    \begin{algorithmic}[1]
    \Require Baseline covariates $Z_1, \cdots, Z_n$
     \State Estimate $\bar{\mu}_i$ by regressing baseline outcomes on  covariates $Z$
     \State Estimate $\bar{\sigma}^2$ the variance of the residuals from this regression
      \State Consider the range of values $\bar{\psi} \in [\bar{\sigma}^2, 4 \bar{\sigma}^2]$
     \If{past experiments are available}
     \State Use $\bar{\phi}_n$ from previous experiments 
     \Else 
     \State Consider a range of values of plausible spillover effects 
    \EndIf 
    \end{algorithmic} 

\begin{algorithmic}
[1]
\Require Baseline covariates $Z_1, \cdots, Z_n$
\State Estimate $\bar{\mu}_i$ by regressing baseline outcomes on covariates $Z$
\State Estimate $\bar{\sigma}^2$ the variance of the residuals from this regression
\State Consider the range of values $\bar{\psi} \in [\bar{\sigma}^2, 4 \bar{\sigma}^2]$
\If{past experiments are available}
\State Use $\bar{\phi}_n$ from previous experiments
\Else
\State Consider a range of values of plausible spillover effects
\EndIf
\end{algorithmic}
{
    "title": "causal clustering: design of cluster experiments under network   interference",
    "id": "2310.14983",
    "abstract": "this paper studies the design of cluster experiments to estimate the global treatment effect in the presence of network spillovers. we provide a framework to choose the clustering that minimizes the worst-case mean-squared error of the estimated global effect. we show that optimal clustering solves a novel penalized min-cut optimization problem computed via off-the-shelf semi-definite programming algorithms. our analysis also characterizes simple conditions to choose between any two cluster designs, including choosing between a cluster or individual-level randomization. we illustrate the method's properties using unique network data from the universe of facebook's users and existing data from a field experiment.",
    "categories": "econ.em math.st stat.me stat.th",
    "doi": "",
    "created": "2023-10-23",
    "updated": "2024-01-13",
    "authors": [
        "davide viviano",
        "lihua lei",
        "guido imbens",
        "brian karrer",
        "okke schrijvers",
        "liang shi"
    ],
    "affiliation": [],
    "url": "https://arxiv.org/abs/2310.14983"
}
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