We report experimental results for a twice-played prisoners' dilemma in which the players can choose the allocation of the stakes across the two periods. Our point of departure is the assumption that some (but not all) people are principled to "do the right thing," or cooperate, as long as their...

We describe research on the impact of health insurance on healthcare spending ("moral hazard"), and use this context to illustrate the value of and important complementarities between different empirical approaches. One common approach is to emphasize a credible research design; we review...

We investigate the potential for Large Language Models (LLMs) to enhance scientific practice within experimentation by identifying key areas, directions, and implications. First, we discuss how these models can improve experimental design, including improving the elicitation wording, coding...

This paper presents an econometric mediation analysis. It considers identification of production functions and the sources of output effects (treatment effects) from experimental interventions when some inputs are mismeasured and others are entirely omitted

We propose a discrete-time stochastic volatility model in which regime switching serves three purposes. First, changes in regimes capture low frequency variations, which is their traditional role. Second, they specify intermediate frequency dynamics that are usually assigned to smooth...

The returns to hedge funds and other alternative investments are often highly serially correlated in sharp contrast to the returns of more traditional investment vehicles such as long-only equity portfolios and mutual funds. In this paper, we explore several sources of such serial correlation...

We analyze the prices of owner-occupied housing in 97 metropolitan areas between 1980 and 2011. Our tests indicate that price changes exhibit positive serial correlation at the one year intervals, with subsequent reversals of price changes over longer intervals. Consistent with our simple model,...

We propose a Bayesian procedure for exploiting small, possibly long-lag linear predictability in the innovations of a finite order autoregression. We model the innovations as having a log-spectral density that is a continuous mean-zero Gaussian process of order 1/√T. This local embedding makes...