# 3_Dove — Temp README

**Topic:** Inflation expectations anchoring (2021–24), Phillips Curve scatter plots comparing pre- vs. post-COVID periods.
**Software:** Stata only. No R, Python, or other dependencies.
**Self-contained:** Yes — all input data and output files are present.

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## Data

| File | Role |
|------|------|
| `Data/Timeseries_SPF_new.xlsx` | Raw input — Survey of Professional Forecasters (inflation & unemployment expectations, quarterly) |
| `Data/Timeseries_SEP_new.xlsx` | Raw input — Fed Summary of Economic Projections (same variables) |
| `Data/Timeseries_SPF.dta` | Processed SPF data |
| `Data/Timeseries_SEP.dta` | Processed SEP data |
| `Data/Timeseries.dta` | Final merged dataset with all expectation gap variables |

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## Scripts (run in order)

1. **`Creating_dtas.do`** — Imports Excel files, assigns quarterly dates, labels variables, saves `.dta` files.
2. **`Creating_full_data.do`** — Merges SPF and SEP on `qdate`; creates ~28 gap variables (e.g., inflation expectation minus 2%, unemployment expectation minus NROU/lagged level).
3. **`Graphing_Scatter_VFdynamicplotting.do`** — Produces 16 scatter PDFs (inflation gap on X, unemployment gap on Y). Pre-COVID (2007Q1–2019Q4) in navy, post-COVID (2021Q1–2025Q2) in orange; separate regression lines for each period.
4. **`Graphing_Scatter_VFdynamicplotting_VNTFINAL.do`** — Same as (3) but axes swapped.

Output: 16 PDFs in `Output/` and duplicated in `Output/Scatter/`.

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## Caveats

- Scripts use hardcoded absolute paths (user's Dropbox directory). Must update `cd` or file paths before running on a different machine.
- SPF: quarterly (Feb/May/Aug/Nov). SEP: quarterly with gaps (COVID 2020Q1 excluded). Until 2015Q2 SEP values are range averages; from 2015Q3 onwards they are medians.
- Excel source files appear to be manually assembled from public SPF/Fed data; no download scripts are included.
