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Can Wealth Taxation Work in Developing Countries? Guest post by Juliana Londoño-Vélez

Development Impact Guest Blogger's picture

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.

Weekly links November 9: a doppelganger U.K., conditional distributions of journal decision times, invisible infrastructure, and more...

David McKenzie's picture
  • 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.

8 lessons on how to influence policy with evidence – from Oxfam’s experience

David Evans's picture

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.”  

Marginal changes for the many or focusing on the few? Trade-offs in firm support policies and jobs

David McKenzie's picture

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.

Weekly links November 2: harnessing shame, measuring markets, African safety nets and apprenticeships, rugby, and more...

David McKenzie's picture
  • “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”

What’s the latest in development economics research? Microsummaries of 150+ papers from NEUDC 2018

David Evans's picture



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).

A Curated List of Our Postings on Technical Topics – Your One-Stop Shop for Methodology

David McKenzie's picture
This is a curated list of our technical postings, to serve as a one-stop shop for your technical reading. I’ve focused here on our posts on methodological issues in impact evaluation – we also have a whole lot of posts on how to conduct surveys and measure certain concepts curated here. In lieu of our regular links this week, it is updated up to October 25, 2018
General

Some advice from survey implementers: Part 2

Markus Goldstein's picture

This is part 2 of a two part blog on what survey implementers would tell the researchers and others who work with them (part one is here).   Before we dive in, I want to reiterate my thank to the folks at EDI and IPA, as well as James Mewera of the Invest in Knowledge Initiative, Ben Watkins at Kimetrica,  and Firman Witoelar at SurveyMeter who took the time to send me really careful thoughts and then answer my queries.   As before, don’t take anything below as something specific any one of them said – I’ve edited, adjusted and merged.   Blame me if you don’t like it.  One final note, as you can see from the list, not everyone one of these is a commercial firm, and some of them do research as well – so not only keep that in mind when filtering the advice, but I’ll abbreviate with SO for survey organization.     
 
Please read this post as me channeling and interpreting their voices.  I am not sure I agree with everything I heard, but I am passing it on.   And all of it gave me food for thought.   Stuff in [italics] is me explicitly responding to a couple of points.   
 

Most good you can do. But for whom?

Berk Ozler's picture

It’s hard to argue against the idea that giving cash to someone in need is the best you can do for that person in most circumstances: money maximizes your choice set and any conditions, strings attached, etc. makes that set smaller. With the advance of mobile technologies and better, bigger data, you can now send someone anywhere in the world money and make that person’s life instantly better – at least in the short run. But, what if I told you that with every dollar you send to one poor person, you’re taking away food from a few other people? How should we evaluate the impact of your transfer then?

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