Globalization is a very broad concept, and many scholars in academic history have tried to define it in different ways. Some argue that the concept cannot be fully defined, others claim that any definition has its limitations, and of course many try to construct their own working definition. Usually, the knowledge-based websites define globalization as “a process of interaction and integration among the people, companies, and governments of different nations, a process driven by international trade and investment and aided by information technology” (Globalization 101, n.d.).
The various angles of globalization have given it several different meanings. Nilsson (2010) stated that “globalization typically refers to the process by which different economies and societies become more closely integrated, and concurrent with increasing worldwide globalization, there has been much research into its consequences” (p. 1191). Al-rodhan (2006) reviewed a lot of definitions of globalization and summarized it as “a process that encompasses the causes, course, and consequences of transnational and transcultural integration of human and non-human activities” (p. 2). As itemized by Scheuerman, the references to globalization include: “the pursuit of classical liberal (or ‘free market’) policies in the world economy (‘economic liberalization’); the growing dominance of western (or even American) forms of political, economic, and cultural life (‘westernization’ or ‘Americanization’); the proliferation of new information technologies (the ‘Internet Revolution’)” (2018, para. 5). In addition to these material aspects of globalization, people are becoming more aware of other cultures and beginning to think as “global citizens” that are integrated with the rest of the world instead of living separately as different cultures (Scheuerman, 2018).
Opinions on globalization are split into the two basic groups of “for” and “against”. The pro-globalization lobby argues that “globalization brings efficiency, because it increases opportunities and competition” (InvestorWords, n.d., para. 2). The two most prominent proglobalization organizations are the World Trade Organization (WTO) and the World Economic Forum. The anti-globalization side argues that “the competition brought by globalization actually puts those groups who lack some resources like knowledge, strength, etc. under too much pressure” (InvestorWords, n.d., para. 3). They claim this phenomenon is the result of being too connected to the rest of the world (InvestorWords, n.d.). Important anti-globalization organizations include environmental groups like Friends of the Earth and Greenpeace, international aid organizations like Oxfam, and third world government organizations like the G-77 Business organizations and trade unions whose competitiveness is threatened by globalization also frequently lobby against it. These include the U.S. textile industry and European farm lobby, as well as the Australian and U.S. trade union movements.
The majority of discussion surrounding globalization has to do with its economic impacts. For example, a local news broadcast is now so universally accessible that a simple business scandal can cause butterfly effects all over the world (Held, 2004). Economic globalization refers to the increasing interactions between world economies because of the rapid growth in international trade, international cash flow and the transformation of technologies.
Gao (2000) states that “the two main causes of economic globalization are the growing importance of information in operations and marketing” (p. 1). Technological and information advancements have greatly reduced the cost of transport and communication, which has promoted the development of international trade and investment, thus making it possible to organize and coordinate global production.
The market-oriented reform carried out throughout the world should be regarded as the institutional driving force for this trend. Under the framework of General Agreement on Tariffs and Trade (GATT) and WTO, many countries have gradually cut down their tariff and non-tariff barriers, and more and more countries are opening up their current accounts and capital accounts (Gao, 2000). All of these have greatly stimulated the development of trade and investment. Moreover, the transition of the former centralized planned economies to market economies has made it truly possible for the individual economies of each country to integrate into a whole.
Multinational corporations (MNCs) have become the main carriers of economic globalization. They are globally organizing production and allocating resources according to the principle of profit maximization. In so doing, their global expansions are reshaping the macroeconomic mechanisms of the world economies (Gao, 2000).
Economic globalists understand globalization as a phenomenon concerning the growing integration of the national economies of most states in the world. They attribute this to the following five interrelated drivers of change (Held, 2004):
- growing international trade resulting from lower trade barriers and more competition
- increasing financial flows in such forms as foreign direct investment (FDI) and technology transfers
- increased communications via both the Internet and ‘traditional’ media
- technological advances in electronics, transportation, bioengineering, etc.
- increased labor mobility
It is interesting to note that the FDI referred to above can take the form of brand-new investments known as ‘greenfield’ investments or it can also include mergers with, and acquisitions of, existing enterprises (Held, 2004).
Economic globalization has had an immense impact on the world. Some of that change has been positive, such as the transformation of industrial and production structure worldwide which has brought huge economic benefits to both developed and developing countries. At the same time, however, it has brought many problems such as the unemployment of entry-level workers caused by industrial relocation and increasing wage inequality caused by different labor costs in some developed countries (Goldberg & Pavcnik, 2007).
In general, automation is defined academically as the execution by a machine agent (usually a computer) of a function that was previously carried out by a human (Parasuraman & Riley, 1997). More broadly, it can also include a process completed with minimal human assistance due to technological assistance (Groover, 2010).
Automated production can complete standard production processes with minimal manual intervention, while reducing the production cost, greatly improving labor productivity and improving the product quality. Automation technology is widely used in industry, agriculture, military, scientific research, transportation, commerce, and medical care (Ruiz-Garcia, Lunadei, Barreiro & Robla, 2009). The continual advancements made in science and technology, especially in regard to artificial intelligence technology, has further accelerated the transformation of industry toward automated processes.
According to Nilsson (1998), “artificial intelligence, broadly (and somewhat circularly) defined, is concerned with intelligent behavior in artifacts. Intelligent behavior, in turn, involves perception, reasoning, learning, communicating, and acting in complex environments” (p. 1). Colloquially, the term “artificial intelligence” (AI) is applied when a machine mimics cognitive functions that humans associate with other human minds, such as learning and problem solving (Russell & Norvig, 2009). The concept of AI was first established in 1956 by J. McCarthy, Professor M. L. Minsky, H. Simon and A. Newell, along with C. E. Shannon, N. Rochester, and other scholars at Dartmouth College (Crevier, 1993). They defined it as “the ability of machines to understand, think, and learn in a similar way to human beings, indicating the possibility of using computers to simulate human intelligence” (Pan, 2016, p. 410). Since the 1970s, AI has expanded into research fields, including mechanical theorem proving, machine translation, expert systems, game theory, pattern recognition, machine learning, robotics, and intelligent control. The exploratory processes related to these fields have led to the development of many technologies and to the formation of various schools of symbolism, connectionism, and behaviorism (Pan, 2016). These advancements in automation technology mean that the possibilities of what can be automated are expanding.
Much of the discussion about automation has revolved around its positive and negative effects on society. Perhaps the most cited advantage of automation is its association with faster production and cheaper labor costs. Another benefit is that it replaces hard, physical, or monotonous work (Lamb, 2013). Not all the effects of automation are positive, however. Increased automation often makes workers anxious about losing their jobs (Autor, 2016). As shown in the following image, in the United States, 47 percent of all current jobs have the potential to be fully automated by 2033, according to the research of experts Carl Benedikt Frey and Michael Osborne (2017). Furthermore, wages and educational attainment appear to have a strong negative correlation with an occupation’s risk of being automated, meaning that the risk prospects are particularly bleak
Figure of job displacement is greatest for the lowes1: Jobs at risk of automation, by country (Frey & Osborne, 2017).
for occupations that do not require a university degree, such as truck driving, which have a high likelihood of becoming automated (Dickinson, 2018). Even in hightech corridors like Silicon Valley, concern is spreading about a future in which a sizable percentage of adults have little chance of sustaining gainful employment (Mashable, 2017).
Globalization and automation are interrelated phenomena that have significant impacts on the economies of the world, and in particular, the labor market.
The impact of globalization on the labor market has varied over time. In the short run, exposure to world markets is associated with lower wages domestically, but foreign direct investment is associated with higher wages, so it could go either way depending on the country and its trade exposure (Rama, 2003). Though the dispersion of wages by occupation does not seem to change much, returns to education increase with openness to trade, and they increase dramatically with foreign direct investment. In the medium run, the effect of trade liberalization on wages switches from negative to positive. Finally, in the long run, the positive impact of openness on per capita output should theoretically lead to a sustained increase in all wages (Matano & Naticchioni, 2010). Trade liberalization lowers unemployment and raises real wages as long as it improves aggregate productivity, net of transport costs (Felbermayr, Prat & Schmerer, 2011).
