diff --git a/R/geom-bar.r b/R/geom-bar.r
index 91d1767f3e..b1c7b5713f 100644
--- a/R/geom-bar.r
+++ b/R/geom-bar.r
@@ -118,6 +118,10 @@ GeomBar <- ggproto("GeomBar", GeomRect,
   non_missing_aes = c("xmin", "xmax", "ymin", "ymax"),
 
   setup_data = function(data, params) {
+    # Contrary to the case of geom_col(), the `width` in `data` is very likely
+    # a calculated column by Stat. So, geom_bar() should use data$width if
+    # available. Note that StatIdentity is not the case, but, as we cannot know
+    # what Stat was used, we can do nothing here.
     data$width <- data$width %||%
       params$width %||% (resolution(data$x, FALSE) * 0.9)
     transform(data,
diff --git a/R/geom-col.r b/R/geom-col.r
index 7ebd51f8fc..22f2fdd399 100644
--- a/R/geom-col.r
+++ b/R/geom-col.r
@@ -38,8 +38,11 @@ GeomCol <- ggproto("GeomCol", GeomRect,
   non_missing_aes = c("xmin", "xmax", "ymin", "ymax"),
 
   setup_data = function(data, params) {
-    data$width <- data$width %||%
-      params$width %||% (resolution(data$x, FALSE) * 0.9)
+    # To ensure bar widths are constant within a PANEL, `width` is not allowed
+    # to be mapped to data. So, even if the `data` already contains `width`, it
+    # should be ignored except when the width is calculated by Stat. But, as
+    # geom_col() uses stat_identity() fixedly, this is not the case.
+    data$width <- params$width %||% (resolution(data$x, FALSE) * 0.9)
     transform(data,
       ymin = pmin(y, 0), ymax = pmax(y, 0),
       xmin = x - width / 2, xmax = x + width / 2, width = NULL
diff --git a/tests/testthat/test-geom-col.R b/tests/testthat/test-geom-col.R
index ed10be1883..12335837c6 100644
--- a/tests/testthat/test-geom-col.R
+++ b/tests/testthat/test-geom-col.R
@@ -14,3 +14,12 @@ test_that("geom_col removes columns with parts outside the plot limits", {
     "Removed 1 rows containing missing values"
   )
 })
+
+test_that("geom_col() ignores width", {
+  dat <- data_frame(x = c(1, 2, 3))
+
+
+  p <- ggplot(dat, aes(x, x, width = x)) + geom_col()
+  d <- layer_data(p)
+  expect_equal(d$xmax - d$xmin, c(0.9, 0.9, 0.9))
+})