The Regional Side of the Story: K‑Shaped Pattern in Region, Wider Gap in Gas Spending
Rajashri Chakrabarti, Thu Pham, Beck Pierce, and Maxim L. Pinkovskiy
In this post, we use the inaugural release of our regional consumer spending indicators to ask whether these patterns hold for a significant portion of the Second District, and how regional spending patterns by income have been similar to or different from the national patterns we documented earlier. We find similar K‑shaped patterns in both retail and gas spending in our region as we do in the nation, with the K‑shaped pattern in gasoline in response to the recent gas price shock being more pronounced in the region.
Explaining the K‑Shaped Economy: What’s Behind the Divide?
Rajashri Chakrabarti, Thu Pham, Beck Pierce, and Maxim L. Pinkovskiy
In our companion post, we used a new module of our Economic Heterogeneity Indicators (EHIs) to shed light on how recent retail spending growth has been driven by high-income households. This fact is consistent with the popular press’s idea of a “K-shaped economy” in which higher-income households experience faster growth in spending than lower-income households. In this post, we dive deeper into the reasons behind this divergence by analyzing for which goods this trend holds true and ask whether it can be explained by changes in wages, inflation, or wealth. We find that, since 2023, wealth has increased the most for high-income households, while inflation has risen the most for low-income households, with both factors helping explain the fact that real retail spending rose the most for high-income households. In contrast, earnings display a more mixed pattern, though earnings of the highest earners have grown more rapidly than earnings of the lowest earners.
Tracking the K‑Shaped Economy: Who’s Driving Spending?
Rajashri Chakrabarti, Thu Pham, Beck Pierce, and Maxim L. Pinkovskiy
Aggregate real consumer spending has risen solidly since 2023. However, it is less clear how widely shared this improvement has been across all segments of society. This is important because systematic heterogeneity may mask the dependence of aggregate growth on a relatively small group of households and thus conceal macroeconomic risks. In this post, we use consumer spending data recently added to the Economic Heterogeneity Indicators (EHIs) and find that retail spending growth has been driven by high-income households—those earning more than $125,000 per year. In the popular press, the phenomenon of higher-income households growing at a faster rate than lower-income households has been referred to as the K-shaped economy. We find that consumption has exhibited a K-shaped economy since 2023, although not in the pre-COVID period or during the post-COVID recovery.
A New Dataset for Consumer Spending in the New York Fed EHIs
Rajashri Chakrabarti, Thu Pham, Beck Pierce, and Maxim L. Pinkovskiy
We are enhancing our set of Economic Heterogeneity Indicators (EHIs) by adding a set of metrics on consumer spending with data presented by income, education, race and ethnicity, age, and urban status. The data will help track the evolution of aggregate behavior by analyzing the spending of specific groups in a more timely manner than is possible using public surveys.
The College Economy: Educational Differences in Labor Market Outcomes
Rajashri Chakrabarti, Thu Pham, Beckett Pierce, and Maxim Pinkovskiy
It is intuitive that workers with higher levels of education tend to earn more than workers with less education. However, it is also true that workers with more education are much more likely to be employed, and this employment advantage of education has, if anything, grown in recent years. In this post, we document profound differences in labor market outcomes by educational attainment. Drawing on the Economic Heterogeneity Indicators, we find that the gap in employment rates between workers who have completed college and workers who have not is 12 percentage points—which is larger than the employment gaps between workers of different races/ethnicities or between men and women—and is wider than the pre-pandemic gap. Moreover, most of this gap and its recent movements are driven by differences in labor force participation rates rather than by differences in unemployment rates. Fostering higher labor force participation of workers without a college degree thus would be quite helpful in promoting maximum employment.
Veterans in the Labor Market: 2024 Update
Rajashri Chakrabarti, Dan Garcia, and Maxim Pinkovskiy
Veterans constitute a significant segment of the male labor force, and understanding labor market disparities between veterans and non‑veterans is an important component of studying disparities in the economy as a whole. In a previous Liberty Street Economics post, we have shown that even relative to a group of comparable non-veterans, veterans have lower employment and labor force participation rates. One year later, we see that veterans continue to experience lower labor market attachment and the employment gap has widened, though the earnings gap has closed.
Recent Disparities in Earnings and Employment
Rajashri Chakrabarti, Kasey Chatterji-Len, Dan Garcia, and Maxim Pinkovskiy
The New York Fed recently released its latest set of Equitable Growth Indicators (EGIs). Updated quarterly, the EGIs continue to report demographic and geographic differences in inflation, earnings (real and nominal), employment, and consumer spending (real and nominal) at the national level. This release also launches a set of national wealth EGIs (which will be examined more closely on Liberty Street Economics early next year). Going forward, EGI releases will also include a set of regional EGIs, which will present disparities in inflation, earnings (real and nominal), employment, and consumer spending (real and nominal) in our region. Drawing on the just released EGIs, in this post, we present recent gender gaps in the labor market at the national and regional levels. We provide a picture of how gender wage and employment disparities have evolved since the pandemic, examining and contrasting gaps at the national and regional level. We find that the gaps between the employment rates and earnings of men and women have declined steadily following the pandemic, but have declined perceptibly more so in our region than in the nation.
The EGIs: Analyzing the Economy Through an Equitable Growth Lens
Rajashri Chakrabarti, Dan Garcia, and Maxim Pinkovskiy
Inflation remains elevated, labor markets are close to the strongest they have been, real consumption is up year-over year, but all of these observations are with respect to averages. Behind these macroeconomic trends can be widely varying experiences across different demographic and socioeconomic groups that make up our society. To provide researchers, practitioners, and the public with timely, regularly updated and comprehensive answers to these questions, we launched the Equitable Growth Indicators (EGIs)—a new tool to help foster the evolving discussion about economic inequality and equitable growth. To illustrate the utility of the EGIs, we provide examples of some striking differences in trends captured in the May release of the EGIs on inflation, real earnings, and real spending. More heterogeneity analysis and data are available at nyfed.org/egi.
Do Veterans Face Disparities in the Labor Market—And What Accounts for Them?
Rajashri Chakrabarti, Dan Garcia, and Maxim Pinkovskiy
We continue our series on military service and consider veterans’ earnings and labor market outcomes. We find that veterans earn more than 12 percent less and are 4 percentage points (18 percent) more likely to be out of the labor force than comparable nonveterans. Interestingly, accounting for veterans’ differences from comparable nonveterans in terms of education and disability status largely explains these labor market differences.
Do Veterans Face Disparities in Higher Education, Health, and Housing?
Rajashri Chakrabarti, Dan Garcia, and Maxim Pinkovskiy
Veterans are an understudied group that forms an important part of the fabric of American society and that constitutes a significant segment of the population. In the first post of this two-part series, we will investigate how the outcomes of veteran men–in educational attainment, health, and housing–differ from those of comparable men who did not serve in the military. Looking only at men, for reasons described below, we find that relative to nonveteran men with a high school degree and a similar distribution of demographic and geographic characteristics, veterans are 7 percentage points less likely to have a college degree and are over 50 percent more likely to experience a disability. Veterans are also somewhat likelier to rent a home than to own and, as renters, pay a lower average rent, suggesting they experience lower quality housing or live in worse neighborhoods.
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