Does Gender Equality Fuel Regional Growth in the European Union?

1. Introduction

Gender equality is now a central focus in European policy discussions. The EU Gender Equality Strategy 2026–2030 framed gender equality not only as a matter of rights and social justice, but also as part of Europe’s strategy for competitiveness, resilience, and inclusive growth (European Commission, 2026). The European Union faces persistent productivity weakness, demographic ageing, labour shortages in some sectors, and deep regional inequalities, and these concerns have become central to the broader debate on European competitiveness and market integration (Draghi, 2024; Letta, 2024). At the same time, gender gaps remain visible in employment, earnings, care burdens, entrepreneurship, and access to decision-making. In 2024, the gender employment gap in the EU stood at 10.0 percentage points, with employment rates of 80.8 per cent for men and 70.8 per cent for women (Eurostat, 2026). Recent estimates suggest that, at the current pace of progress, gender equality in the EU remains at least 50 years away (EIGE, 2025). The World Bank’s Women, Business and the Law 2026 report argues that removing barriers to women’s economic participation can boost jobs, productivity, and inclusive growth, and it highlights that closing the global gender gap in employment and entrepreneurship could raise global GDP by 20 per cent (World Bank, 2026). Even where legal equality has improved, economic outcomes continue to differ sharply across member states and across regions within them.

A long-standing area of literature argues that gender inequality reduces growth by preventing economies from making full use of the available talent and labour (Klasen and Lamanna, 2009; Cuberes and Teignier, 2016). Women may be excluded from paid work, concentrated in lower-productivity activities, constrained by care responsibilities, or discouraged from investing in skills and entrepreneurship. When that happens, economies lose output, productivity, and business dynamism. Recent work sharpens this argument by showing that these costs can be particularly pronounced in activities that rely more heavily on female labour (Bertay, Dordevic, and Sever, 2025).

However, most of the existing evidence comes from either broad cross-country comparisons or non-European samples. This leaves an important gap for EU policy. The European Union is a distinctive setting: it combines relatively advanced welfare states and labour-market institutions with substantial cross-country variation in legal frameworks, social norms, and economic structures. It also has a strong regional dimension. Growth, labour markets, and structural transformation differ sharply not only between countries but also across more granular NUTS-3 regions.1 For policy design, regional variation matters.

This paper brings together these two debates: gender equality and regional growth. It asks whether country-level legal reforms that improve women’s economic rights are followed by stronger growth in EU regions. The analysis uses annual data for EU 1,160 NUTS-3 regions across all 27 current EU member states over the period 1995-2023 and identifies large improvements in the World Bank’s Women, Business and the Law (WBL) index as reform events. The WBL index scores countries on laws affecting women’s economic participation across eight dimensions: workplace protections, pay, marriage, parenthood, entrepreneurship, assets, pensions, and mobility. The empirical framework uses the aggregate index to define significant reforms, and separately examines six of these dimensions (workplace, pay, marriage, parenthood, entrepreneurship, and pensions) to identify which types of legal change are most closely associated with regional growth. The remaining two dimensions, mobility and assets, are excluded because the EU member states had already reached, or were very near, the maximum score on both throughout the sample period, leaving insufficient variation to estimate their effects. The framework relates these reforms to subsequent regional growth over horizons from the year of reform to five years ahead, controlling for region fixed effects, year fixed effects and a rich set of lagged regional and macroeconomic controls.

Three findings stand out. First, major legal reforms are followed by higher regional growth in GDP per capita, but the effect is delayed. The strongest coefficients appear at four to five years after reform. Second, investment responds more clearly than productivity. Investment turns positive and highly significant from three years after reform onwards. Productivity shows a weaker and less consistent response, with significance only at four years after reform. This suggests that reform-led growth may work through labour-force participation, labour reallocation, and investment, rather than through an immediate jump in output per worker. Third, the gains are uneven across sectors. Construction shows the clearest medium-term response. Agriculture also reacts positively, manufacturing gains moderately, and the services sector, which is female-dominated, shows little growth effect.

Combined with the data on sectoral female employment shares, this pattern suggests that reforms may matter most in sectors in which women initially played a smaller role. That interpretation differs from the one given by Bertay, Dordevic, and Sever (2025), who argue that gender inequality is especially harmful in female-intensive industries because those industries depend more on women’s labour. In the EU regional setting examined here, the pattern appears closer to an extensive-margin mechanism: reforms may enable women to enter or remain in activities in which they were previously underrepresented, thereby raising output without necessarily generating immediate productivity gains.

