Postwar US labour market data reveal a significant secular decline in the employment and wage gaps between men and women. This column quantifies the implications of this shift for the US macroeconomy. Using a time series model that maps empirical trends in data onto underlying structural forces, the authors find that gender-specific labour market trends are responsible for a sizable share of the overall trend increase in GDP and labour productivity in the 1970s, 1980s, and 1990s, as well as the slowdown in GDP growth over the last 20 years.
Women’s increased labour market participation is one of the fundamental changes observed in modern economies during the last century. Consider, for example, the US labour market data in Figure 1. In the 1960s, the employment rate for women in the US was less than half the employment rate for men. But the female-to-male employment ratio increased steadily until the late 1990s, before converging to around 85% in recent decades. Gender differences in wages display a similar picture. Although women’s hourly wages stayed relatively flat at 60% of men’s wages until the mid-1970s (despite a substantial employment catch-up during that period), they have since outgrown male wages at about the same pace as the additional growth in female employment, resulting in a major wage convergence between genders. In total, more than 60% of the female-to-male employment gap, and about half of the female-to-male wage gap, disappeared before stabilising around 2000. It is hardly a coincidence that Goldin (2006) refers to a “quiet revolution” when describing these trends.
Figure 1 US gender differences in employment and wages
Notes: The employment (wage) gap is defined as the female-to-male ratio in employment (wage) rates. Based on data from the Current Population Survey, the US Census Bureau, the Bureau of Labor Statistics, and authors’ calculations.
One open question is whether gender convergence in employment and wages resulted in spillovers to the broader US macroeconomy. On the one hand, talent may have been significantly misallocated when only a minority of women participated in paid work, as suggested by Hsieh et al. (2019). On the other hand, an increase in female employment may have crowded out male employment, thus limiting the macroeconomic effects of the gender convergence, as discussed by Fukui et al. (2023).
In a recent paper (Bergholt et al. 2024), we estimate a structural vector autoregressive model with common trends and use it to quantify the spillover of gender-specific labour market trends to the US macroeconomy. The model can be seen as a multivariate, unobserved components model in which the variables enter in levels, and transitory and permanent components in the data are disentangled from each other. As an example, our model decomposes observed GDP dynamics into a cyclical and a permanent component. In turn, the permanent component – understood as the empirical or reduced-form GDP trend – is a function of underlying, structural drivers such as productivity, automation, labour supply, and two gender-specific trends. However, the mapping from these structural drivers to the empirical trend in GDP is unknown ex ante. Therefore, we use a neo-classical theory of gender-specific labour demand and supply to derive necessary identification restrictions. Equipped with these restrictions, we estimate the model with Bayesian methods on data for the US over the period 1960 to 2019.
We identify two gender-specific labour market trends. The first is interpreted as female-biased demand. It captures reduced discrimination against women in the workplace, expansions of women’s rights, technological innovations that increase the returns to intellectual skills in which women have a comparative advantage, or a secular increase in the service sector where women are disproportionately employed. The second trend is interpreted as female-biased supply, and represents factors that increase women’s attachment to the labour market, such as advances in maternal health, contraception products, the emergence of home appliances, the availability and cost of childcare, or cultural factors.
Figure 2 documents how different structural factors have affected aggregate empirical trends in the post-war US macroeconomy. Three important results stand out concerning female-biased productivity growth (green). First, it accounts for a sizable share of the overall increase trend in GDP. Second, it explains most of the post-war rise in the total employment rate, which would have fallen on average since 1960 in the absence of this secular trend. Third, female-specific productivity is also an important driver of aggregate labour productivity – here measured as output per worker – suggesting that women entering the labour market caused productivity gains beyond the mere scale effects of having a larger labour force. Finally, we note that while the trend in female-specific labour supply (light blue) has contributed to aggregate employment, it has played only a minimal role for GDP and aggregate labour productivity.
Figure 2 Structural decomposition of the empirical trends
Notes: Empirical trends (black lines) versus the contributions of individual structural trends (coloured bars). Vertical axes represent log deviations from initial values, horizontal axes measure time in quarters. Pointwise median estimates are reported.
