{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a4768f93",
   "metadata": {},
   "source": [
    "# Replication notebook\n",
    "## Coca Booms, Ports, and the Onset of Ecuador’s Territorial Homicide Divide (2014–2025): Evidence across Four Subnational Scales\n",
    "\n",
    "This notebook reproduces every table and figure in the article, as well as every number cited in the text:\n",
    "\n",
    "| Section | Output |\n",
    "|---|---|\n",
    "| 3 | Panels A–D (Table 1) |\n",
    "| 4 | Event studies, reference year **2019** (main) and **2020** (robustness); joint HC3 Wald pre-trend tests (Tables 2–3; Figures 2, 3, A1, A2) |\n",
    "| 5 | Port-proximity exposure and event study (Figure 5; Table 3) |\n",
    "| 6 | Coca-shift models by window, wild cluster bootstrap, permutation, lag, trend and horse race (Tables 4–5; Figure 4) |\n",
    "| 7 | Key numbers cited in the text |\n",
    "\n",
    "**Data (folder `data/`):**\n",
    "* `mdi_homicidiosintencionales_pm_2014_2025.xlsx` — Ministry of the Interior of Ecuador, intentional homicides, Jan 2014–Dec 2025 (update of 15 May 2026), sheet *1. Homicidios Intencionales*, N = 39,819.\n",
    "* `cultivos_coca_Colombia.xlsx` — hectares of coca in Colombia, UNODC–SIMCI 2014–2024; SIIMA–Policía Nacional, December 2025.\n",
    "* `Distancias_Puertos_y_Fronteras.xlsx` — minimum distance (km) from each canton to eight seaports and to land borders.\n",
    "\n",
    "**Model.** For each panel, log(1 + H_it) = λ_i + γ_t + Σ_τ δ_τ·1(t = τ)·E_i + ε_it, where E_i is the Coast dummy (or standardized port proximity) and the reference year is omitted. Standard errors are HC3. Coca-shift models: log(1 + H_it) = λ_i + γ_t + θ·(E_i × ln Coca_t) + ε_it, estimated within windows, with province-clustered SEs, a Webb wild cluster bootstrap-t (null imposed) and permutation of coca years.\n",
    "\n",
    "Running time: about 1–5 minutes (most of it is the wild bootstrap). Set `FAST = True` to skip the bootstrap and the permutation tests."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae31240a",
   "metadata": {},
   "source": [
    "## 0. Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0c852584",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:24:41.714483Z",
     "iopub.status.busy": "2026-10-09T11:24:41.714321Z",
     "iopub.status.idle": "2026-10-09T11:24:43.163667Z",
     "shell.execute_reply": "2026-10-09T11:24:43.162273Z"
    }
   },
   "outputs": [],
   "source": [
    "import sys, subprocess, importlib.util\n",
    "for pkg in (\"openpyxl\", \"statsmodels\"):\n",
    "    if importlib.util.find_spec(pkg) is None:\n",
    "        subprocess.run([sys.executable, \"-m\", \"pip\", \"install\", \"-q\", pkg], check=True)\n",
    "\n",
    "import warnings, itertools, unicodedata\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import statsmodels.api as sm\n",
    "from scipy import stats\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mp\n",
    "\n",
    "pd.set_option(\"display.width\", 200); pd.set_option(\"display.max_columns\", 30)\n",
    "FAST = False          # True: skip wild bootstrap and permutation tests (point estimates and clustered SEs only)\n",
    "SEED = 1              # seed of the wild bootstrap (each model call is re-seeded, so results do not depend on call order)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b25ebd38",
   "metadata": {},
   "source": [
    "## 1. Data location\n",
    "\n",
    "**Option A (default):** upload and unzip the replication package in Colab, so that the folder `data/` sits next to this notebook (e.g. `!unzip Replication_Ecuador_Divide.zip`, then `%cd Replication_Ecuador_Divide`).\n",
    "\n",
    "**Option B:** put the package in Google Drive and set `DRIVE_DIR`.\n",
    "\n",
    "**Option C:** if `data/` is not found, the cell asks you to upload the three Excel files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6e3c72b2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:24:43.165798Z",
     "iopub.status.busy": "2026-10-09T11:24:43.165520Z",
     "iopub.status.idle": "2026-10-09T11:24:43.173421Z",
     "shell.execute_reply": "2026-10-09T11:24:43.172444Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data folder: /tmp/claude-0/-home-claude/fb344881-8533-56c7-87d8-1e80c6c38743/scratchpad/pkg/Replication_Ecuador_Divide/data\n",
      "Outputs  -> /tmp/claude-0/-home-claude/fb344881-8533-56c7-87d8-1e80c6c38743/scratchpad/pkg/Replication_Ecuador_Divide/output\n"
     ]
    }
   ],
   "source": [
    "DRIVE_DIR = None   # e.g. \"/content/drive/MyDrive/Replication_Ecuador_Divide\"\n",
    "IN_COLAB = \"google.colab\" in sys.modules\n",
    "\n",
    "if DRIVE_DIR:\n",
    "    from google.colab import drive\n",
    "    drive.mount(\"/content/drive\")\n",
    "    BASE = Path(DRIVE_DIR)\n",
    "else:\n",
    "    BASE = Path(\".\")\n",
    "    if not (BASE / \"data\").exists() and Path(\"Replication_Ecuador_Divide/data\").exists():\n",
    "        BASE = Path(\"Replication_Ecuador_Divide\")\n",
    "DATA = BASE / \"data\"\n",
    "FILES = {\"hom\": \"mdi_homicidiosintencionales_pm_2014_2025.xlsx\",\n",
    "         \"coca\": \"cultivos_coca_Colombia.xlsx\",\n",
    "         \"dist\": \"Distancias_Puertos_y_Fronteras.xlsx\"}\n",
    "if not all((DATA / f).exists() for f in FILES.values()):\n",
    "    if IN_COLAB:\n",
    "        from google.colab import files\n",
    "        DATA.mkdir(parents=True, exist_ok=True)\n",
    "        print(\"Upload the three Excel files:\", list(FILES.values()))\n",
    "        for name, content in files.upload().items():\n",
    "            (DATA / name).write_bytes(content)\n",
    "    missing = [f for f in FILES.values() if not (DATA / f).exists()]\n",
    "    assert not missing, f\"Missing data files in {DATA}: {missing}\"\n",
    "OUT = BASE / \"output\"; OUT.mkdir(exist_ok=True)\n",
    "print(\"Data folder:\", DATA.resolve()); print(\"Outputs  ->\", OUT.resolve())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "791532a4",
   "metadata": {},
   "source": [
    "## 2. Homicide microdata, coca series and port distances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b58b7de4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:24:43.175321Z",
     "iopub.status.busy": "2026-10-09T11:24:43.175046Z",
     "iopub.status.idle": "2026-10-09T11:24:51.623586Z",
     "shell.execute_reply": "2026-10-09T11:24:51.622527Z"
    },
    "lines_to_next_cell": 1
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Records: 39,819 | 2014-01-01 to 2025-12-31\n",
      "Provinces: 24 | cantons with at least one homicide: 216\n",
      " year     ha    lncoca  lncoca_l1\n",
      " 2014  69132 11.143773        NaN\n",
      " 2015  96085 11.472988  11.143773\n",
      " 2016 146140 11.892320  11.472988\n",
      " 2017 171495 12.052309  11.892320\n",
      " 2018 169018 12.037760  12.052309\n",
      " 2019 154476 11.947794  12.037760\n",
      " 2020 142784 11.869088  11.947794\n",
      " 2021 204257 12.227134  11.869088\n",
      " 2022 230028 12.345956  12.227134\n",
      " 2023 252572 12.439452  12.345956\n",
      " 2024 261386 12.473754  12.439452\n",
      " 2025 258144 12.461273  12.473754\n"
     ]
    }
   ],
   "source": [
    "df = pd.read_excel(DATA / FILES[\"hom\"], sheet_name=\"1. Homicidios Intencionales\")\n",
    "df[\"fecha_infraccion\"] = pd.to_datetime(df[\"fecha_infraccion\"])\n",
    "COSTA = [\"ESMERALDAS\", \"MANABÍ\", \"SANTA ELENA\", \"GUAYAS\", \"EL ORO\", \"LOS RÍOS\", \"STO DGO DE LOS TSÁCHILAS\"]\n",
    "df[\"grupo\"] = np.where(df.provincia.isin(COSTA), \"Costa\", \"Resto\")\n",
    "df[\"year\"] = df.fecha_infraccion.dt.year; df[\"month\"] = df.fecha_infraccion.dt.month\n",
    "df[\"quarter\"] = (df.month - 1) // 3 + 1\n",
    "df[\"canton_id\"] = df.provincia + \" - \" + df.canton\n",
    "df[\"ym\"] = df.year.astype(str) + \"_\" + df.month.astype(str).str.zfill(2)\n",
    "df[\"y\"] = df.year.astype(str)\n",
    "df[\"yq\"] = df.year.astype(str) + \"_T\" + df.quarter.astype(str)\n",
    "print(f\"Records: {len(df):,} | {df.fecha_infraccion.min():%Y-%m-%d} to {df.fecha_infraccion.max():%Y-%m-%d}\")\n",
    "print(\"Provinces:\", df.provincia.nunique(), \"| cantons with at least one homicide:\", df.canton_id.nunique())\n",
    "\n",
    "COCA = pd.read_excel(DATA / FILES[\"coca\"]).iloc[:, :2]\n",
    "COCA.columns = [\"year\", \"ha\"]\n",
    "COCA[\"lncoca\"] = np.log(COCA.ha); COCA[\"lncoca_l1\"] = COCA.lncoca.shift(1)\n",
    "print(COCA.to_string(index=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2e68f7e5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:24:51.625717Z",
     "iopub.status.busy": "2026-10-09T11:24:51.625477Z",
     "iopub.status.idle": "2026-10-09T11:24:51.774966Z",
     "shell.execute_reply": "2026-10-09T11:24:51.773614Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cantons with zero homicides 2014–2025:\n",
      "        provincia                ck grupo  mindist_km\n",
      "           AZUAY               ONA Resto   99.812331\n",
      "          EL ORO         MARCABELI Costa   58.205598\n",
      "       GALÁPAGOS           ISABELA Resto 1176.132805\n",
      "       GALÁPAGOS     SAN CRISTOBAL Resto  997.876043\n",
      " MORONA SANTIAGO SEVILLA DON BOSCO Resto  226.605060\n",
      "ZAMORA CHINCHIPE          YACUAMBI Resto  121.042631\n",
      "\n",
      "Mainland cantons: 219 (Coast 86, interior 133); mean minimum distance: Coast 58.4 km, interior 163.0 km\n"
     ]
    }
   ],
   "source": [
    "# --- minimum distance from each canton to the eight seaports\n",
    "def nrm(s):\n",
    "    return unicodedata.normalize(\"NFKD\", str(s)).encode(\"ascii\", \"ignore\").decode().upper().strip()\n",
    "\n",
    "PORTS = [\"Puerto de San Lorenzo\", \"Puerto de Esmeraldas\", \"Puerto de Bahía de Caráquez\", \"Puerto de Manta\",\n",
    "         \"Puerto de La Libertad\", \"Puerto de Guayaquil\", \"Puerto de Posorja\", \"Puerto Bolívar\"]\n",
    "D = pd.read_excel(DATA / FILES[\"dist\"]); D.columns = [\"canton\", \"prov\", \"sitio\", \"dm\", \"dkm\"]\n",
    "D = D[D.sitio.isin(PORTS)]\n",
    "mn = D.loc[D.groupby([\"prov\", \"canton\"]).dkm.idxmin()][[\"prov\", \"canton\", \"sitio\", \"dkm\"]]\n",
    "mn = mn.rename(columns={\"dkm\": \"mindist_km\", \"sitio\": \"nearest_port\"})\n",
