Knowledge that Transforms

This paper advances the proposition that economics, as a discipline, gives rewards that favor the “hard” and disfavor the “soft.” Such bias leads economic research to ignore important topics and problems that are difficult to approach in a “hard” way—thereby resulting in “sins of omission.” This paper argues for reexamination of current institutions for publication and promotion in economics—as it also argues for greatly increased tolerance in norms for publication and promotion as one way of alleviating narrow methodological biases.

We examine the record of cross-country growth over the past fifty years and ask if developing countries have made progress on closing the income gap between their per capita incomes and those in the advanced economies. We conclude that, as a group, they have not and then survey the literature on absolute convergence with particular emphasis on that from the last decade or so. That literature supports our conclusion of a lack of progress in closing the income gap between countries. We close with a brief examination of the recent literature on cross-individual distribution of income, which finds that despite the lack of progress on cross country convergence, global inequality has tended to fall since 2000.

The method of model averaging has become an important tool to deal with model uncertainty, for example in situations where a large amount of different theories exist, as are common in economics. Model averaging is a natural and formal response to model uncertainty in a Bayesian framework, and most of the paper deals with Bayesian model averaging. The important role of the prior assumptions in these Bayesian procedures is highlighted. In addition, frequentist model averaging methods are also discussed. Numerical techniques to implement these methods are explained, and I point the reader to some freely available computational resources. The main focus is on uncertainty regarding the choice of covariates in normal linear regression models, but the paper also covers other, more challenging, settings, with particular emphasis on sampling models commonly used in economics. Applications of model averaging in economics are reviewed and discussed in a wide range of areas including growth economics, production modeling, finance and forecasting macroeconomic quantities.

We review research that measures time preferences-i.e., preferences over intertemporal tradeoffs. We distinguish between studies using financial flows, which we call "money earlier or later" (MEL) decisions and studies that use time-dated consumption/effort. Under different structural models, we show how to translate what MEL experiments directly measure (required rates of return for financial flows) into a discount function over utils. We summarize empirical regularities found in MEL studies and the predictive power of those studies. We explain why MEL choices are driven in part by some factors that are distinct from underlying time preferences.

This paper examines the relationship between placement of publications in top five (T5) journals and receipt of tenure in academic economics departments. Analyzing the job histories of tenure–track economists hired by the top 35 US economics departments, we find that T5 publications have a powerful influence on tenure decisions and rates of transition to tenure. A survey of the perceptions of young economists supports the formal statistical analysis. Pursuit of T5 publications has become the obsession of the next generation of economists. However, the T5 screen is far from reliable. A substantial share of influential publications appear in non-T5 outlets. Reliance on the T5 to screen talent incentivizes careerism over creativity.