Archives: Reg Murphy Pubs

Problems with Estimating Multiplier Effects

Last month, I used this space to write about the multiplier effect associated with government spending. Theoretically, each dollar spent by the government—or anyone else, for that matter—is multiplied in its impact on the economy.

Last month, I provided two examples:

1) SNAP benefits, commonly known as food stamps, have been estimated to have a multiplier effect of about 1.5. This means that $1 billion in government spending on SNAP benefits results in a $1.5 billion increase in GDP, as each dollar spent on groceries through SNAP is multiplied as wages for individuals working in food production, sales, and transportation.

2) The CARES Act, passed early in the pandemic to provide cash relief to each American household, is estimated to have a multiplier close to 1. Our GDP will regain almost exactly what was spent in stimulus.

Today, with all due respect to my fellow economists who spend countless hours analyzing data to arrive at these multiplier estimates, I am going to walk this back a little.

Among economists, there actually is a good deal of debate about multiplier effects. Economist Daniel Carroll of the Federal Reserve Bank of Cleveland describes the reasons for this debate in a 2014 article, which I summarize below.

Theoretically, there is some dispute about the existence of a multiplier effect. This goes back to the definition of GDP. GDP is the sum of Consumption, Investment, Government spending, and Net exports. Although an increase in government spending is a direct increase to GDP, that spending must be financed somehow, either through increased taxes, increased government debt, or monetary expansion. Any one of these three options has the effect of decreasing private consumption or investment, or both.

An increase in government spending will only increase GDP if the increase in spending more than offsets the effects of financing that spending.

Generally, I think most folks agree that there probably is some positive multiplier effect on government spending. However, the details of how we assign a value to that multiplication are always in contest. As Carroll points out in his article, and I can attest from my own experience, measuring money multiplication empirically is no simple task and almost always involves making assumptions and doing a lot of guess work.

A major difficulty with estimating the size any economic relationships is that economics studies changes in the real world, and we can rarely observe these changes in a vacuum. In the case of multipliers, it is really hard to tell whether a change in GDP is a result of a specific spending policy, whether the change in spending is a result of the change in GDP, or whether both the changes in GDP and spending are results of some third variable. In fact, it is very likely that all three of these relationships occur at once.

This difficulty establishing causality would tend to lead to overestimations of multipliers should we assume that GDP changes result from spending changes.

Another issue with empirically measuring the size of multipliers is that changes to government spending often are debated and publicized for long periods of time prior to their being enacted. This gives businesses and individuals time to anticipate future increases in their cash flow and change their behavior prior to the actual implementation of the new spending policy.

This anticipation problem would tend to lead to underestimates of multipliers if we cannot measure the extent to which prior GDP changes are related to future government spending.

And all of this is complicated by the fact that there is no single multiplier for government spending. The size of the multiplier depends on the strength of the economy at the time of the spending as well as where the money is spent.

In sum, I believe spending is multiplied, and I believe attempting to measure the size of multipliers is useful for informing policymaking. But, I do not envy those whose job it is to do the estimating. It’s a tough, if not impossible, job.

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Dr. Melissa Trussell is a professor in the School of Business and Public Management at College of Coastal Georgia who works with the College’s Reg Murphy Center for Economic and Policy Studies. Contact her at mtrussell@ccga.edu.

Risk Assesment and Public Policy

As I am writing this in mid-December, the first 100,000 or so doses of the Pfizer COVID-19 vaccine have arrived in Georgia and have begun their deployment to hospitals and long-term care facilities around the state. Just because it’s here, however, does not mean it’s being administered as readily as public health officials might have liked. For instance, I heard from one local physician who indicated that even within the healthcare community in Glynn County, there is some skepticism over the safety of a vaccine that is being released so quickly. Not all healthcare workers who are eligible to receive the vaccine are ready to do so. Likewise, in a  recent McKinsey and Company consumer survey (2466 respondents) more than half the respondents in the United States report they are likely to delay or decline vaccination despite regulatory approval, with safety concerns being the main driver of vaccine hesitancy.

The skepticism, as I understand it, largely revolves around the time that it took for the vaccine to be tested and then released. For a typical vaccine, according to Pfizer’s website, Phase 1 of a clinical trial includes about 100 participants and takes 1 week to several months to complete. Phase 2 includes several hundred participants and takes up to 2 years, Phase 3 can include up to a few thousand participants and takes 1 to 4 years. And the final Phase 4 includes several thousand participants and takes over a year to conclude. In total, at best a typical trial period would take about 3 years. The Pfizer COVID-19 vaccine trial took under a year but did include a similarly large participant pool of 42,000 people.

