Table 10 presents within regressions for the specifications in Tables 3 and 5
respectively. Comparing the within-country regression in the second column in Table 10
to that of the within-country-time regression in Table 3, we see the impact of the betweentime
regression. In a way of generalization, the between-time sum of squares of output
and input is of the order of magnitude of twice as much as that of the within-time-country.
The coefficient of capital increases from 0.37 to 0.53, and many of the coefficients of the
within-country regression are insignificantly different from zero reflecting the influence of
the between-time coefficients. This comparison provides a framework for interpreting
empirical results obtained under different specifications of effects.
With this interpretation we can now compare our results to those presented in
Table 1. In this we ignore the first study by Bhattacharjee because it has no measure of
capital nor of state variables; thus it is not very comparable to the other studies. Most of
the studies are strictly cross-country and as such are comparable to the between-country
results. The similarity is in the low land elasticity, and also the sum of the elasticities of
machines and livestock is close in most cases to the value of 0.4 we obtained for the sum
of structures and equipment and livestock and orchards in the between-country regression.
This similarity is consistent with our interpretation that these studies describe only the
between-country changes; hence they provide a limited and incomplete picture of the
production process. In any case, they do not provide coefficients of a stable production
function and as such, do not provide the appropriate weights for growth accounting, as
they were intended to do.
It is always useful to check the results against all available information. The
Global Trade Analysis Project (GTAP) reported factor shares of land and labor in
agriculture for 1992 for 24 regions (Hertel, 1997). The data needed to compute factor
shares are not available for all countries. The more available data are on labor costs, and
these were used as a pivot to generate the other shares relying on “other sources” where
available (op. cit., p.113). Applying the appropriate regional data to the 37 countries in
our study, we summarize this information in Figure 1 in terms of the empirical
distributions. The median values are 0.24 for land, 0.39 for labor and 0.39 for capital.12
Another source of information is the OECD which reports “compensation of employees”
by sectors. Computing labor shares from these series for 19 countries for the period
1970-90 (for 7 countries the period is somewhat shorter) yields a median value of 0.19.
The labor share in these statistics is higher than the estimated elasticity from the within
regression, but nevertheless, these values are conveniently close to the within estimates
and are conspicuously far away from the between-country estimates. This seems to
provide independent support for our interpretation.