A growing body of research has demonstrated the impacts of remote work on where people live. In 2021, economists Arjun Ramani and Nick Bloom coined the exodus from expensive city centers to surrounding suburbs and exurbs “The Donut Effect” due to how changes in housing prices appeared on a map. As research in this area continues to grow, it’s important to recognize one fact: the geography of remote work is both heterogeneous and still evolving. To this end, this short analysis will illustrate how housing prices have evolved across regions from the start of the pandemic through the most recent data available through April 2023. 

Nearly two years into the remote work revolution, it’s easy to feel that a lifetime has passed. However, the reality is we are just at the beginning of seeing the impacts of remote work. From working habits to commuting patterns, there is an undercurrent of change. This is especially true when we look at the geographical implications of remote work. For the first time, remote work allowed many people across the country to see a life in which the location of their job and where they live did not have to be one and the same. Initially explored just six months into the pandemic in our Remote Workers on the Move report, the research found that even early, remote work affected planned migration in the U.S. But what about two years later? Using a new survey of over 23,000 people in the U.S., Upwork finds that remote work continues to influence Americans’ plans to move. These migrations will likely impact economic geography in the U.S. Furthermore, a review of the existing evidence on the geographical impact of remote work shows that change is already underway.

As employers increasingly say they will let many workers stay remote, and as many employees continue to insist that they do, the debate around remote work has evolved. It is no longer a discussion of whether significant levels of remote work will be with us permanently, but what the impacts will be. While short-run considerations focus on how practical considerations like how office policy will change and where people will move, a bigger long-run consideration must be made: what will happen to U.S. workers competing in a global remote labor market? In this paper, I use data from Upwork, the world’s largest global remote labor market, to shed light on how things already look, and how they will look, for U.S. workers. The results show that overall, U.S. workers earn a pay premium in global labor markets.

Business dynamism in the United States has been falling for decades, and was exacerbated by the fact that the startup rate fell during the Great Recession and never fully recovered. Yet in the aftermath of the pandemic, new business formation has surged. The data shows that much of this is in small businesses and self-employment. So, what is driving this? In this analysis, we will argue that online platforms, like Upwork, are unlocking a wave of entrepreneurship and are a force for more dynamism in an economy that greatly needs it.

2020 has been a year of profound change for businesses and professionals shaped by the global pandemic. As we approach the new year and reflect on the last nine months of the global shift to remote work, many may wonder what this experience will mean for the American workforce going forward. To better understand the impact of the pandemic on the future of work, we surveyed 1,000 hiring managers about the current state of hiring, their sentiment toward a remote workforce, and their future staffing plans.

Does remote work limit people’s opportunities to socialize and does this impact businesses? We conducted two surveys to shed light on this question. Using these results and various other data sources, we illustrate where people plan to work after the pandemic and better understand how remote work and working in the office affect socialization.

The impact of COVID-19 on the way that we work arguably represents the most drastic and rapid shift to the global workforce that we have seen since World War II. This paper investigates the long term impacts of this remote work experiment and what we can anticipate in the future, based on the direct impact that COVID has had on hiring, sentiments around remote work, and plans moving forward. The analysis uses two waves of survey data: one fielded prior to the pandemic in November 2019, and the other fielded during the pandemic in April 2020. The surveys polled a combined 1,500 hiring managers which includes executives, VPs, and managers- so the results reflect the views and plans of those with direct influence over businesses’ remote work decisions. In short, these results provide before and after snapshots of how relevant decision makers view the remote work experiment so far and how it has affected their plans. The results suggest that the remote work experiment has gone better than expected for hiring managers. The perceived benefits of working remotely are causing businesses to significantly increase plans for remote hiring in the future, which will cause an acceleration in the already upward trend of greater remote work.