As for automation, studies since the 1990s have placed too much emphasis on the role of technological progress in promoting wage inequality in developed and developing countries, often ignoring the simultaneous impact of trade openness. Most of the studies examining the trade openness effects on employment and wage inequality effects within undeveloped and developing countries have been based on the mechanism of Stolper-Samuelson theorem and its various generalizations (Gaston & Nelson, 2004). This mechanism argues that trade liberalization promotes increased exports of labor-intensive products in developing countries, thus increasing the demand for low-skilled workers and the price of labor-intensive products (Gaston & Nelson, 2004). This subsequently increases the intensive use of these products, resulting in higher wages for low-skilled workers and a reduction in wage inequality (Gaston & Nelson, 2004). For fully developed countries, however, the mechanism works the opposite way (Gaston & Nelson, 2004). Trade liberalization promotes the export of skills-intensive products (as opposed to labor-intensive), thereby increasing the price of skills-intensive products, which is conducive to expanding the relative demand for highly skilled workers and raising the relative wage of highly skilled workers (Wood, 1997). This results in expanding wage inequality for fully developed countries (OECD, 2011).
Many studies, however, have found that the price effect of trade globalization described by Stolper-Samuelson’s theorem is too small to explain the recent rise in wage inequality in developing and developed countries (Harrison, Mclaren & Mcmillan, 2011). These critics found that technological advances and automation trends in the skillset explain the phenomenon more fully, so in the 1990s this latter explanation became dominant (Mann, 1998). Since 2000, the relationship between trade and wage inequality has largely been neglected, relying on those 19990s studies that favored the effect of automation over trade. It was not until recently that some studies realized how the automation-based studies had underestimated the impact of the globalization of trade, in the same way they had critiqued their predecessors of underestimating automation (Braga & Hoekman, 2016). The recent studies found the two worked together in different ways depending on the economy in question, and that trade globalization could be an even more important factor for developing countries, especially as a conduit for technological progress and the development of automation (Frey & Osborne, 2013).
Compared to globalization, the impact of automation on the labor market is reflected more through its significant correlation with unemployment rate. As mentioned previously, Frey and Osborne’s 2013 study estimated that about 47 percent of American jobs are at risk. In addition, based on their methodology and using data from the World Bank, jobs in developing countries are more susceptible to being replaced by automation (Frey et al., 2016). Compared with developing countries, OECD countries are immersed in panic about the business brought by automation. In fact, according to the research of Arntz, Gregory and Zierahn (2016), they found that on average across the 21 OECD countries, 9 percent of jobs are automatable. They also found further heterogeneity in OECD countries. For instance, while the share of automatable jobs is 6 percent in Korea, the corresponding share is 12 percent in Austria (Arntz et al., 2016). Differences between countries may reflect general differences in workplace organization or differences in previous investments into automation technologies, as well as differences in the education of workers across countries (Arntz et al., 2016).
As globalization and automation progress, the impacts could be severe. It is not simply that 47 percent of U.S. jobs are at risk, it is that the risk is concentrated on those with the lowest income and lowest levels of education. The charts below illustrate how the risk varies greatly based on an occupation’s median hourly wage, and then based on education level, and paint the picture of why these projected impacts are so concerning.
Figure 2: Job risk of automation by median hourly wage – Source: Frey & Osborne (2013)
Figure 3: Job risk of automation by education – Source: Arntz, Gregory, and Zierahn (2016)
Jobs making less than $20 per hour have an 83 percent risk of automation (Frey & Osborne, 2013). Employees with a high school education or less have a 63 percent risk that their job will be lost to automation (Arntz et al., 2016). Interestingly, men are also expected to be impacted more than women, especially when considering low-skilled jobs (Krieger-Boden & Sorgner, 2018).
Figure 4: Job risk of automation by gender – Source: Krieger-Boden & Sorgner (2018)
These pieces of the puzzle explain why policy makers are so concerned about the future. It’s not just that some jobs will be lost while others are created; it’s which jobs will be lost, and which skill set will be provided for in the new jobs.
Both globalization and automation are phenomena that have direct impacts on cultures and economies around the world, so it is natural that the attitudes and policies surrounding them would vary greatly depending on the country considering them.
Globalization can be a great opportunity to expand and strengthen their economy, or it can be a threat to domestic production, jobs, and even the culture. Countries with smaller economies must employ a different strategy than those that dominate the world stage, and developing nations must take special precautions to protect their culture and their people from being exploited, even as they attempt to reap the benefits that can come with opening up to globalization. It has the power to significantly alter the labor market, especially as countries begin to specialize in recognition of markets in which they possess a comparative advantage.
This can push some countries toward low-skill labor and others toward high-skill labor, greatly altering the employment landscape and affecting wage inequality for better or worse.
Automation is generally expected to do one of two things: make it so the same level of productivity can be achieved while using less labor, or conversely, make it so the same level of labor (albeit with different qualities) can achieve greater levels of productivity. Which of these win out is largely dependent on the policies and infrastructure molding the culture in question.
With technological advances occurring faster than ever before, it’s imperative that the proper infrastructure be in place. As stated in a review of the European Parliamentary Research Service (EPRS) and the Organisation for the Economic Cooperation and Development (OECD) report,
“Whereas in the past changes took decades, allowing for gradual adjustment, they now take place in years, posing a challenge to people’s job security and way of life” (Grajewski, 2018, para. 8). The changes being experienced will unavoidably have powerful impacts, but due to the shocking pace of automation’s expansion, whether or not that power can be harnessed for the benefit of the country will largely depend on a country’s ability to anticipate and prepare for those impacts.
Because of this variation seen around the world, in this section we will offer an overview of current policy regarding globalization and automation based on three geographical areas: the United States, Asia, and western Europe. These three spheres represent three different economies, cultures, and therefore approaches, to this issue. While these regions do not represent every possible policy approach, they do offer a variety of perspectives and strategies that are good examples to consider as possible solutions.
For the U.S., the main concern of both globalization and automation is mitigating job loss. Historically the country has been on the leading edge of digitization and research and development, so they are firmly established on the world stage as a dominant economy moving forward in these areas. Socially, there has been increasing income inequality as high-skill jobs are paying increasingly higher wages, while low-skill jobs are confined around a stagnant minimum wage that no longer is sufficient to keep full-time employees above the poverty level. This concern is amplified by the loss of jobs for lower-educated and lower-income individuals as the effects of globalization and automation spread throughout the country eliminating low-skill jobs.
Specifically in regards to globalization, American policy focuses on ensuring that current workers either receive low wage subsidies or receive special training and assistance when they are displaced from their job by increased imports. By providing this training, the policy is trying to provide displaced workers with new skills, so they are able to be find employment in a higherskilled work area. While this is a strong approach, “the nation’s capacity for training and retraining in response to trade would be enhanced,” as Lerman and Schmidt point out, “with improved systems for identifying sectoral skill demands, successful training models, and certification for occupational skills”. The current system could stand to be improved, but it is still a positive policy option for dealing with a globalized economy.
The predominant issue of concern regarding automation in the U.S. has likewise been unemployment. The idea being, that automation takes jobs from people, and whatever new jobs are being added to the pool are for a different skill-level of worker, perpetuating the unemployment of lower skilled workers and exacerbating wage inequality for those who are able to attain the new high skill jobs. To this end, policy discussions have centered on three main categories of action: increased support of education initiatives and (re)training programs, apprenticeship infrastructure, and enhanced social safety net programs. Of these, only a couple have been actually implemented on some level.
Improving and expanding the current educational system is the most commonly referenced solution and appears to have bipartisan support, although the details can vary greatly. Some argue for early childhood education programs, citing the significance of those prekindergarten years in determining future academic and workforce success (EPRS, 2018). Ranked 28th out of the 38 OECD countries, in the proportion of 4-year-olds participating in a preschool program, there is significant room for improvement (OECD, 2016). Others say the shortcomings of the current K-12 system need to be addressed first, and point to the fact that over 60 percent of graduating seniors were deemed not college- or career-ready in 2013 by the National Assessment of Education Progress (Executive Office of the President, 2016). They argue that the US government should focus on improving literacy and math proficiency to levels comparable to other developed nations (Executive Office of the President, 2016). Still others point out that the skills needed are changing, and things like memorizing facts should no longer be a priority of the education system (EPRS, 2018). Instead, a focus on cognitive and social intelligence is needed to train children in the ‘soft skills’ of human communication, empathy, and creativity (EPRS, 2018). There is also an increasingly supported initiative to make digital literacy and computer science a standard part of the curriculum in elementary and secondary education (Executive Office of the President, 2016). Many economists and policy advisors see this as an essential part of ensuring that the nation’s children are being trained in skills that will fit the jobs available to them as they enter the labor force, so that employers are able to find the workers they need and so that unemployment can be kept to a minimum (Executive Office of the President, 2016). An overhaul of the financial infrastructures surrounding higher education has also been recommended, as the tuition for a four-year public college has gone up 33 percent in the last ten years, while state funding for it has decreased by 18 percent (Executive Office of the President, 2016). To this end, President Obama had proposed “America’s College Promise” which would have made 2 years of community college free, however it was not enacted (Executive Office of the President, 2016). In fact, even though discussion of education concerns abounds, so far none of these policies have been implemented at scale for the country.
