Panel experiments and dynamic causal effects: A finite population perspective

Finite Population Causal Standard Errors∗

When a researcher estimates the parameters of a regression function using information on all 50 states in the United States, or information on all visits to a website, what is the interpretation of the standard errors? Researchers typically report standard errors that are designed to capture sampling variation, based on viewing the data as a random sample drawn from a large population of intere...

Perishable Inventory System with a Finite Population and Repeated Attempts

Analysis of Public Goods Experiments Using Dynamic Panel Regression Models*

Laboratory experiments on the provision of public goods follow each subject over time as he interacts with a small group of others, deciding in each period how much of an initial allocation to contribute to a group good that yields a return to all group members. These experiments produce data sets that are rich in dynamics, as subjects respond not only to the parameters of the experiment, but a...

A dynamic causal model study of neuronal population dynamics

In this paper, we compare mean-field and neural-mass models of electrophysiological responses using Bayesian model comparison. In previous work, we presented a mean-field model of neuronal dynamics as observed with magnetoencephalography and electroencephalography. Unlike neural-mass models, which consider only the mean activity of neuronal populations, mean-field models track the distribution ...

Calculating Causal Effects from Panel Data in Eligibility Designs

We present Bayesian models for finding the longitudinal causal effects of a randomized two-arm training program when compliance with the randomized assignment is less than perfect in the training arm (but perfect in the non-training arm) for reasons that are potentially correlated with the outcomes. We deal with the latter confounding problem under the principal stratification framework of Somm...