This distinction is important for policy. It implies that legal reform can be growth-enhancing even if the first-round effect comes mainly through higher labour input and structural change rather than a rapid improvement in average labour productivity.

The analysis does not claim that legal reform is a silver bullet, nor that all dimensions of gender equality matter equally. Rather, it shows that gender-related legal reforms are associated with stronger regional growth in the EU and that the transmission seems to depend on the local economic structure. The paper therefore speaks directly to EU concerns about competitiveness, cohesion, and labour supply.

This is especially relevant at a time when European debates on competitiveness increasingly focus on innovation, industrial policy, strategic autonomy, and the need to improve growth without undermining social cohesion. Those debates often emphasise capital, technology, and energy. The results in this paper suggest that labour allocation deserves equal attention. If legal and institutional barriers continue to limit women’s access to parts of the labour market, Europe is leaving productive capacity unused. In that sense, gender equality is not only part of the social model that the EU seeks to protect, but it is also part of the competitiveness agenda the Union now seeks to renew.

2. Gender equality and growth in the EU: why this matters now

The case for analysing gender equality as an economic issue is particularly strong in today’s Europe. According to the European Institute for Gender Equality (EIGE), progress in gender equality remains uneven across the Union, and full equality is still far away. The 2025 Gender Equality Index underscores the conclusion that improvement has been real but incomplete, with setbacks or stagnation in some domains and large differences between countries. The report also highlights enduring gender segregation in work, persistent care inequalities, and continuing differences in economic and political power.

These are not only social concerns. They matter for macroeconomic performance. Europe’s medium-term outlook is constrained by weak productivity growth and adverse demographics. In this environment, the underutilisation of female talent and labour becomes more costly. If women’s employment choices are restricted by law, norms or institutions, labour is not allocated to its most productive uses. If mothers face career penalties due to inadequate care support, human capital investment yields smaller returns. If women are crowded into a narrow set of occupations or sectors, structural transformation becomes less efficient. The aggregate result can be lower growth.

EU policy discussions increasingly recognise this connection. The Union’s gender equality strategy, work–life balance agenda and debates on childcare, pay transparency and representation all imply that narrowing gender gaps is linked to economic performance. However, evidence on the effects of such changes on regional growth remains limited. Much of the empirical literature either uses country-level growth regressions, for which identification is difficult, or focuses on labour-market outcomes rather than broader regional growth.

Regional evidence is especially valuable because the impact of reform may depend on the local sectoral composition, labour-market conditions and demographic trends. The regional perspective is also important for cohesion policy. Research on EU regional growth shows that small territorial units can conceal substantial heterogeneity within countries and even within richer regions. Lagging areas may coexist with prosperous metropolitan centres, and growth pathways may differ by income level, industrial structure and urbanisation. If gender-equality reforms have regionally differentiated effects, that matters for how Europe thinks about convergence.2

A useful way to motivate the analysis is with three simple stylised facts. First, gender equality still differs markedly across EU member states, despite decades of policy attention. Second, these national differences sit alongside pronounced regional inequality within countries, which is why a regional lens is useful for policy. Third, women’s employment remains highly segregated across sectors. At the country level, women make up on average about 9 per cent of those employed in construction, around 30 per cent in both agriculture and manufacturing, and roughly 55 per cent in services.3 That uneven starting point helps to explain why legal reforms may not have uniform economic effects across sectors or places.

3. What we know from the literature

The broader literature linking gender inequality and growth is extensive. A common argument is that gender gaps in education, health, labour-market opportunities, legal rights, and finance reduce aggregate efficiency and long-run growth. Early research emphasised the role of human capital and labour-force participation, while later work highlighted misallocation and the inefficient use of talent.

A useful synthesis is provided by Bertay, Dordevic, and Sever (2025), who study industry-level data from 65 emerging market and developing economies. Their key idea is simple and powerful: when gender inequality is high, industries that rely more on female labour perform worse because they are disproportionately exposed to barriers affecting women. Using an industry-level difference-in-differences design, they find that greater gender equality is associated with stronger value-added and productivity growth, especially in female-intensive industries.