Similar to the education proposal, many advocate for more job skill training (and retraining) opportunities. There are some programs in place already, such as the Workforce Innovation and Opportunity Act, but even as the largest such program, it only trains 175,000 people per year (Executive Office of the President, 2016). According to the OECD, the US currently spends only 0.03 percent of GDP on training, compared to an OECD average closer to 0.6 percent – that means the US spends 5 percent what other countries do, relative to GDP (CFR, 2017), and in 2016 the United States was spending less than half of what it did, relative to the economy, from 30 years prior, so increasing it would be within reason (Executive Office of the President, 2016).
Figure 5: Public expenditures on active labor market programs as % of GDP – Source: OECD Statistics (2014)
This increase of spending on labor market training programs would allow individuals who are no longer in the conventional school system, to still have access to training opportunities for skills that the changing labor market has in higher demand, through community colleges or other trade institutions. Some even argue for an expanded infrastructure of credentialing arrangements (Mandel & Swanson, 2017). These training programs would enable workers to learn the skills needed to adapt to the changing conditions of their current workplace, or as automation-induced layoffs increase, give them the skills to find other work.
The Trade Adjustment Assistance (TAA) program does address these concerns, by way of both cash assistance and retraining opportunities for those displaced from their employment, but its current structure is insufficient to meet the need. A concept for enhancing it was recently acted upon by the Obama Administration with the TAA Community College and Career
Training program, which directed $2 billion to community colleges for the development of training programs targeted at adults (Litan, 2018). Funds were distributed as 4-year grants, and while 63 percent of all community colleges were able to receive assistance through this program, it was still just a one-time grant and not a continuing piece of the TAA program (Litan, 2018).
Furthermore, the resulting training was frequently irrelevant – it didn’t match the skills needed in available jobs and only 37 percent of participants actually gained employment in what they received training for (Meyers & Besanko, n.d.).
Another example, also introduced through the Obama administration, is TechHire. This is a partnership initiative still in operation that unites communities, employers, training agencies, and federal funding grants to build a “tech talent pipeline” (TechHire). It has largely been viewed as a success, and the number of communities participating has more than doubled since its inception, to 50 (TechHire).
As for the funding of these training opportunities, one proposal with support from Darrell West, Monica Herk, and the Aspen Institute, is based on the idea that automation is going to not just require retraining at a certain point, but continual lifelong learning to adapt as automation continues to change the landscape. With that foundation, “Lifetime Training Accounts” have been proposed that would be a contribution program similar to social security, tax-deferred and government-matched, that would allow people to make withdrawals throughout their life for job skill training purposes (Litan, 2018). This could have the combined benefit of funding training, while also encouraging people to take advantage of training opportunities, thus ensuring that America’s workforce stays up-to-date with technological advances (Litan, 2018). Fortunately, automation itself has ways to help provide this training, and with an increase of massive open online courses (MOOCS) a more intentional utilization of online and virtual reality training options could substantially improve and democratize skill level attainment (Mandel & Swanson, 2017; Meyers & Besanko, n.d.).
Along similar lines, the notion of apprenticeships is also gaining traction in policy discussions in America. Even with the onset of automation, a recent study found that about 20 percent of jobs fall in the category of both not requiring a bachelor’s degree, and still paying an average of $55,000 per year (Litan, 2018). The trouble is, these jobs still require specialized training of some sort, and it typically isn’t what someone naturally has upon high school graduation. They need trade-related training, and apprenticeships are posited as a great way to fill that gap on both ends, by giving un-trained workers an entry point to the industry and by providing a financial incentive for the employer to hire them. This was the view of the Obama administration, which awarded $175 million in 2015 to the expansion on apprenticeships and in October of 2016 continued that vision with an additional $50.5 million in grants for that purpose (Executive Office of the President, 2016). Apart from grants, another idea for accomplishing this is to provide employers with tax credits if they hire an apprentice (Litan, 2018). The obvious critique here is that it may incentivize employers to simply classify a new hire as an apprentice, regardless of their real ability, simply to capitalize on the tax credit, however this could easily be limited by duration or frequency constraints on the use of the credit (Litan, 2018).
Social Safety Net
The final significant category of conversation has revolved around enhanced social safety net infrastructure. A recurring sentiment among American analysts is that automation will not necessarily cause a net loss of jobs, but rather a change in the makeup of those jobs. The fear growing from automation-induced job loss, is therefore less about a net decrease in available jobs, and more about the transition period on the individual level which aggregates into a large concern. The issue is figuring out how to facilitate the transition of workers from their prior job, and into the one that will need them moving forward when it requires a different skill set. While the training and apprenticeship programs are large pieces of this and assist in getting them from one job to the next, there is also the significant concern of taking care of them in the meantime. Losing a job to automation does not sound as scary when you know your basic needs will be met while you are retrained for a new job. In fact, in countries like Sweden with comprehensive social safety net programs, 80 percent of people are in favor of automation and the increased productivity it brings to their country, compared to those in the United States, who do not have that confidence they will be cared for during transition (Roosevelt, 2018). Unemployment insurance has been weakened over time, to the point that now less than 1 out of every 3 unemployed Americans receive unemployment insurance, and it covers a smaller percentage of their wages (Executive Office of the President, 2016). Researchers have several ideas for how the social safety net in America could be improved.
To begin with the most extreme of the options being proposed, a Universal Basic Income (UBI) would ensure that every citizen received a certain baseline of money, regardless of their employment status. An interesting, if minimal, example of this is Alaska’s Permanent Fund Dividend (PFD) program. Alaska maintains ownership of the land that oil companies lease for rights to extract oil, and that income is pooled and distributed as cash dividends to any resident of Alaska who has been there for at least one calendar year and intends to stay (PFD). It doesn’t provide enough money to ever be considered a complete income substitute, providing only $2,072 per person for the year at its peak in 2015, but it’s an interesting approach to the concept (PFD). Most advocates for UBI, however, propose an amount that would be sufficient as the sole income for the household. Proponents argue that this would free them from the fear of losing their job to automation and would promote investing their time in unpaid beneficial activities like education and training, give more freedom in professional choices, and reduce poverty (EPRS, 2018). Opponents say this would incentivize unemployment, be expensive, and not target those who need the assistance the most (CFR, 2017). As CEA Chair Jason Furman commented against UBI, “We should not advance a policy that is premised on giving up on the possibility of workers remaining employed. Instead, our goal should be… to make sure people can get into jobs” (Executive Office of the President, 2016).
For those of a similar mindset, a less extreme option for income support would be a form of government-backed wage insurance (Litan, 2018). This would supplement an individual’s wages if they were unemployed or took another job that paid less than their previous job, at a rate relative to what they were making previously up to a certain amount, and only for a certain amount of time (Litan, 2018). The theory is that it would provide for them in case of layoffs, encourage them to pursue training, and most uniquely, encourage them to take another job that becomes available even if it is at a rate below what they made before (Litan, 2018). This is seen as a way to encourage them to remain in the workforce instead of becoming chronically unemployed and to take jobs that do require a higher skill set, and therefore pay less temporarily during the time the employee is being trained (Meyers & Besanko, n.d.). In the past, America has experimented with trial versions of this concept for specific trade-displaced workers, but although President Obama advocated for it in his last State of the Union address, America has not tried a full scale wage insurance program (Litan, 2018).
An even more palatable approach would be an expansion to the Earned-Income Tax Credit (EITC), with the thought that it can help provide some of that safety to seek training while also incentivizing people to remain in the workforce, but that it would need to be expanded in order to do so sufficiently (Hagermann & Ciuffo, 2017). This expansion was initiated in congress by Rep. Ro Khanna at the end of 2017, but no action has yet been taken (Khanna, 2017). Other social welfare options would be to increase support and time limits for unemployment insurance if retraining is occurring, or to implement a work-share approach to downsizing employment so that instead of laying off a certain number of employees completely and keeping others at their same amount of hours, a larger group of employees would stay employed but have their hours cut to weaken the impact of the effect by distributing it over multiple people (Executive Office of the President, 2016; Irwin, 2018).
