Imputation of Missing Values in the Fundamental Data: Using MICE Framework

Revolutionary developments in the field of big data analytics and machine learning algorithms have transformed the business strategies of industries such as banking, financial services, asset management, and e-commerce. The most common problems these firms face while utilizing data is the presence o...

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Published in:Journal of quantitative economics : journal of the Indian Econometric Society Vol. 17; no. 3; pp. 459 - 475
Main Authors: Meghanadh, Balasubramaniam, Aravalath, Lagesh, Joshi, Bhupesh, Sathiamoorthy, Raghunathan, Kumar, Manish
Format: Journal Article
Language:English
Published: New Delhi Springer India 01.09.2019
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ISSN:0971-1554, 2364-1045
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Abstract Revolutionary developments in the field of big data analytics and machine learning algorithms have transformed the business strategies of industries such as banking, financial services, asset management, and e-commerce. The most common problems these firms face while utilizing data is the presence of missing values in the dataset. The objective of this study is to impute fundamental data that is missing in financial statements. The study uses ‘Multiple Imputation by Chained Equations’ (MICE) framework by utilizing the interdependency among the variables that wholly comply with accounting rules. The proposed framework has two stages. The initial imputation is based on predictive mean matching in the first stage and resolving financial constraints in the second stage. The MICE framework allows us to incorporate accounting constraints in the imputation process. The performance tests conducted on the imputed dataset indicate that the imputed values for the 177 line items are good and in line with the expectations of subject matter experts.
AbstractList Revolutionary developments in the field of big data analytics and machine learning algorithms have transformed the business strategies of industries such as banking, financial services, asset management, and e-commerce. The most common problems these firms face while utilizing data is the presence of missing values in the dataset. The objective of this study is to impute fundamental data that is missing in financial statements. The study uses ‘Multiple Imputation by Chained Equations’ (MICE) framework by utilizing the interdependency among the variables that wholly comply with accounting rules. The proposed framework has two stages. The initial imputation is based on predictive mean matching in the first stage and resolving financial constraints in the second stage. The MICE framework allows us to incorporate accounting constraints in the imputation process. The performance tests conducted on the imputed dataset indicate that the imputed values for the 177 line items are good and in line with the expectations of subject matter experts.
Author Aravalath, Lagesh
Meghanadh, Balasubramaniam
Joshi, Bhupesh
Sathiamoorthy, Raghunathan
Kumar, Manish
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Accounting and financial statement
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References Van Buuren, Brand, Groothuis-Oudshoorn, Rubin (CR3) 2006; 76
Raghunathan (CR14) 2001; 27
Fogarty (CR5) 2006; 41
Kennickell (CR8) 1991; 1
He, Zaslavsky, Landrum, Harrington, Catalano (CR7) 2009; 19
Galler, Kehral (CR6) 2012
Little (CR12) 1988; 83
Rubin (CR17) 1996; 91
CR13
Little, Rubin (CR11) 2002
Schafer (CR18) 1997
Schafer (CR19) 1999; 8
Stuart, Azur, Frangakis, Leaf (CR20) 2009; 169
Buuren, Groothuis-Oudshoorn (CR2) 2010; 45
Rubin (CR16) 1987
King (CR9) 1998
Bouhlila, Sellaouti (CR1) 2013; 1
Kofman, Sharpe (CR10) 2000
De Waal (CR4) 2011
Rubin (CR15) 1976; 63
T Waal De (142_CR4) 2011
JL Schafer (142_CR19) 1999; 8
SV Buuren (142_CR2) 2010; 45
142_CR13
DB Rubin (142_CR15) 1976; 63
TE Raghunathan (142_CR14) 2001; 27
RJ Little (142_CR11) 2002
JL Schafer (142_CR18) 1997
DS Bouhlila (142_CR1) 2013; 1
S Buuren Van (142_CR3) 2006; 76
Gary King (142_CR9) 1998
P Kofman (142_CR10) 2000
B Galler (142_CR6) 2012
Arthur B Kennickell (142_CR8) 1991; 1
DB Rubin (142_CR17) 1996; 91
Y He (142_CR7) 2009; 19
EA Stuart (142_CR20) 2009; 169
DB Rubin (142_CR16) 1987
Roderick JA Little (142_CR12) 1988; 83
DJ Fogarty (142_CR5) 2006; 41
References_xml – volume: 27
  start-page: 85
  year: 2001
  end-page: 96
  ident: CR14
  article-title: A multivariate technique for multiply imputing missing values using a sequence of regression models
  publication-title: Survey methodology
– year: 1997
  ident: CR18
  publication-title: Analysis of incomplete multivariate data
  doi: 10.1201/9781439821862
– year: 1998
  ident: CR9
  publication-title: List-wise deletion is evil: what to do about missing data in political science
– volume: 1
  start-page: 1
  year: 2013
  end-page: 33
  ident: CR1
  article-title: Multiple imputation using chained equations for missing data in TIMSS: a case study
  publication-title: Large-scale Assessments in Education
  doi: 10.1186/2196-0739-1-4
– year: 2012
  ident: CR6
  publication-title: Missing data methods in credit risk
– volume: 8
  start-page: 3
  year: 1999
  end-page: 15
  ident: CR19
  article-title: Multiple imputation: a primer
  publication-title: Statistical Methods in Medical Research
  doi: 10.1177/096228029900800102
– ident: CR13
– volume: 91
  start-page: 473
  year: 1996
  end-page: 489
  ident: CR17
  article-title: Multiple imputation after 18 + years
  publication-title: Journal of the American statistical Association
  doi: 10.1080/01621459.1996.10476908
– year: 2000
  ident: CR10
  publication-title: Imputation methods for incomplete dependent variables in finance. School of finance and economics
– volume: 45
  start-page: 1
  year: 2010
  end-page: 68
  ident: CR2
  article-title: Mice: Multivariate imputation by chained equations in R
  publication-title: Journal of Statistical Software.