    "# canton/province names that are spelled differently in the two sources\n",
    "FIX = {\"CRNEL. MARCELINO MARIDUENA\": \"CORONEL MARCELINO MARIDUENA\", \"GNRAL. ANTONIO ELIZALDE\": \"GENERAL ANTONIO ELIZALDE\",\n",
    "       \"PUEBLO VIEJO\": \"PUEBLOVIEJO\", \"BOLIVAR (MANABI)\": \"BOLIVAR\", \"OLMEDO (MANABI)\": \"OLMEDO\"}\n",
    "PFIX = {\"SANTO DOMINGO DE LOS TSACHILAS\": \"STO DGO DE LOS TSACHILAS\"}\n",
    "mn[\"ck\"] = mn.canton.map(nrm).replace(FIX); mn[\"pk\"] = mn.prov.map(nrm).replace(PFIX)\n",
    "mn[\"key\"] = mn.pk + \"|\" + mn.ck\n",
    "mn = mn[~mn.pk.isin([\"ISLA\"]) & ~mn.pk.str.startswith(\"ZONA\")]          # non-delimited areas\n",
    "\n",
    "hc = df[[\"provincia\", \"canton\", \"canton_id\"]].drop_duplicates()\n",
    "hc[\"key\"] = hc.provincia.map(nrm) + \"|\" + hc.canton.map(nrm)\n",
    "m = hc.merge(mn[[\"key\", \"mindist_km\", \"nearest_port\"]], on=\"key\", how=\"left\")\n",
    "assert m[m.provincia != \"GALÁPAGOS\"].mindist_km.notna().all(), m[m.mindist_km.isna()]\n",
    "\n",
    "# --- cantons with no homicide record in 2014–2025 enter the cantonal panels as all-zero units\n",
    "pnorm = {nrm(p): p for p in df.provincia.unique()}\n",
    "ex = mn[~mn.key.isin(set(hc.key))].copy()\n",
    "ex[\"provincia\"] = ex.pk.map(pnorm); ex[\"canton_id\"] = ex.provincia + \" - \" + ex.ck\n",
    "ex[\"grupo\"] = np.where(ex.provincia.isin(COSTA), \"Costa\", \"Resto\")\n",
    "print(\"Cantons with zero homicides 2014–2025:\\n\", ex[[\"provincia\", \"ck\", \"grupo\", \"mindist_km\"]].to_string(index=False))\n",
    "\n",
    "# --- exposure = −z(distance) and −z(ln distance); mainland only (Galápagos is ~1,000 km from the nearest port)\n",
    "z = lambda s: (s - s.mean()) / s.std(ddof=0)\n",
    "mm = pd.concat([m[m.provincia != \"GALÁPAGOS\"][[\"canton_id\", \"provincia\", \"mindist_km\"]],\n",
    "                ex[ex.provincia != \"GALÁPAGOS\"][[\"canton_id\", \"provincia\", \"mindist_km\"]]])\n",
    "mm[\"exp\"] = -z(mm.mindist_km); mm[\"lnexp\"] = -z(np.log(mm.mindist_km + 1))\n",
    "mm[\"costa\"] = mm.provincia.isin(COSTA)\n",
    "# provincial exposure: mean of cantonal minimum distances\n",
    "mp_ = mn[mn.pk != \"GALAPAGOS\"].groupby(\"pk\").mindist_km.mean().rename(\"pdist\").reset_index()\n",
    "mp_[\"exp\"] = -z(mp_.pdist); mp_[\"lnexp\"] = -z(np.log(mp_.pdist))\n",
    "print(f\"\\nMainland cantons: {len(mm)} (Coast {mm.costa.sum()}, interior {(~mm.costa).sum()}); \"\n",
    "      f\"mean minimum distance: Coast {mm[mm.costa].mindist_km.mean():.1f} km, interior {mm[~mm.costa].mindist_km.mean():.1f} km\")\n",
    "mm.to_csv(OUT / \"canton_port_exposure.csv\", index=False); mp_.to_csv(OUT / \"province_port_exposure.csv\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0aa6e250",
   "metadata": {},
   "source": [
    "## 3. Balanced panels (Table 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c7e72048",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:24:51.777592Z",
     "iopub.status.busy": "2026-10-09T11:24:51.777369Z",
     "iopub.status.idle": "2026-10-09T11:24:51.892987Z",
     "shell.execute_reply": "2026-10-09T11:24:51.891622Z"
    },
    "lines_to_next_cell": 1
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Specification</th>\n",
       "      <th>Units</th>\n",
       "      <th>Treated</th>\n",
       "      <th>Periods</th>\n",
       "      <th>Observations</th>\n",
       "      <th>Share_zero</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A — Province × month</td>\n",
       "      <td>24</td>\n",
       "      <td>7</td>\n",
       "      <td>144</td>\n",
       "      <td>3456</td>\n",
       "      <td>0.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B — Province × year</td>\n",
       "      <td>24</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>288</td>\n",
       "      <td>0.035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C — Canton × quarter</td>\n",
       "      <td>222</td>\n",
       "      <td>86</td>\n",
       "      <td>48</td>\n",
       "      <td>10656</td>\n",
       "      <td>0.573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D — Canton × year</td>\n",
       "      <td>222</td>\n",
       "      <td>86</td>\n",
       "      <td>12</td>\n",
       "      <td>2664</td>\n",
       "      <td>0.328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Specification  Units  Treated  Periods  Observations  Share_zero\n",
       "0  A — Province × month     24        7      144          3456       0.250\n",
       "1   B — Province × year     24        7       12           288       0.035\n",
       "2  C — Canton × quarter    222       86       48         10656       0.573\n",
       "3     D — Canton × year    222       86       12          2664       0.328"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SPECS = {\"A\": (\"provincia\", \"ym\", \"Province × month\"), \"B\": (\"provincia\", \"y\", \"Province × year\"),\n",
    "         \"C\": (\"canton_id\", \"yq\", \"Canton × quarter\"), \"D\": (\"canton_id\", \"y\", \"Canton × year\")}\n",
    "\n",
    "def build(u, p, add_zero=True):\n",
    "    c = df.groupby([p, u]).size().reset_index(name=\"h\")\n",
    "    au = df[list(dict.fromkeys([u, \"grupo\", \"provincia\"]))].drop_duplicates(u)\n",
    "    if add_zero and u == \"canton_id\":\n",
    "        au = pd.concat([au, ex[[\"canton_id\", \"grupo\", \"provincia\"]]])\n",
    "    ap = sorted(df[p].unique())\n",
    "    idx = pd.MultiIndex.from_product([ap, au[u].values], names=[p, u])\n",
    "    pn = pd.DataFrame(index=idx).reset_index().merge(au, on=u).merge(c, on=[p, u], how=\"left\")\n",
    "    pn[\"h\"] = pn.h.fillna(0); pn[\"lh\"] = np.log1p(pn.h); pn[\"costa\"] = (pn.grupo == \"Costa\").astype(float)\n",
    "    pn[\"year\"] = pn[p].str[:4].astype(int)\n",
    "    pn = pn.merge(COCA[[\"year\", \"lncoca\", \"lncoca_l1\"]], on=\"year\", how=\"left\")\n",
    "    step = 12 if p == \"ym\" else 4 if p == \"yq\" else 1\n",
    "    pn[\"tidx\"] = pn[p].map({q: i / step for i, q in enumerate(ap)})     # time in years\n",
    "    return pn\n",
    "\n",
    "def attach_exposure(pn, u):\n",
    "    pn = pn[pn.provincia != \"GALÁPAGOS\"].copy()\n",
    "    if u == \"canton_id\":\n",
    "        return pn.merge(mm[[\"canton_id\", \"exp\", \"lnexp\"]], on=\"canton_id\", how=\"left\")\n",
    "    pn[\"pk\"] = pn.provincia.map(nrm).replace(PFIX)\n",
    "    return pn.merge(mp_[[\"pk\", \"exp\", \"lnexp\"]], on=\"pk\", how=\"left\")\n",
    "\n",
    "PANELS = {k: build(u, p) for k, (u, p, _) in SPECS.items()}\n",
    "T1 = pd.DataFrame([dict(Specification=f\"{k} — {lab}\", Units=PANELS[k][u].nunique(), Treated=PANELS[k][PANELS[k].costa == 1][u].nunique(),\n",
    "                        Periods=PANELS[k][p].nunique(), Observations=len(PANELS[k]), Share_zero=round((PANELS[k].h == 0).mean(), 3))\n",
    "                   for k, (u, p, lab) in SPECS.items()])\n",
    "T1.to_csv(OUT / \"Table1_panels.csv\", index=False); T1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9df879ad",
   "metadata": {},
   "source": [
    "## 4. Event studies: reference 2019 (main) and 2020 (robustness)\n",
    "\n",
    "Joint Wald test (HC3) of the null that **all** pre-reference coefficients are zero, plus a linear pre-trend (exposure × time) on the pre-reference years with province-clustered SEs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "decc091c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:24:51.894985Z",
     "iopub.status.busy": "2026-10-09T11:24:51.894730Z",
     "iopub.status.idle": "2026-10-09T11:25:02.930848Z",
     "shell.execute_reply": "2026-10-09T11:25:02.930131Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done A Province × month\n",
      "done B Province × year\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done C Canton × quarter\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done D Canton × year\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>spec</th>\n",
       "      <th>ref</th>\n",
       "      <th>exposure</th>\n",
       "      <th>N</th>\n",
       "      <th>units</th>\n",
       "      <th>R2</th>\n",
       "      <th>wald_chi2</th>\n",
       "      <th>wald_df</th>\n",
       "      <th>wald_p</th>\n",
       "      <th>pre_sig</th>\n",
       "      <th>pretrend_slope_per_year</th>\n",
       "      <th>pretrend_p</th>\n",
       "      <th>first_sig</th>\n",
       "      <th>first_sig_coef</th>\n",
       "      <th>first_sig_p</th>\n",
       "      <th>peak</th>\n",
       "      <th>peak_per</th>\n",
       "      <th>exp_peak</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>2019</td>\n",
       "      <td>Coast dummy</td>\n",
       "      <td>3456</td>\n",
       "      <td>24</td>\n",
       "      <td>0.852</td>\n",
       "      <td>59.60</td>\n",
       "      <td>60</td>\n",
       "      <td>0.490</td>\n",
       "      <td>5/60</td>\n",
       "      <td>-0.047</td>\n",
       "      <td>0.007</td>\n",
       "      <td>2020_10</td>\n",
       "      <td>0.417</td>\n",
       "      <td>0.0245</td>\n",
       "      <td>1.808</td>\n",
       "      <td>2025_09</td>\n",
       "      <td>6.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>2020</td>\n",
       "      <td>Coast dummy</td>\n",
       "      <td>3456</td>\n",
       "      <td>24</td>\n",
       "      <td>0.852</td>\n",
       "      <td>72.82</td>\n",
       "      <td>72</td>\n",
       "      <td>0.451</td>\n",
       "      <td>5/72</td>\n",
       "      <td>-0.019</td>\n",
       "      <td>0.326</td>\n",
       "      <td>2021_04</td>\n",
       "      <td>0.527</td>\n",
       "      <td>0.0030</td>\n",
       "      <td>1.693</td>\n",
       "      <td>2025_09</td>\n",
       "      <td>5.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>B</td>\n",
       "      <td>2019</td>\n",
       "      <td>Coast dummy</td>\n",
       "      <td>288</td>\n",
       "      <td>24</td>\n",
       "      <td>0.947</td>\n",
       "      <td>1.40</td>\n",
       "      <td>5</td>\n",
       "      <td>0.925</td>\n",
       "      <td>0/5</td>\n",
       "      <td>-0.037</td>\n",
       "      <td>0.195</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>1.216</td>\n",
       "      <td>2023</td>\n",
