diff --git a/src/sparsematrix.jl b/src/sparsematrix.jl
index f94318b2..4fa2adf9 100644
--- a/src/sparsematrix.jl
+++ b/src/sparsematrix.jl
@@ -3908,13 +3908,11 @@ function vcat(X::AbstractSparseMatrixCSC...)
         ptr_res = colptr[c]
         for i = 1 : num
             colptrXi = getcolptr(X[i])
-            col_length = (colptrXi[c + 1] - 1) - colptrXi[c]
+            col_length = colptrXi[c + 1] - colptrXi[c]
             ptr_Xi = colptrXi[c]
 
-            stuffcol!(X[i], colptr, rowval, nzval,
-                      ptr_res, ptr_Xi, col_length, mX_sofar)
-
-            ptr_res += col_length + 1
+            ptr_res = stuffcol!(rowval, nzval, ptr_res, rowvals(X[i]), nonzeros(X[i]), ptr_Xi,
+                                col_length, mX_sofar)
             mX_sofar += mX[i]
         end
         colptr[c + 1] = ptr_res
@@ -3922,17 +3920,14 @@ function vcat(X::AbstractSparseMatrixCSC...)
     SparseMatrixCSC(m, n, colptr, rowval, nzval)
 end
 
-@inline function stuffcol!(Xi::AbstractSparseMatrixCSC, colptr, rowval, nzval,
-                           ptr_res, ptr_Xi, col_length, mX_sofar)
-    colptrXi = getcolptr(Xi)
-    rowvalXi = rowvals(Xi)
-    nzvalXi  = nonzeros(Xi)
-
-    for k=ptr_res:(ptr_res + col_length)
+@inline function stuffcol!(rowval, nzval, ptr_res, rowvalXi, nzvalXi, ptr_Xi,
+                           col_length, mX_sofar)
+    for k=ptr_res:(ptr_res + col_length - 1)
         @inbounds rowval[k] = rowvalXi[ptr_Xi] + mX_sofar
         @inbounds nzval[k]  = nzvalXi[ptr_Xi]
         ptr_Xi += 1
     end
+    return ptr_res + col_length
 end
 
 function hcat(X::AbstractSparseMatrixCSC...)
@@ -3973,6 +3968,42 @@ function hcat(X::AbstractSparseMatrixCSC...)
     SparseMatrixCSC(m, n, colptr, rowval, nzval)
 end
 
+
+# Efficient repetition of sparse matrices
+
+function Base.repeat(A::AbstractSparseMatrixCSC, m)
+    nnz_new = nnz(A) * m
+    colptr = similar(getcolptr(A), length(getcolptr(A)))
+    rowval = similar(rowvals(A), nnz_new)
+    nzval = similar(nonzeros(A), nnz_new)
+
+    colptr[1] = 1
+    for c = 1 : size(A, 2)
+        ptr_res = colptr[c]
+        ptr_source = getcolptr(A)[c]
+        col_length = getcolptr(A)[c + 1] - ptr_source
+        for index_repetition = 0 : (m - 1)
+            row_offset = index_repetition * size(A, 1)
+            ptr_res = stuffcol!(rowval, nzval, ptr_res, rowvals(A), nonzeros(A), ptr_source,
+                                col_length, row_offset)
+        end
+        colptr[c + 1] = ptr_res
+    end
+    @assert colptr[end] == nnz_new + 1
+
+    SparseMatrixCSC(size(A, 1) * m, size(A, 2), colptr, rowval, nzval)
+end
+
+function Base.repeat(A::AbstractSparseMatrixCSC, m, n)
+    B = repeat(A, m)
+    nnz_per_column = diff(getcolptr(B))
+    colptr = cumsum(vcat(1, repeat(nnz_per_column, n)))
+    rowval = repeat(rowvals(B), n)
+    nzval = repeat(nonzeros(B), n)
+    SparseMatrixCSC(size(B, 1), size(B, 2) * n, colptr, rowval, nzval)
+end
+
+
 """
     blockdiag(A...)
 
