## 2025octfiscalmonitordatabase — dataset overview

## Source details

**Canonical URL:** [2025octfiscalmonitordatabase — dataset overview](https://www.imf.org/-/media/files/publications/fiscal-monitor/2025/october/data/2025octfiscalmonitordatabase.xlsx)

## Other formats

- [Markdown version](/-/media/files/publications/fiscal-monitor/2025/october/data/2025octfiscalmonitordatabase.xlsx.md)
- [Structured JSON version](/-/media/files/publications/fiscal-monitor/2025/october/data/2025octfiscalmonitordatabase.xlsx.json)

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### Dataset structure and worksheets
- Workbook contains multiple worksheets including: "Table of Contents", "FM Database Oct. 2025", "Figure 1.1.1", "Figure 1.1.2", "Figure 1.1.3", "Figure 1.1.4", "Figure 1.1.5", "Figure 1.1.6", "Figure 1.2", "Figure 1.3.1", "Figure 1.3.2", "Figure 1.3.3", "Figure 1.3.4", "Figure 1.4.1", "Figure 1.4.2", "Figure 1.4.3", "Figure 1.4.4", "Figure 1.5.1-4", "Figure 1.5.5", "Figure 1.5.6", "Figure 1.6", "Box 1.1", "Bow 1.2".
- Worksheet row and column counts (examples):
  - "Table of Contents": rowCount 62, columnCount 12.
  - "FM Database Oct. 2025": rowCount 33, columnCount 10.
  - "Figure 1.1.1": rowCount 9, columnCount 67.
  - "Figure 1.4.1": rowCount 163, columnCount 21.
  - "Figure 1.6": rowCount 209, columnCount 36.

### Key variables, categories, and groupings
- Recurrent variable labels and groupings:
  - Regional/income groups: "Advanced economies", "Emerging markets", "Low-income developing countries" (also seen as "LIDC", "LIC").
  - Expenditure series: "Expenditure: PFMH" across groupings "AE", "EM", "LIDC".
  - Sector labels in charts/tables: "Defense", "Education", "Health", "R&D", "Social protection", "General public services", "Other".
  - Efficiency and gaps metrics: "eff_gap", "spending rigidity", "avg-q10", "q90-avg", quantiles "q10", "q25", "q75", "q90".
  - Regression/summary fields in Figure 1.4.1 and Figure 1.4.2: "country", "Y", "X", "GDPPC", "income", "band", "upper", "lower", "OLS_summary", "variable", "coef", "const", "var_coef", "var_const", "var_cross".