This paper is an important reference point because it moves beyond broad cross-country correlations and focuses on an economic mechanism. The present paper complements that contribution in two ways. First, it shifts the focus from emerging and developing economies to the European Union. Second, it moves from industries to regions. This makes it possible to ask not just whether gender inequality affects sectors that are intensive in female labour, but also whether legal reform is followed by stronger growth in particular places and through particular sectoral channels.

The empirical design also draws on the regional growth literature. Ganau and Kilroy (2023) show that growth pathways differ strongly across EU NUTS-3 regions. Their work highlights the role of industrial structure, innovation, and inward investment, and demonstrates the value of analysing smaller territorial units rather than relying only on broader regional aggregates.

Methodologically, this paper is also close in spirit to recent work that studies medium-term regional responses to shocks using local-projection style horizons. Usman, González-Torres Fernández, and Parker (2025) show how regional climate-related events can have effects that build over several years rather than having an immediate impact. That insight matters here, too. Legal reforms are unlikely to alter regional output immediately. Firms need time to adjust, households need time to respond, and labour-market transitions are gradual. The estimation of effects over several horizons is therefore better suited to the underlying economics than a focus only on the contemporaneous response.

4. Data and empirical approach

The empirical analysis combines several sources. Regional economic outcomes are measured at the NUTS-3 level for EU regions over time. The main outcomes are growth in gross regional domestic product per capita, productivity growth (output per person), and investment growth (gross fixed capital formation, GFCF). Additional sectoral outcomes capture growth in agriculture, manufacturing, construction, services, and total gross value added (GVA), as well as changes in sectoral output shares. The panel covers 1,160 NUTS-3 regions across all 27 current EU member states over the period 1995–2023.

The reform variable comes from the World Bank’s Women, Business and the Law database. The paper defines a major reform as an increase of at least five points in the WBL index. This captures substantial legal improvements affecting women’s economic rights. Separate specifications also examine the sub-indices, including workplace, pay, marriage, parenthood, entrepreneurship, and pensions.4

The baseline specification is estimated separately for each horizon (h = 0, 1, …, 5):

where 

is the h-period forward difference in the log of the dependent variable y (h = 0, 1, …, 5) for region r at time t;

is a vector of lagged controls (including regional controls as well as country-level macro controls for country c);

Reform_wbl

is an indicator equal to one if country c experiences a major WBL reform in year t;

and 

are region and year fixed effects; and standard errors are clustered at the NUTS-2 level (241 clusters). The coefficient of interest is γ, which captures the average effect of a WBL reform on the cumulative change in the dependent variable between t-1 and t+h.

In other words, the analysis compares how regions in countries that adopted a major legal reform performed over the years that followed, relative to regions in countries that did not reform in the same year, after accounting for each region’s long-run average level, common year-by-year shocks across all regions, and a wide range of economic conditions observed just before the reform took place.

The treatment varies at the country-year level and is therefore shared by all regions within a country in a given year, while the identifying variation comes from differences in reform timing across countries and the dynamic response across horizons. Empirically, the design is best thought of as a fixed-effects event-style framework estimated horizon by horizon, close in spirit to local projections (a method that estimates the effect of a policy change at each point in time separately) rather than as a method that imposes a single dynamic structure on the data.

Estimating the specification separately at each horizon, rather than imposing a single dynamic model, has a practical advantage: it traces out the full path of adjustment without constraining how quickly or slowly the economy responds. This matters here because labour-market and investment responses to legal change are unlikely to be instantaneous, and imposing too much structure on the dynamics could hide important medium-term effects.

The lagged control variables include log GDP per capita, a non-negative population change indicator, net migration as a share of population, natural population change as a share of population, the employment-to-population ratio, gross value added (GVA) shares for manufacturing, construction and services, the investment-to-GDP ratio, the Rule of Law score from the Worldwide Governance Indicators, real GDP per capita in US dollars, inflation, the unemployment rate, government debt as a share of GDP, and an EU membership indicator.5

As a robustness check, Table A2 augments the baseline with country-specific linear time trends (see appendix). This mitigates the concern that reforming and non-reforming countries might already have been on different growth trajectories before the reform took place.

