From c2063b5f10aedcc74e6aedcf4bf04b7c5c28f6ee Mon Sep 17 00:00:00 2001
From: inchang-ing <197932532+inchang-ing@users.noreply.github.com>
Date: Sun, 18 Oct 2026 12:53:16 +0800
Subject: [PATCH] BUG: Raise for ignored flags in out-of-sample panel
 predictions

---
 linearmodels/panel/results.py            | 12 ++++++++++--
 linearmodels/tests/panel/test_results.py | 21 +++++++++++++++++++++
 2 files changed, 31 insertions(+), 2 deletions(-)

diff --git a/linearmodels/panel/results.py b/linearmodels/panel/results.py
index e0f79aca71..e2bbbae011 100644
--- a/linearmodels/panel/results.py
+++ b/linearmodels/panel/results.py
@@ -605,8 +605,9 @@ def predict(
         Raises
         ------
         ValueError
-            If both `exog` and `data` are provided, or if no in-sample output
-            is selected.
+            If both `exog` and `data` are provided, if no in-sample output
+            is selected, or if `effects` or `idiosyncratic` is requested for
+            out-of-sample predictions.
 
         Notes
         -----
@@ -621,6 +622,13 @@ def predict(
         predictions.
         """
         if not (exog is None and data is None):
+            if effects or idiosyncratic:
+                raise ValueError(
+                    "effects and idiosyncratic are not available for "
+                    "out-of-sample predictions"
+                )
+            if not fitted:
+                raise ValueError("At least one output must be selected")
             context = capture_context(1)
             return self._out_of_sample(exog, data, missing, context=context)
         out = []
diff --git a/linearmodels/tests/panel/test_results.py b/linearmodels/tests/panel/test_results.py
index 82a9804d9f..20ae13459f 100644
--- a/linearmodels/tests/panel/test_results.py
+++ b/linearmodels/tests/panel/test_results.py
@@ -387,6 +387,27 @@ def test_predict_no_selection(generated_data):
         res.predict(fitted=False, effects=False, idiosyncratic=False, missing=True)
 
 
+def test_predict_out_of_sample_flags(generated_data):
+    if np.any(np.isnan(generated_data.x)):
+        pytest.skip("Cannot test with missing values")
+    with warns_if_missing(generated_data.y, generated_data.x):
+        mod = PanelOLS(generated_data.y, generated_data.x, entity_effects=True)
+    res = mod.fit()
+    exog = generated_data.x
+    with pytest.raises(
+        ValueError, match=r"not available for out-of-sample predictions"
+    ):
+        res.predict(exog, effects=True)
+    with pytest.raises(
+        ValueError, match=r"not available for out-of-sample predictions"
+    ):
+        res.predict(exog, idiosyncratic=True)
+    with pytest.raises(ValueError, match=r"At least one output must be"):
+        res.predict(exog, fitted=False)
+    pred = res.predict(exog)
+    assert list(pred.columns) == ["predictions"]
+
+
 @pytest.mark.parametrize(
     "constraint_formula",
     [