Are multipliers larger than we thought?

In the last years, much of the debate on fiscal stimulus vs. austerity was centered on the measurement of government spending multipliers. And to a large extend this was a debate between those how used dynamic stochastic general equilibrium (DSGE) models, finding small multipliers, and those using reduced form models, finding large multipliers. Both strategies have pitfalls, the structural one in that the model may be miss-specified as it is always an abstraction of a complex reality, the reduced-form one because of the Lucas Critique.

Patrick Fève, Julien Matheron and Jean-Guillaume Sahuc make the point that there could be a source of downward bias in the estimation of the elasticity in structural models. It arises from ignoring the endogeneity of government expenses combined with complementarity between public and private consumption. With exogenous expenses, the elasticity is 0.97 for the United States, with endogenous ones, it is 1.31. No small potatoes.

Fact of the Day: CEO Pay

Source. 

The relative pay of CEOs skyrocketed during the 1990s and has since fallen by about half.

Tax capital *and* inheritances

I probably do not surprise anyone if I claim that how much to tax capital income and bequests is controversial. In the United States, it is due a divergent beliefs about the motivation of entrepreneurs and luck of being born in the right environment. In Europe, arguments center on fairness. The literature does not help much, with results being very sensitive to income processes, market features and preferences. Capital income is generally taxed less than labor income, often not at all, and results on bequests vary wildly, again often with zero tax results.

Thomas Piketty and Emmanuel Saez add to this bewildering literature with a tour-de-force, a very rich, yet tractable model that allows to disentangle quite a few effects and illustrate what influences these taxes, in particular parameters that can be estimated. The richness is necessary to relate the model to real world better than the extant literature which yields this unrealistic and unobserved zero tax result. It is impossible for me to summarize over 100 pages in a few paragraphs, so here is a short overview.

The model features a large degree of heterogeneity, in taste for bequests and wealth accumulation, and in labor ability. Hence labor income and inheritance are not highly correlated, allowing for a trade-off between capital and labor income taxes because, as Piketty and Saez put it, two-dimensional inequality requires two tax tools. The tax on bequests is higher if bequests represent a large fraction of output, if the aggregate elasticity of bequests with respect to their tax is high, and if the taste for bequests is low. Tax rates on bequests can go all the way to 80%, and are for most parametrizations much higher than for labor income. This is because in general labor income should be favored, as it is derived from ability, unless people really like leaving bequests a lot.

If markets are imperfect and there is risk in capital return, then tax rates of capital income and bequests start differing. The lifetime equivalent of the capital income tax is then much higher than the bequest tax rate. because return fluctuations have stronger impact on periodic capital income than bequests, which are mostly accumulated capital and labor income. Important in this is also that in all economies, most people receive very little if any at all in terms of inheritance. This makes results remarkably robust with respect to welfare criteria.

Being tall and risk aversion

Are tall people less risk-averse than others? That seems like an odd question to ask. In particular, what would one want to do with the answer? Well, if the answer is no, this can help in establishing better insurance policies. Also, if some policies influence height, it is good to know what taller people entails (besides the known higher income and confidence).

Olaf Hübler finds that, yes, tall people are less risk averse. What is more interesting is that this result disappears once you factor in other variables, like personality, skills, and information about parental behavior. That is particularly interesting because such information is often not readily available, whereas height can be easier to find and used as a proxy. So, not such an odd question after all. Another question is then why would there be such a relationship.

On the difficulty of targeting financial aid to students

With the cost of education continuing to rise, financial aid to student becomes more important to help those with merit but little means (or borrowing constraints). Identifying whether financial aid actually helps bright students go to university is of course the most important question.

Loris Vergolini and Nadir Zanini study this in the case of Italy, where they surveyed students before and after university entrance, in the context of a generous financial aid initiative targeted towards bright low-income students. The results are sobering. it does not appear to have motivated more students to go to university. Those who were going anyway now are willing to move farther, presumably to potentially better programs. But this program was only recently introduced and could not have an impact on the school effort of those about to graduate. One can hope that its existence will motivate younger cohorts to excel in school to be eligible and make it to university.

Universities as catalysts of the commercial revolution in the Middle Ages

Universities can have a profound impact on the economy of a region, Silicon Valley being a prime recent example. But this is usually difficult to see as they are spread pretty much everywhere now. Hence the interest in looking at older data, where universities were less common and economic activity differed a lot more across regions.

Davide Cantoni and Noam Yuchtman go way back, up to the 14th century in Germany. They compare the establishment of new market places to the founding of universities and find a surprisingly strong correlation when looking at the distance from the nearest university. Of course, you may think this is all endogenous. If a city or region develops, new market places emerge and there is critical mass or wealth for an institution of higher learning. But the authors argue there is causation from universities to markets. Indeed, the Papal Schism of 1386 was an exogenous shock that allowed the creation of universities, and they exploit the trend shift in the granting of markets around this date. The intuition of the causation is that universities provided training in law, which facilitated the creation of legal institutions and ultimately the enforcement of contracts. So, once more, institutions matters, but this is also an interesting counterexample to the intuition that lawyers create demand for there services with no economic or social benefit.

The cost of hiring in Germany

How much does it cost to hire someone? This question is surprisingly difficult to answer. It is not sufficient to keep a log of all the recruitment expenses, the time spent and the training costs. Indeed, there are a lot of implicit costs that may, or may not, appear in the future. Indeed, when you commit to employ someone, you also commit to insuring this person in many ways. In the US, health care insurance is a factor. In many jurisdictions, rules regarding firing may also entail substantial costs, for example if they force you to retain an underperforming employee. And you often also commit to provide some insurance against productivity changes by paying a relatively stable wage. Summing up, figuring out the cost of a hire is damn hard.

Samuel Muehlemann and Harald Pfeifer try to figure out some of these costs for skilled workers in Germany. They find a cost worth on average eight weeks of pay, and that is only taking into account time and expenses during the recruitment process as well as the monetary and time costs of training. Strangely, there are no economies of scale, as the elasticity with respect to the number of hires is 1.3. Even worse, the cost doubles from small to large firms. Labor market institutions do not seem to be blamed for this convexity. I am not sure how to rationalize all this. Large firms can hire several workers simultaneously, and this must save some costs. Same for training programs.