Another avenue of income security, this one focused on job provision, comes from a proposal most notably made by Senator Bernie Sanders, although without gaining much traction (Litan, 2018). It is a federal jobs guarantee, a strategy also referred to as “employer of last resort”, which would make the federal government responsible to create jobs for the displaced workers (Litan, 2018). These jobs would be in areas such as janitorial services, roadway landscape work, etc., that would guarantee a livable minimum wage and benefits for those otherwise unemployed and seemingly stranded (Litan, 2018).
Gig Economy Infrastructure
As a second category of the social safety net considerations, automation has induced growth in the gig economy, which creates a large pool of workers who no longer have the stability or benefits of conventional employment, such as job stability, health insurance, or even robust inherent social connections (EPRS, 2018). The social safety net infrastructure currently in place in America is largely structured for the economy of the 20th century, where people were typically employees of a specific company, long-term, and those companies provided certain levels of security (CFR, 2017). As the gig economy takes up a larger portion of the workforce, and the cultural dynamics of company loyalty change, it’s important that the infrastructure be updated to protect workers of the 21st century. Proposals in this regard posit that things like health insurance and retirement plans need to be restructured to be independent of the companybased model and better support the range of employment structures and mobility providing security in the midst of flexibility (Mandel & Swanson, 2017; Irwin, 2018).
As helpful as many of the above proposals would be, the reality is that in their nationwide approach they are not taking into account the real discrepancies that exists geographically within the United States. As automation’s impact increases, there is a simultaneous shift across the nation that is concentrating the educated population and wealth in urban centers and leaving the rural areas short on jobs. Lack of affordable housing in the urban centers further hinders the ability of the unemployed to move to where the jobs are (Executive Office of the President, 2016). To combat this inequality, and prepare for this reality, a number of geographically based programs have been proposed. One would be a place-based expansion of the EITC to do more to subsidize employment in high unemployment areas (Litan, 2018). Another proposal, introduced in a bill by Senator Cory Booker, would be a spin on the federally guaranteed jobs program that selects just 15 cities marked by high unemployment to focus on (Litan, 2018). One approach that has actually been implemented is the Partnerships for Opportunity and Workforce and Economic Revitalization (POWER) Initiative, started under the Obama administration (Executive Office of the President, 2016). This has sought to focus on communities related to the coal industry as automation has moved the United States toward other energy producing methods (Executive Office of the President, 2016). POWER helps those communities to strengthen their economy through trainings, grants, and entrepreneurship activities, so the community members can create and find fruitful employment.
Conclusion of U.S. Policy Approaches
American policy makers have been discussing several avenues of policy approaches to mitigate job loss while continuing on the path of globalization and automation. While many have been advocates for education initiatives and training programs, the voices of those advocating for enhanced social welfare programs are also increasing. With so many options for action it can be difficult to decide which avenue to take, but if America wants to thrive in the future of globalization and automation, it will need to do more than just debate the merits of each option and begin actually implementing some of the proposals.
Asia is largely approaching the issues of globalization and automation from the opposite side of the spectrum. In contrast to the U.S., they are eager to experience the productivity boom that can come with greater automation and access to global markets. Historically, the region – especially China, has been more closed off to trade and has imposed harsher tariffs in an effort to protect their sovereignty and culture, however this has been changing in recent decades. Socially, the region has been experiencing dramatic reductions in income inequality, with globalization and automation strengthening economies and resulting in over 997 million people being brought out of extreme poverty (APEC). This is combined with a culture that is more accustomed to government management of the workforce ensuring employment, so they do not share the same fears over job loss. Attitudes in Asia are predominantly excited about the progression of automation and globalization and seek to reap all the benefits from it as they can.
Globalization has been hugely beneficial for the Asian countries in terms of vast improvement in both economic growth and quality of life. While not every country pursues the same objectives in terms of policy, most Asian economies are currently focused on producing products for exports. Recently, there has been a major push for more supportive policy focused on using the income from these exports to strengthen institutions such as schools, since “a study by Le Goff and Singh noted that more (global market) openness results in a reduction of poverty when the access to private credit is deeper, education levels are higher and the quality of institutions is strong” (Support Unit, 2017). By investing in their education system, they would be better positioning themselves to ride the wave of benefits that a more open economy would offer. While current policies focus more on production and are not as supportive of open trade to encourage economic growth, evidence of a push to embrace free trade is beginning to be seen.
As one of the largest manufacturing economies, a brief overview of Chinese globalization policy seems necessary. Unlike the predominant approaches in the U.S. and Europe, China’s globalization policy is designed to take advantage of a globalizing economy in terms of jobs, while preventing a vast majority of imports from foreign countries. Until the 20th century, China was relatively closed off from outside trade and was still a largely agrarian economy. This was followed by a planned economy focused on upgrading infrastructure and agriculture to provide for the population. Now, the country has undergone rapid industrialization and currently has an economy focused on manufacturing and low skill labor. This labor is used to manufacturing products to be exported, and current policy places extreme restrictions on importing the very products produced. China has become home to massive manufacturing facilities that utilize foreign inputs to produce their products. One major piece of policy that encouraged this growth was a 1987 change in the import tariffs and policy, in which “the government expanded… incentives to provide for duty-free import of all raw materials, parts, and components used in the production of goods for export” (Branstetter & Lardy, 2006).
China’s approach to automation is almost the exact opposite of America’s. While America, with its large labor force, is concerned that automation could reduce the number of jobs available for human workers, China, experiencing a decline in the size of its workforce, is excited at the prospect of automation making it possible for each human worker to produce at a higher rate (Khalid, 2017). In automation, China sees the ability to increase their productivity without needing more people to do so. Job loss does not concern them as much, because their subsidy approach has always had a direct hand in the economy and closely approximates the federally guaranteed job structure explained previously (Litan, 2018). China’s expectation that its workforce will shrink by 90 million people, however, provides great cause for alarm and excitement at the prospect of production rates being supplemented by automation (Khalid, 2017). In light of this perspective, they have focused on policies that encourage, and greatly subsidize, automation and the companies that make automation possible.
Figure 6: China’s working age population projection – Source: UN, Macquarie Research (2016)
Chinese President Xi Jinping has led the charge for automation in China through his calls for a “robot revolution” and the initiative Made in China 2025, which aim to focus on local development and production of high-tech goods (China’s manufacturing). This is already being seen through governmental support of various digital businesses. UBTech, a digital company in China that is ranked as the world’s most valuable Artificial Intelligence (AI) startup, not only received a large subsidy for their business, but according to an HR representative, “the land, the factory and even the office furniture are all offered by the government for free” (Khalid, 2017, para. 27). China is doing all it can to make sure that the automated economy of the future is dependent on the products created in China.
Conclusion of Chinese Approaches
China has greatly shifted their policy approach in recent decades. They are beginning to embrace globalization, however selectively, and are strategizing for their role in the global market. They are focused on amplifying the production benefits of automation to the point that production levels can surpass what it anticipates losing in workforce capacity. More than anything, China focused on building up its technological resources and knowledge, gearing up to be an increasingly dominant economy on the world stage.
In an interesting blend of attitudes from both the American and Chinese approaches, the approaches coming from western Europe are somewhere in between. It’s important here to note that the following discussion is focused on the countries of Europe comprising the European Union. Having been less involved historically in the digital scene, their main concern is establishing themselves in the technology market while continuing to protect their citizens’ wellbeing and the signature goods of their respective countries. They are trying to balance increasing globalization with the protection of their unique cultures.
Europe deals with globalization very differently than the United States. For a long time, Europeans were resistant to globalization efforts as “many Europeans worry about globalization’s effects on jobs, economic equality, European culture, or political independence vis-à-vis the United States” (Gordon, 2016). Gordon elaborates on that idea as follows:
It is true that globalization and economic liberalization pose greater challenges for Europe than for the United States. One reason is that the state plays a greater role in EU economies: State spending in the EU averages 48 percent of its Gross Domestic Product, compared with only around 36 percent in the United States; social expenditures average over 25 percent, compared with just 15 percent in the United States. Europeans are also more attached to equality and collective rights than are most Americans, who have a proud tradition of individualism. The problem is further complicated by relatively inflexible European labor markets. EU citizens are almost six times less likely than Americans to move from one region to another, and workers are less likely to accept wage or benefit cuts in order to preserve jobs threatened by trade. Finally, many Europeans fear that globalization—in the guise of “Americanization”—will threaten their local culture. (2016)
In order to combat this harsh view of globalization, the European Union has enforced strict sanctions and trade regulations regarding what can be brought into its member countries. One of their main weapons against foreign encroachment is tariffs, which can drastically increase the cost of international items shipped to European Union countries. These tariffs and regulations can present a major disincentive for foreign companies to compete in European markets, especially considering that these regulations are not present in other international markets.
