Conference Agenda

We examine whether the minimum wage increases wages for women more than men and reduces the gender wage gap in the United States for adults with less than a college degree. We use state variations in the effective minimum wage and conduct two different analyses using Annual Demographic Current Population Survey data from 1977 to 2018. We use a two-way fixed effects and an event study to estimate whether women differentially report earnings gains following minimum wage changes. Preliminary findings are that the gender wage gap narrows following minimum wage changes, with a mean differential elasticity of 0.216. Women at the lower percentiles of the wage distribution experience greater wage increases. Our findings imply that a ten percent increase of the minimum wage can reduce the gender wage gap by approximately 2.5 percent (with significant heterogeneity by state).

Women’s entrepreneurship is a global policy goal in the promotion of women’s economic empowerment. However, studies have generally focused on gender differences in labour force participation and wage gaps in labour markets and not so much on gender differences in entrepreneurship. The relatively limited research is mostly centred on Sub Saharan African countries using one-off specialized studies. Using unique survey data from Georgia, Mongolia, and Philippines, we make several contributions to the literature on gender gaps in entrepreneurship.

First, this study draws insights on gender disparities in the region, using inter-country comparable data following consistent concepts and methodological principles. Second, the research captures both formal and informal entrepreneurship activities as it uses household-level data—providing a more complete view of entrepreneurship patterns. Other studies mostly use data on registered enterprises which usually account only for a small proportion of entrepreneurial activities in many developing countries. Third, unlike conventional household surveys that rely on proxy information provided by one household member, this study provides a comprehensive set of indicators on entrepreneurship at individual-level.

We find the overall incidence of entrepreneurship is highest in Cavite, Philippines, while the gender gap in ownership is highest in Mongolia. Interestingly, women are more likely to be exclusive owners in Cavite with main financial control of their enterprise. On average, enterprises operated by men tend to have larger firm size relative to those operated by women. Except for Mongolia, the average income of male-owned enterprises is greater than the average income of female-owned enterprises. Multivariate analysis suggests that the determinants of income by gender and across countries. The effect of location (urban or rural), whether head or spouse, or education of the owner varies across the models. Enterprise attributes are more likely to be correlated with the income, irrespective of whether it is male-owned or female-owned. Whether the enterprise is registered, the number of employees and the maintenance of accounts (formal or informal) are positively correlated with the income of the enterprise in all three countries.

Using the Oaxaca-Blinder decomposition, we find that the average difference in income between men and women’s enterprise is not significant in Mongolia. However, more than 50% of the gender income gap is explained by observable characteristics in Cavite, Philippines and Georgia. On average, the income of female-owned enterprises would have seen a rise of 64% (Cavite, Philippines) and 59% (Georgia) if they had the same characteristics as male-owned firms.

Announced in June 2021, the Green Recovery Plan for the Amazon Region (GRP-Amazon) foreshadowed a joint state government green transition initiative to address the Covid-19 economic crisis in Brazil. Among the Brazilian initiatives to transition to a low carbon economy, the Green Recovery Plan for the Legal Amazon (PRV-AL) stands out as a certainly interesting analytical framework, at least in terms of its conception: it combines the problem of illegal deforestation (the main source of greenhouse gas emissions in Brazil) with the need to generate employment and income in the short term, favoring the fight against inequalities in Legal Amazon, a region where Brazilian structural disparities are especially highlighted. The Plan was supposed to provide an initial investment of BRL 1.5 billion, partitioned into four main axes: control of illegal deforestation, sustainable development, green technology and training, and green infrastructure. However, it neither offered a detailed description of the procedures nor informed about the division of total resources' allocation. Consequently, little information was available to assess the potential economic impact of the GRP-Amazon. Considering the importance of the Amazon to Brazil's climate policy, this article uses the GRP-Amazon proposal as a departure point to simulate the potential impact of a green recovery plan centered in the region. It focuses on the effects of green spending on the labor market both quantitatively - in terms of the number of jobs created - and qualitatively - looking at the distribution of these jobs by region and according to gender and race categories. We anchor the four axes mentioned in the GRP-Amazon in the real economy and measure the impact on job creation of a demand shock via input-output (IO) employment multipliers. Following the methodology elaborated by Kim, İlkkaracan , and Kaya (2017; 2019), the four axes are structured as synthetic sectors in the Amazon region economy and introduced in a 2015 two-region IO matrix ("Amazon Region" and "Rest of Brazil") as a linear combination of existent sectors. Results suggest that a green recovery plan in the Amazon Region offers perspectives for a just transition to a low-carbon economy in Brazil.

Despite widespread recognition that assets are important for economic wellbeing and women’s empowerment, there is limited research on the gender wealth gap in both developed and developing countries (Deere & Doss 2006). This is largely due to the lack of individual-level data on wealth or net worth (i.e. the value of assets less debt). Most surveys that collect information on wealth do so at the household level, and even where attempts are made to collect data on individual ownership, generally only one member of the household responds on behalf of all others. Research on survey design has shown that who answers the questions about assets, and how the data are elicited, can affect the gender gap substantially (Kilic & Moylan 2016). Best practice requires each adult in the household to report on their own assets and debts, and where these are held jointly, to indicate their share (Doss & Deere 2020). Information on the market value of assets is also important, as studies have found that the share of asset owners who are women is larger than the share of wealth owned by women, as women tend to own assets of lower value than men (Doss et al 2011; 2014). Capturing information on ownership only, and not on values, will therefore underestimate the gap.

In this paper we explore the gender wealth gap using unique individual-level data for South Africa collected in the 2017 National Income Dynamics Survey (NIDS), a representative household survey covering roughly 27 000 adults. NIDS included a detailed module on wealth in which each adult in the household reported on the value of their own assets and debts (across the categories of real estate, business, vehicle, financial, pension, and household durables), as well as their share in assets held jointly. We find a substantial gender wealth gap in our data (greater than the wage gap, as expected). At the mean, for example, the ratio of female-to-male net worth is 0.667, amounting to a gender gap of 33.3%. Unsurprisingly given the extent of inequality in South Africa, this gap is larger than that found in countries such as the US and Germany where similar data exist (Sierminska et al 2010). In addition to measuring the gender wealth gap (and its components), in this paper we also describe heterogeneity in the gap by marital status, and we explore some of the key drivers of gender wealth inequality in South Africa using decomposition techniques.