Inferring Optimal Peer Assignment From Experimental Data

By Debopam Bhattacharya. 2009

97 citations recorded by the source corpus.

Subfields: Education, Gender Studies, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7c0ea2271ff68d6f7f8bc60a0f7fa33d3e7ab0c3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Education

1. L. Castro
2. Bruce I. Sacerdote
3. Antonio F. Galvao

In Gender Studies

1. L. Castro
2. Bruce I. Sacerdote
3. Antonio F. Galvao

In Statistics and Probability

1. L. Castro
2. Bruce I. Sacerdote
3. Antonio F. Galvao

Citations in the corpus

• From Natural Variation to Optimal Policy? The Importance of Endogenous Peer Group Formation (2013, unknown): “…at the potential policy implications of the results.2 Recent econometric studies on assortative matching by Graham, Imbens, and Ridder (2009) and Bhattacharya (2009) have theorized that individuals could be sorted into peer groups to maximize productivity.3 This study takes a first step in…”
• Ethnic Divisions and Production in Firms (2014, unknown): “…problem of maximizing total output subject to the expected output associated with a given type of team and the “budget set” of workers available (see Bhattacharya, 2009; Graham, Imbens and Ridder, 2011).33 The optimal assignments and associated expected output gains are shown in table 11.34…”
• Peer Effects in Education: How Might They Work, How Big Are They and How Much Do We Know Thus Far? (2011, background): “Bobonis and Finan (2009) are able to use experimental variation from Mexico’s PROGRESA program to measure the degree to which peer participation in school raises own participation.”
• Dynamic Quantile Models of Rational Behavior (2019, methodology): “Second, this paper is related to a few works on economic models using the quantile preferences, such as Manski (1988), Chambers (2009), Bhattacharya (2009), Rostek (2010) and Giovannetti (2013). We contribute to this line of work by taking the quantile maximization to a general dynamic optimization ”
• Complementarity and Aggregate Implications of Assortative Matching: A Nonparametric Analysis (2014, unknown): “In Graham, Imbens, and Ridder (2007), we considered optimal allocation rules when both inputs are discrete, allowing for general complementarity or substitutability of the inputs (cf. Bhattacharya (2009)).”