       "      <td>3.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>B</td>\n",
       "      <td>2020</td>\n",
       "      <td>Coast dummy</td>\n",
       "      <td>288</td>\n",
       "      <td>24</td>\n",
       "      <td>0.947</td>\n",
       "      <td>3.61</td>\n",
       "      <td>6</td>\n",
       "      <td>0.729</td>\n",
       "      <td>0/6</td>\n",
       "      <td>-0.011</td>\n",
       "      <td>0.677</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.0265</td>\n",
       "      <td>1.047</td>\n",
       "      <td>2023</td>\n",
       "      <td>2.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>C</td>\n",
       "      <td>2019</td>\n",
       "      <td>Coast dummy</td>\n",
       "      <td>10656</td>\n",
       "      <td>222</td>\n",
       "      <td>0.764</td>\n",
       "      <td>22.59</td>\n",
       "      <td>20</td>\n",
       "      <td>0.309</td>\n",
       "      <td>1/20</td>\n",
       "      <td>-0.021</td>\n",
       "      <td>0.085</td>\n",
       "      <td>2020_T4</td>\n",
       "      <td>0.222</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>1.259</td>\n",
       "      <td>2025_T4</td>\n",
       "      <td>3.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>C</td>\n",
       "      <td>2020</td>\n",
       "      <td>Coast dummy</td>\n",
       "      <td>10656</td>\n",
       "      <td>222</td>\n",
       "      <td>0.764</td>\n",
       "      <td>35.02</td>\n",
       "      <td>24</td>\n",
       "      <td>0.068</td>\n",
       "      <td>5/24</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>0.928</td>\n",
       "      <td>2021_T2</td>\n",
       "      <td>0.251</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>1.235</td>\n",
       "      <td>2025_T4</td>\n",
       "      <td>3.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>D</td>\n",
       "      <td>2019</td>\n",
       "      <td>Coast dummy</td>\n",
       "      <td>2664</td>\n",
       "      <td>222</td>\n",
       "      <td>0.861</td>\n",
       "      <td>8.60</td>\n",
       "      <td>5</td>\n",
       "      <td>0.126</td>\n",
       "      <td>3/5</td>\n",
       "      <td>-0.039</td>\n",
       "      <td>0.065</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.351</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>1.343</td>\n",
       "      <td>2025</td>\n",
       "      <td>3.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>D</td>\n",
       "      <td>2020</td>\n",
       "      <td>Coast dummy</td>\n",
       "      <td>2664</td>\n",
       "      <td>222</td>\n",
       "      <td>0.861</td>\n",
       "      <td>13.38</td>\n",
       "      <td>6</td>\n",
       "      <td>0.037</td>\n",
       "      <td>3/6</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.872</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.343</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>1.334</td>\n",
       "      <td>2025</td>\n",
       "      <td>3.80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   spec   ref     exposure      N  units     R2  wald_chi2  wald_df  wald_p pre_sig  pretrend_slope_per_year  pretrend_p first_sig  first_sig_coef  first_sig_p   peak peak_per  exp_peak\n",
       "0     A  2019  Coast dummy   3456     24  0.852      59.60       60   0.490    5/60                   -0.047       0.007   2020_10           0.417       0.0245  1.808  2025_09      6.10\n",
       "3     A  2020  Coast dummy   3456     24  0.852      72.82       72   0.451    5/72                   -0.019       0.326   2021_04           0.527       0.0030  1.693  2025_09      5.43\n",
       "6     B  2019  Coast dummy    288     24  0.947       1.40        5   0.925     0/5                   -0.037       0.195      2021           0.600       0.0040  1.216     2023      3.37\n",
       "9     B  2020  Coast dummy    288     24  0.947       3.61        6   0.729     0/6                   -0.011       0.677      2021           0.430       0.0265  1.047     2023      2.85\n",
       "12    C  2019  Coast dummy  10656    222  0.764      22.59       20   0.309    1/20                   -0.021       0.085   2020_T4           0.222       0.0014  1.259  2025_T4      3.52\n",
       "15    C  2020  Coast dummy  10656    222  0.764      35.02       24   0.068    5/24                   -0.001       0.928   2021_T2           0.251       0.0002  1.235  2025_T4      3.44\n",
       "18    D  2019  Coast dummy   2664    222  0.861       8.60        5   0.126     3/5                   -0.039       0.065      2021           0.351       0.0006  1.343     2025      3.83\n",
       "21    D  2020  Coast dummy   2664    222  0.861      13.38        6   0.037     3/6                    0.003       0.872      2021           0.343       0.0005  1.334     2025      3.80"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def fit_fe(pn, u, p, xcols, B=0, seed=SEED):\n",
    "    \"\"\"Two-way FE OLS by double demeaning (balanced panel). Returns coefficients, HC3 and province-clustered SEs,\n",
    "    clustered p-values (t with G−1 df) and Webb wild cluster bootstrap-t p-values with the null imposed.\"\"\"\n",
    "    rng = np.random.default_rng(seed)\n",
    "    ui = pd.factorize(pn[u].values)[0]; ti = pd.factorize(pn[p].values)[0]; N = ui.max() + 1; T = ti.max() + 1\n",
    "    def dd(v):\n",
    "        s = pd.Series(v)\n",
    "        return v - s.groupby(ui).transform(\"mean\").values - s.groupby(ti).transform(\"mean\").values + v.mean()\n",
    "    y = dd(pn.lh.values.astype(float)); X = np.column_stack([dd(pn[c].values.astype(float)) for c in xcols]); K = X.shape[1]\n",
    "    XtXi = np.linalg.inv(X.T @ X); b = XtXi @ X.T @ y; e = y - X @ b\n",
    "    h = 1 / T + 1 / N - 1 / (N * T) + np.einsum(\"ij,jk,ik->i\", X, XtXi, X)\n",
    "    se_hc3 = np.sqrt(np.diag(XtXi @ (X.T * (e / (1 - h)) ** 2) @ X @ XtXi))\n",
    "    cl = pd.factorize(pn.provincia.values)[0]; G = cl.max() + 1\n",
    "    def clse(ee):\n",
    "        S = np.zeros((G, K)); np.add.at(S, cl, X * ee[:, None])\n",
    "        return np.sqrt(np.diag(XtXi @ (S.T @ S) @ XtXi * (G / (G - 1))))\n",
    "    se = clse(e)\n",
    "    out = dict(b=b, se_cl=se, se_hc3=se_hc3, G=G, N=len(pn), p_cl=2 * (1 - stats.t.cdf(np.abs(b / se), G - 1)), p_wild=np.full(K, np.nan))\n",
    "    if B:\n",
    "        webb = np.array([-np.sqrt(1.5), -1, -np.sqrt(.5), np.sqrt(.5), 1, np.sqrt(1.5)]); pw = []\n",
    "        for k in range(K):\n",
    "            Xr = np.delete(X, k, axis=1)\n",
    "            fitted = Xr @ np.linalg.lstsq(Xr, y, rcond=None)[0] if Xr.shape[1] else np.zeros_like(y)\n",
    "            er = y - fitted; tobs = abs(b[k] / se[k]); cnt = 0\n",
    "            for _ in range(B):\n",
    "                w = rng.choice(webb, G); ys = fitted + er * w[cl]; bs = XtXi @ (X.T @ ys); ses = clse(ys - X @ bs)\n",
    "                cnt += abs(bs[k] / ses[k]) >= tobs\n",
    "            pw.append((cnt + 1) / (B + 1))\n",
    "        out[\"p_wild\"] = np.array(pw)\n",
    "    return out\n",
    "\n",
    "def event_study(pn, u, p, omit, col):\n",
    "    ap = sorted(pn[p].unique())\n",
    "    ufe = pd.get_dummies(pn[u], prefix=\"u\", drop_first=True).astype(float)\n",
    "    cols = {\"const\": np.ones(len(pn))}\n",
    "    for q in ap:\n",
    "        if q in omit: continue\n",
    "        pc = (pn[p] == q).astype(float).values\n",
    "        cols[f\"t_{q}\"] = pc; cols[f\"int_{q}\"] = pc * pn[col].values\n",
    "    X = pd.concat([pd.DataFrame(cols), ufe.reset_index(drop=True)], axis=1)\n",
    "    mod = sm.OLS(pn.lh.values, X).fit(cov_type=\"HC3\"); ci = mod.conf_int(); rows = []\n",
    "    for q in ap:\n",
    "        if q in omit:\n",
    "            rows.append(dict(per=q, coef=0.0, se=0.0, pval=np.nan, lo=0.0, hi=0.0, omitted=True, name=None))\n",
    "        else:\n",
    "            t = f\"int_{q}\"\n",
    "            rows.append(dict(per=q, coef=mod.params[t], se=mod.bse[t], pval=mod.pvalues[t], lo=ci.loc[t, 0], hi=ci.loc[t, 1], omitted=False, name=t))\n",
    "    r = pd.DataFrame(rows); r[\"year\"] = r.per.str[:4].astype(int)\n",
    "    return mod, r\n",
    "\n",
    "def wald_pre(mod, pre):\n",
    "    names = list(mod.params.index); R = np.zeros((len(pre), len(names)))\n",
    "    for i, nm in enumerate(pre.name): R[i, names.index(nm)] = 1\n",
    "    w = mod.wald_test(R, use_f=False, scalar=True)\n",
    "    return float(w.statistic), len(pre), float(w.pvalue)\n",
    "\n",
    "def omit_year(k, years):\n",
    "    if k == \"A\": return {f\"{y}_{m:02d}\" for y in years for m in range(1, 13)}\n",
    "    if k == \"C\": return {f\"{y}_T{q}\" for y in years for q in range(1, 5)}\n",
    "    return {str(y) for y in years}\n",
    "\n",
    "EXPO = {\"costa\": \"Coast dummy\", \"exp\": \"Port proximity −z(distance)\", \"lnexp\": \"Port proximity −z(ln distance)\"}\n",
    "RES = {}\n",
    "for k, (u, p, lab) in SPECS.items():\n",
    "    pn0 = PANELS[k]; pnm = attach_exposure(pn0, u)\n",
    "    for ref in (\"2019\", \"2020\"):\n",
    "        for col in EXPO:\n",
    "            pn = pn0 if col == \"costa\" else pnm\n",
    "            mod, r = event_study(pn, u, p, omit_year(k, [int(ref)]), col)\n",
    "            pre = r[(r.year < int(ref)) & ~r.omitted]; post = r[r.year > int(ref)]\n",
    "            chi2, dfree, pv = wald_pre(mod, pre)\n",
    "            fs = post[post.pval < 0.05]; pk = r[~r.omitted].nlargest(1, \"coef\").iloc[0]\n",
    "            dpre = pn[pn.year < int(ref)].copy(); dpre[\"xt\"] = dpre[col] * dpre.tidx\n",
    "            ft = fit_fe(dpre, u, p, [\"xt\"])\n",
    "            RES[(k, ref, col)] = dict(r=r, wald=(chi2, dfree, pv), R2=mod.rsquared, N=len(pn), units=pn[u].nunique(),\n",
    "                                      first_sig=fs.per.iloc[0] if len(fs) else None,\n",
    "                                      first_sig_coef=fs.coef.iloc[0] if len(fs) else np.nan,\n",
    "                                      first_sig_p=fs.pval.iloc[0] if len(fs) else np.nan,\n",
    "                                      peak=pk.coef, peak_per=pk.per, pre_sig=int((pre.pval < .05).sum()), pre_n=len(pre),\n",
    "                                      pre_slope=ft[\"b\"][0], pre_slope_p=ft[\"p_cl\"][0])\n",
