This paper describes recent modifications to the mixed-frequency model vector autoregression (MF-VAR) constructed by Schorfheide and Song (2012). The changes to the model are restricted solely to the set of variables included in the model; all other aspects of the model remain unchanged. Forecast evaluations are conducted to gauge the accuracy of the revised model to standard benchmarks and the original model.

This paper uses an estimated structural model to argue that the option to move in and out of the parental home is an important insurance channel against labor market risk for youths who do not attend college. Using data from the NLSY97, I construct a new monthly panel of parent-youth coresidence outcomes and use it to document an empirical relationship between these movements and individual labor market events. The data is then used to estimate the parameters of a dynamic game between youths and their altruistic parents, featuring coresidence, labor supply and savings decisions. Parents can provide both monetary support through explicit financial transfers, and non-monetary support in the form of shared residence. To account for the data, two types of exogenous shocks are needed. Preference shocks are found to explain most of the cross-section of living arrangements, while labor market shocks account for individual movements in and out of the parental home. I use the model to show that coresidence is a valuable form of insurance, particularly for youths from poorer families. The option to live at home also helps to explain features of aggregate data for low-skilled young workers: their low savings rates and their relatively small consumption responses to labor market shocks. An important implication is that movements in and out of home can reduce the consumption smoothing benefits of social insurance programs.

We propose a model of delegated portfolio management with career concerns. Investors hire fund managers to invest their capital either in risky bonds or in riskless assets. Some managers have superior information on the default probability. Looking at the past performance, investors update beliefs on their managers and make firing decisions. This leads to career concerns which affect investment decisions, generating a positive or negative “reputational premium.” For example, when the default probability is high, the return on the risky bond has to be high to compensate the uninformed managers for the high risk of being fired. As the default probability changes over time, the reputational premium amplifies price volatility.

In this paper, we construct a parsimonious overlapping-generations model of human capital accumulation and study its quantitative implications for the evolution of the U.S. wage distribution from 1970 to 2000. A key feature of the model is that individuals differ in their ability to accumulate human capital, which is the main source of wage inequality in this model. We examine the response of this model to skill-biased technical change (SBTC), which is modeled as an increase in the trend growth rate of the price of human capital starting in the early 1970s. The model displays behavior that is consistent with several important trends observed in the US data, including the rise in overall wage inequality; the fall and subsequent rise in the college premium, as well as the fact that this behavior was most pronounced for younger workers; the rise in within-group inequality; the stagnation in median wage growth; and the small rise in consumption inequality despite the large rise in wage inequality. We consider different scenarios regarding how individuals’ expectations evolve during SBTC. Specifically, we study the case where individuals immediately realize the advent of SBTC (perfect foresight), and the case where they initially underestimate the future growth of the price of human capital (pessimistic priors), but learn the truth in a Bayesian fashion over time. Lack of perfect foresight appears to have little effect on the main results of the paper. Overall, the model shows promise for explaining a diverse set of wage distribution trends observed since the 1970s in a unifying human capital framework.

Search theory routinely assumes that decisions about the acceptance/rejection of job offers (and, hence, about labor market movements between jobs or across employment states) are made by individuals acting in isolation. In reality, the vast majority of workers are somewhat tied to their partners—in couples and families—and decisions are made jointly. This paper studies, from a theoretical viewpoint, the joint job-search and location problem of a household formed by a couple (e.g., husband and wife) who perfectly pools income. The objective of the exercise, very much in the spirit of standard search theory, is to characterize the reservation wage behavior of the couple and compare it to the single-agent search model in order to understand the ramifications of partnerships for individual labor market outcomes and wage dynamics. We focus on two main cases. First, when couples are risk averse and pool income, joint search yields new opportunities—similar to on-the-job search—relative to the single-agent search. Second, when the two spouses in a couple face job offers from multiple locations and a cost of living apart, joint search features new frictions and can lead to significantly worse outcomes than single-agent search.

Recent studies say prices change about every four months. Economists have interpreted this high frequency as evidence against the importance of sticky prices for the real effects of monetary policy. Theory implies that this interpretation is correct if most price changes are regular, but not if most are temporary, as in the data. Temporary changes have a striking feature: after such a change, the nominal price tends to return exactly to its preexisting level. We study versions of Calvo and menu cost models that replicate this feature. Both models predict that the degree of aggregate price stickiness is determined mostly by the frequency of regular price changes, not by the combined frequency of temporary and regular price changes. Since regular prices are sticky in the data, the models predict a substantial degree of aggregate price stickiness even though micro prices change frequently. In particular, the aggregate price level in our models is as sticky as in standard models in which micro prices change about once a year. In this sense, prices are sticky after all.

This memo describes a revision to the mixed-frequency vector autoregression (MF-VAR) model originally constructed by Schorfheide and Song (2012) and subsequently revised by Beauchemin (2013). In this most recent version, the 14-variable model is expanded to include nonfarm payroll employment. The forecast performance of the augmented model is compared with that of its predecessor.