These policies help protect European industries and help protect Europe from the ethical and economic issues that it associates with globalization. In ethical terms, European countries view globalization as taking advantage of low skill workers. They are also concerned about “funding conflict and human rights violations” through various industries, especially the mineral industry (Affaris, 2017). One of the recent European policies dealing with globalization is a requirement that companies using minerals be able to source these minerals from a mine that does not engage in human right violations. This is significant because of the large quantity of minerals needed for production of electronics. Minerals often come from poor countries, where workers are placed in harm’s way and paid little for their labor, and where the mines also produce a large amount of pollution and are a detriment to the environment. While these regulations honor the concern Europeans have for social and environmental justice, they can also place immense strain on European countries seeking to produce these goods.
Whereas America has proven itself at the forefront of technological innovation and the digital age, and thus can take for granted the continuing automation of its country and its dominance on the world market, Europe has been relatively inactive on the digital front (EPRS, 2018). Conversely, it is Europe that on average has more comprehensive social safety net infrastructures in place and can therefore better weather the transition of workers as automation expands (EPRS, 2018). These programs make a big difference in the willingness of the people to embrace automation. For this reason, even though the recent OECD report shows that 17 percent of jobs in the EU are highly likely to be automated soon, and another 32 percent are likely to change dramatically in light of automation, Europe isn’t facing the same level of pushback due to fear of job loss (EPRS, 2018). What’s more, they have made the conscious decision explicitly written in the European Parliament report, that trying to isolate themselves from the effects of automation to avoid its negative effects would be crushingly detrimental if not impossible, and therefore they are focused on preparing for and embracing the changes. To do so they are focusing their policy decisions on encouraging automation by increasing support of research and development, adopting fully digital systems for their communities and improving their education infrastructure (EPRS, 2018). Because of the great variety existing within the European Union member countries, these policies are best evaluated by looking at case studies of a few particular countries.
Germany offers three main approaches worth noting. The first is in regard to its education tracks program, which places students in either bachelor’s degree paths, or technical training apprentice-like programs (CFR, 2017). While the methodology for these placements is up for debate, relying on standardized test performance to determine a student’s path, the quality of the resulting workforce has been lauded (Hagermann & Ciuffo, 2017). The apprenticeships split time between classroom and on-site instruction, and are conducted in partnership with employers and the school system to target the development of skills most in demand (Hagermann & Ciuffo, 2017). This has enabled their training programs to prepare workers specifically for what that industry looks like within the context of automation (Meyers & Besanko, n.d.).
The second approach, referred to as Industrie 4.0, is a methodology for approaching manufacturing through the lens of automation. The term was coined in 2011 as a way to refer to the 4th wave of industrial revolution – the first being steam engines; the second, assembly lines; and the third computers and electronics. This fourth wave is characterized by the interconnectedness of cyber and physical systems. In embracing this Industrie 4.0 mentality for their manufacturing industry, they are training workers to view the process differently. They are taught to problem solve, innovate, and utilize the benefits of automation to improve the production process. This is crucial for Germany, as such a large portion of their economy is dedicated to manufacturing, and their ability to adapt to the new mentality of the industry is equipping them with workers who will be able to evolve with the changing landscape of the economy (Meyers & Besanko, n.d.).
No discussion about European approaches to automation and globalization would be complete without a look at Estonia; it is perhaps the most striking example of what can be achieved when a country fully commits to the coming wave of change and prepares appropriately. In the 90s, as they emerged from Soviet rule, their economy was weak at best, but they made a series of policy decisions around the digitization and automation of their country, and now are established as a high-tech European hub that is credited with the creation of Skype and more than 150 other tech companies (Meyers & Besanko, n.d.). The transformation started in 1992, when the prime minister implemented various entrepreneurship- and automation-inducing policies including free trade, privatization, and a simplified business establishment process (AAK, 2013). Then a nationwide push for computerization led to every school having computers and online access by 1998 (AAK, 2013). Critical to that continued transformation was Estonia’s declaration in 2000 that free access to the internet is a human right, followed up in 2002 by the installation of free internet across their country (Meyers & Besanko, n.d.). Not only are all of their schools connected to the internet, but they have gone far beyond that to start teaching children aged 7 to 19 how to code (Bowles, 2015). The idea is to start them young, so that computer thinking and smart technology comes naturally to them and they have the best likelihood of being prepared and adept at the jobs of the future (Bowles, 2015). Furthermore, in 2014, they launched “e-Estonia” which they define as a “digital nation” where anyone from around the world can apply for “digital citizenship” (eEstonia). This does not give them residency or travel rights like a passport, however it does give them full access to business and government resources within the country (eEstonia). Digital citizens can open companies in Estonia, file all necessary paperwork with ease online, open bank accounts, pay taxes, and a whole host of other tools that facilitate incredibly easy business operations (eEstonia). Pairing these digital business initiatives with the tech-educated workforce, it’s no surprise that Estonia has seen a surge of tech companies choosing it as their homebase (eEstonia). They have fully embraced the automated and globalized future and have positioned themselves, small though they are in land area, as a large contributor to the global scene.
Denmark has a whole host of impressive policies that enable high quality of life for its residents, but in terms of automation and globalization, it is their concept of Flexicurity that deserves extra attention. The term flexicurity was created to illustrate the tension and balance between flexibility and security; they see the two concepts as mutually beneficial (Andersen et al., 2011). As illustrated in the graphic below, flexicurity exists based on the interrelationships of three key spheres.
Figure 7: Flexicurity diagram – Source: Madsen (2006)
First, is the flexible labour market. Unlike many other countries, there are not as many regulations on companies to dictate the allowable conditions for an employment relationship to begin or end (Andersen et al., 2011). They operate on what is referred to as an “easy hire, easy fire” basis (Andersen et al., 2011). While this may sound risky from an employee’s perspective, it allows companies the freedom to hire people as needed, without being as concerned about being able to guarantee the job long term, or getting stuck with an employee that isn’t a good fit (Andersen et al., 2011). They can hire when they need more help, lay off people when they don’t, hire people to train, and lay them off if they aren’t able to learn the needed skills (Andersen et al., 2011). In general it makes it less risky for a company to make a new hire, and so they are more likely to do so. As stated though, this volatility can be a scary prospect from the employee’s perspective. That is where the second sphere, unemployment benefits, comes in to play. In Denmark, unemployment insurance provides 90 percent of the previous wage, up to €2,000/month for 2 years (and even those caps were increased during the recession) (Andersen et al., 2011). This generous policy practically eliminates the fears related to losing a job. If those were the only components of the relationship, however, people would likely be incentivized to try and get laid off from a good paying job, so they could receive an income without having to work for two years before applying for another job. That is where the third and final sphere, active labor market policies, proves itself to be crucial. These policies enacted in 1994 and 2001 built a system of “activation offers” (Andersen et al., 2011). The offers fall into three categories: counselling/requalification, job training, and taking employment with a wage subsidy (Andersen et al., 2011). When a worker is laid off from their job, he or she immediately begins receiving unemployment insurance. Soon after, depending on the age of the worker, he or she is given one of these “activation offers” which must be accepted in order to continue receiving the unemployment insurance. The initial offer is for a duration of 6 months, and if it is completed and the individual has not found another job, a new offer will be made every 6 months with a minimum 4-week duration (Andersen et al., 2011). This system gives priority attention to young adults, with those under 30 receiving their first activation offer no later than 13 weeks into their unemployment (Andersen et al., 2011). For those aged 30-60, their first offer is within the first 9 months of unemployment, and those over 60 receive one within 6 months (Andersen et al., 2011). The goal of the offers is to make sure that the time spent unemployed is being invested in gaining new skills and addressing things that may be keeping an individual out of the workforce, so that people can be re-employed quickly. This cycle, while producing a lot of movement within the labor market, leads to a constantly improving workforce and workers that are willing to embrace the process and learn new skills because they are confident they will be taken care of in the times of transition.
