M. Ryan Haley

The Response of Worker Effort to Piece Rates Evidence from the Midwest Logging Industry

Using firm-level payroll data from the Midwest logging industry, I compute a worker’s productivity response to a change in piece-rate pay, an elasticity of effort, using an empirical specification developed in Paarsch and Shearer (1999). Maximum-likelihood estimation of an agency-based structural econometric model of worker choice yields elasticities ranging from 0.413 to 1.507. These estimates are smaller than, but qualitatively similar to, those reported in Paarsch and Shearer, suggesting that their model has perhaps more general applicability than their British Columbia tree-planting example.

Generalized Safety First and a New Twist on Portfolio Performance

We propose a Generalization of Roys (1952) Safety First (SF) principle and relate it to the IID versions of Stutzers (Stutzers 2000, 2003) Portfolio Performance Index and underperformance probability Decay-Rate Maximization criteria. Like the original SF, the Generalized Safety First (GSF) rule seeks to minimize an upper bound on the probability of ruin (or shortfall, more generally) in a single drawing from a return distribution. We show that this upper bound coincides with what Stutzer showed will maximize the rate at which the probability of shortfall in the long-run average return shrinks to zero in repeated drawings from the return distribution. Our setup is simple enough that we can illustrate via direct calculation a deep result from Large Deviations theory: in the IID case the GSF probability bound and the decay rate correspond to the Kullback–Leibler (KL) divergence between the one-shot portfolio distribution and the “closest” mean-shortfall distribution. This enables us to produce examples in which minimizing the upper bound on the underperformance probability does not lead to the same decision as minimizing the underperformance probability itself, and thus that the decay-rate maximizing strategy may require the investor to take positions that do not minimize the probability of shortfall in each successive period. It also makes clear that the relationship between the marginal distribution of the one-period portfolio return and the mean-shortfall distribution is the same as that between the source density and the target density in importance sampling. Thus Gewekes (1989) measure of Relative Numerical Efficiency can be used as a measure of the quality of the divergence measure. Our interpretation of the decay rate maximizing criterion in terms of a one-shot problem enables us to use the tools of importance sampling to develop a “performance index” (standard error) for the Portfolio Performance Index (PPI). It turns out that in a simple stock portfolio example, portfolios within one (divergence) standard error of one another can have very different weights on individual securities.

Ranking top economics and finance journals using Microsoft academic search versus Google scholar: How does the new publish or perish option compare?

Recently, Harzings Publish or Perish software was updated to include Microsoft Academic Search as a second citation database search option for computing various citation‐based metrics. This article explores the new search option by scoring 50 top economics and finance journals and comparing them with the results obtained using the original Google Scholar‐based search option. The new database delivers significantly smaller scores for all metrics, but the rank correlations across the two databases for the h‐index, g‐index, AWCR, and e‐index are significantly correlated, especially when the time frame is restricted to more recent years. Comparisons are also made to the Article Influence score from eigenfactor.org and to the RePEc h‐index, both of which adjust for journal‐level self‐citations.

Rank variability of the Publish or Perish metrics for economics and finance journals

This article analyses the 10 citation-based journal ranking metrics reported by Harzings (2007) Publish or Perish (PoP) software (http://www.harzing.com/pop.htm) for 163 economics and finance journals. The results indicate that the 10 metrics produce rankings that are highly correlated. However, closer examination reveals that the variability in rank across the 10 metrics is significantly larger for some journals than others; this article identifies journals for which this is most poignant and offers possible solutions.

The skill transferability of high-skilled US immigrants

Using the 2000 US Census data, we explored the effect of international transferability of skills on the earnings of high-skilled US immigrants. We confirmed that education and labour market experience received by immigrants from Japan and English-speaking developed countries before migrating have the greatest transferability; immigrants from non-English-speaking and Less Developed Countries (LDCs) make a greater investment in US-specific skills after arrival and earn a salary commensurate with the acquired skill level. Nevertheless, high-skilled workers from English-speaking developed countries still receive higher earnings, other things equal. We explore factors that influence this earnings differential.

Smoothed safety first and the holding of assets

We construct a simple nonparametric portfolio selection rule by minimizing an approximation to the empirical shortfall probability using a smooth sigmoid-shaped function, and then compare the performance of our rule with the Sharpe ratio and the Portfolio Performance Index. Monte Carlo simulations, an application, and bootstrap results suggest our method is competitive with existing methods, offering portfolios with a good balance of expected return, variance, skewness, and especially small shortfall probabilities. Our rule may be of particular interest to fund managers whose primary concern is minimizing the probability of realizing a fund return below some predetermined benchmark or target rate.

Generalized Safety First and the Planting of Crops

This article adapts a modern shortfall-based portfolio selection rule developed by Stutzer (2000) and Haley and Whiteman (2008) to the farm managers land allocation problem. The approach provides a useful normative model of land allocation that obviates distributional assumptions and expected utility specifications, and one that selects an optimal allocation that weighs skewness and other higher order moments in addition to mean and variance. This is of particular interest because crop returns often exhibit skewness, which is not accounted for by traditional Mean-Variance (MV)-based approaches. The rule is demonstrated using the data from Lence and Hart (1997).

Adverse selection, seller reputation and buyer insurance in online auctions for 1960s-era collectible baseball cards

We investigate the differences between Beckett book values and eBay auction prices using an original data set of 876 auctions for 30 baseball cards from the 1960s era. We find that cards of lower quality generally sell (on eBay) above book price, whereas cards of higher quality generally sell below book price. We find that both the presence of buyer insurance and the number of bids increase eBay prices relative to book values and that the sellers reputation and the number of bids increase the probability that the eBay price will be greater than the corresponding book value.

On the inauspicious incentives of the scholar-level h-index: an economist’s take on collusive and coercive citation

ABSTRACT Faculty renewal, promotion, tenure, merit and awards are typically tied to scholarship performance, which is often measured in several ways, among them citation-based metrics like the scholar-level h-index. With the relatively recent developments of ‘one-touch’ Google Scholar citation tracking and Harzing’s Publish or Perish Software, it is simple to monitor and potentially game one’s personal h-index. This article explores this possibility by assessing the incentives embedded in the scholar-level h-index through the lens of cartels, uncertainty, insurance and game-theoretic best response.

Shortfall minimization and the Naive (1/N) portfolio: an out-of-sample comparison

ABSTRACT Naive portfolio selection, wherein an investor allocates an equal portion of their wealth to the field of candidate assets, is a simple ad-hoc way to create a portfolio. Naive portfolio selection contrasts to the many sophisticated portfolio selection rules that are optimal with respect to a specific portfolio allocation objective and which often perform well in sample. However, some recent research finds that many of these ‘optimal’ portfolio allocation mechanisms perform no better than naive diversification in out-of-sample data. This paper extends this line of inquiry by comparing the out-of-sample performance of naive portfolio selection to several recently developed shortfall-minimizing portfolio selection methods. The results corroborate the prior findings that optimal portfolio methods struggle to beat the naive portfolio in out-of-sample environments.