The big public health and public perception question is, “were corners cut in this modified timeline?” When reviewing the Food and Drug Administration panel’s comments on the Pfizer and Moderna vaccines, I saw a lot of discussion about cost benefit and risk analysis. According to a National Public Radio report, one committee member, Dr. Paul Offit director of the Vaccine Education Center at Children’s Hospital of Philadelphia, framed it this way: “The question that’s being asked [of] us is do we have enough evidence in hand to say that the benefits of this vaccine outweigh what, at the moment as far as severe safety issues, are theoretical risks. I think the answer to that question is clearly yes…The question is never when do you know everything, it’s when do you know enough.”

This kind of risk assessment and reasoning sounded very familiar. My field of study is environmental policy, and in this field risk assessment is an important part of the regulatory and law-making process. Human activities almost always carry an environmental or human health risk; developing policy around human activities, therefore, requires risk assessment. The challenge is to determine what constitutes “acceptable risk.” Carcinogens, for instance, are generally regarded as having no acceptable threshold of exposure, and yet even The Food Quality Protection Act (FQPA) of 1996 simply requires “reasonable certainty that no harm will result from aggregate exposure,” not zero tolerance. The reason for this is twofold: uncertainty is inherent in modeling future events, and “sufficient information will rarely be available to permit an accurate assessment of environmental health risks…uncertainties arise at all stages of risk assessment” (James E. Anderson, 1984).

These same ideas surround the vaccines. When the vaccines were released in the UK, there were some adverse immuno-responses that were not observed in the trials. Why then did UK health officials release the vaccine? Because uncertainty is inevitable in risk assessment and they (along with the FDA) found the potential risks are outweighed by the benefits – namely high efficacy rate, increased population immunity, and decreased death rates.

Finally, it’s worth mentioning that two terms – efficacy and effectiveness – are often used interchangeably to talk about the vaccine performance, but they have different meaning. Efficacy is the percent reduction of the disease in the optimal clinical conditions. Effectiveness is how the vaccine operates “in the real world” (different primary care settings, broader population) after it is released to the consumer population. In one’s own assessment of risk, these are important to understand.

Whether you feel comfortable taking this early vaccine or not is ultimately a personal choice. While public health policy is based as much on politics as it is on science, we have not yet heard anything on a federal level that indicates that our country will have compulsory participation. Instead, it will be up to us as individuals within the community to read the science, review the assessments, and determine if we are ready to take on the inherent risk in order to reap the anticipated benefits.

Dr. Heather Farley is Chair of the Department of Criminal Justice, Public Policy & Management and a professor of Public Management in the School of Business and Public Management at College of Coastal Georgia. She is an associate of the College’s Reg Murphy Center for Economic and Policy Studies.

Climate trends and the Pandemic

In late spring of this year, several articles suggested that the global pandemic, and the drastically reduced travel that accompanied it, might actually help “heal” the earth. The assumption was that we would potentially see a reduction in CO2 emissions because people were staying home more and not traveling by plane. Indeed, plane travel has dropped by around 95% and at least 61 million Americans have stopped commuting during the pandemic. These trends are similar globally. News outlets have been reporting that people can actually see and feel the impact, particularly with less smog and cleaner air in large cities like Los Angeles and Mumbai where previously cloaked vistas are now visible. Given that just one roundtrip flight from New York to London generates as much CO2 as the CO2 generated by the average Nicaraguan annually, it is not surprising that these predictions of a “healing earth” were being made.

Cleaner daily air quality, however, seems to be the most encouraging metric; other correlations and data trends do not paint quite as rosy a picture. One data trend that was expected to be a little more encouraging is greenhouse gas concentrations. At the risk of stating something you’ve heard ad nauseum, let me break down for you how greenhouse gas concentrations operate. Greenhouse gases are substances like carbon dioxide (CO2), methane and nitrous oxide. When released into the atmosphere, these gases trap heat and drive up temperatures close to the Earth’s surface. Atmospheric concentrations are cumulative meaning they result from both past and present emissions and are measured in parts per million (ppm). A recent report from the World Meteorological Organization (WMO) suggested that while carbon emissions fell by 17% in early 2020, the overall effect on atmospheric concentrations is very small; again, this is because concentrations are cumulative and so we have only slowed the rate of increase, but we are still increasing. In other words, it will take many more years of continued reductions in emissions to slow the rate of concentration growth from year to year in a meaningful way.