– volume: 169
  start-page: 1133
  year: 2009
  end-page: 1139
  ident: CR20
  article-title: Multiple imputation with large data sets: a case study of the Children’s Mental Health Initiative
  publication-title: American Journal of Epidemiology
  doi: 10.1093/aje/kwp026
– year: 2011
  ident: CR4
  publication-title: Handbook of statistical data editing and imputation
  doi: 10.1002/9780470904848
– year: 1987
  ident: CR16
  publication-title: Multiple imputation for nonresponse in surveys
  doi: 10.1002/9780470316696
– volume: 41
  start-page: 1
  year: 2006
  end-page: 41
  ident: CR5
  article-title: Multiple imputation as a missing data approach to reject inference on consumer credit scoring
  publication-title: Interstat.
– volume: 1
  start-page: 41
  issue: 10
  year: 1991
  ident: CR8
  article-title: Imputation of the 1989 survey of consumer finances: stochastic relaxation and multiple imputation
  publication-title: Proceedings of the Survey Research Methods Section of the American Statistical Association
– volume: 19
  start-page: 653
  year: 2009
  end-page: 670
  ident: CR7
  article-title: Multiple imputation in a large-scale complex survey: a practical guide
  publication-title: Statistical Methods in Medical Research
  doi: 10.1177/0962280208101273
– year: 2002
  ident: CR11
  publication-title: Statistical analysis with missing data
  doi: 10.1002/9781119013563
– volume: 76
  start-page: 1049
  year: 2006
  end-page: 1064
  ident: CR3
  article-title: Fully Conditional Specification in multivariate imputation
  publication-title: Journal of Statistical Computation and Simulation
  doi: 10.1080/10629360600810434
– volume: 83
  start-page: 1198
  issue: 404
  year: 1988
  end-page: 1202
  ident: CR12
  article-title: A test of missing completely at random for multivariate data with missing values
  publication-title: Journal of the American Statistical Association
  doi: 10.1080/01621459.1988.10478722
– volume: 63
  start-page: 581
  issue: 3
  year: 1976
  end-page: 592
  ident: CR15
  article-title: Inference and missing data
  publication-title: Biometrika
  doi: 10.1093/biomet/63.3.581
– volume: 76
  start-page: 1049
  year: 2006
  ident: 142_CR3
  publication-title: Journal of Statistical Computation and Simulation
  doi: 10.1080/10629360600810434
– volume-title: Missing data methods in credit risk
  year: 2012
  ident: 142_CR6
– volume-title: List-wise deletion is evil: what to do about missing data in political science
  year: 1998
  ident: 142_CR9
– volume-title: Multiple imputation for nonresponse in surveys
  year: 1987
  ident: 142_CR16
  doi: 10.1002/9780470316696
– volume: 27
  start-page: 85
  year: 2001
  ident: 142_CR14
  publication-title: Survey methodology
– volume-title: Imputation methods for incomplete dependent variables in finance. School of finance and economics
  year: 2000
  ident: 142_CR10
– volume-title: Handbook of statistical data editing and imputation
  year: 2011
  ident: 142_CR4
  doi: 10.1002/9780470904848
– volume: 8
  start-page: 3
  year: 1999
  ident: 142_CR19
  publication-title: Statistical Methods in Medical Research
  doi: 10.1177/096228029900800102
– volume-title: Analysis of incomplete multivariate data
  year: 1997
  ident: 142_CR18
  doi: 10.1201/9781439821862
– volume: 1
  start-page: 41
  issue: 10
  year: 1991
  ident: 142_CR8
  publication-title: Proceedings of the Survey Research Methods Section of the American Statistical Association
– volume: 19
  start-page: 653
  year: 2009
  ident: 142_CR7
  publication-title: Statistical Methods in Medical Research
  doi: 10.1177/0962280208101273
– volume: 45
  start-page: 1
  year: 2010
  ident: 142_CR2
  publication-title: Journal of Statistical Software.
– ident: 142_CR13
– volume: 91
  start-page: 473
  year: 1996
  ident: 142_CR17
  publication-title: Journal of the American statistical Association
  doi: 10.1080/01621459.1996.10476908
– volume: 41
  start-page: 1
  year: 2006
  ident: 142_CR5
  publication-title: Interstat.
– volume: 169
  start-page: 1133
  year: 2009
  ident: 142_CR20
  publication-title: American Journal of Epidemiology
  doi: 10.1093/aje/kwp026
– volume-title: Statistical analysis with missing data
  year: 2002
  ident: 142_CR11
  doi: 10.1002/9781119013563
– volume: 63
  start-page: 581
  issue: 3
  year: 1976
  ident: 142_CR15
  publication-title: Biometrika
  doi: 10.1093/biomet/63.3.581
– volume: 1
  start-page: 1
  year: 2013
  ident: 142_CR1
  publication-title: Large-scale Assessments in Education
  doi: 10.1186/2196-0739-1-4
– volume: 83
  start-page: 1198
  issue: 404
  year: 1988
  ident: 142_CR12
  publication-title: Journal of the American Statistical Association
  doi: 10.1080/01621459.1988.10478722
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SubjectTerms Econometrics
Economics
Economics and Finance
Finance
Game Theory
Insurance
Management
Original Article
Social and Behav. Sciences
Statistics for Business
Title Imputation of Missing Values in the Fundamental Data: Using MICE Framework
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