### Sample time series and central numeric series (preserved exactly as in source)
- From "Figure 1.1.1" — "Expenditure: PFMH", "AE" series (selected values by column headers 1960…2023):
  - 22.919686, 24.342112, 24.807945, 25.154779, 24.55541, 24.678643, 25.247355, 26.359944, 27.896454, 27.807804, 30.368458, 31.329376, 31.930619, 31.501869, 33.023676, 35.823846, 35.480476, 35.278616, 37.045011, 36.796237, 38.361842, 39.336697, 40.683615, 40.770185, 40.034273, 40.065253, 39.684709, 39.247811, 38.409159, 38.193439, 38.997616, 39.897868, 41.122482, 42.080406, 40.958566, 42.154983, 40.786961, 39.586816, 39.798192, 38.874272, 37.852891, 38.748565, 39.182554, 39.546811, 38.986001, 38.914959, 38.517866, 38.541906, 40.285379, 44.090431, 43.111304, 41.835184, 41.422784, 40.678462, 40.143566, 39.647153, 39.47128, 39.126717, 39.08995, 39.465758, 47.011348, 44.863695, 41.453313, 41.122618
- From "Figure 1.1.1" — "Expenditure: PFMH", "EM" series (selected values):
  - 12.592623, 13.767665, 15.13136, 15.687371, 16.018091, 15.430897, 16.086343, 16.215144, 16.134225, 15.203559, 15.325553, 15.556912, 16.173433, 15.896317, 16.656962, 18.013809, 18.288519, 18.797266, 19.328688, 18.852497, 17.883109, 18.788682, 19.933601, 19.320416, 18.775882, 20.349515, 20.730307, 22.174813, 21.625717, 20.836507, 20.641936, 21.807741, 21.596685, 21.144369, 20.528565, 21.254146, 23.310333, 23.984796, 25.895307, 25.43788, 25.185431, 26.8358, 27.578114, 26.844029, 25.778411, 25.754573, 26.011285, 26.134, 28.073262, 30.047856, 28.957213, 29.194818, 29.689316, 29.7405, 29.892889, 30.984854, 30.907455, 30.382966, 30.589404, 31.021008, 33.710155, 31.174172, 31.309779, 31.81085
- From "Figure 1.1.1" — "Expenditure: PFMH", "LIDC" series (selected values):
  - 12.5015, 12.111027, 13.5065, 11.497365, 9.6938672, 10.891643, 11.410882, 11.249736, 12.666073, 12.852633, 12.45457, 10.482962, 11.266434, 14.11506, 13.724887, 15.271757, 13.397301, 13.452888, 16.641972, 17.43231, 18.750022, 17.964951, 16.954232, 16.649555, 16.148303, 17.054918, 16.554875, 16.5133, 17.809579, 17.798425, 19.577842, 19.779333, 16.406805, 15.038994, 13.522247, 15.025478, 15.93751, 16.641507, 17.699579, 19.025631, 17.329244, 18.740017, 17.463827, 17.77791, 16.767633, 18.377528, 17.777027, 18.566614, 18.630273, 18.258144, 18.674443, 19.013118, 18.442226, 17.805162, 17.108163, 17.130505, 17.520002, 17.617914, 18.413217, 18.099798, 18.523005, 17.938382
- From "Figure 1.1.2" — distributional and summary statistics (preserved exactly):
  - Advanced economies, 1995–2009: Mean 12.615934278787877, p25 8.1124878, p75 13.045041, p10 5.8013247, p90 24.706831600000005, Avg - p10 6.814609578787877, p90 - Avg 12.090897321212127, min 4.1665158, max 38.427904, Avg - min 8.449418478787877, max - Avg 25.811969721212122
  - Advanced economies, 2010–2022: Mean 11.062424848484845, p25 7.0184114, p75 13.234388, p10 5.51476696, p90 21.418651800000006, Avg - p10 5.547657888484845, p90 - Avg 10.356226951515161, min 4.6622537, max 34.09633, Avg - min 6.400171148484845, max - Avg 23.033905151515157
  - Emerging markets excluding China, 1995–2009: Mean 21.88625569459459, p25 14.3218735, p75 28.5489565, p10 10.7008043, p90 34.6204108, Avg - p10 11.185451394594589, p90 - Avg 12.734155105405414, min -11.230773, max 80.929764, Avg - min 33.11702869459459, max - Avg 59.04350830540542
  - Emerging markets excluding China, 2010–2022: Mean 19.802930644303803, p25 12.9464295, p75 25.0535085, p10 8.92872956, p90 30.381790000000006, Avg - p10 10.874201084303802, p90 - Avg 10.578859355696203, min 3.400964, max 66.31422, Avg - min 16.401966644303805, max - Avg 46.511289355696206
  - Low-income developing countries, 1995–2009: Mean 31.97664794318183, p25 22.4494225, p75 40.1635575, p10 17.6316762, p90 49.2163157, Avg - p10 14.34497174318183, p90 - Avg 17.23966775681817, min 9.5371905, max 61.069173, Avg - min 22.43945744318183, max - Avg 29.092525056818168
  - Low-income developing countries, 2010–2022: Mean 31.619987414893608, p25 23.0708505, p75 38.7975275, p10 19.6255492, p90 44.536761399999996, Avg - p10 11.99443821489361, p90 - Avg 12.916773985106389, min 5.7286725, max 72.261685, Avg - min 25.891314914893606, max - Avg 40.64169758510639

### Sectoral shares and composition (selected exact values)
- From "Figure 1.1.3" (sector shares, preserved exactly):
  - Advanced economies, 1995–2009: Defense 9.988719946666667, Education 12.712111600000002, Health 15.223866600000001, R&D 0.3830674293333333, Social protection 33.17507559999999, General public services 15.990038266666668, Other 12.527120557333333
  - Advanced economies, 2010–2022: Defense 9.785681861538462, Education 12.684095692307693, Health 19.38147946153846, R&D 0.426512886923077, Social protection 32.72587738461538, General public services 13.48928976923077, Other 11.507062943846165
  - Emerging markets excluding China, 1995–2009: Defense 12.508390606666666, Education 12.842950733333332, Health 9.052858800000001, R&D 0.24139337466666666, Social protection 32.4430328, General public services 20.979303666666667, Other 11.932070018666664
  - Low-income developing countries, 2010–2022: Defense 40.14490907692307, Education 18.214121692307693, Health 8.225813823076923, R&D 0.5467973922222221, Social protection 18.102001307692305, General public services 13.10696246153846, Other 1.65939424623933

### Quantiles, dispersion, and wage metrics (preserved)
- Public wage bill to exp ("Figure 1.1.4") — Advanced economies:
  - 10pct 19.7156432, 90pct 30.1756442, 90-10pct 10.460001000000002, Median 24.210747, Average 24.915439134228173, 25pct 22.258176, 75pct 26.9159945, avg-q10 5.199795934228174, q90-avg 5.260205065771828, q25-q10 2.5425328, q90-q75 3.2596497000000006
- Public wage premium ("Figure 1.1.5") — Advanced economies:
  - 10pct -6.868751679999998, 90pct 15.80519160000001, 90-10pct 22.673943280000007, Median 5.0609257, Average 5.186112303333333, 25pct 0, 75pct 12.83305725, avg-q10 12.05486398333333, q90-avg 10.619079296666676, q25-q10 6.868751679999998, q90-q75 2.97213435000001