There is also a connection between rising temperatures and the ranges of zoonotic pathogens. I know that was a sentence-full of jargon, but the idea is that as temperatures increase, many of the carriers of pathogens such as dengue fever, zika, west nile, or Lyme disease, can increase their habitable area and increase the spread of these pathogens. Mosquitoes like warmer temperatures. For example, before 1970 the World Health Organization recorded 9 countries with dengue epidemics. In 2019, that number rose to 128 countries as mosquitoes have been able to move northward and into higher elevations due to rising temperatures.

Finally, there is a single business case that I think represents a larger economic issue during the pandemic. Exxon Mobil Corp. owns a complex of pipes, tanks, and pumps over the geological Madison formation in Wyoming where they have been extracting natural gas and helium for more than 30 years. In this process, they have also been dumping CO2, which is also contained within the Madison formation, to the tune of about 300,000 car’s worth of emissions annually. The company was set to start construction in the summer of 2020 on a carbon capture and sequestration project that would have locked away enough CO2 to essentially zero-out the facility’s climate impact. In April, however, amidst falling share prices, the company announced that the project will be on hold indefinitely. The story here is as follows: Company finds a profitable process, company creates externalities (carbon pollution) through the process, company finds a way to mitigate the externality using technology and government programs (tax credits), economy plummets, project is tabled, and the company’s efforts toward climate mitigation are foiled. And Exxon is not simply going back to regular operations. In fact, not only are they not advancing their climate plan, but they are ramping up their core business through a pricey expansion of crude oil operations. The result will be sharp increases in their carbon emissions rather than significant reductions as a reaction to the pandemic-induced economic downturn.

As COVID-19 vaccines are deployed over the next 12-18 months, we will be glad to get “back to normal.” We would be wise, however, to consider whether the pre-COVID normal is exactly what we want to return to from a climate change mitigation perspective. If we return to normal levels of commuting, air travel, and fossil fuel use, we will have missed an opportunity to move climate trends in a positive direction and our friends in big cities will undoubtedly lose their newly-acquired views. Wouldn’t it be nice if some good came out of this pandemic? I hope we will attempt to embrace a new normal instead. Likewise, this is an opportunity for government to consider how the market has impacted business decisions and how COVID relief packages can be developed to promote and incentivize climate-positive actions.

Dr. Heather Farley is Chair of the Department of Criminal Justice, Public Policy & Management and a professor of Public Management in the School of Business and Public Management at College of Coastal Georgia. She is an associate of the College’s Reg Murphy Center for Economic and Policy Studies. For more information on the Reg Murphy Center, please visit www.ccga.edu/murphycenter .

Equity, Diversity, and Inclusion in Hiring. Part II: Doing the Work

In my last article for this column, I discussed systemic and institutional racism in organizational hiring and urged organizations to be wary of pitfalls such as quotas. As I stated in the last article, it’s no wonder why organizations may instinctually turn toward quotas when developing diversity and inclusion plans, but it’s a pitfall that could land an organization in muddy waters at best and the courtroom at worst. If we shouldn’t set aside positions for Black, Indigenous, and People of Color, what should we do? I committed to writing a part 2 that outlines some of the best practices in diversity, inclusion, and equitable hiring and to that end, I spent some time examining resources and approaches to improving diversity and inclusion in the workplace.

First, it’s important to recognize that hiring an individual from a certain demographic into a spot on your team does not a diversity plan make. Creating diversity on your team by using inclusive approaches is a method that is meant to build a group, not check off an individual’s box on an application. Viewing it in this way helps you avoid individual biases.

Next, don’t shy away from the idea that we all have biases and make judgements. It is part of our nature. That does not mean, however, we have to blindly accept these biases. Instead, talking about them within the organization and developing strategies to avoid hiring biases is a good first step. Likewise, discuss the ways in which diversity is a value within your organization and be sure this is explicitly included in job descriptions.

In terms of recruitment, ensuring that your post is getting out to a diverse pool of applicants may require that you evaluate your communication strategy and adjust as needed. For instance, advertising through social media or different professional organizations may help to broaden your reach.

As your organization reviews applications, you might consider building a search committee that includes both members of the department you are hiring for and external members who can help offer an outside perspective. Blind resume review is another way to avoid perpetuating bias. Remove names and dates of degrees before the committee considers the interview pool to avoid the implicit bias I outlined in the last article. Then, provide a rubric of key skills the committee can use to evaluate the qualifications of applicants.

