Should we use standardized inequality databases such as SWIID?

Here is my implicit point of view regarding the debate between Jenkins (2015) and Solt (2016):
Below is a table (Table 1) from Rudra (2004).
Do you notice anything strange about these Gini-coefficients? Hint: to verify inequality data, I always look at the country I know best, to see if data make sense...

[I will update this post with my thoughts eventually]

Clearly, something is wrong with the data regarding Sweden in the 1970s. The table suggests that inequality in Sweden was at its lowest level in 1975 (at 27.3) and at its highest level just a year later, in 1976 (33.1). In a country like Sweden, inequality never jumps that much from one year to another, and for sure not in 1976. Reexamining the Deininger and Squire database, it turns out that the 1975 value comes from the LIS database, whereas the 1976 value is taken from Statistics Sweden. Most likely, the latter includes capital income and the former does not. Checking other figures reveals that mosty data for Sweden are net household income, but for Brazil gross income is used, and for China the unit is the individual, not the household.

Rudra is not alone. In fact, she is better than many other papers because the inclusion of a table like Table 1 above means that the errors are possible to spot by reading the paper closely. Often, D&S data are just added to the analysis without even a simple visual inspection, which means that the analysis uses incomparable Ginis.

One of the biggest benefits of Solt's Swiid, is that all Ginis are converted to the same typ (LIS-standard), and mistakes like these are avoided.

References:
Jenkins, Stephen P. 2015. "World Income Inequality Databases: An Assessment of Wiid and Swiid." Journal of Economic Inequality 13(4):629–71.
Rudra, N. 2004. "Openness, Welfare Spending, and Inequality in the Developing World." International Studies Quarterly 48(3):683-709. doi: 10.1111/j.0020-8833.2004.00320.x.
Solt, Frederick. 2016. "On the Assessment and Use of Cross-National Income Inequality Datasets." Journal of Economic Inequality (forthcoming).

Is degrowth a well-defined concept?

I recently found out that there is an "academic association dedicated to research, training, awareness raising and events organization around degrowth". This is how they define the central concept, "degrowth":
Sustainable degrowth is a downscaling of production and consumption that increases human well-being and enhances ecological conditions and equity on the planet. It calls for a future where societies live within their ecological means, with open, localized economies and resources more equally distributed through new forms of democratic institutions. Such societies will no longer have to “grow or die."
The definition is puzzling for several reasons:
  1. The definition of degrowth starts by defining "Sustainable degrowth". Are these the same? Is degrowth in itself unsustainable? How does (sustainable) degrowth relate to the (also somewhat vague) concept sustainable growth?
  2. The definition of degrowth (or possibly sustainable degrowth) contains a number of concepts that can be defined in a number of ways: human well-being and equity on the planet. Possibly, enhanced ecological conditions should be counted as well. What is gained by lumping two (or three) vague concepts into a new concept without clarifying what is meant by well-being, equity and enhanced ecologiocal conditions?
  3. Apparently, (sustainable) degrowth "calls for a future", suggesting that it is an agent that can act. Based on the definition that was just given, it is unclear how degrowth can call for any type of future. More generally, growth - regardless of type - does not call for anything, it is a term used to decribe something (for example growth of GDP per capita).
  4. Apparently (sustainable) degrowth is a type of growth that calls for "new forms of democratic institutions". Sure. Let's assume that the two sentences cited so far would appear in a student paper. Most serious university teachers would have a talk with the student, advising him/her to be more precise. Or just stop reading. In this case, lets read just a little more:
  5. 'Such societies will no longer have to “grow or die." ' The phrase "grow or die" seems to be cited, but there is no source. The definition is now polemic. But where are the societies that must "grow or die"? There are plenty of societies with low, no or even negative growth (as measured for example by GDP per capita). They don't die, they have constant or shrinking GDP per capita, the consequences of which can and (has been) both examined and discussed. The argument that some (all? capitalist?) societies must "grow or die" is a straw-man. But most importantly: Why does the definition of degrowth contain a normative argument?
There may well be good answers to all of these questions - after all, degrowth is an official theme at the prestigious Pufendorf Institute at Lund University.

