Explaining Growth in Dutch Agriculture: Prices, Public R&D, and Technological Change



Table 3 Price and factor elasticities short-run model (standard errors between brackets)
dependent                        quantities

explanatory

GPAR

MEATR

MILKR

LAB3

FERTR

FODR

GPAP

0.007

0.083

-0.044

-0.008

0.015

0.087

(0.953)

(0.082)

(0.350)

(0.849)

(0.849)

NA

MEATP

0.261

0.133

0.090

0.029

-0.117

0.376

(0.082)

(0.311)

(0.262)

(0.506)

(0.356)

NA

MILKP

-0.096

0.062

0.063

0.132

-0.108

0.103

(0.350)

(0.262)

(0.613)

(0.087)

(0.356)

NA

LAB3P

0.001

-0.026

-0.004

-0.007

0.009

-0.004

(0.849)

(0.624)

(0.087)

(0.670)

(0.473)

NA

FERTP

0.004

0.011

0.015

0.038

-0.047

0.028

(0.849)

(0.356)

(0.489)

(0.473)

(0.728)

NA

FODP

-0.211

-0.287

-0.114

-0.135

0.232

-0.602

NA

NA

NA

NA

NA

NA

FAMILYLAB

-0.451

0.226

-0.839

1.657

-1.070

-0.662

(0.724)

(0.813)

(0.155)

(0.000)

(0.215)

(0.243)

CAPR

0.792

1.970

0.007

0.134

0.670

1.113

(0.296)

(0.001)

(0.069)

(0.576)

(0.189)

(0.003)

ARABL

0.764

-0.022

-0.549

(0.382)

(0.937)

(0.350)

GRASS

-0.995

0.782

-0.189

(0.387)

(0.255)

(0.267)

CDRDEXP

-0.194

-0.247

0.499

0.070

0.749

0.439

(0.765)

(0.616)

(0.093)

(0.728)

(0.090)

(0.267)

QQUOTA

-0.007

(0.836)

Feed input has a relatively high own price demand elasticity (-0.602), although it is still inelastic.
The availability of relatively low priced compound feedstuffs in comparison with other EU countries
because of the nearly zero import tariffs on cereal substitutes and the good seaport access (the so-
called “gate of Rotterdam”) heavily contributed to the growth of the Dutch meat production sector.
The positive cross price elasticities between milk and meat output reflect the complementarity
between both outputs. This confirms the importance of the dairy cow stock in beef and veal
production, and the significant share of beef and veal in total Dutch meat output. Although the cross
price elasticities between milk and arable output are not significantly different from zero, their signs
suggest that they are competing sectors. Fertilizer prices appear to have no significant impact on any
of the outputs. The price range in which fertilizer prices are varying is not influencing its optimal
allocation. Fertilizer application is most likely to be determined by what is optimal from an agronomic
point of view (see literature about Von Liebig hypothesis, for example Paris, 1992).

Some interesting results are found with respect to expenditure on research and development
and the capital input in agriculture. Jointly they play an important role in explaining the evolution of
agricultural outputs and fertilizer input (cf. Ahearn, Yee and Huffman (2002: 17) for a similar finding
for the US). With respect to arable output capital plays a significant role, but research and
development expenditure is not significant. This suggests that technical progress in the arable sector
has mainly come from capital goods, and their improved quality over time. The impact of improved
crop varieties on increased yields (genetic progress), which was expected to show up in the coefficient
for the R&D variable could not be detected. However, this effect is indirectly captured by the positive
impact of R&D expenditure on fertilizer usage. The genetic progress favored higher yielding crops,
which for the realization of their genetic potential relied on increasing fertilizer input. A similar effect
of R&D expenditure was found with respect to feed usage. An increase in R&D expenditure increases
the use of feed. This again suggests that the progress generated by R&D expenditure has been mainly
affecting genetic progress in milk yields and meat growth efficiency (feed conversion rates). This lead
to an improved output price-feed cost ratio, which in turn improved the competitive position of Dutch
agriculture. It explains why an improved feed efficiency ultimately leads to an increased feed use

10



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