the Trump administration and the Chinese government on issues such as the bilateral trade balance, market access, and intellectual property transfers, China and the U.S., the world’s two largest economies, have been quarreling over trade for more than a year. This post reviews a number of measures of the recent performance of China’s economy to see if there have been any discernible impacts to date. The United States has initiated two rounds of tariffs on Chinese goods. In July of last year, 25% tariffs were placed on $50 billion of U.S. imports; in May of this year, a second-round raised tariffs from 10% to 25% on $200 billion of U.S. imports. President Trump has repeatedly warned that the United States may also place tariffs on another $300 billion in Chinese goods. China has responded with tariffs on $60 billion of U.S. goods after the May tariff hike. While tariffs have affected China’s trade, and investors are worried about the possible fallout that could hit companies, whole sectors, and other countries caught in the crossfire, the actual macroeconomic implications for China appear limited so far.

Direct Impacts

Source: OECD

According to recent data, China’s GDP has slowed to 6.3% year on year in the first half of 2019 (see above figure) feeling the pinch from the tariffs imposed. However, this view ignores that ongoingde-leveraging, real estate-regulation, and environmental protection have also caused significant downward pressure on China’s economy. In fact, China’s exports surged in 2018 a move that might be related to thefront-loading impactas exporters pushed out shipments ahead of the implementation of the latest tariffs, backed also by a weaker Chinese currency against the U.S. dollar. But, it’s uncertain whether the recent resilience of exports is likely to be sustained, especially considering that the higher tariffs on $200 billion worth of Chinese goods will soon take effect. In fact, both the World Bank and the International Monetary Fund (IMF) have lowered their forecasts for China’s future GDP growth.

Source: World Bank

Although the trade war between the two countries threatens to become much worse in the future, the direct impact on GDP is still limited in the long- term, since China’s economy is no longer mainly driven by exports. According to the data from the World Bank (above figure), exports accounted for roughly 20% of China’s GDP in 2017, down from 36% in 2006. Also, bilateral trade between the two countries contributes an even smaller amount to GDP. For China, U.S. trade contributes 2.5% to GDP while only 1% for the U.S.

Currency valuation

Source: FRED

Since China’s trade dispute with the United States, China has seen its currency, the renminbi (RMB), decline in value. Although the decline has not been as steep as that of the Turkish lira or the Argentine peso, whether China will also fall into a similar monetary crisis has been an important question for investors. Although the RMB is depreciating, one difference is that China has responded to the trade situation by allowing a moderate and controllable RMB depreciation. Generally, the policy has been to intervene and stabilize the value of RMB within the range (band) of 6 and 7 per US dollar. This should help Chinese exporters mitigate the impact of new tariffs, but it will cost the rest of the economy. In other words, contrary to other emerging market, the depreciation of the exchange rate is more intentional and controllable by the government.

The reason behind this trend is that China’s economic base and ability to control the exchange rates are hard to match in other emerging market countries. This point could be reflected by the recent variation of USD/RMB, where there was clear support when the rate approached 7. On the other hand, various Chinese financial governors have mentioned several times in the media that China won’t use devaluation as a tool in the trade dispute. The possible reason is that the internationalization of the RMB has been one of the top goals for Chinese financial development. In fact, the People’s Bank of China has just managed to successfully convert the one-way renminbi devaluation expectation of the market into the two-way currency fluctuation expectation in recent years. Based on these two considerations, a rapid depreciation of the RMB is not likely in the near future. However, if the trade conflict between the US and China has escalated to a financial war, then the possibility of strong depreciation cannot be ruled out.

Debt condition

There is a widespread view that an escalation of the tariff conflict could trigger a possible debt crisis in China and an increase of debt-to-GDP ratio due to deceleration of the GDP growth rate. But unlike the case of Turkey (and even Argentina’s), where the external debt position was almost 55% of GDP, equivalent to about 5.4 times the level of its foreign exchange reserves, China’s debt is mainly domestically held, while the external part is considered sustainable. Furthermore, China holds considerable USD exchange reserves-one third in the form of US Government securities-and given the slowly opening of its capital markets it can decisively control any capital outflow.

Impact on the Stock Market

The stock market is probably the place that will face the greatest impact. Global investors are worried about the continuous escalation of the US-China trade war. Since the beginning of 2018, China’s stock market has gradually fallen. At the end of the last year, the Shanghai Composite Index (SSE) once fell below 2,500, and the year-to-date decline was close to 30%. The trade dispute between the US and China had been one of the main causes for investor pessimism. To prevent a possible market crash, the top officials of the Chinese Government collectively called for stable expectations. In addition to the optimism over the prospect of a possible deal, the stock market bounced back in early 2019. However, immediately after President Trump increased tariffs on $200 billion worth of Chinese goods, the stock market has fallen sharply below 3,000 again.

Source: Yahoo Finance

Other Potential Impacts

In addition to the declining stock market, the impact of Sino-US trade frictions on China’s economy is gradually moving from the expected and psychological levels to the physical level, from local to global, including trade, investment, the supply chain, employmentand so on. For instance, the impact on the industrial chain cannot be underestimated; such effects are difficult to model quantitatively. For example, due to concerns about the uncertain future of the Sino-US trade war, more and more multinational companies are hesitant about continued investment in China and are gradually adjusting their global profile. According to survey reports, in order to avoid high import tariffs in the United States, large Japanese manufacturers have been re-examining their business strategy and have plans to transfer production lines out of China. The effects of the concern regarding a U.S.-China trade war can be reflected in the recent variation in the manufacturing PMI (Purchasing Managers Index): the PMI had declined to an annual low of 49.2 since the trade dispute. It rebounded back above 50 in recent months due optimism over a possible deal, but it fell again to 49.4 due to recent tariff hike.

The Purchasing Managers’ Index (PMI) is based on a monthly survey of supply chain managers across 19 industries, covering both upstream and downstream activity. The headline PMI is a number from 0 to 100. A PMI above 50 represents an expansion when compared with the previous month. A PMI reading under 50 represents a contraction, and a reading at 50 indicates no change.
Source: The National Bureau of Statistics

The future of the US-China relationship will be essential not only for their wellbeing but for the global economy. Recent news surrounding Huawei and other Chinese tech companies suggests that the bilateral tensions between the two countries have expanded beyond the damaging trade war, and are headed for a keen rivalry in technology and innovations. With the APEC (12-member Asia Pacific Economic Cooperation) meeting in November, it’s possible for the U.S. and China to reach a “narrow” trade deal by the end of this year, but by no means to resolve all the tensions between the two countries. In the long- term, geopolitical experts have been warning that China and the US appear to be falling into the “Thucydides Trap”, which describes a situationin which a war between two countries is inevitable even though both nations may be trying their best to avoid it.

U.S. – China Trade Conflict: Impacts on China2019-07-25T21:11:48+00:00
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