In the outskirts of the capital Addis Ababa, where a lot of rural-urban migrants settle, one starting point into the city’s formal labor market is the country’s burgeoning ready-made garment industry. Ethiopia represents one of the lowest-cost manufacturing destinations in the world. Firms tend to pay extremely low wages clustered around the local poverty line. They offer little to no upward mobility, so that the vast majority of workers will not advance past the level of machine operators. With its low but stable wages and almost no skill requirements, the ready-made garment industry provides what Blattman and Dercon have called an “industrial safety net.”
This is the third in this year's series of posts by PhD students on the job market.
A firm’s success rides heavily on the performance of its employees. It is therefore important that firms design employment contracts that properly incentivize hard work. This becomes more challenging when firms cannot observe the amount of effort employees invest, nor the amount of output they produce. In theory, firms can use monitoring technologies that reveal the performance of their workers more accurately to overcome this constraint (Holmstrom, 1979). In practice, however, the impact of such monitoring technologies on contracts and employee performance is unclear. Managers may not know how to leverage the additional information monitoring technologies reveal. Moreover, weak legal institutions, which prevent companies from credibly sanctioning bad behavior, may limit how useful the new information actually is.
In my job market paper - co-authored with Gregory Lane and David Schönholzer – we study the impact of moral hazard on labor contracting, employee behavior, and the extent to which improved monitoring affects firm operations. We also establish whether any gains to companies come at the expense of their workers, or society at large. To this end, we implement a randomized control trial where we introduce a monitoring device to 255 firms (vehicle owners) operating in Kenya’s transit industry. We design a novel mobile application that provides information to 125 treatment firms regarding: the location of the vehicle, number of kilometers driven, number of hours the ignition was on, and the number of safety violations incurred (sharp-braking, sharp-turning, over-acceleration and speeding). We confirm that 70% of owners consult the app weekly. This information provides treatment owners with a more precise estimate of what revenue should be, and whether drivers are engaging in behavior that damages the vehicle. This has implications for the owners’ choice of contract and drivers’ behavior, which ultimately impact firm profits/growth. We use daily surveys from vehicle owners and drivers over six-months to track the impact of reducing asymmetric information on these outcomes.
- A lovely remembrance of TN Srinivasan by Abhijit Banerjee – T.N. was a professor at Yale when I studied, and then also a visitor at Stanford when I was first there as an assistant professor. He had a well-deserved reputation as tough but kind – and was the co-founder of the JDE, co-editor of the Handbooks in Development Economics, and given his work in pushing India to open up, likely helped to lift more people out of poverty than most development economists.
- Andrew Gelman on why robustness tests can be a joke, especially if used for confirmation rather than exploration.
- Annette Brown on what not to do in a replication study
This is the second in this year's series of posts by PhD students on the job market.
Each evening the sun sets more than 90 minutes later in west India than in the east of the country. This is because time on clocks across India are set to Indian Standard Time, regardless of location. In China all clocks are set to Beijing Time, which means in western part of the country the sun sets 3 hours later than the east of the country. The sun sets at least an hour later in Madrid than in Munich because Franco’s Spain switched clocks ahead one hour to be in sync with Nazi Germany in 1940, even though Spain is geographically in line with Britain, not Germany. Similarly, for a range of historical reasons, clocks in large parts of the planet – e.g., France, Algeria, Senegal, South Sudan, Russia, and Argentina – are set to be ahead of their (solar) time. Therefore, these places see the sun set later in the day. In my job market paper, I show that these arbitrary clock conventions -- by generating large discrepancies in when the sun sets across locations -- help determine the geographic distribution of educational attainment levels.
This is the first in this year's series of posts by PhD students on the job market.
Developed countries have recently begun considering wealth taxes to raise revenue and curb rising inequality. Should developing countries follow suit? On the one hand, developing countries are often afflicted by acute income and wealth inequality (Alvaredo et al., 2018), and could thus benefit from a more progressive tax system. On the other hand, the question remains whether governments can enforce wealth taxes on an elite that have a vast arsenal of tools to avoid and evade taxes altogether.
My job market paper explores individual responses to personal wealth taxes and enforcement policies in Colombia. Colombia provides a unique opportunity to study these issues thanks to its extensive administrative tax microdata on the assets and debts of wealthy individuals, its numerous tax policy changes since 2002, and its recent enforcement efforts to improve compliance among the rich.
- The Wall Street Journal discusses the synthetic control method as a way to understand Brexit (gated): “There are small differences in the various studies, but they all use Prof. Abadie’s method as the basis for constructing a “doppelganger” U.K. from other similar advanced economies, such as the U.S., Canada, France and the Netherlands. They reach similar conclusions, suggesting the British economy at the start of 2018 was around 2% smaller than it would have been had the 2016 referendum gone the other way”
- Market-level experimentation: In the Harvard Business Review, How Uber used synthetic control methods combined with experiments to decide whether to launch Express Pool.
How to use evidence to influence policy? Oxfam Great Britain has some experience in this area, and in a new paper by some of their team – “Using Evidence to Influence Policy: Oxfam’s Experience” – they lay out the lessons they’ve learned over the years. Here are 8 lessons we gleaned from their experience.
1. “One of the least effective ways to use research for influence is to write a paper and then ask ‘right, who do I send it to?’” Making sure that your published paper gets into the right hands is worthwhile, but it’s far more effective to design research with policy impact in mind. With impact evaluations, that often involves co-producing research questions with government or non-profit partners. But it can also involve asking questions that you know are relevant to current policy debates (and answering them before the debates have concluded). As economist Rachel Glennerster recently wrote, “Answer a really important hotly contested question well.”
Should governments aiming to improve job opportunities devote additional resources towards trying to provide programs that attempt to generate marginal changes in many micro and small firms, or try to target the support towards making larger impacts on a smaller number of high-growth and larger firms? For example, should a government spend an additional $5 million on grants and training programs that support 25,000 micro firms at $200 each, use it to give 100 grants of $50,000 each to 100 high-growth potential firms, or use it as a single $5 million tax incentive to encourage one large multinational to set up a manufacturing plant in the country? I’ve been asked my thoughts on this question quite a few times, so thought I’d share them here.
The answer involves many different trade-offs and considerations, and I attempt to summarize some of the key ones in this post. The bottom line is that there are trade-offs (at least in the short-run) between poverty alleviation and productivity growth, and that different policies will have impacts on different types of job creation. A key lesson for policymakers is to be clear about what the job problem is that they are trying to solve, and not try to use the same policy instrument to achieve multiple competing priorities.
- “The average number of new social safety net programs launched each year in African countries since 2010 exceeded 10” – Kathleen Beegle on the Africa Can End Poverty blog discusses the rise of social safety nets in Africa.
- The Declare Design team remind you to stratify your cluster-randomized experiments by cluster size.
- With the job market coming up, a paper on the characteristics of “job market stars” – one factoid is that in development more than half the stars are female, compared to only 20% of all stars...another is that “not a single star student for six years running has taken a permanent job in industry”.
- On VoxDev, Gordon Hanson and Amit Khandelwal discuss using night-light intensity to measure markets- with a comparison to what daytime satellite imagery reveals, and a note that combining the two provides the best results – “daytime imagery is particularly well-suited for defining the extent of market areas, and that nightlight imagery is useful for capturing the intensity of activity within these market boundaries”
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).