Once a candidate is selected for interview, standardize the interview process and agenda to ensure equity. Focus on interview questions that are competency-based and focus on the outcomes necessary to be successful in the role.

Finally, once a candidate has been selected, evaluate your success. Take time to hear back from applicants about the process through survey or other methods and adjust your process based on feedback from those who experienced the hiring process.

Hiring is not a one and done process but an ongoing and evolutionary process that requires planning, evaluation, feedback and redesign. Try to avoid thinking of hiring as fixed, but rather use it to develop as an organization.

Dr. Heather Farley is Chair of the Department of Criminal Justice, Public Policy & Management and a professor of Public Management in the School of Business and Public Management at College of Coastal Georgia. She is an associate of the College’s Reg Murphy Center for Economic and Policy Studies.

Avoiding legal pitfalls in addressing organizational equity

I spent some time last month working with a non-profit organization that has been developing their Equity, Diversity, and Inclusion (EDI) plan. In light of the social justice issues that have gained prominence and public attention this year, the organization is seeking to improve their operations, mission, and hiring practices to ensure that they are not contributing to systemic racism. Quite simply, they are trying to “do better.” It is important work that needs to be done.

I realize the idea of systemic racism has become contentious for some, so before I get to my main point, I would like to take a moment to define what that term means and what it does not mean. Systemic racism, also called institutional or structural racism, is the processes, systems, and structures that create disadvantages for Black, Indigenous, or People of Color (BIPOC). Here are some examples to illustrate what this means. Statistically in the U.S., unemployment is about two times higher among blacks than whites. This holds true no matter what is going on in the economy as a whole and even when we compare similarly-qualified groups (college graduates of different races, for instance). Similarly, when you are applying for a job, research has shown that you are 50% more likely to get an interview with a “white sounding” name versus a “black sounding” name. Again, this holds true when all other factors (like qualifications) are held constant. This does not mean that those engaged in the processes have any particular racial motivation; in fact, people may not even be conscious of race in their decision-making, but the decisions themselves perpetuate racial inequality. There may be a perfectly rational reason or incentive to make these decisions, but the result is the perpetuation of disadvantage. 

So, knowing this, it is not surprising that many businesses and non-profit organizations are seeking to address these issues by intentionally bringing them into focus in their planning. In fact, addressing systemic racism isn’t anything new from a policy perspective – we have been grappling with it since the 1960s when Kennedy introduced the idea of affirmative action in an Executive Order.  Since then, the implementation of affirmative action has taken place in the courts rather than legislatures. In other words, as a policy, it has been refined through the legal system as opposed to the development of new laws.

Employment discrimination laws were introduced in the Civil Rights Act of 1964 through Title VII. The 1976 Supreme Court case, McDonald v. Santa Fe Trail Transportation Co., ruled that “discriminatory preference for any [racial] group, minority or majority” violates Title VII (employment discrimination). This extends to favoring minority employees over White employees as well. Throughout the 1960s and 70s, educational institutions, in particular, began using minority quota systems to improve minority admissions into schools. This was ruled illegal by the Supreme Court in 1978, but consistent and clear rulings on affirmative action have not been the norm from that point on. Two cases in 2003 and 2016 upheld the idea that race can be a consideration in hiring and admissions decisions, but designating spots or quotas is not. This is about the extent of the guidance on affirmative action and diversity/inclusion in hiring.

Interestingly, in talking with the non-profit I was working with, the approach they are taking in their EDI is to include quotas in their hiring to ensure that they have adequate BIPOC representation in the organization. They are hoping to create more diversity in the organization through inclusive hiring practices (necessary and admirable), but the tool they used throughout the plan was quotas (X% of people hired in this area will be BIPOC, for instance).

My warning to them, and to other CEOs and Executive Directors, is this: do not rush blindly into anti-discrimination initiatives that may result in violating anti-discrimination laws. While the work of affirmative action must happen to address systemic racism, organizations also need to be wary of violating existing law.

Now, if an organization or individual wishes to challenge these laws, they certainly could by taking cases to the court system. Otherwise, other methods will need to be employed as we navigate trying to improve systemic racism in our businesses and communities. The U.S. Equal Employment Opportunity Commission (EEOC) along with several organizational success stories offer some good guidance in this regard. I’ll take up the topic of effective, legal, affirmative actions in my next column and I hope it will be useful in both illuminating the legal landscape on this issue and helping to give organizations some ideas on how to “do better.”

