Stata module to perform additive decomposition of sample statistic, statistical software components s411401, boston college department of economics. Axioms under which these values are unique solutions. Find the shapley owen decomposition for the linear regression for the data in range a3. Of course, a parallel posting on stata list is also very welcome, as it can help other users having the same problem. I am trying to apply shapley value to decompose a multidimensional poverty measure that i have constructed. What is shapley value regression and how does one implement. Additionally, iop allows you to compute the decomposition of the inequality of opportunity measures by groups oaxacalike approach and by explanatory factors shapley like decomposition. A shapley based decomposition of the rsquare of a linear regression article in the journal of economic inequality 52. Just type ssc install fmiss in stata to install it. It was named in honor of lloyd shapley, who introduced it in 1951 and won the nobel prize in economics for it in 2012.
Shapley value regression significantly ameliorates the deleterious effects of collinearity on the estimated parameters of a regression equation. This approach addresses the problem of multicollinearity between independent variables in the model by providing an accurate decomposition of the total. Known issues the program has been tested on ols, probit, logit and. Shapleyowen decomposition real statistics using excel. Pdf on jan 1, 2012, stan lipovetsky and others published interpretation of shapley value regression coefficients as approximation for coefficients derived by.
Nov 15, 2006 this note suggests a new way of determining the exact contributions of the explanatory variables to the rsquare of a linear regression. The concept of shapley value was introduced in cooperative collusive game theory where agents form collusion and cooperate with each other to raise the value of a game. The shapley value works for both classification if we are dealing with probabilities and regression. An algorithm for computing the shapley value abdelkrim araar and jeanyves duclos january 12, 2009 1 the shapley value consider a set n of n players that must divide a given surplus among themselves. Shapley regression and relative weights are two methods for estimating the importance of predictor variables in linear regression.
Is anyone aware of ready stata command or code applying this method. Studies have shown that the two, despite being constructed in very different ways, provide surprisingly similar scoresgromping, u. The present paper simplifies the algorithm of shapley value decomposition of r 2 and develops a fortran computer program that executes it. Aug 10, 2015 a priori approaches derive decompositions based on theoretical axioms, and include the factor and subgroup decompositions derived by shorrocks 1982, 1984 and the shapley. Shapley inequality decomposition by factor components.
Decomposes the gini index by income sources with the shapley approach. Shapley value decomposition in empirical applications raises some dilemmas that cannot be solved on purely theoretical grounds. This module should be installed from within stata by typing ssc install adecomp. The shapley value is characterized by a collection of. Shapley2 can be used for most estimation commands, e.
Shapley value decomposition of r 2 and develops a fortran computer program that executes it. In conclusion, shapley value provides a robust framework for measuring relative importance in brand assessment analysis and is an important step forward over ordinary regression techniques. Psychological bulletin and are conceptually similar to shapley value decomposition. The stata software has become a very popular tool to transform and process data. Statistical software components from boston college department of economics. Would greatly appreciate some comments on experiences related to suitability and scaliability of shapley value for this task and suggestions for useful software packages. Also, you will find that some special characters that are legal in spss names do not work in the r code, but ordinary accented characters should be okay. Let ia,b be a function depending on two variables a and b. Thats what s of researchers who already use our software tell us. The domin command produces additive decompositions of r2 or pseudor2 in this case, the r2o metric developed by mike lacy, 2006. Rongve 1995 and chantreuil and trannoy 1997 have both.
We first calculate the r 2 values of all subsets of x 1, x 2, x 3 on y, using the real statistics rsquare function. If you encounter another problem in the software, i would be very grateful if you could directly contact me, because this allows me to take care of the problem and to solve it if possible. This program performs exact additive decomposition of a sample statistic by effects specified in factor list. A priori approaches derive decompositions based on theoretical axioms, and include the factor and subgroup decompositions derived by shorrocks 1982, 1984 and the shapley. Stata module to add text to graphs gary longton adecomp. Dominance analysis or shapley value decomposition will accomplish what youre seeking to do here. The decomposition is performed using the shapley value. Stata module to estimate shapley decomposition by components of a welfare measure, statistical software components s457562, boston college department of economics, revised 12 jan 2019. Alternative to shapley value regression cross validated. The proposed solution to the general decomposition problem turns out to formally equivalent to the shapley value, and is therefore referred to as the shapley decomposition. Existing userwritten commands adocomp, shapley, shapley2 or dsap package are quit limited as they only decompose specific poverty measures offered by those packages. Apr 18, 2016 shapley value regression is computationally and memory intensive, so if you have a lot of variables, i recommend forcing the variables whose importance measure isnt necessary.
Shapley value regression is perhaps the best methods to combat this problem. Take a look at the azen and budescu 2004 article linked to below. Find the shapleyowen decomposition for the linear regression for the data in range a3. Some methodological issues article pdf available in journal of economics 9s1 december 2002 with 1,484 reads how we. Regressionbased approaches for the decomposition of income.
Compared to the user written command shapley, shapley2 is faster and enables you to compute. An algorithm for computing the shapley value abdelkrim araar and jeanyves duclos january 12, 2009 1 the shapley value consider a set n of n players that must divide a given surplus among them selves. Shapley2 is a postestimation command to compute the shorrocksshapley decomposition of any statistic of the model normally the r squared. The interpretation of the shapley value for feature value j is. It also retrieve regression coefficients from the shapley value. To each cooperative game it assigns a unique distribution among the players of a total surplus generated by the coalition of all players.
