MONETARY POLICY AND AGRICULTURAL LENDING BY
PRIVATE SECTOR FINANCIAL INSTITUTIONS
R.L. St Hill
Views expressed in Agricultural Economics Research Unit
Discussion papers are those of the author(s) and do not
necessarily reflect the views of the Director, other members of
the Staff, or members of the Policy or Advisory Committees.
DISCUSSION PAPER NO.
77
November 1983
AGRICULTURAL ECONOMICS RESEARCH UNIT
LINCOLN COLLEGE
CANTERBURY
NEW ZEALAND
I55N 0110-7720
IT-IE AG,RJCULTURiIL ,ECONOMiCS RESEARCH UNIT
The /ig;~iCtl1lLlml Econorn.ics Rese~l.i:ch Unit (iI.ERU) was established in 1962 at LL11COln
CQIlegc\ [Jw7ersity ofCaEterbury. The a.irn.s of the Unit are to assist by \vay of econon-uc
i'eseaIch th:ose groups in.volved in the f"Da.:ny aspects ofl'-J e-V-l Z,ealand prilnary production
ailcl pi-GQUet processlng s distributioD and IT!2.:rketLng.
Major sou.rceS of funding ha<le been ;:u1.nuaI grants horn the Department of Scientific
<Gci Industrial Research and the College. However, a substantial proportion of the
Urdt's budget is derived from specific project research under contract to government
departments, producer boards, b.rmer o;:g=isations and to corrEnerciaJ and industrial
grolIps.
The U:Git is involvecT in a wide spectrum of agricultural economics and management
resea;:ch, with some concentration on production economics, natural resource
ecoTl'Omics, marketiug, processbg ~md trauspoftation. The results of research projects
are published as Research Reports or DisCllssion Papers. (For furtheti..'1formation
regarding the Unit's publications see the L'1side back cover). The Unit also sponsors
periodic corderences and SemL'1arS on topics of regional and national interest" often in
con:1unction with other organisations.
.
The Uuit is guided b policy forma'don by an Advisory Committee flist established in
.
1982~
The AERU, the Department of Agric1lltural Econoffiics and Marketing, and the
Dep2ytment of Farm Ma.:oagement and Rural Valuation maintain a dose working
relationship on research and a5,sociated matters. The heads of these ttllD Departments
are n;p:resented on the Adviscry' Com.n,jti:ee; and togetherwith the Dhector, constitute
&..r."'1. .l~.ERp Policy Committee.
tJ1\i1T ADVISORY COMMI1"TEE
G.W. Butler, M.Sc., FrLdr., F.RS.N.Z.
(AssistaD,t Director-General, Department 'of Scientific & Industrial Research)
KD. Chamberlin
(JuDicr Vice-President, FEderated Farmers of N'ew Zealand Inc.)
P.D. Chudleigh, B.Sc. (Hom), Ph~D.
(Director,(~gricultuial Economics Rese;;,rch Unit, Lincoln College) (ex officio)
J. Clarke;C.M.G.
(Member, J\fevJ Zealand PlannLtlg.Council)
JB. Dent, B.Sc., M.Agr.Sc.,Ph.D.
(profes.~'"T'J-r t:;~ I-iec.d ofDepartrnerrt ofFat:m 1t'f3nag~ment &. RLU:al \Talu.ation, LincoL~ College)
E.J. I\Jeilson~ B ..F.!..,,?B.Com.~ F~C.~~;r :F.C~I.·S.
{I_.iflcoln Coll~ge Co.unci!)
B . } .. Ross; .M.i.~gr_Sc~,
(professor & Head or Departmmtof Agric:citurat Econoroics&jl..iarketing, Lincoln College)
P. Shirtdiffe, RCom.,ACA
(Nomti-ree of Advisory COmmittee)
PmfeSS2-f SirjaxnesStews.rt, M.A., Ph.D., Dip. V.P.M., FNZIAS, FNZSFM
{Principal of Lincoln College)
E.J. Stonyet; B.A"gr. Sc.
(Director, Economics Division, IVEnistiyofAgriculture 9,nd Fisheries)
Ul>JTT llESEiiRCH STliPF: 1983
Director
P.D. Chudleigh, B.Sc.(H6ns),PhJ,).
ReSetTle/J Fellow iii Agricultural Policy
J.G Pryde, O.B.E.,M;l",.., F.N.Z.I.M.
Senior Research
.
. ".. . . Economists
.
AC. Beck. B.Sc.Agr~; M.Ec.
"'.
RIJ.
Lough;~.Agr;Sc.
Sheppard, B.Agr.Sc.(Hoiis), B.B.S.
Research Economist
KG. Moffitt, B.Hoit.Sc., N;D.H.
.lissirtant Resef:1ic~ ECOflO,1!Z[Stj
LB. B<iin, Be Agr., LL.B.
D.E.Foi'.rler, B.BS,Dip. Ag. Econ.
G. Greet, B.Agr.Sc.(H(::ms){D.S.I.R SeconclInent)
S;A. Hughes, B.Sc.(Hons), D.B.A.
G,N. Kefr, B.A.; M,L (Hons)
M.T. Laing, B.Corri.{Agr), IvLCom.(Agr) (Hons)
P.]. IvIcCartin, B. l\.gr.~om.
P.R. McCrea, R.Com. (Agr)
B.SC~1
J.P. Rathbun,
M. Com.(Hons)
Post Graditatf: Fellows
C.K.G, Darkey, B.Sc., M.Sc
Secretary
r
'T'
T..J;l1
CONTENTS
Page
LIST OF TABLES
(v)
LIST OF FIGURES
(v)
PREFACE
(vii)
ACKNOWLEDGEMENTS
1•
3.
4.
5.
(ix)
INTRODUCTION
1.1
Objectives of the Study
1.2
Background
1.3
Outline of the Paper
2
DATA ON LENDING TO THE AGRICULTURAL SECTOR
3
2.1
Definitions
3
2.2
The Share of Agriculture in Loans outstanding
4
AN INDICATOR OF THE STANCE OF MONETARY POLICY
7
3.1
Definition of GAP
7
3.2
The Velocity of Circulation
7
A SINGLE EQUATION REGRESSION MODEL
1)
4.1
Variables Included in the Equation
) )
4.2
Results of the Regression
12
4.3
Interpretation of the Results
)3
SECTORAL ANALYSIS
17
5.1
The Share of Agriculture in Total Loans
Outstanding
17
5.2
The Shares of the Household and Other Sectors
in Total Loans Outstanding
)7
(0
Page
6.