5. Main results

5.1 GDP per capita, productivity, and investment

Table 1. Effect of Women, Business and Law (WBL) indicators reforms on regional economic outcomes
	h = 0	h = 1	h = 2	h = 3	h = 4	h = 5
Panel A: Log GDP per capita
Reform_wbl	0.249	0.569*	0.396	1.226***	2.135***	1.869***
	(0.228)	(0.322)	(0.341)	(0.378)	(0.431)	(0.466)
Adj. R²	0.358	0.427	0.467	0.527	0.592	0.650
Panel B: Log productivity per person employed
Reform_wbl	0.395	0.481	−0.134	0.498	1.000**	0.544
	(0.271)	(0.325)	(0.339)	(0.352)	(0.393)	(0.403)
Adj. R²	0.242	0.329	0.409	0.497	0.572	0.634
Panel C: Investment (GFCF)
Reform_wbl	−0.325	−0.400	0.742	4.058***	5.712***	4.105***
	(0.589)	(0.793)	(0.905)	(1.027)	(1.169)	(1.097)
Observations	30,077	28,917	27,757	26,599	25,440	24,280
Adj. R²	0.280	0.400	0.446	0.504	0.565	0.613
Notes: All regressions include region and year fixed effects and a full set of lagged controls. Standard errors clustered at the NUTS-2 level (241 clusters) in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.

The clearest headline result is that legal reforms are followed by stronger growth in regional GDP per capita, but only after a delay. As Panel A of Table 1 shows, the reform coefficient is small and insignificant in the year of reform and turns marginally significant after one year (0.57%). At two years after reform, the coefficient is positive but insignificant. From three years after reform onwards, the effect becomes statistically significant: 1.23% (p < 0.01), 2.14% (p < 0.01) and 1.87% (p < 0.01) at three, four and five years after reform, respectively.6

The results suggest that legal reforms that improve women’s rights do not automatically translate into higher output in the same year. Labour supply, hiring, occupational mobility and investment all take time to adjust. The medium-term pattern suggests that legal change can contribute to stronger regional growth, but that the pay-off is gradual rather than immediate.

The decomposition across productivity and investment is revealing. Panel B shows that productivity growth exhibits a weaker, less consistent response, with significance only at four years after reform, by which time reforms are associated with a 1% increase in productivity growth. Investment, by contrast, reacts more strongly and earlier. Panel C shows that the coefficient becomes positive and highly significant from three years after reform onwards (4.06%), peaks at four years (5.71%) and remains strong at five years (4.11%).

Taken together, these results suggest that the growth effect is not driven by an immediate improvement in output per worker. Instead, it looks to be more consistent with an extensive-margin or structural-adjustment mechanism. Legal reforms may encourage higher labour-force participation and returns, better job mobility, and stronger incentives for firms and households to invest. Output then rises as labour and capital are reallocated, while average productivity responds more slowly.

This interpretation is important because a weak short-run productivity result should not be read as evidence against gender equality reforms. If the first-round effect is to bring more women into sectors or activities in which they were previously underrepresented, aggregate output can rise even if measured productivity does not jump immediately. Indeed, one should expect productivity effects to arrive more slowly when the adjustment process involves entry, training and sectoral transitions.

5.2 Which dimensions of legal reform matter?

Table 2. Sub-index decomposition: all Women, Business and Law sub-indices in a single specification
	h = 0	h = 1	h = 2	h = 3	h = 4	h = 5
Reform_workplace	1.029***	1.372***	1.373***	1.239***	1.608***	1.592***
	(0.214)	(0.314)	(0.379)	(0.425)	(0.393)	(0.362)
Reform_pay	−0.564***	0.478**	1.795***	1.424***	1.203***	2.719***
	(0.177)	(0.231)	(0.292)	(0.359)	(0.365)	(0.518)
Reform_marriage	−0.270*	−0.893***	−1.578***	−1.847***	−2.826***	−3.020***
	(0.148)	(0.210)	(0.230)	(0.294)	(0.347)	(0.423)
Reform_parenthood	0.438***	0.740***	0.146	0.354	2.162***	2.651***
	(0.124)	(0.244)	(0.255)	(0.312)	(0.356)	(0.424)
Reform_entrepreneurship	−1.183***	−1.812***	−2.340***	−1.595***	−1.875***	−2.084***
	(0.272)	(0.535)	(0.617)	(0.552)	(0.426)	(0.388)
Reform_pension	−0.778**	−1.192***	−2.111***	−1.568***	−0.588	−1.346**
	(0.314)	(0.407)	(0.496)	(0.546)	(0.608)	(0.684)
Observations	30,077	28,917	27,757	26,599	25,440	24,280
Adj. R²	0.362	0.431	0.475	0.531	0.597	0.658
Notes: Dependent variable is the forward difference in log GDP per capita. All six sub-index treatment dummies are included simultaneously. Region and year FE, full lagged controls. SE clustered at NUTS-2 (241 clusters). * p < 0.10, ** p < 0.05, *** p < 0.01.