We report the results of a nationally-representative sample of the US population during the COVID-19 pandemic. The survey ran in two waves from April 1-5, 2020, and May 2-8, 2020. Of those employed pre-COVID-19, we find that about half are now working from home, including 35.2% who report they were commuting and recently switched to working from home. In addition, 10.1% report being laid-off or furloughed since the start of COVID-19. There is a strong negative relationship between the fraction in a state still commuting to work and the fraction working from home. We find that the share of people switching to remote work can be predicted by the incidence of COVID-19 and that younger people were more likely to switch to remote work. Furthermore, states with a higher share of employment in information work including management, professional and related occupations were more likely to shift toward working from home and had fewer people laid off or furloughed. We find no substantial change in results between the two waves, suggesting that most changes to remote work manifested by early April.

Remote work is undoubtedly on the rise, especially as companies adapt to the changing times of COVID-19, but what impact will this have on the broader economy? In this analysis, we examine the potential for remote work to reshape the geography of opportunity in the U.S. Using a variety of data sources, we provide evidence that remote work is already helping to send economic activity from the top 15 most expensive parts of the country to less expensive parts. When this happens, we show that it can be mutually beneficial: higher earnings for independent professionals and lower cost for businesses than in their local labor markets. In addition, both sides will likely benefit from a variety of under-discussed benefits beyond pay.

REFE

As businesses consider reopening offices, many Americans are thinking about what work was like before COVID and, more specifically, how long it took them to get there. One of the most significant benefits of remote work is the lack of a commute. From both a time-saving and productivity standpoint, a lack of commute can improve a personͬs overall happiness and work͡ life balance. But how much time can remote work actually save? And where do workers who can go remote stand to benefit most by going remote? Through this analysis, we explore these questions and find that the potential commuting benefits of remote work are significant across the U.S. Illustrating the potential for these gains, we find that since the onset of COVID-19, the economic benefit of remote work from lower commutes has been $90 billion.

More than half a year into the pandemic, remote work continues to be a reality for businesses across the country. Even as stay-at-home orders and lockdown measures have eased, many professionals are still working from their homes. This persistence, coupled with findings from early survey results, suggests that remote work is here to stay. While remote workers are already experiencing the direct impacts of this, with fewer commuters and fewer meetings, there are also early indicators of some larger, indirect effects of remote work. Perhaps the most significant of these effects is around the ability to access job opportunities far beyond one’s local labor market. In this analysis, we will explore how the ability to work remotely has impacted where people plan to live.

2020 has been a year of profound change for businesses and professionals shaped by the global pandemic. As we approach the new year and reflect on the last nine months of the global shift to remote work, many may wonder what this experience will mean for the American workforce going forward. To better understand the impact of the pandemic on the future of work, we surveyed 1,000 hiring managers about the current state of hiring, their sentiment toward a remote workforce, and their future staffing plans.

Advancing technology is unlocking great potential in remote work opportunities by making it increasingly easy for work that used to be done in person to now be done remotely. Yet these changes have led some researchers to worry about the offshoring of U.S. jobs. In one influential estimate from 2007, economist Alan Blinder projected that a quarter or more of U.S. jobs were at risk of being offshored. In this report, we take a look at the data from the decade-plus since this warning was issued and find that the techno-pessimism was misplaced. Instead of being offshored, the types of work predicted to be at risk of offshoring are increasingly being performed remotely by workers within the U.S.

Freelancing’s direct impact on the economy is close to $1 trillion, which at nearly 5% of U.S. GDP is comparable to that of a major industry like the information sector. The flexibility of the freelance lifestyle means that its value goes beyond its economic footprint. Freelancing does not describe one way of working but rather a wide range of activities. While skilled services are the most common type of work, it ranges from highly-skilled professionals freelancing full time to those occasionally selling goods online.

Estimates of the size of the freelance economy come to significantly different conclusions, ranging from some estimating one in ten workers participate to one in three. Using both Bureau of Labor Statistics (BLS) and Freelancing in America (FIA) data, we show that one major reason why there is such a discrepancy in estimates is due to how occasional freelancers are counted (or not). This research compares estimates, examining complexities in counting caused by varying work frequency among different types of workers (such as the self-employed and multiple job holders).