SUMMARY AND CONCLUSION
2I
REFERENCES
23
APPENDICES
Appendix 1:
Appendix 2:
Loans to the Agricultural Sector and Total
Loans outstanding of Selected Private
Sector Institutions
Descriptive Statistics:
Circulation
(i i 1)
25
Velocity of
27
LIST OF TABLES
Page
4
1•
Institutions Included in the Study
2.
Regression Results
J3
3•
Shares of Five Categories of Loans Outstanding in
Tight and Not-Tight Quarters
J8
LIST OF FIGURES
Page
The Share of Agriculture in Loans outstanding of
Selected private Sector Financial Institutions
5
2.
An Indicator of the Stance of Monetary policy
8
3.
Income Velocity of Circulation
1•
(v)
J0
PREFACE
The AERU recognises the importance of finance to the New
Zealand
agricultural sector.
Hence,
the unit has
been
increasing steadily its
efforts
in studying the finance
resource and its interaction with the agricultural sector.
In the past few years two reports
specifically on the
subject of farm finance have been published by the AERU.
The
first was Research Report No.
114 by J.G.
pryde and S.K.
Martin;
this
report
reviewed the New Zealand rural credit
system.
The second was Discussion paper No.
69
written by
Glen Greer; this paper reviewed finance data availability and
data
requirements
of
institutions
associated
with
farm
finance.
The present paper written by Mr R.L. St Hill, lecturer in
the Department of Agricultural Economics and Marketing at the
College, reports the results of analyses of the relationships
between monetary policy and lending to the agricultural sector
by private sector financial institutions.
It is
interesting
to note that the analysis has been somewhat constrained by a
lack of data on the flow of loans, that is,
an inability
to
identify net new lending each quarter as well as the pattern
of repayments.
Nevertheless,
the paper makes
a
valuable
contribution to our understanding of the financial sector.
The paper constitutes a revised and expanded version of a
paper presented by Mr st Hill
at the New Zealand Branch
Conference of the Australian Agricultural Economics society
held at Wellington in August 1983.
P.D. Chudleigh
Director
(vii)
ACKNOWLEDGEMENTS
The author would like to acknowledge financial assistance
from the Lincoln College Research Fund and to thank those who
have provided suggestions and criticisms.
In particular,
Mr
John Pryde and Mr Bert Ward provided helpful comments.
The author would also like to acknowledge assistance from
the Reserve Bank of New Zealand in compilation of data.
(ix)
1•
INTRODUCTION
1.1
Objectives of the study
Over a decade ago the Committee of Inquiry
into Lending
to Farmers (1972:19) reported that "the evidence submitted to
us indicated that there has been reasonable availability of
loan
finance
for
creditworthy borrowers."
In the mid-1970s
Bayliss and Bayley (1975:6) concluded that "farmers' borrowing
requirements
have
been
well
catered for by financial
institutions."
More recently;
respondents
to a
survey of
farmer
opinion
(pryde and McCartin,
1983)
did not regard
availability of finance
as
an
important factor
limiting
expansion of
farm output.
Although the cost of finance was
regarded as the chief limiting factor
its availability was
ranked ninth out of twenty possible limiting factors.
It is the purpose of this Discussion Paper to report
results
of
a
preliminary investigation into relationships
between monetary policy and lending to the agricultural sector
by private sector financial
institutions in New Zealand.
Specifically, the objective of
the study was
to test the
hypothesis
that private sector financial institutions do not
alter their portfolio compositions
at the margin when the
monetary policy stance becomes more restrictive.
If
the
empirical results suggest that the hypothesis is true it could
be tentatively concluded that changes to a more restrictive
monetary policy stance are not biased in favour
of,
or
against,
agriculture in the sense that this sector bears a
lesser or greater than proportional burden of
any change in
total loans outstanding.
1.2
Background
The agricultural sector in New Zealand has
always
received
close
attention
in
economic management.
Such
attention has usually been fairly obvious
in fiscal policy
implementation as
in the case of the Supplementary Minimum
prices
Scheme.
However,
agriculture has
also
received
consideration
in
monetary
policy
implementation.
In
particular,
lending directives have consistently favoured
lending to the agricultural sector because of its overwhelming
importance as
an
earner of
foreign
exchange.
Directives
should,
in
theory,
allow the authorities
to
insulate
agriculture
against
adverse
fluctuations
in
finance
availability when the monetary stance is restrictive but their
efficacy is hard to determine (Deane; Nicholl and smith, 1983:
I.
2.
263).
pryde and Martin (1980: 53-54) suggested that direction
to lenders and the use of public sector ratios led to a
small
increase in funds available to the agricultural sector towards
the end of the 1970s. I
Clearly, the whole question
of
relationships
between
monetary policy and agricultural
lending
is complex.
As
little is known about such relationships research
is
needed,
especially
if
the government intends to pursue a more active
approach to monetary policy in the future than has
been
the
case in the past (Budget, 1983: 10).
t.3
outline of the Paper
In section 2 data on lending to the agricultural sector
by private sector financial
institutions are presented and
discussed.
In Section 3 a suggested indicator of
the stance
of monetary policy is defined.
The indicator is used as an
explanatory variable in a simple
regression model which
is
outlined in Section 4.
Some sectoral analysis is reported in
Section 5 and tentative conclusions are drawn in Section 6.
I
However, they regarded reduced lending risks associated
with guarantee schemes like SMPs as a more important
po 1 icy fa c tor.
2.
DATA ON LENDING TO THE AGRICULTURAL SECTOR
2.1
Definitions
~he Reserve Bank made available data on loans outstanding
by
the major private sector institutions listed in Table 1.
Institutions included in this
study were the so-called M3
institutions plus life insurance companies.
Loans outstanding
were classified by term, consistent with the classification
adopted
in
the report of
the Agricultural Development
Conference 1963-64
(1966).
short-term loans
(STL)
were
defined as
the sum of stock and station agents' advances to
farmers and sundry debtors plus trading banks' overdrafts
for
farming.
Medium-term loans
(MTL)
were defined as trading
banks' term loans for farming.
All other loans were defined
to be long-term (LTL) and included trustee and private savings
banks' loans, finance companies'
loans
and life insurance
companies'
loans
for
farming.
The sum of all these loans
(PAG) was used in the regression model in Section 4 and the
components
(STL, MTL, LTL) were used in the sectoral analysis
in Section s.