A related insight comes from the sub-index results. Not all legal reforms appear to be equally relevant to growth. Table 2 reports a horse-race specification in which all six sub-index reform indicators enter simultaneously, so the coefficients should be read as conditional associations rather than as clean estimates of the effect of each legal dimension in isolation.

Workplace reforms show a large and persistent positive effect across all horizons. This is the most consistently significant sub-index. The effect of pay reforms is initially negative, but turns strongly positive from two years after reform onwards. Parenthood reforms have a positive and significant effect at short horizons which fades at intermediate horizons then returns strongly.

This pattern is plausible from a policy perspective. Rules shaping workplace protections, equal pay, and the compatibility of paid work with family life are likely to affect labour-market attachment more directly than some other legal reforms, especially in a European context in which care constraints remain important.

Three sub-indices are associated with negative effects. Marriage reforms carry a negative and increasingly large coefficient. Entrepreneurship reforms show persistent negative coefficients across all horizons, and the effect of pension reforms is similarly negative. These findings may reflect transition costs, regulatory burdens, or the absence of complementary conditions. Entrepreneurship reforms may require accompanying access to credit and business support services, while pension and marriage reforms may involve fiscal or institutional adjustments that offset short-term benefits.

Note, however, that the reforms across sub-dimensions may be correlated, and that all six indicators enter together, making these estimates harder to map onto a structural interpretation. They may reflect overlap in reform timing, omitted complementarities, or transitional adjustment costs rather than a straightforward negative effect of reform in those domains.

6. Heterogeneity across regions and sectors

6.1 Income and urban heterogeneity

The heterogeneity results suggest that the medium-term growth response is stronger in lower-income regions. In Panel A of Table 3, the base effect for low-income regions is positive and significant from two years after reform onwards, while the interaction terms for middle- and high-income regions are often negative and usually insignificant. At two years after reform, the high-income interaction is significantly negative. Taken together, the results are consistent with the idea that reforms are more likely to matter where labour allocation is further from its potential.

Table 3. Heterogeneity in the effect of Women, Business and Law reforms on log GDP per capita
	h = 0	h = 1	h = 2	h = 3	h = 4	h = 5
Panel A: By income group (base: Low)
Reform_wbl (Low)	0.244	0.765	1.300**	1.705***	2.441***	1.573*
	(0.400)	(0.537)	(0.572)	(0.646)	(0.805)	(0.914)
Middle × Reform_wbl	−0.286	−0.197	−1.367**	−0.523	−0.453	0.994
	(0.435)	(0.584)	(0.642)	(0.754)	(0.930)	(1.043)
High × Reform_wbl	0.279	−0.591	−2.305***	−1.405*	−0.786	0.253
	(0.411)	(0.572)	(0.666)	(0.806)	(0.966)	(1.066)
Panel B: By urbanisation (base: Rural)
Reform_wbl (Rural)	0.007	0.568	0.778	1.503**	2.453***	2.227**
	(0.339)	(0.517)	(0.563)	(0.630)	(0.833)	(0.934)
Urban × Reform_wbl	0.467	0.089	−0.549	−0.782	−1.126	−1.203
	(0.430)	(0.641)	(0.701)	(0.874)	(1.176)	(1.272)
Intermediate × Reform_wbl	0.364	−0.036	−0.651	−0.313	−0.264	−0.322
	(0.297)	(0.479)	(0.546)	(0.625)	(0.781)	(0.833)
Observations	30,077	28,917	27,757	26,599	25,440	24,280

Notes: Interactions are relative to the base category (Low income / Rural). Full controls, region and year FE. SE clustered at NUTS-2 (241 clusters). * p < 0.10, ** p < 0.05, *** p < 0.01.

Panel B of Table 3 points in a similar direction. The base effect for rural regions is positive and significant at medium horizons, while the urban and intermediate interactions are not statistically distinguishable from zero. This suggests that the growth response is, if anything, somewhat stronger in less urbanised areas.

6.2 Sectoral growth effects

The sectoral results help to illustrate the likely transmission channels. Table 4 shows that total GVA follows a pattern similar to GDP per capita: little immediate effect, followed by stronger positive coefficients at three to five years after reform. Beneath that aggregate result, however, there is substantial sectoral heterogeneity.

