Summary:  View help for Summary Data Build Appendix for “The Response of Consumer Spending to Changes in Gasoline Prices"   By Michael Gelman, Yuriy Gorodnichenko, Shachar Kariv, Dmitri Koustas, Matthew D. Shapiro, Dan Silverman, and Steven Tadelis  

Overview

We provide replication code to generate 4 figures and 6 tables in the paper.  The raw (unaggregated) transactions data from the App cannot be disclosed or shared, so are not included in this repository.  The deposited data includes aggregated data for replication purposes (see below). Raw data from the CEX are not included for practical purposes. The replicator should expect the CEX build to run for about 2 hours.  

Statement about Rights

•            I certify that the author(s) of the manuscript have legitimate access to and permission to use the data used in this manuscript.  

Summary of Availability

•            Some data cannot be made publicly available.  

Details on each Data Source

 

Anonymous App Data

This research is carried out in cooperation with a financial aggregation and bill-paying computer and smartphone application (the “app”). The raw (unaggregated) transactions data from the App cannot be disclosed or shared, so are not included in this repository.  

Consumer Expenditure Survey

Our paper uses both the CEX Interview Survey and the CEX Diary Survey. In the directory “replication_files/Zsupplementary_data,” we provide our final builds of the CEX data from which our readers can replicate results reported in the paper. Our final build of the diary survey data is named, “diarybuild.dta” and our final build of the interview survey data is named, “CGKS_Expenditures_updated.dta.”   We do not provide the raw files due to their size, however interested users can replicate our final build after downloading the raw files. We obtained the raw files from the following sources:   1980-1981 Interview Survey *.txt files from NBER http://data.nber.org/ces/1980-1981/ 1980-1981 Diary Survey (ICPSR 8235): https://doi.org/10.3886/ICPSR08235.v2 1982-1989 *.txt files from ICPSR: 1982-1983 Diary Survey (ICPSR 8599): https://doi.org/10.3886/ICPSR08599.v1 1982-1983 Interview Survey (ICPSR 8598): https://doi.org/10.3886/ICPSR08598.v1 1984 Diary Survey (ICPSR 8628): https://doi.org/10.3886/ICPSR08628.v1 1984 Interview Survey (ICPSR 8671): https://doi.org/10.3886/ICPSR08671.v2 1985 Diary Survey (ICPSR 8905): https://doi.org/10.3886/ICPSR08905.v1 1985 Interview Survey (ICPSR 8904): https://doi.org/10.3886/ICPSR08904.v2 1986 Diary Survey (ICPSR 9114): https://doi.org/10.3886/ICPSR09114.v1 1986 Interview Survey (ICPSR 9113): https://doi.org/10.3886/ICPSR09113.v2 1987 Diary Survey (ICPSR 9333): https://doi.org/10.3886/ICPSR09333.v1 1987 Interview Survey (ICPSR 9332): https://doi.org/10.3886/ICPSR09332.v2 1988 Diary Survey (ICPSR 9570): https://doi.org/10.3886/ICPSR09570.v1 1988 Interview Survey (ICPSR 9451): https://doi.org/10.3886/ICPSR09451.v2 1989 Diary Survey (ICPSR 9714): https://doi.org/10.3886/ICPSR09714.v1 1989 Interview Survey (ICPSR 9712): https://doi.org/10.3886/ICPSR09712.v1              1990-1995 *.txt files from NBER http://data.nber.org/ces/ 1996-2014 *.dta files from NBER http://data.nber.org/ces/              2015 *.dta files from BLS https://www.bls.gov/cex/pumd_data.htm#stata              For the NBER files, we store the data locally with the exact file structure at http://data.nber.org/ces/.  For the ICPSR files, we download all files and preserve the original file names.  We organize files in folders with the following file structure: CEX_[YEAR]/Diary and CEX_[YEAR]/Interview, for Diary and Interview data, respectively.   Our build of the raw CEX Interview Survey follows Coibion, Gorodnichenko, Kueng, and Silvia (CGKS) (2012).  We update the CGKS build through 2015. The CGKS build performs the following steps:  sums expenditures that occur in the same month as recommended by the BLS, drops 4th and higher observations per interview, drops household with zero food expenditures in any interview, and corrects panel expenditure variables with sample breaks.  