Data were collated as at the last reporting date in
each
quarter for each institution from March 1970 to June 1982.
In
earlier years some components of LTL were
estimated.
These
components were trustee and private savings
banks' loans
(March 1970 to June 1978) and finance companies' loans
(March
1970
to March 1977).
Simple semi-log linear regressions with
other components of LTL as regressors were used as a basis for
extrapolation in these cases.
Total loans outstanding to
the private sector
of
the
institutions
included in Table 1 (PC1) was defined as the sum
of
loans
outstanding to the private sector of the
M3
institutions
(this is the Reserve Bank definition of Private
sector Credit)
plus
loans
and major
investments
of
life
insurance companies excluding government securities and cash.
All the data referred to above are tabulated in Appendix
1.
It is
important to note that data represent stocks of
loans to the agricultural sector outstanding at the
end of
each quarter rather than flows of loans during each quarter.
Data on flows of new loans and debt repayments are unavailable
for most of the institutions covered by this study.
Therefore
the analysis concentrates on the share of agriculture in total
loans
outstanding of the institutions covered rather than the
share of new loans which would be a more appropriate measure
of portfolio adjustment.
3.
TABLE 1
Institutions Included in the Study
-~---------------------------------------------------- -------
Term of
Loan
Type of
Loan
Institution
Short
Advances and
sundry debtors
Overdrafts
Stock and
station agents
Trading banks
Medium
Term loans
Trading banks
Long
All loans
Trustee and
private savings
banks
Finance companies
Life insurance
companies
---~--------------------------------~-------------------------
2~2
The Share of Agriculture in Loans Outstanding.
The share of agriculture in total
loans outstanding of
the institutions
in Table 1 (PAG/PC1) is shown in Figure 1.
During the period of study the maximum share was 22.3 per cent
(in the December quarter 1970) and the minimum share was 11.1
per cent ( i n the September quarter
1978).
There was
a
downward trend in the share until mid-1979 but after that time
the share increased slightly. Visual inspection of Figure 1
suggests that there is not much volatility in the share in the
shol:'t term and implies that changes
in the proportion of
agricultural
loans
in the portfolios of private sector
~inancial institutions are usually made by marginal increments
o.r cecrements. 2
2
Deseasonalising the share makes very little difference
since the seasonal indices computed by the moving average
method are all very close to 1.0.
5.
FIGURE
The Share of Agriculture in Loans Outstanding of
Selected Private Sector Financial Institutions
u
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3.
AN INDICATOR OF THE STANCE OF MONETARY POLICY
3.1
Definition of GAP.
An indicator of the stance of monetary policy should
reflect not the intended policy but actual monetary conditions
( Davis and Lewis, 1978 : 20-22).
For
example,
consider a
situation in which the monetary authorities raise the Reserve
Assets and Government security Investment Ratios as part of a
tight monetary policy package.
Ostensibly the monetary policy
stance is
restrictive but,
if
a
sudden surge in
export
receipts
occurred and was not sterilised, actual monetary
conditions and hence actual monetary policy stance could be
permissive.
Recognition
of
this
distinction
leads to the
suggestion that an indicator of relative rates
of
growth in
money
supply and nominal transactions might
be a useful
indicator of the monetary policy stance.
In practise the
value of nominal transactions
is virtually impossible to
calculate.
Gross Domestic product (GOP) must
be substituted
although
it should be recognised that GOP measures only
transactions involving newly produced goods and services.
The approach taken here was to define a variable, GAP, as
the difference between the percentage rates
of growth in
broadly defined money supply (M3) and nominal GOP.
When GAP
is
zero the stance of monetary policy could be said to be
neutral in the sense that
it is
neither restrictive nor
permissive because money supply is growing just fast enough to
allow expenditures on GOP to be financed without a
change in
income velocity of
circulation.
When GAP is positive the
monetary policy stance could be said to be permissive since
money
supply is
growing more rapidly than GOP.
conversely,
when GAP is negative the monetary policy stance could be said
to be restrictive since money supply is not growing rapidly
enough to finance expenditures on GOP without a change in
the
income velocity of circulation.
GAP
is shown
in
Figure
2.
According
to
the
interpretation
above
New Zealand experienced "runs" of
permissive monetary policy punctuated by shorter
"runs" of
restrictive monetary policy between 1970 and 1982. Typically
the restrictive "runs" were of two or three quarters duration.
3.2
The velocity of Circulation.
The usefulness of GAP as an
indicator of the monetary
policy
stance depends
on the validity
of
the implicit
assumption that the velocity of circulation is
constant,
at
least
in the short term.
Two approaches were used to examine
the validity of this assumption.
7.
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9.
First, an
indicator of
velocity was
defined as
the
annualised ratio of GOP to average M3 in each quarter, average
M3 in turn being defined as the mean of M3
at the beginning
and end of each quarter.
Velocity defined in this way is the
income velocity.
In Figure 3 velocity is shown for
the time
period of
the study.
It is
clear
from the Figure that
velocity has been remarkably stable.
The mean of the series
is 2.0
and the coefficient of variation is only 4 per cent.
The secular trend est~mated by regressing velocity against
time was
not significantly different from zero (see Appendix
2).
On this
basis GAP would appear
to be a
reasonable
indicator of the stance of monetary policy.
Second, the correlation coefficient between growth
rates
of nominal M3
and nominal GOP was computed.
If velocity of
circulation was constant one would expect this coefficient to
have had a value close to unity. This follows from the simple
"quantity equation":
MV
=
PY
M
V
P
=
=
=
Y
PY
=
=
nominal money supply (M3)
velocity of circ~lation (income velocity)
index of the general price level (GOP implicit
price deflator)
real income (real GOP)
nominal income
where
When V is constant we expect that:
OM
ot
o(PY)
=
------
ot
Therefore,
if V is
constant the correlation coefficient
between
the rates
of growth in nominal M3 and GOP should be
close to unity.
In this case the computed coefficient was
0.69.
Because this result is not unambiguously high one must
question the validity of the assumption of constant velocity.
Final
judgement
is subjective and the author's judgement was
to accept the assumption on the basis of the overall evidence.
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19751
19752
19753
19754
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4.
A SINGLE EQUATION REGRESSION MODEL
4.1
Variables Included in the Equation.
To estimate the relationship between the monetary policy
stance and the share of agriculture in total loans outstanding
of the private sector financial institutions listed in Table 1
a
simple single equation regression model was employed.
The
model is not an "explanatory" model
in
the sense that the
objective was
to test a number of hypotheses about economic
behaviour.