Dr. Heather Farley is Chair of the Department of Criminal Justice, Public Policy & Management and a professor of Public Management in the School of Business and Public Management at College of Coastal Georgia. She is an associate of the College’s Reg Murphy Center for Economic and Policy Studies.

Millennials: It’s Time we Stopped “Waiting on the World to Change”

I am a millennial. Technically, I am what some people refer to as an “Xennial”; these are individuals in the micro-generation right between gen-X and Millennials who bridge the gap between strictly analog generations and digital generations. We have been described as having “both a healthy portion of Gen X grunge cynicism, and a dash of the unbridled optimism of Millennials” (Anne Garvey, 2015).

I was recently listening to a fellow-Xennial, John Mayer’s, 2006 song “Waiting on the World to Change” and was thinking about the lyrics. In the song, Mayer laments that Millennials are “misunderstood,” that we “feel like we don’t have the means to rise above and beat it,” and so we “keep on waiting on the world to change.” He ends by saying that “one day our generation is gonna rule the population.” Technically, John, we have reached “one day.”

This election year, Millennials (27% of eligible voters) combine with new voters in Gen Z (born between 1996 and 2002) will make up nearly 40% of the electorate. This is noteworthy not because it makes me feel special as a Millennial, but because it highlights an important phenomenon; the slow unfolding of a changing electorate. It’s a fascinating thing to watch in an election year, because it can mean that every election has the potential to be surprising and interesting depending on who actually shows up to the polls.

In years past, the Baby Boomers have been the demographic that matters most in an election. They are large in numbers, they have a longer life expectancy than any time in history, and they show up to vote. As recently as 2012, they made up half of the electorate and they vote consistently. As such, savvy politicians have spent a great deal of time ensuring that their messaging resonates with those born between 1946 and 1964. This generation will remain the leaders in expected voters in 2020, but Millennials and Gen Z are hot on their trail – in number at least. Their willingness to actually vote is unclear.

Gen Z, in particular, is going to be much more racially diverse when compared to the older electorate – they are comprised of 55% white and 45% nonwhite eligible voters compared to a 74% white Baby Boomer electorate. Younger voters are also far more likely to vote Democrat as we saw in the 2018 midterms where they voted for Democratic candidates almost three to one.

Those kinds of numbers should be very exciting for Democrats, except for one major problem – this population doesn’t show up to vote. Non-voters in the 2018 midterms were young and racially diverse. Only 11% of actual voters (as opposed to eligible voters) in 2018 were under 30 years of age. The same group who now have clear advantages in numbers, don’t exercise that advantage and so the impacts of the changing electorate remain slow.

Now for my anecdotal observations. I have taught and listened to students in this younger population for the last ten years in my classes. They consistently report that they haven’t really paid much attention to current events until they were forced to do so in college. They overwhelmingly get their news from social media, which of course comes with a whole host of problems in an election environment tainted by foreign interference via social media. They have good ideas, they are problem-solvers, and they know what they care about it when they see it, but they haven’t yet discovered their strength and potential as a democratic voting body. If they do in 2020, there will be significant changes on the horizon. But, if they continue to stay home and not vote, they will continue to “wait on the world to change.”

Dr. Heather Farley is a professor of Public Management in the School of Business and Public Management at College of Coastal Georgia and Chair of the Department of Criminal Justice, Public Policy & Management. She is an associate of the College’s Reg Murphy Center for Economic and Policy Studies. 

Presidential polling is not telling you what you think it is…

Recently the College of Coastal Georgia introduced a new Bachelor of Science in Data Science degree. Students in the program will learn through statistical analysis, computer programming, and mathematical modeling how to add value to data through analysis. In other words, they will learn how to produce consumable information. This is a highly valuable skill and will make these students very competitive in both the public and private sectors.

Most of us, however, find ourselves in the data consumption camp. Data and interpreted data come at us in large doses and very quickly. How we understand this information can, in turn, shape how we view the world. So, understanding how to be good data consumers is of great consequence.

In this week’s column, I want to explore one particular area of data consumption: Presidential polling numbers. Where Presidential candidates land in the polls has long been fodder for the media and political pundits. As voters, we often rely on this information to tell us how campaigns are going. The 2020 Presidential election cycle is no exception, particularly in light of virtual conventions, diminished rallies, and reliance on media coverage almost exclusively.

