6.5  A simplified Almon estimation

In this section we present results based on an updated version of the model estimated in Scobie and Eveleens (1987). This model is a simplified version of our Almon models presented above, in that the Almon distributed lag variable is a combination of human capital, extension and domestic R&D, and hence these variables are not entered into the regression equation separately. Foreign R&D is also not included in the model. The variable “Deviations from trend net farm income” is included as an explanatory variable, the argument being that in years of high income, farmers may be expected to increase their purchases of inputs.[34] We have not included this variable in our main specification due to concerns about endogeneity. The model is set out in equation 19 below:

(19)     

where REH is the variable combining research and extension defined as log[R_t+(E_t*HK_t)], and transformed by a second degree Almon polynomial lag structure with constrained endpoints, with a total lag length of 22 years, and yd is deviations of net farm income from a fitted trend line. The equation was estimated using the Cochrane-Orcutt correction for autocorrelation, and the results are presented in Table 11 below.

Using an internal rate of return calculation such as that used in Scobie and Eveleens (1987), the fitted second order polynomial implies a rate of return to domestic R&D of 70%.[35] The weather variable is again not significant, while the deviations from trend net farm income appear to have a negative effect on productivity, although the effect is very small. That is, in years of high income, productivity is depressed due to increases in farm spending on inputs.

Note: The coefficient for REH is computed as the sum of the coefficients on the individual lags.

6.6  Testing the absorptive capacity hypothesis

We tested the absorptive capacity argument by interacting the foreign patents variable with both domestic R&D and human capital. A significantly positive coefficient on either of these interactions would indicate that, for a given amount of foreign R&D, increasing the amount of domestic R&D or human capital enables more effective absorption of this foreign research. Thus domestic R&D or human capital respectively would have both a direct and an indirect effect on MFP. We found neither interaction to be significant in the Koyck models and both interactions to be significantly negative in the Phillips-Loretan models. We do not believe that this constitutes definitive evidence that absorptive capacity is not important. One only has to ask how much foreign knowledge a country could absorb were it to have no domestic scientific capacity, to underscore that absorptive capacity is critical in a small open economy such as New Zealand. Rather it reflects the difficulty of defining suitable proxies and then isolating the effects econometrically from aggregate time series data.

The second interaction that we tested was between human capital and domestic R&D, the argument being that research will be more easily adopted and utilised if the sector has a larger stock of human capital, and thus research will have a larger impact on productivity. This interaction was not significant in the Koyck models and was negative and significant in the Phillips-Loretan models. We also tested the interaction between extension and domestic R&D, as more extension workers arguably allow more effective and quicker dissemination of research to those who will use it; this interaction was found to be significant in the Koyck model when the dummy variable was included in the regression equation, but insignificant when it was not included. In the Phillips-Loretan model this interaction was never significant. These results may be an indication that extension staff facilitate the faster absorption of R&D and thus indirectly have a positive effect on MFP, whereas human capital does not appear to have a role in this absorption process.

We also tested whether the elasticity of domestic R&D has changed over time by including an interaction between the dummy variable and domestic R&D. We found this interaction to be insignificant in both the Koyck and PIM models, perhaps indicating that the effect of domestic R&D on agricultural productivity has not changed over time.