Rather the objective was restricted to
examining
the statistical
relationship between the monetary policy
stance and the share of
agriculture
in
total
loans
outstanding.
This
led to the inclusion of some variables as
regressors, such as a proxy for time,
which
did not really
"explain"
anything
but
which
improved the statistical
properties of the equation.
The dependent
variable was PAG/PC1,3 the
share
of
agriculture in
total loans outstanding.
Regressors included
PAG/ PC1 lagged by one-quarter, the indicator of the monetary
policy stance
(GAP),
a proxy for time, the weighted average
interest rate on trading banks' term loans and three seasonal
dummy variables.
Lagged PAG/PC1 was included as a regressor in recognition
of
the fact that PAG/PC1 does not appear to be volatile over
short periods of time (see Figure 1).
This variable could be
taken as
a
proxy
for
inertia in portfolio adjustment.
It
should be emphasised that because PAG/PC1 is a stock variable
its
short term stability could mask quite volatile changes in
short term gross flows of new lending.
Because no
flow data
are available, at best, gross new lending could be proxied by
changes in PAG/PC1 but this is still only a measure of net new
lending and provides
no information on repayment patterns
(Greer, 1983).
GAP was included to enable estimation of the
relationship of interest in this paper.
statistical
Time (T) was represented by a proxy variable whose value
was set at unity for the March quarter 1970 and incremented by
one for each quarter thereafter.
This variable was
included
as
a
means
of
accounting for
a general downward trend in
PAG/PC1 between the March quarter 1970 and the June quarter
1979.
As mentioned above it is recognised that time does not
have any potential as an explanatory variable in the economic
sense.
Inclusion of
the weighted average interest rate on
trading banks' term loans outstanding (I) was dictated mainly
by data availability.
Ideally, the rate on agricultural loans
relative to other loans should be used but interest rate data
on agricultural loans are unavailable. One would
expect that
the lower the relative interest rate on agricultural loans the
lower would be PAG/PC1.
If the assumption that
changes
in
3
Expressed as a proportion rather than as a percentage share.
11.
12.
interest
rates on loans to the agricultural sector lag behind
changes in other rates can be accepted, then an increase in I
would be associated with a fall in PAG/PC1 other things being
equal. 4
The three seasonal
dummy variables were included to
account
explicitly for
seasonality in the raw data. (01 = 1
for March quarter, 0 for all other quarters; 02 = 1 for June
quarter,
0
for
all other quarters;
03 = 1 for september
quarter, 0 for all other quarters).
4.2
Results of the Regression.
Because the dependent
variable was
expressed as
a
proportion, predicted values were restricted to values between
zero and unity by estimating a
logit
equation where the
dependent variable was In
{(PAG/PCI)
}.
)-(PAG/PCl)
Coefficients were estimated by ordinary least squares and are
reported in Table 2.
At the 95 per cent confidence level all
coefficients
except that on 03 are significantly different from zero.
An
F-test on the three seasonal dummy variables jointly indicates
that their inclusion in the equation improves its fit.
The Durbin-Watson statistic quoted in Table 2 was
not used
to test for the presence of first order serial correlation in
the error terms. Where a lagged dependent variable is used as
a.
regressor the Durbin-Watson statistic is biased towards 2.
Durbin's suggested test based on regressing residuals on
lagged residuals and all regressors indicated that first-order
serial correlation was not present in the error terms of the
estimated equation (Durbin, 1970).
The Wallis d4 statistic was used to test for fourth-order
serial correlation in the
error term which is always a
possibility with quarterly data
(Wallis,
1972).
This
test
indicated that the problem was not present.
In St Hill (1983) the weighted average interest rate
on trading banks' overdrafts was used.
In this paper
the weighted average term loan rate is used because it
seems to be a more representative rate.
13.
TABLE 2
Regression Results
Variable
Coefficient
Constant
t
-0.334
2.6
P- I
0.840
12.5
GAP
-0.004
2.0
T
-0.006
2.3
I
0.022
2.6
D1
0.081
4.8
D2
0.060
3.4
D3
0.005
0.4
where:
=
P
ln
(PAG/PC1)
{-----------}
1-(PAG/PC1)
coefficient of determination adjusted for
degrees of freedom = 0.98
F statistic = 336.4
Durbin-Watson statistic = 2.0
Wallis d4 statistic = 1.8
Number of observations = 49
4.3
Interpretation of the Results
The regressor of interest is GAP.
Its
coefficient is
negative implying that
as GAP falls (as the monetary policy
stance becomes more restrictive) the share of
loans
to the
agricultural
sector
rises.
This
follows
from
the
interpretation below:
fj,
In
(PAG/PCI)}
{----)
{
(PAG/PCI)
=
-----------}
I -
II (PAG/PCI)
(PAG/PCI)
=
+
(PAG/PC] )
{I -
-0.004 llGAP
(PAG/PC])}
(PAG/PCI)
fj,
(PAG/PC)
14.
Therefore:
~(PAG/PCI)
~ -0.004 ~ GAP [PAG/PCI
{I -
(PAG/PCI)}]
Thus if PAG/PC1 is 0.15 (mean of PAG/PC1
in the period of
study)
and
GAP is -3 percentage points (standard deviation
of GAP in the period of
study)
then
(PAG/PC1)
is
approximately 0.002 or 0.2 percentage points.
This result is
interesting as it indicates that the agricultural sector
does
not have to do quite as much
"belt-tightening" as other
sectors in quarters when the monetary policy stance becomes
more restrictive.
An important implication is that financial
institutions as a group restructure their portfolios at the
margin in favour of agricultural loans under these conditions.
Such portfolio restructuring may be a
voluntary,
profitmaximising
response by financial
institutions.
If,
for
example, default risks perceived by financial institutions
on
some other types of loans increase in periods of restrictive
monetary policy then expanding the share of agricultural loans
is
a
rational profit-maximising response to tight monetary
policy. It might still be rational to expand the share of
agricultural
loans
even
if there is no change in perceived
default risks on other types of
loans.
For
example,
if
interest rates· are not market determined and are below
appropriate market rates, then rationing of loanable funds
on
the basis of risk is rational behaviour.
Thus if agricultural
loans are perceived to be less risky than other types of loans
their share in total loans outstanding could be expected to
rise when monetary conditions are restrictive.