We know from the 2016 election, however, that polls are not necessarily great predictors of Presidential outcomes. In August of 2016, Hillary Clinton had an 8-point lead over Donald Trump (50% to 42%) among registered voters in some of the largest Presidential polls. Now, in August of 2020, major polls indicate a 9-point lead in favor of Joe Biden (51% to 42%). Prior to the 2016 election, the Biden campaign probably would have found this relatively strong lead comforting. But, we know that despite these almost identical numbers, Hillary Clinton did not win the election. Why? In short, because polling registered voters on a nationally-elected position like President has some caveats that must be considered.

Most importantly, the President is not elected by popular vote, but rather by an Electoral College. Indeed, Hillary Clinton did win the popular vote in 2016 with 2.9 million more votes than Trump, but that has never been the number that matters in a Presidential race. Only the state-by-state electoral counts will get you a win, and Clinton simply did not have those numbers in the “rust belt” states.

So, while polls can show us how voters on the whole are feeling about the candidates, they do not predict the outcome of the election in and of themselves. This was a major polling downfall in 2016; there was significant national polling, but anemic battle-ground state polling. If you want a more predictive picture of the outcome in 2020, you would do better to follow local polling in states where Trump won by 5 points or less: Florida, Georgia, Michigan, North Carolina, Pennsylvania, and Wisconsin.

Next, unless you have the time to dig down into who actually responded to a poll, it can be hard to know whether the poll is really representative of the population. In polling in general, for instance, there often is an overrepresentation of certain populations that are more likely to respond such as college-educated respondents, older respondents (who have a land-line phone), English-speaking voters, and white voters to name a few. The results of these polls, therefore, may not be as representative as we would like.

Finally, there are a few bias issues that are not readily apparent in a polling news headline. “Social desirability bias” is the idea that people may simply lie to a pollster because they think doing so will reflect well on them. In other words, a respondent may not want to tell the stranger on the phone who they are voting for due to a perceived fear of judgment. There can also be leading questions or biases within the way a poll is delivered. For example, questions can be framed in such a way that leads a respondent toward a certain answer.  Another example of a bias issue in polling is the fact that many more people will say they intend to vote than actually vote. There are a number of reasons why this happens, but the result is that a poll suggests that likely voters are leaning in a certain direction, but the outcome turns out quite different.

As we enter party convention month, these specifics of polling will be something to keep in mind. There will likely be a significant uptick in national polling, but unless you are interested in digging into the details of those polls, I recommend looking elsewhere for your data. My hope is that pollsters were stunned enough by the misinterpretation of the 2016 data that they will focus more on state-level, representative (as much as that’s possible) polling.

Dr. Heather Farley is a professor of Public Management in the School of Business and Public Management at College of Coastal Georgia and Chair of the Department of Criminal Justice, Public Policy & Management. She is an associate of the College’s Reg Murphy Center for Economic and Policy Studies.

Is Political Party a Stronger Indicator than Ideology in the COVID Era?

This summer, I have been team teaching a Global Issues class on COVID-19 with a multidisciplinary team of faculty at the College of Coastal Georgia. We have, along with our students, been exploring the COVID-19 pandemic from every angle with professors from across the College’s disciplines: psychological impacts, economic impacts, the biological origins of the virus, challenges in health informatics, and many more. My lecture for the class this week focuses on the socio-political changes and challenges that have emerged in the midst of the pandemic. In simpler terms, what’s going on with the government, laws, policies, and social norms in our American society right now? One trend we can observe is different attitudes toward government according to one’s political ideology.

When I am talking to students about political ideology, I try to make it clear that one’s ideology is not the same as one’s political party affiliation. Ideology is a spectrum ranging from conservative to liberal and statist to libertarian; political parties tend to fall within the ranges of these different ideologies, but not perfectly. When analyzing or predicting the way certain parties might approach a policy, however, we can generally look to the liberal/conservative ideological positions to get a good idea of what to expect. What I found in researching my Global Issues lecture topic, however, is that attitudes about how well the federal government is doing during the COVID-19 crisis is not following political ideology, but rather party loyalty.

In 2010, under the Obama administration, Pew Research Center asked Americans in a large-scale survey how they felt the Federal Government was doing. Then, in May of 2020 under the Trump Administration, the progressive thinktank Data for Progress asked the exact same questions in order to generate comparisons. We would predict that in general, conservatives would favor smaller government and more state control. Likewise, we would predict that liberals would favor greater big-government intervention. Interestingly, the surveys revealed something different.