On the cult of science and the replication crisis

A thoughtful text by William A. Wilson on the replication crisis, including a nice explanation of Bayesian statistics:
Suppose that there are a hundred and one stones in a certain field. One of them has a diamond inside it, and, luckily, you have a diamond-detecting device that advertises 99 percent accuracy. After an hour or so of moving the device around, examining each stone in turn, suddenly alarms flash [...] What is the probability that the stone contains a diamond? [...] if we were to wave the detector over every stone in the field, it would, on average, sound twice—once for the real diamond, and once when a false reading was triggered by a stone. If we know only that the alarm has sounded, these two possibilities are roughly equally probable, giving us an approximately 50 percent chance that the stone really contains a diamond.
More:
once an entire field has been created—with careers, funding, appointments, and prestige all premised upon an experimental result which was utterly false due either to fraud or to plain bad luck—pointing this fact out is not likely to be very popular.
The defense:
Many defenders of the scientific establishment will admit to this problem, then offer hymns to the self-correcting nature of the scientific method.
The counter attack:
So the dogma goes. But these claims are rarely treated like hypotheses to be tested. Partisans of the new scientism are fond of recounting the “Sokal hoax"—physicist Alan Sokal submitted a paper heavy on jargon but full of false and meaningless statements to the postmodern cultural studies journal Social Text, which accepted and published it without quibble—but are unlikely to mention a similar experiment conducted on reviewers of the prestigious British Medical Journal.
The bottom line:
When cultural trends attempt to render science a sort of religion-less clericalism, scientists are apt to forget that they are made of the same crooked timber as the rest of humanity and will necessarily imperil the work that they do. The greatest friends of the Cult of Science are the worst enemies of science’s actual practice.

Absolute poverty is falling. What role does globalization play?

The fact that global absolute poverty is falling, is spreading. It is not uncommon to tweet graphs like the one below, illustrating the good news. But why is poverty falling? Is it happening because of globalization, or perhaps despite globalization?
A standard view, made famous by Dollar and Kraay (2004) is that globalization leads to growth, which leads to falling absolute poverty. When they wrote their paper, there was not enough data to systematically test the globlization-poverty relationship. That would change rapidly.
Testing the link between globalization and absolute poverty using data on up to 114 countries over the period 1983-2007, Bergh and Nilsson (2014) confirmed that more globalization is indeed followed by decreasing poverty, but only a small part is explained by the growth of average income levels. Theoretically, globalization can lead to growth without decreasing poverty or it could lead to falling poverty without increasing growth (though especially the latter is unlikely when longer time spans are considered). In all, it seems that the relationship between globalization and poverty is better described by the picture to the right below, compared to the standard view (to the left).
What is globalization?
A relevant question at this stage is to ask 'Exactly what is globalization?' Globalization typically refers to the process by which different
economies and societies become more closely integrated. A nice measure often used in research is the KOF-index of globalization (Dreher et al. 2008), which allows different dimensions of globalization can be examined in detail, separating economic, social and political globalization. As it turns out, the strongest link to falling poverty are found not for economic globalization in the sense of trade flows (exports plus imports as a share of GDP), but rather from trade restrictions (such as tariffs) and information flows (eg. Internet, Radio, TV and Newspapers).

Is it only about India and China?
It is sometimes noted that most of the global decrease in poverty is explained by the development in China and to some extant also in India. It is true that in any population weighted description of global development, China will dominate. Those who are interested in population weighted development might as well do a case study of China.
In the cross country data analysis, however, the rule is that each country is one observation. Interestingly, the world bank data separates urban china from rural china. Thus, India and China are 3 (!) of the roughly 100 countries studied.

Perhaps globalization is good for the poor only when institutions are good?
While the correlation seems relatively robust on average, one might still worry that globalization is pro-poor only when corruption is low/institutional quality is high/quality of government is high. As expressed by Sindzingre (2005) in an UNU-WIDER report:
[...]the effect of globalization is likely to be heterogeneous with respect to institutional quality, because ‘[i]nstitutions [...] determine whether the benefits of globalization are spread to the poor or are locked in by particular groups’
Theoretically, this might seem plausible. On the other hand, the marginal impact of say free information flows may well be higher where institutional quality is low. Empirically, it turns out that the pattern is exactly the opposite of what Sindzingre suggested. Using various components from the International Country Risk Guide to quantify institutions such as government stability, law and order, bureaucratic quality, corruption and democratic accountability, in combination with the data from Bergh & Nilsson (2014), we showed in a follow-up paper (Bergh, Mirkina and Nilsson 2015) that the poverty-decreasing effect of globalization is bigger in countries where institutions are worse. The graph below shows how the marginal effect of information flows on poverty varies depending on the level of bureaucratic quality. The slope looks the same for all institutional indicators, suggesting that globalization is especially important for the poor in countries with high corruption levels and inefficient public sectors.

What about causality?
Clearly, cross-country correlations do not prove that there is a causal effect of globalization on poverty-reduction. Whether you see this as a big problem or not, depends on what question you are ultimately interested in. If you want to know what would happen if some countries randomly 'globalized', and other not, then you are left in the dark (and probably will be so for a long time). On the other hand, if you are interested in what happend to the countries that actually globalized in various ways and for various reasons during the 1983 to 2007 period, the result is both interesting and robust. The sample covers almost all developing countries, and the model is estimated using variation over time within countries, using 5 year averages.
To put it differently, the data show rather convincingly that globalization has been good for the poor, but you should still be careful when giving policy advice to countries.
This said, Bergh and Nilsson (2014) does contain two instrumental variable approaches, using lagged globalization in neighborig countries, and the duration of McDonalds presence as instruments for globalization. Still far from a randomized experiment, these approaches confirm that the variation in globalization that is imposed on countries by McDonalds entering, or by neighbouring countries becoming more open, is also negatively related to absolute poverty.