As a final note, it is worth mentioning that the Universal Basic Income strategy was tested in Finland starting in early 2017, but was announced a failure by mid 2018 (Jauhiainen & Mäkinen, 2018). It was just a pilot version, issued to a random 2,000 unemployed citizens under the premise it would last for two years (Jauhiainen & Mäkinen, 2018). Upon proven success, it was to be expanded to the rest of the country. When it was announced that the project would not be expanding, there were some that posited that it was not because the UBI failed Finland, but that Finland failed the UBI (Jauhiainen & Mäkinen, 2018). They argue that the limitations of the project in scale, amount, and timeframe had doomed the project before it even began (Jauhiainen & Mäkinen, 2018). Finland is still a robust social welfare country, however, with housing allowances for low-income families and free university tuition plus a €250 monthly stipend for its student citizens, so there is not large cause for alarm at the rejection of UBI (Jauhiainen & Mäkinen, 2018). In fact, a revised unemployment benefit policy referred to as the “activation model” has already been implemented to replace it with the goal of incentivizing job searching (Jauhiainen & Mäkinen, 2018).
Conclusion of European Approaches
European approaches vary greatly country to country, however the recent trends have been toward embracing advancements in globalization and automation and figuring out how best to equip their citizens to do so. They still want to protect their unique cultures and signature goods, but they are also motivated to prove themselves relevant for future economies. For them, it is a balance of preparing their workforce for the continuously evolving high-skill jobs, and providing ample social welfare programs to support their workers in times of transition.
The shift to automation and globalization on a worldwide scale is unavoidable. Workplace technology has been improving at a rapid rate in recent years as tech companies have increased the capabilities of artificial intelligence. Domestic and international businesses are cutting costs by replacing their workforce with machinery and outsourcing their positions overseas. Domestic workers are forced out of jobs without the necessary skills to transition to a new career. Governments must address these issues with policies that provide them sufficient income, train them to adapt to a changing job market, and create new jobs to replace business sectors that may never recover.
We propose implementing policy changes in five key areas to achieve a comprehensive solution: reducing trade tariffs, expanding job (re)training programs, providing a variety of income supplements, and revising the tax code.
Our policy proposals aim to capture the gains felt from globalization, automation, and the integration of economies while helping those who are negatively affected by job loss. Through our policy proposals, we hope to increase U.S. competitiveness in an increasingly automated and competitive world market. We aim to capitalize on the U.S.’s comparative advantages in order to capture as much gains from trade possible, while still helping to minimize the costs felt by those who may be displaced from their job or have their wages affected. Each of these strategies aim to mitigate these known negative effects. Some may address the problem better than others and some may cause additional distortions in the market, so evaluating and understanding each approach and how they work together is critical in determining how to mitigate the negative effects of globalization while harvesting the benefits.
Tariffs are a strategy used at times to impede the effects of globalization and automation. According to data collected by the World Bank, close to every country uses some level of tariffs, with Western economies generally having the lowest rates of tariffs (World Bank, 2018). This is shown in the map below, where lighter shades indicate lower levels of tariffs and darker shades show higher levels of tariffs.
Figure 8: Tariff rates by country – Source: World Bank (2018)
In recent history, most developed countries have advocated for lower tariff rates and freer trade. Since President Trump was elected, however, tariffs have been used as a tool by the U.S. to rejuvenate select sectors of the economy, like the steel and aluminum industries (Stanley, 2018).
As globalization and automation have expanded and world markets have become more integrated, industries like steel and aluminum have suffered due to increased competition. Jobs have been lost in these industries (Stanley, 2018). By imposing tariffs, President Trump has raised the price of foreign imported steel, giving American steel a chance to compete. This has led to greater profits for steel companies in the U.S.; according to the New York Times, ArcelorMittal saw its profits rise by 41 percent in the second quarter of this year compared to the same time period last year (Stanley, 2018). The company’s CEO attributes the rise in profits to the tariffs placed on steel, which increased the price of steel everywhere (Stanley, 2018).
Manufacturing jobs have also boomed in the U.S. since tariffs were increased for steel and aluminum. Manufacturing jobs are now growing the fastest they have in 23 years in the U.S. (Riquer, 2018). Employers in the manufacturing sector are seeing greater profits due to increased prices from tariffs and greater demand due to a booming economy. This has led to a surge in job growth that hasn’t been seen for some time. Tariffs in this sense have reversed the negative effect of job loss in the manufacturing sector in the U.S.
While there have obviously been beneficial results from tariffs, economists generally regard this approach as harmful to the economy. The tariffs on steel and aluminum may have benefited those industries, but prices for other goods like cars have risen due to higher input costs. In order for the U.S. economy to benefit from the tariffs in the aggregate, the increased cost of steel intensive goods must be low enough so as to not completely offset the gains steel producers receive from the higher prices due to tariffs.
Tariffs more generally create inefficiencies in the market. Tariffs artificially raise prices above the market equilibrium, which can be good for producers but bad for consumers. This can lead to higher profits and an increase in the number of jobs for the industry the tariffs are targeting, but it will also cause disruptions in other sectors of the economy. As noted before in regard to the steel industry, higher steel prices led to higher input costs for car manufacturers. This could spur car manufacturers to look for ways to cut costs, which could translate to layoffs for positions that can easily be automated or done away with. This cyclical effect can be observed whenever tariffs are introduced in any sector of the economy. Thus, the benefits of tariffs can be seen as very concentrated while the costs are more spread out among other industries.
With this analysis of tariffs and trade in mind, we propose that tariffs and all other barriers to trade be eliminated entirely across the board. Many of the current policies in place around the world and in the U.S. have been designed to treat the negative symptoms of globalization and automation. They have aimed at protecting certain industries and people regardless of whether or not that industry is truly profitable. By eliminating tariffs everywhere, the markets will be able to decide the allocation of jobs much more efficiently than the government picking winners and losers in the economy. While tariffs may have concentrated benefits, the aggregate U.S. economy benefits more from completely free trade, especially in favor of the consumer. The chart below demonstrates the gains from liberalizing trade in certain markets in the U.S.:
Figure 9: Welfare effects of liberalizing trade in certain U.S. industries – Source: Hufbauer (1994)
From this chart, it can be seen how beneficial free-trade can be for an industry and an entire economy. For example, maritime transport has a tariff or equivalent rate of 85 percent. By liberalizing trade and eliminating tariffs in that market, the consumer gain felt per job lost would be about $415 billion. The net national gain, even after factoring in losses from jobs lost, would still equal about $126 billion. There are enormous gains to be had from completely liberalizing trade across the board. While producers in some industries may suffer, the other pieces of our proposal will help to minimize the magnitude of their suffering.
As technology improves, it is inevitable that the U.S. economy will become more integrated with other economies. That change should be embraced and taken advantage of rather than resisted. Rather than subsidizing markets that are inefficient compared to elsewhere in the world, the U.S. should focus on its comparative advantages. Tariffs and other barriers to trade should be eliminated everywhere in the world and countries should specialize in their comparative advantages in order to feel the enormous gains from free trade. As shown, this will benefit consumers greatly and will eventually benefit producers that will suffer initially.
Retraining programs have often been used to help workers gain the necessary skills they need to get into new jobs. Due to increased competition, specialization, and automation across the globe, many lower skilled jobs have been lost in the U.S. and those workers need help finding employment in other sectors. The Trade Adjustment Assistance (TAA) program in the U.S. was designed to limit the negative effects of globalization and automation on these workers by providing them with three key services: monthly cash benefits, assistance in employment and training services, and services like job search assistance, relocation assistance, and tax credits to help cover the cost of health insurance (Wandner, 2013).
The TAA program has been successful in some respects. Studies have shown that participants of the training aspect of the program have experienced increases in their reemployment probabilities (Guth, 2017). Compared to a group of individuals that exhausted their Unemployment Insurance benefits, those who participated in TAA trainings had significantly greater employment rates after participating in TAA for four years or longer (Guth, 2017). “Specifically,” according to the report, “in the evaluation’s 16th quarter, TAA trainees had employment rates that were 11.3 percentage points higher than those of the comparison group” (Guth, 2017, p. 2).
There seems, however, to be a great amount of evidence against the Trade Adjustment Assistance program. One study found that employment rates of those receiving benefits spike after 26 weeks, which is maximum duration benefits can be received (Baicker, 2004). This would suggest that the TAA program is giving individuals the incentive to stay unemployed longer. They also found that increasing benefits for claimants increased take-up rates and unemployment duration, “with a 10-percentage-point increase in generosity leading to an increase in duration of as much as one week or more” (Baicker, 2004, p. 248). Another study found that those who participated in TAA programs “experienced lower reemployment rates and greater earnings losses 36 months after they lost their jobs” compared to similar workers who did not participate in the program (Guth, 2017, p. 2).