Table 4. Sectoral GVA growth effects of Women, Business and Law reforms
	h = 0	h = 1	h = 2	h = 3	h = 4	h = 5
Panel A: Agriculture
Reform_wbl	4.097***	8.038***	6.824***	2.973**	0.487	2.145**
Panel B: Manufacturing
Reform_wbl	0.561*	1.575***	1.507***	1.914***	2.079***	2.585***
Panel C: Construction
Reform_wbl	−0.955	−1.372*	1.429*	4.642***	7.186***	7.811***
Panel D: Services
Reform_wbl	−0.106	−0.312	−0.514*	−0.278	0.967**	0.708*
Panel E: Total GVA
Reform_wbl	0.260	0.520*	0.395	1.067***	1.905***	1.773***
Observations	30,077	28,917	27,757	26,599	25,440	24,280
Notes: Each panel reports the Reform_wbl coefficient from a separate regression with sectoral log GVA forward difference as the dependent variable. Full controls, region and year FE. SE clustered at NUTS-2 (241 clusters). Standard errors suppressed for brevity. * p < 0.10, ** p < 0.05, *** p < 0.01.

The association between country-level reforms and regional sectoral growth is strongest in construction. The coefficients are negative on impact and after one year, but turn positive from two years after reform onwards and become strongly significant from three years onwards, peaking at 7.81 per cent five years after reform. Agriculture also responds positively, especially at short horizons, while manufacturing shows a steadier positive pattern over time. Services, by contrast, show little robust positive response at shorter horizons and only modestly positive coefficients later.

This pattern does not fit the simple prior assumption that the largest response should occur in services merely because women are already more heavily represented there. Instead, the strongest medium-term gains appear in sectors in which women initially had a smaller role, especially construction. One interpretation is that legal reform may have widened access to occupations and activities for which women’s entry was previously more constrained. That interpretation is suggestive rather than definitive, but it is consistent with the combined evidence from the growth and sector-share results.

6.3 Sectoral shares and structural adjustment

Table 5. Effect of Women, Business and Law reforms on sectoral output shares
	h = 0	h = 1	h = 2	h = 3	h = 4	h = 5
Agriculture share	0.105**	0.210***	0.105**	0.041	−0.056	−0.054
Manufacturing share	0.104*	0.286***	0.244***	0.332***	0.070	0.175**
Construction share	−0.065**	−0.087**	0.100**	0.267***	0.377***	0.413***
Services share	−0.158**	−0.420***	−0.431***	−0.634***	−0.403***	−0.549***
Observations	30,076	28,916	27,756	26,598	25,439	24,279
Notes: Each row reports the Reform_wbl coefficient from a separate regression with the forward difference in sectoral GVA share as the dependent variable. Full controls, region and year FE. SE clustered at NUTS-2 (241 clusters). * p < 0.10, ** p < 0.05, *** p < 0.01.

The sector-share results in Table 5 point in the same direction. Services lose share after reform, with a negative and significant coefficient at all horizons. Construction gains share markedly in the medium term, and manufacturing also gains share. Finally, agriculture gains share in the short run and then fades.

This is not evidence that services are unimportant. Rather, it suggests that part of the growth response may operate through structural adjustment. Legal change may widen the set of occupations and sectors that are practically accessible to women, making it easier for labour and investment to move towards activities in which women’s participation had previously been lower.

7. Policy implications for the EU, and conclusion

First, legal equality should be understood as part of Europe’s growth strategy, not only as a social objective. The results suggest that reforms improving women’s economic rights are followed by stronger regional growth in the EU. That matters in a context of ageing, labour shortages, and a trend for weak growth. The sub-index results indicate that workplace and pay reforms are the most consistently growth-enhancing, while parenthood reforms have important medium-term effects. The EU’s Work–Life Balance Directive provides a framework, but implementation and enforcement vary significantly across member states.

Second, legal reform alone is unlikely to be sufficient. The delayed timing of the effects and the weaker productivity response suggest that complementary policies are important. These include childcare and long-term care provision, work–life balance measures, active labour-market policies, reskilling, and support for transitions into non-traditional sectors. If legal barriers are removed but practical constraints remain, the growth dividend is likely to be smaller. More cautiously, the mixed or negative coefficients for some sub-indices suggest that reforms in those areas may depend more heavily on complementary institutions if they are to translate into stronger growth.

