RDP 2025-05: How Costly are Mark-ups in Australia? The Effect of Declining Competition on Misallocation and Productivity Read me file

Jonathan Hambur and Owen Freestone

August 2025

This ‘read me’ file details the replication files for RDP 2025-05.

Firm-level data used to construct Australian model moments cannot be provided as they are confidential unit record data contained in the ABS Business Longitudinal Analysis Data Environment (BLADE).

Data moments are summarised in ‘Inputs for model.xlsx’, which pulls from raw data files in ‘Inputs’ folder.

Code to construct superelasticity is provided in ‘Datalab code’ folder. The Stata codes were run on Stata MP 16 (64 bit).

Other Australian data moments are taken from work including Hambur (2023) and Champion, Edmond and Hambur (2023) and so code is not provided.

Code and material in ‘Model’ folder is taken directly from Edmond, Midrigan and Xu (2023) (EMX) replication files with minimal changes made, or codes removed (including readme files). Key codes used in this paper, which have been edited, are detailed below and were run on MATLAB 2023a. Some material has been removed from the ‘Model/Figures’ folder in the interest of space (namely saved results, data used by EMX and figures).

Data

  • Inputs\cost_weighted_distr_safe.csv: Cost-weighted distribution of mark-ups, using the main measure of mark-ups in Hambur (2023)

    • Measures include mean, 10th percentile, 5th percentile, median, 75th percentile and 90th percentile

  • Inputs\markups – harmonic.xls: Harmonic sales-weighted average mark=up, taken from Hambur (2023) and Champion et al (2023)

    • ‘aggr’ Is for overall economy; ‘div’ is by division

  • Inputs\Industry cocnentrations.xlsx: Measures of concentration constructed using BAS sales, taken from update of Hambur (2023)

    • See ‘Overview’ sheet for details of measures

  • Inputs\Passthrugh summary.ods: Measures of superelasticity and related measures estimated via code in ‘code’ file. Constructed using codes in ‘DataLab codes’ applied to mark-ups from Hambur (2023)

    • See ‘Details’ sheet for details of measures
  • Inputs\52600550021_2024 (1).xlsx: ABS 5260.0.55.002 ‘Estimates of Industry Multifactor Productivity, Australia’ release. Used for division-level cost shares.

Model

  • Model\Tables\Benchmark\start_calibration_main.m: Estimate parameters for aggregate models; used to create Tables 2, B2 and B5

    • Outputs saved into ‘rdp-2025-05-supplementary-information/Output’ folder
    • Draws on ‘rdp-2025-05-supplementary-information/Inputs for model.xlsx’

  • Model\Tables\Benchmark\start_aggr.m: Estimate costs and mark-up distribution; used to create Tables 4, 5, 11, B3, B6 and B9

    • Outputs saved into ‘rdp-2025-05-supplementary-information/Output’ folder
    • Draws on ‘rdp-2025-05-supplementary-information/Inputs for model.xlsx’ and files in ‘rdp-2025-05-supplementary-information/Output’ folder

  • Model\Tables\Benchmark\start_calibration_div.m: Estimate parameters for division models; used to create Table B7

    • Outputs saved into ‘rdp-2025-05-supplementary-information/Output’ folder
    • Draws on ‘rdp-2025-05-supplementary-information/Inputs for model.xlsx’

  • Model\Tables\Benchmark\start_div.m: Estimate costs for division models; used to create Tables 7 and B8

    • Outputs saved into ‘rdp-2025-05-supplementary-information/Output’ folder
    • Draws on ‘rdp-2025-05-supplementary-information/Inputs for model.xlsx’ and files in ‘Output’ folder

  • Model\Tables\Cournot\start_calibration_agg.m: Estimate parameters for oligopoly; used to create Table 9

    • Outputs saved into ‘rdp-2025-05-supplementary-information/Output’ folder
    • Draws on ‘rdp-2025-05-supplementary-information/Inputs for model.xlsx’

  • Model\Tables\Cournot\start_olig.m: Estimate costs and mark-up distribution; used to create Table 10

    • Outputs saved into ‘rdp-2025-05-supplementary-information/Output’ folder
    • Draws on ‘rdp-2025-05-supplementary-information/Inputs for model.xlsx’ and files in ‘rdp-2025-05-supplementary-information/Output’ folder

Outputs

  • Output\cost_full: Misallocation cost for full economy; used in Tables 4, B3 and B6
  • Output\cost_div: Misallocation cost for divisions; used in Tables 7 and B8
  • Output\cost_oli_ls: Misallocation cost for oligopoly; used in Table 10
  • Output\distr_full: Distribution of mark-ups full economy; used in Table 5
  • Output\out_full: Estimated parameters for full economy; used in Tables 2, B2 and B5
  • Output\out_div: Estimated parameters for divisions; used in Table B7
  • Output\out_oli_ls: Estimated parameters for oligopoly; used in Table 9.
  • Output\welfare: Broader cost measure full economy; used in Tables 11 and B9
  • Output\size_welfare: Broader cost with size subsidy; used in Table B9
  • Output\uni_welfare: Broader cost with uniform subsidy; used in Table B9

Each output noted above has two .do files: ‘_pre’ outputs results for mid-2000s; ‘_post’ outputs results for mid-2010s.

Datalab code:

  • Superelasticity estimation: Estimate superelasticity
  • Superelasticity estimation – time varying: Estimate superelasticity allowing for time variation
  • Superelasticity summary: Summarise superelasticity estimates
  • Superelasticity summary – time varying: Summarise superelasticity estimates that allow for time variation

Estimation code files should be run prior to summary code files.

References

Champion M, C Edmond and J Hambur (2023), ‘Competition, Markups, and Inflation: Evidence from Australian Firm-level Data’, Paper presented at the annual Reserve Bank of Australia Conference on ‘Inflation’, Sydney, 25–26 September.

Edmond C, V Midrigan and DY Xu (2023), ‘How Costly are Markups?’, Journal of Political Economy, 131(7), pp 1619–1675.

Hambur J (2023), ‘Product Market Competition and Its Implications for the Australian Economy’, Economic Record, 99(324), pp 32–57.

14 August 2025

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