Handling the measurement error problem by means of panel data: Moment methods applied on firm data



where Xit = lnYt, ξit = lnXit, β = 1 , αi = -(1 )φi, Yt is either zero, -(1 )ψt
or ln hk(wt:), and c is a constant. The observed log-output and log-input are yit =
χ
it + uit and xit = ξit + vit , where uit and vit are measurement errors. This gives
an equation of the form (3). In the more general case where
Ft represents a non-
homothetic technology, separability of
Gt does not hold. Then the input elasticity
β will be different for different inputs and hence cannot be interpreted as an inverse
scale elasticity.

Neither of these model interpretations imposes a specific normalization on (11)
and (3), as observed input and output are both formally endogenous variables. In
the empirical application, two normalizations will be considered: (i)
yit and xit
are, respectively, the log of an observed factor input and the log of observed gross
production, both measured as values at constant prices and
β corresponds to 1 ,
and (ii)
yit and xit have the reverse interpretation and β corresponds to μ.

3 Estimators based on period means

In this section, we consider various estimators of β constructed from differenced
period means. From (3) we obtain

(12)          ∆sy.t = ∆sXtβ + ∆8l,t,      s = 1 ,...,T-1; t = s + 1 ,...,T,

(13)            ( yt - У) = (χ ∙t - χ)β + ( 4 - ё),          t =1 ,---,t,

where yt = Pi yit∕N, y = Pi Pt yit(NT), χt = Pi xit/N, χ = Pi Pt χit/(NT),
etc. and ∆
s denotes differencing over s periods.

The (weak) law of the large numbers, when (A) is satisfied, implies under weak
conditions [cf. McCabe and Tremayne (1993, section 3.5)],
4 that plim(e.t) = 0,
plim(
χ.t - ξ.t) = 0ιк, so that plim[χφet] = 0кι even if plim[(1 /N) Pn=i χl°teit] =
0K1. From (12) and (13) we therefore get

(14)                plim[^ sχ t ) ' (δ s yt )] = plim[^ sχ t ) ' sχ t )] β,

(15)                plim[(χ-t) '( yt У)] = plim[(χ-t- χ) '( χ-t- χ)]β-



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