Although there is no evidence to substantiate directly
the hypothesis that institutions do alter their perceptions of
risk, agricultural loans are perceived generally by financial
institutions to be safer than many other types of loans, but
this may be because guarantees
such as
the Supplementary
Minimum Prices Scheme mitigate risk (pryde and Martin, 1980).
Restructuring of portfolios may not be voluntary.
It may
be an involuntary response as a result of lending directives
or moral suasionS by the monetary authorities or as a
result
of a
slow-down in the rate of loan repayments by farmers.
Because available data are mostly on a loans outstanding basis
(stock)
it
is
difficult
to
know
whether portfolio
restructuring is voluntary or involuntary.
If
it
were
possible to compile data on new lending and loan repayments
(flows) an attempt to assess the nature of restructuring could
be made, e.g. a reduction in loan repayments would support the
involuntary restructuring argument.
Hill
5
Some comment on the sign of I needs to be made.
As in St
(1983),
where the weighted average interest rate on
Moral suasion is defined in Deane, Nicholl and Smith (1983
256) as tla process of consultation and request" between the
Reserve Bank and financial institutions.
J5 •
trading bank overdrafts was used,
the coefficient
on
I
is
small but significantly different from zero and has a positive
sign.
Although a positive sign was not expected a
priori
it
is possible that
the hypothesis regarding relative interest
rates did not hold in the sample period as
a
result
of
the
combined
effects
of
interest
rate regulations and lending
directives which operated during parts of the
sample period.
Also, using I as an indicator of relative interest rates masks
differences
among institutions.
For
example,
lending to
agriculture by trustee savings
banks
and
life insurance
companies attracts higher
interest
rates
than
lending for
housing while,
in
the
case of
trading banks, lending to
agriculture attracts lower interest rates than other types
of
lending.
Nevertheless,
inclusion
of
I
in
the
equation
overcomes the problem of first-order serial correlation in the
error terms and I was retained for that reason.
5.
SECTORAL ANALYSIS
5.1
The Share of Agriculture in Total Loans Outstanding.
In this section the focus is on the behaviour of
shares
of
components
of PAG in PC1 in tight and not-tight quarters.
For this purpose each quarter
in the period of
study was
classified as tight or not-tight on the basis of GAP.
If GAP
was negative then the quarter was classified as
"tight"
(25
quarters
fell into this subset); if GAP was positive then the
quarter was classified as "not-tight" (24 quarters
fell
into
this subset).
For each subset of quarters the geometric means
of component percentage shares were calculated and t-tests
applied
to
establish
the
statistical significance of
differences between them. 6 Results are displayed in Table 3.
Results obtained in the regression
exercise are
given
some further credibility.7
The percentage share of PAG in PC1
does appear to have been higher in tight quarters
on
average
than
in
not-tight
quarters.
However
when
PAG was
disaggregated into its components it was clear that short-term
loans
(STL)
accounted largely for the result.
The data were
disaggregated even further and it appeared that about
threequarters
of the increase in STL was explained by higher loans
outstanding on the part of stock and station agents;
these
loans were,
in turn,
financed by the agents borrowing from
trading banks.
Unfortunately, this
evidence does
not
shed
much
light
on
the issue of
voluntary versus involuntary
portfolio restructuring.
At best it
is
very weak
evidence
that
restructuring is involuntary and arises because the flow
of loan repayments is
reduced in tight quarters.
without
information on flows of repayments and new loans the issue is
virtually impossible to resolve.
5.2
The Shares of the Household and Other Sectors in
Total Loans outstanding.
For purposes of
comparison two further
categories of
loans were defined.
Data for the household sector (HOUS) were
compiled.
Included in this
sector were trading
banks'
overdrafts
and term loans
for
housing and other personal
purposes, trustee savings banks' loans for housing and flats
6
7
Variances were also calculated and F-tests applied to establish
the statistical significance of differences between pairs.
None
of the differences were statistically significant at the 95 per
cent level.
This result was expected given that differences
in means were small and/or not statistically significant.
Since tight quarters were spread reasonably evenly throughout
the entire period of study the possibility of spurious results
arising due to trends in shares of agricultural loans outstanding was minimised.
17.
18.
TABLE 3
Shares of Five Categories of Loans Outstanding
in Tight and Not-Tight Quarters
Geometric Mean of Shares
Category
Tight
Quarters
Not-Tight
Quarters
Difference
Short-term loans
to agriculture
(STL)
7.78
7.10
.0.68*
Medium-term loans
to agriculture
(MIL)
0.88
0.85
0.03
Long-term loans
to agriculture
(LTL)
6.12
5.90
0.22
Total loans to
agriculture (PAG)
14.78
13.85
0.93*
Loans to households
(HOUS)
29.08
28.13
0.95*
Other loans (OTH)
56.14
58.02
-1.88*
Total loans (PC 1)
100.0
100.0
Indicates that differences are significant at the 95% confidence
level.
19.
and other personal purposes, private savings banks' loans for
houses and flats, Post Office Savings Bank's personal
loans,
finance
companies'
loans
for
houses
and flats
and other
personal purposes
and
life insurance
companies'
loans
on
policies.
Data
for
a
residual
"other"
sector (OTH) were
calculated as the difference between PC1 and the sum of
loans
outstanding to
other sectors.
OTH comprised mainly business
loans and local authority securities.
Geometric means for shares of HOUS and OTH were computed.
The mean
share of HOUS increased in the tight quarter subset
by a little more than did PAG.
By contrast, the share of OTH
fell.
Because HOUS and OTH are highly aggregated only brief
comment can be made.
It seems that in tight quarters business
lending
(the bulk of OTH) shoulders a disproportionate share
of
the burden
of
restrictive monetary policy while the
agricultural
and household sectors do not have to do as much
"belt tightening".
6.
SUMMARY AND CONCLUSION
The preliminary research results outlined in
this paper
indicate that the share of loans to the agricultural sector
outstanding by private sector financial
institutions has
increased at the margin in quarters when the monetary policy
stance has become more restrictive.
The analysis raises
some issues which have not been
resolved.
In particular,
the issue of whether
or not
portfolio restructuring is a voluntary or involuntary response
to changes
in the stance of monetary policy has not been
resolved.
Nevertheless, the results
suggest
that when the
monetary
policy
stance
becomes
more
restrictive the
agricultural sector bears
a
less
than proportional burden
because its
share in total loans outstanding rises slightly.
Therefore it can be tentatively concluded that
changes to
a
more restrictive monetary policy stance are biased slightly in
favour of the agricultural sector.
21.
