institutions_data

A dataset containing dichotomized versions of variables in
Rodrik, Subramanian, and Trebbi (2004).

datasets

Users can declare binary causal models, update beliefs about causal types given data and calculate arbitrary estimands. Model definition makes use of 'dagitty' functionality. Updating is implemented in 'stan'. The approach used in 'CausalQueries' is a generalization of the 'biqq' models described in "Mixing Methods: A Bayesian Approach" (Humphreys and Jacobs, 2015, <DOI:10.1017/S0003055415000453>). The conceptual extension makes use of work on probabilistic causal models described in Pearl's Causality (Pearl, 2009, <DOI:10.1017/CBO9780511803161>).

Till Tietz

CausalQueries

Make, Update, and Query Binary Causal Models

Clara Bicalho

Jasper Cooper

Macartan Humphreys

Alan Jacobs

Merlin Heidemanns

Lily Medina

Julio Solis

Georgiy Syunyaev

institutions_data function

A data frame with 79 rows and 5 columns:<dl>
 <dt>Y</dt>
<dd>Income (GDP PPP 1995), dichotomized</dd> <dt>R</dt>
<dd>Institutions, (based on Kaufmann, Kraay, and Zoido-Lobaton (2002)) dichotomized</dd> <dt>D</dt>
<dd>Distance from the equator (in degrees), dichotomized</dd> <dt>M</dt>
<dd>Settler mortality (from Acemoglu, Johnson, and Robinson), dichotomized</dd> <dt>country</dt>
<dd>Country</dd>
</dl>

Format

Institutions and growth: Data for replication of analysis in
*Integrated Inferences* — institutions_data

A data frame with 79 rows and 5 columns:<dl>
 <dt>Y</dt>
<dd>Income (GDP PPP 1995), dichotomized</dd>

 <dt>R</dt>
<dd>Institutions, (based on Kaufmann, Kraay, and Zoido-Lobaton (2002)) dichotomized</dd>

 <dt>D</dt>
<dd>Distance from the equator (in degrees), dichotomized</dd>

 <dt>M</dt>
<dd>Settler mortality (from Acemoglu, Johnson, and Robinson), dichotomized</dd>

 <dt>country</dt>
<dd>Country</dd>


</dl>

Institutions and growth: Data for replication of analysis in
*Integrated Inferences*

institutions_data: Institutions and growth: Data for replication of analysis in Integrated Inferences

Description

Usage

Arguments

Format