How to do Implicit Association Test?
Implicit Association Tests (IATs) are being increasingly used in applied micro papers. While IATs can be found off-the-shelf, designing your own IAT may allow you to get at respondents’ implicit attitudes towards something more contextual. We added a custom IAT to a survey of commuters in Rio de Janeiro, and here we'll go over the practical steps involved. For our project, we wanted to measure male and female commuters’ implicit attitudes towards women riding the subway on the co-ed car relative to women riding the women’s-only car. The idea was to quantify the stigma women may face for not using gender-segregated spaces.
How to do Implicit Association Test?
A new collection of papers – Towards Gender Equity in Development – sets out to “explore key sources of female empowerment and discuss the current challenges and opportunities for the future” in three categories: marriage, outside options, and laws and cultural norms. The final published book is available for free, and the individual chapters are available as working papers.
In the introduction, Anderson, Beaman, and Platteau discuss the current landscape of gender discrimination in low- and middle-income countries. In a set of tables that I’ve transformed into a single, completely unwieldy figure. We see discrimination in social norms, legal rights, and marriage indicators. (In all of these indicators, 100% is the worst; 0% is the best.) What stands out is that while no single region dominates the discrimination landscape, every region has significant room to improve. West Africa has high rates of female genital mutilation, South Asia has high rates of son bias, Central Africa has high rates of polygyny, West Asia has high mobility restrictions on women, and the Caribbean has few to no laws against harassment.
Last weekend, the North East Universities Development Consortium held its annual conference, with more than 160 papers on a wide range of development topics and from a broad array of low- and middle-income countries. We’ve provided bite-sized, accessible (we hope!) summaries of every one of those papers that we could find on-line. Check out this collection of exciting new development economics research!
The papers are sorted by topic, but obviously many papers fit with multiple topics. There are agriculture papers in the behavioral section and trade papers in the conflict section. You should probably just read the whole post.
If you want to jump to a topic of interest, here they are: agriculture, behavioral, climate change, conflict, early child development, education, energy, finance, firms and taxes, food security, gender, health and nutrition, households, institutions and political economy, labor and migration, macroeconomics, poverty and inequality, risk management, social networks, trade, urban, and water, sanitation, and hygiene (WASH).
One of the arguments in favor of more gender diversity in the economics profession is that men and women bring distinct perspectives to research and are interested in answering different research questions. We focus in on development economics in this post and examine how the research topics studied by men and women differ.
Did you miss this year’s Northeast Universities Development Consortium conference, or NEUDC? I did, unfortunately!
NEUDC is a large development economics conference, with more than 160 papers on the program, so it’s a nice way to get a sense of new research in the field.
Thankfully, since NEUDC posts submitted papers, I was able to mostly catch up. I went through 147 of the papers and summarized them below, by topic. If a paper you loved or presented isn’t in the rundown, feel free to add a brief summary in the comments. (Why 147 instead of 160? I skipped a few macro papers and the papers that weren’t posted.)
These links should take you to your topic of interest: Agriculture, cash transfers and asset transfers, credit and insurance, crime, conflict, violence, and war, culture, norms, and corruption, education, elections and political economy, firms, governance, bureaucracy, and social capital, health (including WASH), jobs (including public works), marriage, methodology, migration, mobile phones and mobile money, poverty, inequality, and shocks, psychology, taxes, and traffic.
The rigorous evidence on vocational training programs is, at best, mixed. For example, Markus recently blogged about some work looking at long term impacts of job training in the Dominican Republic. In that paper, the authors find no impact on overall employment, but they do find a change in the quality of employment, with more folks having jobs with health insurance (for example).