A wage “mystery” has puzzled economics commentators for several years: If unemployment is so low, why has wage growth not picked up? This article will argue that there is no puzzle when the right measures are used. The problem with how wages are measured is that the most commonly used measure is biased over the business cycle. The problem with how labor slack is measured is that the magnitude and depth of the Great Recession led many workers who could and would work again to exit the labor force entirely. As a result, many workers relevant to labor market slack were no longer being counted as unemployed, making the unemployment rate a poor gauge of labor market slack.

Research on the effect of an aging population on economic growth has tended to focus on labor force participation and the dependency ratio, and the limited work that has examined the effect of aging on productivity remains inconclusive. This analysis contributes to the aging and productivity literature and finds a strong negative effect of aging on productivity using both state-industry aggregate data and matched employer-employee microdata. The aggregate data show a clear relationship between an older workforce and lower productivity at the state-industry level, in both cross-section and panel models. The results are confirmed using employer-employee linked data from private sector human resource company ADP that show having older coworkers reduces an individual’s wages. Robustness tests include three-digit ZIP code geographic fixed effects and firm fixed effects for a sample of large nationwide firms. The results suggest that between a quarter and full percentage point of the slowing in annual productivity growth in recent years may be due to aging, an effect that is likely to persist for the next decade.

In December 2015, the Federal Reserve raised interest rates above the zero lower bound for the first time in seven years. Over the next 2½ years, six more hikes occurred, bringing the target range of the federal funds rate to 1.75% to 2% by June 2018. Although each hike has come with considerable debate both within and outside of the Fed, there has been little attempt to look back with hindsight and data to judge whether these decisions appear correct in retrospect. This analysis will provide that retrospect and argue that the Fed in fact raised rates too quickly.

In this article we causally link the effects of population growth to firm startups. We attempt to rule out endogeneity in multiple ways. First, we show that the effect of population in a fixed-effects panel is robust to the inclusion of employment growth, which is the most plausible mechanism through which startup rates would cause population growth. Second, we utilize an instrumental variable for population growth based on metro-to-metro migration rates from Howard (2017), which creates a proxy for annual migration into a specific metro area that is not subject to reverse causality by using historical migration patterns combined with annual changes in migration flows between other metro areas. Finally, we utilize dynamic panel models. Overall, we find a robust and consistent effect of population growth on startup rates. The effect appears to operate through the working-age population, consistent with labor supply rather than demand.

This analysis investigates the relationship between population growth and inflation. Panel models demonstrate a strong association between population growth and inflation in both cross-country data and across a sample of U.S. metro areas. The metro area results are highly robust, including an instrumental variable approach and long-run models using decadal changes over 90 years of data. The metro area analysis suggests that the housing market is the main mechanism through which population growth affects inflation, likely because of regulatory and physical constraints that keep land and housing relatively inelastic in many places. There is suggestive evidence that the relationship between population growth and inflation is nonlinear, with population declines having a stronger effect than population growth. This is consistent with relatively permanent housing stock that declines only slowly in response to declining population. Overall, these results suggest that slowing population growth can be a headwind for inflation and help explain why inflation has remained stubbornly weak in some places.

This study investigates the relationship between the health of a population and the health of an economy using a new health metric, the Blue Cross Blue Shield (BCBS) Health Index. The Health Index captures the relative health of nearly every county in the U.S. using rigorous statistical analysis and health insurance data from millions of members.Overall, the BCBS data clearly indicate that healthy populations are related to strong local economies. Where populations are healthier, we observe lower unemployment, higher income, and higher pay. Moving from a county of average health to the 99th percentile is associated with an increase in average annual pay of $5,302 and a 0.6-percentage point decline in the unemployment rate.

The real trade-weighted value of the U.S. dollar has been on a tear in recent months, rising 10% over the year through January to its highest level since 2003 (see Chart 1). Paradoxically, while this is being driven by a stronger U.S. economy, it is also likely hurting some parts of the economy. Given that there is little reason to expect the dollar’s run to end soon, it is important to understand which parts of the economy are being hurt and which are not. To understand this, sensitivity to the dollar is computed for industries and for metro areas using detailed employment data. Exploring the variation of sensitivity by industry and geography can illustrate why some metro areas and industries may be hurt while others are helped by a strong dollar.