Michigan Survey of Consumers

Consumer gasoline price expectations are used in Figure 1. The raw data were downloaded from https://data.sca.isr.umich.edu/sda-public/ and are found in the “1Build/Michigan_survey” directory.

 

Other Data

-        Daily AAA gasoline prices downloaded from Bloomberg Terminal (3AGSREG) (Bloomberg L.P. n.d.a.) -        New York Harbor Conventional Gasoline Regular Spot Price (EER_EPMRU_PF4_Y35NY_DPGd), downloaded from Bloomberg Terminal (Bloomberg L.P. n.d.b.) -        Gasoline futures, downloaded from Bloomberg Terminal (XBW1-XBW24) (Bloomberg L.P. n.d.c.) -        BLS city average gasoline prices back to 1976 (FRED series APU000074714). -        West Texas Intermediate spot oil prices (FRED series OILPRICE and MCOILWTICO). -         CPI-U (FRED series CPIAUCSL).

Software Requirements

1.      Bash 2.      Stata (code was last run with version 17) -        the program “required_programs.do” will install all dependencies locally, and should be run once. Portions of the code use bash scripting, which may require Linux.   Memory and Runtime Requirements Summary Approximate time needed to reproduce the analyses on a standard desktop machine: CEX replication code runs in approximately 2 hours. App regressions were run on a compute cluster, requiring approximately 500 hours, or 20 days, of total run time.  Details The CEX code was last run on a 6-core Intel-based laptop with MacOS version 10.14.4. Portions of the code were last run on a 32-core compute cluster with 64 GB of RAM. Computation took approximately 500 hours.  

Dataset list

III. Zsupplementary_data contains publicly available supplementary data used in the analysis. An inventory of these files is given below:     Data file Source   1 3AGSREG_Daily.xlsx Bloomberg L.P. (n.d.a.)   2 APP_biweekly_distribution.dta Constructed from the raw App data 3 BLS_gas_price.xlsx BLS (n.d.)   4 CGKS_Expenditures_updated.dta Provided for convenience. Can be constructed using the files in 1/Build/CEX 5 diarybuild.dta Provided for convenience Can be constructed using the files in 1/Build/CEX 6 EER_EPMRU_PF4_Y35NY_DPGd.xls Bloomberg L.P. (n.d.b.)   7 XBW1-36_Comdty_Daily.xlsx.dta Bloomberg L.P. (n.d.c.)  

 

In addition, the following confidential files derived from App data are needed for full replication but cannot be disclosed or shared:                                                          Data file   1 gas_spending_for_fig3.dta   2 gas_spending_for_fig4.dta   3 totals_userXweek_2013.dta   4 gas_paper_build_dropccnosync_all.dta   5 gas_paper_build_dropccnosync_LARGE1.dta   6 gas_paper_build_dropccnosync_LARGE2.dta   7 gas_paper_build_dropccnosync_LARGE3.dta   8 gas_paper_build_core_dropccnosync_LARGE1.dta   9 gas_paper_build_core_dropccnosync_LARGE2.dta   10 gas_paper_build_core_dropccnosync_LARGE3.dta   11 gas_paper_build_core_dropccnosync_all_quarterly.dta   12 gas_paper_build_core_dropccnosync_all_cexstyle.dta    

 