REFERENCES
Agricultural Development Conference 1963-64 (1966),
Reports
and Recommendations.
Government printer, wellington.
Bayliss, L.C. and Bayley, J.G. (1975),
The Future Structure
of Agricultural Finance in New Zealand.
Discussion
Paper NO.6, Department of Economics, Victoria University
of Wellington.
Budget (1983),
Financial Statement.
House of Representatives
28 July, Government Printer, Wellington.
Davis, K. and Lewis, M. (1978),
Monetary Policy, in Gruen,
F.H. (ed),
Surveys of Australian Economics Vol 1, George
Allen and Unwin, sydney, pp. 10-89.
Deane, R.S., Nicholl, P.W.E., and Smith, R.G. (eds) (1983),
Monetary policy and the New Zealand Financial System.
2nd Edition, Reserve Bank of New zealand, wellington.
Durbin, J. (1970),
Testing for Serial Correlation in LeastSquares Regression When Some of the Regressors are Lagged
Dependent Variables, Econometrica, Vol 38, pp. 410-421.
Greer, Glen (1983),
Farm Finance Data:
Availability and
Requirements.
Discussion paper No. 69, Agricultural
Economics Research Unit, Lincoln College.
Lending to Farmers (1972),
Report of the Committee of
Inquiry. Government Printer, Wellington.
pryde, J.G. and Martin, S.K. (1980),
A Review of the Rural
Credit System in New Zealand, 1964 to 1979.
Research
Report No. 114, Agricultural Economics Research Unit,
Lincoln College.
pryde, J.G. and McCartin, P.J. (1983),
Survey of New Zealand
Farmer Intentions and Opinions, October-December 1982.
Research Report No. 136, Agricultural Economics Research
Unit, Lincoln College.
St Hill, R.L. (1983),
Tight Monetary policy and the Share of
Agriculture in Private sector Lending in New Zealand.
Paper presented to the Australian Agricultural Economics
Society (N.Z. Branch) Conference, Agpol convention,
Wellington.
spencer, G.H. (1980),
Monetary Targets: A Comparison of Some
Alternative Aggregates.
Research Paper NO. 30, Reserve
Bank of New Zealand, wellington.
Wallis, Kenneth, F. (1972),
Testing for Fourth-order
Autocorrelation in Quarterly Regression Equations.
Econometrica, Vol. 40, pp. 617-636.
23.
25.
APPENDIX 1
LOANS TO THE AGRICULTURAL SECTOR AND TOTAL LOANS
OUTSTANDING OF SELECTED PRIVATE SECTOR INSTITUTIONS
1970
1970
1970
1970
1971
1971
1971
1971
1972
1972
1972
1972
1973
1973
1973
1973
1974
1974
1974
1974
1975
1975
1975
1975
1976
1976
1976
1976
1977
1977
1977
1977
1978
1978
1978
1978
1979
1979
1979
1979
1980
1980
1980
1980
1981
1981
1981
198!
1982
1982
KEY
I
2
3
4
I
2
3
4
1
2
3
4
I
2
3
4
I
2
3
4
I
2
3
4
I
2
3
4
I
2
3
4
I
2
3
4
I
2
3
4
I
2
3
4
I
2
3
4
I
2
STL
MTL
LTL
223. I
206.2
230.9
245. I
241.6
222.4
243.5
257.6
233.6
215.6
225.7
225.5
223. I
217.0
252.9
272.9
299.6
289.8
299.0
305. I
308.9
274.8
304.7
32 1.9
309.3
263.5
29 1.8
340.8
360.9
335.0
380.3
412.7
397. I
384.0
399.2
419.7
446.7
437.0
478.2
529.8
564.4
527.3
585.4
654. I
707.4
670.7
734.2
840.6
820.8
720.2
3.9
4.1
4.5
4.7
4.6
4.6
4.5
4.4
4.4
5.4
6.3
7.8
1I.3
19.2
28.8
34.0
34.8
37.6
39.0
38.5
37.3
38.4
42.4
48.7
51.6
53.6
57.6
64.6
67.0
72.8
74.3
73. I
70.8
75.3
92.6
107. I
114.9
132.6
140.8
141.5
137.3
143.9
15], 7
165.4
162.3
186.9
223. I
257.9
267.3
284.4
205. I
208.0
209. I
208.9
209.2
210.7
210.6
21 !. 9
21 !. 1
214.2
216.3
217.3
219.6
224.4
23 1.0
234.5
237.4
24 1.6
243.2
243.7
242.8
244.2
245.0
248.9
249.9
252.9
254.9
26 1.3
262.4
26 1.8
272.6
278.4
280.9
288.6
290.0
307.5
309.7
332.9
354.7
364.2
375. I
401.3
428.7
456.6
472.6
521.5
556. I
599.7
610.0
629.8
PAG
432.1
418.3
444.5
458.7
455.4
437.7
458.6
473.9
449. I
435.2
448.3
450.6
454.0
460.6
512.7
541.4
571.8
569.0
58 1.2
587.3
589.9
557.4
592. I
619.5
610.8
570.0
604.3
666.7
690.3
669.6
727.2
764.2
748.8
747.9
781.8
834.3
87 I. 3
902.5
973.7
1035.5
1076.8
1072.5
1165.8
1276. I
1342.3
1379. I
1513.4
1698.2
1698.1
1634.4
PCI
1982.3
1979.2
2035.0
2060.5
2228.0
2208.9
2226.3
2234.3
2392.3
2390.0
2439.2
2505.6
2746.9
2846.0
3021.2
3148.2
3524.3
3637.9
3777 . 2
3739.7
3912.7
3896.6
4007.4
4111. 7
4336.6
4390.6
4650.8
4873.8
5318.6
5865.7
6095. I
6173.5
6518.8
6632.7
7022.2
7355.0
7792.4
8104.8
7827.7
8135.8
8558.2
8643. 1
9073.0
9499.3
10139.5
10528.9
11654.7
11796.6
12787.8
12850.4
I ... March quarter 2 = June quarter 3 = September quarter 4 = December quarter
STL = Short-term loans to the agricultural sector outstanding
MTL = Medium-term loans to the agricultural sector outstanding
LTL = Long-term loans to the agricultural sector outstanding
PAG = Private sector loans to the agricultural sector outstanding
PCI = Total loans to the private sector by selected institutions outstanding
(see Table I for a list of institutions)
27.
