1. INTRODUCTION
An autoregressive process is integrated of order d if its characteristic equation has d roots at z = 1 and the remaining lie outside the unit circle. This is not true in the multivariate case where the multiplicity of the unit root in the characteristic equation is not sufficient to establish the order of integration of the process. This issue is central in the Granger representation theorem where the order of integration must be determined before deriving the different representations: Engle and Granger (1987) start from the moving average representation of an I(1) process that exhibits cointegration and derive the corresponding error correction model; unfortunately their proof is not correct because the order of integration is established by a wrong lemma (for a counterexample to their Lemma 1, see Johansen, 2005a). Johansen (1988, 1992) proves the representation theorems for I(1) and I(2) processes on the basis of the well-known rank conditions on the autoregressive coefficients, whereas other proofs of the same results are based on the Smith form of a matrix polynomial (see Engle and Yoo, 1991; Haldrup and Salmon, 1998) and on the Jordan representation of the companion form (see Archontakis, 1998; Bauer and Wagner, 2003). Other relevant papers in this area are those by Gregoire and Laroque (1993) and Gregoire (1999), who discuss polynomial cointegration in a very general setup, Neusser (2000), who points out some interesting algebraic properties of the I(1) model, and Hansen (2005) for an algorithm to calculate the coefficients in the I(1) case. An attempt to characterize explicitly the polynomial cointegration properties of an I(d) process can be found in la Cour (1998). See Johansen (2005a) for an exhaustive survey of the mathematical results concerning the representation theory and Johansen (2005b) for an application of similar ideas to fractional integration and cofractionality.
In this paper we show that the order of integration of a vector autoregressive process can be determined by counting the number of unit roots as in the univariate case; the reason is that reduced rank of the characteristic polynomial at z = 1 implies that the factor z − 1 is both at the numerator and the denominator of the inverse and thus cancels. More specifically, the order of integration d is equal to the difference between the multiplicity of the unit root in the characteristic equation m and the multiplicity of the unit root in the adjoint matrix polynomial a, that is, d = m − a. In Section 3 we prove the equivalence of m − a = 1 and m − a = 2 with the standard I(1) and I(2) conditions (Johansen, 1996) and in this way provide an alternative derivation of the Granger representation theorem in these well-known cases.
2. MAIN RESULT
The definition of order of integration of a p-dimensional stochastic process is as follows.
DEFINITION 2.1. The linear process Xt = C(L)εt, εt ∼ i.i.d. is called I(0) if

converges for |z| < 1 + δ for some δ > 0 and C(1) ≠ 0p; if ΔdXt is I(0) then Xt is I(d).
Given the autoregressive equation

where εt is an independent and identically distributed (i.i.d.) sequence we want to understand when it defines an I(d) process. It is well known that the solution of (2.1) is an integrated process when the roots of the characteristic equation are either one or lie outside the unit circle. So we assume that

where

is the characteristic polynomial of (2.1), |Π(z)| = det(Π(z)), and the roots of g(z) are outside the unit circle. Note that g(1) ≠ 0 implies that m > 0 is the multiplicity of the unit root in the characteristic equation. From |Π(1)| = 0 we have that rank(Π(1)) = r < p and thus that Π(1) can be written as the product of two p × r matrices α and β of full rank r; that is, −αβ′ = Π(1). Moreover, we have the following result.
PROPOSITION 2.2. Let Πa(z) be the adjoint of Π(z); then

with H(1) ≠ 0p and a ≥ 0 is the multiplicity of the unit root in the adjoint matrix polynomial.
Proof. The entry j,i of the adjoint is the signed determinant of the p − 1 × p − 1 matrix derived by eliminating row i and column j from Π(z). If rank(Π(1)) = r < p − 1, any p − 1 × p − 1 submatrix of Π(1) is singular and Πa(1) = 0p; if instead r = p − 1, there is at least one p − 1 × p − 1 nonsingular submatrix of Π(1) and Πa(1) ≠ 0p. Then Πa(z) = (z − 1)aH(z) where H(1) ≠ 0p, and we call a ≥ 0 the multiplicity of the unit root in the adjoint matrix polynomial. █
As a consequence of the reduced rank of Π(1) the factor z − 1 appears both in |Π(z)| and in Πa(z); this means that Π(z)−1 = Πa(z)/|Π(z)| is then equal to

with H(1) ≠ 0p, g(1) ≠ 0 and the pole at the unit root has order m − a > 0.
It is interesting to see that the number of unit roots in the characteristic equation does not determine the order of integration simply because the factor z − 1 appears both at the numerator and at the denominator of Π(z)−1 and cancels. Exactly as it is in the univariate case the order of integration is equal to the order of the pole of the inverse at the unit root. Then, as the next theorem states, what is relevant is the difference between the two multiplicities and not the number of unit roots in the characteristic equation alone.
THEOREM 2.2. The process Xt in (2.1) is integrated of order

