dfm_diagnostics

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Axis dfm_diagnostics on sub-layer L3_5_B_factor_block_inspection (layer l3_5).

Sub-layer

L3_5_B_factor_block_inspection

Axis metadata

  • Default: 'multi'

  • Sweepable: False

  • Status: operational

Operational status summary

  • Operational: 4 option(s)

  • Future: 0 option(s)

Options

factor_var_stability – operational

Plot of DFM factor-VAR coefficient stability over time.

L3.5.B DFM diagnostic factor_var_stability.

This option configures the dfm_diagnostics axis on the L3_5_B_factor_block_inspection sub-layer of L3.5; output is emitted under manifest.diagnostics/l3_5/L3_5_B_factor_block_inspection/ alongside the other selected views.

When to use

Detecting non-stationarity in the factor dynamics; rolling-window estimates flag breaks.

References

  • macroforecast design Part 4: ‘diagnostic layers default-off; non-blocking; produce JSON + matplotlib views attached to manifest.diagnostics/.’

  • Mariano & Murasawa (2003) ‘A new coincident index of business cycles based on monthly and quarterly series’, JAE 18(4): 427-443.

Related options: idiosyncratic_acf, multi, none

Last reviewed 2026-05-05 by macroforecast author.

idiosyncratic_acf – operational

Autocorrelation of DFM idiosyncratic residuals.

L3.5.B DFM diagnostic idiosyncratic_acf.

This option configures the dfm_diagnostics axis on the L3_5_B_factor_block_inspection sub-layer of L3.5; output is emitted under manifest.diagnostics/l3_5/L3_5_B_factor_block_inspection/ alongside the other selected views.

When to use

Validating the idiosyncratic-AR(1) assumption; large residual ACF at lags > 1 indicates misspecification.

References

  • macroforecast design Part 4: ‘diagnostic layers default-off; non-blocking; produce JSON + matplotlib views attached to manifest.diagnostics/.’

  • Mariano & Murasawa (2003) ‘A new coincident index of business cycles based on monthly and quarterly series’, JAE 18(4): 427-443.

Related options: factor_var_stability, multi, none

Last reviewed 2026-05-05 by macroforecast author.

multi – operational

Render both DFM diagnostics together.

L3.5.B DFM diagnostic multi.

This option configures the dfm_diagnostics axis on the L3_5_B_factor_block_inspection sub-layer of L3.5; output is emitted under manifest.diagnostics/l3_5/L3_5_B_factor_block_inspection/ alongside the other selected views.

When to use

Comprehensive DFM validation; recommended after any DFM fit.

References

  • macroforecast design Part 4: ‘diagnostic layers default-off; non-blocking; produce JSON + matplotlib views attached to manifest.diagnostics/.’

  • Mariano & Murasawa (2003) ‘A new coincident index of business cycles based on monthly and quarterly series’, JAE 18(4): 427-443.

Related options: factor_var_stability, idiosyncratic_acf, none

Last reviewed 2026-05-05 by macroforecast author.

none – operational

Skip DFM-specific diagnostics.

L3.5.B DFM diagnostic none.

This option configures the dfm_diagnostics axis on the L3_5_B_factor_block_inspection sub-layer of L3.5; output is emitted under manifest.diagnostics/l3_5/L3_5_B_factor_block_inspection/ alongside the other selected views.

When to use

Pipelines without DFM blocks (PCA-only or no-factor pipelines).

References

  • macroforecast design Part 4: ‘diagnostic layers default-off; non-blocking; produce JSON + matplotlib views attached to manifest.diagnostics/.’

  • Mariano & Murasawa (2003) ‘A new coincident index of business cycles based on monthly and quarterly series’, JAE 18(4): 427-443.

Related options: factor_var_stability, idiosyncratic_acf, multi

Last reviewed 2026-05-05 by macroforecast author.