Uncertainty, always a potential impediment to growth, has been higher than normal during this business cycle. This has had economic costs, but heightened uncertainty cannot be blamed each time the economy hits a soft patch, particularly during an election year.

Mexican immigration to the United States declined precipitously in the wake of the Great Recession and has continued to fall in subsequent years, resting at lows not seen since the start of mass Mexican immigration to the U.S. in the 1940s. Indeed, in five of the past six years, the number of return migrants to Mexico has exceeded those bound for the U.S. What explains the steep fall in Mexican immigration, and will it persist?

This article describes the Moody’s Analytics new estimate of U.S. household formation, which combines multiple data sources to accurately capture both long-run and short-run trends. In addition, a new house- hold forecast is described that has been developed using these data. The forecast calls for household formation to improve in the near term because of demographic changes and a stronger labor market.

This paper assesses the macroeconomic consequences of presidential candidate Hillary Clinton’s proposed economic policies. These include her policies on taxes and government spending, foreign immigration, and the federal minimum wage.

This paper examines the implications of sticky rents on the measurement of owner-occupied housing in the Consumer Price Index (CPI). I argue that market and not average rents are the most theoretically justified measurement of owners’ equivalent rent (OER), and that the current measurement of rental inflation using average rents is methodologically incorrect. A new data source is used to construct a market rent measure to compare to the existing CPI measure of owner-occupied housing inflation for the Baltimore/Washington D.C. CMSA. The results show that market rents reflect housing market turning points sooner, and show a larger post-housing bubble decline in rents. In addition, market rents are shown to forecast overall inflation better than average rents. The results suggest that switching to market rents may allow the Federal Reserve to be more responsive to housing bubbles.

In September, the U.S. unemployment rate dipped below 6% for the first time since 2008, fueling debate about whether the U.S. economy is approaching full employment—the level beyond which the economy overheats and inflation begins to accelerate. This estimate of unemployment, along with alternative unemployment rates and labor force participation, is based on a representative survey. The BLS determines an individual’s labor market status using their answers to survey questions about their current employment condition and their job search or lack thereof. Economic reasons include: beliefs that no work available in the area of expertise; could not find any work; lacks necessary schooling/training; employers think too young or too old, and other types of discrimination. Noneconomic reasons include: cannot arrange child care; family responsibilities; in school or other training; ill health; physical disability; transportation problems; and other.

Economists have been puzzled by the counterintuitive trend over the past several years in which the U.S. labor market has tightened but wage growth has been mediocre, at best. This paper first looks at the unemployment rate as a measure of labor market slack and finds that is not used this cycle. Finally, the risks are reviewed regarding the possibility that policymakers could make a misstep if they put too much stock into the idea of pent-up wage deflation.

REFER DOCUMENT

Prediction markets are important information-aggregation tools for researchers, businesses, individuals, and governments. This paper provides an overview of why prediction markets matter, how they are regulated, and how the regulation can be improved. The value of prediction markets is illustrated with discussions of their forecasting ability and the characteristics these markets possess which give them advantages over other means of forecasting and information aggregation. The past, current, and future regulatory environments are surveyed.

The Pennsylvania Legislative Budget and Finance Committee (PA-LBFC) engaged Econsult Solutions, Inc. to analyze the current condition of casino gaming in Pennsylvania, as well as the future gaming environment as a whole.

Longer, dissertation version of Sticky Rents and the CPI for Owner Occupied Housing.

This article describes geocode and travels time, two commands that use Google Maps to provide spatial information for data. The geocode command allows users to generate latitude and longitude for various types of locations, including addresses. The traveltime command takes latitude and longitude information and finds travel distances between points, as well as the time it would take to travel that distance by either driving, walking, or using public transportation.