### Country-level regressions, bands, and summaries (Figure 1.4.1 and 1.4.2 samples)
- Figure 1.4.1 — example rows with exact values:
  - Australia: Y 0.366836660833333, X 1.95045669484443, GDPPC 1.3990496461502, income "AE", band -2, computed G result 0.44537721627387744, computed H result 0.011655472897022205, upper 0.46455046918947895, lower 0.42620396335827593, I2-J2 0.038346505831203026; OLS "cci" coef -0.0348501288053897, const 0.375676958663098, var_coef 0.0000202937778808817, var_const 0.0000263853640318887, var_cross -0.00000707239322445092.
  - Austria: Y 0.332786312083333, X 1.69559150711972, GDPPC 1.48657947037989, income "AE", band -1.5, G result 0.4279521518711826, H 0.009657305210938778, upper 0.4438384189431769, lower 0.41206588479918826, I3-J3 0.03177253414398862.
  - Croatia (Figure 1.4.1 example): Y 0.373201160416667, X 0.156330152609049, GDPPC 0.905603213241348, income "AE", band 0, G result 0.375676958663098, H 0.005136668573296189, upper 0.38412677846617027, lower 0.3672271388600258, I-J 0.01689963960614449.
- Figure 1.4.2 — sample rows preserve alternative OLS summaries and computed bands (examples):
  - Croatia: Y 0.373201160416667, X 1.798, GDPPC 0.905603213241348, income "AE", band -2, G result 0.7405181226579072, H 0.10621892534567776, upper 0.915248254851547, lower 0.5657879904642673, I-J 0.34946026438727973; OLS_summary "pima_allo_eff" coef -0.0968949497655411, const 0.546728223126825, var_coef 0.000818353804032781, var_const 0.00243582453020154, var_cross -0.0013933050888145.
  - Greece: Y 0.351303700434783, X 1.868, GDPPC 1.0293336759325, income "AE", band -1, G result 0.6436231728923661, H 0.07772250968582603, upper 0.7714767013255499, lower 0.5157696444591824, I-J 0.2557070568663675.

### Impulse response and coefficient tables (selected exact entries)
- "Figure 1.5.1-4" — rows sample:
  - Row entries: [0, 1.7556895, 0.7431181562000001]; [5, 7.8343786, 2.6719093450000004]; [10, 4.3938234, 1.33722045065]
  - Education/Health IRF samples: [0, 0.32820967, 0.5799039869]; [5, 0.088958652, 2.1531455995]; [10, 0.12899964, 2.523207267]
- "Figure 1.5.5" — parameter estimates for production components (examples):
  - lrkna / pubinv / Investment / K: 4.0389348, 1.8927202210000003
  - lemp / pubinv / Investment / L: 0.78965584, 1.55841294105
  - lrtfpna / pubinv / Investment / TFP: 2.5680769, 2.3157206205
  - lrkna / health / Health / K: 3.0732417, 3.386162752
- "Figure 1.5.6" — coefficient and 90% CI by quartile (examples):
  - 25 / pubinv / Investment / Low: -1.1014924000000001, 6.8058468205
  - 75 / pubinv / Investment / High: 7.293364400000001, 4.75386576
  - 25 / health / Health / Low: -24.084965999999998, 25.06852019
  - 75 / health / Health / High: 2.1740356, 2.8869613465

### Box 1.1 regression summaries (selected exact rows)
- "Box 1.1" — comp_progr_r with ctr_crisis (horizons 0–5) (examples preserve coef, se, N, critical values):
  - horizon 0: coef 0.0708822619229727, se 0.331700802079527, N 576, N_g 39, df_m 20, df_r 16, F 7233.18788451074, r2_w 0.0739881966814323, lag 2; low -0.47471700544024903, high 0.6164815292861945; Critical value (z) for 90% CI: 1.64485362695147.
  - horizon 1: coef -0.515857024765081, se 0.361130603484539, low -1.109864007709798, high 0.07814995817963621.
  - horizon 2: coef -0.741669630485224, se 0.406510975697932, low -1.4103206832575483, high -0.07301857771289977.

### Notable computed statistics and correlations
- Figure 1.4.1 and 1.4.2 show computed band upper/lower values using formulas with exact numeric results (examples preserved above).
- Correlation formulas/results included in worksheets:
  - Example: CORREL(B2:B163,C2:C163) result -0.45686284983094666 (Figure 1.4.1 sample).
  - Example: CORREL(B2:B163,C2:C163) result -0.33407961651259205 (Figure 1.4.2 sample).

*2025octfiscalmonitordatabase.xlsx*

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_Source: https://www.imf.org/-/media/files/publications/fiscal-monitor/2025/october/data/2025octfiscalmonitordatabase.xlsx_