When liberals and conservatives were asked “Is the federal government having a positive or negative effect on the way things are going in the country,” there was a major reversal on the part of conservatives. While in 2010 77% of conservative respondents said the effect of the federal government on the country is negative, this dropped to just 32% in 2020 while the view of liberals remained stable at around 55%. Similarly, when asked “All in all, how good a job does the federal government do running its programs,” conservatives had a large 27-point drop where liberals had just a 10-point increase. Finally, when asked what level of government they trusted more to handle he pandemic, 37% of liberals trusted the federal government more than their local government versus 64% of conservatives. In other words, while we would expect a certain outcome based on traditional ideological stances – liberals favoring big government, conservatives favoring small government – we are seeing something different that speaks more to party affiliation and loyalty.

There could be a variety of reasons for this outcome, but what seems clear is that respondents, and especially conservative respondents, are equating the federal government with the President. Their support for that institution, therefore, seems to depend much more heavily on who is in office than on their attitude toward national government in general. The effect is that policy development and analysis cannot rely solely on ideological predictions. Instead, consideration of party loyalty has to be accounted for as well, which is a much more challenging and fluid metric.

Dr. Heather Farley is a professor of Public Management in the School of Business and Public Management at College of Coastal Georgia and Chair of the Department of Criminal Justice, Public Policy & Management. She is an associate of the College’s Reg Murphy Center for Economic and Policy Studies. 

Race, Inequity, and Health –Wicked Problems Require Policy Innovations

We are living in an unprecedented moment in our history: COVID-19, racial tensions and a push for restructuring an anti-racist society, social isolation and distancing, economic gaps and inequities. Well, if not unprecedented, at the very least we are seeing a stunning confluence of events and tensions in our political, societal, and economic systems that leaves us thinking about really big questions.

Academics would call many of these issues wicked problems – social or cultural problems that are difficult or impossible to solve because we either have: 1) incomplete or contradictory knowledge, 2) too many conflicting people or opinions involved, 3) a large economic burden, or 4) highly interconnected problems. My colleague Don Mathews touched on this in the June 17th, 2020 column in his discussion of race and poverty from an economic perspective. Race and poverty are linked to other issues like access to education, nutrition, healthcare access, and so on. There is no definitive formula for figuring out these questions and the solutions are centered on improvement rather than an end state.

The good news is that history and research can provide guidance to reach a state of improvement. I recently read a study by Jason Coburn et al. (Health in All Urban Policy: City Services through the Prism of Health, 2014) that examined inequality factors and health; another wicked problem. It sought to explain some of the determinants of health and social equity. It also highlighted a policy strategy called “Health in All Policies (HiAP)” that ensures that policy making outside the health sector addresses the determinants of health and social equity. There is an explicit focus on equity and participation by government, experts, and communities.

The Coburn article made me think about the COVID-19 pandemic and the disproportionate impact on people of color. The same determinants explained in the article and by the World Health Organization – economic policies and systems, development agendas, social norms, social policies and political systems – are creating conditions that lead to disproportionately higher death rates in people of color due to COVID-19.

Pre-pandemic realities that limit access to health and wealth for people of color are also leading to higher death rates during the pandemic. For instance, higher rates of underlying conditions (related to less access to quality healthcare), lower access to transportation, and disproportionate representation in occupations that are now frontline jobs, have all led to this unequal share of deaths due to the pandemic.

This wicked problem is a systemic issue. As a result, solutions have to be tailored to address the system. For example, because predominantly African American communities in New Orleans had lower access to personal transportation, Louisiana changed their testing strategy from drive-through testing sites to targeted testing within these communities. This is but one of a set of structural issues related to the pandemic, but it illustrates ways that our public health organizations and states can improve outcomes for racial and socioeconomic groups that are being impacted in unimaginable ways by simply meeting basic needs.

When you can’t access food, private spaces to self-isolate, transportation, quality healthcare, or outdoor spaces away from others, your prospects for successful recovery from COVID-19 shrink significantly. As we grapple right now with ways to combat systemic racism, we should also be considering ways that the system can be changed to generate better outcomes for those communities that are most vulnerable during this ongoing pandemic. The HiAP strategy provides one such option by “integrat[ing] community knowledge and health equity considerations into the agendas of policymakers who have not previously considered health as their responsibility or view the value of such an approach” (Coburn et al. 2014). Tackling these wicked problems is going to require new thinking, but fortunately we have some tested strategies and ideas to guide us along the way.