with m being the multiplicity of the unit root in |Π(z)| and a the multiplicity of the unit root in Πa(z).
Proof. The roots of g(z) being outside the unit circle imply that the function C(z) = H(z)/g(z) is well defined for |z| < 1 + δ for some δ > 0. Thus

converges on the same disc, and it is such that C(1) = H(1)/g(1) ≠ 0p; this means that Δm−aXt is I(0) and thus that Xt is integrated of order d = m − a. █
We know how to calculate the roots of a polynomial; then it is clear that we can find m in |Π(z)| and the number of roots aij in each entry of Πa(z). Then a = minij aij, and the process is integrated of order d = m − a.
Example 1 (Johansen, 1992)
The characteristic polynomial

has adjoint

and determinant

The basic assumption about the roots is satisfied if δ = 0 or δ ≥ 3. When δ ≥ 3, g(1) = δ and m = 1. Because Πa(1) ≠ 0p we have that a = 0 and d = m = 1. When δ = 0,

and m = 2; then Πa(1) ≠ 0p implies d = 2.
Example 2 (Modification of Paruolo, 1996)
The characteristic polynomial

has adjoint

and determinant

The basic assumption about the roots is satisfied, and m = 4. Because a = minij aij = 1, Πa(z) = (1 − z)H(z), and the process is integrated of order d = m − a = 3.
3. EQUIVALENCE WITH THE I(1) AND I(2) CONDITIONS
Next we want to show the equivalence of m − a = 1 and m − a = 2 with the standard rank conditions in Johansen (1996). They are stated as follows:
1For notational convenience we write Π, H, and g instead of Π(1), H(1), and g(1); similarly we drop the reference to one in the derivatives.

, and it is I(2) if and only if

where ξ,η are p − r × s matrices of full rank s < p − r and |ξ⊥′α⊥′θβ⊥η⊥| ≠ 0 where

.
The identity Π(z)Πa(z) = Πa(z)Π(z) = |Π(z)|Ip is written as

evaluated at z = 1 this gives αβ′H = Hαβ′ = 0p, and because H ≠ 0p it implies

for some matrix φd ≠ 0p−r.
PROPOSITION 3.1 (I(1) condition). Let m and a be the multiplicities of the unit root in |Π(z)| and in Πa(z); then

with −αβ′ = Π.
Proof. Differentiate (3.1) at z = 1 and substitute H = β⊥φdα⊥′ and Π = −αβ′ to have

pre- and postmultiply it by α⊥′ and α⊥ to have that

Assume that

; then φd ≠ 0p−r only if m − a = 1 and necessity is proved. Assume now m − a = 1; then

and g ≠ 0 implies |φ1| ≠ 0 and

and the proof is complete. █
In the next proposition we consider the I(2) case.
PROPOSITION 3.2 (I(2) condition). Let m and a be the multiplicities of the unit root in |Π(z)| and in Πa(z); then

with −αβ′ = Π,

, and

.
Proof. Let m − a > 1; then

must be reduced rank, and we write

for two p − r × s matrices ξ and η of full rank s < p − r. The first derivative of (3.1) at z = 1 is

and

.
Pre- and postmultiplying (3.3) by α⊥′ and α⊥ we have that

and similarly from the other version of the identity that

. Then from ξη′φd = φdξη′ = 0p−r and φd ≠ 0p−r it follows that φd = η⊥ψξ⊥′ for some matrix ψ ≠ 0p−r−s and thus that H = β⊥η⊥ψξ⊥′α⊥′.
Note that by premultiplying (3.3) by α′ we have that

The second derivative of (3.1) at z = 1 is

where c = (m − a)(m − a − 1), and premultiplying it by α⊥′ we have

Using Ip = β⊥ β⊥′ + ββ′, (3.2), and (3.4) we see that

and thus that (3.5) becomes

Premultiply by ξ⊥′, substitute H = β⊥η⊥ψξ⊥′α⊥′, postmultiply by α⊥ξ⊥, and let

to see that

Assume that |ξ⊥′α⊥′θβ⊥η⊥| ≠ 0; then ψ ≠ 0p−r−s only if m − a = 2 and necessity is proved. Assume now m − a = 2; then

and g ≠ 0 implies |ψ| ≠ 0 and |ξ⊥′α⊥′θβ⊥η⊥| ≠ 0 and the proof is complete. █
More complicated rank conditions arise for m − a > 2.
4. CONCLUSION
This paper has shown that the order of integration of a vector autoregressive process can be determined by counting the number of unit roots as in the univariate case. The correct way of doing so consists of considering both the multiplicity of the unit root in the characteristic equation and the multiplicity of the unit root in the adjoint matrix polynomial, so that the order of the pole of the inverse becomes explicit.