Alternative Measures of Offshorability: A Survey Approach

This paper reports on a pilot study of the use of conventional household survey methods to measure something unconventional: what we call offshorability, defined as the ability to perform one’s work duties (for the same employer and customers) from abroad. Notice that offshorability is a characteristic of a person’s job, not of the person himself. We see this research as important for two main reasons. First, one of us has argued previously that offshoring is potentially a very important labor market phenomenon in the United States and elsewhere, perhaps eventually amounting to a third Industrial Revolution. In the first Industrial Revolution, the share of the U.S. workforce engaged in agriculture declined by over 80 percentage points. In the second Industrial Revolution, which is still in progress, the share of American workers employed in manufacturing has declined by almost 25 percentage points so far, with most of the migration going to the service sector. The estimates presented here, like those of Blinder (2009b), suggest that the share of U.S. workers performing what Blinder (2006) called impersonal service jobs (defined precisely below) might shrink significantly while the share performing personal service jobs rises. Second, while readers must judge for themselves, we deem the pilot study to have been successful by several criteria that we will explain later. So we hope our survey methods will be replicated, improved upon, and eventually incorporated into some regular government survey, such as the Current Population Survey (CPS). Doing so would enable the U.S. government to track this important phenomenon over time.offshore, labor migration, employment trends

What Does the Public Know about Economic Policy, and How Does It Know It?

Public opinion influences politicians, and therefore influences public policy decisions. What are the roles of self-interest, knowledge, and ideology in public opinion formation? And how do people learn about economic issues? Using a new, specially-designed survey, we find that most respondents express a strong desire to be well informed on economic policy issues, and that television is their dominant source of information. On a variety of major policy issues (e.g., taxes, social security, health insurance), ideology is the most important determinant of public opinion, while measures of self-interest are the least important. Knowledge about the economy ranks somewhere in between.

What Does the Public Know about Economic Policy, and How Does It Know It?

A long tradition in economic theory models economic policy decisions as solutions to optimization problems solved by rational and well-informed agents: A single policymaker minimizes a loss function subject to some constraints. Another body of literature models policy decisions as if they were made by well-informed voters in elections of some sort.

The Supply Shock Explanation of the Great Stagflation Revisited

U.S. inflation data exhibit two notable spikes into the double-digit range in 1973-1974 and again in 1978-1980. The well-known “supply-shock” explanation attributes both spikes to large food and energy shocks plus, in the case of 1973-1974, the removal of price controls. Yet critics of this explanation have (a) attributed the surges in inflation to monetary policy and (b) pointed to the far smaller impacts of more recent oil shocks as evidence against the supply-shock explanation. This paper reexamines the impacts of the supply shocks of the 1970s in the light of the new data, new events, new theories, and new econometric studies that have accumulated over the past quarter century. We find that the classic supply-shock explanation holds up very well; in particular, neither data revisions nor updated econometric estimates substantially change the evaluations of the 1972-1983 period that were made 25 years (or more) ago. We also rebut several variants of the claim that monetary policy, rather than supply shocks, was really to blame for the inflation spikes. Finally, we examine several changes in the economy that may explain why the impacts of oil shocks are so much smaller now than they were in the 1970s.

On the Size-Dependence of the Inclination Distribution of the Main Kuiper Belt

We present a new analysis of the currently available orbital elements for the known Kuiper belt objects. In the non-resonant, main Kuiper belt we find a statistically significant relationship between an object's absolute magnitude (H) and its inclination (i). Objects with H~170 km for a 4% albedo) have higher inclinations than those with H>6.5 (radii >~ 170 km). We have shown that this relationship is not caused by any obvious observational bias. We argue that the main Kuiper belt consists of the superposition of two distinct distributions. One is dynamically hot with inclinations as large as \~35 deg and absolute magnitudes as bright as 4.5; the other is dynamically cold with i6.5. The dynamically cold population is most likely dynamically primordial. We speculate on the potential causes of this relationship.Comment: 14 pages, 6 postscript figure

Bayesian Nonparametric Inference of Switching Linear Dynamical Systems

Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switching linear dynamical system (SLDS) and the switching vector autoregressive (VAR) process. Our Bayesian nonparametric approach utilizes a hierarchical Dirichlet process prior to learn an unknown number of persistent, smooth dynamical modes. We additionally employ automatic relevance determination to infer a sparse set of dynamic dependencies allowing us to learn SLDS with varying state dimension or switching VAR processes with varying autoregressive order. We develop a sampling algorithm that combines a truncated approximation to the Dirichlet process with efficient joint sampling of the mode and state sequences. The utility and flexibility of our model are demonstrated on synthetic data, sequences of dancing honey bees, the IBOVESPA stock index, and a maneuvering target tracking application.Comment: 50 pages, 7 figure

A sticky HDP-HMM with application to speaker diarization

We consider the problem of speaker diarization, the problem of segmenting an audio recording of a meeting into temporal segments corresponding to individual speakers. The problem is rendered particularly difficult by the fact that we are not allowed to assume knowledge of the number of people participating in the meeting. To address this problem, we take a Bayesian nonparametric approach to speaker diarization that builds on the hierarchical Dirichlet process hidden Markov model (HDP-HMM) of Teh et al. [J. Amer. Statist. Assoc. 101 (2006) 1566--1581]. Although the basic HDP-HMM tends to over-segment the audio data---creating redundant states and rapidly switching among them---we describe an augmented HDP-HMM that provides effective control over the switching rate. We also show that this augmentation makes it possible to treat emission distributions nonparametrically. To scale the resulting architecture to realistic diarization problems, we develop a sampling algorithm that employs a truncated approximation of the Dirichlet process to jointly resample the full state sequence, greatly improving mixing rates. Working with a benchmark NIST data set, we show that our Bayesian nonparametric architecture yields state-of-the-art speaker diarization results.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS395 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org