    "            r.drop(columns=\"name\").to_csv(OUT / f\"event_study_{k}_ref{ref}_{col}.csv\", index=False)\n",
    "    print(\"done\", k, lab)\n",
    "\n",
    "SUM = pd.DataFrame([dict(spec=k, ref=ref, exposure=EXPO[col], N=v[\"N\"], units=v[\"units\"], R2=round(v[\"R2\"], 3),\n",
    "                         wald_chi2=round(v[\"wald\"][0], 2), wald_df=v[\"wald\"][1], wald_p=round(v[\"wald\"][2], 3),\n",
    "                         pre_sig=f'{v[\"pre_sig\"]}/{v[\"pre_n\"]}', pretrend_slope_per_year=round(v[\"pre_slope\"], 3),\n",
    "                         pretrend_p=round(v[\"pre_slope_p\"], 3), first_sig=v[\"first_sig\"],\n",
    "                         first_sig_coef=round(v[\"first_sig_coef\"], 3), first_sig_p=round(v[\"first_sig_p\"], 4),\n",
    "                         peak=round(v[\"peak\"], 3), peak_per=v[\"peak_per\"], exp_peak=round(np.exp(v[\"peak\"]), 2))\n",
    "                    for (k, ref, col), v in RES.items()])\n",
    "SUM.to_csv(OUT / \"event_study_summary.csv\", index=False)\n",
    "SUM[SUM.exposure == \"Coast dummy\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "490a642f",
   "metadata": {},
   "source": [
    "### Table 2 — choice of reference period (specification A, Coast dummy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "174ada18",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:25:02.932660Z",
     "iopub.status.busy": "2026-10-09T11:25:02.932393Z",
     "iopub.status.idle": "2026-10-09T11:25:05.032654Z",
     "shell.execute_reply": "2026-10-09T11:25:05.031824Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>candidate</th>\n",
       "      <th>chi2</th>\n",
       "      <th>df</th>\n",
       "      <th>p</th>\n",
       "      <th>rejected_5pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Single month (May 2021)</td>\n",
       "      <td>110.1</td>\n",
       "      <td>84</td>\n",
       "      <td>0.030</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>January–May 2021 block</td>\n",
       "      <td>115.6</td>\n",
       "      <td>84</td>\n",
       "      <td>0.013</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Full year 2019</td>\n",
       "      <td>59.6</td>\n",
       "      <td>60</td>\n",
       "      <td>0.490</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Full year 2020</td>\n",
       "      <td>72.8</td>\n",
       "      <td>72</td>\n",
       "      <td>0.451</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 candidate   chi2  df      p  rejected_5pct\n",
       "0  Single month (May 2021)  110.1  84  0.030           True\n",
       "1   January–May 2021 block  115.6  84  0.013           True\n",
       "2           Full year 2019   59.6  60  0.490          False\n",
       "3           Full year 2020   72.8  72  0.451          False"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "u, p, _ = SPECS[\"A\"]; pnA = build(u, p)\n",
    "cands = [(\"Single month (May 2021)\", {\"2021_05\"}, \"2021_01\"),\n",
    "         (\"January–May 2021 block\", {f\"2021_{m:02d}\" for m in range(1, 6)}, \"2021_01\"),\n",
    "         (\"Full year 2019\", omit_year(\"A\", [2019]), \"2019_01\"),\n",
    "         (\"Full year 2020\", omit_year(\"A\", [2020]), \"2020_01\")]\n",
    "T2 = []\n",
    "for name, om, cut in cands:\n",
    "    mod, r = event_study(pnA, u, p, om, \"costa\")\n",
    "    pre = r[(r.per < cut) & ~r.omitted]; chi2, dfree, pv = wald_pre(mod, pre)\n",
    "    T2.append(dict(candidate=name, chi2=round(chi2, 1), df=dfree, p=round(pv, 3), rejected_5pct=pv < .05))\n",
    "T2 = pd.DataFrame(T2); T2.to_csv(OUT / \"Table2_reference_period.csv\", index=False); T2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c74eca6",
   "metadata": {},
   "source": [
    "### Table 3 — comparative summary (2019 main; 2020 robustness)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e61cecbb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:25:05.034541Z",
     "iopub.status.busy": "2026-10-09T11:25:05.034161Z",
     "iopub.status.idle": "2026-10-09T11:25:05.046547Z",
     "shell.execute_reply": "2026-10-09T11:25:05.045902Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A: Province × month</th>\n",
       "      <th>B: Province × year</th>\n",
       "      <th>C: Canton × quarter</th>\n",
       "      <th>D: Canton × year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Observations</th>\n",
       "      <td>3,456</td>\n",
       "      <td>288</td>\n",
       "      <td>10,656</td>\n",
       "      <td>2,664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R²</th>\n",
       "      <td>0.852</td>\n",
       "      <td>0.947</td>\n",
       "      <td>0.764</td>\n",
       "      <td>0.861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pre-trends: Wald χ² (df)</th>\n",
       "      <td>59.6 (60)</td>\n",
       "      <td>1.4 (5)</td>\n",
       "      <td>22.6 (20)</td>\n",
       "      <td>8.6 (5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pre-trends: p-value</th>\n",
       "      <td>0.490</td>\n",
       "      <td>0.925</td>\n",
       "      <td>0.309</td>\n",
       "      <td>0.126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>First significant period</th>\n",
       "      <td>Oct 2020</td>\n",
       "      <td>2021</td>\n",
       "      <td>Q4 2020</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Peak coefficient δ</th>\n",
       "      <td>+1.81</td>\n",
       "      <td>+1.22</td>\n",
       "      <td>+1.26</td>\n",
       "      <td>+1.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Implied factor exp(δ)</th>\n",
       "      <td>6.1×</td>\n",
       "      <td>3.4×</td>\n",
       "      <td>3.5×</td>\n",
       "      <td>3.8×</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Port proximity: Wald p</th>\n",
       "      <td>0.365</td>\n",
       "      <td>0.555</td>\n",
       "      <td>0.960</td>\n",
       "      <td>0.673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Port proximity: first significant period</th>\n",
       "      <td>Dec 2020</td>\n",
       "      <td>2021</td>\n",
       "      <td>Q4 2020</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Port proximity: peak δ per SD</th>\n",
       "      <td>+0.71</td>\n",
       "      <td>+0.50</td>\n",
       "      <td>+0.54</td>\n",
       "      <td>+0.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Robustness (ref. 2020): Wald χ² (df)</th>\n",
       "      <td>72.8 (72)</td>\n",
       "      <td>3.6 (6)</td>\n",
       "      <td>35.0 (24)</td>\n",
       "      <td>13.4 (6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Robustness (ref. 2020): p-value</th>\n",
       "      <td>0.451</td>\n",
       "      <td>0.729</td>\n",
       "      <td>0.068</td>\n",
       "      <td>0.037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Robustness (ref. 2020): first significant period</th>\n",
       "      <td>Apr 2021</td>\n",
       "      <td>2021</td>\n",
       "      <td>Q2 2021</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Robustness (ref. 2020): peak δ</th>\n",
       "      <td>+1.69</td>\n",
       "      <td>+1.05</td>\n",
       "      <td>+1.23</td>\n",
       "      <td>+1.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Robustness (ref. 2020): port proximity Wald p</th>\n",
       "      <td>0.105</td>\n",
       "      <td>0.400</td>\n",
       "      <td>0.468</td>\n",
       "      <td>0.076</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 A: Province × month B: Province × year C: Canton × quarter D: Canton × year\n",
       "Observations                                                   3,456                288              10,656            2,664\n",
       "R²                                                             0.852              0.947               0.764            0.861\n",
       "Pre-trends: Wald χ² (df)                                   59.6 (60)            1.4 (5)           22.6 (20)          8.6 (5)\n",
       "Pre-trends: p-value                                            0.490              0.925               0.309            0.126\n",
       "First significant period                                    Oct 2020               2021             Q4 2020             2021\n",
       "Peak coefficient δ                                             +1.81              +1.22               +1.26            +1.34\n",
       "Implied factor exp(δ)                                           6.1×               3.4×                3.5×             3.8×\n",
       "Port proximity: Wald p                                         0.365              0.555               0.960            0.673\n",
       "Port proximity: first significant period                    Dec 2020               2021             Q4 2020             2021\n",
       "Port proximity: peak δ per SD                                  +0.71              +0.50               +0.54            +0.53\n",
       "Robustness (ref. 2020): Wald χ² (df)                       72.8 (72)            3.6 (6)           35.0 (24)         13.4 (6)\n",
       "Robustness (ref. 2020): p-value                                0.451              0.729               0.068            0.037\n",
       "Robustness (ref. 2020): first significant period            Apr 2021               2021             Q2 2021             2021\n",
       "Robustness (ref. 2020): peak δ                                 +1.69              +1.05               +1.23            +1.33\n",
       "Robustness (ref. 2020): port proximity Wald p                  0.105              0.400               0.468            0.076"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MON = [\"Jan\", \"Feb\", \"Mar\", \"Apr\", \"May\", \"Jun\", \"Jul\", \"Aug\", \"Sep\", \"Oct\", \"Nov\", \"Dec\"]\n",
    "def fper(per, k):\n",
    "    if per is None: return \"—\"\n",
    "    if k == \"A\": return f\"{MON[int(per[5:]) - 1]} {per[:4]}\"\n",
    "    if k == \"C\": return f\"Q{per[-1]} {per[:4]}\"\n",
    "    return per\n",
    "g = lambda ref, k, col=\"costa\": RES[(k, ref, col)]\n",
    "rows = {\"Observations\": [f'{g(\"2019\", k)[\"N\"]:,}' for k in SPECS],\n",
    "        \"R²\": [f'{g(\"2019\", k)[\"R2\"]:.3f}' for k in SPECS],\n",
    "        \"Pre-trends: Wald χ² (df)\": [f'{g(\"2019\", k)[\"wald\"][0]:.1f} ({g(\"2019\", k)[\"wald\"][1]})' for k in SPECS],\n",
