Recursive and non-recursive models

synchrony 22,975 views 14 slides Jan 19, 2018
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About This Presentation

A recursive model is one where all causal effects are uni-directional and disturbances are uncorrelated

A non-recursive model contains one or more ‘feedback loops’ or ‘reciprocal’ effects


Slide Content

Recursive and non-recursive models

2 Recursivity All models considered so far are ‘recursive ’ A recursive model is one where all causal effects are uni -directional and disturbances are uncorrelated A non-recursive model contains one or more ‘feedback loops’ or ‘reciprocal’ effects

Recursive Model 3 Causal effects uni -directional Disturbances uncorrelated

Non-recursive model 4 Reciprocal causal effects Disturbances correlated

Partially recursive 1 5 No direct effects amongst endogenous = recursive

Partially recursive 2 6 D irect effects amongst endogenous = non-recursive

Recursivity Recursive models always identified, simple to estimate Non -recursive models more flexible But can pose problems for identification Require additional variables for identification 7

Non-recursive models Just because a model is identified does not mean the parameter estimates are correct Consistent estimation of reciprocal paths requires some strict (and often implausible ) assumptions to be met E.g. the exogenous variable used to identify of synchronous parameters must meet be an ‘instrumental variable’ 8

Endogenous regressor OLS assumes error term uncorrelated with predictors Correlation can arise from unobserved variables and from simultaneous causal relationship To interpret β as causal effect, we need instrumental variable for X1 β

Instrumental Variables (IV) An IV is a variable which introduces exogenous variability into an endogenous regressor The IV, Z, must directly cause the endogenous regressor but not the outcome Cov ( Z,u )=0, Cov ( x K ,Z )≠ Random assignment to treatment & control conditions in RCT is a good instrumental variable 10

Instrumental variable Z1 causes X1 Z1 only causes Y1 via effect on X1

Instrumental Variables - examples Vietnam lottery draft for effect of Vietnam war on later outcomes (Angrist and Krueger 1991 ) Proximity of nearest college for education on earnings (Card 1995 ) Variation in amount of compulsory schooling for effects of education on earnings ( Hammon & Walker 1995) 12

13 N on-recursive SEM Does happiness cause trust or trust cause happiness? Direct paths in both directions between happiness and trust Model unidentified without exogenous predictors (income and marital status) Are these valid instrumental variables? Chi2=16; df =10; p<0.098; RMSEA =. 020; CFI=. 997 Data: European Social Survey 2004, GB only

14 N on-recursive SEM Does happiness cause trust or trust cause happiness? Direct paths in both directions between happiness and trust Model unidentified without exogenous predictors (income and marital status) Are these valid instrumental variables? Chi2=16; df =10; p<0.098; RMSEA =. 020; CFI=. 997 Data: European Social Survey 2004, GB only