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Data and Code for: Discrete Prices and the Incidence and Efficiency of Excise Taxes

Principal Investigator(s): View help for Principal Investigator(s) Christopher Conlon, NYU Stern; Nirupama Rao, Univeristy of Michigan, Ross School of Business

Version: View help for Version V1

Version Title: View help for Version Title Initial Upload

Name	File Type	Size	Last Modified
PT Replication			03/05/2020 05:02:PM
code			03/05/2020 04:00:PM
outputs			03/05/2020 04:00:PM
public_data			03/05/2020 04:01:PM
README.md	text/x-web-markdown	3.4 KB	03/05/2020 10:59:AM
output.log	text/x-log	19.5 KB	03/05/2020 10:59:AM
requirements.txt	text/plain	76 bytes	03/05/2020 10:59:AM
run_all.sh	application/x-sh	707 bytes	03/05/2020 10:59:AM
setup.R	text/x-r-syntax	732 bytes	03/05/2020 10:59:AM

Project Citation:

Conlon, Christopher, and Rao, Nirupama. Data and Code for: Discrete Prices and the Incidence and Efficiency of Excise Taxes. Nashville, TN: American Economic Association [publisher], 2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-06-17. https://doi.org/10.3886/E117326V1

Project Description

Summary: This paper uses UPC-level data to examine the relationship between excise taxes, retail prices, and consumer welfare in the distilled spirits market. We document a nominal rigidity in retail prices that arises because firms largely choose prices that end in ninety-nine cents and change prices in whole-dollar increments. A correctly specified model, like an ordered logit, takes this discreteness into account when predicting the effects of alternative taxes. Explicitly accounting for price points substantially impacts estimates of tax incidence and the excess burden cost of tax revenue. Meaningful non-monotonicities in these quantities expand the potential considerations in setting excise taxes.

Scope of Project

Subject Terms: Excise Tax; Incidence; Market power; Price Adjustment; Nominal Rigidities

JEL Classification:
H21 Taxation and Subsidies: Efficiency; Optimal Taxation

Geographic Coverage: United States (Connecticut, Louisiana, Illinois)

Time Period(s): 7/1/2007 – 7/31/2013

Collection Date(s): 7/2013 – 8/2013 (Summer 2013)

Universe: Wholesale Alcohol Prices for Connecticut.

Data Type(s): event/transaction data; program source code

Collection Notes: The Connecticut Wholesale Prices were scraped by the authors and assembled from public filings from the Department of Consumer Protection.

Methodology

Data Source: https://biznet.ct.gov/DCPOpenAccess/LiquorControl/ItemList.aspx

Unit(s) of Observation: Wholesaler-Product-Month

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Published Versions

V2 [2020-10-26]

V1 [2020-06-17]

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