Dr. Heather Farley is a professor of Public Management in the School of Business and Public Management at College of Coastal Georgia and Chair of the Department of Criminal Justice, Public Policy & Management. She is an associate of the College’s Reg Murphy Center for Economic and Policy Studies. 

Elections and Pandemics – Lessons Learned from the Past

This column has been full of COVID-19 analysis over the last couple of months. As academics, it is sort of in our nature to want to analyze something from every possible angle, so forgive us this preoccupation. But, as I promised in an earlier column of mine, I wanted to start thinking about this year’s Presidential election and the electoral politics surrounding it – some perspectives on the history, data, and political machinations taking place.

Presently, we are facing a very uncertain autumn and an unusual election season. Many people are turning to previous pandemics for guidance or lessons learned. While the details of those pandemics, like any historical event, have gotten a bit muddled, ultimately, they can offer some insights as to how we might approach our own lives right now. This week, I want to look at the 1918 midterm elections and how the United States pulled it off in the midst of one of the deadliest pandemics in history.

The first relatively mild wave of the flu swept in during the spring of 1918 followed by a second stronger wave that emerged in September. In the month of October, 195,000 Americans perished from the flu. But, what was going on other than the pandemic at the time? Politically, Woodrow Wilson was in an unenviable position. He and his fellow Democrats were attempting to keep control of Congress in the thick of World War I. In at least eight states, alcohol prohibition was on the ballot and suffragists were trying to build on the momentum of the first twelve states they had won to date. The stakes were high not only for national candidates, but also for state politics. So, how do you implement the Constitutional duty of holding elections during such rough waters for the nation?

Just like the 2020 election season, campaigning had to be planned with strict social distancing and quarantine rules in place. This meant there could be no rallies and campaigning had to take place via alternative communication methods like newspapers and campaign literature. Today, of course, we have widespread television and internet media, which offers rapid distribution of information and tremendous opportunity for both diverse opinions and the spread of misinformation. While plenty of conspiracy theories have popped up during COVID-19, even then some candidates suggested that public health officials were conspiring to limit election turnout calling it a “Republican quarantine against Democratic campaign speeches” (see New York Times Oct. 22, 1918).

Voting, of course, is another issue. Under the purview of local and state governments, the 1918 midterms looked quite different depending on where you lived in the US. Voting ranged from closed polls to strict social distancing guidelines to mandatory mask-wearing. There was no discussion of postponing the election. The result of these measures was a significant drop in voter turnout. One analyst in the Election Law Journal suggested that when controlling for loss of potential voters due to WWI deaths, the flu accounted for a 10% drop in voting with approximately 40% total voter turnout. Six days after the election, the armistice ended WWI, people took to the streets to celebrate, and a new surge if flu cases was reported across the country.

A democracy is only as strong as its participation. That is the definition of democracy: by the people. The job of our state election boards, therefore, will be to ensure that turnout does not suffer in the same way it did during the 1918 pandemic.

One way to allow people to stay home and still vote is mail-in ballots. Interestingly, while I was doing research for this article, I came across no evidence of mail-in voting in 1918. It seems this practice did not emerge until the 1980s. This is currently a political hot-topic, so I wanted to address it here. Statistically, voter fraud in the case of mail-in ballots is quite low and participation is high. I know you’ve heard otherwise, but the data simply do not support the idea that mail-in ballots will lead to rampant voter fraud. There are five states that currently do all mail-in voting and there is no evidence in these states of statistically significant fraud. This is likely due to their best practices: voter signature, signature matching, laws limiting ballot harvesting, and ballot tracking via bar code. Additionally, a 1996-2018 study by Stanford’s Institute for Economic Policy Research found that the partisan effect (ie. does mail-in voting help one party or another) was neutral but that overall average turnout rate increased modestly.

If COVID 19 threatens a possible 10% drop in turnout as it did during the 1918 pandemic, I would argue that even a modest increase in participation would be worth pursuing. Mail-in voting is one option, but election officials will have to consider a range of options to ensure the process is open and accessible to all eligible voters while maintaining public health and safety.

Dr. Heather Farley is a professor of Public Management in the School of Business and Public Management at College of Coastal Georgia and Chair of the Department of Criminal Justice, Public Policy & Management. She is an associate of the College’s Reg Murphy Center for Economic and Policy Studies.