    "        \"Pre-trends: p-value\": [f'{g(\"2019\", k)[\"wald\"][2]:.3f}' for k in SPECS],\n",
    "        \"First significant period\": [fper(g(\"2019\", k)[\"first_sig\"], k) for k in SPECS],\n",
    "        \"Peak coefficient δ\": [f'{g(\"2019\", k)[\"peak\"]:+.2f}' for k in SPECS],\n",
    "        \"Implied factor exp(δ)\": [f'{np.exp(g(\"2019\", k)[\"peak\"]):.1f}×' for k in SPECS],\n",
    "        \"Port proximity: Wald p\": [f'{g(\"2019\", k, \"lnexp\")[\"wald\"][2]:.3f}' for k in SPECS],\n",
    "        \"Port proximity: first significant period\": [fper(g(\"2019\", k, \"lnexp\")[\"first_sig\"], k) for k in SPECS],\n",
    "        \"Port proximity: peak δ per SD\": [f'{g(\"2019\", k, \"lnexp\")[\"peak\"]:+.2f}' for k in SPECS],\n",
    "        \"Robustness (ref. 2020): Wald χ² (df)\": [f'{g(\"2020\", k)[\"wald\"][0]:.1f} ({g(\"2020\", k)[\"wald\"][1]})' for k in SPECS],\n",
    "        \"Robustness (ref. 2020): p-value\": [f'{g(\"2020\", k)[\"wald\"][2]:.3f}' for k in SPECS],\n",
    "        \"Robustness (ref. 2020): first significant period\": [fper(g(\"2020\", k)[\"first_sig\"], k) for k in SPECS],\n",
    "        \"Robustness (ref. 2020): peak δ\": [f'{g(\"2020\", k)[\"peak\"]:+.2f}' for k in SPECS],\n",
    "        \"Robustness (ref. 2020): port proximity Wald p\": [f'{g(\"2020\", k, \"lnexp\")[\"wald\"][2]:.3f}' for k in SPECS]}\n",
    "T3 = pd.DataFrame(rows, index=[f\"{k}: {SPECS[k][2]}\" for k in SPECS]).T\n",
    "T3.to_csv(OUT / \"Table3_summary.csv\"); T3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36def41b",
   "metadata": {},
   "source": [
    "## 5. Figures 2, 3, 5, A1 and A2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b62aa172",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:25:05.048216Z",
     "iopub.status.busy": "2026-10-09T11:25:05.047881Z",
     "iopub.status.idle": "2026-10-09T11:25:09.064270Z",
     "shell.execute_reply": "2026-10-09T11:25:09.063068Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x460 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x460 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x700 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams.update({\"font.size\": 9})\n",
    "def colr(row, ref):\n",
    "    if row.omitted: return \"#d1d5db\"\n",
    "    if row.year < int(ref): return \"#bfdbfe\"\n",
    "    return \"#991b1b\" if row.pval < .01 else \"#dc2626\" if row.pval < .05 else \"#f87171\" if row.pval < .1 else \"#fca5a5\"\n",
    "def legend(ref):\n",
    "    return [mp.Patch(color=c, label=l) for c, l in [(\"#bfdbfe\", f\"Pre-{ref}\"), (\"#d1d5db\", f\"{ref} (reference, omitted)\"),\n",
    "            (\"#fca5a5\", \"Post: n.s.\"), (\"#f87171\", \"Post: p < 0.10\"), (\"#dc2626\", \"Post: p < 0.05\"), (\"#991b1b\", \"Post: p < 0.01\")]]\n",
    "def bars(ax, r, ref, width=.75, err=False):\n",
    "    r = r.reset_index(drop=True); x = np.arange(len(r))\n",
    "    ax.bar(x, r.coef, color=[colr(a, ref) for a in r.itertuples()], width=width, zorder=2)\n",
    "    if err:\n",
    "        msk = ~r.omitted.values\n",
    "        ax.errorbar(x[msk], r.coef[msk], yerr=[(r.coef - r.lo)[msk], (r.hi - r.coef)[msk]], fmt=\"none\", ecolor=\"k\", elinewidth=.5, capsize=1, alpha=.35, zorder=3)\n",
    "    ax.axhline(0, color=\"#92400e\", ls=\"--\", lw=1, alpha=.5)\n",
    "    idx = r.index[r.year == int(ref)]; ax.axvspan(idx[0] - .5, idx[-1] + .5, color=\"gray\", alpha=.08)\n",
    "    first = [i for i in x if r.per.iloc[i][:4] != (r.per.iloc[i - 1][:4] if i > 0 else \"\")]\n",
    "    ax.set_xticks(first); ax.set_xticklabels([r.per.iloc[i][:4] for i in first], fontsize=7.5, rotation=0 if len(r) > 40 else 45)\n",
    "    ax.spines[[\"top\", \"right\"]].set_visible(False); ax.grid(axis=\"y\", alpha=.2)\n",
    "    return r\n",
    "\n",
    "def monthly_fig(ref, fname, title):\n",
    "    fig, ax = plt.subplots(figsize=(12, 4.6))\n",
    "    v = RES[(\"A\", ref, \"costa\")]; r = bars(ax, v[\"r\"], ref, .7, True)\n",
    "    fs = v[\"first_sig\"]; i = r.index[r.per == fs][0]\n",
    "    ax.axvline(i, color=\"#166534\", ls=\":\", lw=1.3)\n",
    "    ax.text(i - .8, 2.3, f\"First significant\\nmonth: {MON[int(fs[5:]) - 1]} {fs[:4]}\", ha=\"right\", va=\"top\", fontsize=8, color=\"#166534\")\n",
    "    il = r.index[r.per == \"2021_05\"][0]; ax.axvline(il + .4, color=\"#374151\", ls=\":\", lw=1.2)\n",
    "    ax.text(il + 1.3, 2.3, \"Lasso takes office\\n(May 2021)\", ha=\"left\", va=\"top\", fontsize=8, color=\"#374151\")\n",
    "    w = v[\"wald\"]; ax.set_title(f\"{title}   (joint pre-trend Wald: χ²({w[1]}) = {w[0]:.1f}, p = {w[2]:.2f})\", fontsize=10, loc=\"left\", fontweight=\"bold\")\n",
    "    ax.set_ylabel(\"$\\\\delta_\\\\tau$ (log points)\"); ax.set_ylim(-1.5, 2.4)\n",
    "    ax.legend(handles=legend(ref), fontsize=7, ncol=3, loc=\"lower left\", frameon=False)\n",
    "    plt.tight_layout(); plt.savefig(OUT / fname, dpi=200); plt.show()\n",
    "\n",
    "def four_fig(ref, fname):\n",
    "    fig, axs = plt.subplots(2, 2, figsize=(12, 7))\n",
    "    for k, ax in zip(SPECS, axs.ravel()):\n",
    "        v = RES[(k, ref, \"costa\")]; bars(ax, v[\"r\"], ref)\n",
    "        ax.set_title(f\"({k}) {SPECS[k][2]}   Wald p = {v['wald'][2]:.2f}\", fontsize=10, fontweight=\"bold\")\n",
    "        ax.set_ylabel(\"$\\\\delta_\\\\tau$ (log points)\", fontsize=8)\n",
    "    fig.legend(handles=legend(ref), ncol=6, fontsize=7.5, loc=\"lower center\", frameon=False)\n",
    "    plt.tight_layout(rect=(0, .04, 1, 1)); plt.savefig(OUT / fname, dpi=200); plt.show()\n",
    "\n",
    "monthly_fig(\"2019\", \"Figure2_monthly_ref2019.png\", \"Reference: 2019\")\n",
    "four_fig(\"2019\", \"Figure3_four_specs_ref2019.png\")\n",
    "monthly_fig(\"2020\", \"FigureA1_monthly_ref2020.png\", \"Reference: 2020 (robustness)\")\n",
    "four_fig(\"2020\", \"FigureA2_four_specs_ref2020.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "867d1927",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:25:09.066347Z",
     "iopub.status.busy": "2026-10-09T11:25:09.066137Z",
     "iopub.status.idle": "2026-10-09T11:25:09.958893Z",
     "shell.execute_reply": "2026-10-09T11:25:09.957564Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Figure 5: event study with port proximity (−z ln distance), reference 2019\n",
    "fig, axs = plt.subplots(2, 2, figsize=(12, 7))\n",
    "for k, ax in zip(SPECS, axs.ravel()):\n",
    "    v = RES[(k, \"2019\", \"lnexp\")]; r = v[\"r\"].reset_index(drop=True); x = np.arange(len(r)); msk = ~r.omitted.values\n",
    "    ax.fill_between(x[msk], r.lo[msk], r.hi[msk], color=\"#1d4ed8\", alpha=.15, lw=0); ax.plot(x[msk], r.coef[msk], color=\"#1d4ed8\", lw=1.2)\n",
    "    ax.axhline(0, color=\"#92400e\", ls=\"--\", lw=1, alpha=.5); idx = r.index[r.year == 2019]; ax.axvspan(idx[0] - .5, idx[-1] + .5, color=\"gray\", alpha=.1)\n",
    "    first = [i for i in x if r.per.iloc[i][:4] != (r.per.iloc[i - 1][:4] if i > 0 else \"\")]\n",
    "    ax.set_xticks(first); ax.set_xticklabels([r.per.iloc[i][:4] for i in first], fontsize=7.5)\n",
    "    ax.set_title(f\"({k}) {SPECS[k][2]}   Wald p = {v['wald'][2]:.2f}\", fontsize=10, fontweight=\"bold\")\n",
    "    ax.set_ylabel(\"$\\\\delta_\\\\tau$ per SD of proximity\", fontsize=8); ax.spines[[\"top\", \"right\"]].set_visible(False); ax.grid(axis=\"y\", alpha=.2)\n",
    "plt.tight_layout(); plt.savefig(OUT / \"Figure5_port_proximity_ref2019.png\", dpi=200); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d31576a",
   "metadata": {},
   "source": [
    "## 6. Coca-shift models (Tables 4–5, Figure 4)\n",
    "\n",
    "Windows: W1 = 2014–2019 (first boom), W2 = 2020–2025 (second boom), W2post = 2021–2025. Period fixed effects absorb the national coca series; θ is identified from differential co-movement within each window. Wild bootstrap: B = 499 for A and C, 999 for B and D."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "05c7e623",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:25:09.960798Z",
     "iopub.status.busy": "2026-10-09T11:25:09.960613Z",
     "iopub.status.idle": "2026-10-09T11:25:11.667392Z",
     "shell.execute_reply": "2026-10-09T11:25:11.666225Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done A Province × month\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done B Province × year\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done C Canton × quarter\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done D Canton × year\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>spec</th>\n",
       "      <th>expo</th>\n",
       "      <th>window</th>\n",
       "      <th>variant</th>\n",
       "      <th>b</th>\n",
       "      <th>se_cl</th>\n",
       "      <th>p_cl</th>\n",
       "      <th>p_wild</th>\n",
       "      <th>N</th>\n",
       "      <th>G</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>costa</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>-0.156</td>\n",
       "      <td>0.084</td>\n",
       "      <td>0.074</td>\n",
       "      <td>0.102</td>\n",
       "      <td>1728</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>2.184</td>\n",
       "      <td>0.328</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.002</td>\n",
       "      <td>1728</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>2.915</td>\n",
       "      <td>0.881</td>\n",
       "      <td>0.003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1440</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>A</td>\n",
       "      <td>exp</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>-0.020</td>\n",
       "      <td>0.038</td>\n",
       "      <td>0.606</td>\n",
       "      <td>0.610</td>\n",
       "      <td>1656</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>A</td>\n",
       "      <td>exp</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>0.478</td>\n",
       "      <td>0.301</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.140</td>\n",
       "      <td>1656</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>A</td>\n",
       "      <td>exp</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>0.472</td>\n",
       "      <td>0.612</td>\n",