Description of programs/code

0submit_MASTER.sh - submits all the files outlined below.   0) required_programs.do - Before running any of the following, first run required_programs.do to install required Stata programs via SSC.    I) 1Build contains the Build files to be used in 2Estimation. These must be run first in order to perform estimation. The 1Build directory is organized as follows:              a) CEX - build files for the CEX   The build files for the CEX Interview Data are in the directory “1Build/CEX/interview/CGKS_update”   0MASTER-cgks_replication.do – master do file. Calls other do files in the directory to produce our build of the Interview Survey data, CGKS_Expenditures_updated.dta.   1interview_build_1980-2014.do – reads raw CEX Interview Survey data from NBER and ICPSR   2CGKS_Expenditures_dk.do – performs the CGKS build of the CEX Interview Survey expenditure data. Calls MTABaggregation.do.   MTABaggregation.do – constructs categories of spending from underlying UCC codes   The build files for the CEX Diary Data are in the directory “1Build/CEX/diary” 0diary_build.do – reads in the raw diary survey data downloaded from NBER and produces our build of the diary data, diarybuild.dta. b) Futures - Futures prices are used for constructing the shocks to yield curves.   step1-build_expectations_data_bloomberg.do – reads in New York Harbor spot price and the futures downloaded from Bloomberg step2-yc_surprise.do – calculates the change in one-month ahead and the 24-month-ahead average change in yield curves over different horizons.    c) Michigan_survey - build files for the Michigan Survey of Consumers. The Stata file and data dictionary are autogenerated by the data provider.                d) Misc – gasprices_to_dta.do converts raw data on gas prices to Stata *.dta format.   II) 2Main contains the files to create all tables and underlying data for the figures in the paper. This code is organized as follows:                a) 0overview                            i. Table1.do - Table 1                            ii. Fig1_PanelA+PanelB.do - Figure 1, Panels A and B                b) 1cex_comparison – Code for comparisons to CEX.                            i. CEX_DIARY_compare_w_APP.do - Table 2, Panel A; Figure 3                            ii. CEX_INTERVIEW_compare_w_APP.do - Table 2, Panel B; Figure 4                            iii. CEX_INTERVIEW_baseline.do - Table 5, Panel B   c) 2app – Code for main regressions using app data. In the folder "output", we provide the output from running the estimation in 2app, which are inputs for Zmake_figures.do.                            i. gas_paper_regressions.do - Table 3; Table 4; Output for Figure 5                            ii. gas_paper_hetero_Y_regressions.do - Table 6                            iii. Zmake_figures.do - Makes Figure 5  

List of tables and programs

The provided code reproduces: •            X Selected tables and figures in the paper, as explained and justified below.   Figure/Table # Program Output file Note Table 1 0overview/Table1.do     Table 2 1cex_comparison /CEX_DIARY_compare_w_APP.do   Table 2, Panel B requires confidential data. Table 3 gas_paper_regressions.do   Requires confidential data to run. See “output” folder for regression output. Table 4 gas_paper_regressions.do   Requires confidential data to run. See “output” folder for regression output. Table 5 CEX_INTERVIEW_regression.do   Table 5, Panel B. Table 5, Panel A. Requires confidential data to run. See “output” folder for regression output. Table 6 gas_paper_hetero_Y_regressions.do   Requires confidential data to run. See “output” folder for regression output.

 

Figure 1 0overview/Fig1_PanelA+PanelB.do fig1.eps   Figure 2 n.a.   Requires confidential data. Figure 3 1cex_comparison /CEX_DIARY_compare_w_APP.do fig3.eps   Figure 4 1cex_comparison /CEX_INTERVIEW_compare_w_APP.do fig4a.eps, fig4b.eps, fig4c.eps Figures 4b-4c requires confidential data.

 

Figure 5 2main/Zmake_figures.do fig5a.eps, fig5b.eps, fig5c.eps  

 

References

Bloomberg L.P. n.d.a. 3AGSREG. Retrieved 4/3/2016 from Bloomberg terminal. Bloomberg L.P. n.d.b. EER_EPMRU_PF4_Y35NY_DPG. Retrieved 4/3/2016 from Bloomberg terminal. Bloomberg L.P. n.d.c. XBW1-36_Comdty_Daily. Retrieved 4/3/2016 from Bloomberg terminal. Bureau of Labor Statistics. 1980–2015. “Consumer Expenditure Survey.” United States Department of Labor. https://www.bls.gov/cex/pumd_data.htm. Bureau of Labor Statistics (n.d.), “Average Price: Gasoline, Unleaded Regular (Cost per Gallon/3.785 Liters) in U.S. City Average” [APU000074714]. Retrieved 6/3/2016. Michigan Survey of Consumers. 2006-2016. Surveys of Consumers SDA Archive. Computer-assisted Survey Methods Program (CSM) at the University of California, Berkeley. https://data.sca.isr.umich.edu/sda-public/  

JEL Classification:  View help for JEL Classification
      E21 Macroeconomics: Consumption; Saving; Wealth
      E32 Business Fluctuations; Cycles
      E43 Interest Rates: Determination, Term Structure, and Effects