RDP 2023-09: Does Monetary Policy Affect Non-mining Business Investment in Australia? Evidence from BLADE Read me file

Supplementary Information

Read me file

This ‘read me’ file details the replication files for RDP 2023-09. Firm-level of the data cannot be provided as they are confidential unit record data contained in the ABS Business Longitudinal Analysis Data Environment (BLADE). Data for figures appearing in the RDP can be found in the spreadsheet ‘rdp-2023-09-graph-data’. The ‘codes’ folder contains Stata's do files that are used to produce the results presented in the paper and the appendices. The Stata codes were run on Stata MP 16 (64 bit) and draw on the files in the ‘ado’ folder.

If you make use of any of these files you should clearly attribute the authors in any derivative work.

Data

  • Rajan zingales – Demmou et al.xlsx – measures of finance dependency mapped to ANZSIC industries. Measures constructed from Demmou, Stefanescu and Arquie (2019).
  • aggregate_data.xlsx – data used for producing aggregate local projection results (Figures 2 and B3).
    • nmbi: non-mining business investment – ABS national accounts
    • btcs: Beckers (2020) shock measure, not accounting for cash rate expectations
    • btcs_ua: Beckers (2020) shock measure, accounting for cash rate expectations – preferred
    • gdp: real gross domestic product level – ABS national accounts
    • gdp: real gross national expenditure level – ABS national accounts
    • me: non-mining machinery and equipment investment – ABS national accounts
    • nrb; non-residential building investment – ABS national accounts
    • eng: non-mining engineering investment – ABS national accounts
    • minv: mining investment – ABS national accounts
    • nmbi_n: nominal non-mining business investment – ABS national accounts
    • me_n: nominal non-mining machinery and equipment investment – ABS national accounts
    • cr: cash rate changes – RBA statistical table F1.1 Interest Rates and Yields – Money Market – Monthly
  • Figure B1 vars.wf1 – Eviews 13 workfile with VAR models for Figure B1. Data as above.

All other data are BLADE or Morningstar data and cannot be provided. They are on the 2017/18 vintage of BLADE. Code files will enable replication, though variable names and basic data construction codes will vary due to changes in the data structure.

Code

Set of code to produce firm-level regression results. Requires access to BLADE.

  • 00 Data set build.do
  • 00a Summary stats.do
  • 01 Baseline results.do
  • 02 By size.do
  • 03 leaders.do
  • 04 By financial dependence.do
  • 05 Fin constrained.do
  • 06 capexregs.do

Code to construct aggregate local projections results: aggregate_lp.do

Code to estimate leader laggard regressions using listed company data for Figure B2 (requires database from Nguyen (2022)): Morningstar results.do

References

Beckers B (2020), ‘Credit Spreads, Monetary Policy and the Price Puzzle’, RBA Research Discussion Paper No 2020-01.

Demmou L, I Stefanescu and A Arquie (2019), ‘Productivity Growth and Finance: The Role of Intangible Assets – A Sector Level Analysis’, OECD Economics Department Working Papers No 1547.

Ngyuen K (2022), ‘The Real Effects of Debt Covenants: Evidence from Australia’, RBA Research Discussion Paper No 2022-05.

11 December 2023

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