       "      <td>0.449</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1380</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>A</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>-0.036</td>\n",
       "      <td>0.038</td>\n",
       "      <td>0.363</td>\n",
       "      <td>0.364</td>\n",
       "      <td>1656</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>A</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>0.725</td>\n",
       "      <td>0.191</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.036</td>\n",
       "      <td>1656</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>A</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>0.895</td>\n",
       "      <td>0.432</td>\n",
       "      <td>0.050</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1380</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>B</td>\n",
       "      <td>costa</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>-0.077</td>\n",
       "      <td>0.133</td>\n",
       "      <td>0.570</td>\n",
       "      <td>0.551</td>\n",
       "      <td>144</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>B</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>1.769</td>\n",
       "      <td>0.433</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.002</td>\n",
       "      <td>144</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>B</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>2.139</td>\n",
       "      <td>1.043</td>\n",
       "      <td>0.052</td>\n",
       "      <td>NaN</td>\n",
       "      <td>120</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>B</td>\n",
       "      <td>exp</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>0.074</td>\n",
       "      <td>0.065</td>\n",
       "      <td>0.268</td>\n",
       "      <td>0.260</td>\n",
       "      <td>138</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>B</td>\n",
       "      <td>exp</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.346</td>\n",
       "      <td>0.690</td>\n",
       "      <td>0.731</td>\n",
       "      <td>138</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>B</td>\n",
       "      <td>exp</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>0.110</td>\n",
       "      <td>0.726</td>\n",
       "      <td>0.880</td>\n",
       "      <td>NaN</td>\n",
       "      <td>115</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>B</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>0.046</td>\n",
       "      <td>0.064</td>\n",
       "      <td>0.480</td>\n",
       "      <td>0.434</td>\n",
       "      <td>138</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>B</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>0.469</td>\n",
       "      <td>0.266</td>\n",
       "      <td>0.092</td>\n",
       "      <td>0.268</td>\n",
       "      <td>138</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>B</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>0.578</td>\n",
       "      <td>0.539</td>\n",
       "      <td>0.295</td>\n",
       "      <td>NaN</td>\n",
       "      <td>115</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>C</td>\n",
       "      <td>costa</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>-0.062</td>\n",
       "      <td>0.053</td>\n",
       "      <td>0.252</td>\n",
       "      <td>0.294</td>\n",
       "      <td>5328</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>C</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>1.868</td>\n",
       "      <td>0.240</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.002</td>\n",
       "      <td>5328</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>C</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>3.419</td>\n",
       "      <td>0.577</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4440</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>C</td>\n",
       "      <td>exp</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>-0.009</td>\n",
       "      <td>0.022</td>\n",
       "      <td>0.679</td>\n",
       "      <td>0.670</td>\n",
       "      <td>5256</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>C</td>\n",
       "      <td>exp</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>0.566</td>\n",
       "      <td>0.180</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.006</td>\n",
       "      <td>5256</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>C</td>\n",
       "      <td>exp</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>0.999</td>\n",
       "      <td>0.364</td>\n",
       "      <td>0.012</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4380</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>C</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>-0.015</td>\n",
       "      <td>0.024</td>\n",
       "      <td>0.550</td>\n",
       "      <td>0.562</td>\n",
       "      <td>5256</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>C</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>0.761</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.002</td>\n",
       "      <td>5256</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>C</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>1.353</td>\n",
       "      <td>0.244</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4380</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>D</td>\n",
       "      <td>costa</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>-0.107</td>\n",
       "      <td>0.092</td>\n",
       "      <td>0.260</td>\n",
       "      <td>0.279</td>\n",
       "      <td>1332</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>D</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>2.188</td>\n",
       "      <td>0.323</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.001</td>\n",
       "      <td>1332</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>D</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>3.716</td>\n",
       "      <td>0.778</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1110</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>D</td>\n",
       "      <td>exp</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>-0.008</td>\n",
       "      <td>0.039</td>\n",
       "      <td>0.835</td>\n",
       "      <td>0.846</td>\n",
       "      <td>1314</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>D</td>\n",
       "      <td>exp</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>0.636</td>\n",
       "      <td>0.218</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.015</td>\n",
       "      <td>1314</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>D</td>\n",
       "      <td>exp</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>1.075</td>\n",
       "      <td>0.411</td>\n",
       "      <td>0.016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1095</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>D</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w1</td>\n",
       "      <td>main</td>\n",
       "      <td>-0.011</td>\n",
       "      <td>0.038</td>\n",
       "      <td>0.766</td>\n",
       "      <td>0.794</td>\n",
       "      <td>1314</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>D</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2</td>\n",
       "      <td>main</td>\n",
       "      <td>0.835</td>\n",
       "      <td>0.136</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.002</td>\n",
       "      <td>1314</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>D</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2post</td>\n",
       "      <td>main</td>\n",
       "      <td>1.421</td>\n",
       "      <td>0.304</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1095</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   spec   expo  window variant      b  se_cl   p_cl  p_wild     N   G\n",
       "0     A  costa      w1    main -0.156  0.084  0.074   0.102  1728  24\n",
       "1     A  costa      w2    main  2.184  0.328  0.000   0.002  1728  24\n",
       "2     A  costa  w2post    main  2.915  0.881  0.003     NaN  1440  24\n",
       "6     A    exp      w1    main -0.020  0.038  0.606   0.610  1656  23\n",
       "7     A    exp      w2    main  0.478  0.301  0.126   0.140  1656  23\n",
       "8     A    exp  w2post    main  0.472  0.612  0.449     NaN  1380  23\n",
       "12    A  lnexp      w1    main -0.036  0.038  0.363   0.364  1656  23\n",
       "13    A  lnexp      w2    main  0.725  0.191  0.001   0.036  1656  23\n",
       "14    A  lnexp  w2post    main  0.895  0.432  0.050     NaN  1380  23\n",
       "22    B  costa      w1    main -0.077  0.133  0.570   0.551   144  24\n",
       "23    B  costa      w2    main  1.769  0.433  0.000   0.002   144  24\n",
       "24    B  costa  w2post    main  2.139  1.043  0.052     NaN   120  24\n",
       "28    B    exp      w1    main  0.074  0.065  0.268   0.260   138  23\n",
       "29    B    exp      w2    main  0.140  0.346  0.690   0.731   138  23\n",
       "30    B    exp  w2post    main  0.110  0.726  0.880     NaN   115  23\n",
       "34    B  lnexp      w1    main  0.046  0.064  0.480   0.434   138  23\n",
       "35    B  lnexp      w2    main  0.469  0.266  0.092   0.268   138  23\n",
       "36    B  lnexp  w2post    main  0.578  0.539  0.295     NaN   115  23\n",
       "44    C  costa      w1    main -0.062  0.053  0.252   0.294  5328  24\n",
       "45    C  costa      w2    main  1.868  0.240  0.000   0.002  5328  24\n",
       "46    C  costa  w2post    main  3.419  0.577  0.000     NaN  4440  24\n",
       "50    C    exp      w1    main -0.009  0.022  0.679   0.670  5256  23\n",
       "51    C    exp      w2    main  0.566  0.180  0.005   0.006  5256  23\n",
       "52    C    exp  w2post    main  0.999  0.364  0.012     NaN  4380  23\n",
       "56    C  lnexp      w1    main -0.015  0.024  0.550   0.562  5256  23\n",
       "57    C  lnexp      w2    main  0.761  0.105  0.000   0.002  5256  23\n",
       "58    C  lnexp  w2post    main  1.353  0.244  0.000     NaN  4380  23\n",
       "66    D  costa      w1    main -0.107  0.092  0.260   0.279  1332  24\n",
       "67    D  costa      w2    main  2.188  0.323  0.000   0.001  1332  24\n",
       "68    D  costa  w2post    main  3.716  0.778  0.000     NaN  1110  24\n",