Based on the majority of the studies conducted on TAA, it would appear that some parts of the program are more effective than others. The training that workers can receive through the program has been shown to have positive effects on employment, but the program overall can lead to longer unemployment durations and lower reemployment rates.
We would propose a variation of the TAA, using the successful aspects of the program and eliminating parts that lead to longer unemployment durations. By eliminating cash benefits and instead focusing solely on the retraining of those affected by job loss and helping individuals find new work, we will end the incentive to remain unemployed while in the program. The takeup rate may fall for the program, but the unemployment duration for those participating in the program will fall as well. While other aspects of our proposal, like some income measures that will be discussed later, could contribute to an increase in unemployment duration, this new TAA will incentivize employment. Participants would be encouraged to find a replacement job, whatever that may be, while being enrolled in retraining.
Expanding and refocusing the retraining program itself would also be beneficial. The purpose of the TAA program is to retrain workers displaced by trade and automation and place them in stable new jobs. Many of the displaced workers that benefit from this program come from low-skilled sectors. Retraining this adversely affected workforce could be seen as a great opportunity for economic growth. While each worker in the program should be free to choose what type of new job training he or she receives, the retraining focus should be reserved for the fastest growing industries. According to Forbes in 2018, the fastest growing industries in the U.S. are construction and construction related jobs, support for mining activities, real estate, architecture, and computer system design, so that is where we propose to focus (Biery, 2018).
The new TAA program will have specific training programs and partnerships with firms in those industries and in the fast-growing industries of the future. Focusing on these industries will ensure that each re-trained worker will have a job after leaving the program. Demand for labor in these industries will obviously be high, so this may help re-trained workers find jobs even quicker than they do with the current TAA retraining program. The TAA program will be a great supplier of labor for firms looking for new hires and will ensure that these types of industries always have enough labor to function.
Not only should the retraining program target fast growing industries, but it should target industries that the United States has a comparative advantage in. The U.S. has a comparative advantage over other countries in areas like research and development and high-tech industries. Our new TAA program will aim to capitalize on these advantages by incentivizing program participants to retrain into one of these fields. This goal will be further incentivized through a wage supplement that will be discussed later. The fields of comparative advantage are essential to focus on because they are the ones most likely to remain in the United States, and even grow here, in the midst of globalization and automation. If the U.S. continues to support industries that are not one of our comparative advantages, we will be exacerbating future losses rather than feeling a reduced impact now. We propose a responsible, forward thinking policy to help workers the most possible in years to come.
While cutting the cash benefit portion for those that participate in our TAA program could have adverse effects on those workers, we believe those will be mitigated by our income related subsidies to be discussed next. We also feel the refined industry focus of the TAA program will better equip the participants to quickly find another job, and a more reliable one at that. With these changes to the TAA program, along with our additional proposals, we hope to create enough pull factors to entice displaced workers to retrain into more profitable industries for the U.S. In consideration of the work requirement budget constraint, our TAA wage subsidy would be formatted as shown below in red.
Figure 10: Budget constraint on work requirement, with proposed TAA subsidy
The concept of a Universal Basic Income (UBI) is one in which every citizen is guaranteed compensation from the government, regardless of their employment status. A set amount could be distributed in check or electronic form. The annual amount that is distributed would differ depending on the age of the recipient and we would propose that it begin as a pilot program targeted at low-income families as a replacement for the collection of current U.S. social welfare programs. Income tax revenue would be shifted from the Supplemental Nutrition Assistance Program (SNAP), Temporary Assistance for Needy Families (TANF) and Supplemental Security Income (SSI) to the UBI fund to cover basic necessities. More extreme measures could also be considered that would include the transfer of Medicare and Social Security funding to a UBI program. Similar programs that were proposed estimated that repealing these major welfare programs would free up around $2.56 trillion for UBI (Ensor, Frailey, Jensen, & Xu, 2017). In 2016, the federal government spent more than two-thirds of their total annual spending to cover the major social insurance programs (DeSilver, 2017). This figure would likely be more than sufficient to fund UBI for low-income families.
The distribution would be based on the per-person federal poverty level in the continental United States. No increases would be considered for each additional person to ensure that that UBI rate is uniform for all those who receive it. The initial proposed rate would be set at $18,210 per person, which is 150 percent of the current federal poverty rate (DHS, 2018). The Department of Labor estimates that annual federal minimum wage income would equal approximately $15,080 at a 40-hour work week. As such, the proposed UBI rate would represent a substantial increase in income for many low-income workers without any employment requirements on their part. The work requirement budget constraint with this UBI applied, would essentially raise the floor to the blue line as shown below and increase the Imax possible.
Figure 11: Budget constraint on work requirement, with UBI
Age requirements would be enforced to guarantee that annual funding does not surpass current social insurance spending that is afforded to both adults and children and UBI would be available to anyone over the age of 18, since it would most likely meet the minimum working age for most businesses. The recipients should have sufficient income to provide for their families as the UBI is intended to be supplemental income.
The Universal Basic Income would offset lost income and jobs due to automation especially, and provide stability while workers learn new skills and embrace the technology of automation to survive in the evolving market. It would also serve a similar function to Unemployment Insurance in times of recession or economic hardship. Spending and consumption would still be somewhat stable during these times because everyone would have a guaranteed income. This would help to boost the economy and smooth consumption over time. While it is up for debate whether or not automation will eventually end the need for human workers, the UBI would be an answer if it were the case that workers were no longer needed. Our current labor markets, however, do still require human labor and the UBI will admittedly have distortionary effects on the market.
With a basic income guaranteed to at least all low-income workers, the incentive to not work would be strong. With our proposed amount of guaranteed income, a minimum wage worker would actually earn more in a year through the UBI than he would if he were to work full-time, and for those in the graph that fall to the right of where the blue and dotted lines meet, they would get more money for not working. For those already working full-time and making well over the UBI, the incentive may not be as strong to quit working. On the other hand, even for those earning well over the guaranteed amount, there may be a pull to cut back on hours to enjoy more leisure time. This could have a large impact on the productivity of the economy, especially in low-skilled labor industries.
We also are hopeful that the TAA-specific wage subsidy will provide a countering incentive for more people to choose employment. This combination of UBI with the TAA subsidy is shown below.
Figure 12: Budget constraint on work requirement, with UBI & TAA subsidy
Tax dependent wage subsidies are another tool used to combat job loss and pay decreases due to globalization and automation. Many countries, including Canada, Germany, Sweden, and the United Kingdom, have developed some sort of wage subsidy for low-income individuals and families (Austin, 2015). In the United States, the Earned Income Tax Credit (EITC) is a form of wage subsidy and is very popular welfare program. Most recipients of the EITC are lower income individuals and families, as shown below.
Figure 13: EITC recipients by adjusted gross income – Source: Austin (2015)
These individuals and families receiving EITC are more likely to be low-skilled workers, which means they are also those most likely to be affected by job and wage loss from globalization and automation.
The EITC has been shown to reach a much larger number of individuals and have a much greater impact on alleviating poverty than other federal programs (Austin, 2015). One study has shown that in 2013, the EITC could be credited with raising 9.1 million individuals out of poverty (Austin, 2015). The only Federal program that can be shown to have a greater effect on poverty reduction is Social Security. The EITC also has been shown to have less work disincentives than other means-tested programs (Austin, 2015). Clearly, the EITC has positive effects for low-income and low-skilled workers that could be affected by globalism and automation.
Unfortunately, expenditures for the EITC are very large compared to other means-tested programs. It currently is the largest federal cash transfer program for low-income workers, costing $69 billion in 2015 (Cato, 2015). Costs for the program have been rising ever since its implementation, as more individuals qualify and become aware of the tax credit. Costs are expected to rise in the future as well. Another downside to the EITC is that it gives employers an incentive to decrease wages for those who receive the tax credit or those that qualify for it, because they count on the government to make up the difference (Austin, 2015). Studies have shown that a 10 percent increase in the EITC benefit leads to a 5 percent reduction in pre-tax wages for high school dropouts and a 2 percent decrease for high school graduates (Austin, 2015). Employers seem to be taking advantage of the wage subsidy by reducing the cost of labor. The EITC also seems to have a version of work disincentive, although much smaller than other means-tested programs. There is incentive to begin working, but once a recipient of the benefit reaches a certain level of income, the wage subsidy they receive begins to phase out. This could incentivize the individual to work less in order to maximize their benefit received.