Third, regions matter. Because the effects are concentrated in lower-income and less urbanised regions, a one-size-fits-all policy approach is unlikely to be optimal. Regions with large construction or manufacturing bases may benefit from targeted measures that help women to enter growing occupations. In cohesion policy terms, gender equality should be mainstreamed into territorial development strategies rather than treated as a separate silo.

This also suggests a broader lesson for EU competitiveness debates. Discussions on productivity and industrial policy often focus on technology, energy, or capital markets, but if legal and institutional barriers prevent half the population from accessing the full range of economic opportunities, competitiveness suffers. Gender equality is therefore not peripheral to Europe’s economic future; it is part of the core agenda.

This paper asks whether gender-related legal reforms are followed by stronger regional growth in the European Union. Using an annual panel of EU NUTS-3 regions and major improvements in the Women, Business and the Law index as reform events, it finds that the answer is yes, but with important qualifications.

The main effect is on growth in GDP per capita, and it emerges only after several years. The strongest point estimate appears at four years after reform. Investment responds more clearly than productivity, which points to a transmission mechanism based on labour-market participation, capital accumulation, and structural adjustment rather than an immediate rise in within-sector efficiency. Among the sub-indices, workplace reforms are the most consistently significant across all horizons, while pay and parenthood reforms show strong medium-term effects.

The sectoral evidence deepens this interpretation. Construction stands out as the strongest medium-term channel. Agriculture also responds, manufacturing gains steadily, and services show little growth effect. When combined with data on women’s employment share, this suggests that reforms may be especially growth-enhancing in sectors in which women were initially underrepresented.

The heterogeneity analysis adds a further dimension: the growth effects are concentrated in lower-income and less urbanised regions, suggesting that gender-equality reforms have the most room to unlock growth where labour allocation is furthest from its potential.

For EU policymakers, the findings suggest that progress in gender-equality legislation can be associated with positive regional economic outcomes, but that these benefits are neither automatic nor uniform across sectors and places. Legal reform can expand opportunity; whether that expansion translates into sustained and inclusive growth depends on the surrounding policy environment.

References

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Cuberes, D. and Teignier, M. (2016). ‘Aggregate effects of gender gaps in the labor market: A quantitative estimate’. Journal of Human Capital, 10(1), 1–32.

Draghi, M. (2024). The Future of European Competitiveness. Part A: A Competitiveness Strategy for Europe. European Commission. 

European Commission (2026). Gender Equality Strategy 2026–2030. COM(2026) 113 final. Brussels. 