       "72    D    exp      w1    main -0.008  0.039  0.835   0.846  1314  23\n",
       "73    D    exp      w2    main  0.636  0.218  0.008   0.015  1314  23\n",
       "74    D    exp  w2post    main  1.075  0.411  0.016     NaN  1095  23\n",
       "78    D  lnexp      w1    main -0.011  0.038  0.766   0.794  1314  23\n",
       "79    D  lnexp      w2    main  0.835  0.136  0.000   0.002  1314  23\n",
       "80    D  lnexp  w2post    main  1.421  0.304  0.000     NaN  1095  23"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "WIN = {\"w1\": (2014, 2019), \"w2\": (2020, 2025), \"w2post\": (2021, 2025)}\n",
    "CO = []\n",
    "def add(k, expo, window, variant, r, j=0):\n",
    "    CO.append(dict(spec=k, expo=expo, window=window, variant=variant, b=r[\"b\"][j], se_cl=r[\"se_cl\"][j],\n",
    "                   p_cl=r[\"p_cl\"][j], p_wild=r[\"p_wild\"][j], N=r[\"N\"], G=r[\"G\"]))\n",
    "for k, (u, p, lab) in SPECS.items():\n",
    "    pn0 = PANELS[k]; pnm = attach_exposure(pn0, u); B = 0 if FAST else (499 if k in \"AC\" else 999)\n",
    "    for col in (\"costa\", \"exp\", \"lnexp\"):\n",
    "        pn = pn0 if col == \"costa\" else pnm\n",
    "        for wn, (a, b_) in WIN.items():\n",
    "            d = pn[(pn.year >= a) & (pn.year <= b_)].copy(); d[\"x\"] = d[col] * d.lncoca\n",
    "            add(k, col, wn, \"main\", fit_fe(d, u, p, [\"x\"], B=B if wn in (\"w1\", \"w2\") else 0))\n",
    "        for wn in (\"w1\", \"w2\"):                      # lagged coca\n",
    "            a, b_ = WIN[wn]; d = pn[(pn.year >= max(a, 2015)) & (pn.year <= b_)].copy(); d[\"x\"] = d[col] * d.lncoca_l1\n",
    "            add(k, col, wn, \"lag1\", fit_fe(d, u, p, [\"x\"]))\n",
    "        d = pn[pn.year >= 2020].copy(); d[\"x\"] = d[col] * d.lncoca; d[\"tt\"] = d[col] * (d.year - 2020)   # own linear trend\n",
    "        add(k, col, \"w2\", \"trend\", fit_fe(d, u, p, [\"x\", \"tt\"]))\n",
    "    for wn in (\"w1\", \"w2\"):                          # horse race, mainland sample\n",
    "        a, b_ = WIN[wn]; d = pnm[(pnm.year >= a) & (pnm.year <= b_)].copy()\n",
    "        d[\"xe\"] = d.lnexp * d.lncoca; d[\"xc\"] = d.costa * d.lncoca\n",
    "        r = fit_fe(d, u, p, [\"xe\", \"xc\"], B=B if wn == \"w2\" else 0)\n",
    "        add(k, \"lnexp\", wn, \"horse\", r, 0); add(k, \"costa\", wn, \"horse\", r, 1)\n",
    "    print(\"done\", k, lab)\n",
    "CO = pd.DataFrame(CO); CO.to_csv(OUT / \"coca_models.csv\", index=False)\n",
    "CO[CO.variant == \"main\"].round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "60267c69",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:25:11.669477Z",
     "iopub.status.busy": "2026-10-09T11:25:11.669260Z",
     "iopub.status.idle": "2026-10-09T11:25:24.968323Z",
     "shell.execute_reply": "2026-10-09T11:25:24.967514Z"
    },
    "lines_to_next_cell": 1
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>spec</th>\n",
       "      <th>expo</th>\n",
       "      <th>window</th>\n",
       "      <th>obs</th>\n",
       "      <th>p_two</th>\n",
       "      <th>p_pos</th>\n",
       "      <th>nperm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>B</td>\n",
       "      <td>costa</td>\n",
       "      <td>w1</td>\n",
       "      <td>-0.0765</td>\n",
       "      <td>0.4778</td>\n",
       "      <td>0.7472</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2</td>\n",
       "      <td>1.7686</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>B</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2post</td>\n",
       "      <td>2.1390</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w1</td>\n",
       "      <td>0.0459</td>\n",
       "      <td>0.5944</td>\n",
       "      <td>0.3056</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2</td>\n",
       "      <td>0.4692</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>B</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2post</td>\n",
       "      <td>0.5784</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>D</td>\n",
       "      <td>costa</td>\n",
       "      <td>w1</td>\n",
       "      <td>-0.1067</td>\n",
       "      <td>0.4389</td>\n",
       "      <td>0.7861</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>D</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2</td>\n",
       "      <td>2.1878</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>D</td>\n",
       "      <td>costa</td>\n",
       "      <td>w2post</td>\n",
       "      <td>3.7162</td>\n",
       "      <td>0.0333</td>\n",
       "      <td>0.0333</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>D</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w1</td>\n",
       "      <td>-0.0115</td>\n",
       "      <td>0.7583</td>\n",
       "      <td>0.6847</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>D</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2</td>\n",
       "      <td>0.8348</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>D</td>\n",
       "      <td>lnexp</td>\n",
       "      <td>w2post</td>\n",
       "      <td>1.4212</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   spec   expo  window     obs   p_two   p_pos  nperm\n",
       "0     B  costa      w1 -0.0765  0.4778  0.7472    720\n",
       "1     B  costa      w2  1.7686  0.0167  0.0167    720\n",
       "2     B  costa  w2post  2.1390  0.1000  0.1000    120\n",
       "3     B  lnexp      w1  0.0459  0.5944  0.3056    720\n",
       "4     B  lnexp      w2  0.4692  0.0167  0.0167    720\n",
       "5     B  lnexp  w2post  0.5784  0.1000  0.1000    120\n",
       "6     D  costa      w1 -0.1067  0.4389  0.7861    720\n",
       "7     D  costa      w2  2.1878  0.0056  0.0056    720\n",
       "8     D  costa  w2post  3.7162  0.0333  0.0333    120\n",
       "9     D  lnexp      w1 -0.0115  0.7583  0.6847    720\n",
       "10    D  lnexp      w2  0.8348  0.0014  0.0014    720\n",
       "11    D  lnexp  w2post  1.4212  0.0083  0.0083    120"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Permutation inference (annual panels): reassign the years of the coca series within each window (6! = 720 orderings)\n",
    "PERM = []\n",
    "if not FAST:\n",
    "    base = COCA.set_index(\"year\").lncoca\n",
    "    for k in (\"B\", \"D\"):\n",
    "        u, p, _ = SPECS[k]; pn0 = PANELS[k]; pnm = attach_exposure(pn0, u)\n",
    "        for col, pn in ((\"costa\", pn0), (\"lnexp\", pnm)):\n",
    "            for wn in (\"w1\", \"w2\", \"w2post\"):\n",
    "                a, b_ = WIN[wn]; d = pn[(pn.year >= a) & (pn.year <= b_)].copy(); yrs = list(range(a, b_ + 1))\n",
    "                def slope(order):\n",
    "                    d[\"x\"] = d[col] * d.year.map(dict(zip(yrs, [base[y] for y in order])))\n",
    "                    return fit_fe(d, u, p, [\"x\"])[\"b\"][0]\n",
    "                obs = slope(yrs); sl = np.array([slope(o) for o in itertools.permutations(yrs)])\n",
    "                PERM.append(dict(spec=k, expo=col, window=wn, obs=obs, p_two=float((np.abs(sl) >= abs(obs) - 1e-12).mean()),\n",
    "                                 p_pos=float((sl >= obs - 1e-12).mean()), nperm=len(sl)))\n",
    "PERM = pd.DataFrame(PERM); PERM.to_csv(OUT / \"coca_permutation.csv\", index=False); PERM.round(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3a528a54",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:25:24.970175Z",
     "iopub.status.busy": "2026-10-09T11:25:24.969983Z",
     "iopub.status.idle": "2026-10-09T11:25:25.017163Z",
     "shell.execute_reply": "2026-10-09T11:25:25.016144Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                              A               B               C               D\n",
      "Coast × ln(coca): Window 1 (2014–2019)             -0.16 (0.08)    -0.08 (0.13)    -0.06 (0.05)    -0.11 (0.09)\n",
      "Coast × ln(coca): Window 2 (2020–2025)           2.18*** (0.33)  1.77*** (0.43)  1.87*** (0.24)  2.19*** (0.32)\n",
      "Coast × ln(coca): Window 2, 2021–2025            2.92*** (0.88)    2.14* (1.04)  3.42*** (0.58)  3.72*** (0.78)\n",
      "Port proximity × ln(coca): Window 1 (2014–2019)    -0.04 (0.04)     0.05 (0.06)    -0.01 (0.02)    -0.01 (0.04)\n",
      "Port proximity × ln(coca): Window 2 (2020–2025)   0.72** (0.19)     0.47 (0.27)  0.76*** (0.10)  0.83*** (0.14)\n",
      "Port proximity × ln(coca): Window 2, 2021–2025    0.90** (0.43)     0.58 (0.54)  1.35*** (0.24)  1.42*** (0.30)\n",
      "                                                         A               B               C               D\n",
      "Coast × ln(coca), lag-1 coca, W2            1.82*** (0.35)  1.43*** (0.42)  1.75*** (0.25)  1.98*** (0.34)\n",
      "Coast × ln(coca), + Coast linear trend, W2  1.88*** (0.40)  1.77*** (0.51)  0.82*** (0.17)  1.21*** (0.23)\n",
      "Horse race, W2: Coast × ln(coca)            2.15*** (0.66)  1.92*** (0.75)   1.54** (0.53)   1.95** (0.59)\n",
      "Horse race, W2: Proximity × ln(coca)          -0.02 (0.32)    -0.20 (0.45)     0.22 (0.21)     0.14 (0.24)\n",
      "Horse race, W1: Coast × ln(coca)            -0.21** (0.09)   -0.28* (0.14)   -0.08* (0.05)   -0.18* (0.10)\n",
      "Horse race, W1: Proximity × ln(coca)           0.04 (0.03)    0.14* (0.07)     0.01 (0.02)     0.05 (0.03)\n",
      "Stars: wild-bootstrap p where computed, otherwise province-clustered p (t, G−1 df). * p<0.10 ** p<0.05 *** p<0.01\n"
     ]
    }
   ],
   "source": [
    "def star(p): return \"***\" if p < .01 else \"**\" if p < .05 else \"*\" if p < .1 else \"\"\n",
    "def pick(k, e, w, v=\"main\"): return CO[(CO.spec == k) & (CO.expo == e) & (CO.window == w) & (CO.variant == v)].iloc[0]\n",
    "def cell(r, wild=True):\n",
    "    pv = r.p_wild if (wild and not np.isnan(r.p_wild)) else r.p_cl\n",
    "    return f\"{r.b:.2f}{star(pv)} ({r.se_cl:.2f})\"\n",
    "T4 = {}\n",
    "for e, lab in ((\"costa\", \"Coast\"), (\"lnexp\", \"Port proximity\")):\n",
    "    for w, wl in ((\"w1\", \"Window 1 (2014–2019)\"), (\"w2\", \"Window 2 (2020–2025)\"), (\"w2post\", \"Window 2, 2021–2025\")):\n",
    "        T4[f\"{lab} × ln(coca): {wl}\"] = [cell(pick(k, e, w)) for k in SPECS]\n",
    "T4 = pd.DataFrame(T4, index=list(SPECS)).T; T4.to_csv(OUT / \"Table4_coca_windows.csv\"); print(T4)\n",
