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Specification and estimation of social interaction models with network structures, (2010)

by L F Lee, X Liu, X Lin
Venue:The Econometrics Journal
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Identification of Social Interactions

by Lawrence E. Blume, Steven N. Durlauf, William A. Brock, Yannis M. Ioannides, Xiangrong Yu , 2010
"... While interest in social determinants of individual behavior has led to a rich theoretical literature and many efforts to measure these influences, a mature “social econometrics ” has yet to emerge. This chapter provides a critical overview of the identification of social interactions. We consider l ..."
Abstract - Cited by 28 (3 self) - Add to MetaCart
While interest in social determinants of individual behavior has led to a rich theoretical literature and many efforts to measure these influences, a mature “social econometrics ” has yet to emerge. This chapter provides a critical overview of the identification of social interactions. We consider linear and discrete choice models as well as social networks structures. We also consider experimental and quasi-experimental methods. In addition to describing the state of the identification literature, we indicate areas where additional research is especially needed and suggest some directions that appear to be especially promising.

Mostly Pointless Spatial Econometrics? In:

by Steve Gibbons , Henry Overman - Journal of Regional Science, , 2012
"... Abstract: We argue that identification problems bedevil applied spatial economic research. Spatial econometrics usually solves these problems by deriving estimators assuming that functional forms are known and by using model comparison techniques to let the data choose between competing specificati ..."
Abstract - Cited by 16 (0 self) - Add to MetaCart
Abstract: We argue that identification problems bedevil applied spatial economic research. Spatial econometrics usually solves these problems by deriving estimators assuming that functional forms are known and by using model comparison techniques to let the data choose between competing specifications. We argue that in many situations of interest this, at best, achieves only very weak identification. Worse, in many cases, such an approach will be uninformative about the causal economic processes at work, rendering much applied spatial econometric research 'pointless', unless the main aim is description of the data. We advocate an alternative approach based on the 'experimental paradigm' which puts issues of identification and causality at centre stage.

A Method of Estimating

by Lung-fei Lee, Jihai Yu - Magnitude of Local Earthquakes from Signal Duration, U.S. Geological Survey, OPEN FILE REPORT , 1972
"... of spatial autoregressive panel data models with xed e¤ects ..."
Abstract - Cited by 14 (1 self) - Add to MetaCart
of spatial autoregressive panel data models with xed e¤ects
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...ed e¤ects has been considered in Lee and Yu (2007a) for a spatial dynamic panel model with large T . In a group setting with groupsxed e¤ects, a similar transformation can eliminate the group e¤ects (=-=Lee et al., 2008-=-). 5However, our modi…ed likelihood is not one of those which could be constructed from their formulas. 2 same representation. By the transformation (In0Wn), the data generating process (DGP) of Kap...

Matlab software for spatial panels

by J. Paul Elhorst, See Profile, J. Paul Elhorst - International Regional Science Review , 2014
"... All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
Abstract - Cited by 12 (0 self) - Add to MetaCart
All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.

Criminal networks: Who is the key player

by Xiaodong Liu, Eleonora Patacchini, Yves Zenou, Lung-fei Lee - CEPR Discussion Paper
"... We develop a key-player model by allowing for link formation so that when a person is removed from a network the other individuals can form new links while still optimally providing crime effort. We then put our model to the test, using data on adolescent delinquents in the United States, and provid ..."
Abstract - Cited by 6 (1 self) - Add to MetaCart
We develop a key-player model by allowing for link formation so that when a person is removed from a network the other individuals can form new links while still optimally providing crime effort. We then put our model to the test, using data on adolescent delinquents in the United States, and provide new results regarding the identification of peer effects. This is done by a structural estimation and simulation of our model. Compared to a policy that removes randomly delinquents from the network, a key player policy engenders a crime reduction that can be as large as 35 percent. We discuss how to implement the key-player policy in the real world, primarily within criminal networks, but also within financial, R&D, development, political and tax-evasion networks.

Systemic Risk and Network Formation in the Interbank Market

by Ethan Cohen-cole, Eleonora Patacchini, Yves Zenou , 2012
"... We propose a novel mechanism to facilitate understanding of systemic risk in …nan-cial markets. The literature on systemic risk has focused on two mechanisms, common shocks and domino-like sequential default. We provide a new model that draws on the games-on-networks literature. Transmission in our ..."
Abstract - Cited by 6 (0 self) - Add to MetaCart
We propose a novel mechanism to facilitate understanding of systemic risk in …nan-cial markets. The literature on systemic risk has focused on two mechanisms, common shocks and domino-like sequential default. We provide a new model that draws on the games-on-networks literature. Transmission in our model is not based on default. In-stead, we provide a simple microfoundation of bankspro…tability based on competition incentives and the outcome of a strategic game. As competitors loans change, both for closely connected ones and the whole market, banks adjust their own decisions as a result, generating a transmissionof shocks through the system. Our approach permits us to measure both the degree that shocks are ampli…ed by the network structure and

2009), “The econometrics of social networks

by Yann Bramoullé, Bernard Fortin - In: S. Durlauf and L. Blume
"... We thank Habiba Djebbari and Marcel Fafchamps for helpful comments. ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
We thank Habiba Djebbari and Marcel Fafchamps for helpful comments.

