Chaitra Nagaraja

Chaitra H. Nagaraja is an associate professor of strategy and statistics at the Gabelli School of Business. She obtained her BS in mathematics at the University of Chicago and her PhD in statistics at the University of Pennsylvania's Wharton School. Before coming to Fordham, she taught statistics at the London School of Economics and was a research mathematical statistician at the U.S. Census Bureau in Washington, D.C. She is interested in macroeconomic applications of statistics, with a particular emphasis on house price indices.

Education

• PhD: The Wharton School, University of Pennsylvania (Statistics)
• MA: The Wharton School, University of Pennsylvania (Statistics)
• BS: University of Chicago (Mathematics with Specialization in Economics)

Research interests

• Time series
• House price indices
• Gini indices
• Survey sampling

Publications

Articles

• Nagaraja, C.H. and Nagaraja, H.N. Distribution-free approximate methods for constructing confidence intervals for quantiles. Forthcoming in the International Statistical Review.
• Nagaraja, C.H. and McElroy, T. (2018). The multivariate bullwhip effect. European Journal of Operational Research, 267(1), 96-106.
• Nagaraja, C.H. (2017). Theory and methods for partitioned Gini coefficients computed on post-stratified data. Communications in Statistics—Theory and Methods, 46(10), 4809-4823.
• McElroy, T. and Nagaraja, C.H. (2016). Tail index estimation with a fixed tuning parameter fraction. Journal of Statistical Planning and Inference, 170, 27-45.
  
• Nagaraja, C.H. and McElroy, T. (2015). On the interpretation of multi-year estimates of the American Community Survey as period estimates. Statistical Journal of the International Association for Official Statistics, 31(4), 661-676.
• Nagaraja, C.H., Thavaneswaran, A., and Appadoo, S.S. (2015). Measuring the bullwhip effect for supply chains with a seasonal demand component. European Journal of Operational Research, 242(2), 445-454.
  
• Nagaraja, C. H. (2014). Introduction to R. In C.R. Rao, M.B. Rao (Eds.), Computational Statistics with R, Handbook of Statistics, 32, 1-48. Oxford, United Kingdom: Elsevier.
• Nagaraja, C.H., Brown, L.D., and Wachter, S. (2014). Repeat sales house price index methodology. Journal of Real Estate Literature, 22, 23-46.
• Nagaraja, C.H. and Brown, L.D. (2013). Constructing and evaluating an autoregressive house price index. In M. Hu, Y. Liu, J. Lin. (Eds.), Topics in Applied Statistics, Springer Proceedings in Mathematics & Statistics, 55, 3-12. New York, NY: Springer.
• Nagaraja, C.H., Brown, L.D., and Zhao, L.H. (2011). An autoregressive approach to house price modeling. Annals of Applied Statistics, 5, 124-149.

Books

• Nagaraja, C.H. (2019). Measuring Society. Chapman and Hall/CRC Press.
• Choudhary, P., Nagaraja, C.H., Ng, H.K.T. (Eds.) (2015). Ordered Data Analysis, Modeling, and Health Research Methods, Springer Proceedings in Mathematics & Statistics, Volume 149. New York, NY: Springer.

Other

• Yang, H., Nagaraja, H.N., Choudhary, P. and Nagaraja, C.H. R Package “BangdiwalaChart.” Published on Github on 12/5/2018. https://github.com/hongbo-yang/BangdiwalaChart/
• Boon, J.E. and Nagaraja, C.H. 7 Surprising facts about women who earn less than men. Published on TIME.com on 10/1/2015. http://time.com/4055916/women-men-pay/
• Boon, J.E. and Nagaraja, C.H. 36 Colleges where women graduates out-earn men. Published on TIME.com on 10/1/2015. http://time.com/4055945/colleges-men-women-pay/
• Nagaraja, C.H. (2015). Deprivation indices for census tracts in Bronx and New York counties. Technical report published by the Global Healthcare Innovation Management Center, Fordham University. http://ghimc.org/pdf/Deprivation_Indices.pdf
  
• Erdman, C. and Nagaraja, C.H. (2010). Imputation procedures for American Community Survey group quarters small area estimation. Census Bureau Research Report (RRS2010/09).
• Nagaraja, C.H., Jensen, S.T., Wyner, A. (2007). Bayesian classification of sleep states in mice. 2007 Proceedings of the American Statistical Association, Section on Bayesian Statistical Science, Salt Lake City, UT: American Statistical Association.