In recognizing the positive foundation of the EITC, we propose an altered form of the EITC to better target those most likely to feel the negative effects of automation and globalization. The EITC has been shown to reduce poverty, encourage individuals who are unemployed to take a new job, and have lower work disincentives than other means-tested programs. However, given the fact that we are already proposing a universal basic income, this program in its current form would be largely ineffective and unnecessary. Thus, we are proposed a modification of the EITC to promote certain kinds of work, rather than all work, through a wage subsidy.
The renowned economist Milton Friedman proposed a hypothetical negative income tax (NIT) plan that would split the difference between the taxes paid by low-income workers. Under this plan, everyone who earned less than $3,000 annually would receive 50 percent of the difference, which would equal around 25 percent of that total income (Weller, 2017). For instance, a worker that earned $2,000 would receive a $500 credit, and a person who earned no income that year would still be eligible for the credit. Reversing the tax liability for the lowincome earners could alleviate the burden of lost income for displaced low-skilled workers. The current proposed adjustment to EITC would essentially make it more similar to this NIT structure, but with a work incentive. Those who are eligible could claim the credit up to $21,000 of annual income, which is based on the original $3,000 cap adjusted for inflation.
Eligibility would be based on income level, and limited to those employed, and specifically those employed in identified industries. Globalization and automation affect the United States differently than a country like China. Low-skilled labor is abundant in China, so naturally they have a comparative advantage in producing goods and services that require lowskilled labor. The U.S. is capital and high-skilled labor abundant, so we have a comparative advantage in producing capital intensive and high-skill labor intensive goods and services. Rather than reward low-skilled labor with a wage subsidy, we propose providing a wage subsidy for industries producing goods and services that are high-skill labor intensive and capital intensive.
This subsidy will be structured similarly to the current EITC. While workers are training at the beginning stages of their careers in these new industries, the wage supplement will phase in at 20 percent. This will encourage new workers to continue to train and gain more skills while solidifying their attachment to this industry. Once their subsidized wages hit 95 percent of the industry’s average for that type of position, the subsidy will plateau. When wages reach 105 percent of the industry’s average, the phase out portion of the subsidy will begin at 10 percent and end when wages hit 110 percent of the industry’s average. This is displayed in the budget constraint below, showing how this EITC expansion is expected to interact with the UBI and TAA subsidy.
Figure 14: Budget constraint on work requirement, with UBI & EITC expansion & TAA subsidy
While these subsidies may not be politically popular, they will help the United States to capitalize on its comparative advantage in high-tech and research and development industries. The wage subsidy will incentivize workers to retrain, leave their old industries that are moving to other countries, and start working in these more stable and growing industries in order to cash in on the wage subsidy. This will help transform the U.S. economy into the research and development and high-tech giant it should be in a global economy with limited tariffs.
Many global businesses avoid major tax liabilities by way of automation because machinery and robots are not subject to state and federal taxes. Companies are also able to take advantage of depreciation on their equipment and other company assets. Additionally, though laid off employees may eventually retrain to transition to job sectors that are stronger during automation, substantial short-term job loss due to automation is likely inevitable. The World Economic Forum estimates that automation could result in the loss of 5.1 million jobs globally by 2020 (Abbott & Botenschneider, 2018). This isn’t only negative for the workers, it means the government will also have decreased revenues because of a reduction in tax receipts.
The data suggests that governments will lose millions of workers in the tax pool without an immediate replacement for the income and payroll tax revenue. One policy proposal that would offset these losses would be a Robot Tax for the usage of robotic machinery and artificial intelligence in the workplace. Similar measures have been proposed overseas in recent years. In 2017, the European Parliament rejected a Robot Tax to help assist displaced workers, but the tax gained the support of Bill Gates as a way to slow down the spread of automation and repair the tax streams (Abbott and Botenschneider, 2018). The tax would be enforced as the cancellation of specific tax deductions. Companies will simply not be afforded the current corporate tax deduction on their robotic machinery when they decide to replace their traditional workforce with machinery. The policy would incentivize businesses to hire or keep more workers as the opportunity costs involved in switching to machinery and robotics would no longer be as attractive. South Korea has experimented with the world’s first robot tax by reducing their corporate tax deduction on automatic machinery to 2 percent (Abbott and Botenschneider, 2018). The proposed U.S. robot tax would be similar, but it would go further in discouraging automation by completely eliminating any tax deductions, corporate or otherwise, on robotic machinery.
While each of our proposed policies comes with its own set of impacts – both those desired and those undesired, it is also important to consider their collective effect. Disincentives of one may be countered by incentives of another, and we believe in the end, the scale tips in favor of creating a stronger economy with more protection for the workers.
We believe that opening up the economies of the world by eliminating tariffs will be beneficial, both to consumers and workers. Many of the past policies that were created to address globalization have not truly addressed the problem; rather, they have tried to put off the inevitable. As technology improves even more in the future, it will become increasingly difficult to mask the negative effects of globalization and automation. It would be better to address the problem head on now, rather than drag it out like it has been in the past.
When countries specialize and trade freely, economic output increases. The training and education programs we have proposed will encourage U.S. workers to work in the industries that the U.S. has a comparative advantage in, such as high-tech industries and research and development. As more skill is developed in these fields, the U.S. will continue to create more output. New jobs will be created to meet the demand in these industries and consumers will benefit from increased competition and lower prices. We recognize, however, that it may not be possible to retrain all individuals into these types of fields, and obviously some may not like these industries or just not be skilled enough to do these types of jobs. Due to this possibility, it would still be advantageous for training to be done for other fast-growing industries in the U.S. that may not be a part of the country’s comparative advantage.
While some of our policies incentivizing automation could potentially slow the economy in the short run due to job loss, they will increase economic output and stability in the long run. The Universal Basic Income has been proposed in order to help with this short-term loss. This would allow many of those that suffer the negative effects of globalization and automation to still have a decent standard of living while taking advantage of our other policy proposals. Admittedly, the UBI has strong work disincentives that could discourage people from participating in or reentering the workforce, but we think it is a necessary component to give workers the reassurance and security they need in order to be willing to embrace advancing automation. With the knowledge that they have a UBI to fall back on, they will not be as resistant to the change, and hopefully will use it as an opportunity to seek out advanced retraining.
The wage subsidies we have proposed also add an encouragement for people to seek employment, and specifically to be workers that specialize in the U.S.’s comparative advantage.
The wage subsidies will act as an incentive for low-skilled workers to receive more training. Before they are even fully trained they will receive a much higher level of pay due to the subsidy. This will cause many workers to rush to the types of jobs that the U.S. will be specializing in due to increased levels of trade. Once they are trained in these industries, it will not make sense for them to leave their new field. They will continue to build expertise and pull even more workers to the field. There is a risk that employers may take advantage of this subsidy and view it as a way to have lower labor costs, but as long as they do not take advantage of the whole subsidy, it will still be advantageous. By decreasing labor costs, employers will benefit and the industry will expand. New jobs could be created and the economy would continue to benefit.
The tax reform will be a benefit to workers affected by automation as well. Although robots are created to do some of the same tasks as humans, they are not taxed the same. This gives businesses a large incentive to decrease their use of human labor and turn to automated labor. By reforming the tax laws in this area, humans will not lose their jobs to automation at an accelerated rate, but rather through gradual transition that will give time for people to be trained into the more sustainable industries. Jobs will be saved, fewer people will be displaced at any given time, and the economy will benefit as well. Admittedly, this policy runs the risk of becoming too dramatic of a damper on the advancement of automation and the economy. Employing automated labor is much cheaper for employers, and by increasing costs of that automated labor, firms will suffer and jobs that could have possibly been created because of automated labor will actually go away. As was cited before, technology and human labor can also be complements rather than just substitutes, and this tax reform views technology as competition to human labor. However, with the majority of our policies focusing on embracing and encouraging automation, this should be viewed more as a small counterweight designed to prevent things from accelerating too quickly and to maintain government funds for programming.
As a whole, we believe this comprehensive policy proposal would encourage the U.S. and other countries to embrace globalization and the benefits that come from it. While some of our policies would actually increase job loss, others would help make up for those losses by retraining the workforce to be better equipped to function in a highly efficient world. The world gains in quality of life and GDP would be enormous if our policies were to be enacted. There would be greater market efficiency and a greater social safety net provided to all individuals, while cutting down on government waste and inefficiency. We believe that these are the correct policies to be enacted in order to address globalization and automation.
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