Using life insurance holdings by age, sex, and marital status, we infer how individuals value consumption in different demographic stages. We estimate equivalence scales and bequest motives simultaneously within a fully specified model where agents face US demographics and save and purchase life insurance. Our findings indicate that individuals are very caring for dependents, that economies of scale are large, that children are very costly (or yield very high marginal utility), that wives with children produce lots of home goods, and that females display habits from marriage, while men do not. These findings contrast sharply with standard equivalence scales.

We find that technology's effect on employment varies greatly across manufacturing industries. Some industries exhibit a temporary reduction in employment in response to a permanent increase in TFP, whereas many more industries exhibit an employment increase in response to a permanent TFP shock. This raises serious questions about existing work that finds a labor productivity shock has a strong negative effect on employment. There are tantalizing and interesting differences between TFP and labor productivity. We argue that TFP is a more natural measure of technology because labor productivity reflects shifts in the input mix as well as in technology.

We address how using different censoring thresholds and imputation procedures affects the baseline results of Coibion, Gorodnichenko, and Hong (2015). Higher censoring thresholds introduce measure ment error and outliers that generate wide variability in results across weighting schemes, but methods that explicitly control for outliers confirm the results of Coibion, Gorodnichenko, and Hong (2015) for all censoring thresholds. We also illustrate how the BLS’s approach to imputing missing prices can introduce a cyclical bias into measures of posted price inflation when store-switching is present in the data.

We study the cyclical properties of sales, regular price changes, and average prices paid by consumers (“effective” prices) using data on prices and quantities sold for numerous retailers across many US metropolitan areas. Inflation in the effective prices paid by consumers declines significantly with higher unemployment while little change occurs in the inflation rate of prices posted by retailers. This difference reflects the reallocation of household expenditures across retailers, a feature of the data which we document and quantify, rather than sales. We propose a simple model with household store-switching and assess its implications for business cycles and policymakers.

We investigate the effect of scale on performance in the active money management industry. We first document that fund returns, both before and after fees and expenses, decline with lagged fund size, even after accounting for various performance benchmarks. We then explore a number of potential explanations for this relationship. This association is most pronounced among funds that have to invest in small and illiquid stocks, suggesting that these adverse scale effects are related to liquidity. Controlling for its size, a fund's return does not deteriorate with the size of the family that it belongs to, indicating that scale need not be bad for performance depending on how the fund is organized. Finally, using data on whether funds are solo-managed or team-managed and the composition of fund investments, we explore the idea that scale erodes fund performance because of the interaction of liquidity and organizational diseconomies.

A variety of identification strategies have a common cell structure, in which the observed heterogeneity of the regression defines a partition of the sample into cells. Typically in the presence of exogenous covariates that define the cell structure, identification assumptions are imposed conditional on each value of the covariate, or cell by cell. Treatment effects across cells are typically heterogeneous. Researchers might be interested in unconditional parameters which are the averaged treatment effects across the cells. Alternatively, treatment effects can be estimated more efficiently if researchers are willing to impose additional parametric and semiparametric structures on the heterogeneous treatment effects across cells.