Displayr will cut your analysis and reporting times in half. Stata module for decomposing goodness of fit according to shapley. Owen and shapley values, two closely related solutional concepts in cooperative game theory, provide unique. Shapley value imputation shapley value regression has its origins in a game theory. On april 23, 2014, statalist moved from an email list to a forum, based at. However, shapley value regression becomes increasingly impracticable as the number of regressor variables exceeds 10, although, in practice, a good regression model may not have. And with recent advancements in shapley value calculations for gradient boosted decision trees and neural networks, computing our proposed metric after model training can come with minimal computational overhead. United kingdom stata users group meetings 2012 from stata users group.
Although chantreuil and trannoy 1999 and sastre et trannoy 2002 limited their application of the shapley value to the decomposition of income. Does any one have experience using sas for shapley value regression. The shapley value is a solution concept often employed in the theory of cooperative games. Pdf shapley inequality decomposition by factor components. Date prev date next thread prev thread next date index thread index. I have not run shapley value regression in sas, but i wrote a macro to run it in spss. This allows computing the shapley value also when having a lot of variables.
This command performs a shorrocksshapely decomposition of many. Shapley importance determines what proportion of rsquare from a linear regression model can be attributed to each independent variable. The proposed methodology combines the socalled shapley approach chantreuil and trannoy, inequality decomposition values. The difference between shapley regression and relative. Multicollinearity and sparse data in key driver analysis. For cases where there are more than 15 independent variables, relative importance analysis values are returned, as the two yield highly similar results. Stata statistical software provides everything you need for data science and inferencedata manipulation, exploration, visualization, statistics, reporting. Stata module to estimate shapley decomposition by components of a welfare measure description. Shapley2 is a postestimation command to compute the shorrocksshapley. To install the shapley decomposition of the hoi enter in the command window ssc install hoishapley. Shapley 1953 and owen 1977 values as means to decompose goodness of fit. Shapley values a method from coalitional game theory tells us how to fairly distribute the payout among the features. Shapley decomposition of rsquared in machine learning models. Some methodological issues article pdf available in journal of economics 9s1 december 2002 with 1,484 reads how we measure reads.
Imagine blending powerpoint, spss, excel, and tableau into one tool thats also fast, easy to use, and excellent for survey data well, thats displayr. Stata module to add twoway plot objects to an existing twoway graph ben jann addtex. Regression based shapley value decomposition rbdineq. Shapley2 is a postestimation command to compute the shorrocks shapley decomposition of any statistic of the model normally the r squared. This note suggests a new way of determining the exact contributions of the explanatory variables to the r square of a linear regression. Shapley value is the most correct method of assigning coefficient weights to your prediction variables. The shapley value is a solution concept in cooperative game theory. If you write the code and dont have millions of surveys, you should be able to do it in excel by writing the vba. Im asking m stata command or code applying this method. The concept of shapley value was introduced in cooperative collusive game theory where agents form collusion and cooperate with each other to raise the value of a game in their favour and later divide it. Dear statalisters i am running a regression based decomposition by using command rbdineq.
Axiomatic arguments for decomposing goodness of fit. The program is still in development, and no warranty is provided regarding the. A shapleybased decomposition of the rsquare of a linear. A shapleybased decomposition of the r square of a linear. As argued by sastre and trannoy 2002, provided all ambiguities about di. Giammatteo the bidimensional decomposition of inequality.
The players may form coalitions these are subsets s of n that appropriate themselves a part of the surplus and redistribute it between their. Decomposition procedures for distributional analysis. Shapley inequality decomposition, including the nested shapley chantreuil and trannoy 1999 and the owen decomposition shorrocks 1999, based on dening a hierarchical structure of incomes. Software components s457543, boston college department of economics. To perform the shapley decomposition, the effects are eliminated one by one, and marginal effects from each exclusion are weighted in such a way that all exclusion trajectories have equal weights. Regressionbased approaches for the decomposition of income inequality in italy, 19982008 6 istituto nazionale di statistica occupational status of the household head, the authors concluded that the income distribution shifted to the advantage of the selfemployed and managers and to the disadvantage of the employees. Displayr analysis and reporting software for survey data. Abstract this program performs exact additive decomposition of a sample statistic by effects specified in factor list. The players may form coalitions these are subsets s of n that appropri ate themselves a part of the surplus and redistribute it between their members. On this decomposition in matrix analysis books, the case is m n, called ldl decomposition, which is derived from triangular decomposition lu decomposition. Stata module to estimate shapley value of growth and distribution components of changes in poverty indicators. It also retrieves regression coefficients from the shapley value. Stanislav kolenikov statistical software components from boston college department of economics. The shapley value shapley, 1953 provides a popular answer to this question.
A short summary of the concept of shapley decomposition 1 the case of two variables. Stata module to perform additive decomposition of sample statistic. A prediction can be explained by assuming that each feature value of the instance is a player in a game where the prediction is the payout. The command dfgts decomposes the allevation of fgt poverty by income components and provides standard errors on elements of the decompositions.
More than 40 million people use github to discover, fork, and contribute to over 100 million projects. Stata module to estimate shapley decomposition by components of a welfare measure joao pedro azevedo, minh nguyen and viviane. This module should be installed from within stata by typing. Shapley decomposition if we want to estimate the marginal contribution of each circumstance to inequality we use the shapley decomposition see shorrocks, 2002.
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