diff --git a/src/sparsevector.jl b/src/sparsevector.jl
index 97cf979e..a2102eff 100644
--- a/src/sparsevector.jl
+++ b/src/sparsevector.jl
@@ -1308,6 +1308,34 @@ hvcat(rows::Tuple{Vararg{Int}}, n1::Number, ns::Vararg{Number}) = invoke(hvcat,
 hvcat(rows::Tuple{Vararg{Int}}, n1::N, ns::Vararg{N}) where {N<:Number} = invoke(hvcat, Tuple{typeof(rows), Vararg{N}}, rows, n1, ns...)
 
 
+### Efficient repetition of sparse vectors
+
+function Base.repeat(v::AbstractSparseVector, m)
+    nnz_source = nnz(v)
+    nnz_new = nnz_source * m
+
+    nzind = similar(nonzeroinds(v), nnz_new)
+    nzval = similar(nonzeros(v), nnz_new)
+
+    ptr_res = 1
+    for index_repetition = 0:(m-1)
+        row_offset = index_repetition * length(v)
+        ptr_res = stuffcol!(nzind, nzval, ptr_res, nonzeroinds(v), nonzeros(v), 1, nnz_source, row_offset)
+    end
+    @assert ptr_res == nnz_new + 1
+
+    SparseVector(length(v) * m, nzind, nzval)
+end
+
+function Base.repeat(v::AbstractSparseVector, m, n)
+    w = repeat(v, m)
+    colptr = Vector{eltype(nonzeroinds(w))}(1 .+ nnz(w) * (0:n))
+    rowval = repeat(nonzeroinds(w), n)
+    nzval = repeat(nonzeros(w), n)
+    SparseMatrixCSC(length(w), n, colptr, rowval, nzval)
+end
+
+
 # make sure UniformScaling objects are converted to sparse matrices for concatenation
 promote_to_array_type(A::Tuple{Vararg{Union{_SparseConcatGroup,UniformScaling}}}) = anysparse(A...) ? SparseMatrixCSC : Matrix
 promote_to_arrays_(n::Int, ::Type{SparseMatrixCSC}, J::UniformScaling) = sparse(J, n, n)
diff --git a/test/sparsematrix_constructors_indexing.jl b/test/sparsematrix_constructors_indexing.jl
index b1b08dbf..a0396f40 100644
--- a/test/sparsematrix_constructors_indexing.jl
+++ b/test/sparsematrix_constructors_indexing.jl
@@ -302,6 +302,19 @@ end
     end
 end
 
+@testset "repeat tests" begin
+    A = sprand(6, 4, 0.5)
+    A_full = Matrix(A)
+    for m = 0:3
+        @test issparse(repeat(A, m))
+        @test repeat(A, m) == repeat(A_full, m)
+        for n = 0:3
+            @test issparse(repeat(A, m, n))
+            @test repeat(A, m, n) == repeat(A_full, m, n)
+        end
+    end
+end
+
 @testset "copyto!" begin
     A = sprand(5, 5, 0.2)
     B = sprand(5, 5, 0.2)
diff --git a/test/sparsevector.jl b/test/sparsevector.jl
index 15499e12..c91f0d69 100644
--- a/test/sparsevector.jl
+++ b/test/sparsevector.jl
@@ -635,6 +635,18 @@ end
         end
     end
 end
+
+@testset "repeat" begin
+    for m = 0:3
+        @test issparse(repeat(spv_x1, m))
+        @test repeat(spv_x1, m) == repeat(x1_full, m)
+        for n = 0:3
+            @test issparse(repeat(spv_x1, m, n))
+            @test repeat(spv_x1, m, n) == repeat(x1_full, m, n)
+        end
+    end
+end
+
 @testset "sparsemat: combinations with sparse matrix" begin
     let S = sprand(4, 8, 0.5)
         Sf = Array(S)