APPENDIX 2
DESCRIPTIVE STATISTICS
Mean of series
2.0
standard deviation
VELOCITY OF CIRCULATION
(annualised quarterly data)
0.08
coefficient of variation
4%
Trend estimated by :
Vel
where
=
1.985
+
(t=80.0)
0.001T
(t=0.8)
= o .01
Vel
=
annualised quarterly income velocity of
circulation
T
=
time (2,
3, 4,
•••
50)
P-ECENT PUl3LICA TIONS
~ESEARCH
REPORTS
Potatoes: A Consumer Suroey of Cbristchurch and Auckland Ilo[.!sec
bolds, r,,1.r.t Rich,M}. Mel.tbn. 1980.
106, SlJTvey of New Zealand FaTT4e~ Intentions aitd OpilZionJ. j~fy~
September, 1979,j.G. Pryde, 1980.
107. A Survey'of nILt and Pest/cide Use in Canterbury and SOljthlan4,
J.D. Mumford, 1980.
'
108. An LC,cimomic Survey of NeW Zealand Town A1i!k Producers, j 9787<), RG. lvfoffitt, 1920.
Ch!2liges in Untied KI?igdom Meat Demand RL. Sheppard.
105.
1980.
110:
',',
"
1980.
'
Fish.~ A ConiumerSuweyofChristchiu'ch HOJisehoids, KJ Brodie,
198.0.
_
-.
:".".
,
/wATla!ysis oj Altirn.<>.tive Wheat Pricing Scheme~. M.t;!. Rich,
L.J. Foulds, 1980.
"
113. An EcollomicSurvq a/New Zealalld W'hetItgrowers; Efztdpris!'
Allcdysis, SiyveiNo. 4197,)c80. JtD.Lough, RM.MacLean,
Pj. McCartin, l;iLM.IUch, 1980,
'
A Rcuiew 0/ tbeR"ra((yedit System in New Zealand, 1964 fa
1979, ].G. Pryae,S.K, .Martin; 1980.
115., ,1'l Socio-EconomicSti:(Jy-ofFann Workers and Farm Managers.
G. T - H~rr~s:t' ·~'989 ~.'
117
136.
St:rvey of New Zealc:illd Fqnnci.'" Tr;f.:'n!iof1J
140.
1i 9
49.
50
Market EVd{qtdiiJJ.'(JSystflTitit.ic Approod . FrozeIJ Green
Sprriu!iTigBrtJi"{:nli;-f!,.)'.,Sheppard. 1980.
51
The E E C~~h~epin~'ai Re.t;i'llI:: Arral!geme?1ts and Implications,
N. B!ytk19S0; ,
PrpceeI1.1)1$S, if.q::S¢~/r/ar ·O.Y} Pub:'? 'D/rect!~f!s ,(or New 'Zealatul
LdmbNfaykei{ni,edited byRL. ~heppilrd, R.J. Brodie, 1980.
52
53
56.
57.
jCij?liiieJe' Agricl4tiiTa/ Pq!i£)'. Dfi;E'/~tw1t:m': im/Jiict2tio1lJ jo;· !'-feu'
60.
61.
An
59 .
An E~onomic Stl:.~t!eY·-O/·~Vew ?ef/ond
,
62.
'.
of
Farm
OW?;;;."'1'Si~ip
Savings
Acc!Jtmts,_
'-'.;'
Tbe l\ft!tij.Ze/llti~il·lV!~qt Trade:"71 t/;e·_r980~s...ajJroj;osq! for chllllge~
E.J. R<?ss?~.:R. :r;. -Sheppar~ -.A.C. Z'wart, 1982.
Supple~~!/ory ..-lv!i·1iliJ.u~ Prices: iZ Rroduciiop. inCetiti'l!e? RL .
Sheppard;] JVLBiggs; 1982.'
Pro~eed~·~g[.qJ.:·a.:$~m.~·~~r.~rz R·oC!d:Tr~·llJ,.tJort in: RtJTa:i Areasr edited
by P.D:Chudleigb.;A.J Nicholson, 1982:
65.
Quaiityfn the. f..Jew Zerz/aild Wheat aud FioliT lHarkels, M.IvL
Rich, ,1982:
''
.
66.
Oesi~ll:' '.~ q~~j/r!'/iqi/onj /£0.'. Compr!ter Based· lYlar.,keti;lg ai?d
I nJor-;noj(01?. Sj~-rt~!ns" P .1. N u thallI 1982:
"'R.eag(Jj;o~it;·'d:71itbeNeUi Zealand AgriwitllTai Sector, R. W.
BohaH{l9~Y ,
'
67.
68
Energy[;s~inN.ew Zeafo;d Agriat!:Nm! Product/olio P.D.
C·p.uql~;(g~, ·gl~1j- Gr.e~r: 1983.
FOT?1IFilltllZCe'D;ta.'Aw!i!ability alit! Reqliirt'ments, Glen Greer,
1983
.'"
70.
Tbe Pa}t;;dii~:~'estdd SectoT: and tbe S;;j'J,o!ementary Mirlimum
PriceI?o!iry,M'J!. Laing, A,C. Zwart, 1983.
.
,
£1n Ecoilomic: SilTvey oj··.lveZl! Zealand f;,7/:: eafgi"OWers: . Financial
/!.naiysis, J980-8/, RD. Lough; P.}. IvicCartin,1982.
J.'Viano$e.meni Strote.gi~s.' tina DrtlJ~ii!lK P~!ifi{~s for
Im;gatet! Cal?terbu,:v Sheep Farms. N.:VL Shadbolt. 1982.
134.' Ecollomics of tie Sheep Breeding Operations of the Departme~t of
Lands and Survey, A.T.G. ~rcArrhur, 1983.
E1Jtftuoi~o1!
K.B. Woodf<ird,1981.
1982.
Wheatgrowen: fl.!1terp~ise
. Analy~is~ Survey i\1.0. '6" 1.981-82; F... D. Lough, .P.]. McCartin)
M.lvL Rich, 1982.
~iL}:~11~r;lf.' ~~,2jE:~a~f~i¥E~~;fi;~ff;;~~:l~f:
N. Blyth, 1981:
64.
131,
et:on!)tTlelri~·-.m()~fe( :.r./I. T. Lair..g. A. C Zwart.,
Zealt!1id. ·A'~ s;:~ . .Zv..·art~ 198!..
l!!ten'st Rir/t.;s: itu.ctf tll1d Fq!!cu:ies. K.B. Yj/oodford. 19·9: .
