1 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

R: Innovating at the Bureau of 

Labor Statistics

Arcenis Rojas

Economist

Division of Consumer Expenditure Surveys

Federal Committee on Statistical Methodology

March 2018
2 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Overview

 IPP: Division of International Prices

 PPI: Division of Industrial Prices and Price 

Indexes

 CE: Division of Consumer Expenditure Survey

 OCWC: Office of Compensation and Working 

Conditions

 OSMR: Office of Survey Methods and 

Research
3 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Overview

 Automation (IPP)

 Quality control (PPI)

 Real-time response rates (OCWC)

 Data visualization (CE)

 Other R Shiny applications

 R packages
4 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

R Shiny Applications
5 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Sample Refinement Automation

 International Prices Program

Receive data from Census and Customs

Must verify Establishment ID Number (EIN), 

name, and address to provide to field economists

1700 export collections units per sample

2400 import collection units per sample

6 IPP sample team members

16 copies, 20 pastes, and 46 clicks per unit
6 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Data Sources
7 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

4

1

3

2

5
8 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Left Side
9 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Right Side
10 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Search Results
11 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Export Addresses at a Glance
12 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

 80-100 hours per sample of time savings

Much less clicking

Better and more thorough sample review

More time to review more problematic collection 

units

Benefits of Automation
13 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Sample Refinement Automation

 Ara Khatchadourian: 

khatchadourian.ara@bls.gov

 Rob Sutton: sutton.robert@bls.gov
14 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Industrial Prices Visualization 

Dashboard
15 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Index Comparisons
16 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Index Review and Revision
17 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Visualization Dashboard

 Neil Wagner: wagner.neil@bls.gov

 Steve York: york.stephen@bls.gov
18 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Interactive CE Visualization Tool
19 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

CE Public-Use Microdata (PUMD)

 Public-Use Microdata

Family-level characteristics

Expenditures by Universal Classification Code 

(UCC)

Member-level characteristics

Expenditures and their characteristics by type of 

expenditure (EXPN... > 50 files each year!)

And more!
20 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Files Required for Analysis

Family Characteristics File 

(34,177 Observations)

Expenditures File

(1,720,755 Observations)
21 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Required Resources / Skills
22 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Interactive CE Visualization Tool
23 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Interactive CE Visualization Tool

1 2 3

4
24 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Interactive CE Visualization Tool

1
25 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Interactive CE Visualization Tool

2
26 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Interactive CE Visualization Tool

3

4
27 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Interactive CE Visualization Tool

Error Bars

Mean = $30,040.00

CV = 24.12%

Sample Size = 3

Lower Bound = $15,548.70

Upper Bound = $44,531.30
28 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Benefits to the user

 Accessibility: The user can access the app for 

free as long as they have internet access on 

a device with a web browser

 Usability: The user operates only the clean, 

user-friendly UI to get data, results, and 

visualizations
29 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Interactive CE Visualization Tool

 Arcenis Rojas: rojas.arcenis@bls.gov
30 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Real-time Response Rate Tool

 Office of Compensation and Working 

Conditions

 Provide real-time response rates to field 

offices

Focus on problem collection areas

Improved sample representativity
31 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Real-time Response Rate Tool

Response rates by region and/or 

establishment size

Detailed summaries for each region
32 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Real-time Response Rate Tool

 Brandon Kopp (OSMR): 

kopp.brandon@bls.gov

 Randall Powers (OSMR): 

powers.randall@bls.gov

 Arcenis Rojas (CE): 

rojas.arcenis@bls.gov
33 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Other Shiny Applications

 Choropleth maps of unemployment data 

(OSMR)

 Energy Information Administration analyzer 

(PPI)

 Text analysis Shiny App (Survey Methods)
34 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

R Packages
35 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

R Packages

 rpms: Recursive Partitioning for Modeling 

Survey Data package (Survey Methods)

 growfunctions: Bayesian Non-Parametric 

Dependent Models for Time-Indexed 

Functional Data package (Survey Methods)
36 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

rpms

 Fits a linear model to survey data in each node 

obtained by recursively partitioning the data.

 Adjusts for complex sample design features 

used to obtain the data.

 Produces design-consistent coefficients to the 

least squares linear model between the 

dependent and independent variables.
37 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

rpms

 The main function returns the resulting binary 

tree with the linear model fit at every endnode.

 Daniell Toth (OSMR): toth.daniell@bls.gov
38 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

growfunctions

 Bayesian Non-Parametric Dependent Models 

for Time-Indexed Functional Data package 

(Survey Methods)

 Estimates a collection of time-indexed 

functions under either of Gaussian process 

(GP) or intrinsic Gaussian Markov random field 

(iGMRF) prior formulations
39 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

growfunctions

 Dirichlet process mixture allows sub-groupings 

of the functions to share the same covariance 

or precision parameters

 The GP and iGMRF formulations both support 

any number of additive covariance or 

precision terms, respectively, expressing 

either or both of multiple trend and 

seasonality. 
40 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

growfunctions

 Terrance Savitsky (OSMR): 

savitsky.terrance@bls.gov
41 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Challenges
42 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Challenges

 Data confidentiality

 Need for an R server to make apps/programs 

public

 Can only put Shiny apps on a webpage via 

iFrames or setting up an account on a cloud 

server (i.e., Digital Ocean, R Studio)
Contact Information

43 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Arcenis Rojas

Economist

Division of Consumer Expenditure Surveys

www.bls.gov/cex

202-691-6884

rojas.arcenis@bls.gov