Table 1 summarises our account of economic growth in the postwar US economy. For each decade we decompose the average, annual growth rates in the trend components of GDP and labour productivity into the estimated contributions of the five structural drivers. Importantly, both GDP growth and labour productivity growth have declined substantially in our data, from about 2.8 and 2.5 percentage points per year in the 1960s, to 1.1–1.4 percentage points in the last 20 years. Most of the decline took place in two waves: between the 1960s and 1970s, and at the beginning of the 2000s.
Table 1 Growth factors in the US economy
Notes: Structural decompositions of the average, annual trend growth rates of (1) real GDP and (2) labour productivity (by decade), into total factor productivity A, automation α, gender-neutral labor supply Ψ, female-specific productivity af, and female-specific labor supply ψf. All numbers are point-wise median estimates.
For the sample as a whole, we find that most of the slowdown is attributable to total factor productivity, which in annual growth terms fell by more than 50% over the first two decades. However, up until the 1980s, lower total factor productivity growth was substantially counteracted by a secular increase in female-specific productivity: its contribution to trend GDP growth went from 0.5 percentage points per year in the 1960s to 1 percentage point in the 1980s. For labour productivity, its contribution increased from 0.3 to 0.7 percentage points per year. Thus, female-specific labour productivity doubled its annual growth rate and, as a result, its contribution to trend growth between the 1960s and the end of the Cold War.
This picture has changed fundamentally in the last 30 years of data. Not only did the overall growth rate of gender-neutral macro trends continue to decline between the 1990s and the 2010s, but also two-thirds of female-specific labour productivity growth disappeared during this period. The latter result is imperative for growth accounting in recent decades according to our model: between the 1990s and 2010s, the slow-down in female-specific labour productivity is responsible for about half of the overall decline in the growth rates of trend GDP and labour productivity.
The finding that gender matters for the macro picture connects us with seminal papers by Hsieh et al. (2019) and Heathcote et al. (2017). However, while they use heavily parametrised structural models, we instead rely on a ‘let the data speak’ approach. Finally, we highlight three important auxiliary results of our analysis.
First, our model allows us to speak to the literature showing that slower trend employment growth may explain the emergence of slow employment recoveries observed after recent recessions (Albanesi 2024, Fukui et al. 2023 and Olsson 2024) by providing a decomposition of the forces driving this decline. While our analysis suggests that about half of the observed slowdown is due to female-specific productivity, it also confirms the relevance of rising labour-saving technological progress (Jaimovich and Siu 2020) and lower gender-neutral labour supply (Pugsley and Sahin 2019).
Second, the fact that female-specific trends are key drivers of employment growth suggests that the crowding-out effect of female employment on male employment is limited, as also shown by Fukui at l. (2023).
Third, we explicitly control for the role of skills and services to address the concern that forces like skill-biased technological progress and the process of structural transformation from goods to services may be captured as gender-specific change in our simple setup. Two main results stand out. First, our identified gender trends remain important drivers of economic growth even within skill segments and within the service sector, confirming a prominent role for genuine productivity trends peculiar to women. Second, when gender gap data by skill segments are considered, a supply-driven expansion of female labour in high-skill jobs emerges, and at the same time a contraction in the supply of female labour in low-skill jobs. These two forces have led to a substantial reallocation of women to skill-intensive jobs and have largely counteracted each other. This partly explains why the net spillover effect from female-specific labour supply factors to the macroeconomy is so limited in our baseline estimation.
Regarding future growth prospects, one possible concern is that muted growth since the 2000s represents a new normal unless labour market participation among women starts accelerating again. On the one hand, gender differences in the US labour market are still sizable, and experiences from other countries (see Albanesi et al. 2023 for an international comparison) suggest that ample pockets of growth may still be available if the right institutional features are put in place. However, further growth could also prove more difficult than in earlier decades given that women’s employment rates are much higher now and given the much smaller gap between women and men than in the past.
Source : VOXeu