Enough with this fixed-effect,2SLS nonsense! What does a scatter plot relating levels of globalization to absolute poverty rates look like?
Like this (from Bergh and Nilsson 2014):

For more on the effects of globalization, see the excellent survey by Potrafke (2015).
References:
Bergh, A. and T. Nilsson (2014). "Is Globalization Reducing Absolute Poverty?" World Development 62 (0): 42-61.
Bergh, A., et al. (2015). "Do the poor benefit from globalization regardless of institutional quality?" Applied Economics Letters: 1-5.
Dreher, A., et al. (2008). Measuring Globalisation: Gauging Its Consequences, Springer.
Dollar, D. and A. Kraay (2004). "Trade, Growth, and Poverty." The Economic Journal 114 (493): F22-F49.
Sindzingre, A. (2005). "Explaining Threshold Effects of Globalization on Poverty: An Institutional Perspective." World Institute for Development Economic Research (UNU-WIDER), Working Paper RP2005:53.
Potrafke, N. (2015). "The Evidence on Globalisation." The World Economy 38 (3): 509-552.

On wealth inequality and growth

Is wealth inequality bad for growth? That depends on its origins, according to a new paper by Sutirtha Bagchia and Jan Svejnarb:
The abstract:
A fundamental question in social sciences relates to the effect of wealth inequality on economic growth. Yet, in tackling the question, researchers have had to use income as a proxy for wealth. We derive a global measure of wealth inequality from Forbes magazine's listing of billionaires and compare its effect on growth to the effects of income inequality and poverty. Our results suggest that wealth inequality has a negative relationship with economic growth, but when we control for the fact that some billionaires acquired wealth through political connections, the relationship between politically connected wealth inequality and economic growth is negative, while politically unconnected wealth inequality, income inequality, and initial poverty have no significant relationship.

Graeme Leach: Forget Nordic exceptionalism: Scandinavia grew wealthy despite big government

The Nordic Model has become the intellectual battleground over which the big versus small state war has played out in the twenty-first century. Scandinavian countries have seemingly perplexed free market economists with their ability to achieve world-class competitiveness rankings and high per capita incomes, while at the same time operating very high tax and public spending levels as a proportion of GDP. But a close look at the evidence shows that the Nordic economies aren’t exceptional at all. They don’t defy the economic laws of gravity, they confirm them. When the size of government really started to grow in the 1960s and 1970s, there was economic stagnation. [...]
These economies offset the negative effects of large governments by applying market-friendly policies in other areas, such as trade openness. The Scandinavian economies have relatively high levels of economic freedom, and on some dimensions of economic freedom actually score higher than the USA.
Small homogenous countries, with high levels of trust, can get away with – up to a point – larger welfare states in a way that larger economies cannot. Trust also reduces “transaction costs" and therefore encourages greater economic activity. So powerful is the effect that some studies show that the positive effect of trust outweighs the negative effect of big government on growth. The danger, of course, is that the rise of the welfare state and a dependency culture undermines trust, makes the welfare state increasingly inefficient, and reduces growth prospects all at the same time.
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"economics research is usually not replicable"

This new working paper by Andrew Chang and Phillip Li has some really disheartening - or even depressing - conclusions:
Abstract We attempt to replicate 67 papers published in 13 well-regarded economics journals using author-provided replication files that include both data and code. Some journals in our sample require data and code replication files, and other journals do not require such files. Aside from 6 papers that use confidential data, we obtain data and code replication files for 29 of 35 papers (83%) that are required to provide such files as a condition of publication, compared to 11 of 26 papers (42%) that are not required to provide data and code replication files. We successfully replicate the key qualitative result of 22 of 67 papers (33%) without contacting the authors. Excluding the 6 papers that use confidential data and the 2 papers that use software we do not possess, we replicate 29 of 59 papers (49%) with assistance from the authors. Because we are able to replicate less than half of the papers in our sample even with help from the authors, we assert that economics research is usually not replicable. We conclude with recommendations on improving replication of economics research.


Wanted: Google scholar embedding

Citations are increasingly being counted in academia, and it is becoming increasingly common to put for example google scholar citation counts on your CV. The weird thing is that to get something like this on a webpage...
...I had to copy my citation count from my google scholar page , which means that it is probably (hopefully...) out of date when you read this.
A little research revealed that apparently it can be done using "R, scholar, ggplot2 and cron", but surely someone at google could let users do it simply by pasting some code the way it is done with youtube videos and whatever.

The fact that this yet does not exist is a bit worrying, but much more worrying is the fact that I seem to be almost the only one looking for an easy way to "embed google scholar citations" - googling this results in exactly one hit [oct 4, 2015].