Trends in Hours, Balanced Growth, and the Role of Technology in the Business Cycle

The present paper revisits a property embedded in most dynamic macroeconomic models: the stationarity of hours worked. First, I argue that, contrary to what is often believed, there are many reasons why hours could be nonstationary in those models, while preserving the property of balanced growth. Second, I show that the postwar evidence for most industrialized economies is clearly at odds with the assumption of stationary hours per capita. Third, I examine the implications of that evidence for the role of technology as a source of economic fluctuations in the G7 countries.

Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations

Using data for the G7 countries, I estimate conditional correlations of employment and productivity, based on a decomposition of the two series into technology and non-technology components. The picture that emerges is hard to reconcile with the predictions of the standard Real Business Cycle model. For a majority of countries the following results stand out: (a) technology shocks appear to induce a negative comovement between productivity and employment, counterbalanced by a positive comovement generated by demand shocks, (b) the impulse responses show a persistent decline of employment in response to a positive technology shock, and (c) measured productivity increases temporarily in response to a positive demand shock. More generally, the pattern of economic fluctuations attributed to technology shocks seems to be largely unrelated to major postwar cyclical episodes. A simple model with monopolistic competition, sticky prices, and variable effort is shown to be able to account for the empirical findings.

A "Quantal Regret" Method for Structural Econometrics in Repeated Games

We suggest a general method for inferring players' values from their actions in repeated games. The method extends and improves upon the recent suggestion of (Nekipelov et al., EC 2015) and is based on the assumption that players are more likely to exhibit sequences of actions that have lower regret. We evaluate this "quantal regret" method on two different datasets from experiments of repeated games with controlled player values: those of (Selten and Chmura, AER 2008) on a variety of two-player 2x2 games and our own experiment on ad-auctions (Noti et al., WWW 2014). We find that the quantal regret method is consistently and significantly more precise than either "classic" econometric methods that are based on Nash equilibria, or the "min-regret" method of (Nekipelov et al., EC 2015)

Recurrent approach to effective material properties with application to anisotropic binarized random fields

Building on the foundation work of Brown, Milton and Torquato, we present a tractable approach to analyse the effective permittivity of anisotropic two-phase structures. This methodology accounts for successive dipolar interactions, providing a recurrent series expansion of the effective permittivity to arbitrary order. Within this framework, we also demonstrate a progressive method to determine tight bounds that converge towards the exact solution. We illustrate the utility of these methods by using ensemble averaging to determine the micro-structural parameters of anisotropic level-cut Gaussian fields. We find that the depolarization factor of these structures is equivalent to that of an isolated ellipse with the same stretchingratio, and discuss the contribution of the fourth order term to the exact anisotropy