We consider the use of randomized experiments to measure social interaction effects. Ran-domization at two levels—across groups and within groups—can resolve an omitted variables problem for a linear-in-means model of endogenous social interactions. We examine how the randomization should be carried out to estimate the coefficients of interest most precisely, and calculate the optimal treatment probabilities under different criteria.
1We would like to thank Gary Chamberlain, Enrico Moretti and participants at UCLAWork-shop in Econom...
Individually randomized treatments are often administered within a group setting. As a consequence, ...
General Information Overview Randomized interventions allow political scientists to claim that compa...
This paper considers the recent case for randomized social experimentation and contrasts it with old...
Randomized experiments are seen as the most rigorous methodology for testing causal explanations for...
In experiments that study social phenomena, such as peer influence or herd immunity, the treatment o...
This paper develops a framework for analyzing the outcome of experiments carried out on forward-look...
This paper proposes a new method for identifying social interactions using conditional variance rest...
<p>(<b>A</b>) Probability distribution of estimations before (no info, blue) and after (full info, r...
Social experiments have been used in research since the 1960s, yet the technique of controlled exper...
This paper analyzes the method of social experiments. The assumptions that justify the experimental ...
This chapter considers the design and analysis of networked experiments, one of the most precise too...
Estimating the effects of interventions in networks is complicated when the units are interacting, s...
Estimating the effects of interventions in networks is complicated due to interference, such that th...
This is the author accepted manuscript. The final version is available from De Gruyter via the DOI i...
1We would like to thank Gary Chamberlain, Enrico Moretti and participants at UCLAWork-shop in Econom...
Individually randomized treatments are often administered within a group setting. As a consequence, ...
General Information Overview Randomized interventions allow political scientists to claim that compa...
This paper considers the recent case for randomized social experimentation and contrasts it with old...
Randomized experiments are seen as the most rigorous methodology for testing causal explanations for...
In experiments that study social phenomena, such as peer influence or herd immunity, the treatment o...
This paper develops a framework for analyzing the outcome of experiments carried out on forward-look...
This paper proposes a new method for identifying social interactions using conditional variance rest...
<p>(<b>A</b>) Probability distribution of estimations before (no info, blue) and after (full info, r...
Social experiments have been used in research since the 1960s, yet the technique of controlled exper...
This paper analyzes the method of social experiments. The assumptions that justify the experimental ...
This chapter considers the design and analysis of networked experiments, one of the most precise too...
Estimating the effects of interventions in networks is complicated when the units are interacting, s...
Estimating the effects of interventions in networks is complicated due to interference, such that th...
This is the author accepted manuscript. The final version is available from De Gruyter via the DOI i...
1We would like to thank Gary Chamberlain, Enrico Moretti and participants at UCLAWork-shop in Econom...
Individually randomized treatments are often administered within a group setting. As a consequence, ...
General Information Overview Randomized interventions allow political scientists to claim that compa...