T.he·EE¢.S.~~qpn?ea~ RE.g.1;~~e: One }t'.'lT O.f1~ N. 31yth. 1981A Re!I~e--~·oj,the. Wqr!d Sb~c-pmeal AJ.a;·.fet: Vo!. 1 - Ovefi.;r·Ew cJt"
'ji),
63.
TiN New Zeat,:miPoi;to Medetirig System, R,I... 'Sheppard,
The
1981.,
The. EcomoinicJ_' 4; Soil' (:o1lset-:uatiofJ. and Water iYIanogemertt
Policies in the OtagoHighColJlltry, G.T. H<,!rris, 1982.
130
.'
N . .M.Shadbolt,{9E i.
Tbe F/I?~tI)~~·Pf(JClis:r/i'l..v. f:/ A"1c:ul. l::.i\'L Silcoc~:, R.L. Sheppard.
TZ1e·!'·Je:t1.l Zealand ~1/:Jeti~-~rj4FburJ;>Jt/!'lStry: ivla,}zet Sfr!Jctur.e I2n4
. Policy .rrl1plica..t~i?,~j~. B.W. B~?rr~n, A... C. Zwart, 1982.
Sun;e;v of I,Jew ?ealo1id.F~rt!ler ltit~~~ti{)ns ana_ OPt~~i~t!s,. Septe1T!.bet.r;fov£~ilJb~G l-9$i~. J~ 0 -:. :p:&g~~ .i9-g2~
127. The Nt ',?etilaFld,Pasto,at LivestockSeClor: A.'1 Eco;iometrii Model
(Ver.rsO/; ~~'·'w{))~ J\.f:t. '-.L~.ng, "1982.
.
128. A ·.Farm-iffVel.lv.~o?ello:Eva!uate -t/~e ]rllpC!ct~. c/' C~r.r?nt~ EnerKy
Policy Options, !l.M.l'vf: ThoIDpSyn, 19.82.
'129. An Economic Sl!luryoj Ne7QZealand lOWll Milk Pl'oducers ]980,
81, KG. Moffitt, 19i1i "
'
'..
NeUi,;Ze~!dlldPtlstora!
55.
~;;~t";~;~~;;/;;:i.Klr~~t~t/{ ~~c;;}:;~:.e~}t:.n~~h:
AlteT17dfitJ{!
TheEva!lJa'tio~:oijob ,Creation Programmes with FarticJJ/ar
Refi're1!/-'e.:· rlj':~~b~_.',Ftfr~ '.Emp!o_yment Pre~'Tqmj~f~ G.~. Harris,
Li1f{:Slock Sector: a pre!imii1Ciry
1. 981.
T/;e 5cht.~j;;j;··Pric~~SJ!jlem and the l-lew Zealand_Lamb P"odlxe~,
54.
.126.
133.
He Cost -(/IOf!e;sea~Shippiilg: 7X'bo Pays/ P.D. Chudleigh,
1981.
Seasonality ~.~'1. tiJ~ J.lb..u. ·Zealand J.:feqt PrOCeJJi7;'g .I::>JauJtry~ R.I:-.
Sheppard, ?9Bi.
'124.
Ecol1omicRelationshipswitbi71 the Japanese Feed and Livestock
Sector, 1,;1. Kagal:$llfi';e;AC. Zwart, 1983.
1980.
.
A.n EcqJ'l{J11li~"S~fyei a/.J-Jew 'Zea0end V{~~/'!t!tgiOJiJers:. Fin4~ciq!
Ailt!!ysis, J978-79.RH Lough, Rlvi MacLea[!, P.J. McCartin,
J·tl. PA. Ric 1-4 "19.80 .
!.vi.<:!ltiplicrs Jfrom R.egioft~! ,'·..loll-.Sf.iroey blptrt-Or.:!,put"Thbles /0'1".
)Vew.Ze.l'.!lclJ.i L.]. Hub1;)as-d ·W.A.. N. BrOWr1., 1981,Survey OjCthe I-J.ei!!th.of·.Ne:w·-Zeala;7d Fa77(lefS: October-r,lovemb.er
J930. }.G.Pryde, 1981.
Iiort:'cJltll're i;.z .A.korGa. ·.Cal.:r:ty~
Ill:,_ Shepp~rd;.19g1 ..
.AR EcoHomic S!.Irv,!"y qf lYe:..!} Zefi//.l7Zd To~.~!,? lUilk Prod!(CeYJ, 1979SO, RG. MofEtt,. 1981.
121. .;1;-? Eco:,!omic Si:roey o),clvi!-r; Zet2ZaF1d Wbe(Jl.'E;jOr;;erJ.~ Efl!e:pf'"ise
Afttzi)rsisr Surv~ blo. 5 J980-81; R. !J~ 1.o;..1gh: P.J.I~cCartill,
AtI.lv1. Rich} 1981 ..
122.
OI)J~<J!ons. OcfoUn--
mSCUSS!ON PAPERS
J
1Ig
O!Jd
Dnwlber, J982,].G. Pryde. P.]. NicCartin, 1983.
137. JiFocsfment aNd'SllpP!i Response /~7 tlJl- ATc';L' Zet!/alld Paslora/
Sector.' An. E.C:O!J(}J;u1Eir lHotiel. NLT. L;1!ng, A.C. ~:W?1rt. 1983
138. The W~~!tl'$j,eej,;j;je~t lrItlrlcft-· tili ec()nometric JtlOj(!i~ N. BLyth,
1983.
139. An .ct::vnom.ic.Stif-r!ey 0/ }J~tV Zealand.Towfll¥lilk :IJrodItcers, 198182, KG, MO:ffitt,1983.
..'
112.
;06.
t~/ate;" and C.~/;oice iTt Cafu:e-rbtlry, E~.L. Lc·athers, B,.i\'LH. Sharp,
'vl.A.N. Brown; 1983
limed/osis Eradication: a deseriptioTl oj tJ ploruwlg model, A. C.
B~ck.
111.
'
1,5.
,
lv1arket;;"g [fistitlltions for Ncu/ Zeafa~7d Sbeipmea£:r, A. C Z'I'l2.rt,
1983.
72.
73.
' .',",
,
SZfpportiFlg1be, AJ51'icu!turai Sector: Ratio1!aie and Po/ky, P.D.
Chudleigh" Glen ,Greer, R.L. Sheppard. 1983.
IsmfRe!qti;ig to tbe Funding of Primary PrOcesSillg Researrh
TbTOIigh RejearcbAs.ff)ciatjol1S, N. Blyth,A.C. Beck, 1983.
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