    "T5 = {\"Coast × ln(coca), lag-1 coca, W2\": [cell(pick(k, \"costa\", \"w2\", \"lag1\"), False) for k in SPECS],\n",
    "      \"Coast × ln(coca), + Coast linear trend, W2\": [cell(pick(k, \"costa\", \"w2\", \"trend\"), False) for k in SPECS],\n",
    "      \"Horse race, W2: Coast × ln(coca)\": [cell(pick(k, \"costa\", \"w2\", \"horse\")) for k in SPECS],\n",
    "      \"Horse race, W2: Proximity × ln(coca)\": [cell(pick(k, \"lnexp\", \"w2\", \"horse\")) for k in SPECS],\n",
    "      \"Horse race, W1: Coast × ln(coca)\": [cell(pick(k, \"costa\", \"w1\", \"horse\"), False) for k in SPECS],\n",
    "      \"Horse race, W1: Proximity × ln(coca)\": [cell(pick(k, \"lnexp\", \"w1\", \"horse\"), False) for k in SPECS]}\n",
    "T5 = pd.DataFrame(T5, index=list(SPECS)).T; T5.to_csv(OUT / \"Table5_robustness_horse_race.csv\"); print(T5)\n",
    "print(\"Stars: wild-bootstrap p where computed, otherwise province-clustered p (t, G−1 df). * p<0.10 ** p<0.05 *** p<0.01\")"
   ]
  },
  {
   "cell_type": "code",
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   "id": "011d1ab2",
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     "shell.execute_reply": "2026-10-09T11:25:25.580857Z"
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    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x440 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Figure 4: coca series and within-window slopes\n",
    "C = COCA[COCA.year.between(2014, 2025)]\n",
    "fig, (a1, a2) = plt.subplots(1, 2, figsize=(12, 4.4), gridspec_kw=dict(width_ratios=[1, 1.25]))\n",
    "a1.plot(C.year, C.ha / 1000, marker=\"o\", color=\"#1f2937\")\n",
    "a1.axvspan(2013.7, 2019.5, color=\"#bfdbfe\", alpha=.35); a1.axvspan(2019.5, 2025.3, color=\"#fecaca\", alpha=.35)\n",
    "a1.text(2016.6, 265, \"Window 1\\n(2014–2019)\", ha=\"center\", fontsize=8.5); a1.text(2022.4, 60, \"Window 2\\n(2020–2025)\", ha=\"center\", fontsize=8.5)\n",
    "a1.set_ylabel(\"Hectares of coca, Colombia (thousands)\"); a1.set_xlim(2013.7, 2025.3); a1.set_ylim(0, 300)\n",
    "a1.spines[[\"top\", \"right\"]].set_visible(False); a1.set_title(\"(a) Colombian coca cultivation\", fontsize=10, fontweight=\"bold\", loc=\"left\")\n",
    "cc = {\"costa\": \"#991b1b\", \"lnexp\": \"#1d4ed8\"}\n",
    "for x, k in enumerate(SPECS):\n",
    "    for wn, wo in ((\"w1\", -.22), (\"w2\", .22)):\n",
    "        for e, eo in ((\"costa\", -.07), (\"lnexp\", .07)):\n",
    "            q = pick(k, e, wn); tc = stats.t.ppf(.975, q.G - 1)\n",
    "            a2.errorbar(x + wo + eo, q.b, yerr=tc * q.se_cl, fmt=\"s\" if wn == \"w1\" else \"o\", mfc=\"white\" if wn == \"w1\" else cc[e], color=cc[e], capsize=2, ms=5)\n",
    "a2.axhline(0, color=\"k\", lw=.8); a2.set_xticks(range(4)); a2.set_xticklabels([f\"({k}) {SPECS[k][2]}\" for k in SPECS], fontsize=8)\n",
    "a2.set_ylabel(\"Coefficient on exposure × ln(coca)\"); a2.spines[[\"top\", \"right\"]].set_visible(False); a2.grid(axis=\"y\", alpha=.2)\n",
    "hs = [plt.Line2D([], [], marker=\"s\", mfc=\"white\", color=\"k\", ls=\"\", label=\"Window 1 (2014–2019)\"),\n",
    "      plt.Line2D([], [], marker=\"o\", color=\"k\", ls=\"\", label=\"Window 2 (2020–2025)\"),\n",
    "      mp.Patch(color=cc[\"costa\"], label=\"Coast dummy\"), mp.Patch(color=cc[\"lnexp\"], label=\"Port proximity\")]\n",
    "a2.legend(handles=hs, fontsize=7.5, frameon=False, loc=\"upper right\")\n",
    "a2.set_title(\"(b) Within-window slopes (95% CI, province-clustered)\", fontsize=10, fontweight=\"bold\", loc=\"left\")\n",
    "plt.tight_layout(); plt.savefig(OUT / \"Figure4_coca.png\", dpi=200); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "668db618",
   "metadata": {},
   "source": [
    "## 7. Key numbers cited in the text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "866c409d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:25:25.583339Z",
     "iopub.status.busy": "2026-10-09T11:25:25.583178Z",
     "iopub.status.idle": "2026-10-09T11:25:25.627024Z",
     "shell.execute_reply": "2026-10-09T11:25:25.626082Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Specification A, ref 2019, Oct 2020–Mar 2021:\n",
      "     per  coef  pval\n",
      "2020_10 0.417 0.025\n",
      "2020_11 0.497 0.005\n",
      "2020_12 0.389 0.062\n",
      "2021_01 0.234 0.359\n",
      "2021_02 0.280 0.344\n",
      "2021_03 0.495 0.018\n",
      "A ref 2019, non-significant months from Mar 2021: ['2021_07']\n",
      "\n",
      "Specification C, ref 2019, 2020–2021:\n",
      "     per   coef  pval\n",
      "2020_T1 -0.035 0.622\n",
      "2020_T2 -0.075 0.270\n",
      "2020_T3 -0.013 0.845\n",
      "2020_T4  0.222 0.001\n",
      "2021_T1  0.167 0.026\n",
      "2021_T2  0.276 0.000\n",
      "2021_T3  0.255 0.000\n",
      "2021_T4  0.355 0.000\n",
      "C ref 2019, non-significant quarters from Q4 2020: []\n",
      "\n",
      "Port proximity (ln), C ref 2019:\n",
      "     per  coef  pval\n",
      "2020_T3 0.005 0.885\n",
      "2020_T4 0.098 0.008\n",
      "2021_T1 0.113 0.001\n",
      "non-significant quarters from Q4 2020: []\n",
      "\n",
      "Annual panels, 2020 coefficient (ref 2019): B  per  coef  pval\n",
      "2020 0.169 0.427 \n",
      "D  per  coef  pval\n",
      "2020 0.009 0.931\n",
      "B: all years 2021–2025 significant: True\n",
      "D: all years 2021–2025 significant: True\n",
      "\n",
      "A ref 2020 first significant: 2021_04 0.527 0.003\n",
      "Linear pre-trend, ref 2019 (years 2014–2018), Coast: {'A': (-0.047, 0.007), 'B': (-0.037, 0.195), 'C': (-0.021, 0.085), 'D': (-0.039, 0.065)}\n",
      "\n",
      "Δ ln coca: 2014→2017 0.909; 2017→2020 -0.183; 2020→2024 0.605\n",
      "Guayaquil share of coastal homicides: 0.327\n"
     ]
    }
   ],
   "source": [
    "def show(k, ref, col, pers):\n",
    "    r = RES[(k, ref, col)][\"r\"]; return r[r.per.isin(pers)][[\"per\", \"coef\", \"pval\"]].round(3).to_string(index=False)\n",
    "print(\"Specification A, ref 2019, Oct 2020–Mar 2021:\\n\", show(\"A\", \"2019\", \"costa\", [\"2020_10\", \"2020_11\", \"2020_12\", \"2021_01\", \"2021_02\", \"2021_03\"]))\n",
    "rA = RES[(\"A\", \"2019\", \"costa\")][\"r\"]; print(\"A ref 2019, non-significant months from Mar 2021:\", rA[(rA.per >= \"2021_03\") & (rA.pval >= .05)].per.tolist())\n",
    "print(\"\\nSpecification C, ref 2019, 2020–2021:\\n\", show(\"C\", \"2019\", \"costa\", [f\"{y}_T{q}\" for y in (2020, 2021) for q in range(1, 5)]))\n",
    "rC = RES[(\"C\", \"2019\", \"costa\")][\"r\"]; print(\"C ref 2019, non-significant quarters from Q4 2020:\", rC[(rC.per >= \"2020_T4\") & (rC.pval >= .05)].per.tolist())\n",
    "print(\"\\nPort proximity (ln), C ref 2019:\\n\", show(\"C\", \"2019\", \"lnexp\", [\"2020_T3\", \"2020_T4\", \"2021_T1\"]))\n",
    "rCl = RES[(\"C\", \"2019\", \"lnexp\")][\"r\"]; print(\"non-significant quarters from Q4 2020:\", rCl[(rCl.per >= \"2020_T4\") & (rCl.pval >= .05)].per.tolist())\n",
    "print(\"\\nAnnual panels, 2020 coefficient (ref 2019): B\", show(\"B\", \"2019\", \"costa\", [\"2020\"]), \"\\nD\", show(\"D\", \"2019\", \"costa\", [\"2020\"]))\n",
    "for k in \"BD\":\n",
    "    r = RES[(k, \"2019\", \"costa\")][\"r\"]; print(f\"{k}: all years 2021–2025 significant:\", bool((r[r.year >= 2021].pval < .05).all()))\n",
    "print(\"\\nA ref 2020 first significant:\", RES[(\"A\", \"2020\", \"costa\")][\"first_sig\"], round(RES[(\"A\", \"2020\", \"costa\")][\"first_sig_coef\"], 3), round(RES[(\"A\", \"2020\", \"costa\")][\"first_sig_p\"], 4))\n",
    "print(\"Linear pre-trend, ref 2019 (years 2014–2018), Coast:\", {k: (round(float(RES[(k, '2019', 'costa')]['pre_slope']), 3), round(float(RES[(k, '2019', 'costa')]['pre_slope_p']), 3)) for k in SPECS})\n",
    "base = COCA.set_index(\"year\").lncoca\n",
    "print(f\"\\nΔ ln coca: 2014→2017 {base[2017]-base[2014]:.3f}; 2017→2020 {base[2020]-base[2017]:.3f}; 2020→2024 {base[2024]-base[2020]:.3f}\")\n",
    "print(\"Guayaquil share of coastal homicides:\", round((df[df.grupo == \"Costa\"].canton == \"GUAYAQUIL\").mean(), 3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6011d1ae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-09T11:25:25.628567Z",
     "iopub.status.busy": "2026-10-09T11:25:25.628399Z",
     "iopub.status.idle": "2026-10-09T11:25:25.673168Z",
     "shell.execute_reply": "2026-10-09T11:25:25.672010Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['All_tables.xlsx', 'Figure2_monthly_ref2019.png', 'Figure3_four_specs_ref2019.png', 'Figure4_coca.png', 'Figure5_port_proximity_ref2019.png', 'FigureA1_monthly_ref2020.png', 'FigureA2_four_specs_ref2020.png', 'Table1_panels.csv', 'Table2_reference_period.csv', 'Table3_summary.csv', 'Table4_coca_windows.csv', 'Table5_robustness_horse_race.csv', 'canton_port_exposure.csv', 'coca_models.csv', 'coca_permutation.csv', 'event_study_A_ref2019_costa.csv', 'event_study_A_ref2019_exp.csv', 'event_study_A_ref2019_lnexp.csv', 'event_study_A_ref2020_costa.csv', 'event_study_A_ref2020_exp.csv', 'event_study_A_ref2020_lnexp.csv', 'event_study_B_ref2019_costa.csv', 'event_study_B_ref2019_exp.csv', 'event_study_B_ref2019_lnexp.csv', 'event_study_B_ref2020_costa.csv', 'event_study_B_ref2020_exp.csv', 'event_study_B_ref2020_lnexp.csv', 'event_study_C_ref2019_costa.csv', 'event_study_C_ref2019_exp.csv', 'event_study_C_ref2019_lnexp.csv', 'event_study_C_ref2020_costa.csv', 'event_study_C_ref2020_exp.csv', 'event_study_C_ref2020_lnexp.csv', 'event_study_D_ref2019_costa.csv', 'event_study_D_ref2019_exp.csv', 'event_study_D_ref2019_lnexp.csv', 'event_study_D_ref2020_costa.csv', 'event_study_D_ref2020_exp.csv', 'event_study_D_ref2020_lnexp.csv', 'event_study_summary.csv', 'province_port_exposure.csv']\n"
     ]
    }
   ],
   "source": [
    "with pd.ExcelWriter(OUT / \"All_tables.xlsx\") as w:\n",
    "    T1.to_excel(w, sheet_name=\"Table1\", index=False); T2.to_excel(w, sheet_name=\"Table2\", index=False)\n",
    "    T3.to_excel(w, sheet_name=\"Table3\"); T4.to_excel(w, sheet_name=\"Table4\"); T5.to_excel(w, sheet_name=\"Table5\")\n",
    "    SUM.to_excel(w, sheet_name=\"EventStudy_summary\", index=False); CO.to_excel(w, sheet_name=\"Coca_models\", index=False)\n",
    "    PERM.to_excel(w, sheet_name=\"Permutation\", index=False)\n",
    "print(sorted(f.name for f in OUT.iterdir()))"
   ]
  }
 ],
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