Peer effects, fast food consumption and adolescent weight gain.

by Bernard Fortin , Myra Yazbeck , Bernard Fortin , Myra Yazbeck , Bernard Fortin , Christopher Auld , Charles Bellemare , Luc Bissonnette , Vincent Boucher , Paul Frijters , Guy Lacroix , Paul Makdissi , Daniel L Millimet , Kevin Moran , Bruce Shearer , Yann Bramoullé , Badi Baltagi , Rokhaya Dieye , Habiba Djebbari , Tue Gorgens , Bob Gregory , Louis Hotte , Linda Khalaf , Lung-Fei Lee , Xin Meng , Rabee - Journal of health economics , 2015
"... ABSTRACT Peer Effects, Fast Food Consumption and Adolescent Weight Gain * This paper aims at opening the black box of peer effects in adolescent weight gain. Using Add Health data on secondary schools in the U.S., we investigate whether these partly flow through the eating habits channel. Adolescen ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
ABSTRACT Peer Effects, Fast Food Consumption and Adolescent Weight Gain * This paper aims at opening the black box of peer effects in adolescent weight gain. Using Add Health data on secondary schools in the U.S., we investigate whether these partly flow through the eating habits channel. Adolescents are assumed to interact through a friendship social network. We propose a two-equation model. The first equation provides a social interaction model of fast food consumption. To estimate this equation we use a quasi maximum likelihood approach that allows us to control for common environment at the network level and to solve the simultaneity (reflection) problem. Our second equation is a panel dynamic weight production function relating an individual's Body Mass Index z-score (zBMI) to his fast food consumption and his lagged zBMI, and allowing for irregular intervals in the data. Results show that there are positive but small peer effects in fast food consumption among adolescents belonging to a same friendship school network. Based on our preferred specification, the estimated social multiplier is 1.15. Our results also suggest that, in the long run, an extra day of weekly fast food restaurant visits increases zBMI by 4.45% when ignoring peer effects and by 5.11%, when they are taken into account. JEL Classification: C31, I10, I12

Properties of the maximum likelihood estimator in spatial autoregressive models. cemmap working paper CWP44/13

by Grant Hillier , Federico Martellosio , Grant Hillier , Federico Martellosio , 2013
"... Abstract The (quasi-) maximum likelihood estimator (MLE) for the autoregressive parameter in a spatial autoregressive model cannot in general be written explicitly in terms of the data. The only known properties of the estimator have hitherto been its first-order asymptotic properties (Lee, 2004, E ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
Abstract The (quasi-) maximum likelihood estimator (MLE) for the autoregressive parameter in a spatial autoregressive model cannot in general be written explicitly in terms of the data. The only known properties of the estimator have hitherto been its first-order asymptotic properties (Lee, 2004, Econometrica), derived under specific assumptions on the evolution of the spatial weights matrix involved. In this paper we show that the exact cumulative distribution function of the estimator can, under mild assumptions, be written down explicitly. A number of immediate consequences of the main result are discussed, and several examples of theoretical and practical interest are analyzed in detail. The examples are of interest in their own right, but also serve to illustrate some unexpected features of the distribution of the MLE. In particular, we show that the distribution of the MLE may not be supported on the entire parameter space, and may be nonanalytic at some points in its support.
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...r space is therefore Λ = (−(m1 − 1), 1). Example 2 (Complete Bipartite Model). In a complete bipartite graph the n observational units are partitioned into two groups of sizes p and q, say, with all individuals 6If the assumption that W has at least one negative eigenvalue were not satisfied it would be appropriate to set λmin = −∞. Note that if all eigenvalues of W are real the fact that W has at least one negative eigenvalue is implied by the assumption that tr(W ) = 0. 6 within a group interacting with all in the other group, but with none in their own group (e.g., Bramoulle et al., 2009, Lee et al., 2010). For p = 1 or q = 1 this corresponds to the graph known as a star, a particularly important case in network theory (see Estrada, 2011). The adjacency matrix of a complete bipartite graph is A := [ 0pp ιpι ′ q ιqι ′ p 0qq ] . The corresponding row-standardized weights matrix is W = [ 0pp 1 q ιpι ′ q 1 p ιqι ′ p 0qq ] . (2.2) This is not symmetric unless p = q. Alternatively, A can be rescaled by its spectral radius, yielding the symmetric weights matrix W = (pq)− 1 2 A. (2.3) We refer to the SAR models with weights matrix (2.2) or (2.3), as, respectively, the row-standardized Complete Bipartit...

Linear Social Interactions Models

by Lawrence E. Blume, William A. Brock, Steven N. Durlauf, Rajshri Jayaraman, Lawrence E. Blume, William A. Brock, Steven N. Durlauf, Rajshri Jayaraman , 2013
"... three referees for very helpful comments and suggestions. Wallice Ao, Joel Han, Hon Ho Kwok, Ariel Roginsky, Kegon Tan and Xiangrong Yu have provided superb research assistance. We are grateful ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
three referees for very helpful comments and suggestions. Wallice Ao, Joel Han, Hon Ho Kwok, Ariel Roginsky, Kegon Tan and Xiangrong Yu have provided superb research assistance. We are grateful
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