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Appendix

Table A1. Variable descriptions
Variable	Description	Source
Panel A: Dependent variables
Δh log GDP per capita	Forward difference in log gross regional domestic product per capita (×100): y(t+h) − y(t−1). Horizons h = 0, 1, …, 5.	Eurostat regional accounts
Δh log productivity	Forward difference in log output per person (×100).	Eurostat regional accounts
Δh investment	Forward difference in log gross fixed capital formation (GFCF) (×100).	Eurostat regional accounts
Δh sectoral GVA	Forward difference in log sectoral GVA (×100) for agriculture, manufacturing, construction, services and total.	Eurostat regional accounts
Sectoral share	Sectoral GVA as a percentage of total GVA (agriculture, manufacturing, construction, services).	Eurostat regional accounts
Panel B: Variables of interest
Reform_wbl	Binary indicator equal to one if the country experienced a WBL index increase of at least 5 points in year t.	World Bank WBL
WBL Index	Women, Business and the Law overall index score (0-100). Measures legal equality across eight dimensions.	World Bank WBL
Reform_workplace	Binary: ≥5-point increase in WBL Workplace sub-index (protections against discrimination, sexual harassment, etc.).	World Bank WBL
Reform_pay	Binary: ≥5-point increase in WBL Pay sub-index (equal remuneration, wage-related constraints).	World Bank WBL
Reform_marriage	Binary: ≥5-point increase in WBL Marriage sub-index (constraints related to marriage, divorce, remarriage).	World Bank WBL
Reform_parenthood	Binary: ≥5-point increase in WBL Parenthood sub-index (maternity/paternity leave, dismissal of pregnant workers).	World Bank WBL
Reform_entrepreneurship	Binary: ≥5-point increase in WBL Entrepreneurship sub-index (access to credit, ability to sign contracts).	World Bank WBL
Reform_pension	Binary: ≥5-point increase in WBL Pension sub-index (retirement age equality, pension-related rules).	World Bank WBL
Panel C: Regional controls (all lagged one period)
Log GDP per capita (t-1)	Log of gross regional product per capita (×100), lagged one year.	Eurostat regional accounts
Non-neg. pop. change	Binary indicator equal to one if natural population change is non-negative in the region.	Author’s calculations
Net migration (% pop)	Adjusted net migration as a percentage of total population in the NUTS-3 region.	Eurostat regional accounts
Net natural population change (% pop)	Adjusted net natural population change as a percentage of total population in the NUTS-3 region.	Eurostat regional accounts
Employment/Pop.	Total employment divided by NUTS-3 population.	Eurostat regional accounts
GVA share: Manuf. (%)	Manufacturing GVA as a percentage of total GVA.	Eurostat regional accounts
GVA share: Constr. (%)	Construction GVA as a percentage of total GVA.	Eurostat regional accounts
GVA share: Services (%)	Services GVA as a percentage of total GVA.	Eurostat regional accounts
Investment/GDP	Gross fixed capital formation divided by GDP in the region.	Eurostat regional accounts
Panel D: Country-level macro controls (all lagged one period)
Rule of Law	World Governance Indicators Rule of Law score (interpolated for 1997, 1999, 2001)	World Bank WGI
Real GDP per capita (USD)	Real GDP per capita in constant US dollars at the country level.	Global Macro Database (GMD) https://github.com/KMueller-Lab/Global-Macro-Database
Inflation (%)	Consumer price inflation rate at the country level.	Global Macro Database (GMD)
Unemployment (%)	National unemployment rate.	Global Macro Database (GMD)
Gov. debt/GDP (%)	Consolidated general government debt as a percentage of GDP.	Global Macro Database (GMD)
EU member	Binary indicator equal to one if the country is an EU member state in year t.	Authors’ compilation
Panel E: Heterogeneity and classification variables
Income group	NUTS-3 regions classified into Low, Middle or High income terciles based on initial GDP per capita.	Authors’ calculation
Urbanisation type	NUTS-3 classification: Urban, Intermediate or Rural, based on Eurostat urban–rural typology.	Eurostat typology
Female employment share	Share of female employment in total sectoral employment at the NUTS-2 level (agriculture, manufacturing, construction, services).	Eurostat
Panel F: Panel structure
NUTS-3 region	Cross-sectional unit identifier for each NUTS-3 region. 1,160 unique units in the estimation sample.	Eurostat
NUTS-2 cluster	Clustering variable for standard errors. 241 unique NUTS-2 regions.	Eurostat
Notes: All forward differences are computed as y(t+h) − y(t−1) and multiplied by 100. Regional controls are measured at the NUTS-3 level unless otherwise stated. Eurostat regional accounts variables are taken from Usman et al. (2025, https://github.com/MilesIParker/GoingNUTS). The WBL index and sub-indices range from 0 to 100, with higher values indicating greater legal equality.

Table A2. Robustness: adding country-specific linear time trends
	h = 0	h = 1	h = 2	h = 3	h = 4	h = 5
treat_wbl	0.140	0.192	−0.278	0.304	0.955***	0.416**
	(0.198)	(0.226)	(0.227)	(0.203)	(0.214)	(0.206)
Observations	30,077	28,917	27,757	26,599	25,440	24,280
Adj. R²	0.385	0.479	0.538	0.617	0.693	0.754
Notes: Specification adds country × year linear trends to the baseline. Dependent variable: forward difference in log GDP per capita. Full controls, region and year FE, SE clustered at NUTS-2 (241 clusters). * p < 0.10, ** p < 0.05, *** p < 0.01.

 

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1 Nomenclature of Territorial Units for Statistics (NUTS) level 3 regions are the smallest of the three classes.

2 See Sever (2025) for a discussion on how legal gender equality matters for country-level convergence.

3 EU-27 country averages from Eurostat employment statistics.

4 See the appendix (Figure A1) for a country-level timeline of the reforms used in the analysis.

5 Newer member states enter the sample before their accession date, and the EU membership indicator controls for any structural break associated with joining the EU.

6 This core finding survives the inclusion of country-specific linear time trends, which accounts for pre-existing differences in national growth trajectories (Table A2).